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Administration Guide
Version 5.1 February 06, 2019

Copyright for ThoughtSpot publications. © 2019 ThoughtSpot, Inc. All rights
reserved.
ThoughtSpot, Inc. 1 Palo Alto Square
Building 1, Suite 200
Palo Alto, CA 94306
All rights reserved. This product is protected by U.S. and international copyright
and intellectual property laws. ThoughtSpot is a trademark of ThoughtSpot, Inc. in
the United States and/or other jurisdictions. All other marks and names mentioned
herein may be trademarks of their respective companies.

ThoughtSpot Administration Guide

February 06, 2019

Table of Contents
Introduction to administration .................................................................................................. 6
Login credentials for administration
administration.........................................................................................
......................................................................................... 7
Understand the architecture

Architectural components ..................................................................................................... 9
Data caching ....................................................................................................................... 10
Authentication frameworks ................................................................................................. 12
Data and object security ..................................................................................................... 13
Performance considerations ............................................................................................... 15
Installation and setup

About installation and upgrades ......................................................................................... 17
Set your locale
locale.....................................................................................................................
..................................................................................................................... 20
Test connectivity between nodes
nodes........................................................................................
........................................................................................ 22
Set the relay host for SMTP ................................................................................................ 23
Set up a fiscal calendar year ............................................................................................... 25
Configure SSL ..................................................................................................................... 26
Configure SAML .................................................................................................................. 28
Enable Active Directory based access
access................................................................................
................................................................................ 29
Integrate LDAP

About LDAP integration .................................................................................................. 31
Configure LDAP for Active Directory
Directory...............................................................................
............................................................................... 32
Add the SSL certificate for LDAP
LDAP....................................................................................
.................................................................................... 34
Test the LDAP configuration ........................................................................................... 35
Sync users and groups from LDAP
LDAP.................................................................................
................................................................................. 36
Configure NAS file system .................................................................................................. 39
Set up monitoring
monitoring................................................................................................................
................................................................................................................ 41
Configure support services ................................................................................................. 42
Network ports
ports......................................................................................................................
...................................................................................................................... 47
Configure load balancing and proxies ................................................................................ 53
Customize ThoughtSpot Help ............................................................................................. 55
Customize look and feel
feel......................................................................................................
...................................................................................................... 57
Enable SearchIQ
SearchIQ..................................................................................................................
.................................................................................................................. 60
Add the Slack integration .................................................................................................... 62
Load and manage data

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ThoughtSpot Administration Guide

February 06, 2019

Introduction to data management
management.......................................................................................
....................................................................................... 63
Configure casing ................................................................................................................. 65
Load CSV files with the UI
UI...................................................................................................
................................................................................................... 66
How to view a data schema ................................................................................................ 70
Plan the schema

About schema planning .................................................................................................. 74
Data types ....................................................................................................................... 77
Constraints
Constraints......................................................................................................................
...................................................................................................................... 79
Sharding
Sharding..........................................................................................................................
.......................................................................................................................... 82
Chasm traps
traps....................................................................................................................
.................................................................................................................... 87
Build the schema

Schema building overview .............................................................................................. 89
Connect with TQL and create a schema ........................................................................ 91
How to write a SQL script ............................................................................................... 93
Schema creation examples
examples.............................................................................................
............................................................................................. 95
Upload an SQL script
script....................................................................................................
.................................................................................................... 100
Change the schema

How to change a schema ............................................................................................. 102
Convert column data type
type.............................................................................................
............................................................................................. 106
Load bulk data

Import CSV files with tsload
tsload..........................................................................................
.......................................................................................... 110
Use a script to load data
data...............................................................................................
............................................................................................... 112
Delete a data source

Delete a data source (table) .......................................................................................... 117
Delete or change a table in TQL ................................................................................... 120
Improve search with modeling

About data modeling
modeling.........................................................................................................
......................................................................................................... 121
Change a table's data model ............................................................................................ 122
Edit the system-wide data model
model......................................................................................
...................................................................................... 124
Data model settings

Overview of the settings
settings................................................................................................
................................................................................................ 127
Set column name, description, and type ...................................................................... 129
Set additive and aggregate values
values................................................................................
................................................................................ 131
Hide a column or define a synonym ............................................................................. 134
Set columns to exclude from SpotIQ analyses
analyses.............................................................
............................................................. 136
Manage suggestion indexing ........................................................................................ 137
Add a geographical data setting ................................................................................... 142
Set number, date, currency formats ............................................................................. 145

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ThoughtSpot Administration Guide

February 06, 2019

Change the Attribution Dimension setting .................................................................... 150
Set entity categories for SearchIQ ................................................................................ 152
Link tables using relationships

Link tables using relationships
relationships......................................................................................
...................................................................................... 154
Delete a relationship
relationship......................................................................................................
...................................................................................................... 157
Use stickers
stickers.......................................................................................................................
....................................................................................................................... 159
Simplify search with worksheets

Create and use worksheets
worksheets...............................................................................................
............................................................................................... 162
Edit a worksheet
worksheet................................................................................................................
................................................................................................................ 167
Create a formula in a worksheet ....................................................................................... 169
Create worksheet filters .................................................................................................... 172
How the worksheet join rule works ................................................................................... 177
Change join rule or RLS for a worksheet .......................................................................... 179
Create a join relationship
relationship...................................................................................................
................................................................................................... 181
Modify joins between worksheet tables
tables............................................................................
............................................................................ 184
Delete a worksheet or table .............................................................................................. 186
Manage users and groups

Understand groups and privileges .................................................................................... 189
Create, edit, or delete a group .......................................................................................... 194
Add, edit, or delete a user ................................................................................................. 199
Manage jobs

Job management (scheduled pinboards)
pinboards)..........................................................................
.......................................................................... 203
Scheduled pinboards management .................................................................................. 205
Security

Overview of security features
features............................................................................................
............................................................................................ 207
System Security ................................................................................................................ 208
Data security

Data security ................................................................................................................. 210
Share tables and columns ............................................................................................ 215
Share worksheets ......................................................................................................... 217
Share a pinboard
pinboard...........................................................................................................
........................................................................................................... 219
Security for SpotIQ functions
functions........................................................................................
........................................................................................ 223
Revoke access (unshare) .............................................................................................. 224
Row level security (RLS)

About row level security (RLS) ...................................................................................... 227
How Rule-Based RLS works
works.........................................................................................
......................................................................................... 229
Set Rule-Based RLS ..................................................................................................... 233
ThoughtSpot Lifecycle ...................................................................................................... 236

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ThoughtSpot Administration Guide

February 06, 2019

System administration

Overview of System administration
administration...................................................................................
................................................................................... 240
Send logs when reporting problems ................................................................................. 241
Set up recording for Replay Search .................................................................................. 243
Monitoring

Introduction to monitoring
monitoring.................................................................................................
................................................................................................. 247
Overview board ................................................................................................................. 249
Data board
board.........................................................................................................................
......................................................................................................................... 259
Cluster Manager board ..................................................................................................... 261
Alerts and Events board .................................................................................................... 264
System worksheets ........................................................................................................... 266
System pinboards ............................................................................................................. 268
Backup and restore

Understand the backup strategies
strategies....................................................................................
.................................................................................... 270
Understand backup/snapshot schedules ......................................................................... 272
Work with snapshots
snapshots.........................................................................................................
......................................................................................................... 276
Work with backups

Understand backup modes .......................................................................................... 279
Create a manual backup ............................................................................................... 281
Configure periodic backups
backups..........................................................................................
.......................................................................................... 283
About restore operations .............................................................................................. 286
Troubleshooting

About troubleshooting
troubleshooting.......................................................................................................
....................................................................................................... 287
Get your configuration and logs
logs........................................................................................
........................................................................................ 288
Upload logs to ThoughtSpot Support ............................................................................... 291
Network connectivity issues
issues..............................................................................................
.............................................................................................. 292
Check the timezone .......................................................................................................... 293
Browser untrusted connection error ................................................................................. 294
Characters not displaying correctly .................................................................................. 295
Clear the browser cache ................................................................................................... 296
Cannot open a saved answer that contains a formula
formula......................................................
...................................................... 298
Data loading too slowly ..................................................................................................... 300
Search results contain too many blanks ........................................................................... 301
Keyword reference ............................................................................................................... 302
TQL reference
reference.......................................................................................................................
....................................................................................................................... 309
tsload flag reference
reference.............................................................................................................
............................................................................................................. 319

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ThoughtSpot Administration Guide

February 06, 2019

tscli command reference
reference......................................................................................................
...................................................................................................... 322
Date and time formats reference
reference..........................................................................................
.......................................................................................... 344
Row level security rules reference
reference........................................................................................
........................................................................................ 347
Formula function reference .................................................................................................. 359
Alert codes reference ........................................................................................................... 374
User action codes reference ................................................................................................ 381
Error codes reference
reference...........................................................................................................
........................................................................................................... 383
Frequently asked questions ................................................................................................. 409

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Introduction to administration

February 06, 2019

Introduction to administration
ThoughtSpot enables you to access and analyze your data through a search-based user interface. You
can create your searches on the fly by typing into a search bar, like you do when using an internet
search engine. ThoughtSpot makes it easy to see your data, get your questions answered, create
interactive graphs, and customize pinboards. You do not need to understand how the data is stored or
know SQL to do these things.
ThoughtSpot gives administrators the ability to modify data properties to meet business needs, for
example by providing search synonyms for common terms, boosting the importance of a column in
search results, or formatting how the data appears. Collaboration and security features make it easy for
you to protect sensitive data and for users to share information safely with others.
To perform the actions in this guide, you need administrative access.

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February 06, 2019

Login credentials for administration
Summary: You need administrative access to perform the actions
discussed in this guide.
You can access ThoughtSpot via SSH at the command prompt and from a Web browser.

Administrative access
Each ThoughtSpot appliance comes pre-built with three default users. You should talk with a
ThoughtSpot Customer Success Engineer or ThoughtSpot support, to get the password for each user.
The default users are:
Type

Username

Description

Shell user

admin

Used for work that requires sudo or root privileges. Does not exist
for application login. Logs for this user are found in /usr/local/
scaligent/logs logs

Shell user

thoughtspot

Used for command line work that does not require sudo or root
privileges. For example, these users can use tsload , tql , and
check the cluster status. This user cannot login to the application.
Logs for this user are found under /tmp .

Application
user

tsadmin

Access through a Web browser.

Both the admin and thoughtspot user can SSH into the appliance. Once on the appliance, either
user can do any of the following:
• tscli
• tsload
• tql
The thoughtspot user is restricted to tscli commands that do not require sudo or root privileges.

SSH to the appliance
To perform basic administration such as checking network connectivity, starting and stopping services,
and setting up email, log in remotely as the Linux administrator user “admin”. To log in with SSH from
any machine, you can use the command shell or a utility like Putty.
In the following procedure, replace with the hostname or IP address of a node in
ThoughtSpot. The default SSH port (22) will be used.
1. Log in to a client machine and open a command prompt.
2. Issue the SSH command, specifying the IP address or hostname of the ThoughtSpot
instance:

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ssh admin@

3. Enter the password for the admin user.

Log in to the ThoughtSpot application
To set up and explore your data, access the ThoughtSpot application from a standard Web browser
using a username and password.
Before accessing ThoughtSpot, you need:
•
•
•
•

The Web address (IP address or server name) for ThoughtSpot.
A network connection.
A Web browser.
A username and password for ThoughtSpot.
Supported Web browsers include:
Browser

Version

Operating System

Google Chrome

20 and above

Windows 7 or greater, Linux, MacOS

Mozilla Firefox

14 and above

Windows 7 or greater, Linux, MacOS

Internet Explorer

Windows 7 or greater

 Tip: While Internet Explorer is supported, using it is not recommended. Depending
on your environment, you can experience performance or UI issues when using IE.

To log in to ThoughtSpot from a browser:
1. Open the browser and type in the Web address for ThoughtSpot:
http://

2. Enter your username and password and click Enter Now
Now.

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Architecture components

February 06, 2019

Architecture components
Summary: To implement ThoughtSpot it is important to understand
where it sits within your overall analytics architecture and how it
provides data to end users.
ThoughtSpot consists of a cluster of one or more nodes, acting together to provide analytic answers to
business questions. As such, there are only a few integration points with ThoughtSpot on your network.
The major components in the a ThoughtSpot cluster are:

ThoughtSpot can handle a wide variety of different data sources. ThoughtSpot does all analysis against
data in memory to help achieve fast results across millions and billions of records of data. ThoughtSpot
caches the data in order to process it.
The ThoughtSpot appliance can be a physical appliance that ThoughtSpot ships, one or more AWS
instances that are clustered together, or one or more VMware instances that are clustered together.
From an external interface, regardless of the appliance type, the appliance appears to be a single
instance.
For authentication (logging in), some source of user information is required. These define the login
requirements and access control groups. Users will access the data from a supported browser to view
saved content or perform searched-based analytics. Finally, it is recommended that you have some sort
of networked attached storage for storing backups in case of hardware failure.

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Data Caching

February 06, 2019

Data Caching
Summary: ThoughtSpot does all analysis against data in memory to
help achieve fast results across millions and billions of records of
data.
ThoughtSpot caches data as relational tables in memory. The tables can be sourced from different data
sources and joined together. ThoughtSpot has four ways to get data into the cluster:

ThoughtSpot provides a JDBC and ODBC driver that can be used to write data to ThoughtSpot. This is
useful for customers who already have an existing ETL process or tool and want to extend it to populate
the ThoughtSpot cache.
Data Connect is a ThoughtSpot add-on that connects to a wide variety of data sources and pulls data
into ThoughtSpot.
You can use the tsload command line tool to bulk load delimited data with very high throughput.
Finally, individual users can upload smaller (< 50MB) spreadsheets or delimited files.
Which approach you use depends on your environment and data needs.
The following table shows the tradeoffs between different data caching options. Many implementations
use a variety of approaches. For example, a solution with a large amount of initial data and smaller daily
increments might use tsload to load the initial data and then use the JDBC driver with an ETL tool for
incremental loads.
JDBC/ODBC

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Data Connect

tsload

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Data Caching

February 06, 2019

• Have an ETL load,
for example, Informatica, SSIS, and
so forth.
• Have available resources to create
and manage ETL.
• Have smaller daily
loads.

ThoughtSpot Administration Guide

• Purchased as an add-on.
• Source data is well formed
for ThoughtSpot or it can be
modified prior to being
loaded.
• Have smaller daily loads.

• Initial data
load.
• When JDBC/
ODBC and
Data Connect
are not options.
• When there
are large recurring daily
loads.
• Higher
throughput but
can add I/O
costs.

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Authentication

February 06, 2019

Authentication
Summary: ThoughtSpot provides LDAP/AD, SAML, and ThoughtSpot
login to authenticate users.
ThoughtSpot provides three ways to authenticate users LDAP/AD, SAML, and ThoughtSpot login. In
general, ThoughtSpot recommends that you use LDAP/AD or SAML if possible since ThoughtSpot
provides only basic authentication with no restrictions on passwords, timeouts, failed logins, etc.
The table below shows each of the options and the items to consider for each.
SAML

LDAP/AD
• Use SAML for
single sign-on
authentication.
• Can redirect
from
ThoughtSpot
to SAML logins.
• Recommended
for portal integration.
• Option to sync
users and
groups if
stored in
LDAP/AD.

• Configuration.
• Users authenticate
against LDAP or AD.
• Option to sync users and
groups with ThoughtSpot
to manage group membership.

ThoughtSpot
• User created and
managed in
ThoughtSpot.
• No enterprise password control (expiration, password
strength, etc.).
• Only recommended
when SAML and
LDAP are not options.

All users and groups must be known to ThoughtSpot. If you are using LDAP/AD or SAML and don’t
create users in ThoughtSpot, a user is created when the user first logs in. However, this user is assigned
to the All group and will only see content available for all users.
Groups are the primary way that security is managed. Groups are not automatically created. You can
create groups and users manually or you need to automate the assignment from a source system.
ThoughtSpot has an assignment script that works with most LDAP / AD stores. It also has public APIs
that you can use to sync users and groups between source systems and your ThoughtSpot appliance.

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Data and object security

February 06, 2019

Data and object security
Summary: Understand how to secure your data and other key
information in ThoughtSpot.
ThoughtSpot provides these features for protecting data security:
•
•
•
•

Object security
Row level security
Column level security
System privileges

Object Security
Object security is the ability for users to see content within ThoughtSpot. Objects can be tables, columns
in tables, worksheets, pinboards, and saved answers.
Users gain access to objects when an object owner share-answers with them. Owners can share with
individual users or with entire groups, giving access to anyone within that group. Owners can share with
edit or view options.
Currently, you cannot restrict someone who has had content shared with them from sharing with others.
Also, a user who belongs in a group can automatically share with anyone else in the group. This has
implications on setting up privileges and applying row level security.

Row level security (RLS)
Row level security controls what data a user can see in each shared piece of content. Even if a user has
access to a worksheet, for example, they can only see rows from the tables they have been given
permission to see.
RLS is applied at the table level and automatically applied every time. Also, in queries where there are
tables with table filters, all joins are always enforced, to avoid accidentally allowing users access to data
they shouldn’t see. RLS requires three things:
• A table filter with a column (possibly in a joined table) that can be used to determine who can
see a row, for example, account id or tenant id.
• A group that can be associated with the row of data by name. For example, if the column is
account_id and has values of 1 , 2 , 3 , users can be assigned to groups group_1 ,
group_2 , group_3 and then only see their data.
• Users must be assigned to the given group. If they are not assigned to a group that has
access, they do not see any data.
Administrative users can always see all rows of data since RLS is not applied for these users.
RLS supports a hierarchy of groups allowing you to give access to some users across multiple groups.
Keep in mind that users within a group can share with one another group. This means that putting
everyone into a company group for RLS means they can share with anyone in the company.

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Data and object security

February 06, 2019

Column level security (CLS)
Column level security means only allowing users to see certain columns in a table. This can be
accomplished by only sharing certain columns with groups of users from a table.
However, most of the time users are given access to worksheets instead of columns. There is currently
no way to only share certain worksheet columns with certain groups. If you need this capability, you
must create different worksheets with the columns you want.
Also, note that because someone can share with anyone in a group they belong to, that means they
could potentially share restricted columns. For example, assume that HR has a column with salary
information in a worksheet that only HR has access to. An HR person could create an answer with the
salary information and share with someone outside of HR. That person would now have access to the
salary information.

System privileges
System privileges refer to what a user can do in ThoughtSpot. For example, can they upload or
download data or share with all users. These privileges are defined on a group level and inherit
downwards. So, if Group A had child groups Group B and Group C, then any privilege given to Group A
is also available to Group B and Group C. What this often means is that separate sets of groups are
required to manage privileges.

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Performance considerations

February 06, 2019

Performance considerations
Summary: Make sure you understand the performance considerations
in your installation.
ThoughtSpot is configured and licensed by memory availability. However, there are other considerations
that will impact the performance of your solution. It’s important to understand these considerations prior
to implementation, since some solutions will perform better than others.
Each node in a ThoughtSpot cluster has been found to perform ideally with less than 250GB of data and
fewer than 0.5 billion total rows of data. For schemas that are particularly complex, performance is
increased with even fewer rows of data per node. Ways to reduce the total amount of data and rows of
data include limiting the amount of data (number of years, etc.) or combining long, but narrow tables
together.
The performance information related on this page apply to a typical 1TB 4 node cluster.

Data Boundaries
Total rows in a result of a join can also have an impact. In general, it is recommended that you have
fewer than 10 billion rows in a many-to-many join. Keep in mind these other boundaries:
Description

Boundary

Max number of rows that can be downloaded

10M (default is 1M)

Size in CSV format

1 TB per appliance

Total number of rows across all tables

1B per appliance

Many-to-Many (Generic) join cardinality

10B per appliance

Load frequency

Once every hour

Worksheet Boundaries
Worksheets must have less than 1000 columns. For aggregated worksheets, you should keep in mind
the following:
• Number of columns should be less than 50
• Number of rows should be less than 10 millions
You can use an ETL process to circumvent these limitations. Speak with ThoughtSpot Customer
Support to learn more.

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Performance considerations

February 06, 2019

Aggregated worksheets and joins
To be able to join an aggregated worksheet with a base table, your installation must be configured to
allow the behavior. The aggregated worksheet cannot have more than 5 tables involved. Moreover, the
number of rows in the final aggregated worksheet cannot be greater than 1000.

Chasm Trap worksheets
For chasm trap scenarios (two or more fact tables joined via a shared dimension) the following
boundaries are recommended:
Description

Boundary

Max number of fact tables in a worksheet

Max number of shared dimensions

Max number of rows in non co-sharded shared dimension table of chasm trap

Max number of rows in co-sharded shared dimension table of chasm trap

Row level security Boundaries
Max number of unique RLS rules with search data suggestions should not exceed 15K.

Data Connect Boundaries
The maximum number of connections should be less than or equal to 25.

Scheduled pinboards
For scheduled pinboards, ideal performance is to have 50 or fewer scheduled pinboard jobs.

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About installation and upgrades

February 06, 2019

About installation and upgrades
Your ThoughtSpot application software is already installed for you in a ThoughtSpot appliance (this is
true for both physical and virtual appliances). The ThoughtSpot software is updated by ThoughtSpot
Support. ThoughtSpot Support will contact you to schedule an update when one becomes available.
As administrator, you are responsible for setting up and configuring ThoughtSpot. This guide explains
how. It will also assist you in troubleshooting some common problems, finding additional resources, and
contacting ThoughtSpot.

Display your current configuration
To perform the set up and configuration, you must first learn how to gain administrative access.
1. Log into the ThoughtSpot cluster as the admin user.
2. Use the tscli feature subcommand to display your current configuration.

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About installation and upgrades

February 06, 2019

Related information
The following tasks are available needed:
•
•
•
•
•
•
•
•
•
•
•
•
•

Set your locale
Test connectivity between nodes
Set the relay host for SMTP
Set up a fiscal calendar year
Configure SSL
Configure SAML
Integrate LDAP
Configure NAS file system
Set up monitoring
Configure support services
Network ports
Configure load balancing and proxies
Customize look and feel

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About installation and upgrades

February 06, 2019

• Add the Slack integration

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Set your ThoughtSpot locale

February 06, 2019

Set your ThoughtSpot locale
Summary: You can change the language displayed in the application.
The language the ThoughtSpot UX displays is based off of the locale in a user’s profile. The locale
preferences control the language and data formats (date and number formats) by geographic locations.
In addition to American English (en-US), ThoughtSpot supports:
Locale

Language

de-DE

German

en-CA

Canadian English

en-GB

United Kingdom English

en-US

English (United States)

es-US

Spanish (United States)

fr-CA

French (Canada)

fr-FR

French (France)

Japanese

pt-BR

Portuguese (Brazil)

zh-CN

Chinese (S)

Date and number formats change to reflect your locale. So, if you set Japanese as your default locale in
your profile settings, then the interface will update to reflect that after you refresh your page.
Keywords, operators, and error messages are included in the translated material. Formulas, however, are
not translated. Also, all metadata remains as user inputted.

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Set your ThoughtSpot locale

February 06, 2019

For example, if you are using ThoughtSpot in the US, the number formatting should look like this:
xxx,xxx.xx . And in Europe, it should look like this: xxx.xxx,xx .

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Test network connectivity between nodes

February 06, 2019

Test network connectivity between
nodes
Summary: Verify your network is properly configured for the
application.
This procedure tests the network connectivity between the ThoughtSpot nodes, and to the LAN. If you
can perform these steps successfully, the network settings on ThoughtSpot are correct.
1. Log in to the Linux shell using SSH.
2. Ping each of the other nodes in the cluster.
3. Ping another machine that exists outside of the cluster, for example, a machine that you will
use to stage data to be loaded.
If you cannot perform these tests successfully, there is a problem with the network setup. If the tests fail,
check Network connectivity issues.

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Set the relay host for SMTP (email)

February 06, 2019

Set the relay host for SMTP (email)
Summary: To enable alert emails, you'll need to set up a relay host for
SMTP traffic.
ThoughtSpot uses emails for sending critical notifications to ThoughtSpot Support. A relay host for
SMTP traffic routes the alert and notification emails coming from ThoughtSpot through an SMTP email
server.

Set up the relay Host
To set up a relay host:
1. Log in to the Linux shell using SSH.
2. Issue the setup command, providing the IP address of the relay host:

$ tscli smtp set-relayhost

3. Verify your settings:

$ tscli smtp show-relayhost

4. Verify that email is working.

Configure an email to receive alerts
ThoughtSpot sends alerts to the email address specified during installation. If no email address was
entered, no alerts are sent. You should add an email to receive alerts by issuing:

$ tscli monitoring set-config --email

To send to multiple emails, provide a comma-separated list with no spaces.

Verify the relay with an email
Check if the email settings are working properly by using this procedure.
1. Log in to the Linux shell using SSH.
2. Try sending an email to yourself by issuing:

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Set the relay host for SMTP (email)

February 06, 2019

$ echo | mail -s Hello

3. If you receive the email at the address(es) you supplied, email is working correctly.

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Set up a fiscal calendar year

February 06, 2019

Set up a fiscal calendar year
Summary: You can customize your fiscal calendar to start in month
other than January.
By default, the application’s fiscal calendar in January. If your company’s calendar year starts in another
month, setting a fiscal calendar quarter makes the ThoughtSpot date searches reflect your fiscal year.
Date formulas with the fiscal option specified will also reflect the fiscal year you set here.
When you set a custom fiscal year, you will designate the month on which your company’s fiscal year
begins. All the date language will then reflect your change, so if someone searches for this quarter or q3
q3,
the answer will conform to the fiscal quarter in use. When you make this change, existing pinboards also
change to reflect the custom fiscal calendar. Because of this, if you make this change after your users
have been using ThoughtSpot for any period of time, you should alert them of the change you will be
making and how it affects previous saved searches.
Contact ThoughtSpot Support, so they can help you set the custom fiscal year.

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Configure SSL

February 06, 2019

Configure SSL
Summary: SSL provides authentication and data security
You should use SSL (secure socket layers) for sending data to and from ThoughtSpot. SSL provides
authentication and data security. This section applies to both SSL to enable secure HTTP and secure
LDAP.

About SSL
Many IT departments require SSL for their applications that access data. To use SSL with ThoughtSpot,
you’ll need your company’s own SSL certificate. The certificate is issued per domain, so if you want to
use SSL for both HTTP and LDAP, you will need two separate certificates - one for the HTTP domain
and one for the LDAP domain.
If you do not have an SSL certificate:
• Check with your IT department to see if they already have an SSL certificate you can use.
• If not, you will need to obtain the certificate from an issuing authority.
• Alternatively, you may disable SSL if you don’t want the security it provides by using the
command tscli ssl off .
There are many SSL vendors to choose from. Check with your existing Web hosting provider first, to see
if they can provide the certificate for you.
When you apply for the SSL certificate, you may specify a SAN, wildcard, or single domain certificate.
Any of these can work with ThoughtSpot.

Configure SSL for web traffic
This procedure shows how to add SSL (secure socket layers) to enable secure HTTP (HTTPS) in
ThoughtSpot. To set up SSL, you will need:
• The SSL certificate
• The private key
To install the SSL certificate:
1. Follow the instructions from your certifying authority to obtain the certificate. This is usually
sent via email or available by download.
2. Copy the certificate and key files to ThoughtSpot:

$ scp admin@:

3. Log in to the Linux shell using SSH.
4. Change directories to where you copied the certificate:

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Configure SSL

February 06, 2019

$ cd

5. Issue the tscli command to install the certificate:

$ tscli ssl add-cert

6. To test that the certificate was installed correctly, Log in to the ThoughtSpot application.
You should see that the application’s URL begins with https:// .

Set the recommended TLS version
There are a couple of security vulnerabilities due to SSL certificates supporting older versions of TLS
(Transport Layer Security). This procedure shows you how to set the recommended TLS version to avoid
these vulnerabilities.
The PCI (Payment Card Industry) Data Security Standard and the FIPS 140-2 Standard require a
minimum of TLS v1.1 and recommends TLS v1.2.
ThoughtSpot supports SSL v3, TLS v1.0, and TLS v1.1 for backwards compatibility. However, the
recommended version is TLS v1.2. Therefore, to set the recommended TLS version:
1. Enable your web browser to support TLS v1.2. This can be done in your browser’s advanced
settings.
2. Log in to the Linux shell using SSH..
3. Issue the following command:

tscli ssl set-min-version 1.2

This will block all usage of older versions.

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Configure SAML

February 06, 2019

Configure SAML
Summary: You can use the Security Assertion Markup Language
(SAML) to authenticate users
You can set up SAML through the shell on ThoughtSpot using a tscli based configurator.

Prerequisites
Before configuring SAML, you will need this information:
•
•
•
•

IP of the server where your ThoughtSpot instance is running.
Port of the server where your ThoughtSpot instance is running.
Protocol, or the authentication mechanism for ThoughtSpot.
Unique service name that is used as the unique key by IDP to identify the client.
It should be in the following format: urn:thoughtspot:callosum:saml

• Allowed skew time, which is the time after authentication response is rejected and sent back
from the IDP. It is usually set to 86400.
• The absolute path to the idp-meta.xml file. This is needed so that the configuration persists
over upgrades.
• This configurator also checks with the user if internal authentication needs to be set or not.
This internal authentication mechanism is used to authenticate tsadmin , so set it to true if
you do not know what it does.

Use tscli to configure SAML
Use this procedure to set up SAML on ThoughtSpot for user authentication. Note that this configuration
persists across software updates, so you do not need to reapply it if you update to a newer release of
ThoughtSpot.
1. Log in to the Linux shell using SSH.
2. Execute the command to launch the interactive SAML configuration:

tscli saml configure

3. Complete the configurator prompts with the information you gathered above.
4. When the configuration is complete, open a Web browser and go to the ThoughtSpot login
page. It should now show the Single Sign On option.

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Enable Active Directory based access

February 06, 2019

Enable Active Directory based access
Summary: ThoughtSpot supports enabling Active Directory (AD)
based access individually on each node where the commands are
run.

Enable Active Directory based access on a
ThoughtSpot node
ThoughtSpot supports enabling Active Directory (AD) based access individually on each node where the
commands are run. There is no provision to enable AD access for the whole cluster with a single
command. To enable AD access on a cluster, you need to run these commands on each individual node
and on any additional nodes added to the cluster.
The command to enable system AD user access is:

tscli sssd enable --user --domain

You will then be prompted for password credentials.

 Note: The user must have permission to join a computer or VM to the domain.

Set sudoers AD Group on a local node
Just like enabling AD based access on a node, setting sudo AD group applies only on the node where
the command is run, and is not set for the whole cluster.
The command to allow sudo permissions for AD group:

tscli sssd set-sudo-group

Clear sudoers AD Group on a local node
Clearing sudo AD group only applies on the node where command is run, and is not set for the whole
cluster.
The command to clear sudo permissions for the AD group:

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tscli sssd clear-sudo-group

Disable AD based access on a local node
Currently ThoughtSpot supports disabling AD based access individually on each node where the
commands are run. There is no provision to disable AD access for the whole cluster with a single
command. To disable AD access on a cluster, run these commands on each individual node and any
additional nodes added to the cluster.
Command to disable system AD user access is:

tscli sssd disable

 Note: Running this command will also remove the AD group from sudoers list.

Related Information
• sssd in the tscli command reference

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About LDAP integration

February 06, 2019

About LDAP integration
Summary: You authenticate users against an LDAP server.
Some companies use LDAP (Lightweight Directory Access Protocol) to manage user authentication.
Using LDAP provides security and makes user management more centralized. You can choose to
authenticate users against an LDAP server, against ThoughtSpot, or both.
ThoughtSpot supports both anonymous and non-anonymous LDAP integration. Non-anonymous LDAP
binding is more rigorous than anonymous authentication, but it should help you track what your users
are querying and keep a log trace for auditing purposes.
If you have been using ThoughtSpot with users you created manually, and you now want to transition to
LDAP, please contact ThoughtSpot Support. They can assist you in migrating existing users to their
LDAP equivalents.
ThoughtSpot supports LDAP with Active Directory.

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Configure LDAP for Active Directory

February 06, 2019

Configure LDAP for Active Directory
Summary: Use this procedure to set up integration with LDAP using
Active Directory.
Before you configure LDAP for Active Directory, collect this information:
• URL to connect to Active Directory.
For example, ldap://192.168.2.48:389
• Default LDAP domain.
The default domain is the domain under which users who want to be authenticated against
Active Directory reside. When a user logs in with a username, the default domain is added to
the username before sending it to the LDAP server. If users reside in multiple domains, you
can still designate one of them as the default. Users belonging to a non-default domain will
have to explicitly qualify their username when they log in, for example:
username@ldap1.thoughtspot.com .
• Whether you will use SSL.
If yes, you’ll need the certificate from the issuing authority.
• LDAP search base.
This prompt adds the search base information that allows ThoughtSpot to find user properties
such as email and displayname from LDAP.
• Automatically add LDAP users in ThoughtSpot?
If you choose ‘yes’ for this, when a user is authenticated against LDAP, if that user does not
exist in ThoughtSpot, then the user is automatically created. When users are created in this
way, their passwords exist only in LDAP and are not stored in ThoughtSpot.
In order to log in to ThoughtSpot, the user has to exist in ThoughtSpot independent of
whether that user is authenticated against LDAP or against ThoughtSpot’s internal
authentication. If you choose ‘no’ for this, users who will authenticate against LDAP have to
be manually created with a dummy password as a placeholder in ThoughtSpot before they
can log in. The username you specify when creating the LDAP authenticated user manually in
ThoughtSpot has to be domain qualified, for example: username@ldap1.thoughtspot.com .
• Also use ThoughtSpot internal authentication?
If you choose ‘yes’ for this, when a user logs in, ThoughtSpot will first attempt to authenticate
the user against LDAP. If that attempt fails, it will then attempt to authenticate the user against
ThoughtSpot. If either of these succeed, then the user is successfully logged in. This option is
useful in scenarios where some users are not in LDAP and are created only in ThoughtSpot.
You do not need to create a user called tsadmin on your LDAP server. Internal authentication can be
used for tsadmin . To configure LDAP:
1. Log in to the Linux shell using SSH.
2. Run the command to configure LDAP:

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Configure LDAP for Active Directory

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$ tscli ldap configure

3. Answer the prompts using the information you collected. For example:

Choose the LDAP protocol:
[1] Active Directory
Option number: 1
Configuring Active Directory
URL to connect to Active Directory. (Example: ldap://19
2.168.2.100:389): ldap://192.168.2.100:389
Default domain (Example: ldap.thoughtspot.com): ldap.th
oughtspot.com
Use SSL (LDAPS) (y/n): n
LDAP search base (Example: cn=Users): cn=Users
Automatically add LDAP users in ThoughtSpot (y/n): y
Also use ThoughtSpot internal authentication (y/n): y

4. If you are using SSL, Add the SSL certificate for LDAP.
5. If you want to remove the LDAP configuration, issue:

$ tscli ldap purge-configuration

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Add the SSL certificate for LDAP

February 06, 2019

Add the SSL certificate for LDAP
Summary: Install the certificate to support LDAPS
When you set up LDAP, you specified whether or not to use SSL for LDAP (LDAPS). If using SSL, you
must install the LDAP SSL certificate. Before you can add the SSL certificate, you must Configure LDAP
for Active Directory.
You must have the SSL certificate before you start. For more information on obtaining an SSL certificate,
see Configure SSL (secure socket layers).
To add the SSL certificate for LDAP:
1. Follow the instructions from your certifying authority to obtain the certificate. This is usually
sent via email or available by download.
2. Copy the certificate to ThoughtSpot:

$ scp admin@:

3. Log in to the Linux shell using SSH.
4. Change directories to where you copied the certificate:

$ cd

5. Run the command to configure SSL for LDAP, designating an alias for this certificate using
the parameter:

$ tscli ldap add-cert

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Test the LDAP configuration

February 06, 2019

Test the LDAP configuration
Summary: This procedure allows you to test the LDAP connection
you created.
After configuring LDAP, you can test to make sure it is working by issuing a command.
1. Log in to the Linux shell using SSH.
2. Issue the LDAP testing command, supplying the information for the LDAP server you
configured, as in this example:

$ ldapsearch -x -h 192.168.2.61 -p 389 -D "testuser@lda
p.thoughtspot.com" -W -b "dc=ldap,dc=thoughtspot,dc=co
m" cn

3. Supply the LDAP password when prompted.
4. If the connection works, you’ll see a confirmation message.

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Sync users and groups from LDAP

February 06, 2019

Sync users and groups from LDAP
Summary: Use this procedure to synchronize your ThoughtSpot
system with an LDAP server.
Before synchronizing users and groups, you will need this information:
• IP address and port of the server where your ThoughtSpot instance is running. This hostport
is needed in the following format http(s)://: or http(s):// .
• Administrator login username and password for your ThoughtSpot instance.
• URL of the LDAP server, or hostport.
For example, ldap://192.168.2.48:389
• Login username and password for the LDAP system.
An example username would be moo_100@ldap.thoughtspot.com
• Distinguished Name (DN) for the base to start searching for users in the LDAP system.
For example, DC=ldap,DC=thoughtspot,DC=com
• Location of the Python synchronization script, in case you want to modify it or create your
own: /usr/local/scaligent/release/callosum/utilities/ldap_sync_python_api/
syncUsersAndGroups.py

There are two ways for you to fetch users and groups from LDAP and populate them into your
ThoughtSpot system:
• Run the synchronization script in interactive mode, which will walk you through the process
(shown here).
• Create your own Python script by using the ThoughtSpot Python APIs. If you need details on
the Python APIs, contact ThoughtSpot Support. If you choose this method, you can run the
script periodically using a cron job.
To run the LDAP sync script in interactive mode:
1. Log in to the Linux shell using SSH.
2. Run the command to start the script:

python syncUsersAndGroups.py interactive

3. Answer the prompts using the information you collected above. For example:

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Sync users and groups from LDAP

February 06, 2019

Complete URL of TS server in format "http(s)://:": http://10.77.145.24:8088
Disable SSL authentication to TS server (y/n): y
Login username for ThoughtSpot system: admin
Login password for ThoughtSpot system: 12345
Complete URL of server where LDAP server is running in
format ldap(s)://:: ldap://192.168.2.48:389
Login username for LDAP system: moo_100@ldap.thoughtspo
t.com
Login password for LDAP system: 12345
Syncs user and groups between LDAP and TS systems (y/
n): y
Delete entries in ThoughtSpot system that are not curre
ntly in LDAP tree being synced (y/n): n
Distinguished name for the base to start searching grou
ps in LDAP System: DC=ldap,DC=thoughtspot,DC=com
Scope to limit the search to (choice number)
0:base Searching only the entry at the base DN
1:one Searching all entries on level under the base DN
- but not including the base DN
2:tree Searching of all entries at all levels under an
d including the specified base DN: 2

Filter string to apply the search to: (|(CN=TestGroupAl
pha)(CN=TestGroupBeta))

Answering this prompt is optional. If left blank, the default value of '(CN=*)' will be used.

Apply sync recursively, i.e. Iterates through group mem
bers and creates member groups, users and relationships
in a recursive way. (y/n): n

This prompt is asking if you would like to include group members even if they do not belong
to the current sub tree that is being synced.
4. Alternatively, to input your own shorthand script commands:
Issue the Python script commands, supplying all of the above information, following this
format example:

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Sync users and groups from LDAP

February 06, 2019

python syncUsersAndGroups.py script \
–-ts_hostport \
--disable_ssl \
--ts_uname \
--ts_pass \
--ldap_hostport '' \
--ldap_uname '' \
--ldap_pass '' \
--sync \
--purge \
--basedn 'DC=ldap,DC=thoughtspot,DC=com' \
--filter_str '(|(CN=TestGroupAlpha)(CN=TestGroupBet
a))' \
--include_nontree_members

The bottom half of the above command example targets sub trees under the DC called
TestGroupAlpha and TestGroupBeta, and iterates through them recursively to create/sync
users, groups, and their relationships in the ThoughtSpot system. It also deletes any other
entities created in the ThoughtSpot system from this LDAP system that are not currently
being synced.

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Configure NAS file system

February 06, 2019

Configure NAS file system
Summary: You can use network attached storage to support backup/
restore and data loading.
Some operations, like backup/restore and data loading, require you to either read or write large files. You
can mount a NAS (network attached storage) file system for these operations. Currently, ThoughtSpot
does not have an option for direct attached storage. Your NAS storage can use whichever drive format
you would like.
This procedure shows you how to mount a NAS file system for storing or accessing large files. The file
system will be mounted at the same location on each node in the cluster automatically. When any node
is restarted, the file system will be mounted again automatically, if it can be found.
When supplying a directory for writing or reading a backup, you can specify the mount point as the
directory to use. Likewise, you can stage data there for loading.
Backups are written by the Linux user admin . If that user does not have permission to write to the NAS
file system, you could write the backups to disk (for example /export/sdc1 , /export/sdd1 ,
/export/sde1 , or /export/sdf1 ) and then set up a cron job that executes as root user and copies
the backup to the NAS device every night, then deletes it from the directory.
Do not send the periodic backups or stage files on /export/sdb1 since it is a name node. It is used
internally by Hadoop Distributed File System (HDFS) and if this drive fills up, it can cause serious
problems. Do not allow backups or data files to accumulate on ThoughtSpot. If disk space becomes
limited, the system will not function normally.
1. Log in to the Linux shell using SSH.
2. Mount the directory to the file system, by issuing the appropriate command:
• For an NFS (Network File System) directory:

tscli nas mount-nfs
--server
--path_on_server
--mount_point
--options vers=, sec=,

 Note: Other command-line options are available to forward to the
command (default: noexec).

• For a CIFS (Common Internet File System) directory:

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Configure NAS file system

February 06, 2019

tscli nas mount-cifs
--server
--path_on_server
--mount_point
--username
--password
--uid
--gid
--options

 Note: Other command-line options are available to forward to the
mount.cifs command (default: noexec).

3. Use the mounted file system as you wish, specifying it by referring to its mount point.
4. When you are finished with it, you may optionally unmount the NAS file system:

tscli nas unmount --dir

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Set up monitoring

February 06, 2019

Set up monitoring
Summary: Setting up monitoring is a one time operation.
To configure monitoring of your cluster, set up the frequency of heartbeat and monitoring reports and an
email address to receive them.
1. Log in to the Linux shell using SSH.
2. Issue the tscli command to set up monitoring:

tscli monitoring set-config
--email
--heartbeat_interval
--report_interval

The parameters are:
•

--email is a comma separated list (no spaces) of email addresses
where the cluster will send monitoring information.

•

--heartbeat_interval is the heartbeat email
generation interval in seconds. Must be greater than 0.

•

--report_interval sets the cluster report email
generation interval in seconds. Must be greater than 0.

3. To view your settings and verify that they have been applied, issue:

tscli monitoring show-config

You should see information like:

Monitoring Configuration:
Alert Email: dev-alerts@thoughtspot.com
Heartbeat Interval: 900 sec
Report Interval: 21600 sec

4. After the heartbeat interval has passed, check your email to verify that emails are being
delivered.
5. If you don’t receive any emails, verify that email is working.

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Configure support services

February 06, 2019

Configure support services
Summary: Set up and configure ThoughtSpot support services for
your installation.
There are several configurations you can set up in your installation to ensure your company’s support
from ThoughtSpot works smoothly.

Set up a reverse tunnel for support
You can set up a reverse tunnel to allow ThoughtSpot Support to get access to your ThoughtSpot
instance, to perform support-related activities. This setup is a much simpler, more secure, and scalable
than the alternative option of using a virtual meeting room.
Granting remote support access can streamline troubleshooting activities, since it enables your support
agent to work directly in a secure setting. The remote tunnel enables SSH and HTTP access to your by
ThoughtSpot Support. This access can be granted and revoked easily, so you can enable it for a
troubleshooting session, and then disable it again. Before doing this procedure, make sure your
company’s security policies allow reverse tunneling.
Before you can do this procedure, your networking team needs to open port 22 in your firewall
outgoing rules.
To enable remote support:
1. Contact ThoughtSpot and open a support ticket for making the appropriate reverse tunnel
settings on our end. Provide the cluster name of the cluster for which you want to enable
remote support.
2. After the ticket is completed, continue with the remaining steps in this procedure to make the
settings on your side.
3. Log into the Linux shell using SSH.
4. Issue the command to configure the destination for the remote tunnel.
You only need to do this once, when you are enabling the tunnel for the very first time. After
that, this setting persists when you start and stop the remote tunnel.

$ tscli support set-remote --addr tunnel.thoughtspot.co
m --user ubuntu

5. Test that the setting is configured:

$ tscli support show-remote

6. Enable the remote tunnel:

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Configure support services

February 06, 2019

$ tscli support start-remote

7. Contact ThoughtSpot and test the setup with your ThoughtSpot Support contact.
8. After your remote session with ThoughtSpot Support, turn the remote tunnel off, until you
need to use it again:

$ tscli support stop-remote

You can repeat the steps to start and stop the remote tunnel as needed for future support
operations.
9. Ensure that the remote tunnel is disabled:

$ tscli support show-remote

Configure a secure file server
ThoughtSpot Support uses a secure file server to provide new releases and to receive logs and
troubleshooting files that you upload. The secure server connection is also required if you want to enable
the optional statistics collection using the call home feature.
Before you can upload a file to the secure file server, obtain your user name and password for logging in
to the secure file server. You can get these from ThoughtSpot Support.
Configuring the connection to the file server is a one time operation. You do not need to reconfigure the
connection unless your password changes. Note that you can do a one time override of the user and
password you used to configure the connection. This is done by passing a different user and password
on the command line when uploading or downloading a file.
To configure the connection to the secure file server:
1. Log in to the Linux shell using SSH.
2. Issue the command to configure the file server:

$ tscli fileserver configure --user [--pass
word ]

If you do not supply the --password parameter, you are prompted to enter it.

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Configure support services

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Call home with cluster usage data
“Call home” data is metadata and usage data from your ThoughtSpot cluster. This data allows
ThoughtSpot’s Support team to troubleshoot your cluster. They use the data to see basic usage
information over time for your ThoughtSpot instance. ThoughtSpot’s “call home” functionality
intermittently sends a call home bundle of statistics to a ThoughtSpot S3 server via HTTPS. The data is
encrypted at rest on the server.
By default, call home is enabled on your cluster. You can disable call home in by doing the following:
1. Log into the ThoughtSpot server as admin user.
2. Use the tscli command to disable.

$ tscli callhome disable

Designate a support contact
A support contact person can answer questions for about data and searching at your company. If the
person can’t answer a question that person should submit system and software-related questions to
ThoughtSpot Support. Your designated support contact should have an available email and phone
number.
To designate the custom support contact:
1. Log in to the Linux shell using SSH.
2. Issue the tscli command to set the email address:

$ tscli support set-admin-email

3. Issue the tscli command to set the phone number:

$ tscli support set-admin-phone

4. If you need to reset both of these to the default (ThoughtSpot Support), issue:

$ tscli support rm-admin-email
$ tscli support rm-admin-phone

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Manage the feedback contact
Users in ThoughtSpot may be asked for feedback for new or BETA features in the system. By default,
feedback goes directly to ThoughtSpot support. Alternatively, you can send feedback to someone in
your company, this is useful if you are using ThoughtSpot embedded.
Your designated feedback contact should have an available email. To designate the custom feedback
contact, do the following:
1. Log in to the Linux shell using SSH.
2. To set the feedback email address, do the following:

$ tscli support set-feedback-email

3. Verify the email address was set:

$ tscli support show-feedback-email

If you need to reset the email to the default (ThoughtSpot support), issue:

$ tscli support rm-feedback-email

You can also choose not to send feedback out of your system at all by doing the following:

$ tscli support set-feedback-email ' '

How users find your company’s support
contact
After you set the custom support contact information, here’s where your users will see it:
• In the Help Center, when a user selects Contact Support
Support.

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Configure support services

February 06, 2019

• In error messages, when a user selects What Happened?

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Page 46

Network ports

February 06, 2019

Network ports
Summary: Lists the required and optional ports for an installation.
For regular operations and for debugging, there are some ports you will need to keep open to network
traffic from end users. Another, larger list of ports must be kept open for network traffic between the
nodes in the cluster.

Required ports for operations and debugging
The following ports need to be opened up to requests from your user population. There are two main
categories: operations and debugging.
Port

Protocol

Service
Name

Direction

Source

Destination

Description

SSH

bidirectional

Administrators
IP addresses

All nodes

Secure shell access.
Also used for scp (secure copy).

HTTP

bidirectional

All users IP
addresses

All nodes

Hypertext Transfer
Protocol for website
traffic.

443

HTTPS

bidirectional

All users IP
addresses

All nodes

Secure HTTP.

12345

TCP

Simba

bidirectional

Administrators
IP addresses

All nodes

Port used by ODBC
and JDBC drivers
when connecting to
ThoughtSpot.

2201

HTTP

Orion
master
HTTP

bidirectional

Administrator
IP addresses

All nodes

Port used to debug
the cluster manager.

2101

HTTP

Oreo
HTTP

bidirectional

Administrator
IP addresses

All nodes

Port used to debug
the node daemon.

4001

HTTP

Falcon
worker
HTTP

bidirectional

Administrator
IP addresses

All nodes

Port used to debug
the data cache.

