Postgre SQL Quick Guide

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PostgreSQL - Quick Guide
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PostgreSQL - Overview
PostgreSQL is a powerful, open source object-relational database system. It has more than
15 years of active development phase and a proven architecture that has earned it a
strong reputation for reliability, data integrity, and correctness.
This tutorial will give you a quick start with PostgreSQL and make you comfortable with
PostgreSQL programming.

What is PostgreSQL?
PostgreSQL (pronounced as post-gress-Q-L) is an open source relational database
management system (DBMS) developed by a worldwide team of volunteers. PostgreSQL is
not controlled by any corporation or other private entity and the source code is available
free of charge.

A Brief History of PostgreSQL
PostgreSQL, originally called Postgres, was created at UCB by a computer science
professor named Michael Stonebraker. Stonebraker started Postgres in 1986 as a follow-up
project to its predecessor, Ingres, now owned by Computer Associates.
1977-1985 − A project called INGRES was developed.
Proof-of-concept for relational databases
Established the company Ingres in 1980
Bought by Computer Associates in 1994
1986-1994 − POSTGRES



Development of the concepts in INGRES with a focus on object orientation
and the query language - Quel
The code base of INGRES was not used as a basis for POSTGRES
Commercialized as Illustra (bought by Informix, bought by IBM)
1994-1995 − Postgres95
Support for SQL was added in 1994
Released as Postgres95 in 1995
Re-released as PostgreSQL 6.0 in 1996
Establishment of the PostgreSQL Global Development Team

Key Features of PostgreSQL
PostgreSQL runs on all major operating systems, including Linux, UNIX (AIX, BSD, HP-UX,
SGI IRIX, Mac OS X, Solaris, Tru64), and Windows. It supports text, images, sounds, and
video, and includes programming interfaces for C / C++, Java, Perl, Python, Ruby, Tcl and
Open Database Connectivity (ODBC).
PostgreSQL supports a large part of the SQL standard and offers many modern features
including the following −
Complex SQL queries
SQL Sub-selects
Foreign keys
Trigger
Views
Transactions
Multiversion concurrency control (MVCC)
Streaming Replication (as of 9.0)
Hot Standby (as of 9.0)

You can check official documentation of PostgreSQL to understand the above-mentioned
features. PostgreSQL can be extended by the user in many ways. For example by adding
new −
Data types
Functions
Operators
Aggregate functions

Index methods

Procedural Languages Support
PostgreSQL supports four standard procedural languages, which allows the users to write
their own code in any of the languages and it can be executed by PostgreSQL database
server. These procedural languages are - PL/pgSQL, PL/Tcl, PL/Perl and PL/Python.
Besides, other non-standard procedural languages like PL/PHP, PL/V8, PL/Ruby, PL/Java,
etc., are also supported.

PostgreSQL - Environment Setup
To start understanding the PostgreSQL basics, first let us install the PostgreSQL. This
chapter explains about installing the PostgreSQL on Linux, Windows and Mac OS platforms.

Installing PostgreSQL on Linux/Unix
Follow the given steps to install PostgreSQL on your Linux machine. Make sure you are
logged in as root before you proceed for the installation.
Pick the version number of PostgreSQL you want and, as exactly as possible, the
platform you want from EnterpriseDB
I downloaded postgresql-9.2.4-1-linux-x64.run for my 64 bit CentOS-6
machine. Now, let us execute it as follows −
[root@host]# chmod +x postgresql-9.2.4-1-linux-x64.run
[root@host]# ./postgresql-9.2.4-1-linux-x64.run
-----------------------------------------------------------------------Welcome to the PostgreSQL Setup Wizard.
-----------------------------------------------------------------------Please specify the directory where PostgreSQL will be installed.
Installation Directory [/opt/PostgreSQL/9.2]:

Once you launch the installer, it asks you a few basic questions like location of the
installation, password of the user who will use database, port number, etc. So keep
all of them at their default values except password, which you can provide
password as per your choice. It will install PostgreSQL at your Linux machine and
will display the following message −
Please wait while Setup installs PostgreSQL on your computer.
Installing
0% ______________ 50% ______________ 100%
#########################################

----------------------------------------------------------------------Setup has finished installing PostgreSQL on your computer.

Follow the following post-installation steps to create your database −
[root@host]# su - postgres
Password:
bash-4.1$ createdb testdb
bash-4.1$ psql testdb
psql (8.4.13, server 9.2.4)
test=#

You can start/restart postgres server in case it is not running using the following
command −
[root@host]# service postgresql restart
Stopping postgresql service:
Starting postgresql service:

[
[

OK
OK

]
]

If your installation was correct, you will have PotsgreSQL prompt test=# as shown
above.

Installing PostgreSQL on Windows
Follow the given steps to install PostgreSQL on your Windows machine. Make sure you
have turned Third Party Antivirus off while installing.
Pick the version number of PostgreSQL you want and, as exactly as possible, the
platform you want from EnterpriseDB
I downloaded postgresql-9.2.4-1-windows.exe for my Windows PC running in 32bit
mode, so let us run postgresql-9.2.4-1-windows.exe as administrator to install
PostgreSQL. Select the location where you want to install it. By default, it is
installed within Program Files folder.

The next step of the installation process would be to select the directory where
your data would be stored. By default, it is stored under the "data" directory.

Next, the setup asks for password, so you can use your favorite password.

The next step; keep the port as default.

In the next step, when asked for "Locale", I selected "English, United States".
It takes a while to install PostgreSQL on your system. On completion of the
installation process, you will get the following screen. Uncheck the checkbox and
click the Finish button.

After the installation process is completed, you can access pgAdmin III, StackBuilder and
PostgreSQL shell from your Program Menu under PostgreSQL 9.2.

Installing PostgreSQL on Mac
Follow the given steps to install PostgreSQL on your Mac machine. Make sure you are
logged in as administrator before you proceed for the installation.
Pick the latest version number of PostgreSQL for Mac OS available at EnterpriseDB
I downloaded postgresql-9.2.4-1-osx.dmg for my Mac OS running with OS X
version 10.8.3. Now, let us open the dmg image in finder and just double click it
which will give you PostgreSQL installer in the following window −

Next, click the postgres-9.2.4-1-osx icon, which will give a warning message.
Accept the warning and proceed for further installation. It will ask for the
administrator password as seen in the following window −

Enter the password, proceed for the installation, and after this step, restart your Mac
machine. If you do not see the following window, start your installation once again.

Once you launch the installer, it asks you a few basic questions like location of the
installation, password of the user who will use database, port number etc.
Therefore, keep all of them at their default values except the password, which you
can provide as per your choice. It will install PostgreSQL in your Mac machine in
the Application folder which you can check −

Now, you can launch any of the program to start with. Let us start with SQL Shell.
When you launch SQL Shell, just use all the default values it displays except, enter
your password, which you had selected at the time of installation. If everything

goes fine, then you will be inside postgres database and a postgress# prompt will
be displayed as shown below −

Congratulations!!! Now you have your environment ready to start with PostgreSQL
database programming.

PostgreSQL - Syntax
This chapter provides a list of the PostgreSQL SQL commands, followed by the precise
syntax rules for each of these commands. This set of commands is taken from the psql
command-line tool. Now that you have Postgres installed, open the psql as −
Program Files → PostgreSQL 9.2 → SQL Shell(psql).
Using psql, you can generate a complete list of commands by using the \help command.
For the syntax of a specific command, use the following command −
postgres-# \help 

The SQL Statement
An SQL statement is comprised of tokens where each token can represent either a
keyword, identifier, quoted identifier, constant, or special character symbol. The table given
below uses a simple SELECT statement to illustrate a basic, but complete, SQL statement
and its components.
SELECT

id, name

FROM

states

Token Type

Keyword

Identifiers

Keyword

Identifier

Description

Command

Id and name columns

Clause

Table name

PostgreSQL SQL commands
ABORT
Abort the current transaction.
ABORT [ WORK | TRANSACTION ]

ALTER AGGREGATE
Change the definition of an aggregate function.
ALTER AGGREGATE name ( type ) RENAME TO new_name
ALTER AGGREGATE name ( type ) OWNER TO new_owner

ALTER CONVERSION
Change the definition of a conversion.
ALTER CONVERSION name RENAME TO new_name
ALTER CONVERSION name OWNER TO new_owner

ALTER DATABASE
Change a database specific parameter.
ALTER
ALTER
ALTER
ALTER

DATABASE
DATABASE
DATABASE
DATABASE

name
name
name
name

SET parameter { TO | = } { value | DEFAULT }
RESET parameter
RENAME TO new_name
OWNER TO new_owner

ALTER DOMAIN
Change the definition of a domain specific parameter.
ALTER
ALTER
ALTER
ALTER
ALTER

DOMAIN
DOMAIN
DOMAIN
DOMAIN
DOMAIN

name
name
name
name
name

{ SET DEFAULT expression | DROP DEFAULT }
{ SET | DROP } NOT NULL
ADD domain_constraint
DROP CONSTRAINT constraint_name [ RESTRICT | CASCADE ]
OWNER TO new_owner

ALTER FUNCTION
Change the definition of a function.
ALTER FUNCTION name ( [ type [, ...] ] ) RENAME TO new_name
ALTER FUNCTION name ( [ type [, ...] ] ) OWNER TO new_owner

ALTER GROUP
Change a user group.

ALTER GROUP groupname ADD USER username [, ... ]
ALTER GROUP groupname DROP USER username [, ... ]
ALTER GROUP groupname RENAME TO new_name

ALTER INDEX
Change the definition of an index.
ALTER INDEX name OWNER TO new_owner
ALTER INDEX name SET TABLESPACE indexspace_name
ALTER INDEX name RENAME TO new_name

ALTER LANGUAGE
Change the definition of a procedural language.
ALTER LANGUAGE name RENAME TO new_name

ALTER OPERATOR
Change the definition of an operator.
ALTER OPERATOR name ( { lefttype | NONE }, { righttype | NONE } )
OWNER TO new_owner

ALTER OPERATOR CLASS
Change the definition of an operator class.
ALTER OPERATOR CLASS name USING index_method RENAME TO new_name
ALTER OPERATOR CLASS name USING index_method OWNER TO new_owner

ALTER SCHEMA
Change the definition of a schema.
ALTER SCHEMA name RENAME TO new_name
ALTER SCHEMA name OWNER TO new_owner

ALTER SEQUENCE
Change the definition of a sequence generator.
ALTER SEQUENCE name [ INCREMENT [ BY ] increment ]
[ MINVALUE minvalue | NO MINVALUE ]
[ MAXVALUE maxvalue | NO MAXVALUE ]
[ RESTART [ WITH ] start ] [ CACHE cache ] [ [ NO ] CYCLE ]

ALTER TABLE
Change the definition of a table.