4251

HTTP

Sage
master
HTTP

bidirectional

Administrator
IP addresses

All nodes

Port used to debug
the search engine.

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Network ports

February 06, 2019

Network Ports
This reference lists the potential ports to open when setting up your security group.

Required ports for inter-cluster operation
Internally, ThoughtSpot uses static ports for communication between services in the cluster. Do not
close these ports from inter-cluster network communications. In addition, a number of ports are
dynamically assigned to services, which change between runs. The dynamic ports come from the range
of Linux dynamically allocated ports (20K+).
Port

Protocol

Service Name

Direction

Source

Dest.

Description

TCP

nginx

inbound

All nodes

All
nodes

Primary app HTTP
port (nginx)

443

TCP

Secure nginx

inbound

All nodes

All
nodes

Primary app
HTTPS port (nginx)

2100

RPC

Oreo RPC port

bidirectional

All nodes

All
nodes

Node daemon
RPC

2101

HTTP

Oreo HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Node daemon
HTTP

2181

RPC

Zookeeper servers
listen on this port
for client connections

bidirectional

All nodes

All
nodes

Zookeeper servers
listen on this port
for client connections

2200

RPC

Orion master RPC
port

bidirectional

All nodes

All
nodes

Internal communication with the
cluster manager

2201

HTTP

Orion master
HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port used to debug the cluster
manager

2210

RPC

Cluster stats service RPC port

bidirectional

All nodes

All
nodes

Internal communication with the
stats collector

2211

HTTP

Cluster stats service HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port used to debug the stats collector

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Network ports

February 06, 2019

Port

Protocol

Service Name

Direction

Source

Dest.

Description

2230

RPC

Callosum stats
collector RPC port

bidirectional

All nodes

All
nodes

Internal communication with the BI
stats collector

2231

HTTP

Callosum stats
collector HTTP
port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port used to debug the BI stats
collector

2240

RPC

Alert manager

bidirectional

All nodes

All
nodes

Port where alerting
service receives
alert events

2888

RPC

Ports used by
Zookeeper servers
for communication
between themselves

bidirectional

All nodes

All
nodes

Ports used by
Zookeeper servers
for communication
between themselves

3888

RPC

Ports used by
Zookeeper servers
for communication
between themselves

bidirectional

All nodes

All
nodes

Ports used by
Zookeeper servers
for communication
between themselves

4000

RPC

Falcon worker
RPC port

bidirectional

All nodes

All
nodes

Port used by data
cache for communication between
themselves

4001

HTTP

Falcon worker
HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port used to debug the data
cache

4021

RPC

Sage metadata
service port (exported by Tomcat)

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port where search
service contacts
metadata service
for metadata

4201

HTTP

Sage auto complete server HTTP
interface port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port used to debug the search
service

4231

HTTP

Sage index server
HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port used to debug the search
service

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Network ports

February 06, 2019

Port

Protocol

Service Name

Direction

Source

Dest.

Description

4232

RPC

Sage index server
metadata subscriber port

bidirectional

All nodes

All
nodes

Port used for
search service internal communication

4233

RPC

Sage index server
RPC port

bidirectional

All nodes

All
nodes

Port used for
search service internal communication

4241

HTTP

Sage auto complete server HTTP
port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Port used to debug the search
service

4242

RPC

Sage auto complete server RPC
port

bidirectional

All nodes

All
nodes

Port used for
search service internal communication

4243

RPC

Sage auto complete server metadata subscriber
port

bidirectional

All nodes

All
nodes

Port used for
search internal
communication

4251

RPC

Sage master RPC
port

bidirectional

All nodes

All
nodes

Port used for
search service internal communication

4405

RPC

Diamond (graphite)
port

bidirectional

All nodes

All
nodes

Port used for communication with
monitoring service

4500

RPC

Trace vault service
RPC port

bidirectional

All nodes

All
nodes

Trace collection
for ThoughtSpot
services

4501

HTTP

Trace vault service
HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Debug trace collection

4851

RPC

Graphite manager
RPC port

bidirectional

All nodes

All
nodes

Communication
with graphite manager

4852

HTTP

Graphite manager
HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Debug graphite
manager

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Network ports

February 06, 2019

Port

Protocol

Service Name

Direction

Source

Dest.

Description

4853

RPC

Elastic search
stack (ELK) manager RPC port

bidirectional

All nodes

All
nodes

Communication
with log search
service

4853

HTTP

Elastic search
stack (ELK) manager HTTP port

bidirectional

Admin IP
addresses
and all
nodes

All
nodes

Debug log search
service

5432

Postgres

Postgres database
server port

bidirectional

All nodes

All
nodes

Communication
with Postgres
database

8020

RPC

HDFS namenode
server RPC port

bidirectional

All nodes

All
nodes

Distributed file
system (DFS)
communication
with clients

8080

HTTP

Tomcat

bidirectional

All nodes

All
nodes

BI engine communication with
clients

8787

HTTP

Periscope (UI) service HTTP port

bidirectional

All nodes

All
nodes

Administration UI
back end

8888

HTTP

HTTP proxy server
(tinyproxy)

bidirectional

All nodes

All
nodes

Reverse SSH tunnel

11211

Memcached

Memcached server port

bidirectional

All nodes

All
nodes

BI engine cache

12345

ODBC

Simba server port

bidirectional

All nodes

All
nodes

Port used for ETL
(extract, transform,
load)

50070

HTTP

HDFS namenode
server HTTP port

bidirectional

All nodes

All
nodes

Debug DFS metadata

50075

HTTP

HDFS datanode
server HTTP port

bidirectional

All nodes

All
nodes

Debug DFS data

Required ports for inbound and outbound cluster access
ThoughtSpot uses static ports for inbound and outbound access to a cluster.
Port

Protocol

Service
Name

Direction

Source

Dest.

Description

SCP

SSH

bidirectional

ThoughtSpot
Support

All
nodes

Secure shell access.

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Network ports

February 06, 2019

Port

Protocol

Service
Name

Direction

Source

Dest.

Description

HTTP

bidirectional

ThoughtSpot
Support

All
nodes

Hypertext Transfer Protocol
for website traffic.

443

HTTPS

bidirectional

ThoughtSpot
Support

All
nodes

Secure HTTP.

12345

TCP

Simba

bidirectional

ThoughtSpot
Support

All
nodes

Port used by ODBC and JDBC drivers when connecting
to ThoughtSpot.

Port

Protocol

Service
Name

Direction

Source

Destination

Description

443

HTTPS

outbound

All nodes

208.83.110.20

For transferring files to
thoughtspot.egnyte.com (IP
address 208.83.110.20).

25
or
587

SMTP

SMTP
or Secure
SMTP

outbound

All nodes
and
SMTP relay (provided by
customer)

All nodes

Allow outbound access for
the IP address of whichever
email relay server is in use.
This is for sending alerts to
ThoughtSpot Support.

389
or
636

TCP

LDAP
or
LDAPS

outbound

All nodes
and
LDAP
server
(provided
by customer)

All nodes

Allow outbound access for
the IP address of the LDAP
server in use.

Required ports for IPMI (Intelligent Platform Management Interface)
ThoughtSpot uses static ports for out-of-band IPMI communications between the cluster and
ThoughtSpot Support.
Port

Protocol

Service
Name

Direction

Source

Dest.

Description

HTTP

bidirectional

ThoughtSpot
Support

All
nodes

Hypertext Transfer Protocol
for website traffic.

Related information
EC2 Best Practices

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Configure load balancing and proxies

February 06, 2019

Configure load balancing and proxies
Summary: A load balancer is needed in front of a server group in
order to direct traffic to individual servers in a way that maximizes
efficiency.
Here are some of the best practices and guidelines for a typical implementation with ThoughtSpot. Your
experience may differ depending on your environment and preference.

Load balance across ThoughtSpot nodes
The following shows a network architectural diagram which includes a load balancer for ThoughtSpot
nodes.

The load balancer is an appliance in your infrastructure that routes traffic automatically to nodes to
provide failover. You can also place a load balancer or proxy in front of the ThoughtSpot appliance if
you’d like external network users to access the system.
The best way to load balance across all ThoughtSpot nodes in a cluster is to map one domain name
(FQDN) to all the IPs in the cluster in a round robin fashion.
For example, if you want to use a DNS server based load balancing, then you can define multiple “A”
resource records (RR) for the same name.
Below is an example of how you could set that up

thoughtspot.customer.com
thoughtspot.customer.com
thoughtspot.customer.com
thoughtspot.customer.com

IN
IN
IN
IN

A
A
A
A

69.9.64.11
69.9.64.12
69.9.64.13
69.9.64.14

The example indicates that IP addresses for the domain thoughtspot.customer.com are 69.9.64.11,
69.9.64.12, 69.9.64.13, and 69.9.64.14.

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Configure load balancing and proxies

February 06, 2019

Session Affinity
Session Affinity refers to directing requests to the same application server for the time it takes to
complete a task.
In order for session affinity to work on ThoughtSpot, HTTPS (an SSL certificate) has to be installed on
the load balancer level. If it is installed outside of the load balancer, session affinity may not occur and
the ThoughtSpot system will fail.

Web proxies
You can access ThoughtSpot through any standard web proxy server. Web proxies are fairly universal
regardless of the application they are proxying. However, ThoughtSpot doesn’t use any new protocols,
like SPDY or HTTP/2, which may have a dependency on the proxy. Instead, ThoughtSpot is commonly
placed behind a web HTTP/HTTPS proxy.
Additionally, the proxy can round robin across multiple nodes in the ThoughtSpot backend. You can
essentially use the web proxy as a load balancer. Therefore, your session will carry over if the proxy
round robins between the ThoughtSpot backends as long as the URL doesn’t change.

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Page 54

Customize ThoughtSpot Help

February 06, 2019

Customize ThoughtSpot Help
Summary: You customize ThoughtSpot Help to be specific to your
data, examples, and documentation.
You can customize the Help for your ThoughtSpot application to tailor it to your organization.
Configuring these Help settings sets system-wide defaults for all your users.
When your ThoughtSpot users click the Help icon, they see a list of links.

As an administrator, you can add your own links to this list. This allows you to include documentation
specific to your company, such as information about the data available in ThoughtSpot, where to get
support internally, or company-specific training.

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Customize ThoughtSpot Help

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You can also edit existing links, change icons, or remove items from the help listing altogether.

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Page 56

Customize look and feel

February 06, 2019

Customize look and feel
Summary: You can brand the ThoughtSpot application for your
company.
You can customize the look and feel of the ThoughtSpot application for your company. Configuring
these settings sets system-wide defaults for all your users.
Style customization is enabled by default. You can configure your cluster to disable this functionality.
Contact support@thoughtspot.com for information about disabling this feature.

Where to customize styles
A user with administrative rights can view and access the customization on the Admin page.

Use the Style Customization page to access the configuration settings.

General guidelines for customization
Your changes take effect either immediately or with browser refresh. You can revert your changes by
using the Reset button which displays when your cursor moves to the right of any setting.

The table below lists the style customizations you can configure.
Setting

Description

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Customize look and feel

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Application
Logo
(Default) &
Favicon

Sets a default application and favicon logo. This should be 140 pixels square.

Application
Logo (Wide)

This logo should be 440 x 100 pixels.

Chart
Visualization
Fonts

Set a font for chart labels. You can specify any Web Open Font Format (`WOFF`) file.

Table
Visualization
Fonts

Set a font for table labels. You can specify any Web Open Font Format (`WOFF`) file.

Embedded
Application
Background

Set the background for an embedded ThoughtSpot instance. This is only used if you
are embedding ThoughtSpot in another application.

Chart Color
Palettes

Set the default palette for all charts. To set a value, however over a color value and
enter a HEX value or select one from the chart. Individual users can still customize
their own chart colors. They can use the **Reset colors** option on a chart to clear
their changes.

Footer text

Define a footer to appear with the ThoughtSpot application.

Page title

Sets the title for the browser tab.

How to specify fonts
You can set your systems default fonts by specifying either or both of the Chart Visualization Fonts and
Table Visualization Fonts values. To set this values, your font must be defined in a Web Open Font
Format ( WOFF ) file.
Changes to chart and table defaults apply only to charts and features created after you configure a
value. If you change table fonts, older tables retain their previous fonts. Some settings can be overridden
on a per-object level. Users cannot configure their own defaults.
To set a new font:

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Customize look and feel

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1. Make sure you have a WOFF file available for your font.
2. Select the label you want to change.
3. Press the + button.
The system displays the Custom Font dialog.
4. Press the Custom Font field.
The system displays the file finder.
5. Add the WOFF file you want.
The file appears in the font dialog
6. Press Save to change the font.

How to specify the behavior or clickable links in
data
There is a system-wide setting which determines what happens when a user clicks on a link within the
data. When your data includes URLs, they display as clickable links in ThoughtSpot tables. By default,
clicking on a link opens the URL in a separate tab. But there is a system-wide setting that can be
changed to open the links within the context in which they appear.
Changing this setting opens the links:
Link type

Opens in

Link in search result table in ThoughtSpot

Same browser tab as ThoughtSpot application

Link in table embedded in an iFrame

Same iFrame that contains the table

Link in full ThoughtSpot application embedded in an
iFrame

Same iFrame that contains the application

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Page 59

Enable SearchIQ

February 06, 2019

Enable SearchIQ
Summary: Enable SearchIQ to provide natural language search for
some or all of your users.
SearchIQ is a different search experience that understands more natural, speech-like search language
than the original ThoughtSpot search or Search+
Search+. For example, you can search for What was my top
selling product last month? , instead of having to type top 1 product by sales last month .
You can also speak your search using the voice-to-text capability of your operating system.

 Note: SearchIQ is turned off by default, you can have ThoughtSpot Support enable it for you.

Users can easily teach SearchIQ their language as they use it. Over time, SearchIQ gets smarter about
how to interpret terms that don’t come directly from keywords, column names, or data values. In order to
give it time to learn, the best practice recommendation is to enable SearchIQ for a small group of users
initially. Over time you can roll it out to larger groups as SearchIQ learns what your users search for the
most.
To enable SearchIQ on a ThoughtSpot instance:
1. Call ThoughtSpot Support and ask them to turn on SearchIQ for your ThoughtSpot instance.
2. Grant the Can use experimental features privilege to any group that should have access to the
SearchIQ search experience.

 Note: Because the SearchIQ search experience is very different from the original ThoughtSpot
search experience, you should give your new users some orientation on it, so they know what to
expect.

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Enable SearchIQ

February 06, 2019

Related information
• About SearchIQ
• Use SearchIQ
• Teach SearchIQ your language

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Page 61

Slack integration

February 06, 2019

Slack integration
Working with ThoughtSpot, you can configure your installation to work with Slack. Users can use the
integration, called Spot
Spot, to make queries or view charts. Any users with administrative rights can apply a
spot sticker to specific objects. Then, the object is available through Slack.
The first time a user messages Spot, it returns a link to log into ThoughtSpot. Once a user logs in, the
user’s Slack and ThoughtSpot account are associated. Actions a user makes from Slack are tied to the
user’s permissions and authorization.

Spot workflow for administration
Here are the high level steps:
1.
2.
3.
4.
5.
6.

Work with support@thoughtspot.com to install the Spot Slack bot on your cluster.
Log into ThoughtSpot.
Label answers, pinboards, and other objects with the spot sticker.
Start Spot Bot.
Register Spot bot with your company’s Slack instance.
Register your Spot Slack account to ThoughtSpot.

Related Information
Relevant tscli commands are here, but these will not work until Spot is enabled by ThoughtSpot
Support. Support will work with you to install Spot, and then provide the rest of the workflow to you,
including tscli command usage.

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Page 62

Load and manage data

February 06, 2019

Load and manage data
Summary: There are several methods of loading data into
ThoughtSpot. This section describes each method and why you might
choose it above the others. Consider setting up data-cleansing tasks
alongside data-load tasks to make the most of your ThoughtSpot
cluster's capacity
The fastest and easiest way to load a new table is by importing it using the Web browser. This is best for
one time data loads of small tables which do not have complex relationships to other tables. This
method is limited to tables that are under 50 MB (megabytes) in size.
Using ThoughtSpot Loader, you can script recurring loads and work with multi-table schemas.
If your data already exists in another database with the schema you want to use in ThoughtSpot, you can
pull the schema and data in using the ODBC or JDBC driver.
These are the methods you can use to load data, along with the benefits of each method:
Method

Description

Benefits

Load data
from the
ThoughtSpot
UI

Use the ThoughtSpot Web interface to
upload an Excel or CSV (comma separated values) file from your local machine.

Easy way to do a one-time data load of
a small file (under 50MB).End users can
upload their own data and explore it
quickly.

Use
ThoughtSpot
Data Connect. For details, see the
ThoughtSpot
Data Connect
Guide

This is a premium feature, available at
additional cost. Use ThoughtSpot Data
Connect to connect directly to external
data sources and pull in tables and
columns from them. You can also set up
recurring loads to keep the data fresh.

Easy way to connect to multiple
sources of data directly and set up recurring loads. You won’t need to define
a schema to accept the data loads, because this is done automatically for
you.

Import with
the
ThoughtSpot
Loader
(tsload)

Use TQL and tsload to load data directly
into the back end database that
ThoughtSpot uses.

Best way to load large amounts of data
or a schema with multiple tables.Can
be scripted and used for recurring data
loads, such as monthly sales results or
daily logs. Can be integrated with an
ETL solution for automation.

Use the
ODBC/JDBC
driver to connect to
ThoughtSpot

Use the ODBC or JDBC client with your
ETL tool. For information, see the
ThoughtSpot Data Integration Guide.

Make use of an established ETL
process and tool(s).Connect to
ThoughtSpot using third party tools like
SSIS. You don’t need to define a
schema to accept the data load.

If you’re uploading data through the Web interface, you can use a native Excel file. If you want to use a
CSV (comma separated values) or delimited file, or you are loading using ThoughtSpot Loader, you’ll
need to create CSV files with the data to be loaded first.

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Load and manage data

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 Note: End users will almost always work with worksheets and data they upload.

Related Information
•
•
•
•
•
•

Load CSV files with the UI
Append data through the UI
Schema planning concepts
Overview of schema building
Import CSV files with tsload
How to view a data schema

ThoughtSpot Administration Guide

Page 64

Configure casing

February 06, 2019

Configure casing
Summary: You can set the type of case sensitivity you would like to
see reflected in the ThoughtSpot display.
Before you load your data, you should consider the type of casing you would like your data to reflect.
The case sensitivity for source data strings is preserved in the display. So, the visual display of results is
identical to the input case that is loaded.

 Note: The casing will remain lowercase in other parts of the application, such as when you ask
a question or filter.

It is important to note that string casings aren’t applied globally, but by column. So datasets will have
different string casings as long as they’re in different columns. Tables that are already compacted will
keep their lowercase format. In these cases, to get the specific string case that you want, you would
have to truncate related tables and reload them.
To take advantage of case configuration, you need to have ThoughtSpot Support enable it on your
cluster for you. In addition, title casing should be disabled for string casing to properly work.

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Page 65

Load CSV files with the UI

February 06, 2019

Load CSV files with the UI
Summary: The simplest way to load data is to upload a CSV or Excel
file from the ThoughtSpot Web interface.
Loading data through the Web browser is recommended for smaller tables (under 50MB) with simple
relationships between them. This method is recommended for small, one time data loads. Using this
method, the data schema is created for you automatically.
Any user who belongs to a group that has the privilege Has administration privileges or Can upload user
data can upload their own data from the browser.
Your data should be in a CSV (comma separated values) before you load it. A CSV file is a text file made
up of data fields separated by a delimiter and optionally enclosed with an enclosing character. If your
data contains multiple tables, you’ll have a separate CSV for each table.

Formatting the CSV
Your ETL (extract, transform, load) process will typically generate CSV files. You can also create a CSV
file from a Microsoft Excel spreadsheet by opening the spreadsheet in Excel, choosing Save As and
selecting CSV.
A CSV file contains a delimiter that marks the separation between fields in the data. The delimiter is
usually comma, but it can be any character. The file also contains fields optionally enclosed with double
quotes. Use these guidelines when creating the CSV file:
• If the CSV contains column headers, they must match the column names in the database
exactly.
• Often a | (pipe) or tab is used as the delimiter, because it may be less likely to occur within
the data values.
• When a field contains a double quote, it must be escaped with the character specified in the
escape character argument in tsload .
• When a field contains the delimiter, the field must be enclosed in double quotes.
ThoughtSpot supports a wide range of date and timestamp formats in the CSV file. Blank values in user
uploaded CSV files are interpreted as NULL values. These include the values (case insensitive):
• NULL
• \N
• NA
• N/A
• [space]
If you are appending data to an existing schema or table, columns in the CSV file must be in the same
order as defined in the target table.
If you are loading a fact table that joins to dimension tables, you must load the fact table first, and then
the dimension tables. The joining key must be a single column of unique values in the dimension table.
NULL values in the fact table cannot be joined.

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Load CSV files with the UI

February 06, 2019

Create a CSV file
The first step in loading data is to obtain or create one or more CSV files that contain the data to be
loaded into ThoughtSpot. CSV is a common format for transferring data between databases.
ThoughtSpot requires this format.
Most applications such as Microsoft Excel or Google Sheets can output CSV formatted files. If your
source is an Excel spreadsheet or Google Sheet:
1. Save, export, or download the file in CSV format. The exact procedure you use will depend on
the source application.
2. Review the file’s format before uploading it to ThoughtSpot.
Your source data may be in another database. If this is the case, your company’s ETL
(extract, transform, load) process will typically generate CSV files. If your source is another
database:
3. Connect to the source database.
4. Extract each table you wish to import into ThoughtSpot as a CSV file.
The column delimiter should be a , (comma), | (pipe), or tab.
For general information about CSV files and the rules for creating them, see the Commaseparated_values on Wikipedia.

Load the CSV File
Any user who belongs to a group that has the privilege Has administration privileges or Can upload user
data can upload their own data from the browser. To load the CSV or Excel file into ThoughtSpot:
1. Log into ThoughtSpot from a browser.
2. Click Data
Data, on the top navigation bar.
3. Click the the ellipses icon (3 dots)

, in the upper right corner, and select Upload Data
Data.

4. Upload the CSV or Excel file by doing one of these options:
a. Click on Browse your files and select the file.

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Load CSV files with the UI

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b. Drag and drop the file into the drop area.
5. Answer the question Are the column names already defined in the file header?
6. Answer the question Are the fields separated by? Click Next
Next.
7. Click on the column header names to change them to more useful names, if you’d like. Click
Next
Next.
8. Review the automatically generated data types for each column, and make any changes you
want.
There are four data types: Text, Integer, Decimal, and Date.
9. Click Import
Import.
When an upload is complete, the system reports the results and offers you some further
actions.

• Click Link to Existing Data if you want to link the data you uploaded to the data in
another table or worksheet.
• Click Search if you want to begin a new search.
• Click Auto analyze if you want to use the SpotIQ feature to find insights in your new
data.

Append to an existing table
You can append data to your existing system tables through the ThoughtSpot application, even if the
tables were initially loaded using Data Connect or tsload . The CSV file must have the same structure
as the table it is being loaded into, including number and type of columns, in the same order as the
target table.
To append data into ThoughtSpot:
1. Log in to ThoughtSpot from a browser.
2. Click Data on the top navigation bar.

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Load CSV files with the UI

February 06, 2019

3. Click the name of the table you would like to append data to.
4. Click the Load Data button.

5. Upload the CSV or Excel file by doing one of these options:
• Click Browse your files and select the file.
• Drag and drop the file into the drop area.
6.
7.
8.
9.
10.

Answer the question Are the column names already defined in the file header?
header?.
For the question Do you want to append to the existing data or overwrite it?
it?, select Append
Append.
Answer the question Are the fields separated by?
by?, and click Next
Next.
Click Upload
Upload.
Click Link to existing data if you want to link the data you uploaded to the data in another
table or worksheet. Or click Ask a question if you want to begin a new search.

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Page 69

How to view a data schema

February 06, 2019

How to view a data schema
Summary: Use the schema viewer to see tables and worksheets and
their relationships.
ThoughtSpot offers a schema viewer that lets you see your database schema in the web browser. The
Schema Viewer is interactive, so you can configure it to show just what you want to see.
You need Admin privileges to use the Schema Viewer
Viewer.

Bringing up the Schema Viewer
You can bring up the Schema Viewer from the Data screen. Click the ellipses icon (3 dots)

, and

select View Schema
Schema.

When viewing the schema, you can filter the tables shown similarly to how you filter data sources. The
list of tables, worksheets, and imported data on the left includes only those objects you want to see.
Clicking on one of the objects brings it to the middle of the viewer and highlights it. You can drag the
objects around in the viewer.

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How to view a data schema

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Why to use the Schema Viewer
You can use the Schema Viewer to find out information like:
• What is the relationship between two tables? What tables make up this
• worksheet, and how are they joined?
The schema viewer shows joins between tables, join directionality, and join type (whether they are
Foreign Key to Primary Key, relationship joins, or joins defined by users through the web interface). Use
the Table list to find a specific table or worksheet.

How the Schema Viewer shows joins
You can use the Schema Viewer to review your schema and ensure that it was modeled using best
practices. For example, joins are shown in separate colors that indicate their type:
• Red is used for generic relationships
• Green is used for primary key/foreign key joins
When viewing a worksheet, you’ll also be able to see whether an inner, left outer, right outer, or full outer
join was used between each of the joined tables.
A good rule to follow is “Keep it Green”. This means that you’ll get better results from PK/FK joins rather
than from using generic relationships. You should only use generic relationships when the tables being
joined have a many-to-many rather than a PK/FK structure. If you find tables that have been joined using
a generic relationship, but could have used a PK/FK join, you should drop the relationship and create a
PK/FK join instead. To do this, you need to use the ALTER TABLE…DROP RELATIONSHIP statement in
TQL. Then use ALTER TABLE…ADD FOREIGN KEY to create the PK/FK join.

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How to view a data schema

February 06, 2019

Worksheet view
Worksheets are often based on more than one table. The worksheet schema will show schemas for the
tables behind the worksheet, as well as the joins between tables that were created as a part of the
worksheet.
Click on a worksheet, to see it in the Schema Viewer. If the schema view is not showing the schema
behind the worksheet, double click the tab on the top right of the worksheet object.

The worksheet view shows the following information:
• All tables in the worksheet, and the relationships between these tables.
• Source columns for all columns of a worksheet.
• Keys and definitions for each relationship, as well as join paths and types.
• Columns that are derived from formulas.
• Correct join paths for newly created chasm trap worksheets. Existing chasm
• trap worksheets created prior to ThoughtSpot version 4.4 will not show the correct join paths.

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How to view a data schema

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Related Information
• Worksheet joins
• Change the schema using TQL
• Constraints

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Schema planning concepts
Summary: Considerations in creating a schema for the ThoughtSpot
Loader.
Before you can load data with ThoughtSpot Loader, you must create a schema to receive it, using the
SQL command line interface (TQL).
The TQL syntax is similar to the SQL used in other relational databases, but with some important
differences. You’ll use DDL (data definition language) to create the schema into which you’ll load the
data. You’ll probably want to put all your DDL statements into a text file, which you’ll use as a script for
creating the schema.
Before writing your TQL script, you need to understand some basic ThoughtSpot concepts.

About databases and schemas
ThoughtSpot organizes objects in a hierarchical namespace. Databases contain schemas, which contain
tables.

ThoughtSpot can contain one or more databases, and each database can have multiple schemas. If you
do not specify a schema, the default schema ( falcon_default_schema ) is used automatically. This
makes it easier to add tables to the database without the need to explicitly create a schema.
If you do create an additional schema, you must refer to its objects using the syntax
. . If you do not qualify the schema when referencing its objects, the
default schema ( falcon_default_schema ) will always be assumed.
By default, ThoughtSpot creates an internal database to host tables corresponding to data that is
imported by users from a Web browser.

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Review the structure of your data
The schema you create to hold the data needs to be a good fit for your data. First, familiarize yourself
with the tables you want to load, and understand their structure. Make note of this information for each
table:
•
•
•
•
•

The column names and data types
Type of table (fact or dimension)
Primary key column(s)
The size of the table on disk
Any other tables it can be joined with (foreign keys)

Here’s what you’ll need to take into account in your TQL for creating each table, based on these
properties:
Table type

Table
size

To be
joined
with

Schema recommendations

Fact

Any

Small dimension
table(s)

Sharded. Foreign key references the primary key in the dimension table.

Fact

Any

Large dimension
table(s)

Sharded on the same distribution key as the dimension table it
will be joined with. Foreign key references the primary key in the
dimension table.

Fact

Any

Another
fact table

Sharded on the same distribution key as the fact table it will join
with. Many-to-many relationship defines how the tables will be
joined.

Dimension

under
50MB

Fact
table(s)

Replicated (not sharded). Has a primary key.

Dimension

over
50MB

Fact
table(s)

Distributed dimension table, sharded on the same distribution
key as the fact table it will be joined with. Primary key must be
the same as the distribution key.

Where to go next
• Data types
ThoughtSpot supports the common data types. Compare these with the data types you want
to load, and do any necessary conversion ahead of loading the data.
• Constraints
Constraints include primary keys, foreign keys, and relationships. Relationships allow you to
create a generic relationship for use when you want to join tables that don’t have a primary
key/foreign key relationship.
• Sharding
For the best performance, you should split (or shard) very large tables across nodes. If you
have a large dimension table, you might choose to co-shard it with the fact table it will be

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joined with.
• Chasm traps
In a complex schema, you may have a fact table with no relationship to another fact table,
except that each contains a foreign key to a shared dimension table. This is known as a
chasm trap, and ThoughtSpot can handle it!

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Data types

February 06, 2019

Data types
Summary: ThoughtSpot supports the common data types.
Before you import data, compare the data types you want to load with these supported data types.
Then, convert your data before loading it. Typically, you would export the data, transform it to meet
these type rules, and then load the data. This is known as an extract-transform-load process.

Supported data types
The tables you create to receive the data must have the same number of columns and data types as the
data you will be loading. Choose a data type for each column from the list of supported data types:
Data

Supported data types

Details

Character

VARCHAR(*n*)

Specify the maximum number of characters, as
in VARCHAR(255) . The size limit is 1GB for
VARCHAR values.

Floating point

DOUBLE or FLOAT

DOUBLE is recommended. DOUBLE has a range
of 1.7E +/- 308 (15 digits).

Boolean

BOOL

Can be true or false .

Integer

INT or BIGINT

INT holds 32 bits. BIGINT holds 64 bits. INT
has a range of –2,147,483,648 to
2,147,483,647 . BIGINT range is
–9,223,372,036,854,775,808 to
9,223,372,036,854,775,807 .

Date or time

DATE , DATETIME ,

DATETIME , TIMESTAMP , and TIME are stored
at the granularity of seconds. TIMESTAMP is
identical to DATETIME , but is included for syntax compatibility.

TIMESTAMP , TIME

 Warning: There is a 1GB limitation on the number of characters for VARCHAR. If you have any
VARCHAR data that exceeds this limit, the entire load will fail.

Geographical data types
For geographical data types, use VARCHAR. For latitude and longitude, you can use either VARCHAR or
DOUBLE . After loading the data, designate it as a geographical data type when you Edit the system-wide
data model. Wherever abbreviations or codes are used, they are the same as what the USPS (United
States Postal Service) recognizes.
These data types can be designated as geographical data, which enables them to be visualized using
the Geo chart types:

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Data types

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• Countries, for example:
• United States
• long name : United States
• name_sort : United States of America
• abbreviation : U.S.A.
• adm0_a3 : USA
• adm0_a3_is : USA
• adm0_a3_us : USA
• admin : United States of America
• brk_a3 : USA
• brk_name : United States
• formal_en : United States of America
• iso_a2 : US
• iso_a3 : USA
• iso_n3 : 840
•

COUNTY for counties in the United States, for example:

• santa clara county
• pike county, ohio
• pike county, OH
•

STATE_PROVINCE for states in the United States, for example:

•
•
•

name : California
US Postal Service abbreviation : CA

LATITUDE which must be used with LONGITUDE , for example:

• 37.421023
• 1.282911
•

LONGITUDE which must be used with LATITUDE

• 122.142103
• 103.848865
•

ZIP_CODE for zip codes and zip codes +4 in the United States

•
•
•

po_name : MT MEADOWS AREA
ZIP : “00012”
zip2 : 12

• Other Sub-nation Regions which are administrative regions found in countries other than the
United States, for example:
• bremen
• normandy
• west midlands

 Important: You cannot upload your own custom boundaries.

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Constraints

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Constraints
Summary: Constraints allow you to build relationships and join tables.
Constraints include primary keys, foreign keys, and relationships. Relationships allow you to create a
generic relationship for use when you want to join tables that don’t have a primary key/foreign key
relationship.

Primary keys
When a primary key is selected for a table, it impacts data loading behavior. When a new row is added:
• If another row already exists with same primary key, it is updated with the values in the new
row.
• If a row with the same primary key does not exist already, the new row is inserted into the
table.
This behavior is referred to as “upsert” because it does an INSERT or an UPDATE , depending on
whether a row with the same primary key already exists.
Note that ThoughtSpot does not check for primary key violations across different shards of the table.
Therefore, you need to shard the table on the primary key columns if you require this “upsert” behavior.

Foreign key relationships
Foreign key relationships tell ThoughtSpot how two tables can be joined. These relationships are only
used for joining the tables, and not for referential integrity constraint checking.
The directionality of primary key - foreign key relationships is important. The foreign key relationship is
defined on the fact table and references the primary key(s) in the dimension table. So you can think of
the fact table as the source and the dimension table as the target. In the schema viewer, you’ll notice
that the arrow that represents a PK/FK join points to the dimension table.
If you use primary and foreign keys, when users search the data from the search bar, tables are
automatically joined. For example, assume there are two tables:
• revenue, which is a fact table
• region, which is a dimension table
There is a foreign key on the fact table on regionid which points to the id in the region dimension
table. When a user types in “revenue by region”, the two tables will be joined automatically.
Foreign keys have to match the primary key of the target table they refer to. So if there are multiple
columns that make up the primary key in the target table, the foreign key must include all of them, and in
the same order.

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Constraints

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Generic relationships (many-to-many)
You may have a schema where there is a fact table that you want to join with another fact table. If there
isn’t a primary key/foreign key relationship between the tables, you can use many-to-many to enable
this. You can do this by using the RELATIONSHIP syntax to add a link between them, that works
similarly to the WHERE clause in a SQL join clause.

 Note: Using generic relationships is not a best practice. In cases where you have two fact
tables you want to join, it is better to find a way to create a bridge table between them, so you
have a chasm trap. Look at your two fact tables to see if they share some common data that you
could use to create a dimension table between them. For example a date or product dimension
could be use to join an inventory fact table with a sales fact table. This is best done in your ETL
process, before bringing the data into ThoughtSpot.

 Note: A many-to-many implementation does not protect from over counting in some searches.
If you plan to use it, make sure your searches don’t include aggregation or count searches that will
count one value multiple times, because it satisfies the join condition for multiple rows.

This is a special kind of relationship, that applies to specific data models and use cases. For example,
suppose you have a table that shows wholesale purchases of fruits, and another table that shows retail
fruit sales made, but no inventory information. In this case, it would be of some use to see the wholesale
purchases that led to sales, but you don’t have the data to track a single apple from wholesale purchase
through to sale to a customer.
In a many-to-many relationship, the value(s) in a table can be used to join to a second table, using an
equality condition (required) and one or more range conditions (optional). These conditions act like the
WHERE clause in a SQL JOIN clause. They are applied using AND logic, such that all conditions must be
met for a row to be included.
To use a many-to-many relationship, you need to follow a few rules:
• There must be one equality condition defined between the two tables.
• Each table must be sharded on the same key that will be used for the equality condition.
• There can optionally be one or more range conditions defined.
This example shows the TQL statements that create the two fact tables and the relationship between
them.

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Constraints

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TQL> CREATE TABLE "wholesale_buys" (
"order_number" VARCHAR(255),
"date_ordered" DATE,
"expiration_date" DATE,
"supplier" VARCHAR(255),
"fruit" VARCHAR(255),
"quantity" VARCHAR(255),
"unit_price" DOUBLE
)

PARTITION BY HASH (96) KEY ("fruit");

TQL> CREATE TABLE "retail_sales" (
"date_sold" DATE,
"location" VARCHAR(255),
"vendor" VARCHAR(255),
"fruit" VARCHAR(255),
"quantity" VARCHAR(255),
"sell_price" DOUBLE
)

PARTITION BY HASH (96) KEY ("fruit");

TQL> ALTER TABLE "wholesale_buys" ADD RELATIONSHIP WITH "retai
l_sales" AS "wholesale_buys"."fruit" = "retail_sales"."fruit" a
nd ("wholesale_buys"."date_ordered" < "retail_sales"."date_sol
d" and "retail_sales"."date_sold" < "wholesale_buys"."expiratio
n_date");

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Sharding

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Sharding
Summary: Sharding partitions very large tables into smaller, faster,
more easily managed parts called data shards.
ThoughtSpot tables can be replicated or sharded. Replicated tables exist in their entirety, the complete
data set, on each node. Sharded tables consist of a single data set divided into multiple tables or shards.
The shards have identical schemas but different sets of data.

When to use sharding
By default, ThoughtSpot tables are replicated, you must explicitly shard tables. Sharding your tables
impacts the total amount of memory used by the table as well as its performance.
For example, you might shard a large table of sales data. So, you could divide a single sales table into
shards each of which contains only the data falling within a single year. These shards are then
distributed across several nodes. Requests for sales data are dispersed both by the year and the
location of the shard in the node cluster. No single table or node is overloaded, and so the performance
of a query and the system load are both improved.
To optimize ThoughtSpot performance, you should shard very large fact tables whenever possible. If you
have a large dimension table, you might choose to shard it along with the fact table it is joined with.
Sharding both the fact and dimension table is known as co-sharding.

Table sizes and sharding recommendations
Number of rows per shard

5-10 million

Maximum

10 million rows per shard

Maximum number of shards

~ 80% of CPU cores

Example
Number of rows in table

1.1 billion

CPUS in cluster

256

HASH (128)

~50% of total CPUs
8.6 million rows per shard

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Sharding

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How to shard
Sharding is a type partitioning and is sometimes called Horizontal partitioning. The term sharding is
particular to situations where data is distributed not only among tables but across nodes in a system. To
create a sharded table add the add PARTITION BY HASH ( ) clause to your CREATE TABLE
statement.

TQL> CREATE TABLE ...
...PARTITION BY HASH (96) KEY ("customer_id");

The HASH parameter determines the number of shards and the KEY parameter the sharding key. The
recommended number of shards depends upon the number of nodes in your cluster:
Number of Nodes

Number of Shards

4-12

128

13-24

256

25-36

384

37-48

512

49-60

640

61-72

768

If you omit the PARTION BY HASH statement or if the HASH parameter is 1 (one), the table is
unsharded. This also means the table physically exists in its entirety on each node.
If you want to use the primary key for sharding, specify that the table is to be partitioned by HASH on
the primary key, as in this example:

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Sharding

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TQL> CREATE TABLE "supplier" (
"s_suppkey" BIGINT,
"s_name" VARCHAR(255),
"s_address" VARCHAR(255),
"s_city" VARCHAR(255),
"s_phone" VARCHAR(255),
CONSTRAINT PRIMARY KEY ("s_suppkey")
) PARTITION BY HASH (96) KEY ("s_suppkey");

The system does not use primary keys as sharding keys by default. If you specify the PARTION BY
HASH statement with a HASH greater than 1 (one) but omit the KEY parameter ThoughtSpot shards the
table randomly. This is not recommended; avoid this by always ensuring you specify the KEY parameter
with a HASH greater than 1 (one).

How to choose a shard key
When you shard a large table, you select a shard key from the table. This key exists in every shard. You
can use any data type that is valid for use as the primary key as the shard key. Choosing a shard key
plays an important role in the number of shards and the size of any single shard.
A shard key should contain a value that has a good distribution (roughly the number of rows with each
value in that column). This value is typically part of the primary key, but it can include other columns. For
example:

CREATE TABLE "sales_fact"
("saleid" int,
"locationid" int,
"vendorid" int,
"quantity" int,
"sale_amount" double,
"fruitid" int,
CONSTRAINT
PRIMARY KEY("saleid,vendorid"))
PARTITION BY HASH(96)
KEY ("saleid");

Notice the shard key contains the saleid value that is also part of the primary key. When creating a
shard key use these guidelines.
• Include one or more values of the table’s primary key in the shard key.
This prevents scenarios where the data with the same primary key ends up in different shards
and nodes because the shard key changed.
• If you expect to join two tables that are both sharded, make sure both tables use the same
shard key.

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Sharding

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This guideline ensures better join performance. So, for example, if you have two tables and
the primary keys are:
PRIMARY KEY("saleid,vendorid") on A PRIMARY KEY("saleid,custerid") on B

You should use saleid for your shared key when you shard both table A and B.
• Choose a shard key so that the data is distributed well across the keys.
For example, suppose the table you want to shard has a primary key made up of
saleid , custid ,and locationid . If you have 10K sales but 400 locations, and 2000
customers, you would not want to use the locationid in your shard key if 5k sales were
concentrated in just 2 locations. The result would be data in fewer shards and degrade your
performance. Instead, your shard key may be custid ,and locationid .
• Choose a shard key that results in a wide variety of keys.
For example, suppose the table you want to shard has a primary key made up of
saleid , productid ,and locationid . Suppose the table has 10K sales, 40 locations, and
200 products. If the sales are evenly distributed across locations you would not want to use
the locationid in your shard key. Instead, saleid and productid would be the better
choice as it results in a wider variety of keys.
As mentioned in the previous section, it is possible to simply use the primary key as a shard key. It isn’t a
good idea to use shard keys outside of the primary key. The reason is that it, with a non-primary shard
key, it is possible to get two versions of a record if the shard key for a record changes, but the primary
key doesn’t. A second version reults because, in the absence of a unique shard key, the system create a
secondary record rather than doing a SQL MERGE ( upsert ).

Sharded dimension tables
In a typical schema, you’d have a sharded fact table with foreign keys to small dimension tables. These
small dimension tables are replicated in their entirety and distributed on every node. This works best
where dimension tables under 50MB in size.
If you have a large dimension table, replicating it and distributing it can impact the performance of your
ThoughtSpot System. In this case, you want to shard the dimension tables and distribute it the same
way as the fact table it joins to.
When sharding both a fact and its dimension table (known as co-sharding) keep in mind the guidance for
creating a shard key. Only shard dimension tables if the dimension table is large (over 50MB) and the join
between the fact and dimension tables use the same columns. Specifically, the tables must:
• be related by a primary key and foreign key
• be sharded on the same primary key/foreign key
• have the same number of regions (or shards)
If these requirements are met, ThoughtSpot automatically co-shards the tables for you. Co-sharded
tables are always joined on the sharding key. Data skew can develop if a very large proportion of the
rows have the same sharding key.
This example shows the CREATE TABLE statements that meet the criteria for sharding both a fact table
and its dimension table:

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Sharding

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TQL> CREATE TABLE products_dim (
"id" int,
"prod_name" varchar(30),
"prod_desc" varchar(100),
PRIMARY KEY ("id")
)
PARTITION BY HASH (96) KEY ("id")
;
TQL> CREATE TABLE retail_fact (
"trans_id" int,
"product_id" int,
"amount" double,
FOREIGN KEY ("product_id") REFERENCES products_dim ("id")
)
PARTITION BY HASH (96) KEY ("product_id")
;

If a dimension table is joined to multiple fact tables, all of the fact tables must be sharded in the same
way as the dimension table. Self-joins are not supported.

Joining two sharded fact tables
You can also join two sharded fact tables with different shard keys, this is known as non co-sharded
tables. It may take a while to join two tables sharded on different keys since a lot of data redistribution is
required. Therefore, ThoughtSpot recommends that you use a common shard key for two fact tables.
You are not limited by the column connection or relationship type.

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Chasm traps

February 06, 2019

Chasm traps
Summary: A chasm trap occurs when two many-to-one joins
converge on a single table.
In a complex schema, you may have a fact table with no relationship to another fact table, except that
each contains a foreign key to a shared dimension table. This is known as a chasm trap, and
ThoughtSpot can handle it!

Understand how chasm traps occur
A fact table, just as it sounds, stores facts about your business. If you are selling apples, the sales fact
table has facts about these apples.
SaleID

AppleTypeID

StoreID

Units Sold

Dimension tables describe the attributes that are interesting to analyze. For example, the apple table
might look like this.
AppleTypeID

Color

Name

Use

Red

Red Delicious

Snack

Green

Granny Smith

Cooking

Yellow

Golden

Snack

As you can imagine, in a business you might have several fact tables that access dimension tables. So,
an apple business may record waste as well as sales.
TimeID

AppleTypeID

StoreID

Units Wasted

Both the sales and waste tables are facts that reference the apple dimension table.

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A chasm trap in a data schema can introduce problems of over counting if you join the two fact tables
through their shared dimension table. This diagram shows a typical complex schema with several tables
that are related over a chasm trap:

Examples of use cases where a chasm trap could occur when attribution analysis compare campaign
data with purchase data, where all they have in common is that both contain a customer identifier that is
a foreign key to a customer dimension table. Chasm traps also occur, for example, in cost of sales
analysis when wholesale orders data is only related to the retail sales data through a shared products
dimension table.
In many databases, joining tables across a chasm trap creates a Cartesian product or cross join. That is
each row from the first fact table is joined to each row from the second table. A Cartesian product
causes over counting when computing counts and aggregates. ThoughtSpot protects you from this kind
of over counting.
There are still just a few things to look out for when using a schema that contains chasm traps:
• The tables should be joined to the dimension table via an equi-join (i.e. a primary key/foreign
key relationship). They cannot be joined using a range of values.
• Review the column setting called Attribution Dimension. You may need to change this setting
if some of the columns in the shared dimension table should not be used for attribution when
combining fact tables.
• Tables that will be joined across a chasm trap do not need to be co-sharded. They will be
joined appropriately automatically in the most efficient way.

Chasm trap limitations
Join information in What am I Looking At? does not appear for searches on a worksheet containing a
chasm trap or on base tables that are related over a chasm trap.

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Overview of schema building

February 06, 2019

Overview of schema building
Summary: Before you can load data into ThoughtSpot, you must build
a database schema to receive it.
You can build a schema by writing a SQL script that creates the objects in your schema. ThoughtSpot
provides the ThoughtSpot SQL Command Line (TQL) for creating, viewing, and managing a schema
using SQL. Your script can use any statements that are supported in ThoughtSpot SQL Command Line
(TQL). The TQL syntax is similar to the SQL used in other relational databases, but with some important
differences.
You’ll use DDL (data definition language) to create the schema into which you’ll load the data. You’ll
probably want to put all your DDL statements into a text file, which you’ll use as a script for creating the
schema.

Upload the script through the browser
You can upload an your SQL script directly through the browser in the ThoughtSpot application. You can
edit the script or add to it right within the browser, too. The steps to build a schema through the browser
are:
1. Write a SQL script to create the schema
2. Import a schema (use the SQL editor)

Use TQL on the SQL command line
You can choose to run your SQL script within the Linux shell instead. You can run TQL in interactive
command line mode, or you can write a script and use TQL to run it. The SQL syntax in ThoughtSpot is
called TQL for ThoughtSpot SQL. The ThoughtSpot SQL Command Line (TQL) runs in an interactive
mode. To invoke TQL Log in to the Linux shell using SSH and type tql . At the prompt, type h or
help to see a list of supported commands.
The steps to build a schema using TQL include:
1. Connect to the database with the ThoughtSpot SQL Command Line (TQL).
2. Write a SQL script to create the schema.
3. Type your SQL commands on the command line, terminating each command with a
semicolon (;).
Commands can span multiple lines. ThoughtSpot supports a limited number of SQL
commands, plus some custom SQL extensions. For example, you can specify the number of
shards and the distribution key as part of the CREATE TABLE syntax. A full list of supported
SQL in TQL is available in the TQL reference.

Where to go next
• Connect with TCL and create a schema
Having examined the structure of the data to be loaded and become familiar with the
ThoughtSpot SQL Command Line (TQL), you are now ready to create the schema.
• Write a SQL script to create the schema

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Using a SQL script to create your schema is a recommended best practice. This makes it
easier to adjust the schema definitions and recreate the schema quickly, if needed.
• Schema creation examples
These examples demonstrate the steps involved in creating a schema using the ThoughtSpot
SQL Command Line (TQL). After the schema is created, you can load data into it with
ThoughtSpot Loader.
• Upload and run a SQL script)
You can run a SQL script to create your database schema through the browser, without
having to log in to the shell on the ThoughtSpot instance. You can edit the script and run it
directly in the browser to create the schema.

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Connect with TCL and create a schema

February 06, 2019

Connect with TCL and create a schema
To perform administrative tasks directly in the database, you will use the ThoughtSpot SQL Command
Line (TQL). TQL supports many, but not all, common SQL commands.