ALTER TABLE [ ONLY ] name [ * ]
action [, ... ]
ALTER TABLE [ ONLY ] name [ * ]
RENAME [ COLUMN ] column TO new_column
ALTER TABLE name
RENAME TO new_name

Where action is one of the following lines −
ADD [ COLUMN ] column_type [ column_constraint [ ... ] ]
DROP [ COLUMN ] column [ RESTRICT | CASCADE ]
ALTER [ COLUMN ] column TYPE type [ USING expression ]
ALTER [ COLUMN ] column SET DEFAULT expression
ALTER [ COLUMN ] column DROP DEFAULT
ALTER [ COLUMN ] column { SET | DROP } NOT NULL
ALTER [ COLUMN ] column SET STATISTICS integer
ALTER [ COLUMN ] column SET STORAGE { PLAIN | EXTERNAL | EXTENDED | MAIN }
ADD table_constraint
DROP CONSTRAINT constraint_name [ RESTRICT | CASCADE ]
CLUSTER ON index_name
SET WITHOUT CLUSTER
SET WITHOUT OIDS
OWNER TO new_owner
SET TABLESPACE tablespace_name

ALTER TABLESPACE
Change the definition of a tablespace.
ALTER TABLESPACE name RENAME TO new_name
ALTER TABLESPACE name OWNER TO new_owner

ALTER TRIGGER
Change the definition of a trigger.
ALTER TRIGGER name ON table RENAME TO new_name

ALTER TYPE
Change the definition of a type.
ALTER TYPE name OWNER TO new_owner

ALTER USER
Change a database user account.
ALTER
ALTER
ALTER
ALTER

USER
USER
USER
USER

name
name
name
name

[ [ WITH ] option [ ... ] ]
RENAME TO new_name
SET parameter { TO | = } { value | DEFAULT }
RESET parameter

Where option can be −

[
|
|
|

ENCRYPTED | UNENCRYPTED ] PASSWORD 'password'
CREATEDB | NOCREATEDB
CREATEUSER | NOCREATEUSER
VALID UNTIL 'abstime'

ANALYZE
Collect statistics about a database.
ANALYZE [ VERBOSE ] [ table [ (column [, ...] ) ] ]

BEGIN
Start a transaction block.
BEGIN [ WORK | TRANSACTION ] [ transaction_mode [, ...] ]

Where transaction_mode is one of −
ISOLATION LEVEL {
SERIALIZABLE | REPEATABLE READ | READ COMMITTED
| READ UNCOMMITTED
}
READ WRITE | READ ONLY

CHECKPOINT
Force a transaction log checkpoint.
CHECKPOINT

CLOSE
Close a cursor.
CLOSE name

CLUSTER
Cluster a table according to an index.
CLUSTER index_name ON table_name
CLUSTER table_name
CLUSTER

COMMENT
Define or change the comment of an object.
COMMENT ON {
TABLE object_name |

COLUMN table_name.column_name |
AGGREGATE agg_name (agg_type) |
CAST (source_type AS target_type) |
CONSTRAINT constraint_name ON table_name |
CONVERSION object_name |
DATABASE object_name |
DOMAIN object_name |
FUNCTION func_name (arg1_type, arg2_type, ...) |
INDEX object_name |
LARGE OBJECT large_object_oid |
OPERATOR op (left_operand_type, right_operand_type) |
OPERATOR CLASS object_name USING index_method |
[ PROCEDURAL ] LANGUAGE object_name |
RULE rule_name ON table_name |
SCHEMA object_name |
SEQUENCE object_name |
TRIGGER trigger_name ON table_name |
TYPE object_name |
VIEW object_name
}
IS 'text'

COMMIT
Commit the current transaction.
COMMIT [ WORK | TRANSACTION ]

COPY
Copy data between a file and a table.
COPY table_name [ ( column [, ...] ) ]
FROM { 'filename' | STDIN }
[ WITH ]
[ BINARY ]
[ OIDS ]
[ DELIMITER [ AS ] 'delimiter' ]
[ NULL [ AS ] 'null string' ]
[ CSV [ QUOTE [ AS ] 'quote' ]
[ ESCAPE [ AS ] 'escape' ]
[ FORCE NOT NULL column [, ...] ]
COPY table_name [ ( column [, ...] ) ]
TO { 'filename' | STDOUT }
[ [ WITH ]
[ BINARY ]
[ OIDS ]
[ DELIMITER [ AS ] 'delimiter' ]
[ NULL [ AS ] 'null string' ]
[ CSV [ QUOTE [ AS ] 'quote' ]
[ ESCAPE [ AS ] 'escape' ]
[ FORCE QUOTE column [, ...] ]

CREATE AGGREGATE
Define a new aggregate function.

CREATE AGGREGATE name (
BASETYPE = input_data_type,
SFUNC = sfunc,
STYPE = state_data_type
[, FINALFUNC = ffunc ]
[, INITCOND = initial_condition ]
)

CREATE CAST
Define a new cast.
CREATE CAST (source_type AS target_type)
WITH FUNCTION func_name (arg_types)
[ AS ASSIGNMENT | AS IMPLICIT ]
CREATE CAST (source_type AS target_type)
WITHOUT FUNCTION
[ AS ASSIGNMENT | AS IMPLICIT ]

CREATE CONSTRAINT TRIGGER
Define a new constraint trigger.
CREATE CONSTRAINT TRIGGER name
AFTER events ON
table_name constraint attributes
FOR EACH ROW EXECUTE PROCEDURE func_name ( args )

CREATE CONVERSION
Define a new conversion.
CREATE [DEFAULT] CONVERSION name
FOR source_encoding TO dest_encoding FROM func_name

CREATE DATABASE
Create a new database.
CREATE DATABASE name
[ [ WITH ] [ OWNER [=] db_owner ]
[ TEMPLATE [=] template ]
[ ENCODING [=] encoding ]
[ TABLESPACE [=] tablespace ]
]

CREATE DOMAIN
Define a new domain.
CREATE DOMAIN name [AS] data_type
[ DEFAULT expression ]
[ constraint [ ... ] ]

Where constraint is −
[ CONSTRAINT constraint_name ]
{ NOT NULL | NULL | CHECK (expression) }

CREATE FUNCTION
Define a new function.
CREATE [ OR REPLACE ] FUNCTION name ( [ [ arg_name ] arg_type [, ...] ] )
RETURNS ret_type
{ LANGUAGE lang_name
| IMMUTABLE | STABLE | VOLATILE
| CALLED ON NULL INPUT | RETURNS NULL ON NULL INPUT | STRICT
| [ EXTERNAL ] SECURITY INVOKER | [ EXTERNAL ] SECURITY DEFINER
| AS 'definition'
| AS 'obj_file', 'link_symbol'
} ...
[ WITH ( attribute [, ...] ) ]

CREATE GROUP
Define a new user group.
CREATE GROUP name [ [ WITH ] option [ ... ] ]
Where option can be:
SYSID gid
| USER username [, ...]

CREATE INDEX
Define a new index.
CREATE [ UNIQUE ] INDEX name ON table [ USING method ]
( { column | ( expression ) } [ opclass ] [, ...] )
[ TABLESPACE tablespace ]
[ WHERE predicate ]

CREATE LANGUAGE
Define a new procedural language.
CREATE [ TRUSTED ] [ PROCEDURAL ] LANGUAGE name
HANDLER call_handler [ VALIDATOR val_function ]

CREATE OPERATOR
Define a new operator.
CREATE OPERATOR name (
PROCEDURE = func_name
[, LEFTARG = left_type ] [, RIGHTARG = right_type ]
[, COMMUTATOR = com_op ] [, NEGATOR = neg_op ]

[,
[,
[,
[,

RESTRICT = res_proc ] [, JOIN = join_proc ]
HASHES ] [, MERGES ]
SORT1 = left_sort_op ] [, SORT2 = right_sort_op ]
LTCMP = less_than_op ] [, GTCMP = greater_than_op ]

)

CREATE OPERATOR CLASS
Define a new operator class.
CREATE OPERATOR CLASS name [ DEFAULT ] FOR TYPE data_type
USING index_method AS
{ OPERATOR strategy_number operator_name [ ( op_type, op_type ) ] [ RECHECK ]
| FUNCTION support_number func_name ( argument_type [, ...] )
| STORAGE storage_type
} [, ... ]

CREATE RULE
Define a new rewrite rule.
CREATE [ OR REPLACE ] RULE name AS ON event
TO table [ WHERE condition ]
DO [ ALSO | INSTEAD ] { NOTHING | command | ( command ; command ... ) }

CREATE SCHEMA
Define a new schema.
CREATE SCHEMA schema_name
[ AUTHORIZATION username ] [ schema_element [ ... ] ]
CREATE SCHEMA AUTHORIZATION username
[ schema_element [ ... ] ]

CREATE SEQUENCE
Define a new sequence generator.
CREATE [ TEMPORARY | TEMP ] SEQUENCE name
[ INCREMENT [ BY ] increment ]
[ MINVALUE minvalue | NO MINVALUE ]
[ MAXVALUE maxvalue | NO MAXVALUE ]
[ START [ WITH ] start ] [ CACHE cache ] [ [ NO ] CYCLE ]

CREATE TABLE
Define a new table.
CREATE [ [ GLOBAL | LOCAL ] {
TEMPORARY | TEMP } ] TABLE table_name ( {
column_name data_type [ DEFAULT default_expr ] [ column_constraint [ ... ] ]
| table_constraint
| LIKE parent_table [ { INCLUDING | EXCLUDING } DEFAULTS ]
} [, ... ]

)
[
[
[
[

INHERITS ( parent_table [, ... ] ) ]
WITH OIDS | WITHOUT OIDS ]
ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
TABLESPACE tablespace ]

Where column_constraint is −
[ CONSTRAINT constraint_name ] {
NOT NULL |
NULL |
UNIQUE [ USING INDEX TABLESPACE tablespace ] |
PRIMARY KEY [ USING INDEX TABLESPACE tablespace ] |
CHECK (expression) |
REFERENCES ref_table [ ( ref_column ) ]
[ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ]
[ ON DELETE action ] [ ON UPDATE action ]
}
[ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

And table_constraint is −
[ CONSTRAINT constraint_name ]
{ UNIQUE ( column_name [, ... ] ) [ USING INDEX TABLESPACE tablespace ] |
PRIMARY KEY ( column_name [, ... ] ) [ USING INDEX TABLESPACE tablespace ] |
CHECK ( expression ) |
FOREIGN KEY ( column_name [, ... ] )
REFERENCES ref_table [ ( ref_column [, ... ] ) ]
[ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ]
[ ON DELETE action ] [ ON UPDATE action ] }
[ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

CREATE TABLE AS
Define a new table from the results of a query.
CREATE [ [ GLOBAL | LOCAL ] { TEMPORARY | TEMP } ] TABLE table_name
[ (column_name [, ...] ) ] [ [ WITH | WITHOUT ] OIDS ]
AS query

CREATE TABLESPACE
Define a new tablespace.
CREATE TABLESPACE tablespace_name [ OWNER username ] LOCATION 'directory'

CREATE TRIGGER
Define a new trigger.
CREATE TRIGGER name { BEFORE | AFTER } { event [ OR ... ] }
ON table [ FOR [ EACH ] { ROW | STATEMENT } ]
EXECUTE PROCEDURE func_name ( arguments )

CREATE TYPE
Define a new data type.
CREATE TYPE name AS
( attribute_name data_type [, ... ] )
CREATE TYPE name (
INPUT = input_function,
OUTPUT = output_function
[, RECEIVE = receive_function ]
[, SEND = send_function ]
[, ANALYZE = analyze_function ]
[, INTERNALLENGTH = { internal_length | VARIABLE } ]
[, PASSEDBYVALUE ]
[, ALIGNMENT = alignment ]
[, STORAGE = storage ]
[, DEFAULT = default ]
[, ELEMENT = element ]
[, DELIMITER = delimiter ]
)

CREATE USER
Define a new database user account.
CREATE USER name [ [ WITH ] option [ ... ] ]

Where option can be −
SYSID uid
| [ ENCRYPTED | UNENCRYPTED ] PASSWORD 'password'
| CREATEDB | NOCREATEDB
| CREATEUSER | NOCREATEUSER
| IN GROUP group_name [, ...]
| VALID UNTIL 'abs_time'

CREATE VIEW
Define a new view.
CREATE [ OR REPLACE ] VIEW name [ ( column_name [, ...] ) ] AS query

DEALLOCATE
Deallocate a prepared statement.
DEALLOCATE [ PREPARE ] plan_name

DECLARE
Define a cursor.

DECLARE name [ BINARY ] [ INSENSITIVE ] [ [ NO ] SCROLL ]
CURSOR [ { WITH | WITHOUT } HOLD ] FOR query
[ FOR { READ ONLY | UPDATE [ OF column [, ...] ] } ]

DELETE
Delete rows of a table.
DELETE FROM [ ONLY ] table [ WHERE condition ]

DROP AGGREGATE
Remove an aggregate function.
DROP AGGREGATE name ( type ) [ CASCADE | RESTRICT ]

DROP CAST
Remove a cast.
DROP CAST (source_type AS target_type) [ CASCADE | RESTRICT ]

DROP CONVERSION
Remove a conversion.
DROP CONVERSION name [ CASCADE | RESTRICT ]

DROP DATABASE
Remove a database.
DROP DATABASE name

DROP DOMAIN
Remove a domain.
DROP DOMAIN name [, ...] [ CASCADE | RESTRICT ]

DROP FUNCTION
Remove a function.
DROP FUNCTION name ( [ type [, ...] ] ) [ CASCADE | RESTRICT ]

DROP GROUP
Remove a user group.

DROP GROUP name

DROP INDEX
Remove an index.
DROP INDEX name [, ...] [ CASCADE | RESTRICT ]

DROP LANGUAGE
Remove a procedural language.
DROP [ PROCEDURAL ] LANGUAGE name [ CASCADE | RESTRICT ]

DROP OPERATOR
Remove an operator.
DROP OPERATOR name ( { left_type | NONE }, { right_type | NONE } )
[ CASCADE | RESTRICT ]

DROP OPERATOR CLASS
Remove an operator class.
DROP OPERATOR CLASS name USING index_method [ CASCADE | RESTRICT ]

DROP RULE
Remove a rewrite rule.
DROP RULE name ON relation [ CASCADE | RESTRICT ]

DROP SCHEMA
Remove a schema.
DROP SCHEMA name [, ...] [ CASCADE | RESTRICT ]

DROP SEQUENCE
Remove a sequence.
DROP SEQUENCE name [, ...] [ CASCADE | RESTRICT ]

DROP TABLE
Remove a table.
DROP TABLE name [, ...] [ CASCADE | RESTRICT ]

DROP TABLESPACE
Remove a tablespace.
DROP TABLESPACE tablespace_name

DROP TRIGGER
Remove a trigger.
DROP TRIGGER name ON table [ CASCADE | RESTRICT ]

DROP TYPE
Remove a data type.
DROP TYPE name [, ...] [ CASCADE | RESTRICT ]

DROP USER
Remove a database user account.
DROP USER name

DROP VIEW
Remove a view.
DROP VIEW name [, ...] [ CASCADE | RESTRICT ]

END
Commit the current transaction.
END [ WORK | TRANSACTION ]

EXECUTE
Execute a prepared statement.
EXECUTE plan_name [ (parameter [, ...] ) ]

EXPLAIN
Show the execution plan of a statement.
EXPLAIN [ ANALYZE ] [ VERBOSE ] statement

FETCH
Retrieve rows from a query using a cursor.
FETCH [ direction { FROM | IN } ] cursor_name

Where direction can be empty or one of −
NEXT
PRIOR
FIRST
LAST
ABSOLUTE count
RELATIVE count
count
ALL
FORWARD
FORWARD count
FORWARD ALL
BACKWARD
BACKWARD count
BACKWARD ALL

GRANT
Define access privileges.
GRANT { { SELECT | INSERT | UPDATE | DELETE | RULE | REFERENCES | TRIGGER }
[,...] | ALL [ PRIVILEGES ] }
ON [ TABLE ] table_name [, ...]
TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]
GRANT { { CREATE | TEMPORARY | TEMP } [,...] | ALL [ PRIVILEGES ] }
ON DATABASE db_name [, ...]
TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]
GRANT { CREATE | ALL [ PRIVILEGES ] }
ON TABLESPACE tablespace_name [, ...]
TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]
GRANT { EXECUTE | ALL [ PRIVILEGES ] }
ON FUNCTION func_name ([type, ...]) [, ...]
TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]
GRANT { USAGE | ALL [ PRIVILEGES ] }
ON LANGUAGE lang_name [, ...]
TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]
GRANT { { CREATE | USAGE } [,...] | ALL [ PRIVILEGES ] }
ON SCHEMA schema_name [, ...]
TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]

INSERT
Create new rows in a table.

INSERT INTO table [ ( column [, ...] ) ]
{ DEFAULT VALUES | VALUES ( { expression | DEFAULT } [, ...] ) | query }

LISTEN
Listen for a notification.
LISTEN name

LOAD
Load or reload a shared library file.
LOAD 'filename'

LOCK
Lock a table.
LOCK [ TABLE ] name [, ...] [ IN lock_mode MODE ] [ NOWAIT ]

Where lock_mode is one of −
ACCESS SHARE | ROW SHARE | ROW EXCLUSIVE | SHARE UPDATE EXCLUSIVE
| SHARE | SHARE ROW EXCLUSIVE | EXCLUSIVE | ACCESS EXCLUSIVE

MOVE
Position a cursor.
MOVE [ direction { FROM | IN } ] cursor_name

NOTIFY
Generate a notification.
NOTIFY name

PREPARE
Prepare a statement for execution.
PREPARE plan_name [ (data_type [, ...] ) ] AS statement

REINDEX
Rebuild indexes.
REINDEX { DATABASE | TABLE | INDEX } name [ FORCE ]

RELEASE SAVEPOINT
Destroy a previously defined savepoint.
RELEASE [ SAVEPOINT ] savepoint_name

RESET
Restore the value of a runtime parameter to the default value.
RESET name
RESET ALL

REVOKE
Remove access privileges.
REVOKE [ GRANT OPTION FOR ]
{ { SELECT | INSERT | UPDATE | DELETE | RULE | REFERENCES | TRIGGER }
[,...] | ALL [ PRIVILEGES ] }
ON [ TABLE ] table_name [, ...]
FROM { username | GROUP group_name | PUBLIC } [, ...]
[ CASCADE | RESTRICT ]
REVOKE [ GRANT OPTION FOR ]
{ { CREATE | TEMPORARY | TEMP } [,...] | ALL [ PRIVILEGES ] }
ON DATABASE db_name [, ...]
FROM { username | GROUP group_name | PUBLIC } [, ...]
[ CASCADE | RESTRICT ]
REVOKE [ GRANT OPTION FOR ]
{ CREATE | ALL [ PRIVILEGES ] }
ON TABLESPACE tablespace_name [, ...]
FROM { username | GROUP group_name | PUBLIC } [, ...]
[ CASCADE | RESTRICT ]
REVOKE [ GRANT OPTION FOR ]
{ EXECUTE | ALL [ PRIVILEGES ] }
ON FUNCTION func_name ([type, ...]) [, ...]
FROM { username | GROUP group_name | PUBLIC } [, ...]
[ CASCADE | RESTRICT ]
REVOKE [ GRANT OPTION FOR ]
{ USAGE | ALL [ PRIVILEGES ] }
ON LANGUAGE lang_name [, ...]
FROM { username | GROUP group_name | PUBLIC } [, ...]
[ CASCADE | RESTRICT ]
REVOKE [ GRANT OPTION FOR ]
{ { CREATE | USAGE } [,...] | ALL [ PRIVILEGES ] }
ON SCHEMA schema_name [, ...]
FROM { username | GROUP group_name | PUBLIC } [, ...]
[ CASCADE | RESTRICT ]

ROLLBACK

Abort the current transaction.
ROLLBACK [ WORK | TRANSACTION ]

ROLLBACK TO SAVEPOINT
Roll back to a savepoint.
ROLLBACK [ WORK | TRANSACTION ] TO [ SAVEPOINT ] savepoint_name

SAVEPOINT
Define a new savepoint within the current transaction.
SAVEPOINT savepoint_name

SELECT
Retrieve rows from a table or view.
SELECT [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]
* | expression [ AS output_name ] [, ...]
[ FROM from_item [, ...] ]
[ WHERE condition ]
[ GROUP BY expression [, ...] ]
[ HAVING condition [, ...] ]
[ { UNION | INTERSECT | EXCEPT } [ ALL ] select ]
[ ORDER BY expression [ ASC | DESC | USING operator ] [, ...] ]
[ LIMIT { count | ALL } ]
[ OFFSET start ]
[ FOR UPDATE [ OF table_name [, ...] ] ]

Where from_item can be one of:
[ ONLY ] table_name [ * ] [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
( select ) [ AS ] alias [ ( column_alias [, ...] ) ]
function_name ( [ argument [, ...] ] )
[ AS ] alias [ ( column_alias [, ...] | column_definition [, ...] ) ]
function_name ( [ argument [, ...] ] ) AS ( column_definition [, ...] )
from_item [ NATURAL ] join_type from_item
[ ON join_condition | USING ( join_column [, ...] ) ]

SELECT INTO
Define a new table from the results of a query.
SELECT [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]
* | expression [ AS output_name ] [, ...]
INTO [ TEMPORARY | TEMP ] [ TABLE ] new_table
[ FROM from_item [, ...] ]
[ WHERE condition ]
[ GROUP BY expression [, ...] ]
[ HAVING condition [, ...] ]
[ { UNION | INTERSECT | EXCEPT } [ ALL ] select ]

[
[
[
[

ORDER BY expression [ ASC | DESC | USING operator ] [, ...] ]
LIMIT { count | ALL } ]
OFFSET start ]
FOR UPDATE [ OF table_name [, ...] ] ]

SET
Change a runtime parameter.
SET [ SESSION | LOCAL ] name { TO | = } { value | 'value' | DEFAULT }
SET [ SESSION | LOCAL ] TIME ZONE { time_zone | LOCAL | DEFAULT }

SET CONSTRAINTS
Set constraint checking modes for the current transaction.
SET CONSTRAINTS { ALL | name [, ...] } { DEFERRED | IMMEDIATE }

SET SESSION AUTHORIZATION
Set the session user identifier and the current user identifier of the current session.
SET [ SESSION | LOCAL ] SESSION AUTHORIZATION username
SET [ SESSION | LOCAL ] SESSION AUTHORIZATION DEFAULT
RESET SESSION AUTHORIZATION

SET TRANSACTION
Set the characteristics of the current transaction.
SET TRANSACTION transaction_mode [, ...]
SET SESSION CHARACTERISTICS AS TRANSACTION transaction_mode [, ...]