Connect with TQL
Before connecting with TQL, you will need:
• Access to your ThoughtSpot instance Linux shell from a client machine.
• The administrator OS login.
To connect to TQL:
1. Log in to the Linux shell using SSH.
2. Invoke TQL:

$ tql
TQL>

3. Enter your SQL command, followed by a semicolon ( ; ).

Enter a SQL script
Having examined the structure of the data to be loaded and become familiar with the ThoughtSpot SQL
Command Line (TQL), you are now ready to create the schema.
This method is a good way to get familiar with TQL and how to create database objects, but when
creating a schema in a production system, you will most likely Write a SQL script to create the schema.
To create the schema directly in TQL:
1. Connect to the database with the ThoughtSpot SQL Command Line (TQL).
2. If the database you will be using does not exist, create it now:

TQL> CREATE DATABASE my_database;

3. Connect to the database:

TQL> USE my_database;

4. If you wish to use a schema other than the default one, create it now:

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Connect with TCL and create a schema

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TQL> CREATE SCHEMA my_schema;

5. Issue a CREATE TABLE command for each table you will create, using the information in Plan
the schema.

 Tip: Foreign key declaration within a CREATE TABLE will show the table created even
if there are problems with the foreign key. Therefore, it is good practice to also issue a
separate ALTER TABLE ADD CONSTRAINT FOREIGN KEY command.

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How to write a SQL script

February 06, 2019

How to write a SQL script
Summary: Using a SQL script to create your schema is a
recommended best practice. This makes it easier to adjust the
schema definitions and recreate the schema quickly, if needed.
The schema creation script is a text file that contains all the SQL commands to create your schema.
Comments should be enclosed in the comment tags /* and */.
Enclose all object names (schema, table, and column) in double quotes and any column values in single
quotes in your scripts. Object names that are also reserved words in SQL, or that contain special
characters (any character other than alphanumeric or _ ), must be surrounded by double quotes. If you
see the error message “Error parsing SQL. Check SQL input.”, you should check for object names
without double quotes in your script.
If you are working in a schema other than the default schema, object names must be fully qualified, as in
""."" .
If your schema includes constraints to define relationships between tables (foreign key, or the
RELATIONSHIP syntax), it is recommended that your script first creates all the tables, and then at the
end, creates the relationships between them using the ADD CONSTRAINT syntax. This makes it easier to
troubleshoot the script and make changes.
If TQL is run using the flag --allow_unsafe , your statements will always execute without this warning.
Note that when running TQL from a script, you will need to decide what behavior you want if the script
contains changes that affect dependent objects. If you want the script to run even if objects with
dependencies are affected, run it using this flag, for example:

cat safest_script_ever.sql | tql --allow_unsafe

1. Open a new file in a text editor.
2. Type in the command to create the database, if it does not already exist:

CREATE database ;

3. Type in the command to specify the database to use:

USE database ;

4. Type in the command to create the schema, if you don’t want to use the default schema:
5. Type in each of the CREATE TABLE statements, with its column definitions, primary key
constraints, and sharding specification (if any).
6. At the end of your script, optionally type in the ALTER TABLE statements to add foreign keys
to use in joining the tables.
7. Save the file.

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8. Run the script using one of these methods:
• Import a schema (use the SQL editor).
• Log in to the shell, copy your script to your ThoughtSpot instance using scp, and
pipe it to TQL:

$ cat create-schema.sql | tql

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Schema creation examples

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Schema creation examples
Summary: Simple examples that illustrate how to use the TQL and the
ThoughtSpot Loader.
These examples demonstrate the steps involved in creating a schema using the ThoughtSpot SQL
Command Line (TQL). After the schema is created, you can load data into it with ThoughtSpot Loader.

Simple schema creation example
The example creates a database ( tpch ) with two tables ( customer , transaction ). The example
does not create a schema explicitly. So it will use the default schema (falcon_default_schema).
In this example:
• The table customer has a primary key called customer_id. The table
customer_transactions has a primary key called transaction_id.
• The customer table is unsharded.
• The customer_transactions table is sharded into 96 shards using the transaction_id
column.
• Both tables have referential integrity on customer_id .

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$tql

TQL> CREATE DATABASE tpch;

TQL> USE tpch;

TQL> CREATE TABLE customer (
name

VARCHAR(100),

address VARCHAR(255),
zipcode INT,
customer_id INT,
CONSTRAINT PRIMARY KEY (customer_id)
);

TQL> CREATE TABLE customer_transactions (
transaction_id INT,
customer_id INT,
amount DOUBLE,
transaction_date DATETIME,
CONSTRAINT PRIMARY KEY (transaction_id),
CONSTRAINT FOREIGN KEY (customer_id) REFERENCES
customer(customer_id)
)

PARTITION BY HASH (96) KEY (transaction_id);

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More complex schema creation example
The example uses a custom schema called sample_schema to hold the tables. Because of this, every
table reference has to be schema qualified.

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$ tql

TQL> CREATE DATABASE "sample_db";
TQL> USE "sample_db";
TQL> CREATE SCHEMA "sample_schema";
TQL> CREATE TABLE "sample_schema"."customer" (
"c_custkey" BIGINT,
"c_name" VARCHAR(255),
"c_address" VARCHAR(255),
"c_city" VARCHAR(255),
"c_nation" VARCHAR(255),
"c_region" VARCHAR(255),
"c_phone" VARCHAR(255),
CONSTRAINT PRIMARY KEY ("c_custkey")
);
TQL> CREATE TABLE "sample_schema"."supplier" (
"s_suppkey" BIGINT,
"s_name" VARCHAR(255),
"s_address" VARCHAR(255),
"s_city" VARCHAR(255),
"s_nation" VARCHAR(255),
"s_region" VARCHAR(255),
"s_phone" VARCHAR(255),

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CONSTRAINT PRIMARY KEY ("s_suppkey")
);
TQL> CREATE TABLE "sample_schema"."lineorder" (
"lo_orderkey" BIGINT,
"lo_linenumber" BIGINT,
"lo_custkey" BIGINT,
"lo_partkey" BIGINT,
"lo_suppkey" BIGINT,
"lo_orderdate" DATE,
"lo_orderpriority" VARCHAR(255),
"lo_shippriority" VARCHAR(255),
"lo_quantify" BIGINT,
"lo_extendprice" BIGINT,
"lo_ordtotalprice" BIGINT,
"lo_discount" BIGINT,
"lo_commitdate" DATE,
CONSTRAINT PRIMARY KEY ("lo_orderkey","lo_linenumber"),
CONSTRAINT FOREIGN KEY ("lo_custkey") REFERENCES "sample_sche
ma"."customer" ("c_custkey"),
CONSTRAINT FOREIGN KEY ("lo_suppkey") REFERENCES "sample_sche
ma"."supplier" ("s_suppkey")
)

PARTITION BY HASH (96) KEY (lo_orderkey);

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Upload and run a SQL script

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Upload and run a SQL script
Summary: Importing a schema through the Web browser makes it
possible to run your SQL script without needing to have a Linux login.
You can run a SQL script to create your database schema through the browser, without having to log in
to the shell on the ThoughtSpot instance. You can edit the script and run it directly in the browser to
create the schema. You can use this capability in any of these ways:
• Create the SQL script ahead of time, and use the browser to run it.
• Use the editor to type your SQL directly into the browser.
• Use the browser SQL interface as an interactive SQL editor, for example to test an existing
script or make changes to an existing schema.
1. Log into ThoughtSpot from a browser.
2. Click Data
Data, on the top navigation bar.
3. Click the ellipses icon (3 dots)

, and select Upload schema
schema.

4. Drag and drop your SQL file into the browser, or choose Browse Your Files to locate it.
5. You’re now in the SQL editor. Use it to view your script and make any changes.

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6. When ready, run your script by clicking the Execute button.
7. If there are any errors, correct them and run the script again.

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How to change a schema

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How to change a schema
Summary: After you've created a schema and loaded data, you may
find yourself wishing you'd set things up a little differently. You can
make changes to the schema, such as changing the primary key,
relationships to other tables, and sharding.
Making changes to a schema after data has been loaded and users have created worksheets or
pinboards on the tables requires care, so that you don’t lose the relationship between the objects
created in ThoughtSpot and the underlying tables. If you follow the procedures here, your tables will
retain their relationships to the objects created on top of them.

 Tip: Always take a snapshot of your database before making any schema changes. This
snapshot allows you to revert back to the prior state if you make an error, or something doesn’t
work as you expected after the schema change.

Change the primary key for a table
Use this procedure to change the primary key for a table. But use it with caution, particularly if you are
changing to a primary key for which values are not unique.
You can change the primary key of a table without having to TRUNCATE it first and reload the data.
However, changing the primary key could result in data deletion. This is because of the upsert behavior
which is applied when multiple rows have the same primary key. This is very important to understand
ahead of time, if you are considering changing to a primary key for which values are not unique.
To change the primary key, first remove any existing primary key, and then define a new one (if any). You
do not need to truncate the tables to do this operation beginning in version 3.2. Any dependent objects
(pinboards or worksheets) will remain intact.
To change the primary key of a table:
1. Create a manual snapshot.
2. Connect to the database with the ThoughtSpot SQL Command Line (TQL).
3. Drop the existing primary key (if any), by issuing a command like this example:

TQL> ALTER TABLE "cart"
DROP CONSTRAINT
PRIMARY KEY;

Dropping a primary key can impact existing worksheets, answers, and pinboards. The system
warns you if dropping a primary key impacts other objects. To continue, use the -allow_unsafe flag.
4. Add a new primary key, if desired:

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TQL> ALTER TABLE "cart"
ADD CONSTRAINT
PRIMARY KEY ("owner_id");

5. Test that any dependent objects (pinboards, worksheets, etc.) are still working correctly.
6. Delete the snapshot you created earlier using the command:

tscli snapshot delete

Change a relationship between tables
Use this procedure to remove a relationship between tables or define a new one. This operation works
for both kinds of relationships: foreign key or generic relationship.
To change a relationship between two tables, first remove any existing relationship, and then define the
new relationship (if any). You do not need to truncate the tables to do this operation. Any dependent
objects (pinboards or worksheets) will remain intact.
To change the relationship between tables:
1. Create a manual snapshot.
2. Connect to the database with the ThoughtSpot SQL Command Line (TQL).
3. Issue the command to drop the existing relationship
Before dropping a relationship TQL checks for and then warns of any dependent objects. To
continue with the drop any way, use the --allow_unsafe flag. The following examples
illustrate several different types of drop operations.
Drop a foreign key by name, if it was given a name when it was defined:

TQL> ALTER TABLE
"sales_fact"
DROP CONSTRAINT
"FK_PO_number";

Drop a relationship by name, if it was given a name when it was defined:

TQL> ALTER TABLE "fruit_dim"
DROP RELATIONSHIP "REL_dates";

Drop the foreign key relationship explicitly, if it doesn’t have a name, by referencing the two
tables that are joined. This drops all foreign keys between the two tables:

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TQL> ALTER TABLE "shipments"
DROP CONSTRAINT
FOREIGN KEY "orders";

Drop all generic relationships between two tables:

TQL> ALTER TABLE "wholesale_buys"
DROP RELATIONSHIP
WITH "retail_sales";

4. Define a new relationship, if you want to, using ALTER TABLE...ADD CONSTRAINT...
5. Test that any dependent objects (pinboards, worksheets, etc.) are still working correctly.
6. Delete the snapshot you created earlier using the command:

tscli snapshot delete

Change sharding on a table
You can change the sharding on a table or remove it altogether (creating a replicated table) using this
procedure. This procedure preserves the data within the table.
This procedure reshards a table. This is also called redistributing or repartitioning. You can use this
method to reshard a table without losing its data or metadata. This means that worksheets and
pinboards built on top of the table will continue to work.
You can use these steps to do any of these operations:
• shard a table that was previously replicated.
• change a replicated table to a sharded table.
• change the number of shards to use for a sharded table.
To change the sharding on a table:
1. Create a manual snapshot.
2. Connect to the database with the ThoughtSpot SQL Command Line (TQL).
3. Issue the command to change the sharding using this syntax:

TQL> ALTER TABLE
[SET DIMENSION | SET FACT
[PARTITION BY HASH
[()]
[KEY()]]]

For example:

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• To make a sharded table into a dimension table (replicated on every node), use:

ALTER TABLE "products"
SET DIMENSION;

• To make a dimension table into a sharded (fact) table or change the number of
shards, use:

ALTER TABLE "sales"
SET FACT PARTITION BY HASH (96)
KEY ("productID");

4. Test that any dependent objects (pinboards, worksheets, etc.) are still working correctly.
5. Delete the snapshot you created earlier using the command:

tscli snapshot delete

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Convert column data type

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Convert column data type
Summary: You can convert the data in a column from one data type
to another by issuing a TQL command.
There are some details you should be aware of when doing a data type conversion.

Data type conversion behavior
When converting from one data type to another, any values that can not be converted will be set to
NULL. If errors occur during data type conversion, the operation is aborted. However, you may choose
to force the conversion despite the errors. You can start TQL in allow_unsafe mode to continue with the
data conversion, at your own risk, of course! To start TQL in unsafe mode, issue this command:

tql --allow_unsafe

Multiple columns of a single table can be converted using a single TQL command. The behavior is
transactional. So for example, you would issue a command like this example:

ALTER TABLE products
MODIFY COLUMN product_id int,
MODIFY COLUMN supplier VARCHAR(4);

Also note that changing data type has implications on the primary key and sharding enforcement. For
example, changing the data type of a column that is part of the sharding key would lead to a
redistribution of data. Then imagine that the sharding key column contained the text values 00100 ,
0100 , and 100 , which all map to same integer value. If this type of a column is changed from a
VARCHAR to an INT , then it would be subject to the upsert behavior on primary keys. So, in this
example, only one of the three rows would be preserved.
Be aware that data type conversion will preserve the data in the underlying database table, but there is
no guarantee that any objects built on top of it (worksheets or pinboards) will be preserved. This is
because you might make a data type change that makes a chart built on top of the table invalid (for
example a growth chart would be invalidated if the date column it depends on were changed to a
varchar column).

Supported data type conversions
In general, the data type conversions that make logical sense are supported. But there are a few
nuances you should be aware of:
• When you convert from INT to BOOL , zero is converted to false, and all non-zero values are
converted to true.
• When you convert from BOOL to INT , true gets converted to 1, and false gets converted to

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0.
• When you convert from DOUBLE to INT , the value gets rounded.
• When you convert from INT to DOUBLE , the value gets rounded.
• When you convert from DATETIME to DATE , the date part of value is preserved and the time
part is dropped.
• When you convert from DATE to DATETIME , the time gets added as 00:00:00 . The date
part of the value is preserved.
• When you convert from DATETIME to TIME , the time part of the value is preserved.
• Conversion from TIME to DATETIME is not supported.

Date and time conversions
Some data type conversion require a format string. These include:
• conversion from DATE / TIME / DATETIME
• conversion to DATE / TIME / DATETIME
For these types of conversions, you’ll use a special syntax using parsinghint and the date format
specifications supported in the strptime library function.
For the example, first create a table with a timestamp stored as a VARCHAR :

CREATE TABLE fruit_sales
(time_of_sale VARCHAR(32));
INSERT INTO fruit_sales
VALUES ('2015-12-29 13:52:39');

Now, convert the column from a VARCHAR to DATETIME , using the format %Y-%m-%d %H:%M:%S :

ALTER TABLE fruit_sales
MODIFY COLUMN time_of_sale DATETIME
[parsinghint="%Y-%m-%d %H:%M:%S"]

Finally, convert the column back to VARCHAR:

ALTER TABLE fruit_sales
MODIFY COLUMN time_of_sale VARCHAR(32);

String to boolean conversions
String to boolean conversions have format strings, too. You’ll use parsinghint as you do for date and
time conversions. You can choose among these approaches:

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OPTION 1: Specify string values for both true and false. Any non-matching values get converted to null.
In this example, “100” gets converted to true, and “0” gets converted to false. “-1” gets converted to
null.

ALTER TABLE db
MODIFY COLUMN s bool [parsinghint="100_0"];

OPTION 2: Specify a string value for true. Any non-matching value gets converted to false. In this
example, “100” gets converted to true, “-1” and “0” get converted to false.

ALTER TABLE db
MODIFY COLUMN s bool [parsinghint="100_"];

Option 3: Specify a string value for false. Any non-matching value get converted to true. In this example,
“-1” and “100” get converted to true, and “0” gets converted to false.

ALTER TABLE db
MODIFY COLUMN s bool [parsinghint="_0"];

String to boolean conversions
When converting from a string to a boolean, you must specify a string for true and false. By default, a
string to boolean conversion generates true for true , false for false .

ALTER TABLE db
MODIFY COLUMN b varchar(32);

But you may override the default strings that get generated by using parsinghint , as in this example:

ALTER TABLE db
MODIFY COLUMN b varchar(32) [parsinghint="tr_fa"];

Change the Data Type of a Column
When you issue the TQL command to convert a column from one data type to another, the conversion is
handled automatically. However, you’ll need to ensure that any visualizations built on top of the table
display correctly.

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You should always take a snapshot of your database before making any schema changes. This will allow
you to revert back to the prior state if you make an error, or something doesn’t work as you expected
after the schema change.
When changing a data type in an existing table, be aware that answers and pinboards created on top of
that table (or worksheets that include it) may change. This is because charts and aggregations depend
upon the data type. So for example changing from INTEGER to VARCHAR could break charts that used
the numeric data type INTEGER to calculate an average or a total. Because of this, use caution, and
check all dependent objects before and after changing the data type, to ensure that they display as
intended.
To change the data type of a column:
1. Connect to the database with the ThoughtSpot SQL Command Line (TQL).
2. Issue the command to change the data type using this syntax:

TQL> ALTER TABLE
MODIFY COLUMN ;

For example:

ALTER TABLE fact100
MODIFY COLUMN product_id int;

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Import CSV files with tsload

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Import CSV files with tsload
Summary: The tsload command is a common way to import data
from a CSV file.
Use ThoughtSpot Loader ( tsload ) to load data from a CSV text file into an existing table in
ThoughtSpot. ThoughtSpot Loader ( tsload ) is a common way to import data. When using tsload ,
you can load larger datasets and make the loading process repeatable through scripting. The tsload
command accepts flags that enable you to specify column and row separators, date or timestamp
formats, null value representations, and similar parameters. Many of these options have defaults that you
can override.
Before importing data, you need to Build the schema.
To use ThoughtSpot Loader, type the command tsload followed by the appropriate flags. You can see
the list of the flags it accepts in the ThoughtSpot Loader flag reference or by issuing tsload -help .
tsload supports both full and incremental data loads. For incremental loads, an upsert (insert or update)
is performed. If an incoming row has the same primary key as an existing row, it updates the existing row
with the new values.
You can integrate tsload into your ETL environment for more automated data loads. Most ETL tools
provide the ability to write target data into files and support scripted post-transformation actions that can
include loading data into ThoughtSpot. This procedure describes manually loading data, but the tsload
commands could be saved as a script:
1. Log in to the Linux shell using SSH.
2. Change to the directory where your CSV files are staged.
3. Use the following syntax to invoke tsload , specifying the appropriate flags and your data
source file:

$ tsload --target_database=my_database
--target_table=my_table --alsologtostderr
--empty_target --source_file=my_file.csv --v 1
--field_separator="separator_char"

This example imports the CSV file ssbm_customer.csv into the table CUSTOMER:

$ tsload --target_database=SAMPLE_DB
--target_table=CUSTOMER --alsologtostderr
--empty_target --source_file=ssbm_customer.csv
--v 1 --field_separator "|"

4. Once the processing begins, you’ll see messages to indicate the progress and then two
summary messages after the load is complete.

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Started processing data row
Source has 32 data rows, ignored row count 0
Waiting for rows to commit...(please wait)
Source summary
-------------Data source:
ssbm_customer.csv
Source data format:
csv
Header row?:
no
Tokenizer Options:
escape_char: "" fiel
d_separator: "|" enclosing_char: "\""
Date format:
%Y%m%d
Date time format:
%Y%m%d %H:%M:%S
Flexible mode?:
no
Load summary
-----------Target table:
CUSTOMER
Should empty target?:
yes
Status:
Successful
Rows total:
32
Rows successfully loaded:
30
Rows failed to load:
0
Rows duplicate/omitted:
2
% of Rows successfully loaded:
93.75 %
Load Rate (MB/s):
0.00 MB/s
Load Rate (Rows/s):
3.53 Rows/s
Start time (Wallclock):
Tue Jan 29 09:09:07
End time (Wallclock):
Tue Jan 29 09:09:08
Total load time = 1.13 seconds = 0.02 minutes = 0.00 ho
urs
Data size = 50 bytes = 0.06 KB = 0.00 MB

5. In the load summary, be sure to check the Rows duplicate/omitted number. This indicates the
number of rows (if any) that were omitted from loading because they did not satisfy the table
constraints. A common cause of this would be a duplicate primary key. If any rows were
omitted, review your CSV file, make the required adjustments, and then load it again.
6. Once your file has been loaded properly, repeat this process to load data from any additional
CSV files.

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Use a script to load data

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Use a script to load data
Summary: Learn how to load one or files in bulk with a script.
If you need to load data from multiple CSV files, create a script to automate the process. You can also
use a similar script to automate recurring data feeds.

Understand how to create a script
The data loading script is a text file that contains all the calls to tsload for loading the data from your
CSV files.
The example script shown here uses the cat command to read the data file, and pipes it to tsload .
When creating and testing your script, you may wish to replace each cat with cat -10 , to load only
the first ten lines of each file. This allows you to quickly run a test of your script. When the test succeeds
for all the data files, you can then remove each -10 , so the complete files will load when you run the
script again.
1. Log in to the Linux shell using SSH.
2. Navigate to the directory that contains your CSV files and open a new file in a text editor.
3. Type in the commands to load the data.
This example shows commands to load three files:

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cat Players.csv | tsload
--target_database baseball --target_table "players"
--empty_target --field_separator ","
--max_ignored_rows 10 --bad_records_file bad_record
s.txt
--has_header_row --alsologtostderr --null_value ""
cat AllstarFull.csv | tsload
--target_database baseball --target_table "allstarfu
ll"
--empty_target --field_separator ","
--max_ignored_rows 10 --bad_records_file bad_record
s.txt
--has_header_row --alsologtostderr --null_value ""
cat Appearances.csv | tsload
--target_database baseball --target_table "appearanc
es"
--empty_target --field_separator ","
--max_ignored_rows 10 --bad_records_file bad_record
s.txt
--has_header_row --alsologtostderr --null_value ""

4. Save the file.
5. Run the script:

$ ./load_baseball_data.sh

Loading data efficiently
If you have a very large data file that takes a long time to load, you can reduce the load time by splitting
it up into multiple files and loading them in parallel using multiple invocations of tsload . If the size of
any of your data files is greater than 50 million rows, running tsload in parallel can reduce the load
time significantly.
• Split up your large data file into multiple smaller files.
• Stage the data files in a location accessible to the node on which you’ll run the script. Usually
you’ll use an NAS mounted file system.
• Create a script to load the files (see example below).
• Run the script to load the files. You will make your script multi-threaded by invoking multiple
loader threads (between 1 and 5 are recommended).

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To optimize the load time even further, determine what the bottleneck is and adjust your process
accordingly. If the disk I/O for reading the data files is the bottleneck, you can stage the data files on
separate NAS mounted file systems and reference them accordingly in your script. If the CPU on the
machine you’re using to run the load script is the bottleneck, you can split the load script into the same
number of parts as you have nodes in your ThoughtSpot instance, place one script on each node, and
run them in parallel. Make sure the other nodes are able to access the data files where they are staged.
Running the load script on separate nodes will put the data on all the nodes, just as when you run the
script on a single node. Running the script on all the nodes at the same time just lets you take advantage
of CPU power of each node for hashing data files.
For example, suppose you have 30 days of data in 30 files, one for the data collected on each day. Each
day’s data file contains 10 million rows, for a total of 300 million rows of data. You want to load the
whole month of data. For this example we’ll have 5 loader processes, each one handling 6 days of data.
Here is a sample script you could use the load the data files in parallel:

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/* Script load_script.sh, loads 30 days of data in parallel */
#!/bin/bash
pidlist=""
cat day1.csv day2.csv day3.csv day4.csv day5.csv day6.csv | tsl
oad
--target_database sales --target_table SALES_FACT --max_ignore
d_rows 10
--bad_records_file ./SALES_FACT.bad --date_format %Y-%m-%d
--date_time_format "%Y-%m-%d %H:%M:%S" --source_data_format del
imited
--field_separator "|" --null_value "" --enclosing_character
"\""
--boolean_representation 1_0 &
pidlist="$pidlist $!" &
cat day7.csv day8.csv day9.csv day10.csv day11.csv day12.csv |
tsload
--target_database sales --target_table SALES_FACT --max_ignore
d_rows 10
--bad_records_file ./SALES_FACT.bad --date_format %Y-%m-%d
--date_time_format "%Y-%m-%d %H:%M:%S" --source_data_format del
imited
--field_separator "|" --null_value "" --enclosing_character
"\""
--boolean_representation 1_0 &
pidlist="$pidlist $!" &
cat day13.csv day14.csv day15.csv day16.csv day17.csv day18.cs
v | tsload
--target_database sales --target_table SALES_FACT --max_ignore
d_rows 10
--bad_records_file ./SALES_FACT.bad --date_format %Y-%m-%d
--date_time_format "%Y-%m-%d %H:%M:%S" --source_data_format del
imited
--field_separator "|" --null_value "" --enclosing_character
"\""
--boolean_representation 1_0 &
pidlist="$pidlist $!" &

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cat day19.csv day20.csv day21.csv day22.csv day23.csv day24.cs
v | tsload
--target_database sales --target_table SALES_FACT --max_ignore
d_rows 10
--bad_records_file ./SALES_FACT.bad --date_format %Y-%m-%d
--date_time_format "%Y-%m-%d %H:%M:%S" --source_data_format del
imited
--field_separator "|" --null_value "" --enclosing_character
"\""
--boolean_representation 1_0 &
pidlist="$pidlist $!" &
cat day25.csv day26.csv day27.csv day28.csv day29.csv day30.cs
v | tsload
--target_database sales --target_table SALES_FACT --max_ignore
d_rows 10
--bad_records_file ./SALES_FACT.bad --date_format %Y-%m-%d
--date_time_format "%Y-%m-%d %H:%M:%S" --source_data_format del
imited
--field_separator "|" --null_value "" --enclosing_character
"\""
--boolean_representation 1_0 &
pidlist="$pidlist $!" &
wait $pidlist

Call your script using a command like:

nohup bash ./load_script.sh > master_log.txt &
tail -f master_log.txt

Constructing your script in this way will execute all the commands in the background, and output to the
file master_log.txt . You’ll see a running status as the commands in the script execute. After the
script completes, you can check the log file for detailed information, such as the number of rows that
loaded successfully.

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Delete a data source

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Delete a data source
Summary: How to prepare for and delete a data source using the
ThoughtSpot application.
There are two separate ways to delete a data source, through the browser or through TQL describes the
dependency checking that occurs when deleting or changing a table using TQL. When you want to
delete a data source, you first need to handle any dependent objects that have been built on top of it.
You can easily see these dependencies, and choose how to handle them before deleting the data
source.

Check data source dependencies
You can see all of the dependencies for any data source (worksheet or table) on the Data page.
To view dependent objects for a data source:
1. Click Data on the top navigation bar.
2. Click the name of the data source whose dependencies you want to view.
3. Click Dependents
Dependents.
You will see a list of the names of the dependent objects (worksheets and pinboards), and the
columns they use from that data source. You can use this information to determine the impact
of changing the structure of the data source or to see how widely it is used.

4. Click on a dependent object to modify or delete it.
If you want to remove the dependency by modifying the dependent object, you’ll need to
remove all search terms or columns that refer back to the data source you are trying to delete.
5. When all dependencies have been removed, you will be able to go back and delete the data
source.

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Delete a data source

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Delete a data source
You can delete data sources from the browser, as long as they were not created by an administrator
through tsload or Data Connect.
You can delete data sources from the browser if they were created from the browser. These types of
data sources include:
• Data imported from the browser.
• Worksheets.
ThoughtSpot checks for dependencies whenever you try to delete a table or worksheet.
1. Click Data on the top navigation bar.
2. Check the box next to the name of the data source you want to delete.
3. Click the delete icon.

4. If you attempt to delete a data source with dependent objects, the operation will be blocked.
You will see a list of dependent objects with links.

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Delete a data source

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5. Click on a dependent object to modify or delete it.
If you want to remove the dependency by modifying the dependent object, you’ll need to
remove all search terms or columns that refer back to the data source you are trying to delete.
6. When all dependencies have been removed, you will be able to go back and delete the data
source.

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Delete or change a table in TQL

February 06, 2019

Delete or change a table in TQL
Summary: You can delete a data source in the web browser or using
ThoughtSpot SQL Command Line (TQL).
When you enter a TQL statement, the system warns you of possible dependency consequences with a
prompt asking if you’d like to proceed. This should make you feel safe issuing TQL commands, even
commands like dropping a table.
If TQL is run using the flag --allow_unsafe , your statements will always execute without this warning.
Note that when running TQL from a script, you will need to decide what behavior you want if the script
contains changes that affect dependent objects. If you want the script to run even if objects with
dependencies are affected, run it using this flag, for example:

cat safest_script_ever.sql | tql --allow_unsafe

If you do not run the script using the flag, it will fail if any of its commands might cause problems with
dependent objects.
TQL actions with possible dependency consequences include:
• Change, add, or remove a primary key.
• When changing or adding a primary key, if the key in question is not unique in the
data it may cause deletion of rows, because of upserts occurring when duplicate
primary keys are found.
• When changing or removing a primary key, incoming foreign key relationships will
be broken.
•
•
•
•
•

Change a column datatype.
Add a relationship or foreign key.
Drop a relationship or foreign key constraint.
Change or add a sharding key.
Drop a table, schema, or database.

When issuing one of the above commands, you will see a warning message similar to this:

TQL> ALTER TABLE table1
DROP CONSTRAINT PRIMARY KEY;
WARNING: This operation will break the Foreign Key relationshi
p “products”
with table “sales”, which will break 34 user-visible visualizat
ions and
2 Worksheets. We recommend taking a snapshot before performing
this operation.
Do you wish to proceed? (yes/no).

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About data modeling

February 06, 2019

About data modeling
Summary: Modeling, tagging, and adding links between your data
sources can make the data even easier to search.
Data modeling allows you to define metadata and other aspects of your data. For example, you can give
data columns search friendly names or predefine how they can be explored and aggregated. Metadata
include such information as Column Names
Names, Column Visibility
Visibility, Column and Data Definition
Definition, Column Rank
and so forth.
When you load data, ThoughtSpot has defaults for data modeling metadata. After loading data, you can
start searching your data without doing any data modeling, creating relationships, or tagging. However,
since you know your data best, you can customize the modeling settings. Putting some thought into
these will make the data even easier and more intuitive to search for your end users.

User interfaces for modeling data
Data modeling is a very lightweight process compared to what you may have experienced in other tools.
You can configure the model for an individual data table or you can view and configure all the system
data using a modeling file. Editing the data model file requires that you have administrative privileges.
The model file contains a row for each column in your data set. It isn’t unusual to have tens of thousand
of rows in this file. This means editing this file is equivalent to editing all the tables at once. When you
add new data to your system, this file expands to accommodate the new data columns you have added.
Both of these methods, have the same effect, they improve search. Moreover, while they have different
effects of scale, they use the same mechanisms to accomplish these effects.

Modeling topics
The following topics explain how to model your data:
• Change a table’s data model
Explains how to make modeling settings for a table you’ve just loaded, or to make a quick
change to existing settings.
• Edit the system-wide data model
Explains how to define a default data model to use for data system-wide.
• Data modeling settings
Explains the possible data model settings and their accepted values. These are the same for a
table or the system.
• Link tables using relationships
Linked tables can be searched together or combined into a worksheet for easy searching.
Tables that have no relationship between their columns can not be combined in a single
search.
• About stickers
You can create stickers to make it easier for people to find data sources and pinboards.

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Change a table's data model

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Change a table's data model
Summary: You can adjust the data model for a newly loaded table.
To make modeling settings for a data source you’ve just loaded, or to make a quick change to existing
settings, use the ThoughtSpot web interface. You can adjust the Columns settings from the data
management listing.
You can change all the same data model settings here as in the model file. This method is easier and
faster, unless you need to make many settings in bulk. In that case, using the model file is
recommended.

About data sources
You can change the data modeling settings for base Tables
Tables, Worksheets
Worksheets, and Views
Views. Worksheets will
inherit the data modeling settings from the tables upon which they are based. However, if you make
further changes to a base table after you’ve created worksheets on it, the new data model changes will
not propagate up. You will need to make any new data model changes directly to the worksheets (if you
want them).

Change the data model for a data source
1. Click Data on the top navigation bar.
2. Click on a data source you own or can edit.

This brings up the Columns screen, where you’ll make your modeling settings.
3. Modify one or more column settings.
Descriptions of the possible settings are listed in Data modeling settings.
4. Save your changes.

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5. To check your changes, use the SEARCH page to search for across the changed data.

Related information
• Data modeling settings
• Edit the system-wide data model
• Understand data sources

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Edit the system-wide data model

February 06, 2019

Edit the system-wide data model
Summary: Edit the modeling file to edit your data settings.
When you load data, ThoughtSpot uses defaults for data modeling metadata. You change these defaults
using the data modeling file if you have access to the ADMIN > Data Management page. This means
editing this file allows you to navigate and edit all your system’s data columns at once, in bulk. When you
(or your users) add new data to your system, this file changes as it expands to accommodate new data
columns.

 Tip: If you just want to change a subset of your data, use the Change a table’s data model
instead.

Overview of the modeling process
The data formats you use in your system are controlled by the modeling file, an Excel file. To make these
changes you download the model file, change the model, and upload your changes back into the
system.
In each row of the modeling file, all the data properties corresponding to a column from your data are
listed. You can modify many of these properties by typing in the new value. Remember these important
guidelines when editing the model file:
• Do not modify any value in a column which contains DoNotModify in the field under the
column heading.
• Make sure to keep the file in the same format as it had when you downloaded it.
The model file contains a row for each column in your data set. It isn’t unusual to have tens of thousand
of rows in this file. You can change all or a subset of rows. You can edit the file to leave the heading
rows and only those rows you want to change. This can make the file more convenient to work with.
The model file must be saved as UTF-8 encoded. If your model file includes multi-byte characters, make
sure you save it in the correct format or you won’t be able to upload it after making your changes.

Download the model file
Before you can make changes to the model file, you need to download it. Then, you edit it using
Microsoft Excel, vi/vim, or a similar text editing tool.
To obtain the model file:
1. Log in to ThoughtSpot from a browser as an Administrator user.
2. Click on the admin tab in the top navigation bar.

3. Click on Data Management
Management.
4. Click Download model.xls
model.xls.

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Edit the system-wide data model

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Edit the file and change the settings
You’ll make changes to the settings using this procedure. To see a list of the changes you can make, see
Data modeling settings. You can edit any of the values in the model file, except for those where the
words DoNotModify appear below the column header. To make changes in the model file:
1. Open the model file you downloaded ( model.xls ) in Excel, vi/vim, or a text editor.
If you are using Excel, you may see a warning message.

Click YES to proceed.
2. Find the column you want to modify.
Descriptions of the meanings of the columns are listed in Data modeling settings.
3. Select the value you want to change.
4. Type in the new value.
5. After making all your changes, save the model file.
If you are using Excel, you will see a message. Click YES to save the file.

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Edit the system-wide data model

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The model file must be saved as UTF-8 encoded. If your model file includes multi-byte
characters, edit the file using vi or vim to ensure the file is saved in the correct format.
Otherwise, you won’t be able to upload it after making your edits.

Upload the edited file
After you have made changes to the modeling file, you must upload it back to ThoughtSpot before the
changes will take effect. To upload the model file:
1. Log in to ThoughtSpot from a browser as an Administrator user.
2. Click on the Admin icon, on the top navigation bar.

3. Click on Data Management
Management.
4. Click Browse your files to upload the model.xls file, or drag and drop it in the zone.

If you receive an error message upon uploading the file, check that it does not include any
multi-byte characters (for example, Japanese or other multi-byte language characters). If it
does, you’ll need to download the file again and make your edits using vi or vim.
If you choose to remove all the rows you have not changed from the model file before
uploading it. If you upload a model file that includes only the changed rows, you won’t lose
any of the pre-existing model file settings. This is a good option if your model file is causing
an error on upload, but you aren’t sure where in the model file the problem is.
As soon as the file is uploaded, ThoughtSpot performs any necessary re-indexing for you automatically.
Your new settings will be reflected within a few minutes.

Related information
• Data modeling settings
• Change a table’s data model

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Overview of data modeling settings

February 06, 2019

Overview of data modeling settings
You can change these settings in two ways, both of which change the model. If you want to make a few
small changes, you should make them in the ThoughtSpot application . If you want to make many
changes you should edit the modeling file. Whether you are changing data modeling settings using the
modeling file or the Web interface, the settings and their accepted values are the same.

Modeling settings
This index lists the editable data modeling settings.
Setting
name

Description

Column
Name

Sets the name of the column to be used in searches.

Description

Adds a text description of what the column contains.

Data Type

Read only. Shows the column’s data type.

Column
Type

Sets the type of column, either ATTRIBUTE or MEASURE .

Additive

Controls the type of aggregations that will be available for a column.

Aggregation

Sets the default aggregation type for a column.

Hidden

Sets the visibility of a column.

Synonyms

Adds synonyms that can be used in the search bar to refer to a column.

SpotIQ
Preference

Excludes specified columns from SpotIQ analyses. By Default, all columns are included in SpotIQ.

Index Type

Sets the type of index that will be created for a column.

Geo Config

Enables a column to be used in GeoMap visualizations.

Index Priority

Changes the priority of a column in search suggestions.

Format Pattern

Specifies the format to use for numeric values or dates that show in the column.

Currency
Format

Specifies the format to use when showing the currencies in a column.

Attribution
Dimension

Only applies to tables that join over a Chasm Trap. Designates whether the tables depend on this column for attribution.

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Overview of data modeling settings

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Setting
name

Description

Entity Category

Specifies how to categorize the data in the column by entity type. By default, ENTITY TYPE is not set. Entity categories support SearchIQ so that when you type a natural question, ThoughtSpot better knows how to interpret it. For example, if you ask
“who are the top performers?” ThoughtSpot will first choose columns set with PERSON from which to return answers. If you ask “when was the movie Jurassic Park released?”, columns set to TIME will be used to answer the “when” part of the question, and so forth.

Data modeling for worksheets
For worksheets, only some of the settings can be modified, whether you are using the modeling file or
the Web interface. The editable settings for worksheets are:
• Name
• Description
• Synonyms
If you want to change any of the settings that cannot be modified in a worksheet, you need to make your
changes to the underlying table instead, and they will be reflected in all worksheets that use the table.

Related information
• Model the data for searching
• Add a geographical data setting for a column

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Set column name, description, and type

February 06, 2019

Set column name, description, and type
Summary: Modeling includes setting basic information for a data
column such as its name, description, and type.
Basic information for a data column is its NAME
NAME, DESCRIPTION
DESCRIPTION, and TYPE
TYPE. All of these can influence
how a user experiences your data. For example, the DESCRIPTION appears as a “tip” when a user
hovers over a column. So it is the means for helping users understand where the data comes from.

Change the column name
Column Name (UI)/ColumnName
ColumnName (model file) is the name that displayed to users for that column in
ThoughtSpot. The column name is what users type to add that column to their search. Change the text
that is shown for the column names in ThoughtSpot to make the names more meaningful to users.
The model file contains a row for each column in your data set. It isn’t unusual to have tens of thousand
of rows in this file. You can change all or a subset of rows. You can edit the file to leave the heading
rows and only those rows you want to change. This can make the file more convenient to work with.
The default is the name you gave the column when you defined the table in the database or imported the
CSV file from the browser.
1. Find the column name you want to change.
2. Type in the new column name.
3. Save your changes.

Change column description
Description (UI)/ColumnDescription
ColumnDescription (model file) an optional description for the corresponding column.
You can provide a description for a specific column, to provide additional information for users about the
data it contains. When a user hovers over the column, a tooltip will show this description.
To create a column description:
1.
2.
3.
4.

Find the column description you want to change.
Enter a new description.
Repeat for all columns where you want to add a description.
Save your changes.

Change column type
Column Type (UI)/ColumnType
ColumnType (model file) describes the kind of data a column stores. This is set
automatically upon defining the table, but in some cases, you may want to change the type. There are
two types of columns:
•
•

ATTRIBUTE contains a property, like name, address, or id number.
MEASURE contains a numeric value that can be compared in a meaningful way using math,
such as a count or measurement.

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When a new table is created, the default column type is set according to the Data Type (UI)/DataType
DataType
(model file) defined for each column. By default, columns with the numeric data types ( FLOAT , DOUBLE ,
INT , or BIGINT ) are assigned the type MEASURE . Columns with VARCHAR , BOOL , or date/time data
types are assigned the type ATTRIBUTE .
Usually the default setting for column type works fine. But occasionally you’ll need to change a
MEASURE to an ATTRIBUTE . Examples of numeric values for which mathematical operations are not
meaningful include:
•
•
•
•
•

ID numbers
Key values that are primarily used for joining tables
Product number or SKU
Sports team member jersey number
Year, when separate from a date (e.g. 1999, 2000)

To change the column type:
1. Find the column type you want to change.
2. Change it to either MEASURE or ATTRIBUTE .
3. Save your changes.

Related information
• Model the data for searching
• Hide column or define a column synonym

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Set ADDITIVE or AGGREGATION

February 06, 2019

Set ADDITIVE or AGGREGATION
Summary: You can allow aggregate on MEASURE columns and some
ATTRIBUTE columns.
Aggregation is grouping many units or parts into a new value. In data, aggregation gathers multiple input
values and calculates an summary value from them. You then use this aggregated value to do an
analysis.
Every summary value results from a data aggregation function. An example aggregation function would
be average or minimum. You can control how aggregation works in your data.

Making an ATTRIBUTE column ADDITIVE
Your data may contain a column with a numeric data type that you have defined as an ATTRIBUTE
rather than a MEASURE . For example, you may have ATTRIBUTE column with an INTEGER data type
that represents age. Typically, these columns have an ADDITIVE setting of NO . Within a search result
that contains data from this column, the options for each column on the left side of the screen includes:
• UNIQUE COUNT OF
• TOTAL COUNT OF

To display extended aggregate view options, you must set ADDITIVE to YES on these ATTRIBUTE
columns. This option is only possible on columns that have a numeric data type ( FLOAT , DOUBLE or
INTEGER ) or a date data type ( DATE , DATETIME , TIMESTAMP , or TIME ). After you make this change,
these additional view options area-charts offered:
•
•
•
•
•
•
•
•

TOTAL OF
AVG OF
STD DEVIATION OF
VARIANCE OF
TOTAL COUNT OF
UNIQUE COUNT OF
MIN OF
MAX OF

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Set ADDITIVE or AGGREGATION

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To change this setting:
1. Find the column whose ADDITIVE setting you want to change
2. Select the ADDITIVE toggle.
3. Change the value to one of these:
• YES or NO , if using the Web interface.
• TRUE or FALSE , if using the model file.
4. Save your changes.

Change Aggregation
Both MEASURE columns and ATTRIBUTE columns support AGGREGATION operations. To aggregate a
column without having to enter the aggregation type explicitly in your searches every time, you can set a
default Aggregation for that column. Setting this default can make combining data more intuitive and
faster.
ATTRIBUTE columns have AGGREGATION
AGGREGATION(UI)/AggregationType
AggregationType (model file) values with default
aggregate type of NONE
NONE. You can change AGGREGATION to one of the supported aggregation types.
To extend the available aggregation actions, set ADDITIVE on these columns to YES ( TRUE ).

Aggregate type

Description

NONE

Does no aggregation. This is the default for ATTRIBUTE type columns.

SUM

Adds the values together and returns the total. This is the default for MEASURE
type columns.

AVERAGE

Calculates the average of all the values.

MIN

Calculates the minimum value.

MAX

Calculates the maximum value.

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Set ADDITIVE or AGGREGATION

Aggregate type

Description

STD_DEVIATION

Calculates the standard deviation of all the values.

VARIANCE

Calculates the variance of all the values.

COUNT

Calculates the total number of values.

COUNT_DISTINCT

Calculates the total number of distinct values.

February 06, 2019

Keep in mind that not all MEASURE data should be aggregated. Consider a table containing data about
athletes on a sports team. The data contains some numerical values, including points scored, salaries,
and jersey numbers for each of the players. Because jersey number is an INTEGER, it would become a
column of type MEASURE (not ATTRIBUTE ). So it will aggregate, by default. But you may want to make
its aggregation type NONE instead. This ensures that search results that include jersey number will not
attempt to compare or aggregate those values in a way that is not meaningful.
To set this value.
1.
2.
3.
4.

Find the column whose default aggregation type you want to change
Select its Aggregation
Aggregation. If using the modeling file, use the AggregationType setting.
Select the new default aggregation type.
Save your changes.

Related information
Model the data for searching

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Hide a column or define a synonym

February 06, 2019

Hide a column or define a synonym
Summary: Hide a column from users or make it easier to find by
assigning a synonym.
You can hide columns from users in ThoughtSpot without dropping them from the database. It is
common to hide a column when its data contains identifier columns that are used to join tables, but
which do not have any meaning to users.
Alternatively, rather than hiding a column, you can make it easier to find by creating synonyms for it. This
is helpful, for example, when different departments refer to the data using different terminology.

Hide a column
As the number of columns in the dataset increases, the search experience requires more effort. Users
have to navigate through larger numbers of columns to choose the correct one. There might also be
some columns in the dataset that you don’t want to expose to the users.
Change the HIDDEN (UI)/Hide
Hide (model file) setting to hide a column. By default, all columns in a data
source ware shown in ThoughtSpot. To hide these columns, set the HIDDEN setting to YES .
1. Find the HIDDEN (UI)/Hide
Hide (model file) setting for a column.
2. Set its value to YES .
3. Save your changes.

Create synonyms for a column
When users search a data source, they might try typing different words to try to retrieve a particular
column. This could be due to different groups in your organization using different terms for the same
data. Or maybe your users just intuitively use different words when searching for that item. Using
synonyms allows them to access the data even if the term they choose isn’t the same as the actual
column name.
You can set column synonyms for columns in tables, user imported data, and worksheets. The returned
table or chart uses the actual column name, but the search bar reflects the term the user typed in (the
synonym).
To create a column description:
1. Find the column for which you want to add synonyms.
2. Select its Synonyms
Synonyms.
3. Type in a comma separated list of the synonyms you want to add.
If a synonym is more than one word, it must be enclosed in double quotes. If you are using
the Web interface, you would type:

profit,"gross profit"

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If you are using the model file, the list of synonyms must be enclosed in square brackets. For
example:

[profit, "gross profit"]

4. Save your changes.

Related information
Model the data for searching

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Set columns to exclude from SpotIQ analyses

February 06, 2019

Set columns to exclude from SpotIQ
analyses
Summary: You can specify columns to exclude from SpotIQ analyses.
SpotIQ is a ThoughtSpot feature that provides users with insights about their data by automatically
surfacing interesting characteristics (trends, correlations, outliers, and so on).
If you have access to tables, worksheets, and views for data modeling purposes, you can specify
columns to exclude from SpotIQ analyses. By default, all columns are included in SpotIQ analyses.

Exclude columns from SpotIQ analyses
To specify columns to exclude from SpotIQ analyses:
1. Click Data in the top menu, and choose Tables
Tables, Worksheets
Worksheets, or Views
Views.
2. Click on the name of your data source.
3. On the Columns tab, find the COLUMN NAMES you want to exclude from SpotIQ analyses,
and scroll to the right to find SPOTIQ PREFERENCE .
4. Use the drop-down menu to set the SPOTIQ PREFERENCE to EXCLUDE for each column you
want to exclude.
5. Click SAVE CHANGES in the upper right.

Include columns in SpotIQ analyses
By default, all columns are included in SpotIQ analyses.
If you have previously set some columns to EXCLUDE and you want to re-set these to be included, do
the following.
1. Click Data in the top menu, and choose Tables
Tables, Worksheets
Worksheets, or Views
Views.
2. Click on the name of your data source.
3. On the Columns tab, find the COLUMN NAMES you want to set back to include in SpotIQ
analyses, and scroll to the right to find SPOTIQ PREFERENCE .
4. Use the drop-down menu to set the SPOTIQ PREFERENCE to DEFAULT for each column you
want to include.
5. Click SAVE CHANGES in the upper right.

Related information
• SpotIQ tutorial
• Overview of data modeling settings

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Manage suggestion indexing

February 06, 2019

Manage suggestion indexing
Summary: ThoughtSpot dynamically indexes Search bar suggestions
for column names and values.
When a user searches in the Search bar, ThoughtSpot supplies the user with suggestions for column
names and their column values. The COLUMN NAME and any SYNONYMS appear in Search
suggestions. A column’s INDEX TYPE controls whether and how ThoughtSpot suggests column values.
Additionally, ThoughtSpot uses a column’s INDEX PRIORITY value to determine where to rank a
column’s name and values in the search suggestions. These values impact the dynamically calculated
usage based ranking (UBR),

Example of Search suggestion behavior
The example below illustrates how searching for promotion_last_name t causes the system to
suggest several ways of completing the t in the search:

The system is suggesting the synonym type (callout A) for a column in the Promotion table. It is also
suggesting a value of theil (callout B) for the Promotion_Last Name column. If you look in the Data
> Tables page, you’ll see there is a type synonym for the Promotion_Type column which is using
default indexing.