Where transaction_mode is one of −
ISOLATION LEVEL { SERIALIZABLE | REPEATABLE READ | READ COMMITTED
| READ UNCOMMITTED }
READ WRITE | READ ONLY

SHOW
Show the value of a runtime parameter.
SHOW name
SHOW ALL

START TRANSACTION
Start a transaction block.
START TRANSACTION [ transaction_mode [, ...] ]

Where transaction_mode is one of −
ISOLATION LEVEL { SERIALIZABLE | REPEATABLE READ | READ COMMITTED
| READ UNCOMMITTED }
READ WRITE | READ ONLY

TRUNCATE
Empty a table.
TRUNCATE [ TABLE ] name

UNLISTEN
Stop listening for a notification.
UNLISTEN { name | * }

UPDATE
Update rows of a table.
UPDATE [ ONLY ] table SET column = { expression | DEFAULT } [, ...]
[ FROM from_list ]
[ WHERE condition ]

VACUUM
Garbage-collect and optionally analyze a database.
VACUUM [ FULL ] [ FREEZE ] [ VERBOSE ] [ table ]
VACUUM [ FULL ] [ FREEZE ] [ VERBOSE ] ANALYZE [ table [ (column [, ...] ) ] ]

PostgreSQL - Data Type
In this chapter, we will discuss about the data types used in PostgreSQL. While creating
table, for each column, you specify a data type, i.e., what kind of data you want to store in
the table fields.
This enables several benefits −
Consistency − Operations against columns of same data type give consistent
results and are usually the fastest.
Validation − Proper use of data types implies format validation of data and
rejection of data outside the scope of data type.
Compactness − As a column can store a single type of value, it is stored in a
compact way.

Performance − Proper use of data types gives the most efficient storage of data.
The values stored can be processed quickly, which enhances the performance.
PostgreSQL supports a wide set of Data Types. Besides, users can create their own custom
data type using CREATE TYPE SQL command. There are different categories of data types
in PostgreSQL. They are discussed below.

Numeric Types
Numeric types consist of two-byte, four-byte, and eight-byte integers, four-byte and eightbyte floating-point numbers, and selectable-precision decimals. The following table lists
the available types.
Name

Storage Size

Description

Range

smallint

2 bytes

small-range
integer

-32768 to +32767

integer

4 bytes

typical choice for
integer

-2147483648 to +2147483647

bigint

8 bytes

large-range
integer

-9223372036854775808 to
9223372036854775807

variable

user-specified
precision,exact

up to 131072 digits before the decimal
point; up to 16383 digits after the decimal
point

numeric

variable

user-specified
precision,exact

up to 131072 digits before the decimal
point; up to 16383 digits after the decimal
point

real

4 bytes

variableprecision,inexact

6 decimal digits precision

double
precision

8 bytes

variableprecision,inexact

15 decimal digits precision

smallserial

2 bytes

small
autoincrementing
integer

1 to 32767

serial

4 bytes

autoincrementing
integer

1 to 2147483647

8 bytes

large
autoincrementing
integer

1 to 9223372036854775807

decimal

bigserial

Monetary Types
The money type stores a currency amount with a fixed fractional precision. Values of the
numeric, int, and bigint data types can be cast to money. Using Floating point numbers is
not recommended to handle money due to the potential for rounding errors.
Name

Storage Size

Description

Range

money

8 bytes

currency
amount

-92233720368547758.08 to
+92233720368547758.07

Character Types
The table given below lists the general-purpose character types available in PostgreSQL.
S. No.

Name & Description

character varying(n), varchar(n)
1

variable-length with limit
character(n), char(n)

2

fixed-length, blank padded
text

3

variable unlimited length

Binary Data Types
The bytea data type allows storage of binary strings as in the table given below.
Name

Storage Size

Description

bytea

1 or 4 bytes plus the actual binary string

variable-length binary string

Date/Time Types
PostgreSQL supports a full set of SQL date and time types, as shown in table below. Dates
are counted according to the Gregorian calendar. Here, all the types have resolution of 1
microsecond / 14 digits except date type, whose resolution is day.

Name

Storage Size

Description

Low Value

High Value

timestamp [(p)]
[without time
zone ]

8 bytes

both date and
time (no time
zone)

4713 BC

294276 AD

timestamp [(p) ]
with time zone

8 bytes

both date and
time, with time
zone

4713 BC

294276 AD

date

4 bytes

date (no time of
day)

4713 BC

5874897 AD

time [ (p)] [
without time zone
]

8 bytes

time of day (no
date)

00:00:00

24:00:00

time [ (p)] with
time zone

12 bytes

times of day only,
with time zone

00:00:00+1459

24:00:00-1459

interval [fields ]
[(p) ]

12 bytes

time interval

-178000000
years

178000000
years

Boolean Type
PostgreSQL provides the standard SQL type Boolean. The Boolean data type can have the
states true, false, and a third state, unknown, which is represented by the SQL null value.
Name

Storage Size

Description

boolean

1 byte

state of true or false

Enumerated Type
Enumerated (enum) types are data types that comprise a static, ordered set of values.
They are equivalent to the enum types supported in a number of programming languages.
Unlike other types, Enumerated Types need to be created using CREATE TYPE command.
This type is used to store a static, ordered set of values. For example compass directions,
i.e., NORTH, SOUTH, EAST, and WEST or days of the week as shown below −
CREATE TYPE week AS ENUM ('Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun');

Enumerated, once created, can be used like any other types.

Geometric Type

Geometric data types represent two-dimensional spatial objects. The most fundamental
type, the point, forms the basis for all of the other types.
Name

Storage Size

Representation

Description

point

16 bytes

Point on a plane

(x,y)

line

32 bytes

Infinite line (not fully
implemented)

((x1,y1),(x2,y2))

lseg

32 bytes

Finite line segment

((x1,y1),(x2,y2))

box

32 bytes

Rectangular box

((x1,y1),(x2,y2))

path

16+16n bytes

Closed path (similar to
polygon)

((x1,y1),...)

path

16+16n bytes

Open path

[(x1,y1),...]

polygon

40+16n

Polygon (similar to closed path)

((x1,y1),...)

circle

24 bytes

Circle

<(x,y),r> (center point and
radius)

Network Address Type
PostgreSQL offers data types to store IPv4, IPv6, and MAC addresses. It is better to use
these types instead of plain text types to store network addresses, because these types
offer input error checking and specialized operators and functions.
Name

Storage Size

Description

cidr

7 or 19 bytes

IPv4 and IPv6 networks

inet

7 or 19 bytes

IPv4 and IPv6 hosts and networks

macaddr

6 bytes

MAC addresses

Bit String Type
Bit String Types are used to store bit masks. They are either 0 or 1. There are two SQL bit
types: bit(n) and bit varying(n), where n is a positive integer.

Text Search Type

This type supports full text search, which is the activity of searching through a collection of
natural-language documents to locate those that best match a query. There are two Data
Types for this −
S. No.

Name & Description

tsvector
1

This is a sorted list of distinct words that have been normalized to merge
different variants of the same word, called as "lexemes".
tsquery

2

This stores lexemes that are to be searched for, and combines them honoring
the Boolean operators & (AND), | (OR), and ! (NOT). Parentheses can be used
to enforce grouping of the operators.

UUID Type
A UUID (Universally Unique Identifiers) is written as a sequence of lower-case hexadecimal
digits, in several groups separated by hyphens, specifically a group of eight digits, followed
by three groups of four digits, followed by a group of 12 digits, for a total of 32 digits
representing the 128 bits.
An example of a UUID is − 550e8400-e29b-41d4-a716-446655440000

XML Type
The XML data type can be used to store XML data. For storing XML data, first you have to
create XML values using the function xmlparse as follows −
XMLPARSE (DOCUMENT '


...
')
XMLPARSE (CONTENT 'xyzbarfoo')

JSON Type
The json data type can be used to store JSON (JavaScript Object Notation) data. Such data
can also be stored as text, but the json data type has the advantage of checking that each
stored value is a valid JSON value. There are also related support functions available,
which can be used directly to handle JSON data type as follows.

Example

Example Result

array_to_json('{{1,5},{99,100}}'::int[])

[[1,5],[99,100]]

row_to_json(row(1,'foo'))

{"f1":1,"f2":"foo"}

Array Type
PostgreSQL gives the opportunity to define a column of a table as a variable length
multidimensional array. Arrays of any built-in or user-defined base type, enum type, or
composite type can be created.

Declaration of Arrays
Array type can be declared as
CREATE TABLE monthly_savings (
name text,
saving_per_quarter integer[],
scheme text[][]
);

or by using the keyword "ARRAY" as
CREATE TABLE monthly_savings (
name text,
saving_per_quarter integer ARRAY[4],
scheme text[][]
);

Inserting values
Array values can be inserted as a literal constant, enclosing the element values within curly
braces and separating them by commas. An example is shown below −
INSERT INTO monthly_savings
VALUES (‘Manisha’,
‘{20000, 14600, 23500, 13250}’,
‘{{“FD”, “MF”}, {“FD”, “Property”}}’);

Accessing Arrays
An example for accessing Arrays is shown below. The command given below will select the
persons whose savings are more in second quarter than fourth quarter.
SELECT name FROM monhly_savings WHERE saving_per_quarter[2] > saving_per_quarter[4];

Modifying Arrays
An example of modifying arrays is as shown below.

UPDATE monthly_savings SET saving_per_quarter = '{25000,25000,27000,27000}'
WHERE name = 'Manisha';

or using the ARRAY expression syntax −
UPDATE monthly_savings SET saving_per_quarter = ARRAY[25000,25000,27000,27000]
WHERE name = 'Manisha';

Searching Arrays
An example of searching arrays is as shown below.
SELECT * FROM monthly_savings WHERE saving_per_quarter[1] = 10000 OR
saving_per_quarter[2] = 10000 OR
saving_per_quarter[3] = 10000 OR
saving_per_quarter[4] = 10000;

If the size of array is known, the search method given above can be used. Else, the
following example shows how to search when the size is not known.
SELECT * FROM monthly_savings WHERE 10000 = ANY (saving_per_quarter);

Composite Types
This type represents a list of field names and their data types, i.e., structure of a row or
record of a table.

Declaration of Composite Types
The following example shows how to declare a composite type
CREATE TYPE inventory_item AS (
name text,
supplier_id integer,
price numeric
);

This data type can be used in the create tables as below −
CREATE TABLE on_hand (
item inventory_item,
count integer
);

Composite Value Input
Composite values can be inserted as a literal constant, enclosing the field values within
parentheses and separating them by commas. An example is shown below −
INSERT INTO on_hand VALUES (ROW('fuzzy dice', 42, 1.99), 1000);

This is valid for the inventory_item defined above. The ROW keyword is actually optional
as long as you have more than one field in the expression.

Accessing Composite Types
To access a field of a composite column, use a dot followed by the field name, much like
selecting a field from a table name. For example, to select some subfields from our
on_hand example table, the query would be as shown below −
SELECT (item).name FROM on_hand WHERE (item).price > 9.99;

You can even use the table name as well (for instance in a multitable query), like this −
SELECT (on_hand.item).name FROM on_hand WHERE (on_hand.item).price > 9.99;

Range Types
Range types represent data types that uses a range of data. Range type can be discrete
ranges (e.g., all integer values 1 to 10) or continuous ranges (e.g., any point in time
between 10:00am and 11:00am).
The built-in range types available include the following ranges −
int4range − Range of integer
int8range − Range of bigint
numrange − Range of numeric
tsrange − Range of timestamp without time zone
tstzrange − Range of timestamp with time zone
daterange − Range of date
Custom range types can be created to make new types of ranges available, such as IP
address ranges using the inet type as a base, or float ranges using the float data type as a
base.
Range types support inclusive and exclusive range boundaries using the [ ] and ( )
characters, respectively. For example '[4,9)' represents all the integers starting from and
including 4 up to but not including 9.

Object Identifier Types
Object identifiers (OIDs) are used internally by PostgreSQL as primary keys for various
system tables. If WITH OIDS is specified or default_with_oids configuration variable is
enabled, only then, in such cases OIDs are added to user-created tables. The following

table lists several alias types. The OID alias types have no operations of their own except
for specialized input and output routines.
Name

References

Description

Value Example

oid

any

numeric object identifier

564182

regproc

pg_proc

function name

sum

regprocedure

pg_proc

function with argument
types

sum(int4)

regoper

pg_operator

operator name

+

regoperator

pg_operator

operator with argument
types

*(integer,integer) or (NONE,integer)

regclass

pg_class

relation name

pg_type

regtype

pg_type

data type name

integer

regconfig

pg_ts_config

text search configuration

English

regdictionary

pg_ts_dict

text search dictionary

simple

Pseudo Types
The PostgreSQL type system contains a number of special-purpose entries that are
collectively called pseudo-types. A pseudo-type cannot be used as a column data type, but
it can be used to declare a function's argument or result type.
The table given below lists the existing pseudo-types.
S. No.

Name & Description

any
1

Indicates that a function accepts any input data type.
anyelement

2

Indicates that a function accepts any data type.
anyarray

3

4

Indicates that a function accepts any array data type.
anynonarray

Indicates that a function accepts any non-array data type.
anyenum
5

Indicates that a function accepts any enum data type.
anyrange

6

Indicates that a function accepts any range data type.
cstring

7

Indicates that a function accepts or returns a null-terminated C string.
internal

8

Indicates that a function accepts or returns a server-internal data type.
language_handler

9

A procedural language call handler is declared to return language_handler.
fdw_handler

10

A foreign-data wrapper handler is declared to return fdw_handler.
record

11

Identifies a function returning an unspecified row type.
trigger

12

A trigger function is declared to return trigger.
void

13

Indicates that a function returns no value.

PostgreSQL - CREATE Database
This chapter discusses about how to create a new database in your PostgreSQL.
PostgreSQL provides two ways of creating a new database −
Using CREATE DATABASE, an SQL command.
Using createdb a command-line executable.

Using CREATE DATABASE
This command will create a database from PostgreSQL shell prompt, but you should have
appropriate privilege to create a database. By default, the new database will be created by
cloning the standard system database template1.

Syntax
The basic syntax of CREATE DATABASE statement is as follows −
CREATE DATABASE dbname;

where dbname is the name of a database to create.

Example
The following is a simple example, which will create testdb in your PostgreSQL schema
postgres=# CREATE DATABASE testdb;
postgres-#

Using createdb Command
PostgreSQL command line executable createdb is a wrapper around the SQL command
CREATE DATABASE. The only difference between this command and SQL command
CREATE DATABASE is that the former can be directly run from the command line and it
allows a comment to be added into the database, all in one command.

Syntax
The syntax for createdb is as shown below −
createdb [option...] [dbname [description]]

Parameters
The table given below lists the parameters with their descriptions.
S. No.

Parameter & Description

dbname
1

The name of a database to create.
description

2

3

Specifies a comment to be associated with the newly created database.
options

command-line arguments, which createdb accepts.

Options
The following table lists the command line arguments createdb accepts −
S. No.

Option & Description

-D tablespace
1

Specifies the default tablespace for the database.
-e

2

Echo the commands that createdb generates and sends to the server.
-E encoding

3

Specifies the character encoding scheme to be used in this database.
-l locale

4

Specifies the locale to be used in this database.
-T template

5

Specifies the template database from which to build this database.
--help

6

Show help about createdb command line arguments, and exit.
-h host

7

Specifies the host name of the machine on which the server is running.
-p port

8

Specifies the TCP port or the local Unix domain socket file extension on which
the server is listening for connections.
-U username

9

10

User name to connect as.
-w

Never issue a password prompt.
-W
11

Force createdb to prompt for a password before connecting to a database.

Open the command prompt and go to the directory where PostgreSQL is installed. Go to
the bin directory and execute the following command to create a database.
createdb -h localhost -p 5432 -U postgres testdb
password ******

The above given command will prompt you for password of the PostgreSQL admin user,
which is postgres, by default. Hence, provide a password and proceed to create your new
database
Once a database is created using either of the above-mentioned methods, you can check it
in the list of databases using \l, i.e., backslash el command as follows −
postgres-# \l
List of databases
Name
| Owner
| Encoding | Collate | Ctype |
Access privileges
-----------+----------+----------+---------+-------+----------------------postgres | postgres | UTF8
| C
| C
|
template0 | postgres | UTF8
| C
| C
| =c/postgres
+
|
|
|
|
| postgres=CTc/postgres
template1 | postgres | UTF8
| C
| C
| =c/postgres
+
|
|
|
|
| postgres=CTc/postgres
testdb
| postgres | UTF8
| C
| C
|
(4 rows)
postgres-#

PostgreSQL - SELECT Database
This chapter explains various methods of accessing the database. Assume that we have
already created a database in our previous chapter. You can select the database using
either of the following methods −
Database SQL Prompt
OS Command Prompt

Database SQL Prompt
Assume you have already launched your PostgreSQL client and you have landed at the
following SQL prompt −
postgres=#

You can check the available database list using \l, i.e., backslash el command as follows −
postgres-# \l
List of databases
Name
| Owner
| Encoding | Collate | Ctype |
Access privileges
-----------+----------+----------+---------+-------+----------------------postgres | postgres | UTF8
| C
| C
|
template0 | postgres | UTF8
| C
| C
| =c/postgres
+
|
|
|
|
| postgres=CTc/postgres
template1 | postgres | UTF8
| C
| C
| =c/postgres
+
|
|
|
|
| postgres=CTc/postgres
testdb
| postgres | UTF8
| C
| C
|
(4 rows)
postgres-#

Now, type the following command to connect/select a desired database; here, we will
connect to the testdb database.
postgres=# \c testdb;
psql (9.2.4)
Type "help" for help.
You are now connected to database "testdb" as user "postgres".
testdb=#

OS Command Prompt
You can select your database from the command prompt itself at the time when you login
to your database. Following is a simple example −
psql -h localhost -p 5432 -U postgress testdb
Password for user postgress: ****
psql (9.2.4)
Type "help" for help.
You are now connected to database "testdb" as user "postgres".
testdb=#

You are now logged into PostgreSQL testdb and ready to execute your commands inside
testdb. To exit from the database, you can use the command \q.

PostgreSQL - DROP Database
In this chapter, we will discuss how to delete the database in PostgreSQL. There are two
options to delete a database −
Using DROP DATABASE, an SQL command.
Using dropdb a command-line executable.
Be careful before using this operation because deleting an existing database would
result in loss of complete information stored in the database.

Using DROP DATABASE
This command drops a database. It removes the catalog entries for the database and
deletes the directory containing the data. It can only be executed by the database owner.
This command cannot be executed while you or anyone else is connected to the target
database (connect to postgres or any other database to issue this command).

Syntax
The syntax for DROP DATABASE is given below −
DROP DATABASE [ IF EXISTS ] name

Parameters
The table lists the parameters with their descriptions.
S. No.

Parameter & Description

IF EXISTS
1

Do not throw an error if the database does not exist. A notice is issued in this
case.
name

2

The name of the database to remove.

We cannot drop a database that has any open connections, including our own
connection from psql or pgAdmin III. We must switch to another database or
template1 if we want to delete the database we are currently connected to. Thus, it
might be more convenient to use the program dropdb instead, which is a wrapper
around this command.

Example
The following is a simple example, which will delete testdb from your PostgreSQL schema
−
postgres=# DROP DATABASE testdb;
postgres-#

Using dropdb Command
PostgresSQL command line executable dropdb is a command-line wrapper around the SQL
command DROP DATABASE. There is no effective difference between dropping databases
via this utility and via other methods for accessing the server. dropdb destroys an existing

PostgreSQL database. The user, who executes this command must be a database super
user or the owner of the database.

Syntax
The syntax for dropdb is as shown below −
dropdb

[option...] dbname

Parameters
The following table lists the parameters with their descriptions
S. No.

Parameter & Description

dbname
1

The name of a database to be deleted.
option

2

command-line arguments, which dropdb accepts.

Options
The following table lists the command-line arguments dropdb accepts −
S. No.

Option & Description

-e
1

Shows the commands being sent to the server.
-i

2

Issues a verification prompt before doing anything destructive.
-V

3

Print the dropdb version and exit.
--if-exists

4

Do not throw an error if the database does not exist. A notice is issued in this
case.

5

--help
Show help about dropdb command-line arguments, and exit.

-h host
6

Specifies the host name of the machine on which the server is running.
-p port

7

Specifies the TCP port or the local UNIX domain socket file extension on which
the server is listening for connections.
-U username

8

User name to connect as.
-w

9

Never issue a password prompt.
-W

10

Force dropdb to prompt for a password before connecting to a database.
--maintenance-db=dbname

11

Specifies the name of the database to connect to in order to drop the target
database.

Example
The following example demonstrates deleting a database from OS command prompt −
dropdb -h localhost -p 5432 -U postgress testdb
Password for user postgress: ****

The above command drops the database testdb. Here, I have used the postgres (found
under the pg_roles of template1) username to drop the database.

PostgreSQL - CREATE Table
The PostgreSQL CREATE TABLE statement is used to create a new table in any of the given
database.

Syntax
Basic syntax of CREATE TABLE statement is as follows −

CREATE TABLE table_name(
column1 datatype,
column2 datatype,
column3 datatype,
.....
columnN datatype,
PRIMARY KEY( one or more columns )
);

CREATE TABLE is a keyword, telling the database system to create a new table. The unique
name or identifier for the table follows the CREATE TABLE statement. Initially, the empty
table in the current database is owned by the user issuing the command.
Then, in brackets, comes the list, defining each column in the table and what sort of data
type it is. The syntax will become clear with an example given below.