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Manage suggestion indexing

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Managing search suggestions through INDEX TYPE and INDEX PRIORITY is important. Properly
configured suggestions can decrease “noise” in the suggestion list. Increasing the visibility of important
columns is helpful for new or intermittent ThoughtSpot users.

Understand the default indexing behavior
ThoughtSpot has a system default INDEX TYPE behavior for search suggestions. This system default is
configured on your cluster and applies to all worksheets and tables. You can override this default
behavior on a per-column basis.
The system behavior when the INDEX TYPE is DEFAULT is as follows:
• With two exceptions, the system indexes all columns using their COLUMN NAME value. The
exceptions are columns with COLUMN TYPE of MEASURE and columns with DATA TYPE of
DATE .
• Columns that contain data values with large amount of free-form strings, that is, a length is
greater than 50 words, are indexed as PREFIX_ONLY by default.

 Warning: If a column has a very large free text values, ThoughtSpot recommends
you keep DEFAULT or set DONT_INDEX. Other settings indexing on these values may
generate confusing suggestions.

• Short strings (like a firstname column) are indexed using PREFIX_AND_SUBSTRING by
default, which indexes both prefix and substrings.
• If a column is using has a cardinality – the number of unique column values – greater than 10
million, it is not indexed.
If a column’s INDEX TYPE is not DEFAULT and the column’s cardinality is greater than 30 million,
ThoughtSpot does not index the column.

High cardinality and performance
A column’s cardinality can impact indexing. If you have a column with a very high cardinality and a very
high number of rows, indexing these values can impact your ThoughtSpot performance. ThoughtSpot
Support recommends you turn off indexing of primary key columns on extremely large tables (> 10
million rows) in your cluster.

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High cardinality is relative to other considerations. In some cases, columns with fewer than 10 million
rows but with columns containing long strings can cause performance problems with memory. If you
have concerns or questions, your ThoughtSpot Customer Success Engineer can help you determine
appropriate cardinality thresholds for your ThoughtSpot installation.

Configure your own cluster defaults
If you need to, you can work with ThoughtSpot Support or your Customer Success Engineer to configure
new cluster defaults.

Override the system default on a column
You can change a column’s INDEX TYPE in the Data > Tables > Columns page or in the Index value in
the modeling file.
The values you can set for INDEX TYPE are:
Index type

Description

DEFAULT

The default behavior applies to all ATTRIBUTE columns that are
not DATE types. PREFIX_AND_SUBSTRING for short values and
PREFIX_ONLY for long values and free-form text.

DONT_INDEX

Prevents indexing on the column values. The column doesn’t appear in search suggestions.

PREFIX_AND_SUBSTRING

Allows full indexing such that prefix and sub-string search both
work for the column values.

PREFIX_AND_WORD_SUBSTRING

Allows indexing such that only prefix search works for each word
of a multi-word string, for the column values.

PREFIX_ONLY

Allows indexing such that only prefix search works for the column
values.

Consider a column in which there are four values ThoughtSpot , Thought , Spot and Thought
Spot . If you search for sp , depending on the setting for indexing, the column value search result
suggestions will vary:
Index field value
DEFAULT
DONT_INDEX

Search bar suggestions
ThoughtSpot , Spot and Thought Spot

No suggestions.

PREFIX_AND_SUBSTRING

ThoughtSpot , Spot and Thought Spot

PREFIX_ONLY

Spot

PREFIX_AND_WORD_SUBSTRING

Spot and Thought Spot

To change a value in the application UI:

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1.
2.
3.
4.

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Open a worksheet or table from the Data page.
Find the column whose index type you want to modify.
Set its INDEX TYPE
TYPE.
Save your changes.

If you are using the model file, locate the Index cell, and enter the INDEX TYPE you want to use.

Change a column’s suggestion priority
A column’s INDEX PRIORITY determines the order or rank in which it and its values appear in the search
dropdown.

By default, the INDEX PRIORITY value is set to 1 for all columns. You can push a column up in the
order (increase the rank) by increasing its INDEX PRIORITY value. A higher value (like 2 ) will cause the
corresponding column and its values to appear higher up in the search dropdown than columns with
lower value (like 1 ).

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You should only use numbers between 1-10 in the INDEX PRIORITY field.Use a value between 8-10 for
important columns to improve their search ranking. Use 1-3 for low priority columns.
To change a value in the application UI:
1.
2.
3.
4.

Open a worksheet or table from the Data page.
Find the column whose index type you want to modify.
Change the INDEX PRIORITY to a number between 1 and 10.
Save your changes.

If you are using the model file, locate the Index cell, and enter the priority you want to use.

Related information
• Model the data for searching
• Usage based rankings (UBR).

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Add a geographical data setting
Certain attribute columns that contain location data can be used to create GeoMaps. ThoughtSpot
supports Latitude, Longitude, Zip Code, US States, US Counties, Countries, and select international
sub-nation regions.
You can designate a column as Geo by editing the GEO CONFIG column in the table Columns page.
You cannot edit the geo configuration column information in the model.xls file.

Guidelines for geographic columns
Columns that can be designated as Geo columns need to contain text ( VARCHAR ) data unless they
contain latitude/longitude data. Latitude and longitude columns can contain numeric data ( DOUBLE ) or
text.
If you are using a column with the data type DOUBLE for latitude and longitude, you will also need to
change the following settings for those columns:
• set Column Type to ATTRIBUTE
• set Additive to NO
• set Aggregation Type to NONE
For information these settings, see Set ADDITIVE or AGGREGATION.

How to edit geographic columns
1. Find the GEO CONFIG for the column that contains the geographical data.
2. Select the column to display the Specify Geographic Configuration dialog.

3. Change the value to the appropriate GEO CONFIG
CONFIG, depending on the kind of geo data the
column contains.
If your data includes latitude and/or longitude columns that are stored as a numeric data type
( DOUBLE ), make these changes for those columns:
a. Change the Type to ATTRIBUTE .
b. Change ADDITIVE to NO / FALSE .

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4. Save your changes.

List of geotypes
GeoType

Description

Type: Example

COUNTRY_REGION

Countries

• name: United States
• long name: United States
• name_sort: United States
of America
• abbreviation: U.S.A.
• adm0_a3: USA
• adm0_a3_is: USA
• adm0_a3_us: USA
• admin: United States of
America
• brk_a3: USA
• brk_name: United States
• formal_en: United States of
America
• iso_a2: US
• iso_a3: USA
• iso_n3: 840

COUNTY

Counties in the United States

• santa clara county
• pike county, ohio
• pike county, OH

STATE_PROVINCE

States in the United States

• name: California
• US Postal Service abbreviation: CA

LATITUDE

Must be used with LONGITUDE

• 37.421023
• 1.282911

LONGITUDE

Must be used with LATITUDE

• −122.142103
• 103.848865

ZIP_CODE

Zip codes and zip codes +4 in the
United States

• po_name: MT MEADOWS
AREA
• ZIP: "00012"
• zip2: 12

Administrative regions found in countries other than the United States

• bremen
• normandy
• west midlands

Other Sub-nation
Regions

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Related information
Model the data for searching

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Set number, date, and currency formats
Summary: Explains how to set key formats for column values.
You can set number, date, and currency display formats. These formats define how these value types
display in tables and charts.

Number formats
You can set a format for how numbers are displayed in tables and charts. For example, you can display
numbers with a different number of digits after the decimal point, based on the data modeling setting
Format Pattern
Pattern. You can use any of the supported number formats for delimiters and number of digits to
show using Java Decimal Notation. Currency symbols are not supported.
The system has default values which are:
#,###

For integer data types INT and BIGINT . As you can see, these can only contain
numbers, alpha characters are not permitted.

#,###.00

for decimal data types DOUBLE and FLOAT .

These are some examples of formats you can use:
Stored Value

Format Pattern

Display Value

12345.6789

#,##0.##

12,345.68

12345.6789

#,##0.###

12,345.679

12345.6789

#,##0.00000

12,345.68

12345.6789

#,##0

12,345

12345.6789

#,##0.00

12,345.68

12345

#,##0.##

12,345

12345

#,##0.00

12,345.00

You can change the date format used to display a column’s values for a single table or, by editing the
data model, for the entire ThoughtSpot instance. Editing the data model file requires that you have
administrative privileges.
1. Decide if the change is for a table or the entire instance.
2. Find the Format Pattern for the column.
This is either a column in a single table or a column in the data modeling file.

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3. In the column, enter the format you want to use.
4. Save your changes.
If you are using a data-modeling file you’ll need to upload the new file to your installation.

Profile-based number formatting
Number formatting is set by default based on your ThoughtSpot profile’s Preferred locale setting. You
can set this value to accommodate your geographic locations.

For example, if you are using ThoughtSpot in the US, the number formatting should look like this:
xxx,xxx.xx . And in Europe, it should look like this: xxx.xxx,xx .

Date formats
Format Pattern (UI)/ Format Pattern (model file) formats for how dates are displayed in tables and charts.
For example, you can display dates in a standard European or US format based on the data modeling
setting Format Pattern
Pattern. These are some examples of formats you can use:
Format mask

Description

YYYY or yyyy

four digit year such as 2017

YY or yy

last two digits of year such as 17

month with no leading zero 1 - 12

Two digit month 01 - 12

MMM

Three letter month such as Jan

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Format mask

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Description

Day of year without a leading zero 0 - 365

Day of year with up to one leading zero 01 - 365

DDD

Day of year with up to two leading zeroes 001 - 365

Day of month with no leading zero 1 - 31

Two digit day of month 01 - 31

Two digit 24 hour representation of hour 00 - 23

Two digit 12 hour representation of hour 01 - 12

24 hour representation of hour with no leading zero 0 - 23

12 hour representation of hour with no leading zero 1 - 12

Minutes 00 - 59

Minutes with no leading zero 0 - 59

Seconds 00 - 59

Seconds with no leading zero 0 - 59

AM/PM indicator

Valid delimiters include most non-alphabet characters. This includes but is not limited to:
•
•
•
•
•
•
•

\ (forward slash)
/ (backward slash)
| (pipe symbol)
: (colon)
- (dash)
_ (underscore)
= (equal sign)

Examples of valid format masks you can produce for display are as follows:
•
•
•
•
•

MM/dd/yyyy
MMM
DD/MM/yyyy
MM/dd/yyyy HH:mm
DD/MM/yyyy HH:mm

To change the date format used to display a column’s values for a single table or, by editing the data
model, for the entire ThoughtSpot instance.
1. Decide if the change is for a table or the entire instance.
2. Find the Format Pattern for the column.
This is either a column in a single table or a column in the data modeling file.

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3. In the column, enter the format you want to use.
4. Save your changes.
If you are using a data-modeling file you’ll need to upload the new file to your installation.

Set currency format
You can set a format for how currencies are displayed in tables and charts when using the ThoughtSpot
Data API or embedding. For example, you can display currencies in a standard European Euro or US
Dollar format based on the data modeling setting Currency Type
Type.
You can change the currency format used to display a column’s values for a single table. When you
specify the currency type of your data in the Columns settings, your currency data will only display the
correct format and currency code in the embedded use case. Currency specific symbols are available in
the non-embedded use case as well, but they are not localized.
All users are treated as if they are in en-US locale unless they are in embed mode and their browser
configuration tells ThoughtSpot that they are in some other locale. For example, 100 Polish Zloty
appears as 100zł to a user in Poland, but without localization enabled, it appears as PLN 100 .
This subtle difference can be seen when you use the REST API. See the ThoughtSpot Application
Integration Guide for more information on the API.
1. Find the Currency Type for the column whose display format you want to change.
2. Click on it to open the Specify Currency Type menu.

3. Select one of the following ways you would like to change the format.
Option

Description

Infer
From
Browser

Your currency data will be modeled upon the locale of your browser setting.

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Option

Description

From a
column

Your currency data will be modeled upon the existing currency information in
the selected column This option is disabled if there is no VARCHAR column to
choose from.

Specify
ISO
Code

Your currency data will be modeled upon your selection from the available currency code choices.

4. Click Ok to save your changes.

Related information
Model the data for searching

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Change the Attribution Dimension

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Change the Attribution Dimension
Summary: The **Attribution Dimension** setting applies only to tables
that are related through a chasm trap. If your schema does not
include these, you can ignore this setting.
The Attribution Dimension setting only applies to tables that join over a Chasm Trap. By default, the
attribution dimension setting will be set to YES , but you can override that by setting the column’s
attribution dimension property to NO , as described here.

Understand chasm traps and attribute
dimension
In the classic chasm trap, two fact tables are related through a shared dimension table. When the two
fact tables are joined, the shared column(s) in the dimension table are used to attribute rows in one fact
table to match with rows in the other fact table.
Usually, all goes well using this method. But sometimes an incorrect or illogical attribution can result.
This can happen because the column chosen is not meaningful for performing this attribution. If you are
seeing unexpected results in searches that include tables across a chasm trap, this setting is for you.
Below is an example of a column that is not an attribution dimension. Suppose you have two fact tables,
Wholesale Purchases and Retail Sales, that share a common dimension Date.

In this example, the date column in the Date dimension should not be used for attribution, since
unrelated rows in both of the fact tables could share the same row in the Date table. Why? Because if
Sally bought oranges wholesale on April 25, 2005 and made a retail sale of apples on the same day,
there is no logical relationship between those two events. Combining the two events using the date they
share will not create any meaningful information.
If matching rows in two fact tables over a chasm trap depends on the values in a column contained in a
dimension table, that column is known as an attribution dimension.

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In this example, the Product ID column in the Products dimension table is an attribution dimension. For
rows where the Product ID in the Wholesale Purchases and in the Retail Sales tables is a match, those
rows are logically related in a meaningful way. They can be combined in charts and reports to produce a
logical, expected outcome.

How to set attribute dimension
You cannot configure this setting in the model file. You can only configure it on a table-by-table basis. To
designate a column as not being an attribution dimension (i.e. not producing any meaningful attribution
across a chasm trap):
1.
2.
3.
4.

Find the column that is not an attribution dimension.
Select its Attribution Dimension
Dimension.
Set the value to NO . If you’re using the modeling file, set it to FALSE
FALSE.
Save your changes.

Related information
Model the data for searching

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Set entity categories for SearchIQ

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Set entity categories for SearchIQ
Summary: You can specify a per column entity category to help
SearchIQ.
SearchIQ is a search experience that allows you to ask more natural questions, similar to the way you
might talk to a person.
If you have access to tables and worksheets for data modeling purposes, you can specify columns entity
types for different columns in your data sources which support the SearchIQ user experience.

About Entity Categories
Category

Description

PERSON

Contains data that represents a person, relevant to questions about “who?”

PLACE

Contains data that represents a location, relevant to questions about “where?”

TIME

Contains data that represents a date or time, relevant to questions about
“when?”

PRODUCT

Contains data that represents a product

ZIP_CODE

Contains zip code data, relevant to questions like “where?” or “what zip code?”

LAT_LONG

Contains data that represents geographical positioning, relevant to questions like
“where?”

COMPANY_ORG

Contains data that represents a company or organization

NUM_TYPES

Contains numerical data

Set Entity Categories
To specify entity categories:
1. Click Data in the top menu, and choose Tables or Worksheets
Worksheets.
2. Click on the name of your table or worksheet.
3. On the Columns tab, find the COLUMN NAMES for which you want to specify entity
categories, and scroll to the right to find ENTITY CATEGORY .
4. Use the drop-down menu to set the ENTITY CATEGORY to the type you want.
5. Click SAVE CHANGES in the upper right.

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Related information
• SearchIQ
• Overview of data modeling settings

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Link tables using relationships

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Link tables using relationships
You can link tables by creating relationships between their columns. Linked tables can be searched
together or combined into a worksheet for easy searching. Tables that have no relationship between
their columns can not be combined in a single search.
There are two ways to create relationships between tables:
1. Create a constraint using TQL.
2. Create a relationship through the web interface.
The two methods create the same kind of relationship both from an end user perspective and an
administrative perspective. When creating a relationship between two tables, the columns that form the
link must be the exact same data type. For example, a column of type INT32 to another INT32
column.
Both types of relationships exist within the database. You can also generate a script through TQL that
contains all relationships, whether create via the web interface or in TQL.
Relationships created through either method can be managed either via TQL or by going to the
Relationships page when viewing data in the Date Modeling section in the ThoughtSpot application. You
can view, modify, or delete relationships in either place.
You may create relationships using a mixture of TQL and the web interface, but the relationships you
create cannot form a circular relationship, or “cycle”. If you attempt to create a relationship that would
complete a cycle, you will see a message saying that the relationship could not be added because it
conflicts with another existing relationship.

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Join a table or view to another data source

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Join a table or view to another data
source
Summary: Learn how to define joins between a table or view and
another table, view, or worksheet
Joining a table or view to another table, view, or worksheet creates a relationship that allows them to be
searched together. Choose a column to join on that both tables contain (e.g. employee ID or product
key). This process creates a generic join between the table or view and the other table, view, or
worksheet on the column you specify.
If you want to create a primary key/foreign key relationship, you need to use TQL rather than the web
interface.
You must have either the Can administrator ThoughtSpot or the Can manage data privilege to create a
join relationship. If you’re not an administrator, you also need edit permissions on the table, view, or
worksheet.
When creating a join between the columns in two data sources, the columns being linked must have the
same data type, with the same meaning. That is, they must represent the same data. Normally, you’ll
make this kind of link from a fact table column to a column in a dimension table that uniquely identifies a
logical entity in your data such as Employee ID for a person, Product ID for a product, or Date Key for a
specific date in a date lookup table.
To create a relationship through the Web interface:
1. To find your table or view, click Data in the top menu, and choose Tables or Views
Views.
2. Click on the name of your table or view.
3. Click Schema
Schema. You will see the list showing existing joins.
4. Click the + Add Join button on the upper right side of the screen.

5. Use the Map source to destination dialog to choose the destination table, view, or worksheet
you want to join to.

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6. Choose the columns you want to join on from the table or view (source) and destination table,
view, or worksheet. Click Next
Next.

7. Give your join a name and description and click ADD JOIN
JOIN.
8. Repeat these steps until all the joins you want to make have been created.
After creating the join, you may change its name and description by clicking the edit icon. If you want to
change the data source or column being joined, you’ll need to delete the join and create a new one.

Related Information
• Constraints

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Delete a relationship

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Delete a relationship
Summary: You can delete relationship (link) between tables through
the application or TQL.
You must have either the Can administrator ThoughtSpot or the Can manage data privilege to delete a
relationship. If you’re not an administrator, you also need edit permissions on the table, view, or
worksheet.
If you created a relationship (join or link) between tables using the Web interface, you can also delete it
from the Web interface. But if the relationship was created using TQL, you must also use TQL to delete
it.
To delete a relationship using TQL, use an ALTER TABLE...DROP CONSTRAINT... or ALTER
TABLE...DROP RELATIONSHIP... statement.
To delete a relationship from the Web interface:
1. Click Data on the top navigation bar.
2. Click on the name of the data source you from which you want to remove the relationship.
3. Click Schema
Schema. You will see the list showing existing joins.
If this is a worksheet, you will need to click on Joins within worksheets and choose Joins
between worksheets
worksheets.

4. Find the relationship you want to delete, and click the Delete icon
icon.

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5. Repeat these steps until all the joins you want to remove have been deleted.

Related Information
• Constraints

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About stickers

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About stickers
Summary: Stickers enable you to create categories for classification
of objects, including pinboards, answers, data sources, and
worksheets.
You can create stickers to make it easier for people to find data sources and pinboards. Stickers are
global in scope. This means that everyone can see the stickers and use them to tag objects. They can
also filter lists of objects by sticker. Stickers are often used to designate subject areas, such as sales,
HR, and finance, but you can use them any way you like.
Keep in mind these permissions when working with stickers:
• Only administrators can create stickers.
• Anyone can apply a sticker.
• Anyone can filter by a sticker.

Create a sticker
Only administrator users can create stickers. Anyone can apply the stickers you create, or use them as
filters when selecting from a list of sources or pinboards.
To create a sticker:
1. Navigate to the Manage Data or Pinboards screen using the icons in the top navigation bar.
2. Choose the currently selected sticker, scroll to the bottom of the list, and click + Add
Add.

3. Type the name for the new sticker.
4. You can change the name of a sticker by clicking the edit icon next to its name.

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5. You can change the color of a sticker by clicking the color circle next to its name.

Apply a sticker
Only administrators create stickers, but anyone with edit privileges can tag an object with a sticker.
To tag an object with a sticker:
1. From the top menu, choose Answers, Pinboards, or Data.

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2. Find the item(s) you want to tag in the list, and check the box next to its name.
3. Click the apply sticker icon and choose one from the list. You can apply as many stickers as
you like to an object.

Filter by stickers
Whenever you are selecting objects from a list, you can filter by sticker to find what you’re looking for.
Anyone can use stickers to filter lists of pinboards or data sources. You can also filter by sticker when
selecting data sources.
To filter by sticker:
1. From the top menu, choose Answers
Answers, Pinboards
Pinboards, or Data
Data.

2. Click Select sticker
sticker, and select the name of the sticker you want to filter by.

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Simplify search with worksheets

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Simplify search with worksheets
Summary: Worksheets are flat tables created by joining columns from
a set of one or more tables or imported datasets.
After modeling the data, create worksheets to make searching easier. For example, a sales executive
might need to search for information about retail sales. The required data could be contained in several
tables (sales, customers, products, stores, etc.), with foreign key relationships between them. An
administrator who is familiar with the data model can create a retail sales worksheet, that combines all of
the related fact and dimension tables into a single, easy-to-use view, and share it with the sales
executive. This provides access to the data without requiring an understanding of how it is structured.

Guidelines for worksheets
Users are often unfamiliar with tables and how they are related to one another. A worksheet groups
multiple related tables together in a logical way. You might use a worksheet for these reasons:
•
•
•
•
•
•

To pre-join multiple tables together.
To give a user or group access to only part of the underlying data.
To include a derived column using a formula.
To rename columns to make the data easier to search.
To build in a specific filter or aggregation.
To give users a filtered set of data to search.

Typically, you create one worksheet for each set of fact and dimension tables. For example, you may
have a sales fact table and an inventory fact table. Each of these fact tables shares common dimensions
like date, region, and store. In this scenario, you would create two worksheets: sales and inventory. The
following diagram depicts the workflow for creating the sales worksheet.

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The process for creating a worksheet is:
1. Decide which tables to use for the worksheet.
2. Create a new worksheet.
3. Add sources (tables) to the worksheet.
4. Choose the worksheet join rule.
5. Select the columns to include.
6. Optionally modify the join types within the worksheet.
7. Optionally create formulas.
8. Optionally create worksheet filters.
9. Save the worksheet.
10. Share the worksheet with groups or users.

Create a worksheet
Create a worksheet to make the data easy for users to search. This process includes adding a new
worksheet, after which you will choose the data sources to include in it.
To create a new worksheet:
1. Click on Data
Data, on the top navigation bar.

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2. Click the the ellipses icon (3 dots)

February 06, 2019

, and select Create worksheet
worksheet.

Add sources and columns to a worksheet
After creating a worksheet, you need to add the sources that contain the data. Sources is another name
for tables. The sources you choose are typically related to one another by foreign keys.
To add the sources to the worksheet:
1. Click on the + icon
icon.

2. Check the box next to each of the sources you want to include in the worksheet.

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Note that the list of sources only shows the data sources on which you have view or edit
privileges.

3. If you want to see what the data inside the sources looks like, click Explore all data
data.
4. Choose the worksheet join rule.
5. If you want to disable Row Level Security, for this worksheet, check the checkbox to disable
it.
6. Click CLOSE to save your changes.
7. Expand the table names under Columns to select the columns to add to the worksheet.
a. To add all of the columns from a table, click on the table name and click + Add
Columns
Columns.
b. To add a single column, double click on its name.
c. To add multiple columns, Ctl+click on each column you want to add and click +
Add Columns
Columns.
Note that once you add a column, non-related tables (i.e. those without a primary/foreign key
relationship) become hidden. If you are working with two tables that should be related, but are
not, you can add a relationship between them.
8. Optionally modify the join types within the worksheet.
9. Optionally create formulas.
10. Optionally create worksheet filters.8. Click on the worksheet title to name it, and then Save it.
11. Click on each column name to give it a more user-friendly name for searching. You can tab
through the list of columns to rename them quickly.
12. If you want to add a prefix to the name of several columns, select them, click the Add Prefix
button, and type in the prefix.

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Simplify search with worksheets

13. Click the the ellipses icon (3 dots)

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, and select Save
Save.

14. Share your worksheet, if you want other people to be able to use it.

Where to go next
• How the worksheet join rule works
Use the worksheet join rule to specify when to apply joins when a search is done on a
worksheet. You can either apply joins progressively, as each search term is added
(recommended), or apply all joins to every search.

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Edit or rename worksheet

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Edit or rename worksheet
Summary: A worksheet can be edited by anyone with the proper
permissions.
If you created a worksheet, or you have edit permissions on it, you can make changes such as adding
sources and columns, adding or editing formulas, changing relationships, and changing column names.
You can also rename a worksheet or change its description.

Edit a worksheet
To edit a worksheet:
1. Click on Data on the top navigation bar.
2. Click on the name of the worksheet you want to edit.
3. Click the Edit button in the upper right hand side of the screen.
4. Make your changes to the worksheet.
5. Click the the ellipses icon (3 dots)

, and select Save
Save.

Rename a worksheet or table
You can change a worksheet or table name from the ThoughtSpot application.
To change the name of a worksheet or table:
1. Click on Data
Data, on the top navigation bar.
2. Find the worksheet or table you want to rename and click on its name.
3. Click the current name, and enter a new name.

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Edit or rename worksheet

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Related information
• Change the join rule for a worksheet
• Add joins between a worksheet and other data
• Modify table joins within a worksheet

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Create a formula in a worksheet

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Create a formula in a worksheet
Summary: You can define formulas and use them to create derived
columns in worksheets.
You create formulas by combining standard functions and operators, column names, and constant
values.
Anyone who can create a worksheet can add a formula to it. Formulas are not reusable; the formula you
create is associated only with the worksheet it belongs to. A complete list of available formulas and
examples of each is available in the Formula function reference.
You can create a formula in a worksheet by using the Formula Builder. When you do this, the result of
the formula gets added to the worksheet as a column. Use these steps to create a formula:
1. Create a new worksheet, or edit an existing one.
2. Click the + button next to Formulas
Formulas.

d
3. Type your formula in the Formula Builder.

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Note: Formulas elements are color coded by type and can include the formula operators and
functions (blue), the names of columns (purple), and/or constants (black).
4. If you want to change what your formula returns, use the Advanced settings
settings.
Depending on your formula, you may be able to change:
• Data type
• ATTRIBUTE or MEASURE
• Aggregation type

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5. You can see a list of formula operators with examples by clicking on Formula Assistant.

6. Name the formula by clicking on its title and typing the new name. Click Save
Save.

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Add a filter to a worksheet

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Add a filter to a worksheet
Summary: You can add a filters to a worksheet to limit the data users
can access from the worksheet.
Beginning in ThoughtSpot version 5.0, you can add filters to a worksheet to limit the data it contains.
This is useful when you have underlying tables that store more data than is necessary for the types of
analyses the worksheet is intended for. You can also use worksheet filters to provide data security, when
you want different groups of users to be able to see different data without relying on row level security.
To add a filter to a worksheet:
1. Click Data in the top menu bar, find your worksheet, and click on its name.
2. Click the Edit Worksheet button.

3. Click Filters on the left menu and click +.

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Add a filter to a worksheet

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4. Choose the column you want to filter on.

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Add a filter to a worksheet

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5. Select the values to include in your answer.

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Add a filter to a worksheet

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6. If you want to exclude values, click Exclude and choose values to exclude.

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Add a filter to a worksheet

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7. Click ADD FILTER
FILTER.
If there are too many values, you can use the filter search bar to find the ones you want.

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How the worksheet join rule works

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How the worksheet join rule works
Use the worksheet join rule to specify when to apply joins when a search is done on a worksheet. You
can either apply joins progressively, as each search term is added (recommended), or apply all joins to
every search.

Understand progressive joins
Often, a worksheet includes several dimension tables and a fact table. With progressive joins, if your
search only includes terms from the fact table, you’ll see all of the rows that satisfy your search. But as
you add terms from dimension tables, the total number of rows shown may be reduced, as the joins to
each dimension table are applied. It works like this:
• If you choose Apply joins progressively (recommended for most cases)
cases), joins are only applied
for tables whose columns are included in the search.
• If you choose Apply all joins
joins, all possible joins are applied, regardless of which tables are
included in the search.
When using Apply joins progressively
progressively, the number of rows in a search using the worksheet depends on
which tables are part of the search. The worksheet acts like a materialized view. This means that it
contains the results of a defined query in the form of a table. So if a particular dimension table is left out
of the search, its joins are not applied.

Rule-Based Row Level Security (RLS) with
worksheets
With Rule-Based RLS, you need to protect every table that contains any sensitive data. To do this, you’ll
grant access by creating explicit row level security rules on each of the underlying tables which contain
data that row level security should apply to.
When creating the row level security rules for a table that’s part of a worksheet, you aren’t limited to
referencing only the columns in that table. You can specify columns from other tables in the worksheet
as well, as long as the tables are joined to the table you’re creating the rule on. Then, when creating a
worksheet on top of them, the behavior is consistent regardless of the worksheet join rule you choose.
Users will never be able to see data they should not, regardless of what their search contains.
Imagine you have a worksheet that contains a Sales fact table, and Customer and Product
dimensions that are joined on Customer SSN and Product Code columns. In order to secure the
Sales table, you can use Customer Name from the Customer column to create a row level security
rule.

How joins are applied with chasm traps
When working with worksheets and row level security, you need to understand how joins are applied.
This is particularly important with chasm trap schemas. For chasm trap schemas, if row level security is
only set on one of the tables, people could see data they should not see if the scope of their search does
not include that table. (this protects them from having people see the wrong things if they have chasm
trap).

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For chasm trap worksheets, progressive and non-progressive joins do not apply. There is an entirely
different methodology for how worksheet joins on a chasm trap schema work with row level security. So
you can safely ignore that setting.

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Change the join rule or RLS setting for a worksheet

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Change the join rule or RLS setting for a
worksheet
Summary: As long as you have permissions to edit a worksheet, you
can always go into it and set a different join or RLS rule.
If you find that the charts and tables built on a worksheet contain a large number of null values (which
display as {blank} in the web browser), you can fix this by changing the internal joins for the
worksheet.
If you have the Can administer ThoughtSpot privilege or the Can manage data plus edit privilege on a
worksheet, you can edit the worksheet and change its RLS or other key settings.

Change/configure a worksheet
Before working through this procedure, make sure you are familiar with how the following affect data:
• internal worksheet joins
• worksheet join rule
• row level security (RLS)
To configure these values for a worksheet:
1. Click on Data on the top navigation bar and then on Worksheets
Worksheets.
2. Click on the name of the worksheet you want to edit from the list.
3. Click the Edit Worksheet button in the upper right hand side of the screen.
4. Click on the + icon next to Sources
Sources.
5. Scroll to the bottom of the page.
6. Configure the worksheet join rule and RLS setting as needed.

7. Click CLOSE
CLOSE.

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Change the join rule or RLS setting for a worksheet

8. Click the the ellipses icon (3 dots)

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, and select Save
Save.

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Join a worksheet to another data source

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Join a worksheet to another data source
Summary: Learn how to define joins between a worksheet and a
table, view, or other worksheet
Joining a worksheet to a table, view, or another worksheet creates a relationship that allows them to be
searched together. Choose a column to join on that both data sources contain (e.g. employee ID or
product key). This process creates a generic join between the worksheet and the other table, view, or
worksheet on the column you specify.
You must have either the Can administer ThoughtSpot privilege or the Can manage data privilege to
create a join relationship. If you’re not an administrator, you also need edit permissions on the table,
view, or worksheet.
When creating a join between the columns in two data sources, the columns being linked must have the
same data type, with the same meaning. That is, they must represent the same data.
To create a relationship through the Web interface:
1. To find your worksheet, click Data in the top menu, and choose Worksheets
Worksheets.
2. Click on the name of your worksheet.
3. Click Schema
Schema. You will see the list showing existing joins within the worksheet.
4. To view the joins between the worksheet and other data sources, click on Joins within
worksheets and choose Joins between worksheets
worksheets.

5. Click the + Add Join button on the upper right side of the screen.

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6. Use the Map source to destination dialog to choose the destination table, view, or worksheet
you want to join to.

7. Choose the columns you want to join on from the worksheet (source) and destination data
source. Click Next
Next.

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8. Give your join a name and description and click ADD JOIN
JOIN.
9. Repeat these steps until all the joins you want to make have been created.
After creating the join, you may change its name and description by clicking the edit icon. If you want to
change the data source or column being joined, you’ll need to delete the join and create a new one.

Related Information
• Constraints

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Modify joins within a worksheet
Summary: Learn how to change the join type between the tables
within a worksheet
When you create a worksheet, you select a join rule. The join rule works together with the joins defined
within the worksheet determine how the tables that make up the worksheet are joined, and how those
joins behave when searching on the worksheet.
Beginning in ThoughtSpot version 5.0, you aren’t limited to just one join rule for the entire worksheet.
You can define different types of joins for each join between tables in a worksheet. Be default, each of
these individual table joins uses an inner join. But you can override this at the individual join level.
You must have either the Can administer ThoughtSpot privilege or the Can manage data privilege to
modify joins within worksheets.
To modify the join types within a worksheet:
1. To find your worksheet, click Data in the top menu, and choose Worksheets
Worksheets.
2. Click on the name of your worksheet.
3. Click Schema
Schema. You will see the list showing existing joins within the worksheet. The joins
shown here include all the joins between the underlying tables, whether created using TQL or
in the browser.
If you don’t see the joins within the worksheet, make sure Joins within worksheets is chosen.

4. Find the join you want to modify and click the Edit icon. Note that the fact table is always the
left table, and it is shown on the left side.

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5. Select the join type to use for this relationship in the worksheet and click Save
Save.

Now these two tables will be joined using the type you selected, in the context of this worksheet.

Related Information
• Join rule
• Create joins using TQL
• Create join relationships in the browser

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Delete a worksheet or table

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Delete a worksheet or table
Summary: When you try to delete a worksheet or table, you'll see a
message listing any dependent objects that must be removed first.
ThoughtSpot checks for dependencies whenever you try to remove a table or worksheet. A list of
dependent objects is shown, and you can click on them to delete them or remove the dependency. Then
you’ll be able to remove the table or worksheet.
To delete a worksheet or table:
1. Click on Data
Data, on the top navigation bar.
2. Find the worksheet or table you want to remove in the list, and check the box next to its
name.
3. Click the Delete icon.

If you are attempting to delete a data source with dependent objects, the operation will be
blocked. You will see a warning, with a list of dependent objects with links.
4. Click on the link for an object to modify or delete it.
When all its dependencies are removed, you will be able to delete the data source.

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Delete a worksheet or table

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5. You can also click on the name of a worksheet or table and then click Dependents
Dependents, to see a
list of dependent objects with links.
The Dependents list shows the names of the dependent objects (worksheets and pinboards),
and the columns they use from that source. You can use this information to determine the
impact of changing the structure of the data source or to see how widely used it is. Click on a
dependent object to modify or delete it.

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Delete a worksheet or table

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Understand groups and privileges

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Understand groups and privileges
Summary: Creating groups and assigning users to them makes
privilege management easier.
Before people can log in and use ThoughtSpot, you need to create a username, a password, and a
membership in one or more groups for them.
This page describes manual creation of users, groups, and privileges, but you can also manage users
through LDAP or SAML. For information on setting up SAML authentication, see the ThoughtSpot
Application Integration Guide.

Privileges and groups
Privileges determine what kinds of actions users are allowed to do. You assign privileges to groups.
Then, you create users and assign them to groups. This is how you grant users access to different
capabilities in ThoughtSpot.
Each group includes a set of privileges for its users. The privileges a group has determine the actions
that its members are allowed to do. If a user belongs to more than one group, they will have the highest
level of the privileges from all the groups they belong to. Plan your groups so that you can use them to
assign a common set of privileges to multiple users. Good planning will pay off in ease of administration
and a better search experience.
There is a default group called All
All, which includes every user in ThoughtSpot. When you create a new
user, they will be added to the All group automatically. You cannot delete the All group or remove
members from it.
You can also have a hierarchy of groups. That is, groups can belong to (that is, be children of) other
groups. When using group hierarchies, permissions are inherited from the parent group. So if you’re a
member of a sub-group, you would automatically have the privileges of the parent group.

List of privileges
Here are the different privileges, and the capabilities they enable:
Privilege

Description

Can administer
ThoughtSpot

Can manage Users and Groups and has view and edit access to all data.
Users with this privilege can also download a saved answer.

Can upload user data

Can upload their own data from the application's Data page using Actions
> Upload data
data.

Can download data

Can download data from search results and pinboards.

Can share with all
users

Can see the names of and share with users outside of the groups the user
belongs to. Members of groups with this privilege can also share with
groups marked as NOT SHAREABLE
SHAREABLE.

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Privilege

Description

Can manage data

Can create a worksheet. Can also create an aggregated worksheet from
the results of a search by selecting Save as worksheet
worksheet. Can also use
ThoughtSpot Data Connect, if it is enabled on your cluster.

Can use experimental
features

Can access trial and experimental features that ThoughtSpot makes available to early adopters.

Can invoke Custom R
Analysis

Can access R scripts to further explore search answers. Includes options
to invoke R scripts on visualizations, create and share custom scripts, and
share the results of R analysis as answers and pinboards.

Can schedule pinboards

Can create pinboard schedules and edit their own scheduled jobs.

Can administer and
bypass RLS

Users in groups with this privilege (directly or via group inheritance):
• Are exempt from row-level security (RLS) rules.
• Can add/edit/delete existing RLS rules.
• Can check or uncheck Bypass RLS on a worksheet.
Your installation configuration may enable or disable the availability of this
privilege. By default, it is enabled. Administrators or groups with the privilege Can administer ThoughtSpot can grant this privilege.

Typically, the ALL group has a common set of privileges applies such as the Can upload user data and/
or Can download data privileges.
Privileges are additive, meaning that if a user belongs to more than one group, they will have the highest
level of privileges from among the groups they are a member of. They are also inherited from the parent,
so that a sub-group gets all the same privileges of its parent, all the way up the group hierarchy.
If you add the privilege Has administration privileges to a group, note that all users in that group will be
able to see all the data in ThoughtSpot. Administrators can see all data sources, and Row level security
does not apply to them.
Permissions to see and edit tables, worksheets, and pinboards are set when you share them with users
and groups, as described in the topic Data security.

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The following table shows the intersection of user privilege and ability:

Can Administer
and Bypass RLS

Can Auto-Analyze
(SpotIQ privilege)

Can share with all
users

Can manage data

Can download data

Can upload user
data

Can administer
ThoughtSpot

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Understand groups and privileges

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With edit permission.

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Understand groups and privileges

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Related information
• Add a group and set security privileges
• Add a user

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Create, edit, or delete a group

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Create, edit, or delete a group
Summary: Good planning when creating groups and assigning
privileges will pay off in ease of administration and a better search
experience.
Before adding users, create the groups they will belong to. Each group includes a set of privileges for its
users.

Create a group
To create a group and add privileges for the group:
1. Log into ThoughtSpot from a browser.
2. Click on the Admin icon, on the top navigation bar.

3. In the Admin panel, click on User Management and Groups
Groups.

4. Click the + Add Group button on the upper right hand side of the list of groups.

5. Enter the details for the new group:

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Field

Description

Group name

Enter a unique name for the group.

Display name

Name of the group as it appears in ThoughtSpot.

Sharing
visibility

Indicate whether objects can be shared with this group. When set to
SHAREABLE
SHAREABLE, this group is an option in the Share dialog.

Description

Optionally enter a description.

Privileges

Check the privileges you want to grant to the group. If you add the privilege Has administration privileges to a group, all users in that group can
see all the data in ThoughtSpot. Administrators can always see all data
sources, and Row level security does not apply to them.

6. Click the Manage Groups tab if you want to add sub-groups.
Find the groups you want to add in the list, or search for them by name. Check the box next
to each group you want to add to the group.
7. Click the Manage Users tab if you want to add users.
Find the users you want to add in the list, or search for them by name. Check the box next to
each user you want to add to the group.
8. Click Add to create the group.

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Edit a group or delete a group
After adding a group, you can always go in and edit its settings to add or revoke privileges. The new
settings will apply to all the group members. When editing a group, keep in mind that only sub-groups
appear in a group:

The No Groups in Group only indicates there are no children in this group’s hierarchy. There may be a
parent. This group inherits all the privileges of any parent group it may have. Keep this in mind when
adding users.
To edit or delete an existing group:
1. Log into ThoughtSpot from a browser.
2. Click on the Admin icon, on the top navigation bar.
3. In the Admin panel, click on User Management and Groups
Groups.

4. Find the group you want to edit in the list and click its name, or the edit icon

If you don’t see the name of the group, try searching for it. You can also delete a group from
this page by clicking the Delete icon. Deleting a group does not delete its users.
5. Make your changes and click Update
Update.

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List the group members
The system shows you the first 15 users in your group. To identify if other users are present, you must
search for the specific user name.
1. Click Admin from the top navigation bar.
The system displays the Admin panel.
2. Select User Management
Management.
3. Click on a group to edit it.
The system displays the Edit group dialog.

4. Choose Manage Users
Users.
The first 100 users which are in the group are listed. The group could maintain more, you have
to search for a specific user to find others.

Add multiple users to a group
You can add multiple users to a group using one button. To add multiple users to a group:
1. Log into ThoughtSpot from a browser.
2. Click on the Admin icon, on the top navigation bar.
3. In the Admin panel, click on User Management and Users
Users.

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4. Select the users you would like to add to the same group from the list.
5. Click the Add Users to Groups button on the top of the list of users.

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Add, edit, or delete a user

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Add, edit, or delete a user
You will create a user account for each unique person who will access ThoughtSpot, either manually or
through LDAP. If a user has access through LDAP, that user’s information is managed via your LDAP
installation. If you create a user manually in ThoughtSpot, you manage that user in ThoughtSpot.
You can edit manually created users through the interface. If a manually-created user forgets their
password, you can reset it by editing the user. If you have forgotten the admin password, please call
ThoughtSpot Support.

Create a user through the interface
This procedure shows how to creating a user manually. When you create a user, you can assign group
memberships. The group’s privileges and permissions apply to all of its members. Any user you create
will be added to the group All automatically.
1. Log into ThoughtSpot from a browser.
2. Click on the Admin icon, on the top navigation bar.

3. In the Admin panel, click on User Management and Users
Users.

4. Click the + Add User button on the upper right hand side of the list of groups.

5. Enter the details for the new user:

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Field
Username

February 06, 2019

Description

A login name for the user. Usernames must be unique and lowercase.
If you are using Active Directory to authenticate users, and your LDAP
configuration requires users to be created manually (i.e. they are not
created automatically in ThoughtSpot upon authentication), the username you specify has to be domain qualified (e.g. username@ldap.thoughtspot.com ), and you must enter a dummy password.

Display name

A unique name for the user (usually their first and last name).

Sharing
visibility

Indicate whether objects can be shared with this user. When set to
SHAREABLE
SHAREABLE, this user is an option in the Share dialog.

Change
password

A password.

Confirm
password

Enter the password again.

Email address

The user's email address. This is used for notification when another
user shares something with them.

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Manage
groups

February 06, 2019

Select all the groups the user will belong to. If you add the user to a
group that has the privilege Has administration privileges
privileges, note that they
will be able to see all the data in ThoughtSpot.
When you create a new user, the groups they belong to define the
user's:
• Privileges, the actions they are allowed to do, which are defined when you Add a group and set security privileges.
• Permissions, the data they can access and view, which is
defined when you Data security.
Administrators can see all data sources, and Row level security does
not apply to them.

6. Click Add to create the user.

Edit or delete a user
After a user has been created, you can always go back and change their settings, for example to change
their group memberships or change their password. You can also change their name as long as it
remains unique
As an administrator, you can edit a user and change the groups the user belongs to. You can also edit a
user to reset a user’s password by entering and confirming the new password. This is useful if a user has
forgotten their password, or to effectively disable an account.
To edit an existing user:
1. Log into ThoughtSpot from a browser.
2. Click on the Admin icon, on the top navigation bar.

3. In the Admin panel, click on User Management and Users
Users.

4. Find the user you want to edit in the list and click on its name or the edit icon

. If you

don’t see the name of the user, try searching for it.

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You can also delete a user from this page by clicking the Delete icon.
5. Make your changes and click Save
Save.

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Job management (scheduled pinboards)

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Job management (scheduled pinboards)
Summary: All jobs on your cluster will appear on the Jobs
Management page. You can also view jobs for individual pinboards
under the pinboard Actions dropdown.
The Jobs Management page found on the Admin section in the ThoughtSpot web application allows you
to create and manage jobs, namely scheduled pinboards. Scheduled pinboards should help with
preparing for recurrent meetings, when reviewing the same pinboard is necessary. They should also be
useful when you have metrics you want to monitor at a consistent interval, like daily or monthly sales
targets.
You can get pinboards emailed to you on a regular basis and do analysis offline. This introduces an
additional format for you to consume and share pinboards with others, including those who don’t have a
ThoughtSpot account.
Contact ThoughtSpot Support if scheduled pinboards is not enabled on your cluster, or you can run the
command tscli scheduled-pinboards to enable it yourself.

Scheduled pinboard creators
Administrators and users with can schedule pinboard privilege can schedule and manage pinboard jobs.
These scheduled pinboard creators must have at least edit-only and view-only rights to the pinboard
they want to share.

 Warning: It is recommended that admins carefully choose who to give can schedule pinboard
privilege to, since there is a possible security hole where a user with limited access can get a
pinboard email with all access data.

Row level security
The scheduled pinboards respect row level security rules. This means if the recipients are users in
ThoughtSpot, then they can only see data based on their own access to the pinboard. If the user does
not have at least view-only access to the pinboard, then they will not see anything in the email. However,
if the recipients are from outside of the cluster, then they will have access to the dataset of the pinboard
based on the sender’s permissions.

Scheduled pinboard formats
The pinboard visualizations are attached to the scheduled email as CSV or PDF files. Saved
configurations such as pinboard filters are applied to the attachments. Refer to the table to see how the
pinboard data is represented in each file format.

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CSV

PDF

The CSV file gets data only for table visualizations.

The PDF file gets data for all visualizations.

The email has n CSV attachments, where there are n table visualizations in the pinboard.

The email has only one attachment file, which includes every visualization on its own page.

Table visualizations have all data rows that they’re supposed to
have.

Table visualizations include only
the first 100 rows.

In the case of a corrupted pinboard: no email is sent. An error
message indicating failure to export data is visible on the Admin Jobs Management page.

In the case of a corrupted pinboard: the PDF attachment has
empty/error screenshots.

In the case of a corrupted visualization: an email with the visualizations whose data can be exported is sent. An error message indicating visualization export error is visible on the Jobs
Management page.

In the case of a corrupted visualization: the PDF attachment has
empty/error slots for the corrupted
visualizations.

The size of each email is limited to 25 MB, which matches most email services size limitations.
And the total number of recipients for a scheduled pinboard job cannot exceed the default of 1000.

Related information
For information on creating a pinboard, see the Schedule a pinboard job.

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Scheduled pinboards management
Summary: You can manage all scheduled pinboards on the Jobs
Management page under Admin.
Users who are not admins, but have can schedule pinboard privilege, can only view pinboard schedules
they’ve created. You can select specific jobs and choose to pause, resume, edit, or delete them. You
can have up to 50 scheduled jobs on your cluster at time. Contact ThoughtSpot Support if you’d like to
increase this limit.

Bulk actions
Select the scheduled pinboards and use the Delete
Delete, Resume
Resume, and Pause buttons to perform these bulk
actions. Deleting a pinboard will also delete any schedules linked to it.

Job statuses
Clicking on the row of a job will open a detailed view of every generated update of that job. You can see
the start and end times of the job, as well as the status. Clicking on a job will show more information
about the status updates.

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Pinboard links
Click the scheduled pinboard name link to jump to a Edit schedule page, where you can edit the
schedule configurations.
You can also click on the pinboard link provided in the scheduled pinboard emails to jump to the
pinboard in ThoughtSpot. In order to have the link direct you to the correct URL, you must first configure
front end host and port access. Contact ThoughtSpot Support to configure these settings.

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Overview of security features

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Overview of security features
There are several aspects of security, including access and permissions, data security and privacy, and
security from an IT perspective.
• System Security refers to audit logs and security policies.
• Data Security refers to which users can see which data in the ThoughtSpot application, and
includes:
• Users and Groups
• Privileges
• Table and columns sharing
• Row level security
• Worksheet sharing
• Pinboard sharing
• Network Security refers to ports for external traffic and traffic within the cluster. Some ports
must remain open for handling network requests from outside the ThoughtSpot instance. To
see a list of network ports that must remain open to outside traffic, and for inter-cluster
communication, review the information in Network ports.