Examples
The following is an example, which creates a COMPANY table with ID as primary key and
NOT NULL are the constraints showing that these fields cannot be NULL while creating
records in this table −
CREATE TABLE COMPANY(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
);

Let us create one more table, which we will use in our exercises in subsequent chapters −
CREATE TABLE DEPARTMENT(
ID INT PRIMARY KEY
NOT NULL,
DEPT
CHAR(50) NOT NULL,
EMP_ID
INT
NOT NULL
);

You can verify if your table has been created successfully using \d command, which will be
used to list down all the tables in an attached database.
testdb-# \d

The above given PostgreSQL statement will produce the following result −
List of relations
Schema |

Name

| Type

|

Owner

--------+------------+-------+---------public | company

| table | postgres

public | department | table | postgres
(2 rows)

Use \d tablename to describe each table as shown below −
testdb-# \d company

The above given PostgreSQL statement will produce the following result −
Table "public.company"
Column

|

Type

| Modifiers

-----------+---------------+----------id

| integer

| not null

name

| text

| not null

age

| integer

| not null

address

| character(50) |

salary

| real

|

join_date | date

|

Indexes:
"company_pkey" PRIMARY KEY, btree (id)

PostgreSQL - DROP Table
The PostgreSQL DROP TABLE statement is used to remove a table definition and all
associated data, indexes, rules, triggers, and constraints for that table.
You have to be careful while using this command because once a table is deleted
then all the information available in the table would also be lost forever.

Syntax
Basic syntax of DROP TABLE statement is as follows −
DROP TABLE table_name;

Example
We had created the tables DEPARTMENT and COMPANY in the previous chapter. First,
verify these tables (use \d to list the tables) −
testdb-# \d

This would produce the following result −
List of relations
Schema |

Name

| Type

|

Owner

--------+------------+-------+---------public | company

| table | postgres

public | department | table | postgres
(2 rows)

This means DEPARTMENT and COMPANY tables are present. So let us drop them as follows
−
testdb=# drop table department, company;

This would produce the following result −
DROP TABLE
testdb=# \d
relations found.
testdb=#

The message returned DROP TABLE indicates that drop command is executed successfully.

PostgreSQL - Schema
A schema is a named collection of tables. A schema can also contain views, indexes,
sequences, data types, operators, and functions. Schemas are analogous to directories at
the operating system level, except that schemas cannot be nested. PostgreSQL statement
CREATE SCHEMA creates a schema.

Syntax
The basic syntax of CREATE SCHEMA is as follows −
CREATE SCHEMA name;

Where name is the name of the schema.

Syntax to Create Table in Schema
The basic syntax to create table in schema is as follows −
CREATE TABLE myschema.mytable (
...
);

Example
Let us see an example for creating a schema. Connect to the database testdb and create a
schema myschema as follows −
testdb=# create schema myschema;
CREATE SCHEMA

The message "CREATE SCHEMA" signifies that the schema is created successfully.
Now, let us create a table in the above schema as follows −
testdb=# create table myschema.company(
ID
INT
NOT NULL,
NAME VARCHAR (20)
NOT NULL,
AGE INT
NOT NULL,
ADDRESS CHAR (25),
SALARY
DECIMAL (18, 2),
PRIMARY KEY (ID)
);

This will create an empty table. You can verify the table created with the command given
below −
testdb=# select * from myschema.company;

This would produce the following result −
id | name | age | address | salary
----+------+-----+---------+-------(0 rows)

Syntax to Drop Schema
To drop a schema if it is empty (all objects in it have been dropped), use the command −
DROP SCHEMA myschema;

To drop a schema including all contained objects, use the command −
DROP SCHEMA myschema CASCADE;

Advantages of using a Schema
It allows many users to use one database without interfering with each other.
It organizes database objects into logical groups to make them more manageable.
Third-party applications can be put into separate schemas so they do not collide
with the names of other objects.

PostgreSQL - INSERT Query
The PostgreSQL INSERT INTO statement allows one to insert new rows into a table. One
can insert a single row at a time or several rows as a result of a query.

Syntax

Basic syntax of INSERT INTO statement is as follows −
INSERT INTO TABLE_NAME (column1, column2, column3,...columnN)
VALUES (value1, value2, value3,...valueN);

Here, column1, column2,...columnN are the names of the columns in the table into
which you want to insert data.
The target column names can be listed in any order. The values supplied by the
VALUES clause or query are associated with the explicit or implicit column list leftto-right.
You may not need to specify the column(s) name in the SQL query if you are adding values
for all the columns of the table. However, make sure the order of the values is in the same
order as the columns in the table. The SQL INSERT INTO syntax would be as follows −
INSERT INTO TABLE_NAME VALUES (value1,value2,value3,...valueN);

Output
The following table summarizes the output messages and their meaning −
S. No.

Output Message & Description

INSERT oid 1
1

Message returned if only one row was inserted. oid is the numeric OID of the
inserted row.
INSERT 0 #

2

Message returned if more than one rows were inserted. # is the number of
rows inserted.

Examples
Let us create COMPANY table in testdb as follows −
CREATE TABLE COMPANY(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL,
JOIN_DATE
DATE
);

The following example inserts a row into the COMPANY table −
INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY,JOIN_DATE) VALUES (1, 'Paul', 32, 'California', 2

The following example is to insert a row; here salary column is omitted and therefore it will
have the default value −
INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,JOIN_DATE) VALUES (2, 'Allen', 25, 'Texas', '2007-12-13'

The following example uses the DEFAULT clause for the JOIN_DATE column rather than
specifying a value −
INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY,JOIN_DATE) VALUES (3, 'Teddy', 23, 'Norway', 2000

The following example inserts multiple rows using the multirow VALUES syntax −
INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY,JOIN_DATE) VALUES (4, 'Mark', 25, 'Rich-Mond ', 6

All the above statements would create the following records in COMPANY table. The next
chapter will teach you how to display all these records from a table.

ID

NAME

AGE

ADDRESS

SALARY

JOIN_DATE

----

----------

-----

----------

-------

--------

1

Paul

32

California

20000.0

2001-07-13

2

Allen

25

Texas

3

Teddy

23

Norway

20000.0

4

Mark

25

Rich-Mond

65000.0

2007-12-13

5

David

27

Texas

85000.0

2007-12-13

2007-12-13

PostgreSQL - SELECT Query
PostgreSQL SELECT statement is used to fetch the data from a database table, which
returns data in the form of result table. These result tables are called result-sets.

Syntax
The basic syntax of SELECT statement is as follows −
SELECT column1, column2, columnN FROM table_name;

Here, column1, column2...are the fields of a table, whose values you want to fetch. If you
want to fetch all the fields available in the field then you can use the following syntax −
SELECT * FROM table_name;

Example
Consider the table COMPANY

having records as follows −

id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following is an example, which would fetch ID, Name and Salary fields of the
customers available in CUSTOMERS table −
testdb=# SELECT ID, NAME, SALARY FROM COMPANY ;

This would produce the following result −
id | name

| salary

----+-------+-------1 | Paul

|

20000

2 | Allen |

15000

3 | Teddy |

20000

4 | Mark

|

65000

5 | David |

85000

6 | Kim

|

45000

7 | James |

10000

(7 rows)

If you want to fetch all the fields of CUSTOMERS table, then use the following query −
testdb=# SELECT * FROM COMPANY;

This would produce the following result −
id | name

| age | address

| salary

----+-------+-----+-----------+-------1 | Paul

|

32 | California|

20000

2 | Allen |

25 | Texas

|

15000

3 | Teddy |

23 | Norway

|

20000

4 | Mark

|

25 | Rich-Mond |

65000

5 | David |

27 | Texas

|

85000

6 | Kim

22 | South-Hall|

45000

24 | Houston

10000

|

7 | James |

|

(7 rows)

PostgreSQL - Operators
What is an Operator in PostgreSQL?
An operator is a reserved word or a character used primarily in a PostgreSQL statement's
WHERE clause to perform operation(s), such as comparisons and arithmetic operations.
Operators are used to specify conditions in a PostgreSQL statement and to serve as
conjunctions for multiple conditions in a statement.
Arithmetic operators
Comparison operators
Logical operators
Bitwise operators

PostgreSQL Arithmetic Operators
Assume variable a holds 2 and variable b holds 3, then −
Example
Operator

Description

Example

+

Addition - Adds values on either side of
the operator

a + b will give 5

-

Subtraction - Subtracts right hand
operand from left hand operand

a - b will give -1

*

Multiplication - Multiplies values on either
side of the operator

a * b will give 6

/

Division - Divides left hand operand by
right hand operand

b / a will give 1

%

Modulus - Divides left hand operand by
right hand operand and returns
remainder

b % a will give 1

^

Exponentiation - This gives the exponent
value of the right hand operand

a ^ b will give 8

|/

square root

|/ 25.0 will give 5

||/

Cube root

||/ 27.0 will give 3

!

factorial

5 ! will give 120

!!

factorial (prefix operator)

!! 5 will give 120

PostgreSQL Comparison Operators
Assume variable a holds 10 and variable b holds 20, then −
Show Examples
Operator

Description

Example

=

Checks if the values of two operands are equal or
not, if yes then condition becomes true.

!=

Checks if the values of two operands are equal or
not, if values are not equal then condition becomes
true.

(a != b) is true.

<>

Checks if the values of two operands are equal or
not, if values are not equal then condition becomes
true.

(a <> b) is true.

(a = b) is not true.

>

Checks if the value of left operand is greater than
the value of right operand, if yes then condition
becomes true.

(a > b) is not true.

<

Checks if the value of left operand is less than the
value of right operand, if yes then condition
becomes true.

(a < b) is true.

>=

Checks if the value of left operand is greater than
or equal to the value of right operand, if yes then
condition becomes true.

(a >= b) is not true.

<=

Checks if the value of left operand is less than or
equal to the value of right operand, if yes then
condition becomes true.

(a <= b) is true.

PostgreSQL Logical Operators
Here is a list of all the logical operators available in PostgresSQL.
Show Examples

S. No.

Operator & Description

AND
The AND operator allows the existence of multiple conditions in a PostgresSQL

1

statement's WHERE clause.
NOT
The NOT operator reverses the meaning of the logical operator with which it is

2

used. Eg. NOT EXISTS, NOT BETWEEN, NOT IN etc. This is negate operator.
OR
The OR operator is used to combine multiple conditions in a PostgresSQL

3

statement's WHERE clause.

PostgreSQL Bit String Operators
Bitwise operator works on bits and performs bit-by-bit operation. The truth table for & and
| is as follows −
p

q

p&q

p|q

0

0

0

0

0

1

0

1

1

1

1

1

1

0

0

1

Assume if A = 60; and B = 13; now in binary format they will be as follows −
A = 0011 1100
B = 0000 1101
----------------A&B = 0000 1100
A|B = 0011 1101
~A = 1100 0011
Show Examples
The Bitwise operators supported by PostgreSQL are listed in the following table −

Operator

Description

Example

&

Binary AND Operator copies a bit to the
result if it exists in both operands.

(A & B) will give 12 which is 0000 1100

|

Binary OR Operator copies a bit if it
exists in either operand.

(A | B) will give 61 which is 0011 1101

~

Binary Ones Complement Operator is
unary and has the effect of 'flipping' bits.

(~A ) will give -61 which is 1100 0011
in 2's complement form due to a
signed binary number.

<<

Binary Left Shift Operator. The left
operands value is moved left by the
number of bits specified by the right
operand.