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System security
Summary: System security refers to audit logs and security policies.
ThoughtSpot includes a number of management tools, monitoring applications, and automated
processes to support system security. System security includes managing access and privileges, audit
logs, security policies, and Linux OS installed package updates.

Audit logs
There are several ways you can view audit log information in ThoughtSpot. You can see recent events in
the Control Center or view more detailed audit logs using tscli. Administrators can view audit logs of
configuration changes users have made to ThoughtSpot in these ways:
• Monitor events from the Control Center.
• Generate audit log reports through the tscli command.
You can access an audit log of cluster events through tscli. You can also access information on cluster
updates, configurations, data loading and metadata events.
Use the tscli event list command to return an audit list of events from the cluster. The syntax is:

tscli event list
[--include ]
[--since
| --from
--to ]
[--detail]
[--summary_contains
<'string1'| 'string2' ...>]
[--detail_contains
<'string1'| 'string2' ...>]
[--attributes
]

Optional parameters are:
Parameter

Description

--include

Specifies the type of events to include, and can be all , config , or notification .

--detail

Returns the events in a detail format rather than a tabular summary, which
is the default.

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Parameter

Description

--summary_contains <'string1' |
'string2' ...>
--detail_contains
<'string1'|
'string2' ...>
--attributes

And a time window made up of either:
•

--since is a time in the past for where the event audit begins,
ending at the present time. Specify a human readable duration string, e.g. 4h (4 hours), 30m
(30 minutes), 1d (1 day).

Or both:
•

--from is a timestamp for where to begin the event audit. It must be of
the form: yyyymmdd-HH:MM.
• --to is a timestamp for where to end the event audit. It must be of the
form: yyyymmdd-HH:MM.

To get audit logs:
1. Log in to the Linux shell using SSH.
2. Issue the tscli event list command, with the desired parameters, for example:

$ tscli event list
--include config
--since 24 hours

Security policies
Security policies are the principles and processes ThoughtSpot uses in development to ensure a product
that conforms to security standards. Security policies ensure a secure product with each release. When
a release is in development, each build is tested using Qualys Network Security and Vulnerability
Management Suite. Issues and vulnerabilities are fixed proactively, based on the results.
The ThoughtSpot Engineering and ThoughtSpot Support teams are notified of Common Vulnerabilities
and Exposures (CVEs), so they can patch OS packages proactively as well. You can view installed
packages along with their version numbers at any time, in order to see if you require an update to
ThoughtSpot.
Whenever a CVE is identified, and an OS package needs to be updated, the next patch release will
include the patch or update. You can view installed Linux packages at any time, along with the version
numbers of the installed packages.

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Data security

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Data security
Summary: Data security refers to which users can see which data in
the ThoughtSpot application.
Sharing and security privileges govern what data a user can access and what they can do with the data.
Admins can use privileges to regulate access to information and provide a personalized user experience.

Users, groups, and privileges
Data security applies to users and groups. Users can be managed manually or through LDAP. Each user
can have membership in one or more groups. Admins can make security settings that determine what
users are allowed to do in ThoughtSpot. These settings are applied at the group level.
The following table shows the intersection of user privilege and ability:

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Data security

The following table shows the intersection of user privilege and ability:

Can Administer
and Bypass RLS

Can Auto-Analyze
(SpotIQ privilege)

Can share with all
users

Can manage data

Can download data

Can upload user
data

Can administer
ThoughtSpot

None

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Table notes:
1.
2.
3.
4.
5.

Applies to non-owners only.
Any tables.
Author of at least one table in relationship.
Only when read permission for columns used in the relationship.
With edit permission.

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Data security

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Security model for sharing objects
You can share with groups and with individual users. Sharing of tables can be defined at the table,
column, or row level. This provides flexibility in modeling your data security policy. Security and sharing
settings apply to several different types of objects, each of which has its own security default settings
and rules.
Object type

Description

Default security model

Tables

The source data tables
that have been loaded
using ThoughtSpot
Loader.

Administrator users have access to source tables. They can share a table with other users or
groups. See [Share tables and columns](sharesource-tables.html#)

Columns

The columns in the
source data tables
that have been loaded
using ThoughtSpot
Loader.

Administrator users have access to columns in
the source tables. They can share selected
columns with other users or groups. See [Share
tables and columns](share-source-tables.html#)

Rows

The rows in the source
data tables that have
been loaded using
ThoughtSpot Loader.

All rows in the source tables are shared with all
users by default.

Imported data

Data that was imported using a Web
browser.

Only the user who imported the data (and any
user with administrator privileges) has access to
it by default. They can share a table (or selected
columns) with other users or groups. See [Share
tables and columns](share-source-tables.html#)

Worksheets

A worksheet created
using a Web browser.

Only the creator of the worksheet (and any user
with administrator privileges) has access to it by
default. They can share a worksheet with other
users or groups. See [Share worksheets](shareworksheets.html)

Pinboards

A pinboard of saved
search results.

Anyone who can view a pinboard can share it.
See [Share a pinboard](share-pinboards.html)

Understanding SHAREABLE
When you share an object, only the users and groups that have SHAREABLE set for the Sharing visibility
option appear on the dialog.

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Only users in the Administrators group or users with Admin privileges can share with groups marked as
NOT SHAREABLE
SHAREABLE. Members of a group with Can share with all users authorization can also share with
groups marked as NOT SHAREABLE
SHAREABLE.
Users in groups marked NOT SHAREABLE cannot share objects among themselves. In multi-tenant
scenarios, admins can create groups that bring together portions of two non-share groups so that they
can share. For example, the members of group C can share even if they belong to other groups that
cannot.

Row level security
ThoughtSpot includes robust row level security, which allows you to filter all objects users see based on
conditions you set at the level of row values in base data tables.
You may find it useful to create groups for RLS. To prevent these groups from appearing in the Share
dialog, create a NOT SHAREABLE group with a single user and an RLS group with another single user
(1-to-1).

Related information
• Revoke access (unshare)
• Row level security

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Share tables and columns
Summary: You can share an entire table, or only some of its columns.
By default, when data is loaded using the ThoughtSpot Loader, ODBC, or JDBC, it is only visible to
administrators. Data imported from a Web browser is visible to administrators and the user who
uploaded it. Administrators and owners can share Can View or Can Edit privileges on tables with other
users, who can further share them with others.

Permissive or strict sharing
Use caution when sharing tables, because any objects created from them will have dependencies on the
tables and their underlying structure. Objects created from tables can include worksheets, answers, and
pinboards. This means that if a user wants to drop or modify a table, any object that depends upon it
must be edited or removed first, to remove the dependency.
For this reason, it is a best practice to only grant the Edit permission on tables to a small number of
users. If you want to prevent shares from also revealing the columns regardless of where it appears
(worksheets, answers, and pinboards), you can ask ThoughtSpot Customer Support to enable a stricter
behavior.

How to share
Share a table or imported data by following these steps:
1. Click Data in the top navigation bar.
2. Click on Tables
Tables.

3. Select one or more tables to share, and click the Share icon.
4. Select Entire Table or Specific Columns
Columns.

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5. If you selected Specific Columns
Columns, select the column to share.
6. Click + and select the users and groups with whom you want to share.
7. Configure the level of access by selecting from the dropdown list. You can select:
• Can View to provide read-only access. This enables viewing the table data and
defining worksheets on the table.
• Can Edit to allow modification. This enables renaming, modifying, or deleting the
entire table and adding or removing its columns.
8. Click Add and Save
Save.
9. Click Done
Done.

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Share worksheets

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Share worksheets
Summary: You can share worksheets with users or with groups.
Sharing a worksheet allows users to select it as a data source and
search it.
When you share a worksheet, all of its columns are shared. Sharing a worksheet does not share the
underlying tables. If you want to share the underlying tables, see Share tables and columns. A worksheet
can be shared by the owner of the worksheet, or by an administrator. Users can start searching a
worksheet as soon as the worksheet is shared with them.
To share a pinboard:
1. Click Data on the top navigation bar and choose Worksheets
Worksheets.
2. Select one or more worksheets to share, and click the Share icon.

3. Click + Add users or groups and select users or groups that you want to share with.

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Share worksheets

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4. Configure the level of access by selecting from the dropdown list. You can select:
• Can View to provide read-only access. Enables viewing the worksheet and
searching on it.
• Can Edit to allow modification. Enables renaming, modifying filters, or deleting the
worksheet and adding or removing its columns. To add columns to a worksheet a
user needs access to the underlying table.
5. Click Add and Save
Save.
6. Click Done
Done.

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Share a pinboard

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Share a pinboard
Summary: Whenever you view a pinboard you have the option of
sharing it with others.
When you share a pinboard what you are really sharing is a live link to the pinboard, when you click
Share with…
with…. So whenever someone else views it, they will see the most recently saved version with the
most recent data. You do not have to be an administrator or the owner to share saved pinboards. Any
user can share them, based on the access levels the user has.
To share a pinboard:
1. Configure it to look as you’ll want it to appear when shared.
2. From within a pinboard, click the ellipses icon (3 dots)

, and select Share
Share.

Alternatively, select the pinboard you want to share from the list of pinboards and click Share
Share.
(The profile picture or avatar for the owner of each pinboard is shown in the list.)

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3. Click the plus (+
+) at the bottom of the Share dialog, and select users or groups with whom you
want to share.

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Share a pinboard

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4. Configure the level of access by selecting from the dropdown next to each user or group.
Available options are based on your own access level. For example, if you have only View
access, you will not have an option to share as Edit
Edit. You can select:
• Can View to provide read-only access. If the person doesn’t have access to the
underlying data, they can only view a shared pinboard. If they change anything on
the pinboard, their changes are not saved. In order to persist the changes, the user
would need to make a copy of the modified pinboard.
• Can Edit to allow modification. Enables renaming or deleting the shared pinboard.
If a person with edit privileges modifies a shared pinboard, their changes will be
saved to it.
5. Click Add to save your changes, then click Done
Done.

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Security for SpotIQ functions

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Security for SpotIQ functions
SpotIQ is a feature in ThoughtSpot that automatically generates insights into system data. The feature
works on all the data in your system, search queries, saved answers, and pinboards. Because SpotIQ
uses the same data security model as other data in the system, there is no need to build a new schema
or security model to support it.
SpotIQ automatically generates insights into data when a user requests them. These requests can be run
immediately or users can schedule regular analysis. SpotIQ requests for insights can put additional load
on your system depending on the amount of data being analyzed and how frequently users make use of
it.
Users are required to have the Has Spot IQ privilege to use this feature. Users without this privilege
cannot view insights unless the users that generated the insights add them to a pinboard and share the
pinboard with others.
You may want to restrict access to a subset of your users or even to a subset of your managers. To
restrict access to this feature:
1. Create a group called SpotIQUsers
SpotIQUsers.
2. Grant this group Has Spot IQ privilege
privilege.
3. Enable users to this group.

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Revoke access (unshare)

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Revoke access (unshare)
You may need to revoke access to an object (table, worksheet, or pinboard) that you have previously
shared. Unsharing an object is very similar to sharing it.
To unshare one or more objects:
1. Go to the area where the object(s) you want to unshare is located. From the top menu bar:
• If the object is a table or worksheet, click Data
Data.
• If the object is a pinboard, click Pinboards
Pinboards.
• If the object is an answer, click Answers
Answers.
2. Find the object(s) in the list, and check the corresponding box(es).
3. Click the Share icon.

4. Click the X next to the users and groups that you want to remove from sharing.

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Revoke access (unshare)

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5. Click Save
Save, and then click Done
Done.

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About row level security (RLS)

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About row level security (RLS)
Summary: Using row level security, you can restrict data that appears
in search results and pinboards by group.
Row level security (RLS) allows you to restrict a group’s access to table row data. You do this by
creating a rule that associates a filter with a group. When a group member searches, views an answer, or
otherwise works with data, ThoughtSpot evaluates the rules and prevents the display of the restricted
data. Users see only the data they are permitted to see.

How does RLS impact user interactions?
The security rules apply to objects shared with users individually or via groups they are a member of. The
rules restrict the visible data when users:
•
•
•
•

view a table
view a worksheet derived from the table
search for data in the worksheet or table
view answers from restricted data &endash; either that they’ve created or that were shared
with them
• interact with pinboards from restricted data &endash; either that they’ve created or that were
shared with them
Search suggestions also fall under row-level security. If a user would not have access to the row data,
then values from the row do not appear in Search suggestions.

Why use RLS?
RLS allows you to set up flexible rules that are self-maintaining. An RLS configuration can handle
thousands of groups. There are several reasons you might want to use row level security:
Reason

Example

Hide sensitive data from groups who
should not see it.

In a report with customer details, hide potential customers (those who have not yet completed their purchase) from everyone except the sales group.

Filter tables to reduce their size, so that
only the relevant data is visible.

Reduce the number of rows that appear in a very large
table of baseball players, so that players who are no
longer active are not shown except to historians.

Enable creation of a single pinboard or
visualization, which can display different
data depending on the group who is accessing it.

Create one sales pinboard that shows only the sales in
the region of the person who views it. This effectively
creates a personalized pinboard, depending on the viewer's region.

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Related information
• To continue learning about RLS, see How rule-based RLS works.
• Search suggestions relies on compile indices to present suggestions to users from your data.
See Manage suggestion indexing to learn how to configure suggestions.

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How rule-based RLS works
Summary: Use rule-based RLS to restrict a group's access to data.
Users see only accessible row data.
Row level security works at the group level and is configured on tables. A table’s RLS rules also apply to
any objects with data from that table. So, searches, answers, worksheets, and pinboards that rely on a
table’s data fall under RLS rules.

Worksheet queries and RLS
You cannot set RLS rules on worksheets, only on tables. However, administrators can disable RLS on
worksheets that are derived from tables with RLS rules. Once RLS rules are disabled, users with access
to the worksheet can see all its data.
By default, worksheet queries only take into account RLS rules on tables whose columns appear in the
query. Other related tables that may underly the worksheet are ignored. This means that not all RLS rules
on underlying tables are applied when a user queries a worksheet.
You can configure a stricter application of RLS rules to take into account RLS rules from all the tables
underlying the worksheet. This is recommended if you have key dimension tables that worksheets rely
on but that are not necessarily regularly accessed through query. To do this, contact ThoughtSpot
Customer Support.

Privileges that allow users to set, or be exempt
from, RLS
Users in the Administrators group or with the Has administration privilege have full access to everything
in the system. As a result:
• Row level security does not apply to them.
• They can create, edit, and delete RLS rules.
• They can also disable RLS rules on individual worksheets.
If your installation has enabled the Can Administer and Bypass RLS privilege, administrators can also
grant Can Administer and Bypass RLS to groups. Members of groups with Can Administer and Bypass
RLS
RLS:
• Are exempt from row-level security (RLS) rules.
• Can add/edit/delete existing RLS rules.
• Can check or uncheck Bypass RLS on a worksheet.
This behavior is true regardless of whether the privilege is from a direct group membership or indirect
(through a group hierarchy).

Examples of RLS rules
An RLS rule evaluates against two system variables:

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Function

February 06, 2019

Description

Examples

ts_groups

Returns a list of all the groups the current logged
in user belongs to. For any row, if the expression
evaluates to true for any of the groups, the user
can see that row.

ts_groups = 'east'

ts_username

Returns the user with the matching neame.

ts_username != 'mark'

ThoughtSpot filters a table’s rows by evaluating a rule against the authenticated user.
A rule is an expression that returns a boolean, TRUE or FALSE . If the rule evaluates to TRUE , a user
can see that row. If the rule evaluates to FALSE for the user, then the user cannot view the data and
instead they see the message No data to display .
Rule expression can be implicit or explicit. And rules may or may not contain logic. A simple implicit RLS
rule has the format:
COLUMN_FILTER = ts_groups

An example of an explicit rule that contains logic would be:
if ( COLUMN_FILTER ) then true else false

Rules can also reference tables other than the table you are securing.
Consider a simple RLS rule example. Your company has vendor-purchase table such as:

You want to give your vendors the ability to see trends in company purchases. You give vendor
personnel access to ThoughtSpot and add them to self-titled vendor groups. So, all users from the
Starbucks vendor are in the Starbucks group and all users from round table are in the Round
Table group. Then, you set a Row security on the vendor-purchase table as follows:
VENDOR = ts_groups

Only users in Starbucks group see starbucks data and so forth. Rules ignore case inconsistencies
and spaces are evaluated so round table in the data matches the Round table group but not a
group named RoundTable .

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Rules can be simple or they can incorporate logic such as if/then rules. For example, vendors should
see their own data but your accounts payable group needs to see all the vendor data:
VENDOR = ts_groups or 'Accounts Payable' = ts_groups

This rule continues to work as you add data from new vendor or team members to Accounts Payable .
In this way, a well-written rule is self maintaining, meaning you don’t have to revisit the rule as your
system changes.
You can also create rules that reference tables other than the table you are securing. For example, if you
have a sales table and store dimension table, you can use attributes from the store table to
secure the sales table.

Multiple rules and multiple group membership
You can define multiple rules on table. In this case, ThoughtSpot treats the rules as additive. That is, they
are applied using an OR operator. If any of the rules evaluate to true for a user on a row, that row’s
data is visible.
If a user is a member of multiple groups, the user can see all the rows that are visible to all of their
groups. The most permissive policy is used.
Members of groups with Can Administer and Bypass RLS are exempt from row-level security (RLS)
rules. This is true regardless of whether the group membership is direct or indirect (through a group
hierarchy).

Best practices for using Rule-Based Row Level
Security
Use these best practices for Rule-Based Row Level Security:
• Use Share as the first level of data access.
Non-administrative users and groups have no way to access any data without first having it
shared with them. So, only share what you need.
When you share, share worksheets. This is a general best practice. Worksheets simplify the
data environment for end users; they only need to choose among a few sources, rather than
many tables. Also, one worksheet can also combine data from several tables.
• Set row level security wherever you want to keep data secure.
It is always a possible that a particular search only includes data from a single table, and a
user will see something they shouldn’t. So, protect your data by setting row level security
wherever you want to keep data secure.
• Explicitly grant access for users that should see all rows.
As soon as you define a rule on a table for one group, you prevent access by all others
outside of that group hierarchy. Subsequent rules should specifically add groups that need
access.
• Keep in mind that multiple rules on a table are additive with or .
If you are concerned with security, start with very limited access. Then, expand the access as
needed.
• Keep rules simple.

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Complex rules can impact the system performance. So, err on the side of simple rules rather
than complex rules with a lot of logic.

Related information
• To learn the procedure you follow for setting a rule, Set RLS rules
• For a list of operators and functions you can use to build RLS rules see Row level security
rules reference.
• For information on bypassing rules on a worksheet, see Change inclusion, join, or RLS for a
worksheet.

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Set row level security rules
Summary: Explains the process for setting RLS rules.
When rule-based row level security (RLS) is set, it prevents users from seeing data they shouldn’t in
tables and the objects derived from them. You must have administrative rights on ThoughtSpot to set
RLS rules.
Before you create a rule, make sure you have read How rule-based RLS works.

Create a rule on a table
You can set RLS rules only on tables. To set up rule-based row level security, do the following:
1. Click Data
Data, and double-click on a table.
2. Click Row security
security.
3. Click + Add row security
security.

The system displays the Rule Builder.

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You define row level security by creating an expression that gets evaluated for every row and
group combination. This powerful feature can be used with up to thousands of groups.
4. Open the Rule Builder.
5. Give your rule a name.
6. Enter an expression for your rule.
The rule gets evaluated against an authenticated user for every row and group combination. If
the rule evaluates to true, the user can’t see that row’s data. Use the variable ts_groups to
refer to the group name.

You can see a list of available operators by clicking on Rule Assistant
Assistant.

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As you type, ThoughtSpot suggests formula syntax, variables, and column names. If you can’t
remember the exact column name or variable you want to use, the suggestions can help.
When your expression is valid, a green indicator appears at the bottom of the Rule Builder.
7. Click Save
Save.
The rule you created is listed in the rules. You can edit the rule or add more rules by clicking + Add
Add.

Test your rule with restricted and unrestricted
users
To test your rule, log in as users in different groups. Search within the table for data both that you test
user can and can’t access. Make sure your test users are seeing the appropriate rows.

Related information
• Administrators can bypass the RLS rules set on a the table at the worksheet level. See how to
“Change inclusion, join, or RLS for a worksheet in this documentation for more information.
• For a list of operators and functions you can use to build RLS rules see Row level security
rules reference.

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ThoughtSpot Lifecycle
Summary: This topic covers security processes for the entire lifecycle
of a ThoughtSpot deployment from development, release, installation,
upgrades, to software patching.

Overview
A ThoughtSpot deployment consists of the following high level software systems:
• Operating System (OS) and software packages installed on the OS
• Third-party software
• ThoughtSpot application services (binaries and configuration)

Operating System
All ThoughtSpot physical appliances, virtual machines (VMs) and public cloud images come pre-installed
with CentOS 7. The CentOS distribution of Linux is owned by RedHat and closely tracks versions of
RedHat Enterprise Linux (RHEL).
ThoughtSpot uses the minimal install of CentOS 7 with the addition of a few software packages (e.g.
Python) needed for ThoughtSpot operations. The most notable change to the installation is to the Linux
kernel, which is sourced from the current long term stable kernel version instead of the default included
in CentOS 7 (kernel-lt package). To list all the installed packages, see Checking Package Versions below.

Third-Party Software (Middleware)
Third party software used includes Java, Boost C++ libraries, Google protocol buffers, etc. These are
software components necessary for operation of the ThoughtSpot application. ThoughtSpot only uses
software licensed for distribution.

Development and Release Process
ThoughtSpot releases its software as a tarball containing all the ThoughtSpot application (binaries and
configuration), third-party software, and an operating system image. Installation or update using this
release tarball on appliances, VMs, or cloud instances updates each of these components.

Operating System
Building the operating system image including software packages is a multi-step process:
1. Begin with the set of packages in the base OS image and our added packages.
2. Configure all installation to only use official public RedHat repositories.
3. For each package, install the current stable version including any security patches.

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4. Bring up the image on all supported platforms for stability and performance testing along with
the ThoughtSpot application stack. Success criteria: no OS impact on stability or
performance.
5. Scan the Operating System and ThoughtSpot application stack using Qualys scans with
additional modules enabled: Vulnerability Management, Web App Scanning.
6. Review all vulnerabilities found. Success criteria is zero severity 4+ vulnerabilities.
7. Assuming all above testing and exit criteria are met, the OS image is considered qualified.

Third-Party Software
Third-party software is periodically sourced from the upstream distribution of each software component.
Unlike OS and ThoughtSpot application, this changes less frequently and on an as needed basis, when
any new security vulnerability or stability issue is discovered in the library. The list of all third-party
software as well as licensing details are here.

ThoughtSpot Application
ThoughtSpot follows industry standard best practices for writing robust software. Every code change is
reviewed by at least one engineer. Our engineering team consists of senior engineers from Enterprise
software and web companies.
ThoughtSpot uses a small number of proven programming languages powering some of the largest
enterprises in the world. ThoughtSpot tracks stability, performance, and reliability of our software and
services aggressively. The ThoughtSpot platform is trusted by dozens of global F2000 organizations.

Protection of Source Code
Source code is private and not shared publicly, e.g. all distribution to customers is in binary or minified
format to discourage reverse engineering.

Automated Tools
We use automated tools and infrastructure like Jenkins, Kubernetes, AWS, partnering with the teams
behind these systems so as to adopt best practices. For example, all our automation runs through
Jenkins, which is managed by CloudBees (the company behind Jenkins) using an enterprise license with
regular security patching, and so on. We upgrade our automation tools regularly.

Independent Testing
Independent testing is done outside of the product team by pre sales and post sales before promoting to
production. Some areas are tested by third party testers.

Security Hardening
Starting 4.5.1.5, we have also taken specific steps to incorporate most of CIS standard
recommendations towards hardening.

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Installation and Upgrade Process
ThoughtSpot is installed or updated from a release tarball which contains the ThoughtSpot application
(binaries and configuration), third-party software, and Operating System image.

Operating System Image Installation
Installing ThoughtSpot on any node (VM, cloud instance, appliance) automatically updates the operating
system and required packages on the node. No Internet or repository access is required for this, the
update is applied directly from the release tarball.
Specifically, all nodes running ThoughtSpot are required to have two root partitions on their boot drive of
which one of them is booted from at any given time. During installation or update, the Operating System
image contained in the release tarball is copied into the second currently-unused root partition and the
system switches to it through a reboot.

Checking OS Package Versions
The following command run from any ThoughtSpot node will indicate versions of all installed packages:

rpm -qa

Upgrades
ThoughtSpot patches the Operating System at the time of upgrades. The exact same process used
during installation is also applied during upgrades. The previous OS image on a node gets replaced by
the new image carried in the release tarball.
Only some releases may patch the Operating System, not all. Typically, all major and minor releases (e.g.
4.4, 4.5, 4.5.1, 5.0) upgrade OS patches, whereas only some patch releases (e.g. 4.4.1.4) contain OS
patches.

Distributed Clusters and Failure Handling
On distributed clusters, individual nodes receive the OS image from the release tarball individually.
Initially, the new image is deployed on a single node only. When that node is deemed healthy following
the update and a rich set of tests, the image is made available to remaining nodes in the cluster.
If a node fails to patch, then ThoughtSpot support will modify the upgrade workflow to either retry the
patching or skip and exclude the node.

Third-Party Software
Installation or upgrade of ThoughtSpot deployments automatically upgrades all third-party software to
the version included in the release tarball.

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Security Scanning and Patching Process
The ThoughtSpot Security team continuously scans security bulletins for new vulnerabilities discovered
in included OS packages (e.g., Linux Kernel, libc) and third party software (e.g., Java). Additionally,
weekly scans are done for all release branches using Qualys with the following additional modules
enabled: Vulnerability Management, Web App Scanning. The security scans discover vulnerabilities at all
layers: OS, third-party software, as well as ThoughtSpot application binaries and configuration.
Additionally, ThoughtSpot periodically scans all source code for third-party software as well as
ThoughtSpot’s proprietary code base for vulnerabilities or unsafe usage using SourceClear.
Once a critical new vulnerability is found (severity 4 or 5), ThoughtSpot includes the corresponding patch
in the next patch release for all supported release branches. Consult ThoughtSpot documentation or
support to find out if you are on an active or supported release branch.
Once a new patch release with a critical security vulnerability is available, customers are encouraged to
upgrade their deployment quickly.

Latency
We recommend customers to wait for the next regular release for receiving security patches. However,
should a critical vulnerability be discovered in the interim, ThoughtSpot can push out a new patch
release containing the required patches, if available upstream.
ThoughtSpot targets a three week or less cadence for generating patch releases for all supported
release branches. Timeline for the new release and patching depends on availability of the patch
upstream (e.g., not all vulnerabilities in Linux are immediately fixed) and qualification (ThoughtSpot
qualifies each build on each supported cloud and on-prem platform). If a fix is unavailable upstream at
the moment, customers and ThoughtSpot support can work together to identify potential workarounds.

Storage Security
Encryption at Rest
• On-prem: Not supported yet
• Cloud: Supported on AWS, GCP, Azure

Secure Erase
Current erase guide

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System administration

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System administration
System administration includes applying upgrades, backing up and restoring the cluster, snapshotting,
and adding or removing nodes.

Administration tools
Use these tools to perform administrative actions:
• tscli: an administrative command line interface.
• tsload: a command for loading data directly into the database.
• TQL: a command line SQL interface to interact with databases.

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Send logs when reporting problems
You can generate a log bundle which you can then send to ThoughtSpot Support or you can send logs
direct to your administrator.

Generate log bundle
Before you can send a log bundle to ThoughtSpot Support, you must Connect to the ThoughtSpot
Support file server. This is a one-time setup operation.
To generate a log bundle:
1. Log in to the Linux shell using SSH.
2. Issue the command to generate the log bundle:

tscli callhome generate-bundle
--d --since

Note: Don’t forget to include d after your specified number of days. For example, 30d .
3. Change directories to the directory where you wrote the log bundle.
4. Issue the command to send the log bundle to ThoughtSpot Support:

tscli fileserver upload
--file_name
--server_dir_path

Send a log to the administrator
Alternately, you can easily send log files directly to your administrator with a single click. When
ThoughtSpot encounters a problem, a red bar displays in the browser with an error message. You can
use the Report Problem option to complete this task.
Click Report Problem in the bottom right corner of the error message.

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The logs will be sent to your administrator as an email attachment from your email account. Your
administrator then has the option to followup with ThoughtSpot, if necessary.

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Set up recording for Replay Search

February 06, 2019

Set up recording for Replay Search
Summary: You can use the recording to create training for your users
on how to search your own data.
Recording a search replay requires administrator privileges and a Firefox browser. You must override
some of your browser security settings in order to use the ThoughtSpot application to make the
recording. This is a one time setup operation. If you do not wish to do this, you can replay the search
and record it using QuickTime, Camtasia, or another screen cam recording tool.
To record a search replay using ThoughtSpot:
1. While viewing a chart or table in ThoughtSpot, click the Replay Search icon.

2. Click the Record Replay button.
If you do not see the button, you must log in as a user with administrator privileges.

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A message will display, showing a URL and a domain or an IP address.
3. Make note of both of these items.
4. Open a new browser tab and go to the URL shown in the message ( for example,
“about:config”).
Depending on which browser and version you are using, you may need to access the browser
configurations through a menu or by typing in a different URL. Check your own browser help
section for information on how to access the browser configuration settings, if necessary.

You may see a message warning that you are about to override the browser settings.
5. If you trust yourself, click “I’ll be careful, I promise!”.

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6. Find the setting for media.getusermedia.screensharing.allowed_domains
media.getusermedia.screensharing.allowed_domains, and add the domain
used by ThoughtSpot.
This domain will be the same one you made note of from the Cannot record screen message.

7. If you see a message asking if you’d like to share your screen with the IP address or domain
name of ThoughtSpot, select Entire screen
screen.

8. When the search replay has been recorded, you’ll see a confirmation. Select Download
Download.

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9. Save the recording on your computer by selecting Save File and clicking OK
OK.

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Introduction to monitoring

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Introduction to monitoring
System monitoring tools in ThoughtSpot include an Admin > System Health page and system logs.
Additionally, ThoughtSpot provides several worksheets and out-of-the-box system monitoring
pinboards. From these worksheets, you can create your own custom visualizations and pinboards. This
page introduces these features and directs you towards more detailed information.

System Health center
The ThoughtSpot application includes a System Health center, for easy monitoring of usage, alerts,
events and general cluster health. You view the System Health Center by choosing the Admin icon and
then selecting System Health
Health.

Only users with administrative privileges can view the System Health center. However, administrative
users can present to others the information that displays in the System Health center.
Administrators can also create their own, custom boards that reflect system data in ways that are
meaningful to specific departments or groups. For more information, see the following documentation:
•
•
•
•
•
•

Health Overview board
Data board
Cluster Manager board
Alerts and Events board
System worksheets
System pinboards

Much of the data presented by these boards is also available through tscli commands.

Log files
Many of the administration commands output logging information to log files. The logs get written into
the fixed directory /export/logs , with a sub-directory for each subsystem. The individual log
directories are the following:
•
•
•
•

/export/logs/orion
/export/logs/oreo
/export/logs/hadoop
/export/logs/zookeeper

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You can also view additional topics that also touch on log files throughout the documentation.

System monitoring notifications
You can configure ThoughtSpot to send emails to addresses you specify with monitoring reports and a
cluster heartbeat. Follow these steps to Set up monitoring.

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Overview board

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Overview board
The Overview pinboard summarizes essential information about your cluster and its users. Choose
Admin > System Health > Overview to see this pinboard.

Understand system boards and pinboards
The Overview page includes system panels and standard ThoughtSpot answers. The system charts are
generated in real time and rely on internal system data. The answers rely on underlying system
worksheets which are available to ThoughtSpot administrators. The information in these worksheets is
updated hourly from internal tables that collect monitoring statistics.
Each answer has a menu. You can present or copy the links to the system charts. The answers have a
subset of the ThoughtSpot answer menu. You can use the menu to do additional actions such as
download the answer or present information about your ThoughtSpot cluster. While you can interact with
and change the search, you cannot save changes to the underlying query.
You can also interact with the answers, drilling into them to explore the detail as with any other pinboard
answer.
To find out how a particular answer was created, do the following:
1. Select Edit from the panel menu.

This displays a Search bar.
2. Investigate the components of the search as you would normally.

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Cluster Summary
This system panel contains basic information about your cluster. The NUMBER OF NODES is the
number of installed nodes. This doesn’t reflect the active nodes which may be more or less.
This summary includes the LAST SNAPSHOT TIME it reflects whether regular snapshots of your cluster
are collected. This value should update regularly in real time. If you do not see it change or empty, you
should check your cluster snapshot policy using the tscli command:

$ tscli snapshot-policy show
schedule {
period {
number: 1
unit: HOUR
}
retention_policy {
bucket {
time {
number: 1
unit: HOUR
}
capacity: 3
}
bucket {
time {
number: 4
unit: HOUR
}
capacity: 2
}
}
offset_minutes_from_sunday_midnight: 0
}
enabled: false

You can see this policy is disabled, which is a problem. Production clusters should enable the default
snapshot policy. When you show or enable the snapshot policy, you’ll see your tscli command
reflected in the Configuration Events panel on this same page.

Relational Data Cache
This section reports real-time information about tables in your cluster. Worksheet data is not included.

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Value

Description

TABLES LOADED

Number of currently loaded tables.

TABLES BEING UPDATED

Number of table loads in-progress.

NEW TABLES BEING LOADED

Number of tables being loaded for the first time.

ROWS

Number of rows combined across all tables in ThoughtSpot.

Relational Search Engine
Value

Description

TABLES SEARCHABLE

Tables that are indexed and can be searched.

TABLES BEING INDEXED

Total of in-progress table indexing.

NEW TABLES BEING INDEXED

Total of first-time, in-progress table indexing.

TOKENS SEARCHABLE

Number of tokens of all table (combined) indexed in ThoughtSpot.

Critical Alerts
Displays critical and warning alerts. This includes when an alert was generated and from which service
and machine. Administrators can get a custom report by issuing a tscli alert list on the
appliance:

tscli alert list --since 4w

The critical alerts you can encounter in this display are the following:
•

TASK_FLAPPING

Msg
Msg: Task {{.Service}}.{{.Task}} terminated {{._actual_num_occurrences}}
times in last {{._earliest_duration_str}}

This alert is raised when a task is crashing repeatedly. The service is evaluted across the
whole cluster. So, if a service crashes 5 times in a day across all nodes in the cluster, this
alert is generated.
•

OREO_TERMINATED

Msg
Msg: Oreo terminated on machine {{.Machine}}
This alert is raised when the Oreo daemon on a machine terminates due to an error. This
typically happens due to an error accessing Zookeeper, HDFS, or a hardware issue.
•

HDFS_DISK_SPACE

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Msg
Msg: HDFS has less than {{.Perc}}% space free
Raised when a HDFS cluster is low on total available disk space.
•

ZK_INACCESSIBLE

Msg
Msg: Zookeeper is not accessible
Raised when Zookeeper is inaccessible.
•

PERIODIC_BACKUP_FLAPPING

Msg
Msg: Periodic backup failed {{._actual_num_occurrences}} times in last
{{._earliest_duration_str}}

This alert is raised when a periodic backup failed repeatedly.
•

PERIODIC_SNAPSHOT_FLAPPING

Msg
Msg: Periodic snapshot failed {{._actual_num_occurrences}} times in last
{{._earliest_duration_str}}

This alert is raised when periodic snapshot failed repeatedly.
•

APPLICATION_INVALID_STATE_EXTERNAL

Msg
Msg: {{.Service}}.{{.Task}} on {{.Machine}} at location {{.Location}}
Raised when Application raises invalid state alert.
The possible alert types are CRITICAL , WARNING , ERROR , and INFO . For a full reference, see the
Alert code reference.

Space Utilization
The Space Utilization chart is one of the available charts for you to use when checking the cluster
overview. This line chart displays the total capacity and estimated used capacity over time.

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The x-axis is by time and the y-axis measures the size in GB. You can zoom in and see daily or hourly
utilization data. So, in the Space Utilization chart above, the green line shows the amount of capacity in
use in the system, while the red line shows the total capacity. An increase in the red line at the end of a
time period indicates the addition of extra hardware, resulting in increased capacity.
The query for this answer is the following:

day of timestamp
total capacity (gb)
total used space (gb)
daily
last 90 days last 25 hours
total capacity (gb) > 0
total used space (gb) > 0

The chart relies on the TS: Internal Table Wise Capacity WS worksheet. It tracks total used
space, which consists of raw uncompressed data, including replication.

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Monthly Active Users
This chart shows the number of active users in the system over the last four months and current month.
An active user is defined as a user who has logged in at least once in the defined time interval, in this
case months.
The query for this answer is the following:

monthly
last 4 months this month
active users
user != {null}

This query relies on the TS: BI server worksheet.

Monthly Ad-hoc Searches
Number of ad-hoc searches (queries) issued per month. An ad-hoc query is defined as any search or
change to a search that builds a new answer (result). An ad-hoc search can also be generated through
SpotIQ or another UI/API interaction.
ThoughtSpot considers all of the following as ad-hoc searches (queries):
• User edits tokens (boxed terms) in the search bar.
• User opens an existing saved answer and makes changes to tokens in the search bar.
• User opens an existing saved pinboard, edits a visualization, and makes change to the search
tokens.
• Searches initiated by an API call for data with runtime filters
It is not considered a search (query) in this context if a user opens an existing saved aggregated
worksheet and makes changes to its underlying query.
The query for this answer is the following:

ad-hoc search
user action = 'answer_pinboard_context' 'answer_saved' 'answe
r_unsaved'
monthly
last 4 months this month

This answer relies on data from the TS: BI Server worksheet.

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Monthly Pinboard Views
Number of times a saved pinboard is viewed by a user. These scenarios are considered pinboard views:
• User opens an existing saved pinboard.
• User opens an embedded pinboard from a URL.
• Pinboard data is accessed using the an API.
These scenarios are not considered pinboard views:
•
•
•
•

A user opens SpotIQ tab pinboards.
A user opens admin tab pinboards.
The system loads a pinboard on the homepage.
The system loads the ‘learn how to use ThoughtSpot’ pinboard.

The query underlying this answer is:

pinboard views
user action = 'pinboard_embed_view' 'pinboard_tspublic_no_runti
me_filter' 'pinboard_tspublic_runtime_filter' 'pinboard_view'
monthly
last 4 months this month

The query uses the TS: BI Server data source.

Top Users Last Month
This answer shows the top ThoughtSpot users ranked by number of actions the users performed in the
last 30 days. The possible user actions include:
answer_unsaved

User makes a change to tokens in the search
bar.

answer_saved

User opens an existing saved answer and makes
changes to tokens in the search bar.

answer_pinboard_context

User opens an existing saved pinboard, edits a
context viz and makes a change to tokens in the
search bar.

answer_aggregated_worksheet

User opens an existing saved aggregated worksheet and makes changes to tokens in the
search bar.

answer_upgrade

Requests made for the sole purpose of upgrade.

pinboard_view

User opens an existing saved pinboard.

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pinboard_filter

User adds, removes or applies values to a pinboard filter.

pinboard_ad_hoc

User drills down in a pinboard viz.

data_chart_config

Request for new data being generated following
a chart config change.

data_show_underlying_row

Request to show underlying data for a data
row(s).

data_export

Request to export data.

pinboard_tspublic_runtime_filter

Request to TSPublic/pinboarddata with runtime
filters.

answer_aggregated_worksheet_save

User updates aggregated worksheet.

answer_add_new_filter

User adds a filter using the UI.

data_show_underlying_viz

Request to show underlying data for a data
row(s).

answer_view

User opens an existing, saved answer.

answer_viz_context_view

User opens an existing saved pinboard, edits a
context viz.

pinboard_insight_view

User opens SpotIQ tab pinboards.

pinboard_admin_view

User opens admin tab pinboards.

pinboard_embed_view

User opens embed pinboard from a URL.

pinboard_homepage_view

On loading of homepage pinboard.

pinboard_learn_view

On loading learn pinboard.

pinboard_tspublic_no_runtime_filter

Request to TSPublic/pinboard data without runtime filters.

The query underlying this answer is:

top 10
ranked by user actions
user action != 'invalid'
user != {null}
user
last 30 days today

The query uses the TS: BI Server data source.

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Top Pinboards Last Month
This answer shows the top ThoughtSpot users ranked by number of pinboard actions the user
performed in the last 30 days. The possible user actions include:
• User opens an existing saved pinboard (‘pinboard_view’).
• User opens an embedded pinboard from a URL (‘pinboard_embed_view’ ).
• Pinboard data is accessed using an API (‘pinboard_tspublic_no_runtime_filter’ or
‘pinboard_tspublic_runtime_filter’).
The query underlying this answer is:

top 10
ranked by pinboard views
user action = 'pinboard_embed_view' 'pinboard_tspublic_no_runti
me_filter' 'pinboard_tspublic_runtime_filter' 'pinboard_view'
pinboard != {null}
pinboard
last 30 days today

The query uses the TS: BI Server data source.

Configuration Events
This system answer displays recent events that changed the configuration of the system. This panel
displays configuration events related to:
Cluster Configuration

Reports configuration actions from the `tscli` and `tql` commands.

Metadata Management

Events related to metadata such as column names, column visibility,
column and data definition, column rank and so forth.

User Management

Events related to creating, updating, or adding new users and groups.

For a more detailed list, including the user that issued a command, you can use the tscli event list
command. Administrators can ssh into the cluster and specify a time period or even a type of
command to include.

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User
"gues
tscl
Metad
Metad
Oppor
AE an

About deprecated boards
There are a number of deprecated boards on this page. They are there to support older installations that
relied on them. New installations, should not use or rely on deprecated boards. Older installations that
have used these boards in some way, should use the new boards and remove any dependencies.

Related information
tscli logs command

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Data board

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Data board
The Data page shows all the stored tables with details on the last update time, time taken for autoindexing, number of rows, and so forth.

You can click on a column name to sort by table name. This table information is based on an underlying
system data, you can present it or copy the link, but you cannot access the underlying query.

Database Status
The Database Status column can have the following possible values:
Status

Meaning
The data has been loaded.

READY

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Status

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Meaning

IN PROGRESS

The data is still being loaded.

STALE

The data is not up to date.

ERROR

The table is invalid. Call Customer Support.

Replication Status
The Replicated column indicates if the table has been replicated or sharded. This can be used in
conjunction with the Total Shards column to see how your data is distributed.
If the table is replicated on a multi node system, the Used Capacity (MB) column will indicate the total
space used on all nodes. a 10MB table replicated on a 4 node system will show 40MB used capacity for
example.

Search Status
The Search Status column can have the following possible values:
Status

Meaning
The data is up to date and searchable.

READY

The data is not ready to be searched.
NOT READY

DELETING INDEX

The table has already been deleted, but the index still exists due to the
latency between the database and search engine.

INDEXING DISABLED

Either too many tokens exist in a column for it to be indexed, or indexing has been disabled manually.

CREATING INDEX

The index is being created.

UPDATING INDEX

A change has been made to indexing or the data, and the index is being updated to reflect it.

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Cluster Manager board
The Cluster Manager section show detailed information about a cluster including latency over time,
snapshot status, installed release, node functions, and logs.

Only the Average Latency Last 2 Weeks (sec) panel contains a standard ThoughtSpot visualization. The
other visualizations rely on internal queries that are not accessible. You can, however, Present or Copy
link on them.

Cluster Details
The fields on this visualization has the following meaning:
Field

Description

Cluster Name

The name of the cluster defined at installation time.

Cluster ID

The ID of the cluster set at installation time.

Last Update Time

Last time the cluster was updated.

Release

Version of the current release.

Zookeeper Servers

IP addresses of the Zookeeper servers.

HDFS Name Nodes

Control nodes for Hadoop Distributed File System (HDFS).

Cluster Logs
The fields on this visualization has the following meaning:

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Field

Description

Time

A timestamp indicating when an action occurred.

Type

Type of action.

Release

Identifies the full release number.

You can also use the tscli logs command to review log data from your cluster.

List of Snapshots
This visualization shows the snapshots and the backups taken on the cluster. The fields on this
visualization has the following meaning:
Field

Description

Time

A timestamp indicating when a snapshot or backup happened
occurred.

Name

Name of the snapshot file. These files are stored in the `/usr/local/scaligent/backup` directory on your cluster.

Reason

Identifies the reason the snapshot/backup was created. You
should see several period snapshots if your cluster is configured
properly. You may also see evidence here of manual backups.
For example, you should be sure your cluster is backed up before major events such as upgrades. Email support@thoughtspot.com if you don't see evidence your cluster is
periodically creating snapshots.

Size

Size of the backup in gigabytes.

Average Latency Last 2 Weeks (sec)
This visualization relies on the TS: BI Server worksheet to display the average database latency over
the last 15 days. The database latency measures how long it takes for a search to return data from
ThoughtSpot - this does not include the time taken to send the answer back to the client, it measures
internal processing time. You can use the visualization menu to drill down to its underlying query:

average datacache (sec)
average total (sec)
daily
last 15 days
for database latency (us) > 0

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Related information
tscli logs command

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Alerts and Events board

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Alerts and Events board
The Alerts and Events section shows notifications, alerts, and an audit trail of cluster configuration
changes.

Alerts
The fields on this answer have the following meaning:
Field

Description

Time

When the alert was sent.

Type

The ID of the event.

Message

The text of the alert message.

For a full reference of possible alerts, see the Alert code reference.

Configuration Events
This system answer displays recent events that changed the configuration of the system. This list can
contain the same types of information available on the Admin System Health > Overview page. This
answer displays the Time
Time, the User that performed the action, and a Summary of the action.

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Notification events
This answer displays notifications of data loads. The display the Time
Time, the User that performed the
action, and a Summary of the action. Notifications are kept for 90 days before being discarded.

Related information
Alert code reference

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System worksheets
Most of the monitoring information in System Health are sourced from system worksheet which
administrators can view, but not modify. The underlying tables are protected system tables that cannot
be accessed directly. However, administrators can create new, custom monitoring reports from the
worksheets.

List the system worksheets
To list the system worksheets:
1. Go to the Data tab.
2. Choose All and Worksheets
Worksheets.
3. Enter TS: in the search field.

Summary of the worksheets
Worksheet

Description

TS: BI Server

Contains data related to the systems associated with underlying
the ThoughtSpot BI server. This includes database latency,
browser clients, size of responses, and more.

TS: Database

Contains information related to the database cache and queries
run on the database. For example, you could use this worksheet
to see data on the query errors returned by the database.

TS: Internal Capacity WS

Describes cluster memory capacity by node over time.

TS: Internal Table Wise

Describes memory capacity by node, table name, shard count,
and CSV replication over time.

Capacity WS
TS: Metrics

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Contains metrics by cluster and host over time.

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TS: Search

Contains data related to the number of searches (queries) run in
the system. This contains information such as uptime, host, and
timestamps.

TS: Service Resources

Contains data related to cluster nodes including page faults,
memory usage, memory failures, and more.

TS: Table Info

Describes the named tables by timestamp, row count, row
shards, and row size.

TS: Table Row Counts

Describes the named tables by timestamp and row count.

TS: Table Row Counts and

Describes the named tables by timestamp, row count, row
shards, and row size.

Shards
TS: Table Row Size

Describes the named tables by timestamp and row size.

TS: Table Shards

Describes the named tables by timestamp and shard count.

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System pinboards

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System pinboards
There are several system monitoring pinboards in ThoughtSpot that provide answers for system status
and resource usage questions. The information in these pinboards are updated hourly from internal data
sources that collect monitoring statistics.

Only users with administrative privilege can view the monitoring pinboards. They are based on
worksheets, which administrators can view, but not modify. However, you can create new monitoring
pinboards from the worksheets.

List system pinboards
To list these system pinboards:
1. Go to the Pinboards tab.
2. Choose All
All.
3. Enter TS: in the search field.

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Summary of system pinboards
Pinboard
Learn how to use

Description
Contains search replays created in the system.

ThoughtSpot
TS Stats: Alert Detail

Combines alerts, notification events, and configuration events
boards.

TS Stats: Cluster Detail

Contains cluster details, logs, snapshots, and latency data.

TS Stats: System Informa-

Replicates the **Admin > System Health > Overview** page.

tion and Usage
TS Stats: Latency Visualizations
TS Stats: Table Status

Latency on servers and impression counts. This data comes
from the `TS: BI Server` worksheet.
Replicates the **Data** board.

About deprecated boards
The deprecated boards ( TS status: Usage - Deprecated and TS StaTS: Queries -Deprecated ) are there to support older installations. New installations, should not use or rely on
deprecated boards. Older installations that have used these boards in some way, should use the new
boards and remove any dependencies.

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Understand the backup strategies
This section discusses three strategies for backing up your ThoughtSpot cluster.

Snapshots
A snapshot is a point-in-time image of your running cluster. Snapshots are both taken on and restored to
a cluster while it is running. Each cluster has a periodic snapshot configuration enabled by default. This
configuration instructs the system to periodically take snapshots. Creation of a snapshot takes about 20
seconds. Once taken, a snapshot is persisted on disk in the cluster’s HDFS.
You can also create a snapshot manually. You should create a snapshot before making any changes to
the environment, loading a large amount of new data, or changing the structure of a table. A snapshot
may only be restored to the same cluster on which it was taken. The cluster software release version
must match the snapshot release version.
If you need to move data between clusters or restore to a cluster that was updated to a new release,
contact ThoughtSpot Support.