A << 2 will give 240 which is 1111
0000

>>

Binary Right Shift Operator. The left
operands value is moved right by the
number of bits specified by the right
operand.

A >> 2 will give 15 which is 0000 1111

#

bitwise XOR.

A # B will give 49 which is 0100 1001

PostgreSQL - Expressions
An expression is a combination of one or more values, operators, and PostgresSQL
functions that evaluate to a value.
PostgreSQL EXPRESSIONS are like formulas and they are written in query language. You
can also use to query the database for specific set of data.

Syntax
Consider the basic syntax of the SELECT statement as follows −
SELECT column1, column2, columnN
FROM table_name
WHERE [CONDITION | EXPRESSION];

There are different types of PostgreSQL expressions, which are mentioned below −

PostgreSQL - Boolean Expressions
PostgreSQL Boolean Expressions fetch the data on the basis of matching single value.
Following is the syntax −
SELECT column1, column2, columnN
FROM table_name

WHERE SINGLE VALUE MATCHTING EXPRESSION;

Consider the table COMPANY

having records as follows −

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

Here is the simple example showing usage of PostgreSQL Boolean Expressions −
testdb=# SELECT * FROM COMPANY WHERE SALARY = 10000;

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+----------+-------7 | James |

24 | Houston

|

10000

(1 row)

PostgreSQL - Numeric Expression
These expressions are used to perform any mathematical operation in any query. Following
is the syntax −
SELECT numerical_expression as OPERATION_NAME
[FROM table_name WHERE CONDITION] ;

Here numerical_expression is used for mathematical expression or any formula. Following
is a simple example showing usage of SQL Numeric Expressions −
testdb=# SELECT (15 + 6) AS ADDITION ;

The above given PostgreSQL statement will produce the following result −
addition
---------21
(1 row)

There are several built-in functions like avg(), sum(), count() to perform what is known as
aggregate data calculations against a table or a specific table column.
testdb=# SELECT COUNT(*) AS "RECORDS" FROM COMPANY;

The above given PostgreSQL statement will produce the following result −
RECORDS
--------7
(1 row)

PostgreSQL - Date Expressions
Date Expressions return the current system date and time values and these expressions
are used in various data manipulations.
testdb=#

SELECT CURRENT_TIMESTAMP;

The above given PostgreSQL statement will produce the following result −
now
------------------------------2013-05-06 14:38:28.078+05:30
(1 row)

PostgreSQL - WHERE Clause
The PostgreSQL WHERE clause is used to specify a condition while fetching the data from
single table or joining with multiple tables.
If the given condition is satisfied, only then it returns specific value from the table. You can
filter out rows that you do not want included in the result-set by using the WHERE clause.
The WHERE clause not only is used in SELECT statement, but it is also used in UPDATE,
DELETE statement, etc., which we would examine in subsequent chapters.

Syntax
The basic syntax of SELECT statement with WHERE clause is as follows −
SELECT column1, column2, columnN
FROM table_name
WHERE [search_condition]

You can specify a search_condition using comparison or logical operators.
LIKE, NOT, etc. The following examples would make this concept clear.

Example
Consider the table COMPANY

having records as follows −

like >, <, =,

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

Here are simple examples showing usage of PostgreSQL Logical Operators. Following
SELECT statement will list down all the records where AGE is greater than or equal to 25
AND salary is greater than or equal to 65000.00 −
testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 AND SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −
id | name

| age |

address

| salary

----+-------+-----+------------+-------4 | Mark

|

5 | David |

25 | Rich-Mond

|

65000

27 | Texas

|

85000

(2 rows)

The following SELECT statement lists down all the records where AGE is greater than or
equal to 25 OR salary is greater than or equal to 65000.00 −
testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 OR SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+-------------+-------1 | Paul

|

32 | California

|

20000

2 | Allen |

25 | Texas

|

15000

4 | Mark

25 | Rich-Mond

|

65000

27 | Texas

|

85000

|

5 | David |
(4 rows)

The following SELECT statement lists down all the records where AGE is not NULL which
means all the records, because none of the record has AGE equal to NULL −
testdb=#

SELECT * FROM COMPANY WHERE AGE IS NOT NULL;

The above given PostgreSQL statement will produce the following result −

id | name

| age | address

| salary

----+-------+-----+------------+-------1 | Paul

|

32 | California |

20000

2 | Allen |

25 | Texas

|

15000

3 | Teddy |

23 | Norway

|

20000

4 | Mark

25 | Rich-Mond

|

65000

5 | David |

27 | Texas

|

85000

6 | Kim

22 | South-Hall |

45000

24 | Houston

10000

|
|

7 | James |

|

(7 rows)

The following SELECT statement lists down all the records where NAME starts with 'Pa',
does not matter what comes after 'Pa'.
testdb=# SELECT * FROM COMPANY WHERE NAME LIKE 'Pa%';

The above given PostgreSQL statement will produce the following result −
id | name | age |address

| salary

----+------+-----+-----------+-------1 | Paul |

32 | California|

20000

The following SELECT statement lists down all the records where AGE value is either 25 or
27 −
testdb=# SELECT * FROM COMPANY WHERE AGE IN ( 25, 27 );

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+------------+-------2 | Allen |

25 | Texas

|

15000

4 | Mark

25 | Rich-Mond

|

65000

27 | Texas

|

85000

|

5 | David |
(3 rows)

The following SELECT statement lists down all the records where AGE value is neither 25
nor 27 −
testdb=# SELECT * FROM COMPANY WHERE AGE NOT IN ( 25, 27 );

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+------------+-------1 | Paul

|

32 | California |

20000

3 | Teddy |

23 | Norway

|

20000

6 | Kim

22 | South-Hall |

45000

|

7 | James |

24 | Houston

|

10000

(4 rows)

The following SELECT statement lists down all the records where AGE value is in BETWEEN
25 AND 27 −
testdb=# SELECT * FROM COMPANY WHERE AGE BETWEEN 25 AND 27;

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+------------+-------2 | Allen |

25 | Texas

|

15000

4 | Mark

25 | Rich-Mond

|

65000

27 | Texas

|

85000

|

5 | David |
(3 rows)

The following SELECT statement makes use of SQL subquery where subquery finds all the
records with AGE field having SALARY > 65000 and later WHERE clause is being used
along with EXISTS operator to list down all the records where AGE from the outside query
exists in the result returned by sub-query −
testdb=# SELECT AGE FROM COMPANY
WHERE EXISTS (SELECT AGE FROM COMPANY WHERE SALARY > 65000);

The above given PostgreSQL statement will produce the following result −
age
----32
25
23
25
27
22
24
(7 rows)

The following SELECT statement makes use of SQL subquery where subquery finds all the
records with AGE field having SALARY > 65000 and later WHERE clause is being used
along with > operator to list down all the records where AGE from outside query is greater
than the age in the result returned by sub-query −
testdb=# SELECT * FROM COMPANY
WHERE AGE > (SELECT AGE FROM COMPANY WHERE SALARY > 65000);

The above given PostgreSQL statement will produce the following result −

id | name | age | address

| salary

----+------+-----+------------+-------1 | Paul |

32 | California |

20000

AND and OR Conjunctive Operators
The PostgreSQL AND and OR operators are used to combine multiple conditions to narrow
down selected data in a PostgreSQL statement. These two operators are called conjunctive
operators.
These operators provide a means to make multiple comparisons with different operators in
the same PostgreSQL statement.

The AND Operator
The AND operator allows the existence of multiple conditions in a PostgreSQL statement's
WHERE clause. While using AND operator, complete condition will be assumed true when
all the conditions are true. For example [condition1] AND [condition2] will be true only
when both condition1 and condition2 are true.

Syntax
The basic syntax of AND operator with WHERE clause is as follows −
SELECT column1, column2, columnN
FROM table_name
WHERE [condition1] AND [condition2]...AND [conditionN];

You can combine N number of conditions using AND operator. For an action to be taken by
the PostgreSQL statement, whether it be a transaction or query, all conditions separated
by the AND must be TRUE.

Example
Consider the table COMPANY

having records as follows −

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following SELECT statement lists down all the records where AGE is greater than or
equal to 25 AND salary is greater than or equal to 65000.00 −

testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 AND SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+------------+-------4 | Mark

|

|

65000

27 | Texas

|

85000

5 | David |

25 | Rich-Mond

(2 rows)

The OR Operator
The OR operator is also used to combine multiple conditions in a PostgreSQL statement's
WHERE clause. While using OR operator, complete condition will be assumed true when at
least any of the conditions is true. For example [condition1] OR [condition2] will be true if
either condition1 or condition2 is true.

Syntax
The basic syntax of OR operator with WHERE clause is as follows −
SELECT column1, column2, columnN
FROM table_name
WHERE [condition1] OR [condition2]...OR [conditionN]

You can combine N number of conditions using OR operator. For an action to be taken by
the PostgreSQL statement, whether it be a transaction or query, only any ONE of the
conditions separated by the OR must be TRUE.

Example
Consider the COMPANY

table, having the following records −

# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following SELECT statement lists down all the records where AGE is greater than or
equal to 25 OR salary is greater than or equal to 65000.00 −
testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 OR SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −

id | name

| age | address

| salary

----+-------+-----+------------+-------1 | Paul

|

32 | California |

20000

2 | Allen |

25 | Texas

|

15000

4 | Mark

25 | Rich-Mond

|

65000

27 | Texas

|

85000

|

5 | David |
(4 rows)

PostgreSQL - UPDATE Query
The PostgreSQL UPDATE Query is used to modify the existing records in a table. You can
use WHERE clause with UPDATE query to update the selected rows. Otherwise, all the rows
would be updated.

Syntax
The basic syntax of UPDATE query with WHERE clause is as follows −
UPDATE table_name
SET column1 = value1, column2 = value2...., columnN = valueN
WHERE [condition];

You can combine N number of conditions using AND or OR operators.

Example
Consider the table COMPANY

, having records as follows −

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following is an example, which would update ADDRESS for a customer, whose ID is 6
−
testdb=# UPDATE COMPANY SET SALARY = 15000 WHERE ID = 3;

Now, COMPANY table would have the following records −
id | name | age | address
| salary
----+-------+-----+------------+-------1 | Paul | 32 | California | 20000

2 | Allen
4 | Mark
5 | David
6 | Kim
7 | James
3 | Teddy
(7 rows)

|
|
|
|
|
|

25
25
27
22
24
23

|
|
|
|
|
|

Texas
Rich-Mond
Texas
South-Hall
Houston
Norway

|
|
|
|
|
|

15000
65000
85000
45000
10000
15000

If you want to modify all ADDRESS and SALARY column values in COMPANY table, you do
not need to use WHERE clause and UPDATE query would be as follows −
testdb=# UPDATE COMPANY SET ADDRESS = 'Texas', SALARY=20000;

Now, COMPANY table will have the following records −
id | name | age | address | salary
----+-------+-----+---------+-------1 | Paul | 32 | Texas
| 20000
2 | Allen | 25 | Texas
| 20000
4 | Mark | 25 | Texas
| 20000
5 | David | 27 | Texas
| 20000
6 | Kim
| 22 | Texas
| 20000
7 | James | 24 | Texas
| 20000
3 | Teddy | 23 | Texas
| 20000
(7 rows)

PostgreSQL - DELETE Query
The PostgreSQL DELETE Query is used to delete the existing records from a table. You can
use WHERE clause with DELETE query to delete the selected rows. Otherwise, all the
records would be deleted.