Backups
A backup is a procedure that stores a snapshot outside of a ThoughtSpot cluster. Backups are stored in
a directory on a local or network file system. You can store all of the data associated with a snapshot or
a portion of that data or only metadata. There is no default configuration enabled for backing up a
cluster. You can configure on yourself or you can take backups manually. Backing up periodically
protects your company from losing data and/or user work.
You can use a backup to restore a cluster to a prior state, a differently configured appliance, or move the
backup from an appliance to a virtual cluster or vice versa.

Offline backup cluster
The most robust strategy for backup and recovery requires having a backup cluster offline that is kept in
sync with the production cluster. Then, if the production cluster fails, the backup cluster can be drafted
to take its place with minimal loss of work and disruption to operations.
Details on this architecture and instructions on setting it up are available in the ThoughtSpot Disaster
Recovery Guide, which you can request from ThoughtSpot.

Choosing when to use a strategy
Depending on your situation and your goals, you can choose to use a snapshot or a backup. This table
should help you decide:
Snapshot

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Used to

To restore to a cluster to particular point
in time.

Stored

In the cluster's HDFS

February 06, 2019

• Restore a cluster to a prior
state.
• Move a cluster to a different
HW appliance.
• Move a cluster to VM appliance.
• Removal of a node.
• Restoring to a cluster running
a different release from the
one where the backup was
taken.

Outside the cluster on either local or
NAS disk.

Advantages

• Can be taken on or restored
to a running cluster
• Creation and restore is fast

• Very stable medium.
• Can be used to recover from
data loss or corruption, even
if your cluster was destroyed.
• Can be typed as full, lightweight, or dataless.

Limitations

• Includes all data, state, and
metadata etc. created between snapshot creation and
restore.
• Are lost if the HDFS name
node fails, you lose multiple
disks at once, or the entire
cluster is destroyed
• Can only restored to the cluster they were taken from

• Backups require deleting the
existing cluster first.
• You are responsible for validating your backup configuration as viable for restoring a
cluster.
• Best practice recommends
you to maintain multiple
backups.
• Are typically large in size.

You should never restore
from a snapshot or backup
yourself, instead contact
ThoughtSpot Support for
help.

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Understand backup/snapshot schedules
Summary: Explains how schedules and gives examples.
You can schedule periodic snapshots and backups. For snapshots, ThoughtSpot comes configured with
a strongly recommended periodic snapshot policy. For backups, there is no such policy but you may
want to create one or several of your own configurations. This section helps to understand existing
schedules and how to configure new schedules.

Configuration format
ThoughtSpot uses a protocol buffer configuration file to hold snapshot and backup policies. There are
slight differences between the configuration of snapshots and backups. You’ll read more about these
later. However, the file format defines a schedule structure which is the same for both snapshots and
backups. The following example shows the schedule format:

schedule {
period {
number: integer
unit: MINUTE | HOUR | DAY
}
retention_policy {
bucket {
time {
number: integer
unit: MINUTE | HOUR | DAY
}
capacity: integer
}
}
offset_minutes_from_sunday_midnight: integer
}

The schedule has the following components:
period

Specifies the frequency in the chosen unit . You can
specify the unit as MINUTE , HOUR , or DAY .

retention_policy

Specifies retention intervals. Retention is on a first-infirst-out (FIFO) basis. So, the oldest result is always
discarded. You can specify the unit as MINUTE ,
HOUR , or DAY . You can specify multiple retention
buckets and they can have different retention policies.

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offset_minutes_from_sunday_midnight

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Determines the minute within the hour you’d like execution to start. Setting this to zero is equivalent to
midnight.

Work through an example schedule
In this section, you work through an example schedule. This is a working example that is the actual
default snapshot schedule set on every ThoughtSpot instance.

schedule {
period {
number: 1
unit: HOUR
}
retention_policy {
bucket {
time {
number: 1
unit: HOUR
}
capacity: 3
}
bucket {
time {
number: 4
unit: HOUR
}
capacity: 2
}
}
offset_minutes_from_sunday_midnight: 0
}

Under this policy, a snapshot is taken every hour starting at midnight. You can see that by combining the
period of 1 hour with the midnight offset of 0.

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schedule {
period {
number: 1
unit: HOUR
}
...
}
offset_minutes_from_sunday_midnight: 0
}

Using this frequency, a total of 24 snapshots are taken in a day.
1

…

If you were to specify a number of 2, the frequency changes. The first execution would start at midnight
but subsequent executions would happen every 2 hours as shown here:
2

…

You use the retention_policy to control how many snapshots are kept. In this example, the first
bucket retains a snapshot every three hours.

retention_policy {
bucket {
time {
number: 1
unit: HOUR
}
capacity: 3
}
...
}

When the fourth hour comes along, the snapshot from first hour is discarded as per FIFO behavior. So in
the 4th hour, you’ll have the snapshots from hours 2, 3, and 4 in this retention bucket.
1D

…

The second bucket retains the snapshot taken at four hour intervals.

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retention_policy {
...
bucket {
time {
number: 4
unit: HOUR
}
capacity: 2
}
}

It retains two of these four-hour-interval snapshots at any one time. By hour 9 during the day, you have
the snapshots from hour 4 and hour 8 in this second bucket.
1

…

Consider what you will have in the first bucket in hour 9? The first bucket will have the snapshots from
hour 9, 8, and 7.
At the end of the day, in the first bucket, you will have 22, 23, and 24th snapshot. While in the second
bucket, you will have the 20th hour and the 24th hour snapshots.
1

…

20R

22R

23R

24R

What if you changed the period frequency to every 2 hours? What would you have retained in your
buckets at hour 24?
1

…

18R

20R

22R

24R

As you can see, when defining a policy it can be helpful to graphically represent the frequency you
configure. Then, determine which time blocks are important to retain before determining your retention
bucket.

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Work with snapshots
Summary: A snapshot is a point-in-time image of your running cluster
you can use to restore the cluster back to a specific point in time.
In this section, you learn how to work with the default snapshot configuration that is enabled on ever
cluster and how to take manual snapshots of your own.

Create a manual snapshot
You should create a snapshot before making any changes to the environment, loading a large amount of
new data, or changing the structure of a table. You can have up to 20 manual snapshots at a time, after
which, you have to clear one before you are able to create another. If you need to delete a snapshot,
contact ThoughtSpot Support.

 Note: When you upgrade, all existing snapshots from the previous version of ThoughtSpot will
become manual snapshots.

Taking a snapshot is fast, about 20 seconds. It happens invisibly in the background of a running cluster.
If you would like to restore from a snapshot instead, contact ThoughtSpot Support.
To create a snapshot:
1. Log in to the Linux shell using SSH.
2. Initiate a snapshot, providing a name and reason for creating it: Snapshot names must be 44
characters or less.

$ tscli snapshot create

3. Check that the snapshot was created:

$ tscli snapshot ls

Configure periodic snapshots
By default, each ThoughtSpot cluster is configured to take automatic, periodic snapshots of your cluster.
This section explains how to learn more about the periodic snapshots in your cluster.
The default snapshot policy is enabled for every cluster. You can use the tscli snapshot-policy
show command to display the current policy for periodic snapshots.

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[admin@dogfood1 ~]$ tscli snapshot-policy show
schedule {
period {
number: 1
unit: HOUR
}
retention_policy {
bucket {
time {
number: 1
unit: HOUR
}
capacity: 3
}
bucket {
time {
number: 4
unit: HOUR
}
capacity: 4
}
bucket {
time {
number: 1
unit: DAY
}
capacity: 4
}
bucket {
time {
number: 1
unit: WEEK
}
capacity: 2
}
}
offset_minutes_from_sunday_midnight: 0
}
enabled: true

This policy starts at midnight on Sunday. It retains the snapshots from the last three 4-hour intervals and
two snapshots from two of the previous 4 hour intervals. That means, there are 7 periodic snapshots
retained overall. For detailed information about understanding the schedule, see Understand backup/
snapshot schedules.

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You shouldn’t change this default policy unless instructed to by support. If you have to adjust it for some
reason, you can use, tscli snapshot-policy update command. This opens the current policy in an
editor. Your policy should never retain more than 20 snapshots at any point in time. Exceeding this
number can impact cluster performance.
You cannot delete the snapshot policy. However, you can disable the policy by executing the tscli
snapshot-policy disable command. And you can re-enable it by running, tscli snapshot
enable-policy .

 Warning: Backups rely on the snapshot system. For this reason, you should never disable the
periodic snapshot system. For example, if you have disabled the periodic snapshots and periodic
backups are enabled, then the periodic backup may use a very outdated snapshot or it may fail all
together.

To check your current periodic snapshot policy:
1. Log in to the Linux shell using SSH.
2. Enter tscli snapshot-policy show to view the policy.

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Understand backup modes
A backup is a procedure that stores a snapshot outside of a ThoughtSpot cluster. You can use a backup
to restore a cluster to a prior state, a differently configured appliance, or move it to from an appliance to
a virtual cluster or vice versa. Other advanced administrative operations also use backups.
You can create a manual backup or configure an automated, periodic backup A backup stores snapshot
outside of a ThoughtSpot cluster. For manual backups, the system creates a backup using the named
snapshot you specify. For periodic backups, the system uses the most recent snapshot to create the
backup.

 Warning: You should never disable the periodic snapshot system as backups rely on it. For
example, if you have disabled the periodic snapshots system and periodic backups are enabled,
then the periodic backup may use a very outdated snapshot or it may fail all together.

Backups are usually stored on a NAS (network attached storage) file system but you can store them on a
local disk as well. When creating a backup, ThoughtSpot copies a release tarball and several supporting
files to a disk you specify. Storing these supporting files takes about 10 GB of extra space beyond the
backup itself. The final backup image is smaller because these extra files are removed after the backup
completes successfully. So, make sure you have enough disk space both to take a backup and store the
result. Use the tscli storage df command to identify the amount of space available.
You can create a backup using one of three modes, full, lightweight or dataless.

Full backups
Full backups are entire backups of the cluster with all data, whether loaded from the web interface or
from tsload . This is the best mode for restoring a cluster and all your data. Once a FULL backup is
created, you can move them between clusters, even if the cluster configuration is different. Full backups
can be as large as 20 GB in addition to the 5 GB of additional files. Some installations can exceed these
limits, this is why it is important to test your backup configuration.
Before creating a manual backup or configuring automated backups, make sure there is enough disk
space on the target disk. Consider an example, where you want to store three backups. If the backup
itself takes 18GB, you need about 18 + 5 = 23 GB of free disk space. Don’t forget that the backup size
can grow over time, so you should occasionally check to ensure you are not in danger of running out of
disk space to store backups.

Lightweight backups
Lightweight backups contain everything that makes up a cluster so they contain the following:
• Cluster configuration (SSH, LDAP, etc.)
• In-memory data cache
• All data that is stored unencrypted in HDFS
• Data uploaded by users
• Metadata for the data store
• Users, groups and permissions

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• Objects created by users (pinboards, worksheets, and formulas) with their shares and
permissions.
• Data model and row-level security rules.
Data loaded through ThoughtSpot Loader ( tsload ), ODBC/JDBC drivers, and Data Connect is
excluded. The expectation is that data loaded via tsload is from external sources and so can be reloaded after the cluster is restored. An exception is if these mechanisms were used to load data into
tables that were first created through CSV import (that is, a user first loaded the tables via the GUI). In
this case, the data, like the tables they were loaded into, are saved.

Dataless backups
A dataless backup saves a backup of the schema (metadata), with no data. Dataless backups allow you
to send a copy of your cluster metadata to ThoughtSpot Support for troubleshooting without
compromising data security and privacy. The size of a dataless backup is usually within 10’s of
megabytes provided you do not have customized binaries.
When restoring from a dataless backup, you must supply the correct release tarball, since this type of
backup does not include the software release.

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Create a manual backup
Use this procedure when you want to manually create a backup. If you would like to restore from a
backup, contact ThoughtSpot Support.
You create a manual backup from an existing snapshot. So, you must identify an existing snapshot to
use or take a new snapshot first. The time required to take a backup depends on the data size. Taking a
backup does not take long, and happens in the background while the cluster is running.
1. Log in to the Linux shell using SSH.
2. Create a manual snapshot or find a snapshot you want to use. To find a snapshot you want to
back up use the following command:

$ tscli snapshot ls

-------------------------------------------------------------------------Name
:
Reason
:
Hdfs snapshot :
Start
:
End
:
Size(Full)
:
Size(LW)
:
Size(Dataless):

pre330
pre3.3.0
pre330
Wed May 4 18:07:32 2016
Wed May 4 18:08:23 2016
13.24 GB
4.96 GB
39.76 MB

-------------------------------------------------------------------------...

3. Make sure you have enough room on the target disk.
In addition to the size of the snapshot, you will need 10 to 12 GB of disk space. This is
because the process requires space for temporary files. You can use the df command to
check disk size.

$ df -h

4. Create the backup, designating the type of backup, the snapshot name, and a directory:
Choose the mode of backup you want to create, either full, lightweight, or dataless. The
destination directory is created for you; do not specify an existing directory. The BASE value
is the name

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$ tscli backup create [-h]
[--mode {full|light|dataless}]
[--type {full}]
[--base snapshot_name>]
[--storage_type {local|nas}][--remote]

5. Check that the backup was created:

$ tscli backup ls

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Configure periodic backups
You can configure ThoughtSpot to backup automatically at specified times. The policy allows you to
control the type, frequency, retention periods (first-in-first-out), and output location for a periodic
backup.
A periodic backup uses the same steps as creating a backup manually. However, you do not need to
specify a snapshot name, the system uses the most recent backup. You can backup to a local file
system or mount a NAS (network attached storage) file system to hold the backup. A NAS is
recommended. Make sure you have adequate space to store the number of backups you want to
archive.
The format for a policy includes the following:

name: "name_for_backup"
param {
mode: FULL | DATALESS | LIGHTWEIGHT
type: STANDALONE
}
schedule {
period {
number: integer
unit: MINUTE | HOUR | DAY
}
retention_policy {
time {
number: integer
unit: MINUTE | HOUR | DAY
}
capacity: integer
}
}
offset_minutes_from_sunday_midnight: integer
}
directory: "NAME"
storage_type: NAS | LOCAL

Before creating a policy, make sure you have read Understand backup/snapshot schedules for
information on configuring a schedule element. In addition, you must specify:
Element

Description

mode

The backup mode. FULL backups are necessary for restoring a cluster. See
Work with backups for details on each backup mode.

type

Currently, only STANDALONE is supported.

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Element

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Description

directory

The location on the disk to place the backup.

storage_type

The type of storage you are using. NAS storage is recommended for FULL
backups.

Backups cannot start when another backup is still running. So, choose a reasonable frequency for the
mode in you policy. For example, a FULL backup takes longer than a DATALESS backup. Consider the
load on the system when configuring. Do not backup up when the system would experience a heavy
load. For example, you may want to take FULL backups late in the evening or on weekends.
The retention system deletes the oldest stored backup and the corresponding snapshot on a first-in firstout basis (FIFO). This means that if you set a bucket retention of 1 the system stores a single backup at
any one time. The system deletes the older backup after the new full backup is successful.
To configure periodic backups:
1. Log in to the Linux shell using SSH.
2. Find a directory with enough disk space to support the retention_policy number you
configure.
You can use df -h to see free disk space and tscli snapshot ls to view existing
snapshots and their size on disk.
3. Use the tscli backup-policy create command.
The command opens a vi editor for you to configure the backup policy.
4. Write and save the file to store your configuration.
By default, newly created policies are automatically enabled. To disable a policy, use the
tscli backup-policy disable command.
5. Verify the policy using the tscli backup periodic-config command.

Doing more with backup
The following table lists some additional backup commands you can use.
To

Command

List present backup policies.

tscli backup-policy ls

Show a backup policy.

tscli backup-policy show

Check the status of a policy.

tscli backup-policy status

Change an existing policy.

tscli backup-policy update

Disable or enable an existing policy.

tscli backup-policy disable or enable

Delete a policy

tscli backup-policy delete

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Finally, you can time a crontab job with your periodic backup configuration to move a backup to
longer term storage. Simply create a crontab job that moves the backup to a location outside of the
directory defined in the periodic schedule.

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About restore operations

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About restore operations
When restoring to a running cluster that where the ThoughtSpot software was not updated, you’ll usually
use a snapshot. But in the case where you’ve updated the cluster to a new release, the configuration has
changed significantly, or you’re restoring to a different cluster, you’ll need to restore from a backup.
Restoring from backup require that you first delete the old cluster. Changes to a cluster that require
restoring from a backup instead of a snapshot include:
• Removal of a node.
• Restoring to a different cluster from the one where the snapshot/backup was taken.
• Restoring to a cluster running a different release from the one where the snapshot/backup
was taken.
You should never restore from a snapshot or backup yourself. To perform a restore from a snapshot or
backup, contact ThoughtSpot Support.

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About troubleshooting

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About troubleshooting
The information here provides very basic troubleshooting. For more detailed troubleshooting, Contact
ThoughtSpot.
• Get your configuration and logs
For troubleshooting on specific incidents or cluster problems, getting a log bundle can help.
• Network connectivity issues
If network connectivity to and from ThoughtSpot is not working, try using these steps to find
and correct the issue.
• Check the timezone
ThoughtSpot comes configured with the timezone where it is to be installed.
• Browser untrusted connection error
If you are not using a SSL certificate for authentication, users will see an untrusted connection
error in their browser when accessing ThoughtSpot. The error looks slightly different
depending upon the Web browser being used.
• Characters not displaying correctly
Your CSV files are more likely to load smoothly if they are encoded with UTF-8. If you’re
having problems with some characters rendering incorrectly, you can convert the files to
UTF-8 encoding before loading the data.
• Clear the browser cache
You might occasionally see unexpected behavior that is due to the Web browser caching
information from ThoughtSpot. In this case, clearing the browser cache and reloading the
page should resolve the problem.
• Cannot open a saved answer that contains a formula
• Data loading too slowly
Some tables may take an unusually long time to load due to a high data version issue. This
issue normally arises when ThoughtSpot completes an upgrade or the system is recovering
after a crash.
• Search results contain too many blanks
If you find that your search results contain too many blanks when your data source is a
worksheet, there is a simple adjustment you can make to fix this.

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Get your configuration and logs

February 06, 2019

Get your configuration and logs
For troubleshooting on specific incidents or cluster problems, two things are important. Understanding
your current configuration and getting a log bundle.

Check your configuration
1. Log into the ThoughtSpot cluster as the admin user.
2. Use the tscli feature subcommand to display your current configuration.

How to get logs
There are two ways to get logs:

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• When ThoughtSpot encounters a problem, a red bar displays in the browser with an error
message. You can click on What Happened? in the error message for more details. To
download related logs, click Download Trace
Trace. Send the logs as an email attachment to the
support contact that is provided. Clicking Report Problem will also send the logs as an email
attachment to your administrator.

• You can generate a log bundle using the tscli command tscli logs collect if you are
comfortable with Linux. The command lets you specify which logs to collect and from what
time periods.
Usage for this command is:

tscli logs collect
--include
[--exclude ]
[--since
| --from
--to ]
[--out ]
[--maxsize ]
[--sizeonly]

The full list of all selectors is:
•

all collects all of the logs listed from the system and the ThoughtSpot
application.
• system collects all system logs, e.g. syslog, upstart, mail logs, etc.
• ts collects all logs from the ThoughtSpot application. This includes falcon, sage,
orion core (cluster management), etc.
• orion collects all orion logs including cluster management, hdfs, zookeeper, etc.
Detailed syntax and options are listed in the tscli command reference.

Examples
Here are some examples of usage for the command tscli logs collect :
To collect all logs from the past day to the default location ( /tmp/logs.tar.gz ):

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$ tscli logs collect --include all --since 1d

In this example, all is a selector for all the available logs.
In most cases, you’ll probably use the selector ts to only capture logs for the ThoughtSpot application:

$ tscli logs collect --include ts --since 2d

For debugging cluster management issues, use a command like this one, which collects logs for system
and orion from the past 2 hours. The output is written to /tmp/debug.tar.gz as specified using --out :

$ tscli logs collect --include system,orion --since 2h --out /t
mp/debug.tar.gz

This command collects logs from a specific time window:

$ tscli logs collect --include system,orion --from 20150520-1
2:00:00 --to 20150522-12:30:00

Advanced usage alert! You can also use --include and --exclude to specify filesystem paths as a
glob pattern. This works like the Linux find(1) command. Pass all the entries in --include starting with
/ to find(1), and all entries in --exclude which are not selectors to find(1) using the -not -path
flag.

$ tscli logs collect --include system,orion --exclude *hadoo
p*,*zookeeper* --since 2h

The above command collects all system and all orion logs, but excludes hadoop (hdfs) and zookeeper
logs. See Upload logs to ThoughtSpot Support about using a secure file sever to collect log files or other
files needed for troubleshooting. You can easily send log files to this file serve directly from the
ThoughtSpot instance.

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Upload logs to ThoughtSpot Support

February 06, 2019

Upload logs to ThoughtSpot Support
ThoughtSpot Support uses a secure file sever to collect log files or other files needed for
troubleshooting. You can easily send log files to this file serve directly from the ThoughtSpot instance.

Metrics collection
ThoughtSpot collects the diagnostic information from your system on an ongoing basis: there is no time
needed to collect diagnostic information after a problem is reported. These metrics allow for:
• Our support team can begin working to remediate any issue with you at once.
• Metrics provides direct visibility to the ThoughtSpot team on your system’s limits. Therefore,
our Support team can proactively identify critical threshold issues and work to prevent
failures. Metrics also help reduce SLA times as the team can debug much faster.
• ThoughtSpot can tune search algorithms by studying search history and schema.
• ThoughtSpot analyzes expensive and complex query patterns to look for performance
optimizations.
Finally, the metrics pipeline allows ThoughtSpot to identify application-use patterns that contribute to
performance bottlenecks with specific browsers and help your team prevent or alleviate them.

Other log uploads
Before you can upload a file to the secure file server:
1. Configure the connection to the file server.
2. Obtain the directory path on the file server.
The server directory path for uploading a file is formatted like this example: /Shared/
support/ . If you do not know the customer name, contact ThoughtSpot Support.
You can upload files directly to the file server using this procedure:
1. Log in to the Linux shell using SSH.
2. Navigate to the directory where the file to be uploaded is located.
3. Issue the command to upload the file, specifying the file name and directory path:

$ tscli fileserver upload --file_name --server_d
ir_path

When your upload succeeds, you will see a confirmation message.

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Network connectivity issues

February 06, 2019

Network connectivity issues
If network connectivity to and from ThoughtSpot is not working, try using these steps to find and correct
the issue.
To troubleshoot network connectivity for ThoughtSpot:
1. Make sure that the network cables are connected correctly.
2. Check that the network cable is connecting the nodes to the network switch.
3. Try replacing the cable with a cable from a known working system to rule out a bad cable or
switch connectivity issues.
4. Make sure the eth0 interface is connected to the network by issuing: ethtool eth0 The
port that’s currently connected will have “link detected” in the last line of the output.
5. If the networking settings have been reconfigured, reboot each of the nodes.

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Check the timezone

February 06, 2019

Check the timezone
ThoughtSpot comes configured with the timezone where it is to be installed. Data is imported based on
the timezone of the node from which tsload or tql is run. To see the timezone your ThoughtSpot
node is running under, log into the server as the thoughtspot user and run the date command:

[thoughtspot@ts.server etc]$ date
Tue Feb 20 09:07:04 PST 2018

To see the current timezone used by the ThoughtSpot application, choose Admin > Cluster Manager and
review the Cluster Details
Details:

The timezones should match.
Sometimes the timezone that is listed by date is not the active timezone for the ThoughtSpot
application and the application needs to be reset. If you need to change the timezone, contact
ThoughtSpot Support and they will change the timezone for you. You may need to change the timezone
if you move the server between data centers.

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Browser untrusted connection error

February 06, 2019

Browser untrusted connection error
If you are not using a SSL certificate for authentication, users will see an untrusted connection error in
their browser when accessing ThoughtSpot. The error looks slightly different depending upon the Web
browser being used.
ThoughtSpot uses secure HTTP (the HTTPS protocol) for communication between the browser and
ThoughtSpot. By default there is no SSL certificate for authentication. This must be added by the site
administrator. If the site administrator has not added the certificate, the browser warns the user.
Browser

Warning

Google Chrome

The site’s security certificate is not trusted!

Mozilla Firefox

This Connection is Untrusted

If you see the warning message, choose one of the following options:
• Ask the site administrator to install the certificate.
• Ask the site administrator to turn off SSL using this command in the shell on the ThoughtSpot
instance:

$ tscli ssl off

• You can choose to ignore the message, and access ThoughtSpot without SSL.

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Characters not displaying correctly

February 06, 2019

Characters not displaying correctly
Your CSV files are more likely to load smoothly if they are encoded with UTF-8. If you’re having problems
with some characters rendering incorrectly, you can convert the files to UTF-8 encoding before loading
the data.
You might see unexpected characters in your data, especially characters whose ASCII values are at the
high and low end of possible values. Some examples of characters that can appear incorrectly are: æ, ñ,
ä, í, ö.
If this happens, your data will look like this:

Instead of displaying correctly like this:

To encode your data as UTF-8:
1. On Windows, open your CSV file in Notepad. Save the file as CSV with the Unicode option.
2. On Linux or MacOS, issue a command like:

$ iconv -f -t UTF-8 .csv > .csv

3. Reload the data.
4. Attempt to import it again.

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Clear the browser cache

February 06, 2019

Clear the browser cache
You might occasionally see unexpected behavior that is due to the Web browser caching information
from ThoughtSpot. In this case, clearing the browser cache and reloading the page should resolve the
problem. You can usually resolve these situations by clearing the browser cache:
• During a ThoughtSpot session, the browser suddenly displays a white screen and reloading
does not fix the problem. This is due to a self-signed SSL certificate that has timed out during
the session.
• When accessing the Help Center, you see a login screen. This is due to a problem during
automatic authentication in the Help Center, after which the bad login gets cached by the
browser.
To resolve any of these situations, clear the browser cache:
1. Clear the browser cache.
This works a little differently on individual browser versions and operating systems. For
example, when using Chrome, to get to the browser cache settings, navigate to:

chrome://settings/clearBrowserData

2. Click Clear browsing data
data.
This is the name of the button on Chrome. The name may vary slightly on other browsers.
3. Reload the page.

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February 06, 2019

For example, on Chrome you would click the Reload icon:

Now the problem should be fixed, and the page will appear as expected.

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Cannot open a saved answer that contains a formula

February 06, 2019

Cannot open a saved answer that
contains a formula
When working with formulas, keep in mind the data types they return. You may occasionally see
unexpected results, or even be unable to open a saved answer, due to problems with data types and
formulas.
In this scenario, “data type” refers the data type as defined in the column definition when creating the
schema (INT, TIMESTAMP, VARCHAR, etc.).
When you define a formula, both the data type it returns is set automatically. This can lead to problems,
if you build another formula that uses the output of the first formula as input. This can be hard to
understand, so an example will be helpful.
Suppose you have created a worksheet that contains a formula called “weekday” defined as:

day_of_week(date)

The output of that formula is the day of the week (Monday, Tuesday, etc.) returned as a text string
(VARCHAR, ATTRIBUTE).
Then suppose you create an answer using the worksheet as a source. And in the answer, you create
another formula on top of the formula column in the worksheet. This formula is supposed to return the
day of the week that is two days after the given day of the week:

weekday + 2

In this case, you have effectively created a formula on top of another formula. This works fine, so long as
the data types in the worksheet formula can work in the answer formula. If not, you may not be able to
save the answer, or open it once it has been saved. Here, the second formula you created does not
work, because it is invalid. It is trying to subtract a number from a text string.
If you encounter this issue, you will need to open the worksheet and edit its formula so that it returns the
type expected by the formula that was built on top of it. In this case, a numeric data type.
You must change the underlying worksheet column to use day_number_of_week instead of
day_of_week. This is because day_number_of_week returns a numeric data type.
Here are the steps to resolve an issue like this:
1. Open the underlying worksheet that contains the formula whose output data type you need to
change.
2. Click on the formula name to edit the formula.

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February 06, 2019

3. In the Formula Builder, modify the formula, so that it returns the expected data type.
There are data type conversion formulas available to make this easier. To view them and their
syntax, open the Formula Assistant
Assistant, and expand the section called Conversion
Conversion.

4. Make your changes, and saving the formula by clicking Save
Save.
5. Save the worksheet by clicking Save
Save.
6. Now you will be able to open the answer that was created on top of the worksheet.

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Data loading too slowly

February 06, 2019

Data loading too slowly
Some tables may take an unusually long time to load due to a high data version issue. This issue
normally arises when ThoughtSpot completes an upgrade or the system is recovering after a crash.
The data version is the number of loads that have been historically applied to a table. Every completed
load increments the version number of the table by one. ThoughtSpot would need to process each
version of the table during restoration, which could increase the time it takes to build the table.
There are a few steps you can take to check for a high data version issue and fix it. To improve data
loading speed, run the following command to find the number of tables that are building and their names

tscli cluster status --mode table

You may notice that a few small tables are taking up a lot of time to be built. This could simply be due to
the deceivingly large size of the table. There is also the chance it could be due to a high data version
issue. To determine if this is a high data version issue, check the size of the table by running the
following command:

echo 'show statistics for server;' | tql

If there is a large number of rows in the table, go on to shard the table. If the table has a small number of
rows, then the slow loading speed is caused by a high data version issue, and you do not have to shard
the table. Use the compact table functionality to trim the table down to its actual size:

tql> compact table ;

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Page 300

Search results contain too many blanks

February 06, 2019

Search results contain too many blanks
If you find that your search results contain too many blanks when your data source is a worksheet, there
is a simple adjustment you can make to fix this.
If you find that the charts and tables built on a worksheet contain a large number of null values (which
display as {blank} in the web browser), you can fix this by changing the inclusion rule for the worksheet.
An inclusion rule that specifies Exclude Empty Rows (Inner Join) will reduce the number of null values in
the result. Imagine a worksheet that includes data about a retail grocery store. There are rows in the
worksheet from these source tables:
Table Name

Description

sales

Fact table with sales made per product per store.

products

Dimension table with information about every product.

stores

Dimension table with information about every store.

When creating the worksheet, suppose you choose Include Empty Rows (Left Outer Join) for the
inclusion rule and Progressive Joins for the join rule. In this case, if you type “product name” in your
search, you’ll see a list of all the products that exist. Suppose you then add “store name” to your search.
You will see a lot of null ({blank}) values in the result. This happens because the columns “store name”
and “product name” are joined through the fact table, “sales”. So for every product that has never been
sold in a particular store, you’ll see {blank} in the “store name” column. This may be what you want to
see, in which case, you can leave the worksheet as is, and choose Exclude for the {blank} values in your
table or chart, whenever you don’t want to see them.
However, in may cases, including all the {blank} values could confuse end users. So if you encounter this
problem, you can edit the worksheet, and change the inclusion rule to Exclude Empty Rows (Inner Join)
Join).
Now when searching for “store name” and “product name” on the worksheet, users will not be
overwhelmed by null values. They’ll only see the rows where a particular product has been sold in a
particular store.

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Keyword reference

February 06, 2019

Keyword reference
You can use keywords when asking a question to help define your search. This reference lists the
various keywords. You can also see this list of keywords and examples from within the help center.

Keywords in Other Languages
Currently, we offer the following keyword translations.
日本語

中文 (简体)

Deutsche

Español
(latín)

Español
(España)

Français
(Canada)

Français
(France)

Português
(Brasil)

Português
(Portugal)

Italiano

Dansk

Suomi

Svenska

Norsk

Nederland

General
Keyword

Examples

top

bottom

•
•

top sales rep by count sales for average revenue > 10000

•
•
•

bottom revenue average

sales rep average revenue for each region top

bottom revenue by state
customer by revenue for each sales rep bottom

top 10 sales rep revenue

bottom 25 customer by revenue for each sales rep

sort by

•
•

revenue by state sort by average revenue
revenue by customer sort by region

Date
Keyword

Examples

after

order date after 10/31/2014

before

order date before 03/01/2014

between … and ...

order date between 01/30/2012 and 01/30/2014

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Keyword reference

Keyword

February 06, 2019

Examples

daily year-over-year

growth of revenue by order date daily year-over-year

daily

shipments by region daily

day

count monday restaurant

day of week

revenue by day of week last 6 months

day of week

count shipments Monday

n days for each month

sales last 2 days for each month

n days for each quarter

revenue last 15 days for each quarter

n days for each week

total sold last 2 days for each week

n days for each year

revenue last 300 days for each year

growth of … by … daily

growth of sales by order date daily

growth of … by …
monthly

growth of sales by date shipped monthly sales > 24000

growth of … by …
quarterly

growth of sales by date shipped quarterly

growth of … by …
weekly

growth of sales by receipt date weekly for pro-ski2000

growth of … by …
yearly

growth of sales by date closed yearly

growth of … by ...

growth of sales by order date

n hours for each day

sales last 2 hours for each day

last day by

customers last day by referrer

last month by

customers last month by day

last n days

visitors last 7 days

last n quarters

visitors last 2 quarters by month by campaign

last n weeks

visitors last 10 weeks by day

last quarter

customers last quarter sale > 300

last week

customers last week by store

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Keyword reference

Keyword

February 06, 2019

Examples

last year

top 10 customers last year by sale by store for region west

last n years

visitors last 5 years by revenue for sum revenue > 5000

month to date

sales by product month to date sales > 2400

month year

commission by sales rep February 2014

month

commission January

month

revenue by month last year

monthly year-overyear

growth of revenue by receipt date monthly year-over-year

monthly

commission > 10000 monthly

n months for each
quarter

cost last 2 months for each quarter

n months for each
year

last 8 months for each year

n days ago

sales 2 days ago

n months ago

sales 2 months ago by region

n months

visitors last 6 months for homepage visits > 30 by month

n quarters ago

sales 4 quarters ago by product name contains deluxe

n weeks ago

sales 4 weeks ago by store

n years ago

sales 5 years ago by store for region west

n years

opportunities next 5 years by revenue

next day

shipments next day by order

next month

appointments next month by day

next n days

shipments next 7 days

next n months

openings next 6 months location

next n quarters

opportunities next 2 quarters by campaign

next n weeks

shipments next 10 weeks by day

next quarter

opportunities next quarter amount > 30000

next week

shipments next week by store

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Keyword reference

February 06, 2019

Keyword

Examples

next year

opportunities next year by sales rep

quarter to date

sales by product quarter to date for top 10 products by
sales

quarterly year-overyear

growth of revenue by date shipped quarterly year-over-year

quarterly

sales quarterly for each product

n quarters for each
year

last 2 quarters for each year

today

sales today by store

week to date

sales by order date week to date for pro-ski200

week

revenue by week last quarter

weekly year-over-year

growth of revenue by date shipped weekly year-over-year

weekly

revenue weekly

n weeks for each
month

sales last 3 weeks for each month

n weeks for each
quarter

last 2 weeks for each quarter

n weeks for each year

last 3 weeks for each year

year to date

sales by product year to date

year

revenue by product 2014 product name contains snowboard

yearly

shipments by product yearly

yesterday

sales yesterday for pro-ski200 by store

Time
Keyword

Examples

detailed

ship time detailed

last minute

count homepage views last minute

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Keyword reference

Keyword

February 06, 2019

Examples

last hour

count unique visits last hour

n minutes

count visitors last 30 minutes

n hours

count visitors last 12 hours

hourly

visitors by page name hourly

n minutes
ago

sum inventory by product 10 minutes ago

n hours ago

sum inventory by product by store 2 hours ago

Text
Keyword

Examples

begins with

product name begins with 'pro'

contains

product name contains "alpine" description contains "snow shoe"

ends with

product name ends with 'deluxe'

not begins
with

product name not begins with "tom's"

not contains

product color not contains 'tan' product color not contains 'red'

not ends
with

product name not ends with "trial"

similar to

course name similar to 'hand'

not similar
to

course name not similar to 'hand'

Number
Function
sum

Examples
sum revenue

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Keyword reference

Function

February 06, 2019

Examples

average

average revenue by store

count

count visitors by site

max

max sales by visitor by site

min

min revenue by store by campaign for cost > 5000

standard
deviation

standard deviation revenue by product by month for date after
10/31/2010

unique
count

unique count visitor by product page last week

variance

variance sale amount by visitor by product for last year

Comparative
Function

Examples

all

between... and

revenue between 0 and 1000

vs, versus

revenue east vs west

sum sale amount by visitor by product for last year
sale amount > 2000

unique count visitor by product by store for sale
amount < 20

count calls by employee lastname >= m

count shipments by city latitude <= 0

unique count visitor by store purchased products = 3
for last 5
days

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sum sale amount region != canada region != mexico

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Keyword reference

February 06, 2019

Location
Keyword

Examples

near

revenue store name county near san francisco

near... within n miles|km|meters

revenue store name county near alameda within 50
miles

farther than n miles|km|meters
from

average hours worked branch farther than 80 km from
scarborough

Location keywords only work for searches where the data source includes latitude/longitude data.

Period
Keyword

Example

quarter (date)

quarter (purchase date)

quarter of year (date)

quarter of year (purchase date)

month of quarter (date)

month of quarter (purchase date)

week of year (date)

week of year (ship date)

week of quarter (date)

week of quarter (ship date)

week of month (date)

week of month (ship date)

day of year (date)

day of year (ship date)

day of quarter (date)

day of quarter (ship date)

day (date)

day (ship date)

day of month (date)

day of month (order date)

day of week (date)

day of week (order date)

hour (datetime)

hour (timestamp)

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TQL reference

February 06, 2019

TQL reference
TQL is the ThoughtSpot language for entering SQL commands. This reference lists TQL commands you
can use to do things like creating a schema or verifying a data load.

About using TQL
You can use TQL either through the ThoughtSpot application’s web interface or the command line
interface in the Linux shell.
Use --query_results_apply_top_row_count flag to limit the number of result rows
returned by a query. For example:
$ tql --query_results_apply_top_row_count 100

As a best practice, you should enclose object names (database, schema, table, and column) in double
quotes, and column values in single quotes. When referring to objects using fully qualified object names,
the syntax is:

"database"."schema"."table"

To get help on SQL when using TQL, enter help on the command line.
You can use TQL to view and modify schemas and data in tables. Remember to add a semicolon after
each command. Commands are not case sensitive but are capitalized here for readability.

 Note: Worksheets and pinboards in ThoughtSpot are dependent upon the data in the
underlying tables. Use caution when modifying tables directly. If you change or remove a schema
on which those objects rely, the objects could become invalid.

View schemas and data
Syntax
SHOW DATABASES

Description
Lists all available databases.
Examples:
SHOW DATABASES;

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TQL reference

Syntax

USE

February 06, 2019

Description
Switches the context to the specified database. This is required if queries
do not use fully qualified names (database.schema.table) for specifying tables.
Examples:
USE "fruit_database";

SHOW SCHEMAS

Lists all schemas within the current database. For example:
SHOW SCHEMAS;

SHOW TABLES

Lists all tables within the current database by schema. For example:
SHOW TABLES;

SHOW TABLE

Lists all the columns for a table. For example:

SHOW TABLE "locations";

SCRIPT SERVER

Generates the TQL schema for all tables in all databases on the server. For
example:
SCRIPT SERVER;

SCRIPT DATABASE

Generates the TQL schema for all tables in a database. For example:

SCRIPT DATABASE "fruit_database";

SCRIPT TABLE

Generates the TQL schema for a table. For example:

SCRIPT TABLE "vendor";

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TQL reference

Syntax

February 06, 2019

Description
Shows specified set of table data.

SELECT

FROM

If you do not specify the TOP number of rows to select, the top 50 rows will
be returned by default. The number of rows to return can be set using the
TQL command line flag:

[WHERE ]
[GROUP BY ]

You can use the following aggregation functions:

[ORDER BY ]

sum
count
count distinct
stddev
avg
variance
min
max

You can use the following date functions:
• absyear
• absmonth
• absday
• absquarter
• date
• time
For example:
SELECT TOP 10 "quantity" FROM "sales_fact";
SELECT COUNT(*) FROM "vendor";
SELECT "vendor", SUM("quantity") FROM "sales_fact" GROUP BY
"vendor";
SELECT "vendor", SUM("amount") FROM "vendor", "sales_fact"
WHERE "sales_fact"."vendorid" = "vendor"."vendorid"
AND "amount" > 100 GROUP BY "vendor" ORDER BY "amount"
DESC;
SELECT "vendor", SUM("quantity") FROM "sales_fact"
GROUP BY "vendor" LIMIT 10;

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TQL reference

February 06, 2019

Schema creation
Syntax

Description

Creates a database. For example:

CREATE DATABASE

Creates a schema within the current database. For example:

CREATE SCHEMA

CREATE SCHEMA "fruit_schema";

Creates a table with the specified column definitions and constraints.

CREATE TABLE
(
[]) [PARTI-

Do not specify relationship constraints ( FOREIGN KEY or RELATIONSHIP ) in the CREATE TABLE statement. Instead, define these using ALTER TABLE statements at the end of your TQL script, after creating your
tables. This method guarantees that tables are created before they are
referenced in the constraint definitions. For example:

TION BY HASH () [KEY
("")]])

CREATE TABLE "vendor" ("vendorid" int, "name" varchar(255));
CREATE TABLE "sales_fact" ("saleid" int, "locationid" int,
"vendorid" int,
"quantity" int, "sale_amount" double, "fruitid" int,
CONSTRAINT PRIMARY KEY("saleid")) PARTITION BY HASH(96) KEY
("saleid");

Schema modification
Syntax

Description

DROP DATABASE

Drops a database and all of its schemas and tables. For example:

ThoughtSpot Administration Guide

DROP DATABASE "fruit_database";

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TQL reference

February 06, 2019

Syntax

Description

DROP SCHEMA

Drops a schema within the current database, and drops all of the tables in
the schema. For example:
DROP SCHEMA "fruit_schema";

DROP TABLE

Drops a table. For example:

DROP TABLE "location";

TRUNCATE TABLE

Removes all data from a table, but preserves its metadata, including all
GUIDs, relationships, etc. This can be used to force a new schema for a
table without losing the metadata.
However, this operation removes all existing data from the table and must
be used with caution. You must reload the data following a TRUNCATE , or
all dependent objects (worksheets and pinboards) in ThoughtSpot will become invalid. For example:
TRUNCATE TABLE "location";

Alters a table to add, drop, or rename a column.
ALTER TABLE

ADD|DROP|RENAME

When you add a column to an existing table, you must provide a default
value to use for existing rows. For example:

COLUMN
ALTER TABLE "cart" ADD COLUMN "nickname" varchar(255) DE-

FAULT 'no
nickname';
ALTER TABLE "cart" DROP COLUMN "nickname";
ALTER TABLE "cart" RENAME COLUMN "nickname" TO "shortname";

ALTER TABLE
DROP CONSTRAINT PRIMARY
KEY;

Drops the primary key from a table.
Note that if you then add a new primary key, the same upsert behavior will
be applied as with adding any primary key. This can result in data deletion,
so make sure you understand how the upsert will affect your data ahead of
time. For example:
ALTER TABLE "sales" DROP CONSTRAINT PRIMARY KEY;
ALTER TABLE "sales" ADD CONSTRAINT PRIMARY KEY ("PO_number");

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Syntax

Description

ALTER TABLE
DROP [FOR-

Drops the named foreign key or relationship between two tables. For example:

EIGN KEY| RELAALTER TABLE "sales_fact" DROP CONSTRAINT FOREIGN KEY

TIONSHIP]
;

"FK_PO_number";
ALTER TABLE "fruit_dim" DROP RELATIONSHIP "REL_dates";

ALTER TABLE
DROP [CONSTRAINT FOREIGN
KEY
[] |
RELATIONSHIP

You must use this syntax when dropping relationships between tables created before ThoughtSpot version 3.2. This is because relationships could
not be named in older versions.
Drops the foreign key or relationship between two tables where you cannot
reference it by relationship name. If the relationship was created without a
name, use:
• the name of the referenced table, for a foreign key.
• the name of the related table, for a relationship.

[WITH
];

If you drop a foreign key without specifying the referenced table, all foreign
keys from the table you are altering will be dropped.
Examples:
ALTER TABLE "shipments" DROP CONSTRAINT FOREIGN KEY "orders";
ALTER TABLE "wholesale_buys" DROP RELATIONSHIP WITH "retail_sales";

Drops all relationships that have wholesale_buys as a source.
ALTER TABLE "wholesale_buys" DROP RELATIONSHIP;

Drops all foreign keys from wholesale_buys.
ALTER TABLE "wholesale_buys" DROP CONSTRAINT FOREIGN KEY;

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Syntax

Description

ALTER TABLE

Changes the partitioning on a table by doing one of:

[SET DI-

• re-sharding a sharded table
• changing a replicated table to a sharded table
• changing a sharded table to a replicated (unsharded) table

MENSION | SET
FACT [PARTITION BY
HASH
[()]
[KEY()]]]

By default, ThoughtSpot does not shard dimension tables.
To change the partitioning on a table, or to change a dimension table to a
sharded table, use ALTER TABLE...SET FACT PARTITION BY HASH...;
To make a sharded table into a dimension table (replicated on every node),
use ALTER TABLE...SET DIMENSION; command.
Examples of this statement:
ALTER TABLE "sales_fact" SET FACT PARTITION BY HASH (96) KEY
("PO_number");
ALTER TABLE "fruit_dim" SET DIMENSION;

ALTER TABLE
MODIFY

Changes the data type of a column. This can have implications on sharding
and primary key behavior. See About data type conversion. For example:

COLUMN
ALTER TABLE fact100 MODIFY COLUMN product_id int;

;

Modify data
Syntax

INSERT INTO
VALUES ...

Description

Inserts values into a table. Only use this for testing. Do not use INSERT on
a production system. For example:
INSERT INTO "vendor" VALUES ('helen rose', 'jacob norse',
'eileen ruff',
'manny gates');

ALTER TABLE
SET LOAD
PRIORITY

Sets the load priority for a table. Load priority determines the order in
which a table is loaded on a cluster restart. You can set any value from
1-100 . The system default for all tables is 50 . For example:

;

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Syntax

UPDATE
... SET ...
[WHERE ...]

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Description

Updates rows in a table that match optionally provided predicates. Predicates have the form column = value connected by the AND keyword.
Sets the column values to the specified values. For example:

UPDATE "location" SET "borough" = 'staten island', "city" =
'new york'
WHERE "borough" = 'staten isl' AND city = 'NY';

DELETE FROM
[WHERE...]

Deletes rows from a table that match optionally provided predicates. Predicates have the form column = value connected by the AND keyword.
For example.
DELETE FROM "vendor" WHERE "name" = 'Joey Smith' AND "vendorid" =
'19463';

Constraints and relationships
Constraints and relationships in ThoughtSpot are used to define the relationships between tables (i.e.
how they can be joined). However, constraints are not enforced, as they would be in a transactional
database. You can define the following constraints when creating a table with CREATE TABLE , or add
them to an existing table using the ADD CONSTRAINT syntax:
Syntax

Description

PRIMARY KEY

Designates a unique, non-null value as the primary key for a table. This can
be one column or a combination of columns. If values are not unique, an
upsert will be performed if a row includes a primary key that is already present in the data. Some examples:
CREATE TABLE "schools" ( "schoolID" varchar(15), "schoolName"
varchar(255), "schoolCity" varchar(55), "schoolState" varchar(55), "schoolNick"
varchar(55), CONSTRAINT PRIMARY KEY ("schoolID") ) ;
ALTER TABLE "cart" ADD CONSTRAINT PRIMARY KEY ("cart_id");
ALTER TABLE "cart" DROP CONSTRAINT PRIMARY KEY "cart_id";

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Description

Defines a relationship where the value(s) in the table are used to join to a
second table. Uses an equality operator. The foreign key must match the
primary key of the table that is referenced in number, column type, and order of columns.
When creating a foreign key, give it a name. You can reference the foreign
key name later, if you want to remove it.
Examples of this statement:
ALTER TABLE "batting" ADD CONSTRAINT "FK_player" FOREIGN KEY
("playerID")
REFERENCES "players" ("playerID");
ALTER TABLE "batting" ADD CONSTRAINT "FK_lg_team" FOREIGN
KEY ("lgID" ,"teamID")
REFERENCES "teams" ("lgID" ,"teamID");
ALTER TABLE "shipment" ADD CONSTRAINT "FK_PO_vendor" FOREIGN
KEY ("po_number",
"vendor") REFERENCES "orders" ("po_number", "vendor");
ALTER TABLE "shipment" DROP CONSTRAINT "FK_PO_vendor";

RELATIONSHIP

Defines a relationship where the value(s) in the table can be used to join to
a second table, using an equality condition (required) and one or more
range conditions (optional). These conditions act like a WHERE clause
when the two tables are joined. They are applied using AND logic, such
that all conditions must be met for a row to be included.
You may add multiple relationships between tables. When creating a relationship, give it a name. You can reference the relationship name later, if
you want to remove it.
Examples of this statement:
ALTER TABLE "wholesale_buys" ADD RELATIONSHIP "REL_fruit"
WITH
"retail_sales" AS "wholesale_buys"."fruit" = "retail_sales"."fruit" AND
("wholesale_buys"."date_order" < "retail_sales"."date_sold"
AND
"retail_sales"."date_sold" < "wholesale_buys"."expire_date");
ALTER TABLE "wholesale_buys" DROP RELATIONSHIP "REL_fruit";

Data types
ThoughtSpot supports a simplified list of data types:

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Description

Examples

Character

• VARCHAR(n)

Specify the maximum number of characters, as
in VARCHAR(255). The size limit is 1GB for VARCHAR values.

Floating point

• DOUBLE
• FLOAT

DOUBLE is recommended.

Boolean

• BOOL

Can be true or false .

Integer

• INT
• BIGINT

INT holds 32 bits.

Date or time

•
•
•
•

DATE
DATETIME
TIMESTAMP
TIME

BIGINT holds 64 bits.

DATETIME, TIMESTAMP, and TIME are stored
at the granularity of seconds
.
TIMESTAMP is identical to DATETIME, but is included for syntax compatibility.

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tsload flag reference
For recurring data loads and for scripting loads, use tsload (the ThoughtSpot Loader). This reference
section lists all the flags that can be used to modify the behavior of tsload .

General tsload flags
Flag
--target_database

Description

Notes

Specifies the pre-existing
target database into which
tsload should load the data.

--target_schema

Specifies the target schema.

Default is “falcon_default_schema”.

--target_table

Specifies the tables that you
want to load into the database.

The tables must exist in the database specified by --target_database .

--empty_target

Specifies that any data in
the target table is to be removed before the new data
is loaded.

If supplied, any rows that exist in the table
specified by --target_database and -target table will be deleted before this
data load. To perform an “upsert” on the existing data, omit this flag or specify -noempty_target .

--max_ignored_rows

--bad_records_file
/

--date_format

--date_time_format

--time_format

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Flag

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Description

Notes

--v=[0|1|2|3

Specifies the verbosity of
log messages.

Provide a value for verbosity level. By default, verbosity is set to the minimum, which
is 0. This value is similar to a volume control.
At higher levels your log receives more messages and that log more frequently. This is
used for debugging. You should not change
this value unless instructed by ThoughtSpot
Support.

--skip_second_fraction

Skips fractional seconds
when loading data.

If supplied, the upserts logic may be affected, especially if the date time being loaded
is a primary key, and the data has millisecond granularity. Load the data twice, once
as a string with a primary key, and again
with second granularity date time. There is
no support to store fractional seconds in the
ThoughtSpot system.

File loading tsload flags
The following flags are used when loading data from an input file:
Flag
--source_file
/
--source_data_format
[csv|delimited]
--field_separator ""
-- trailing_field_separator

--null_value ""

--date_converted_to_epoch
[true|false]

--boolean_representation
[true_false | 1_0 | T_F |
Y_N]

Description

Notes

Specifies the location of the
file to be loaded.
Specifies the data file format.

Optional. The default is csv.

Specifies the field delimiter
used in the input file.
Specifies that the field separator appears after every
field, including the last field
per row.

Example row with trailing field separator:
a,b,c,The default is false.

Specifies how null values
are represented in the input
file.

These values will be converted to NULL upon loading.

Specifies whether the “date”
or “datetime” values in the
input file are represented as
epoch values.
Specifies the format in
which boolean values are
represented in the input file.

The default is T_F. You can also use this flag
to specify other values. For example, if your
data used Y for true and NULL for false, you
could specify: --boolean_representation Y_NULL

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Description

Notes

--has_header_row

Indicates that the input file
contains a header row.

If supplied, column names in the header row
are used to match column names in the target table in ThoughtSpot. If not supplied, the
first row of the file is loaded as data, the
same as all subsequent rows.

--escape_character ""
--enclosing_character
""

--use_bit_boolean_values
= [true | false]

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--enclosing_character "\""

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tscli command reference
The tscli command line interface is an administration interface for the ThoughtSpot instance. Use
tscli to take snapshots (backups) of data, apply updates, stop and start the services, and view
information about the system. This reference defines each subcommand and what you can accomplish
with it.
The command returns 0 upon success and a non-zero exit code upon failure. Because the tscli
command is typically running a command on multiple codes, an error may be called at different points.
As much as possible, the command attempts to save errors to the stderr directory as configured on a
node.

How to use the tscli command
The tscli command has the following syntax:

tscli [-h] [--helpfull] [--verbose] [--noautoconfig]
[--autoconfig] [--yes] [--cluster ]
[--zoo ] [--username username] [--identit
y_file identity_file]
{access,alert,backup,backup-policy,callhome,cassandr
a,cluster,command,dr-mirror,etl,event,feature,fileserver,firewa
ll,hdfs,ipsec,ldap,logs,map-tiles,monitoring,nas,node,patch,rpa
ckage,saml,scheduled-pinboards,smtp,snapshot,snapshot-policy,sp
ot,sssd,ssl,storage,support,tokenauthentication}

The tscli command has several subcommands such as alert , backup , and so forth. You issue a
subcommand using the following format:

tscli [subcommand ]

Subcommands have their own additional options and actions such as tscli backup create or
tscli backup delete for example. To view help for a subcommand:

tscli [subcommand] -h

A subcommand itself may have several options.

tscli subcommands
This section lists each subcommand and its syntax.

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access

tscli access [-h] {list} ...

Use this subcommand to do the following:
•

tscli access list Lists objects by last access time.

alert

tscli alert [-h] {count,info,list,off,on,refresh,silence,statu
s,unsilence} ...

Use this subcommand to do the following:
•
•
•
•
•

tscli alert info Lists all alerts.
tscli alert list Lists the generated alerts.
tscli alert off Disables all alerts from the cluster in the cluster’s timezone.
tscli alert on Enables alerts from the cluster.
tscli alert silence --name

Silences the alert with alert_name . For example, DISK_ERROR. Silenced alerts are still
recorded in postgres, however emails are not sent out.
•

tscli alert status Shows the status of cluster alerts.

•

tscli alert unsilence-name

alert_name

Unsilences the alert with alert_name . For example, DISK_ERROR .

backup

tscli backup [-h] {create,delete,ls,restore} ...

Use this subcommand to do the following:
•

tscli backup create [-h] [--mode {full,light,dataless}] [--type
{full,incremental}] [--base BASE] [--storage_type {local,nas}] [--remote]
name out

Pulls a snapshot and saves it as a backup where:
•

--mode {full,light,dataless}

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Mode of backups. To understand these diffrent modes see Understand backup
modes.
•

--type {full,incremental} Type of backup.(Incremental incremental is not

implemented yet) (default: full)
•

--base BASE

Based snapshot name for incremental backup. (Not Implemented yet) (default:
None)
•

--storage_type {local,nas}

Storage type of output directory. (default: local)
•

--remote

Take backup through orion master. (default: True)
•
•
•

tscli backup delete * name * Deletes the named backup.
tscli backup ls List all backups taken by the system.
tscli backup restore Restore cluster using backup.

backup-policy

tscli backup-policy [-h] {create,delete,disable,enable,ls,sho
w,status,update} ...

Use this subcommand to do the following:
•

tscli backup-policy create Prompts an editor for you to edit the parameters of the

backup policy.
•
•
•
•
•
•
•

tscli backup-policy delete
tscli backup-policy disable
tscli backup-policy enable

name Deletes the backup policy with name .
name Disables the policy name .
name Enables the policy name .

tscli backup-policy ls List backup policies.
tscli backup-policy show

name Show the policy name .

tscli backup-policy status

name Enables the policy name .

tscli backup-policy update * name * Prompts an editor for you to edit the policy

name .

callhome

tscli callhome [-h] {disable,enable,generate-bundle} ...

Use this subcommand to do the following:
•
•

tscli callhome disable Turns off the periodic call home feature.
tscli callhome enable --customer_name

customer_name `

Enables the “call home” feature, which sends usage statistics to ThoughtSpot This feature is
enabled by default.

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The parameter customer_name takes the form Shared/*`customer_name`*/stats .
•

tscli callhome generate-bundle –d directory

•
•

--since

DAYS

--d D Dest folder where tar file will be created. (default: None)
--since

DAYS

Grab callhome data from this time window in the past. Should be a human
readable duration string, e.g. 4h (4 hours), 30m (30 minutes), 1d (1 day).
(default: None) Generates a tar file of the cluster metrics and writes it to the
specified directory where DAYS is how far back you’d like to generate the tar file
from in days. For example, 30 . If this parameter is not specified, the command
will collect the stats from the last 7 days by default.

cassandra

tscli cassandra [-h] {backup,restore} ...

Use this subcommand to do the following:
•
•

tscli cassandra backup Take a backup of cassandra
tscli cassandra restore Restore cassandra from a backup

cluster

tscli cluster [-h] {abort-reinstall-os,check,create,get-confi
g,load,reinstall-os,report,restore,resume-reinstall-os,resume-u
pdate,set-config,set-min-resource-spec,show-resource-spec,star
t,status,stop,update,update-hadoop} ...

Use this subcommand to do the following:
•
•

tscli cluster abort-reinstall-os Abort in-progress reinstall.
tscli cluster check --includes {all,disk,zookeeper,hdfs,orion-cgroups,orionoreo} Check the status nodes in the cluster.

You must specify a component to check.
•

tscli cluster create

release

Creates a new cluster from the release file specified by release . This command is used by
ThoughtSpot Support when installing a new cluster, for example, tscli cluster create
2.0.4.tar.gz

•

•
•
•
•

tscli cluster get-config Get current cluster network and time configuration. Prints
JSON configuration to stdout. If for some reason the system cannot be connected to all
interfaces, the command returns an error but continues to function.
tscli cluster load Load state from given backup onto existing cluster
tscli cluster reinstall-os Reinstall OS on all nodes of the cluster.
tscli cluster report Generate cluster report.
tscli cluster restore --release release_tarball backupdir `

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Restores a cluster using the backup in the specified directory backupdir . If you’re restoring
from a dataless backup, you must supply the release tarball for the corresponding software
release.
•
•
•

tscli cluster resume-reinstall-os Resume in-progress reinstall.
tscli cluster resume-update Resume in-progress updates.
tscli cluster set-config

Set cluster network and time configuration. Takes JSON

configuration from stdin.
•
•
•
•

tscli cluster set-min-resource-spec Sets min resource configuration of the cluster
tscli cluster show-resource-spec Prints default or min.
tscli cluster start Start cluster.

tscli cluster status Gives the status of the cluster, including release number, date last
updated, number of nodes, pending tables time, and services status.
• tscli cluster stop Pauses the cluster (but does not stop storage services).
• tscli cluster update Update existing cluster.
• tscli cluster update-hadoop Updates Hadoop/Zookeeper on the cluster.

command

tscli command [-h] {run} ...

Command to run a command on all nodes.
tscli command run [-h] [--nodes

COPYFIRST ] [--timeout

•

--nodes

NODES ] --dest_dir

TIMEOUT ]

DEST_DIR

[--copyfirst

command

NODES Space separated IPs of nodes where you want to run the command.

(default: all )
•

DEST_DIR Directory to save the files containing output from each nodes.

--dest_dir

(default: None)
•
•

--copyfirst
--timeout

COPYFIRST Copy the executable to required nodes first. (default: False )

TIMEOUT Timeout waiting for the command to finish. (default: 60 )

dr-mirror

tscli dr-mirror [-h] {start,status,stop} ...

•

tscli dr-mirror start Starts a mirror cluster which will continuously recover from a

primary cluster.
•
•

tscli dr-mirror status Checks whether the current cluster is running in mirror mode.
tscli dr-mirror stop Stops mirroring on the local cluster.

etl

tscli etl [-h] {change-password,disable-lw,download-agent,enabl
e-lw,show-lw} ...

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tscli etl change-password --admin_username

admin_user

--username

Informatica_user `

Changes the Informatica Cloud account password used by ThoughtSpot Data Connect.
Required parameters are:
•

--admin_username

admin_user specifies the Administrator username for

ThoughtSpot.
•

--username

Informatica_user specifies the username for the Informatica

Cloud.
•
•

tscli etl disable-lw Disables ThoughtSpot Data Connect.
tscli etl download-agent Downloads the ThoughtSpot Data Connect agent to the

cluster.
•

tscli etl enable-lw [-h] --username

THOUGHTSPOT_URL
--org_id

--admin_username

ORG_ID

proxy_port

USERNAME

--thoughtspot_url

ADMIN_USERNAME

[--groupname

PIN_TO ] [--proxy_host

[--pin_to

PROXY_PORT ] [--proxy_username

GROUPNAME ]

PROXY_HOST ] [--

PROXY_USERNAME

] [--max_wait

MAX_WAIT ]

You should contact ThoughtSpot Support for assistance in setting this up. Required
parameters are:
•
•

--username

USERNAME Username for Informatica Cloud (default: None)
THOUGHTSPOT_URL URL to reach thoughtspot. (default:

--thoughtspot_url

None)
•

--admin_username

ADMIN_USERNAME Admin username for ThoughtSpot

(default: None)
•
•

•

•
•
•
•

•

--groupname
--org_id

GROUPNAME

ORG_ID specifies the Informatica id of the organization (company).

For ThoughtSpot, this is 001ZFA . org_id shouldn’t include the prefix Org . For
example, if on Informatica cloud, the orgid is Org003XYZ , then use only
--pin_to PIN_TO specifies the IP address to pin to. If you specify an IP to pin
to, that node becomes sticky to the Informatica agent, and will always be used.
Defaults to the public IP address of the localhost where this command was run.
--proxy_host PROXY_HOST Proxy server host for network access (default: )
--proxy_port PROXY_PORT Proxy server port (default: )
--proxy_username PROXY_USERNAME Proxy server username (default: )
--max_wait MAX_WAIT Maximum time in seconds to wait for Data Connect
agentto start (default: None)

tscli etl show-lw Shows the status of ThoughtSpot Data Connect. It also returns the
Informatica username and OrgId.

event

tscli event [-h] {list} ...

This subcommand has the following actions:
tscli event list [-h] [--include

TO ] [--limit
detail_contains

INCLUDE ] [--since

LIMIT ] [--detail] [--summary_contains
DETAIL_CONTAINS ] [--attributes

ThoughtSpot Administration Guide

SINCE ] [--from

FROM ] [--to

SUMMARY_CONTAINS ] [--

ATTRIBUTES ]

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•
•

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--include
--since

INCLUDE Options are all, config, notification. Default config. (default: config)

SINCE Grab events from this time window in the past. Should be a human

readable duration string, e.g. 4h (4 hours), 30m (30 minutes), 1d (1 day). (default: None)
--from FROM Begin timestamp, must be of the form: yyyymmdd-HH:MM (default: None)
--to TO End timestamp, must be of the form: yyyymmdd-HH:MM (default: None)
--limit LIMIT Max number of events to fetch. (default: 0)
--detail Print events in detail format. This is not tabular. Default is a tabular summary.
(default: False)
• --summary_contains SUMMARY_CONTAINS Summary of the event will be checked for this
string. Multiple strings to check for can be specified by separating them with | (event
returned if it matchesALL). Put single quotes around the param value to prevent undesired
glob expansion (default: None)
• --detail_contains DETAIL_CONTAINS Details of the event will be checked for this string.
Multiple strings to check for can be specified by separating them with | (event returned if it
matches ALL). Put single quotes around the param value to prevent undesired glob expansion
(default: None)
• --attributes ATTRIBUTES Specify attributes to match as key=value. Multiple attributes to
check for can be specified by separating them with | (event returned if it matches ALL). Put
single quotes around the param value to prevent undesired glob expansion (default: None)
•
•
•
•

feature

tscli feature [-h] {get-all-config} ...

This subcommand has the following actions:
tscli feature get-all-config Gets the configured features in a cluster. The command will return a
list of features, such as custom branding, Data Connect, and call home, and tell you whether they are
enabled or disabled.

fileserver

tscli fileserver [-h] {configure,download-release,purge-confi
g,show-config,upload} ...

This subcommand has the following actions:
•

tscli fileserver configure [-h] --user

USER

[--password

PASSWORD

]

Configures the secure file server username and password for file upload/download and the
call home feature. You only need to issue this command once, to set up the connection to the
secure file server. You only need to reissue this command if the password changes. The
parameter PASSWORD is optional. If a password is not specified, you will be prompted to
enter it.
•

tscli fileserver download-release [-h] [--user

PASSWORD ]

USER ] [--password

release Downloads the specified release file and its checksum. Specify the

release by number, to the second decimal point (e.g. 3.1.0, 3.0.5, etc.). You may optionally
specify the --user and --password to bypass the credentials that were specified when
configuring the file server connection with tscli fileserver configure . Before using this
command for the first time, you need to set up the file server connection using tscli

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fileserver configure .

•
•
•

tscli fileserver purge-config Removes the file server configuration.
tscli fileserver show-config Shows the file server configuration.
tscli fileserver upload [-h] [--user
file_name

USER ] [--password

PASSWORD ] --

FILE_NAME* –server_dir_path * SERVER_DIR_PATH`

Uploads the file specified to the directory specified on the secure file server. You may
optionally specify the --user and --password to bypass the credentials that were
specified when configuring the file server connection with tscli fileserver configure .
Before using this command for the first time, you need to set up the file server connection
using tscli fileserver configure .
Accepts these flags
•
•

--user

USER Username of fileserver (default: None)

PASSWORD Password of fileserver (default: None). This is required
and the command prompts you for it if you do not supply it.
• --file_name FILE_NAME Local file that needs to be uploaded (default: None)
• --server_dir_path SERVER_DIR_PATH Directory path on fileserver. (default:
None) The SERVER_DIR_PATH parameter specifies the directory to which you want
to upload the file. It is based on your customer name, and takes the form
/Shared/support/* customer_name * .
--password

firewall

tscli firewall [-h] {close-ports,disable,enable,open-ports,stat
us} ...

•

tscli firewall close-ports

Closes given ports through firewall on all nodes. Takes a list of ports to close, comma
separated. Only closes ports which were previously opened using “open-ports”. Ignores ports
which were not previously opened with “open-ports” or were already closed.
•
•
•

tscli firewall disable Disable firewall.
tscli firewall enable Enable firewall.
tscli firewall open-ports

--ports

ports

Opens given ports through firewall on all nodes. Takes a list of ports to open, comma
separated. Ignores ports which are already open. Some essential ports are always kept open
(e.g. ssh ), they are not affected by this command or by close-ports .
•

tscli firewall status Shows whether firewall is currently enabled or disabled.

hdfs

tscli hdfs [-h] {leave-safemode} ...

This subcommand has the following actions:

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tscli hdfs leave-safemode Command to get HDFS namenodes out of safemode.

ipsec

tscli ipsec [-h] {disable,enable,status} ...

This subcommand has the following actions:
tscli ipsec disable Disable IPSec tscli ipsec enable Enable IPSec tscli ipsec status
Show IPSec status on all nodes

ldap

tscli ldap [-h] {add-cert,configure,purge-configuration} ...

This subcommand has the following actions:
•

name

tscli ldap add-cert

certificate

Adds an SSL certificate for LDAP. Use only if LDAP has been configured without SSL and you
wish to add it. Use * name * to supply an alias for the certificate you are installing.
•

tscli ldap configure

Configures LDAP using an interactive script. You can see detailed instructions for setting up
LDAP in About LDAP integration.
•

tscli ldap purge-configuration Purges (removes) any existing LDAP configuration.

logs

tscli logs [-h] {collect,runcmd} ...

This subcommand has the following actions:
•

tscli logs collect [-h] [--include
since

SINCE ] [--from

INCLUDE ] [--exclude

FROM ] [--to

MAXSIZE ] [--sizeonly] [--nodes

TO ] [--out

EXCLUDE ] [--

OUT ] [--maxsize

NODES ]

Extracts logs from the cluster. Does not include any logs that have been deleted due to log
rotation.
These parameters have the following values:
•

--include

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Specifies a comma separated list of logs to include. Each entry is either a
“selector” or a glob for matching files.Selectors must be among: all , orion ,
system , ts . Anything starting with / is assumed to be a glob pattern and
interpreted via find(1) . Other entries are ignored. Put single quotes around the
param value to prevent undesired glob expansion (default: all )
•

--exclude

EXCLUDE

Comma separated list of logs to exclude. Applies to the list selected by –include.
Params are interpreted just like in –include (default: None)
•

--since

SINCE

Grab logs from this time window in the past. Should be a human readable duration
string, e.g. 4h (4 hours), 30m (30 minutes), 1d (1 day). (default: None)
•

--from

FROM Timestamp where collection begins, must be of the form:

yyyymmdd-HH:MM (default: None)

•

--to

TO Timestamp where collection ends, must be of the form: yyyymmdd-

HH:MM (default: None)

•

--out

OUT Tarball path for dumping logs from each node (default: /tmp/

logs.tar.gz )

•

--maxsize MAXSIZE Only fetch logs if size is smaller that this value. Can be
specified in megabytes/gigabytes, e.g. 100MB, 10GB. (default: None)
• --sizeonly Do not collect logs. Just report the size. (default: False)
• --nodes NODES Comma separated list of nodes from where to collect logs. Skip
this to use all nodes. (default: None)

•

tscli logs runcmd [-h] --cmd

EXCLUDE ] [--since
[--outdir
nodes

CMD [--include

SINCE] [--from

OUTDIR ] [--cmd_infmt

INCLUDE ] [--exclude

FROM ] [--to

TO ] [--outfile

CMD_INFMT ] [--cmd_outfmt

OUTFILE ]

CMD_OUTFMT ] [--

NODES ]

Runs a Unix command on logs in the cluster matching the given constraints. Results are
reported as text dumped to standard out, the specified output file, or as tarballs dumped into
the specified directory.
•

--cmd

CMD

Unix-Command to be run on the selected logs. Use single quotes to escape
spaces etc. Language used to specify CMDSTR has following rules.
• A logfile and its corresponding result file can be referred by keywords
SRCFILE & DSTFILE . eg. cp SRCFILE DSTFILE
• Without any reference to DSTFILE in CMDSTR, > DSTFILE will be
appended to CMDSTR for output redirection. eg du -sch SRCFILE
gets auto- transtalted to du -sch SRCFILE > DSTFILE
• Without any reference to SRCFILE, content of log is streamed to
CMDSTR via pipe. eg. tail -n100 | grep ERROR gets autotranstalted to cat SRCFILE | tail -n100 | grep ERROR >
DSTFILE (default: None)
•

--include

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Comma separated list of logs to include,each entry is either a “selector” or a glob
for matching files.Selectors must be among: all , orion , system , ts .
Anything starting with / is assumed to be a glob pattern and interpreted via
find(1) . Other entries are ignored. TIP: put single quotes around the param
value to prevent undesired glob expansion (default: all)
•

--exclude

EXCLUDE

Comma separated list of logs to exclude. Applies to the list selected by -include . Params are interpreted just like in --include (default: None)
•

--since

SINCE

Grab logs from this time window in the past. Should be a human readable duration
string, e.g. 4h (4 hours), 30m (30 minutes), 1d (1 day). (default: None)
•

--from

FROM Timestamp where collection begins, must be of the form:

yyyymmdd-HH:MM (default: None)

•

--to

TO Timestamp where collection ends, must be of the form: yyyymmdd-

HH:MM (default: None)

•

--outfile

OUTFILE File path for printing all the results. By default printed to

stdout (default: None)
•

--outdir OUTDIR Directory path for dumping results with original dir structure
from each node. Used as an alternative to printing output to outfile/stdout (default:
None)

•

--cmd_infmt CMD_INFMT Specify if the inputfile should be compressed/
uncompressed before running CMD . C =compressed, U =uncompressed. Don’t
use this flag if CMD works on both (default: None)

•

--cmd_outfmt CMD_OUTFMT Specify if OUTFILE generated by CMD will be
compressed/uncompressed. C =compressed, U =uncompressed. Don’t use this
flag if output file will be of same format as input file (default: None)

•

--nodes NODES Comma separated list of nodes where to run command. Skip
this to use all nodes. (default: None)

map-tiles

tscli map-tiles [-h] {disable,enable,status} ...

This subcommand supports the following actions:
•

tscli map-tiles enable [-h] [--online] [--offline] [--tar TAR] [--md5 MD5]

Enables ThoughtSpot’s map tiles, which are used when constructing geomap charts. If you
don’t have interest access, you must download the map tiles tar and md5 files. Then you
must append the following to the tscli command.
•
•
•
•

--online Download maptiles tar from internet. (default: True)
--offline Using maptiles tar from local disk. (default: False)
--tar

TAR Specified tar file for map-tiles. (default: )

--md5

MD5 Specified md5 file for map-tiles. (default: )

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•

tscli map-tiles disable

•

tscli map-tiles status

Disable map-tiles functionality.
Check whether map-tiles is enabled.

monitoring

tscli monitoring [-h] {set-config,show-config} ...

This subcommand has the following actions:
•

tscli monitoring set-config [-h] [--email EMAIL] [--clear_email] [-heartbeat_interval HEARTBEAT_INTERVAL] [--heartbeat_disable] [-report_interval REPORT_INTERVAL] [--report_disable] Sets the monitoring

configuration.
•
•
•
•
•
•
•

--email EMAIL Comma separated list (no spaces) of email addresses where the
cluster will send monitoring information.
--clear_email Disable emails by clearing email configuration. (default: False)
--heartbeat_interval HEARTBEAT_INTERVAL Heartbeat email generation
interval in seconds. Should be greater than 0.
--heartbeat_disable Disable heartbeat email generation. (default: False)
--report_interval REPORT_INTERVAL Cluster report email generation interval
in seconds. Should be greater than 0.
--report_disable Disable cluster report email generation. (default: False)

tscli monitoring show-config Shows the monitoring configuration.

nas

tscli nas [-h] {ls,mount-cifs,mount-nfs,unmount} ...

This subcommand has the following actions:
•

tscli nas ls [-h] List mounts managed by NAS mounter service.

•

tscli nas mount-cifs [-h] --server

PATH_ON_SERVER
password

] --mount_point

PASSWORD

[--uid

SERVER

MOUNT_POINT

UID ] [--gid

[--path_on_server
--username

USERNAME

GID ] [--options

OPTIONS

Mounts a CIFS device on all nodes.
•

--server

SERVER IP address or DNS name of CIFS service. For example,

10.20.30.40 (default: None)

•

--path_on_server PATH_ON_SERVER Filesystem path on the CIFS server to
mount (source). For example: /a (default: / )
--mount_point

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Directory on all cluster nodes where the NFS filesystem should be mounted
(target). This directory does not need to already exist. If this directory already
exists, a new directory is not created and the existing directory is used for
mounting. For example: /mnt/external (default: None)
•

--username

USERNAME Username to connect to the CIFS filesystem as (default:

None)
•
•

--password
--uid

PASSWORD CIFS password for --username (default: None)

UID

UID that will own all files or directories on the mounted filesystem when the server
does not provide ownership information. See man mount.cifs for more details.
(default: 1001 )

•

--gid

GID

Gid that will own all files or directories on the mounted filesystem when the server
does not provide ownership information. See man mount.cifs for more details.
(default: 1001 )
•

•

--options OPTIONS Other command-line options to forward to mount.cifs
command (default: noexec )

tscli nas mount-nfs [-h] --server SERVER [--protocol PROTO --path_on_server
PATH_ON_SERVER] --mount_point MOUNT_POINT [--options OPTIONS]

Mounts a NFS device on all nodes. Parameters are:
•

--server

SERVER IP address or DNS name of NFS service. For example,

10.20.30.40 (default: None)

•
•

--path_on_server PATH_ON_SERVER Filesystem path on the NFS server to
mount (source). For example: /a/b/c/d (default: / )
--mount_point

MOUNT_POINT

--options

OPTIONS Command-line options to forward to mount command

(default: noexec ).
•
•

--protocol PROTO One of nfs or nfs4 . The default is nfs .

tscli nas unmount [-h] --dir

DIR

Unmounts all devices from the specified DIR (directory) location. This command returns an
error if nothing is currently mounted on this directory via tscli nas mount (default: None)

node

tscli node [-h] {check,ls,reinstall-os,resume-reinstall-os,stat
us} ...

This subcommand has the following actions:

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tscli node check [-h] [--select {reinstall-preflight}] [--secondary

SECONDARY ]

Run checks per node. Takes the following parameters:
•

--select {reinstall-preflight} Select the type of node check (default:
reinstall-preflight )

•

--secondary

SECONDARY Secondary drive for reinstall-preflight (default:

sdd )

•

tscli node ls [-h] [--type {all,healthy,not-healthy}] Filter by node state

(default: all )
•

tscli node reinstall-os [-h] [--secondary

SECONDARY

] [--cluster] Reinstall

OS on a node. This takes the following parameters:
•

--secondary SECONDARY Secondary drive to be used to carry to reinstall
(default: sdd )
• --cluster Is the node part of a cluster (default: False )

•

tscli node resume-reinstall-os Resume in-progress reinstall

patch

tscli patch [-h] {apply,ls,resume-apply,resume-rollback,rollbac
k} ...

This subcommand has the following actions:
•

tscli patch apply [-h] [

release ]

Apply the patch on an existing cluster. Takes the following parameters:
•
•

release The relative path to the patch tar ball

tscli patch ls [-h] [--applied] [--rolled_back] [--service SERVICE] [--md5
MD5] [--history] Lists the patches currently applied. This takes the following parameters:

•
•

--applied Show only the patches applied since last full release (default: ` False` )
--rolled_back Show only the patches rolled back since last full release (default:

` False` )
•
•
•
•

--service SERVICE Show patches filtered by service (default: ` None` )
--md5 MD5 Shows the details of the patch specified (default: ` None` )
--history Shows the history of all patch apply/rollback release (default: ` False` )

tscli patch resume-apply [-h]

Resume patch apply
•

tscli patch resume-rollback [-h]

Resume patch roll-backup
•

tscli patch rollback [-h]

Rollback the patch from an existing cluster

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rpackage

tscli rpackage [-h] {add,delete,list} ...

Manages R packages available to SpotIQ.
•

tscli rpackage add [-h] [--repo

DEST_DIR ] [--nodes

NODES ]

REPO ] [--timeout

TIMEOUT ] [--dest_dir

package_name Command to add an R package_name

to the cluster. This command has the following options:
•
•
•

--repo

REPO Specify the url of a specific repo to download packages

--timeout

REPO Timeout waiting for the R Package to be installed (default: 60)
REPO Directory where output of this command will be placed

--dest_dir

(default: None)
•

•

--nodes NODES Space separated IPs of nodes where you want to run the
command. (default: all).

tscli rpackage add [-h] [--timeout
nodes

NODES ]

TIMEOUT ] [--dest_dir

DEST_DIR ] [--

package_name Command to delete an installed R package from the

cluster. This command has the following options:
•
•

--timeout

REPO Timeout waiting for the R Package to be removed (default: 60)

--dest_dir

REPO Directory where output of this command will be placed

(default: None)
•

•

--nodes NODES Space separated IPs of nodes where you want to run the
command. (default: all).

tscli rpackage list [-h] [--detailed] List all R packages installed on the cluster.

saml

tscli saml [-h] {configure,purge-configuration}

This subcommand has the following actions:
•

tscli saml configure [-h] Configures SAML. To see a list of prerequisites refer to

Configure SAML.
•

tscli saml purge-configuration Purges any existing SAML configuration.

scheduled-pinboards

tscli scheduled-pinboards [-h] {disable,enable}

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This subcommand has the following actions:
•
•

tscli scheduled-pinboards disable [-h] Disable scheduled pinboards for this cluster.
tscli scheduled-pinboards enable [-h] Enables scheduled pinboards, which is

disabled in prod clusters by default.

 Note: When you enable scheduled pinboards, you should also configure a whitelist of intended
email domains. Contact ThoughtSpot Support for help configuring a whitelist.

smtp

tscli smtp [-h] {remove-mailfromname,remove-mailname,remove-rel
ayhost,remove-saslcredentials,reset-canonical-mapping,set-canon
ical-mapping,set-mailfromname,set-mailname,set-relayhost,set-sa
slcredentials,show-canonical-mapping,show-mailfromname,show-mai
lname,show-relayhost}

This subcommand takes supports the following actions:
•
•
•
•

tscli smtp remove-mailfromname Removes current cluster mailfromname

•

tscli smtp reset-canonical-mapping Deletes the current postmap mapping.

•

tscli smtp remove-mailname Removes current cluster mailname
tscli smtp remove-relayhost Removes current cluster relayhost
tscli smtp remove-saslcredentials Clears SASL credentials and disables SMTP AUTH

tscli smtp set-canonical-mapping [-h]

new_key

new_value Sets a new Postmap

mapping.
•

tscli smtp set-mailfromname mailfromname Sets the name, an email address, from
which email alerts are sent, for the cluster.
• tscli smtp set-mailname mailname Sets the mailname, a domain, where email alerts
are sent, for the cluster.
• tscli smtp set-relayhost [-h] [--force FORCE] relayhost Sets the Relay Host for
SMTP (email) sent from the cluster.

•

--force

FORCE Set even if relay host is not accessible. (default: False )

•

tscli smtp set-saslcredentials Sets SASL credentials and enables SMTP AUTH

•
•

tscli smtp show-canonical-mapping Shows the current postmap mapping.
tscli smtp show-mailfromname Shows the mailname, from which email alerts are sent, for

the cluster.
•

tscli smtp show-mailname Shows the mailname, where email alerts are sent, for the

cluster.
•

tscli smtp show-relayhost Shows the for SMTP (email) sent from the cluster. If there is
no Relay Host configured, the command returns NOT FOUND .

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snapshot

tscli snapshot [-h] {backup,create,delete,ls,pin,restore,unpi
n,update-ttl}

Learn more about snapshots and backups see the Understand the backup strategies documentation.
This subcommand supports the following actions:
•

tscli snapshot backup [-h] [--mode {full,light,dataless}] [--type
{full,incremental}] [--base

name

BASE

] [--storage_type {local,nas}] [--remote]

out

Pull snapshot out as a backup. This takes the following parameters:
•
•

--mode {full,light,dataless} Mode of backups. (default: full )

name Name of snapshot to pull out as a backup. To list all snapshots, run tscli
snapshot ls .

•
•

out Directory where backup will be written, must not already exist.

--type {full,incremental} Type of backup.(Incremental backup is not
implemented yet) (default: full )
• --base BASE Based snapshot name for incremental backup. (Not Implemented
yet) (default: None)
• --storage_type {local,nas} Storage type of output directory. (default:
local )
• --remote Take backup through Orion master. (default: True )

•

tscli snapshot create [-h]

name

reason

ttl

Creates a new snapshot with the name and reason provided. This command does not
accept . (periods), but does accept - (dashes). The ttl parameters is the number of
days after which this snapshot will be automatically deleted. A value of -1 disables
automatic deletion.
•

tscli snapshot pin [-h]

name Pins a snapshot so it cannot be deleted or garbage

collected.
•
•
•

tscli snapshot delete [-h]

name Deletes the named snapshot.

tscli snapshot ls [-h] List available snapshots.
tscli snapshot restore [-h] [--allow_release_change] [--only_service_state]

name Restore cluster to an existing snapshot. This takes the following parameters:

•

--allow_release_change Allow restoration to a snapshot at a different release.

(default: False )
•
•

--only_service_state Restore only service state. (default: False )

tscli snapshot unpin [-h]

name Unpin a snapshot so it can be deleted or garbage

collected.
•

tscli snapshot update-ttl [-h] [--disable

DISABLE

]

name

ttl

Updates manual snapshot garbage collection policy.

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•
•

name Specifies which snapshot to update.

ttl Extends the manual snapshot ttl (time-to-live) value. Use a positive value
to increase ttl . Use negative value to decrease it.
• --disable DISABLE Disable manual snapshot garbage collection. Setting this
value to True will override any ttl value. (default: False)

snapshot-policy

tscli snapshot-policy [-h] {disable,enable,show,update}

This subcommand supports the following actions:
•
•
•
•

tscli snapshot-policy disable [-h] Disable snapshot policy.
tscli snapshot-policy enable -h Enable specified snapshot policy.
tscli snapshot-policy show [-h] Show snapshot policy.
tscli snapshot-policy update [-h] [--config

CONFIG ] Update periodic snapshot

config. This takes the following parameter:
•

--config

CONFIG Text format of periodic backup policy config (default: None)

spot

tscli spot [-h] {enable} ...

Enables Spot integration. This subcommand supports the following actions:
tscli spot enable [-h] --token
cache_timeout

CACHE_TIMEOUT

TOKEN

--thoughtspot_url

THOUGHTSPOT_URL

[--

]

•

--token TOKEN Slack authroization token for Spot bot. This is required. You receive this
token when your Slack administrator adds the Spot application.
• --thoughtspot_url THOUGHTSPOT_URL URL for the ThoughtSpot application. This is
required.
• --cache_timeout CACHE_TIMEOUT Internal cache timeout (default: 60000 )

ssl

tscli ssl [-h] {add-cert,clear-min-tls-version,off,on,rm-cert,s
et-min-tls-version,status,tls-status} ...

This subcommand supports the following actions:
•
•

tscli ssl add-cert [-h]

key

certificate Adds an SSL certificate, key pair.

tscli ssl clear-min-tls-version [-h] Clears any customizations for the minimum TLS

version to support.

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tscli ssl off

Disables SSL. Disabling SSL will stop users from seeing a security warning when accessing
ThoughtSpot from a browser if there is no SSL certificate installed.
•
•
•

•
•

tscli ssl on [-h] If SSL is enabled and there is no certificate, users will see a security
warning when accessing ThoughtSpot from a browser.
tscli ssl rm-cert Removes the existing SSL certificate, if any.
tscli ssl set-min-tls-version [-h] {1.0,1.1,1.2} Sets the minimum supported TLS
version. Sets the minimum SSL version to be supported by the ThoughtSpot application.
Please ensure that client browsers are enabled for this version or newer.
tscli ssl status Shows whether SSL authentication is enabled or disabled.
tscli ssl tls-status [-h] Prints the status of TLS support.

sssd

tscli sssd {enable, disable, set-sudo-group, clear-sudo-group}
...

This subcommand uses system security services daemon (SSSD), and has the following actions:
•

tscli sssd enable --user

USER

--domain

DOMAIN

Enables system Active Directory (AD) user access on a single node. You will be prompted for
password credentials. The user must have permission to join a computer or VM to the
domain.
•

tscli sssd disable

Disables system AD based access on a local node. Running this command will also remove
the AD group from sudoers list.
•

tscli sssd set-sudo-group

ACTIVE_DIRECTORY_GROUP_NAME

Allows sudo permissions for AD group.
•

tscli sssd clear-sudo-group

ACTIVE_DIRECTORY_GROUP_NAME

Clears any set AD sudo group.
For more about setting up Active Directory access, see Enable Active Directory based access.

storage

tscli storage [-h] {gc,df} ...

This subcommand supports the following actions:
•

tscli storage gc [-h] [--log_age

LOG_AGE

] [--force] [--localhost_only]

Garbage collect unused storage. Before issuing this command, you must stop the cluster
using tscli cluster stop . After garbage collection has completed, you can restart the
cluster with tscli cluster start . The command frees space in these directories:

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•
•
•
•
•
•
•

/tmp
/usr/local/scaligent/logs/
/export/logs/orion
/export/logs/oreo
/export/logs/hadoop
/export/logs/zookeeper
cores

Accepts these optional flags:
•

--log_age

LOG_AGE

Delete logs older than these many hours. Use a non-zero value ideally. A zero value
will cause all temporary files to be deleted, including say those which are just
temporarily closed while they are being passed from one component to the next.
(default: 4 )

•

--force Forces deletion of all logs and temporary files regardless of age. This
must only be run on a stopped cluster. (default: False)

•

--localhost_only If used, only the logs on the localhost will be removed. If not
specified, the command acts on the entire cluster.

tscli storage df [--mode disk|hdfs]

Checks the disk usage on the relevant mounts. Returns output similar to the Linux system
command df -h .

support

tscli support [-h]
{bundle,restart-remote,rm-admin-email,rm-admin-phone,rm-feedbac
k-email,set-admin-email,set-admin-phone,set-debug-ui-password,s
et-feedback-email,set-remote,show-admin-email,show-admin-phon
e,show-feedback-email,show-remote,start-remote,stop-remote} ...

This subcommand supports the following actions:
•

tscli support bundle [-h] [--include INCLUDE] [--exclude EXCLUDE] [-list_selectors] [--since SINCE] [--from FROM] [--to TO] [--out OUT] [--nodes
NODES]

•

--include INCLUDE Comma separated list of selectors to include, each entry is
either a “selector” or a glob for matching files. To see the list of valid selectors, run
this command with --list_selectors . You may also specify: “ all to get all
selectors and logs, and “basic” to get only the basic selectors. Selectors may also
be selectors meant for logs collect: all, orion, system, ts, or the name of a service.
Anything starting with / is assumed to be a glob pattern and interpreted via find(1).
Other entries are ignored. TIP: put single quotes around the param value to prevent
undesired glob expansion. Use “all” to collect all selectors and all logs (default:
all_but_logs)

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•

--exclude EXCLUDE Comma separated list of selectors to exclude. Applies to
the list selected by --include . Params are interpreted just like in --include .
Use the special keyword “logs” to exclude logs collection all together. (default:
None)

•

--list_selectors List the selectors available for --include and --exclude ,
and then exit. (default: False )

•

--since SINCE Grab logs from this time window in the past. Should be a
human readable duration string, e.g. 4h (4 hours), 30m (30 minutes), 1d (1 day).
(default: None)

•

--from

FROM Timestamp where collection begins, must be of the form:

yyyymmdd-HH:MM (default: None)

•

--to

TO Timestamp where collection ends, must be of the form: yyyymmdd-

HH:MM (default: None)

•

--out

OUT Tarball path for dumping the support bundle (default: /tmp/

support_bundle.tar.gz )

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this to use all nodes. (default: None)

tscli support restart-remote Restarts remote support.
tscli support rm-admin-email Removes the email address for contacting the customer
administrator. Replaces it with the default ThoughtSpot Support email address.
tscli support rm-feedback-email Removes the email address for product feedback.
Replaces it with the default ThoughtSpot Support email address.
tscli support rm-admin-phone Removes the phone number for contacting the customer
administrator. Replaces it with the default ThoughtSpot Support phone number.
tscli support rm-feedback-email Removes the email for sending feedback out of the
system. If you would like to set a blank email address, issue the command tscli support
set-feedback-email ' ' .
tscli support set-admin-email email Sets the email address for contacting the
customer administrator. If you would like to display a blank email address, issue the
command tscli support set-admin-email ' ' .
tscli support set-feedback-email email Sets the email address for sending
feedback. If you would like to display a blank email address, issue the command tscli
support set-feedback-email ' ' .
tscli support set-admin-phone phone_number Sets the phone number for contacting
the customer administrator. Specify a phone number using any value (e.g. +1 800-508-7008
Ext. 1 ). If you would like to display a blank phone number, issue the command tscli
support set-admin-phone .
tscli support set-remote [-h] [--addr ADDR ] [--user USER ] Configures the
cluster for remote support through SSH tunneling, where ADDR is the address of support,
e.g. t unnel.thoughtspot.com , and USER is the support username.
tscli support show-admin-email Shows the email address for customer administrator, if
set.
tscli support show-feedback-email Shows the email address for product feedback, if
set.
tscli support show-admin-phone Shows the phone number for customer administrator, if
set.
tscli support show-remote Shows the status and configuration of remote support.
tscli support start-remote Starts remote support.
tscli support stop-remote Stops remote support.

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tscli command reference

February 06, 2019

tokenauthentication

tscli cli tokenauthentication [-h] {disable,enable}

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tscli cli tokenauthentication enable Generates a token.
tscli cli tokenauthentication disable Purges token login configuration.

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Date and time formats reference

February 06, 2019

Date and time formats reference
This is a references for the date and time contexts and formats you can use with ThoughtSpot. You
define data formats in specific contexts and, depending on the context, your choices in data formatting
differ. You must understand date and time when you load data in these contexts:
• using data upload from the browser
• through tsload command
• through data connect or another extract, transform, load (ETL) tool
Data loading formats do not change how data is displayed in tables and charts.
The context where you can control date and time formats is data modeling. Data modeling controls how
data is displayed in search and their resulting answers.

Data loading formats via tsload
When loading via the tsload command you must specify date and timestamp formats using the
format specifications defined in thestrptime library function. Data is imported based on the timezone of
the node from which tsload is run.
For date data types, the default format is %Y%m%d which translates to yearmonthday For example,
Dec 30th, 2001 is represented as 20011230 . For time and datetime data types, the default is
%Y%m%d %H:%M:%S which translates to yearmonthday hour:minute:second , for example, Dec
30th, 2001 1:15:12 is represented as 20011230 01:15:12 .

Data modeling formats for browser data upload
These date and time formats are supported in a CSV file when uploading via the browser. You cannot
specify the date format; ThoughtSpot will pick the format that fits your data best:
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1/30/2014
2014-01-30
2014-1-30
30-Jan-2014
2014-Jan-30
2014-01-30 10:32 AM
2014-01-30 14:52
2014-01-30 10:32:22
2014-01-30 10:32:22 AM
2014-01-30 10:32:22.0
2014-01-30 10:32:22.0 AM
2014-01-30 10:32:22.000
2014-01-30 10:32:22.000 AM
1/30/2014
30-Jan-14
01-Mar-02 (assumes 2002)
30/1/2014 10:32 AM
30/1/2014 14:52
30/1/2014 10:32:22
30/1/2014 10:32:22 AM
30/1/2014 10:32:22.0
30/1/2014 10:32:22.0 AM

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Date and time formats reference

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February 06, 2019

30/1/2014 10:32:22.000
30/1/2014 10:32:22.000 AM
30-Jan-14 10:32 AM
30-Jan-14 14:52
30-Jan-14 10:32:22
30-Jan-14 10:32:22 AM
30-Jan-14 10:32:22.0
30-Jan-14 10:32:22.0 AM
30-Jan-14 10:32:22.000
30-Jan-14 10:32:22.000 AM
Fri Jan 30 2014 3:26 PM
Fri Jan 30 2014 13:46
Fri Jan 30 2014 10:32:22
Fri Jan 30 2014 10:32:22 AM
Fri Jan 30 2014 10:32:22.0
Fri Jan 30 2014 10:32:22.0 AM
Fri Jan 30 2014 10:32:22.000
Fri Jan 30 2014 10:32:22.000 AM
14:52
10:32 AM
10:32:22
10:32:22 AM
10:32:22.0
10:32:22.000
10:32:22.0 AM
10:32:22.000 AM

Data loading formats via data connect or
another ETL tool
Data that is loaded via ETL arrives through ODBC or JDBC connection. After you extract the data from
the source and before you load it into ThoughtSpot, you must transform any date or timestamp into a
valid format for ThoughtSpot. Once transformed, no explicit data masking is required. See the data
integration guide for more details of loading data via ODBC and JDBC.

Data modeling formats
A user with administrative rights can configure data modeling for data on one or all files. You can set
number, date, and currency display formats. These formats define how these value types display in
tables and charts. See the Admin Guide for more information about data modeling settings. The
following format strings are available for use:
Format mask

Description

YYYY or yyyy

four digit year such as 2017

YY or yy

last two digits of year such as 17

month with no leading zero 1 - 12

Two digit month 01 - 12

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Date and time formats reference

Format mask

February 06, 2019

Description

MMM

Three letter month such as Jan

Day of year without a leading zero 0 - 365

Day of year with up to one leading zero 01 - 365

DDD

Day of year with up to two leading zeroes 001 - 365

Day of month with no leading zero 1 - 31

Two digit day of month 01 - 31

Two digit 24 hour representation of hour 00 - 23

Two digit 12 hour representation of hour 01 - 12

24 hour representation of hour with no leading zero 0 - 23

12 hour representation of hour with no leading zero 1 - 12

Minutes 00 - 59

Minutes with no leading zero 0 - 59

Seconds 00 - 59

Seconds with no leading zero 0 - 59

AM/PM indicator

Valid delimiters include most non-alphabet characters. This includes but is not limited to:
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\ (forward slash)
/ (backward slash)
| (pipe symbol)
: (colon)
- (dash)
_ (underscore)
= (equal sign)

Examples of valid format masks you can produce for display are as follows:
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MM/dd/yyyy
MMM
DD/MM/yyyy
MM/dd/yyyy HH:mm
DD/MM/yyyy HH:mm

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Page 346

Row level security rules reference

February 06, 2019

Row level security rules reference
ThoughtSpot allows you to create row level security rules using expressions. If an expression evaluates
to “true” for a particular row and group combination, that group will be able to see that row. This
reference lists the various operators and functions you can use to create rules.
For information on how to use the row level security functions and operators, see About Rule-Based
Row Level Security. There is a special variable called ts_groups, which you can use when creating row
level security rules. It fetches a list of the groups that the currently logged in user belongs to. For each
row, f the expression in the rule evaluates to ‘true’ for any one of these groups, that row will be shown to
the user.
You can also see this list of operators and examples from within the Rule Builder by selecting Rule
Assistant
Assistant.

Conversion functions
These functions can be used to convert data from one data type to another. Conversion to or from date
data types is not supported.
Function
to_bool

Description
Returns the input as a boolean (true or false).

Examples
to_bool (0) = false
to_bool (married)

to_date

to_double

Accepts a date represented as an integer or text
string, and a second string parameter that can
include strptime date formatting elements. Replaces all the valid strptime date formatting elements with their string counterparts and returns
the result. Does not accept epoch formatted
dates as input.
Returns the input as a double.

to_date (date_sold, '%Y%m-%d')

to_double ('3.14') = 3.14
to_double (revenue * .01)

to_integer

Returns the input as an integer.

to_integer ('45') + 1 =
46
to_integer (price + tax cost)

to_string

Returns the input as a text string. To convert a
date to a string, specify the date format you
want to use.

to_string (45 + 1) = '46'
to_string (revenue cost)
to_string
(date,('%m/%d/%y'))

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Row level security rules reference

February 06, 2019

Date functions
Function
add_days

Description
Returns the result of
adding the specified
number of days to
the given date.

Examples
add_days (01/30/2015, 5) = 02/04/
2015
add_days (invoiced, 30)

date

Returns the date
portion of a given
date.

date (home visit)

day

Returns the number
(1-31) of the day for
the given date.

day (01/15/2014) = 15

day_number_of_quarter

day_number_of_week

ThoughtSpot Administration Guide

Returns the number
of the day in a quarter for a given date.
Add an optional
second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01.)
Returns the number
(1-7) of the day in a
week for a given
date with 1 being
Monday and 7 being
Sunday.

day (date ordered)

day_number_of_quarter (01/30/2015)
= 30
day_number_of_quarter (01/30/2015,
'fiscal') = 91

day_number_of_week(01/15/2014) = 3
day_number_of_week (shipped)

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Row level security rules reference

Function
day_number_of_year

day_of_week

diff_days

diff_time

February 06, 2019

Description
Returns the number
(1-366) of the day in
a year from a given
date. Add an optional second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01.)
Returns the day of
the week for the given date.
Subtracts the second date from the
first date and returns
the result in number
of days, rounded
down if not exact.
Subtracts the second date from the
first date and returns
the result in number
of seconds.

Examples
day_number_of_year (01/30/2015) =
30
day_number_of_year ( 01/30/2015,
'fiscal' ) = 275
day_number_of_year (invoiced)

day_of week (01/30/2015) = Friday
day_of_week (serviced)

diff_days (01/15/2014, 01/17/2014)
= -2
diff_days (purchased, shipped)

diff_time (01/01/2014, 01/01/2014)
= -86,400
diff_time (clicked, submitted)

hour_of_day

Returns the hour of
the day for the given
date.

hour_of_day (received)

is_weekend

Returns true if the
given date falls on a
Saturday or Sunday.

is_weekend (01/31/2015) = true

Returns the month
from the given date.

month (01/15/2014) = January

month

ThoughtSpot Administration Guide

is_weekend (emailed)

month (date ordered)

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Row level security rules reference

Function
month_number

month_number_of_quarter

February 06, 2019

Description
Returns the number
(1-12) of the month
from a given date.
Add an optional
second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01.)
Returns the month
(1-3) number for the
given date in a quarter. Add an optional
second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01.)

Examples
month_number (09/20/2014) = 9
month_number ( 09/20/2014, 'fiscal'
) = 5
month_number (purchased)

month_number_of_quarter (02/20/
2018) = 2
month_number_of_quarter (02/20/
2018,'fiscal' ) = 1

now

Returns the current
timestamp.

now ()

quarter_number

Returns the number
(1-4) of the quarter
associated with the
given date. Add an
optional second parameter to specify
'fiscal' or 'calendar'
dates. Default is
'calendar'. (In examples, start of fiscal
year is set to May
01.)

quarter_number ( 04/14/2014) = 2

ThoughtSpot Administration Guide

quarter_number ( 04/14/2014, 'fiscal' ) = 4
quarter_number ( shipped )

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Row level security rules reference

Function
start_of_month

start_of_quarter

start_of_week

start_of_year

time

ThoughtSpot Administration Guide

February 06, 2019

Description
Returns MMM yyyy
for the first day of
the month. Your installation configuration can override
this setting so that it
returns a different
format such as MM/
dd/yyyy . Speak
with your
ThoughtSpot administrator for information on doing this.
Returns the date for
the first day of the
quarter for the given
date. Add an optional second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01.)
Returns the date for
the first day of the
week for the given
date.
Returns the date for
the first day of the
year for the given
date. Add an optional second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01.)
Returns the time
portion of a given
date.

Examples
start_of_month ( 01/31/2015 ) = Jan
FY 2015
start_of_month (shipped)

start_of_quarter ( 04/01/2014) =
Apr 2014
start_of_quarter ( 04/01/2014, 'fiscal') = Feb 2014
start_of_quarter (sold)

start_of_week ( 06/01/2015 ) = 05/
30/2015 Week
start_of_week (emailed)

start_of_year (04/01/2014) returns
Jan 2014
start_of_year (04/01/2014, 'fiscal') returns May 2013
start_of_year (joined)

time (3/1/2002 10:32) = 10:32
time (call began)

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Row level security rules reference

Function
week_number_of_month

week_number_of_quarter

week_number_of_year

year

ThoughtSpot Administration Guide

February 06, 2019

Description

Examples

Returns the week
number for the given
date in a month.

Returns the week
number for the given
date in a quarter.
Add an optional
second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01.)
Returns the week
number for the given
date in a year. Add
an optional second
parameter to specify
whether a 'fiscal' or
'calendar' year is
used to calculate
the result. Default is
'calendar'. (In examples, start of fiscal
year is set to May
01.)
Returns the year
from a given date.
Add an optional
second parameter
to specify whether a
'fiscal' or 'calendar'
year is used to calculate the result.
Default is 'calendar'.
(In examples, start
of fiscal year is set
to May 01. Per standard convention, the
fiscal year is defined
by the year-end
date.)

week_number_of_month(03/23/2017) =

week_number_of_quarter (04/03/2017)
= 1
week_number_of_quarter (04/03/2017,
'fiscal') = 10

week_number_of_year (01/17/2014) =
3
week_number_of_year ( 01/17/2014,
'fiscal') = 38

year (01/15/2014) = 2014
year (12/15/2013, 'fiscal' ) = 2014
year (date ordered)

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Row level security rules reference

February 06, 2019

Mixed functions
These functions can be used with text and numeric data types.
Function
!=

greatest

Description

Examples

Returns true if the first value is not
equal to the second value.

3 != 2 = true

Returns true if the first value is less
than the second value.

3 < 2 = false

Returns true if the first value is less
than or equal to the second value.

1 <= 2 = true

Returns true if the first value is equal to
the second value.

2 = 2 = true

Returns true if the first value is greater
than the second value.

3 > 2 = true

Returns true if the first value is greater
than or equal to the second value.

3 >= 2 = true

Returns the larger of the values.

greatest (20, 10) = 20

revenue != 1000000

revenue < 1000000

revenue <= 1000000

revenue = 1000000

revenue > 1000000

revenue >= 1000000

greatest (q1 revenue, q2 revenue)
least

Returns the smaller of the values.

least (20, 10) = 10
least (q1 revenue, q2 revenue)

Number functions
Function
*

ThoughtSpot Administration Guide

Description

Examples

Returns the result of multiplying
both numbers.

3 * 2 = 6

Returns the result of adding both
numbers.

1 + 2 = 3

Returns the result of subtracting
the second number from the first.

3 - 2 = 1

Returns the result of dividing the
first number by the second.

6 / 3 = 2

price * taxrate

price + shipping

revenue - tax

markup / retail price

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Row level security rules reference

Function
^

abs

February 06, 2019

Description

Examples

Returns the first number raised to
the power of the second.

3 ^ 2 = 9

Returns the absolute value.

abs (-10) = 10

width ^ 2

abs (profit)
acos

asin

atan

atan2

cbrt

ceil

cos

cube

Returns the inverse cosine in degrees.

acos (0.5) = 60

Returns the inverse sine (specified in degrees).

asin (0.5) = 30

Returns the inverse tangent in
degrees.

atan (1) = 45

Returns the inverse tangent in
degrees.

atan2 (10, 10) = 45

Returns the cube root of a number.

cbrt (27) = 3

Returns the smallest following integer.

ceil (5.9) = 6

Returns the cosine of an angle
(specified in degrees).

cos (63) = 0.45

Returns the cube of a number.

cube (3) = 27

acos (cos-satellite-angle)

asin (sin-satellite-angle)

atan (tan-satellite-angle)

atan2 (longitude, latitude)

cbrt (volume)

ceil (growth rate)

cos (beam angle)

cube (length)
exp

exp2

Returns Euler’s number (~2.718)
raised to a power.

exp (2) = 7.38905609893

Returns 2 raised to a power.

exp2 (3) = 8

exp (growth)

exp2 (growth)
floor

Returns the largest previous integer.

floor (5.1) = 5

Returns the natural logarithm.

ln (7.38905609893) = 2

floor (growth rate)

ln (distance)
log10

log2

mod

ThoughtSpot Administration Guide

Returns the logarithm with base
10.

log10 (100) = 2

Returns the logarithm with base 2
(binary logarithm).

log2 (32) = 5

Returns the remainder of first
number divided by the second
number.

mod (8, 3) = 2

log10 (volume)

log2 (volume)

mod ( revenue , quantity )

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Row level security rules reference

Function
pow

random

round

safe_divide

sign

sin

spherical_distance

February 06, 2019

Description

Examples

Returns the first number raised to
the power of the second number.

pow (5, 2) = 25

Returns a random number between 0 and 1.

random ( ) = .457718

Returns the first number rounded
to the second number (the default is 1).

round (35.65, 10) = 40

Returns the result of dividing the
first number by the second. If the
second number is 0, returns 0 instead of NaN (not a number).

safe_divide (12, 0) = 0

pow (width, 2)

random ( )

round (battingavg, 100)

safe_divide (total_cost,
units)

Returns +1 if the number is
greater than zero, -1 if less than
zero, 0 if zero.

sign (-250) = -1

Returns the sine of an angle
(specified in degrees).

sin (35) = 0.57

Returns the distance in km between two points on Earth.

sign (growth rate)

sin (beam angle)
spherical_distance
(37.465191, -122.153617,
37.421962, -122.142174) =
4,961.96
spherical_distance (start_latitude, start_longitude,
start_latitude, start_longitude)

sqrt

Returns the square of a numeric
value.

sq (9) = 81

Returns the square root.

sqrt (9) = 3

sq (width)

sqrt (area)
tan

ThoughtSpot Administration Guide

Returns the tangent of an angle
(specified in degrees).

tan (35) = 0.7
tan (beam angle)

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Row level security rules reference

February 06, 2019

Operators
Operator
and

Description

Examples

Returns true when both conditions
are true, otherwise returns false.

(1 = 1) and (3 > 2) = true
lastname = 'smith' and state
='texas'

 Note: Not available for row level
security (RLS) formulas.

if…then…else

Conditional operator.

if (3 > 2) then 'bigger' else
'not bigger'
if (cost > 500) then 'flag' else
'approve'

ifnull

Returns the first value if it is not null,
otherwise returns the second.

ifnull (cost, 'unknown')

isnull

Returns true if the value is null.

isnull (phone)

not

Returns true if the condition is false,
otherwise returns false.

not (3 > 2) = false

Returns true when either condition is
true, otherwise returns false.

(1 = 5) or (3 > 2) = true

not (state = 'texas')

state = 'california' or state
='oregon'

Text functions
Function
concat

contains

Description
Returns the one or more values
as a concatenated text string.
Be sure to use single quotes
instead of double quotes
around each of the strings.
Returns true if the first string
contains the second string,
otherwise returns false.

Examples
concat ( 'hay' , 'stack' )
= 'haystack'
concat (last_name ,
first_name )

contains ('broomstick',
'room') = true
contains (product, 'trial
version')

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Page 356

Row level security rules reference

Function
edit_distance

edit_distance_with_cap

similar_to

similarity

spells_like

ThoughtSpot Administration Guide

February 06, 2019

Description
Accepts two text strings. Returns the edit distance (minimum number of operations required to transform one string
into the other) as an integer.
Works with strings under 1023
characters.
Accepts two text strings and
an integer to specify the upper
limit cap for the edit distance
(minimum number of operations required to transform one
string into the other). If the edit
distance is less than or equal
to the specified cap, returns
the edit distance. If it is higher
than the cap, returns the cap
plus 1. Works with strings under 1023 characters.
Accepts a document text string
and a search text string. Returns true if relevance score
(0-100) of the search string
with respect to the document
is greater than or equal to 20.
Relevance is based on edit distance, number of words in the
query, and length of words in
the query which are present in
the document.
Accepts a document text string
and a search text string. Returns the relevance score
(0-100) of the search string
with respect to the document.
Relevance is based on edit distance, number of words in the
query, and length of words in
the query which are present in
the document. If the two
strings are an exact match, returns 100.
Accepts two text strings. Returns true if they are spelled
similarly and false if they are
not. Works with strings under
1023 characters.

Examples
edit_distance ('attorney',
'atty') = 4
edit_distance (color,
'red')

edit_distance_with_cap
('pokemon go', 'minecraft
pixelmon', 3) = 4
edit_distance_with_cap
(event, 'burning man', 3)

similar_to ('hello world',
'hello swirl') = true
similar_to (current team,
drafted by)

similarity ('where is the
burning man concert', 'burning man') = 46
similarity (tweet1, tweet2)

spells_like ('thouhgtspot',
'thoughtspot') = true
spells_like (studio, distributor)

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Row level security rules reference

Function

February 06, 2019

Description
Returns the length of the text.

strlen

Examples
strlen ('smith') = 5
strlen (lastname)

Returns the numeric position
(starting from 0) of the first occurrence of the second string
in the first string, or -1 if not
found.

strpos

Returns the portion of the given string, beginning at the location specified (starting from
0), and of the given length.

substr

strpos ('haystack_with_needles', 'needle') = 14
strpos (complaint,
'lawyer')

substr ('persnickety', 3,
7) = snicket
substr (lastname, 0, 5)

Variables
These variables can be used in your expressions.
Function

Description

Examples

ts_groups

Returns a list of all the groups the current logged
in user belongs to. For any row, if the expression
evaluates to true for any of the groups, the user
can see that row.

ts_groups = 'east'

ts_username

Returns the user with the matching neame.

ts_username != 'mark'

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Page 358

Formula function reference

February 06, 2019

Formula function reference
ThoughtSpot allows you to create derived columns in worksheets using formulas. You create these
columns by building formulas using the Formula Assistant
Assistant. An individual formula is constructed from n
combination of operators and functions.
This reference lists the various operators and functions you can use to create formulas.

Operators
Operator
and

Description
Returns true when both conditions
are true, otherwise returns false.

Examples
(1 = 1) and (3 > 2) = true
lastname = 'smith' and state
='texas'

 Note: Not available for row level
security (RLS) formulas.

if…then…else

Conditional operator.

if (3 > 2) then 'bigger' else
'not bigger'
if (cost > 500) then 'flag' else
'approve'

ifnull

Returns the first value if it is not null,
otherwise returns the second.

ifnull (cost, 'unknown')

isnull

Returns true if the value is null.

isnull (phone)

not

Returns true if the condition is false,
otherwise returns false.

not (3 > 2) = false

Returns true when either condition is
true, otherwise returns false.

(1 = 5) or (3 > 2) = true

not (state = 'texas')

state = 'california' or state
='oregon'

Aggregate functions (group aggregate)
These functions can be used to aggregate data.
Function
average

ThoughtSpot Administration Guide

Description
Returns the average of all the values of a
column.

Examples
average (revenue)

Page 359

Formula function reference

Function
average_if

February 06, 2019

Description

Examples

Returns the average of all the columns that
meet a given criteria.

"San Francisco", rev-

average_if(city =
enue)

count

Returns the number of rows in the table
containing the column.

count_if

Returns the number of rows in the table
containing the column.

cumulative_average

cumulative_max

cumulative_min

cumulative_sum

group_aggregate

Takes a measure and one or more attributes. Returns the average of the measure, accumulated by the attribute(s) in the order
specified.
Takes a measure and one or more attributes. Returns the maximum of the measure,
accumulated by the attribute(s) in the order
specified.
Takes a measure and one or more attributes. Returns the minimum of the measure,
accumulated by the attribute(s) in the order
specified.
Takes a measure and one or more attributes. Returns the sum of the measure, accumulated by the attribute(s) in the order
specified.
Takes a measure and, optionally, attributes
and filters. These can be used to aggregate
measures with granularities and filters different from the terms/columns used in the
search. Especially useful for comparison
analysis.

count (product)

count_if(region
=’west’, region)
cumulative_average
(revenue, order date,
state)

cumulative_max (revenue, state)

cumulative_min (revenue, campaign)

cumulative_sum (revenue, order date)

group_aggregate (sum
(revenue) , {ship
mode, date} , {} )
group_aggregate (sum
(revenue) , {ship
mode , date},

This formula takes the form: group_aggregate (< aggregation (measure) >, < groupings >, < filters >)

{day_of_week (date) =

Lists can be defined with {} and optional list
functions query_groups or query_filters , which by default specify the lists or
filters used in the original search. Plus (+) or
(-) can be used to add or exclude specific
columns for query groups.

(revenue) ,

'friday'} )
group_aggregate (sum
query_groups() ,
query_filters() )
group_aggregate (sum
(revenue) ,
query_groups() +
{date} , query_filters() )

ThoughtSpot Administration Guide

Page 360

Formula function reference

Function
group_average

group_count

group_max

group_min

group_stddev

group_sum

group_unique_count

group_variance

February 06, 2019

Description

Examples

Takes a measure and one or more attributes. Returns the average of the measure
grouped by the attribute(s).

enue, customer re-

Takes a measure and one or more attributes. Returns the count of the measure
grouped by the attribute(s).

customer region)

Takes a measure and one or more attributes. Returns the maximum of the measure
grouped by the attribute(s).

customer region)

Takes a measure and one or more attributes. Returns the minimum of the measure
grouped by the attribute(s).

customer region)

Takes a measure and one or more attributes. Returns the standard deviation of the
measure grouped by the attribute(s).

enue, customer region)

Takes a measure and one or more attributes. Returns the sum of the measure
grouped by the attribute(s).

customer region)

Takes a measure and one or more attributes. Returns the unique count of the measure grouped by the attribute(s).

(product , supplier)

Takes a measure and one or more attributes. Returns the variance of the measure
grouped by the attribute(s).

enue, customer region)

max

Returns the maximum value of a column.

max_if

Returns the maximum value among
columns that meet a criteria.

group_average (revgion, state)
group_count (revenue,

group_max (revenue,

group_min (revenue,

group_stddev (rev-

group_sum (revenue,

group_unique_count

group_variance (rev-

max (sales)
max_if( (revenue >
10) , customer region
)

min

Returns the minimum value of a column.

min_if

Returns the minimum value among columns
that meet a criteria.

min (revenue)
min_if( (revenue <
10) , customer region
)

ThoughtSpot Administration Guide

Page 361

Formula function reference

Function
moving_average

moving_max

moving_min

moving_sum

ThoughtSpot Administration Guide

February 06, 2019

Description
Takes a measure, two integers to define the
window to aggregate over, and one or more
attributes. The window is (current Num1…Current + Num2) with both end
points being included in the window. For
example, “1,1” will have a window size of 3.
To define a window that begins before Current, specify a negative number for Num2.
Returns the average of the measure over
the given window. The attributes are the ordering columns used to compute the moving average.
Takes a measure, two integers to define the
window to aggregate over, and one or more
attributes. The window is (current Num1…Current + Num2) with both end
points being included in the window. For
example, “1,1” will have a window size of 3.
To define a window that begins before Current, specify a negative number for Num2.
Returns the maximum of the measure over
the given window. The attributes are the ordering columns used to compute the moving maximum.
Takes a measure, two integers to define the
window to aggregate over, and one or more
attributes. The window is (current Num1…Current + Num2) with both end
points being included in the window. For
example, “1,1” will have a window size of 3.
To define a window that begins before Current, specify a negative number for Num2.
Returns the minimum of the measure over
the given window. The attributes are the ordering columns used to compute the moving minimum.
Takes a measure, two integers to define the
window to aggregate over, and one or more
attributes. The window is (current Num1…Current + Num2) with both end
points being included in the window. For
example, “1,1” will have a window size of 3.
To define a window that begins before Current, specify a negative number for Num2.
Returns the sum of the measure over the
given window. The attributes are the ordering columns used to compute the moving
sum.

Examples
moving_average (revenue, 2, 1, customer
region)

moving_max (complaints, 1, 2, store
name)

moving_min (defects,
3, 1, product)

moving_sum (revenue,
1, 1, order date)

Page 362

Formula function reference

Function

February 06, 2019

Description

Examples

stddev

Returns the standard deviation of all values
of a column.

stddev_if

Returns a standard deviation values filtered
to meet a specific criteria.

stddev (revenue)

stddev_if( (revenue >
10) , (revenue/10.0) )

sum

Returns the sum of all the values of a column.

sum_if

Returns sum values filtered by a specific
criteria.

revenue)

Returns the number of unique values of a
column.

tomer)

Returns the number of unique values of a
column provided it meets a criteria.

enue > 10) , order

unique count

unique_count_if

sum (revenue)

sum_if(region=’west’,

unique count (cus-

unique_count_if( (revdate )

variance

Returns the variance of all the values of a
column.

variance_if

Returns the variance of all the values of a
column provided it meets a criteria..

variance (revenue)

variance_if( (revenue
> 10) , (revenue/
10.0) )

Conversion functions
These functions can be used to convert data from one data type to another. Conversion to or from date
data types is not supported.
Function
to_bool

Description
Returns the input as a boolean (true or false).

Examples
to_bool (0) = false
to_bool (married)

to_date

to_double

to_date (date_sold, '%Y%m-%d')

to_double ('3.14') = 3.14
to_double (revenue * .01)

ThoughtSpot Administration Guide

Page 363

Formula function reference

Function
to_integer

February 06, 2019

Description

Examples

Returns the input as an integer.

to_integer ('45') + 1 =
46
to_integer (price + tax cost)

to_string

Returns the input as a text string. To convert a
date to a string, specify the date format you
want to use.

to_string (45 + 1) = '46'
to_string (revenue cost)
to_string
(date,('%m/%d/%y'))

Date functions
Function
add_days

Description
Returns the result of
adding the specified
number of days to
the given date.

Examples
add_days (01/30/2015, 5) = 02/04/
2015
add_days (invoiced, 30)

date

Returns the date
portion of a given
date.

date (home visit)

day

Returns the number
(1-31) of the day for
the given date.

day (01/15/2014) = 15

day_number_of_quarter

day_number_of_week

ThoughtSpot Administration Guide

day (date ordered)

day_number_of_quarter (01/30/2015)
= 30
day_number_of_quarter (01/30/2015,
'fiscal') = 91

day_number_of_week(01/15/2014) = 3
day_number_of_week (shipped)

Page 364

Formula function reference

Function
day_number_of_year

day_of_week

diff_days

diff_time

February 06, 2019

Examples
day_number_of_year (01/30/2015) =
30
day_number_of_year ( 01/30/2015,
'fiscal' ) = 275
day_number_of_year (invoiced)

day_of week (01/30/2015) = Friday
day_of_week (serviced)

diff_days (01/15/2014, 01/17/2014)
= -2
diff_days (purchased, shipped)

diff_time (01/01/2014, 01/01/2014)
= -86,400
diff_time (clicked, submitted)

hour_of_day

Returns the hour of
the day for the given
date.

hour_of_day (received)

is_weekend

Returns true if the
given date falls on a
Saturday or Sunday.

is_weekend (01/31/2015) = true

Returns the month
from the given date.

month (01/15/2014) = January

month

ThoughtSpot Administration Guide

is_weekend (emailed)

month (date ordered)

Page 365

Formula function reference

Function
month_number

month_number_of_quarter

February 06, 2019

Examples
month_number (09/20/2014) = 9
month_number ( 09/20/2014, 'fiscal'
) = 5
month_number (purchased)

month_number_of_quarter (02/20/
2018) = 2
month_number_of_quarter (02/20/
2018,'fiscal' ) = 1

now

Returns the current
timestamp.

now ()

quarter_number

quarter_number ( 04/14/2014) = 2

ThoughtSpot Administration Guide

quarter_number ( 04/14/2014, 'fiscal' ) = 4
quarter_number ( shipped )

Page 366

Formula function reference

Function
start_of_month

start_of_quarter

start_of_week

start_of_year

time

ThoughtSpot Administration Guide

February 06, 2019

Examples
start_of_month ( 01/31/2015 ) = Jan
FY 2015
start_of_month (shipped)

start_of_quarter ( 04/01/2014) =
Apr 2014
start_of_quarter ( 04/01/2014, 'fiscal') = Feb 2014
start_of_quarter (sold)

start_of_week ( 06/01/2015 ) = 05/
30/2015 Week
start_of_week (emailed)

start_of_year (04/01/2014) returns
Jan 2014
start_of_year (04/01/2014, 'fiscal') returns May 2013
start_of_year (joined)

time (3/1/2002 10:32) = 10:32
time (call began)

Page 367

Formula function reference

Function
week_number_of_month

week_number_of_quarter

week_number_of_year

year

ThoughtSpot Administration Guide

February 06, 2019

Description

Examples

Returns the week
number for the given
date in a month.

week_number_of_month(03/23/2017) =

week_number_of_quarter (04/03/2017)
= 1
week_number_of_quarter (04/03/2017,
'fiscal') = 10

week_number_of_year (01/17/2014) =
3
week_number_of_year ( 01/17/2014,
'fiscal') = 38

year (01/15/2014) = 2014
year (12/15/2013, 'fiscal' ) = 2014
year (date ordered)

Page 368

Formula function reference

February 06, 2019

Mixed functions
These functions can be used with text and numeric data types.
Function
!=

greatest

Description

Examples

Returns true if the first value is not
equal to the second value.

3 != 2 = true

Returns true if the first value is less
than the second value.

3 < 2 = false

Returns true if the first value is less
than or equal to the second value.

1 <= 2 = true

Returns true if the first value is equal to
the second value.

2 = 2 = true

Returns true if the first value is greater
than the second value.

3 > 2 = true

Returns true if the first value is greater
than or equal to the second value.

3 >= 2 = true

Returns the larger of the values.

greatest (20, 10) = 20

revenue != 1000000

revenue < 1000000

revenue <= 1000000

revenue = 1000000

revenue > 1000000

revenue >= 1000000

greatest (q1 revenue, q2 revenue)
least

Returns the smaller of the values.

least (20, 10) = 10
least (q1 revenue, q2 revenue)

Number functions
Function
*

ThoughtSpot Administration Guide

Description

Examples

Returns the result of multiplying
both numbers.

3 * 2 = 6

Returns the result of adding both
numbers.

1 + 2 = 3

Returns the result of subtracting
the second number from the first.

3 - 2 = 1

Returns the result of dividing the
first number by the second.

6 / 3 = 2

price * taxrate

price + shipping

revenue - tax

markup / retail price

Page 369

Formula function reference

Function
^

abs

February 06, 2019

Description

Examples

Returns the first number raised to
the power of the second.

3 ^ 2 = 9

Returns the absolute value.

abs (-10) = 10

width ^ 2

abs (profit)
acos

asin

atan

atan2

cbrt

ceil

cos

cube

Returns the inverse cosine in degrees.

acos (0.5) = 60

Returns the inverse sine (specified in degrees).

asin (0.5) = 30

Returns the inverse tangent in
degrees.

atan (1) = 45

Returns the inverse tangent in
degrees.

atan2 (10, 10) = 45

Returns the cube root of a number.

cbrt (27) = 3

Returns the smallest following integer.

ceil (5.9) = 6

Returns the cosine of an angle
(specified in degrees).

cos (63) = 0.45

Returns the cube of a number.

cube (3) = 27

acos (cos-satellite-angle)

asin (sin-satellite-angle)

atan (tan-satellite-angle)

atan2 (longitude, latitude)

cbrt (volume)

ceil (growth rate)

cos (beam angle)

cube (length)
exp

exp2

Returns Euler’s number (~2.718)
raised to a power.

exp (2) = 7.38905609893

Returns 2 raised to a power.

exp2 (3) = 8

exp (growth)

exp2 (growth)
floor

Returns the largest previous integer.

floor (5.1) = 5

Returns the natural logarithm.

ln (7.38905609893) = 2

floor (growth rate)

ln (distance)
log10

log2

mod

ThoughtSpot Administration Guide

Returns the logarithm with base
10.

log10 (100) = 2

Returns the logarithm with base 2
(binary logarithm).

log2 (32) = 5

Returns the remainder of first
number divided by the second
number.

mod (8, 3) = 2

log10 (volume)

log2 (volume)

mod ( revenue , quantity )

Page 370

Formula function reference

Function
pow

random

round

safe_divide

sign

sin

spherical_distance

February 06, 2019

Description

Examples

Returns the first number raised to
the power of the second number.

pow (5, 2) = 25

Returns a random number between 0 and 1.

random ( ) = .457718

Returns the first number rounded
to the second number (the default is 1).

round (35.65, 10) = 40

Returns the result of dividing the
first number by the second. If the
second number is 0, returns 0 instead of NaN (not a number).

safe_divide (12, 0) = 0

pow (width, 2)

random ( )

round (battingavg, 100)

safe_divide (total_cost,
units)

Returns +1 if the number is
greater than zero, -1 if less than
zero, 0 if zero.

sign (-250) = -1

Returns the sine of an angle
(specified in degrees).

sin (35) = 0.57

Returns the distance in km between two points on Earth.

sign (growth rate)

sin (beam angle)
spherical_distance
(37.465191, -122.153617,
37.421962, -122.142174) =
4,961.96
spherical_distance (start_latitude, start_longitude,
start_latitude, start_longitude)

sqrt

Returns the square of a numeric
value.

sq (9) = 81

Returns the square root.

sqrt (9) = 3

sq (width)

sqrt (area)
tan

Returns the tangent of an angle
(specified in degrees).

tan (35) = 0.7
tan (beam angle)

Text functions
Function
concat

ThoughtSpot Administration Guide

Description
Returns the one or more values
as a concatenated text string.
Be sure to use single quotes
instead of double quotes
around each of the strings.

Examples
concat ( 'hay' , 'stack' )
= 'haystack'
concat (last_name ,
first_name )

Page 371

Formula function reference

Function
contains

February 06, 2019

Description

Examples

Returns true if the first string
contains the second string,
otherwise returns false.

'room') = true

contains ('broomstick',
contains (product, 'trial
version')

edit_distance

edit_distance_with_cap

similar_to

similarity

ThoughtSpot Administration Guide

Accepts two text strings. Returns the edit distance (minimum number of operations required to transform one string
into the other) as an integer.
Works with strings under 1023
characters.
Accepts two text strings and
an integer to specify the upper
limit cap for the edit distance
(minimum number of operations required to transform one
string into the other). If the edit
distance is less than or equal
to the specified cap, returns
the edit distance. If it is higher
than the cap, returns the cap
plus 1. Works with strings under 1023 characters.
Accepts a document text string
and a search text string. Returns true if relevance score
(0-100) of the search string
with respect to the document
is greater than or equal to 20.
Relevance is based on edit distance, number of words in the
query, and length of words in
the query which are present in
the document.
Accepts a document text string
and a search text string. Returns the relevance score
(0-100) of the search string
with respect to the document.
Relevance is based on edit distance, number of words in the
query, and length of words in
the query which are present in
the document. If the two
strings are an exact match, returns 100.

edit_distance ('attorney',
'atty') = 4
edit_distance (color,
'red')

edit_distance_with_cap
('pokemon go', 'minecraft
pixelmon', 3) = 4
edit_distance_with_cap
(event, 'burning man', 3)

similar_to ('hello world',
'hello swirl') = true
similar_to (current team,
drafted by)

similarity ('where is the
burning man concert', 'burning man') = 46
similarity (tweet1, tweet2)

Page 372

Formula function reference

Function
spells_like

strlen

February 06, 2019

Description
Accepts two text strings. Returns true if they are spelled
similarly and false if they are
not. Works with strings under
1023 characters.
Returns the length of the text.

Examples
spells_like ('thouhgtspot',
'thoughtspot') = true
spells_like (studio, distributor)

strlen ('smith') = 5
strlen (lastname)

strpos

substr

ThoughtSpot Administration Guide

Returns the numeric position
(starting from 0) of the first occurrence of the second string
in the first string, or -1 if not
found.
Returns the portion of the given string, beginning at the location specified (starting from
0), and of the given length.

strpos ('haystack_with_needles', 'needle') = 14
strpos (complaint,
'lawyer')

substr ('persnickety', 3,
7) = snicket
substr (lastname, 0, 5)

Page 373

Alerts code reference

February 06, 2019

Alerts code reference
This reference identifies the messages that can appear in the System Health > Overview > Critical Alerts
and in the Alerts dashboard.

Informational alerts
TASK_TERMINATED
Msg
Msg: Task {{.Service}}.{{.Task}} terminated on machine {{.Machine}}
Type
Type: INFO
This alert is raised when a task terminates.

DISK_ERROR
Msg
Msg: Machine {{.Machine}} has disk errors
Type
Type: INFO
Raised when a machine has disk errors.

ZK_AVG_LATENCY
Msg
Msg: Average Zookeeper latency is more than {{.Num}} msec
Type
Type: INFO
Raised when average Zookeeper latency is above a threshold.

ZK_MAX_LATENCY
Msg
Msg: Max Zookeeper latency is more than {{.Num}} msec
Type
Type: INFO
Raised when max Zookeeper latency is above a threshold.

ZK_MIN_LATENCY
Msg
Msg: Min Zookeeper latency is more than {{.Num}} msec
Type
Type: INFO
Raised when min Zookeeper latency is above a threshold.

ZK_OUTSTANDING_REQUESTS
Msg
Msg: Number of outstanding Zookeeper requests exceeds {{.Num}}
Type
Type: INFO

ThoughtSpot Administration Guide

Page 374

Alerts code reference

February 06, 2019

Raised when there are too many outstanding Zookeeper requests.

ZK_NUM_WATCHERS
Msg
Msg: Number of Zookeeper watchers exceeds {{.Num}}
Type
Type: INFO
Raised when there are too many Zookeeper watchers.

MASTER_ELECTION
Msg
Msg: {{.Machine}} elected as Orion Master
Type
Type: INFO
Raised when a new Orion Master is elected.

PERIODIC_BACKUP
Msg
Msg: {{.Process}} periodic backup for policy {{.Name}} failed.
Type
Type: INFO
Raised when periodic backup fails.

PERIODIC_SNAPSHOT
Msg
Msg: {{.Process}} periodic snapshot {{.Name}} failed.
Type
Type: INFO
Raised when a periodic snapshot fails.

HDFS_CORRUPTION
Msg
Msg: HDFS root directory is in a corrupted state.
Type
Type: INFO
Raised when HDFS root directory is corrupted.

APPLICATION_INVALID_STATE
Msg
Msg: {{.Service}}.{{.Task}} on {{.Machine}} at location {{.Location}}
Type
Type: INFO
Raised when Application raises invalid state alert.

UPDATE_START
Msg
Msg: Starting update of ThoughtSpot cluster {{.Cluster}}
Type
Type: INFO
Raised when update starts.

ThoughtSpot Administration Guide

Page 375

Alerts code reference

February 06, 2019

UPDATE_END
Msg
Msg: Finished update of ThoughtSpot cluster {{.Cluster}} to release {{.Release}}
Type
Type: INFO
Raised when update completes.

Errors
TIMELY_JOB_RUN_ERROR
Msg
Msg: Job run {{.Message}}
Type
Type: ERROR
Raised when a job run fails.

TIMELY_ERROR
Msg
Msg: Job manager {{.Message}}
Type
Type: ERROR
Raised when a job manager runs into an inconsistent state.

Warnings
DISK_SPACE
Msg
Msg: Machine {{.Machine}} has less than {{.Perc}}% disk space free
Type
Type: WARNING
Raised when a disk is low on available disk space. Valid only in the 3.2 version of ThoughtSpot.

ROOT_DISK_SPACE
Msg
Msg: Machine {{.Machine}} has less than {{.Perc}}% disk space free on root partition
Type
Type: WARNING
Raised when a machine is low on available disk space on root partition.

BOOT_DISK_SPACE
Msg
Msg: Machine {{.Machine}} has less than {{.Perc}}% disk space free on boot partition
Type
Type: WARNING
Raised when a machine is low on available disk space on boot partition.

ThoughtSpot Administration Guide

Page 376

Alerts code reference

February 06, 2019

UPDATE_DISK_SPACE
Msg
Msg: Machine {{.Machine}} has less than {{.Perc}}% disk space free on update
partition

Type
Type: WARNING
Raised when a machine is low on available disk space on update partition.

EXPORT_DISK_SPACE
Msg
Msg: Machine {{.Machine}} has less than {{.Perc}}% disk space free on export
partition

Type
Type: WARNING
Raised when a machine is low on available disk space on export partition.

HDFS_NAMENODE_DISK_SPACE
Msg
Msg: Machine {{.Machine}} has less than {{.Perc}}% disk space free on HDFS namenode
drive

Type
Type: WARNING
Raised when a machine is low on available disk space on HDFS namenode drive.

MEMORY
Msg
Msg: Machine {{.Machine}} has less than {{.Perc}}% memory free
Type
Type: WARNING
Raised when a machine is low on free memory.

OS_USERS
Msg
Msg: Machine {{.Machine}} has more than {{.Num}} logged in users
Type
Type: WARNING
Raised when a machine has too many users logged in.

OS_PROCS
Msg
Msg: Machine {{.Machine}} has more than {{.Num}} processes
Type
Type: WARNING
Raised when a machine has more too many processes.

SSH
Msg
Msg: Machine {{.Machine}} doesn't have an active SSH server

ThoughtSpot Administration Guide

Page 377

Alerts code reference

February 06, 2019

Type
Type: WARNING
Raised when a machine has more than 600 processes.

DISK_ERROR_EXTERNAL
Msg
Msg: Machine {{.Machine}} has disk errors
Type
Type: WARNING
Raised when more than 2 disk errors happen in a day.

ZK_FD_COUNT
Msg
Msg: Zookeeper has more than {{.Num}} open file descriptors
Type
Type: WARNING
Raised when there are too many open Zookeeper files.

ZK_EPHEMERAL_COUNT
Msg
Msg: Zookeeper has more than {{.Num}} ephemeral files
Type
Type: WARNING
Raised when there are too many Zookeeper ephemeral files.

HOST_DOWN
Msg
Msg: {{.Machine}} is down
Type
Type: WARNING
Raised when a host is down.

TASK_UNREACHABLE
Msg
Msg: {{.ServiceDesc}} on {{.Machine}} is unreachable over HTTP
Type
Type: WARNING
Raised when a task is unreachable over HTTP.

TASK_NOT_RUNNING
Msg
Msg: {{.ServiceDesc}} is not running
Type
Type: WARNING
Raised when a service task is not running on any machine in the cluster.

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Alerts code reference

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Critical alerts
TASK_FLAPPING
Msg
Msg: Task {{.Service}}.{{.Task}} terminated {{._actual_num_occurrences}} times in last
{{._earliest_duration_str}}

Type
Type: CRITICAL
This alert is raised when a task is crashing repeatedly. The service is evaluted across the whole cluster.
So, if a service crashes 5 times in a day across all nodes in the cluster, this alert is generated.

OREO_TERMINATED
Msg
Msg: Oreo terminated on machine {{.Machine}}
Type
Type: CRITICAL
This alert is raised when the Oreo daemon on a machine terminates due to an error. This typically
happens due to an error accessing Zookeeper, HDFS, or a hardware issue.

HDFS_DISK_SPACE
Msg
Msg: HDFS has less than {{.Perc}}% space free
Type
Type: CRITICAL
Raised when a HDFS cluster is low on total available disk space.

ZK_INACCESSIBLE
Msg
Msg: Zookeeper is not accessible
Type
Type: CRITICAL
Raised when Zookeeper is inaccessible.

PERIODIC_BACKUP_FLAPPING
Msg
Msg: Periodic backup failed {{._actual_num_occurrences}} times in last
{{._earliest_duration_str}}

Type
Type: CRITICAL
This alert is raised when a periodic backup failed repeatedly.

PERIODIC_SNAPSHOT_FLAPPING
Msg
Msg: Periodic snapshot failed {{._actual_num_occurrences}} times in last
{{._earliest_duration_str}}

Type
Type: CRITICAL

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Alerts code reference

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This alert is raised when periodic snapshot failed repeatedly.

APPLICATION_INVALID_STATE_EXTERNAL
Msg
Msg: {{.Service}}.{{.Task}} on {{.Machine}} at location {{.Location}}
Type
Type: CRITICAL
Raised when Application raises invalid state alert.

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Page 380

User action code reference

February 06, 2019

User action code reference
This reference identifies the user action codes that can appear in the System Health pages and in logs or
other reports.
answer_unsaved

User makes a change to tokens in the search
bar.

answer_saved

User opens an existing saved answer and makes
changes to tokens in the search bar.

answer_pinboard_context

User opens an existing saved pinboard, edits a
context viz and makes a change to tokens in the
search bar.

answer_aggregated_worksheet

User opens an existing saved aggregated worksheet and makes changes to tokens in the
search bar.

answer_upgrade

Requests made for the sole purpose of upgrade.

pinboard_view

User opens an existing saved pinboard.

pinboard_filter

User adds, removes or applies values to a pinboard filter.

pinboard_ad_hoc

User drills down in a pinboard viz.

data_chart_config

Request for new data being generated following
a chart config change.

data_show_underlying_row

Request to show underlying data for a data
row(s).

data_export

Request to export data.

pinboard_tspublic_runtime_filter

Request to TSPublic/pinboarddata with runtime
filters.

answer_aggregated_worksheet_save

User updates aggregated worksheet.

answer_add_new_filter

User adds a filter using the UI.

data_show_underlying_viz

Request to show underlying data for a data
row(s).

answer_view

User opens an existing, saved answer.

answer_viz_context_view

User opens an existing saved pinboard, edits a
context viz.

pinboard_insight_view

User opens SpotIQ tab pinboards.

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User action code reference

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pinboard_admin_view

User opens admin tab pinboards.

pinboard_embed_view

User opens embed pinboard from a URL.

pinboard_homepage_view

On loading of homepage pinboard.

pinboard_learn_view

On loading learn pinboard.

pinboard_tspublic_no_runtime_filter

Request to TSPublic/pinboard data without runtime filters.

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Page 382

Error code reference

February 06, 2019

Error code reference
Summary: List of error codes and messages.
This section lists error codes that can appear in ThoughtSpot, with summary information and actions to
take. Error codes and messages are shown in ThoughtSpot when something goes wrong. These
messages can appear in the application and in logs.
When you see an error code, you will also see a message with a brief summary of what has happened. If
there is a remediation action you can take, it will be listed in this references. If there is no action listed,
please contact ThoughtSpot Support.

 Tip: Only the base code number is listed for each error. So keep this in mind when searching
through these codes. For example, error code TS-00125 is simply listed as 125.

Metadata Errors (100 - 499)|
Code

Severity

Summary

Details

Action

TS-00100

INFO

Success. {1} has
been added to {2}.
\# {1} – name of visualization \# {2} –
{name/link to pinboard}

None

TS-00101

ERROR

Failure adding {1} to
{2}

Visualization could
not be added to {2}
\# {1} – name of visualization \# {2} –
name/link to pinboard

None

TS-00102

ERROR

Failure adding {1} to
{2} due to corruption

{1} could not be
added to {2} as the
pinboard has one or
more invalid visualizations

Please try again after
removing the invalid
visualization(s) from
{2} \# {1} – name of visualization \# {2} –
name/link to pinboard

TS-00103

INFO

Success. Visualization has been deleted from {1}. 1 –
name/link to pinboard

None

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Error code reference

February 06, 2019

TS-00104

ERROR

Failure deleting visual from {1}

Visualization could
not be deleted from
the pinboard. 1 –
name/link to pinboard

None

TS-00105

ERROR

Failure deleting visual from {1} due to
corruption

Visualization could
not be deleted from
{1} as the pinboard
has one or more invalid visualizations.
1 – name/link to pinboard

Please try again after
removing the invalid
visualization(s) from
the pinboard

TS-00106

INFO

Success. {1} created
successfully. 1 –
name/link to pinboard

None

TS-00107

ERROR

Failure creating {1}.
1 – name/link to pinboard

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00108

INFO

Sticker created successfully.

None

TS-00109

ERROR

Failure creating the
sticker.

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00110

INFO

Sticker deleted successfully.

None

TS-00111

ERROR

Failure deleting
sticker.

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00112

INFO

Pinboards deleted
successfully.

None

TS-00113

ERROR

Failure deleting pinboards

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00114

INFO

Answers deleted
successfully.

None

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Error code reference

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TS-00115

ERROR

Failure deleting answers

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00116

INFO

Tables deleted successfully.

None

TS-00117

ERROR

Failure deleting tables

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00118

INFO

Relationship created
successfully.

None

TS-00119

ERROR

Failure creating relationship

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00120

INFO

Relationship updated successfully.

None

TS-00121

ERROR

Failure updating the
relationship

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00122

INFO

Relationship deleted
successfully.

None

TS-00123

ERROR

Failure deleting the
relationship

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00124

ERROR

Failure fetching details for table

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00125

ERROR

Failure fetching details for the tables

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

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Error code reference

February 06, 2019

TS-00126

ERROR

Failure fetching details for datasource

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00127

ERROR

Failure fetching details for datasources

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00128

ERROR

Failure fetching details for metadata
items

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00129

ERROR

Failure opening the
answer

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00130

ERROR

Failure opening the
pinboard

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00131

ERROR

Failure opening the
worksheet

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00132

INFO

Table saved successfully.

None

TS-00133

ERROR

There was a problem saving the table

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00134

INFO

Visualization update
successful

None

TS-00135

ERROR

Visualization failed
to update

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

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Error code reference

February 06, 2019

TS-00136

INFO

{1} saved 1 – name
of answer

None

TS-00137

ERROR

{1} could not be
saved 1 – name of
answer

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00138

INFO

{1} saved 1 - name
of pinboard / link

None

TS-00139

ERROR

{1} could not be
saved 1 - name of
pinboard / link

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00140

INFO

{1} saved 1 – name
of worksheet

None

TS-00141

ERROR

{1} could not be
saved 1 – name of
worksheet

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00142

INFO

{1} saved 1 – name
of answer

None

TS-00143

ERROR

{1} could not be
saved

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}. 1 – name
of answer

None

TS-00144

INFO

{1} saved 1 – name/
link to pinboard

None

TS-00145

ERROR

{1} could not be
saved

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}. 1 – name
of pinboard

None

TS-00146

INFO

Worksheet saved

None

TS-00147

ERROR

Worksheet could not
be saved

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

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Error code reference

February 06, 2019

TS-00148

INFO

Sticker updated

None

TS-00149

ERROR

The sticker could
not be updated

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00150

INFO

Successfully assigned sticker

None

TS-00151

ERROR

The sticker could
not be assigned

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00152

INFO

Successfully unassigned sticker

None

TS-00153

ERROR

The sticker could
not be unassigned

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00154

ERROR

Failed to fetch metadata list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00155

ERROR

Failed to fetch table
list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00156

ERROR

Failed to fetch relationship list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00157

ERROR

Failed to fetch answer list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

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Error code reference

February 06, 2019

TS-00158

ERROR

Failed to fetch pinboard list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00159

ERROR

Failed to fetch worksheet list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00160

ERROR

Failed to fetch aggregated worksheet
list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00161

ERROR

Failed to fetch imported data list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00162

ERROR

Failed to fetch system table list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00163

ERROR

Failed to DB view
list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00164

ERROR

Failed to fetch data
source list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00165

ERROR

Failed to fetch column list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00166

ERROR

Failed to label list

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

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Error code reference

February 06, 2019

TS-00167

ERROR

Failed to fetch answer

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00168

ERROR

Failed to fetch worksheet

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00169

INFO

Aggregated worksheet {1} created 1 –
name of aggregated
worksheet

None

TS-00170

ERROR

Failure creating Aggregated Worksheet.

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00171

INFO

{1} updated 1 –
name of aggregated
worksheet

None

TS-00172

ERROR

{1} failed to update
1 – name of aggregated worksheet

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00173

ERROR

{1} failed to update
1 – name of the formula

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00174

ERROR

Comments cannot
be fetched

Failed to save client
state

None

TS-00175

ERROR

Comment cannot be
created

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00176

ERROR

Comment cannot be
updated

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

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Error code reference

February 06, 2019

TS-00177

ERROR

Comment cannot be
deleted

Uh oh. We’re not
sure what happened. Please email
the trace file to {adminEmail}.

None

TS-00178

INFO

Rule saved successfully

None

TS-00179

ERROR

Rule could not be
saved

We're not sure what
happened. Please
email the trace file
to {adminEmail}.

None

TS-00180

INFO

Rule deleted successfully

None

TS-00181

ERROR

Rule could not be
deleted

We're not sure what
happened. Please
email the trace file
to {adminEmail}.

None

TS-00182

INFO

Item deleted successfully.

None

TS-00183

ERROR

Item could not be
deleted.

We're not sure what
happened. Please
email the trace file
to {adminEmail}.

None

TS-00184

INFO

| ThoughtSpot Thought Spot Administration Guide 5.1

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