Syntax
The basic syntax of DELETE query with WHERE clause is as follows −
DELETE FROM table_name
WHERE [condition];

You can combine N number of conditions using AND or OR operators.

Example
Consider the table COMPANY

, having records as follows −

# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000

6 | Kim
|
7 | James |
(7 rows)

22 | South-Hall|
24 | Houston
|

45000
10000

The following is an example, which would DELETE a customer whose ID is 7 −
testdb=# DELETE FROM COMPANY WHERE ID = 2;

Now, COMPANY table will have the following records −
id | name | age | address
| salary
----+-------+-----+-------------+-------1 | Paul | 32 | California | 20000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond
| 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall | 45000
7 | James | 24 | Houston
| 10000
(6 rows)

If you want to DELETE all the records from COMPANY table, you do not need to use WHERE
clause with DELETE queries, which would be as follows −
testdb=# DELETE FROM COMPANY;

Now, COMPANY table does not have any record because all the records have been deleted
by the DELETE statement.

PostgreSQL - LIKE Clause
The PostgreSQL LIKE operator is used to match text values against a pattern using
wildcards. If the search expression can be matched to the pattern expression, the LIKE
operator will return true, which is 1.
There are two wildcards used in conjunction with the LIKE operator −
The percent sign (%)
The underscore (_)

The percent sign represents zero, one, or multiple numbers or characters. The underscore
represents a single number or character. These symbols can be used in combinations.
If either of these two signs is not used in conjunction with the LIKE clause, then the LIKE
acts like the equals operator.

Syntax
The basic syntax of % and _ is as follows −

SELECT FROM table_name
WHERE column LIKE 'XXXX%'
or
SELECT FROM table_name
WHERE column LIKE '%XXXX%'
or
SELECT FROM table_name
WHERE column LIKE 'XXXX_'
or
SELECT FROM table_name
WHERE column LIKE '_XXXX'
or
SELECT FROM table_name
WHERE column LIKE '_XXXX_'

You can combine N number of conditions using AND or OR operators. Here XXXX could be
any numeric or string value.

Example
Here are number of examples showing WHERE part having different LIKE clause with '%'
and '_' operators −
S. No.

Statement & Description

WHERE SALARY::text LIKE '200%'
1

Finds any values that start with 200
WHERE SALARY::text LIKE '%200%'

2

Finds any values that have 200 in any position
WHERE SALARY::text LIKE '_00%'

3

4

Finds any values that have 00 in the second and third positions

WHERE SALARY::text LIKE '2_%_%'
Finds any values that start with 2 and are at least 3 characters in length
WHERE SALARY::text LIKE '%2'
5

Finds any values that end with 2
WHERE SALARY::text LIKE '_2%3'

6

Finds any values that have 2 in the second position and end with a 3
WHERE SALARY::text LIKE '2___3'

7

Finds any values in a five-digit number that start with 2 and end with 3

Postgres LIKE is String compare only. Hence, we need to explicitly cast the integer
column to string as in the examples above.

Let us take a real example, consider the table COMPANY

, having records as follows −

# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following is an example, which would display all the records from COMPANY table
where AGE starts with 2 −
testdb=# SELECT * FROM COMPANY WHERE AGE::text LIKE '2%';

This would produce the following result −
id | name

| age | address

| salary

----+-------+-----+-------------+-------2 | Allen |

25 | Texas

|

15000

3 | Teddy |

23 | Norway

|

20000

4 | Mark

25 | Rich-Mond

|

65000

5 | David |

27 | Texas

|

85000

6 | Kim

22 | South-Hall

|

45000

24 | Houston

|

10000

|
|

7 | James |

8 | Paul

|

24 | Houston

|

20000

(7 rows)

The following is an example, which would display all the records from COMPANY table
where ADDRESS will have a hyphen (-) inside the text −
testdb=# SELECT * FROM COMPANY WHERE ADDRESS

LIKE '%-%';

This would produce the following result −
id | name | age |

address

| salary

----+------+-----+-------------------------------------------+-------4 | Mark |

25 | Rich-Mond

|

65000

6 | Kim

22 | South-Hall

|

45000

|

(2 rows)

PostgreSQL - LIMIT Clause
The PostgreSQL LIMIT clause is used to limit the data amount returned by the SELECT
statement.

Syntax
The basic syntax of SELECT statement with LIMIT clause is as follows −
SELECT column1, column2, columnN
FROM table_name
LIMIT [no of rows]

The following is the syntax of LIMIT clause when it is used along with OFFSET clause −
SELECT column1, column2, columnN
FROM table_name
LIMIT [no of rows] OFFSET [row num]

LIMIT and OFFSET allow you to retrieve just a portion of the rows that are generated by
the rest of the query.

Example
Consider the table COMPANY

having records as follows −

# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000

6 | Kim
|
7 | James |
(7 rows)

22 | South-Hall|
24 | Houston
|

45000
10000

The following is an example, which limits the row in the table according to the number of
rows you want to fetch from table −
testdb=# SELECT * FROM COMPANY LIMIT 4;

This would produce the following result −
id | name

| age | address

| salary

----+-------+-----+-------------+-------1 | Paul

|

32 | California

|

20000

2 | Allen |

25 | Texas

|

15000

3 | Teddy |

23 | Norway

|

20000

4 | Mark

25 | Rich-Mond

|

65000

|

(4 rows)

However, in certain situation, you may need to pick up a set of records from a particular
offset. Here is an example, which picks up three records starting from the third position −
testdb=# SELECT * FROM COMPANY LIMIT 3 OFFSET 2;

This would produce the following result −
id | name

| age | address

| salary

----+-------+-----+-----------+-------3 | Teddy |

23 | Norway

|

20000

4 | Mark

25 | Rich-Mond |

65000

27 | Texas

85000

|

5 | David |

|

(3 rows)

PostgreSQL - ORDER BY Clause
The PostgreSQL ORDER BY clause is used to sort the data in ascending or descending
order, based on one or more columns.

Syntax
The basic syntax of ORDER BY clause is as follows −
SELECT column-list
FROM table_name
[WHERE condition]
[ORDER BY column1, column2, .. columnN] [ASC | DESC];

You can use more than one column in the ORDER BY clause. Make sure whatever column
you are using to sort, that column should be available in column-list.

Example
Consider the table COMPANY

having records as follows −

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following is an example, which would sort the result in ascending order by SALARY −
testdb=# SELECT * FROM COMPANY ORDER BY AGE ASC;

This would produce the following result −
id | name

| age | address

| salary

----+-------+-----+------------+-------6 | Kim

|

22 | South-Hall |

45000

3 | Teddy |

23 | Norway

|

20000

7 | James |

24 | Houston

|

10000

8 | Paul

|

24 | Houston

|

20000

4 | Mark

|

25 | Rich-Mond

|

65000

2 | Allen |

25 | Texas

|

15000

5 | David |

27 | Texas

|

85000

1 | Paul

32 | California |

20000

|

9 | James |

44 | Norway

|

5000

10 | James |

45 | Texas

|

5000

(10 rows)

The following is an example, which would sort the result in ascending order by NAME and
SALARY −
testdb=# SELECT * FROM COMPANY ORDER BY NAME, SALARY ASC;

This would produce the following result −
id | name

| age | address

| salary

----+-------+-----+--------------+-------2 | Allen |

25 | Texas

|

15000

5 | David |

27 | Texas

|

85000

10 | James |

45 | Texas

|

5000

9 | James |

44 | Norway

|

5000

7 | James |

24 | Houston

|

10000

6 | Kim

|

22 | South-Hall

|

45000

4 | Mark

|

25 | Rich-Mond

|

65000

1 | Paul

|

32 | California

|

20000

8 | Paul

|

24 | Houston

|

20000

23 | Norway

|

20000

3 | Teddy |
(10 rows)

The following is an example, which would sort the result in descending order by NAME −
testdb=# SELECT * FROM COMPANY ORDER BY NAME DESC;

This would produce the following result −
id | name

| age | address

| salary

----+-------+-----+------------+-------3 | Teddy |

23 | Norway

|

20000

1 | Paul

|

32 | California |

20000

8 | Paul

|

24 | Houston

|

20000

4 | Mark

|

25 | Rich-Mond

|

65000

6 | Kim

|

22 | South-Hall |

45000

7 | James |

24 | Houston

|

10000

9 | James |

44 | Norway

|

5000

10 | James |

45 | Texas

|

5000

5 | David |

27 | Texas

|

85000

2 | Allen |

25 | Texas

|

15000

(10 rows)

PostgreSQL - GROUP BY
The PostgreSQL GROUP BY clause is used in collaboration with the SELECT statement to
group together those rows in a table that have identical data. This is done to eliminate
redundancy in the output and/or compute aggregates that apply to these groups.
The GROUP BY clause follows the WHERE clause in a SELECT statement and precedes the
ORDER BY clause.

Syntax
The basic syntax of GROUP BY clause is given below. The GROUP BY clause must follow the
conditions in the WHERE clause and must precede the ORDER BY clause if one is used.

SELECT column-list
FROM table_name
WHERE [ conditions ]
GROUP BY column1, column2....columnN
ORDER BY column1, column2....columnN

You can use more than one column in the GROUP BY clause. Make sure whatever column
you are using to group, that column should be available in column-list.

Example
Consider the table COMPANY

having records as follows −

# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

If you want to know the total amount of salary of each customer, then GROUP BY query
would be as follows −
testdb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME;

This would produce the following result −
name

|

sum

-------+------Teddy | 20000
Paul

| 20000

Mark

| 65000

David | 85000
Allen | 15000
Kim

| 45000

James | 10000
(7 rows)

Now, let us create three more records in COMPANY table using the following INSERT
statements −
INSERT INTO COMPANY VALUES (8, 'Paul', 24, 'Houston', 20000.00);
INSERT INTO COMPANY VALUES (9, 'James', 44, 'Norway', 5000.00);
INSERT INTO COMPANY VALUES (10, 'James', 45, 'Texas', 5000.00);

Now, our table has the following records with duplicate names −
id | name | age | address
| salary
----+-------+-----+--------------+-------1 | Paul | 32 | California
| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond
| 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall
| 45000
7 | James | 24 | Houston
| 10000
8 | Paul | 24 | Houston
| 20000
9 | James | 44 | Norway
|
5000
10 | James | 45 | Texas
|
5000
(10 rows)

Again, let us use the same statement to group-by all the records using NAME column as
follows −
testdb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME ORDER BY NAME;

This would produce the following result −
name

|

sum

-------+------Allen | 15000
David | 85000
James | 20000
Kim

| 45000

Mark

| 65000

Paul

| 40000

Teddy | 20000
(7 rows)

Let us use ORDER BY clause along with GROUP BY clause as follows −
testdb=#

SELECT NAME, SUM(SALARY)
FROM COMPANY GROUP BY NAME ORDER BY NAME DESC;

This would produce the following result −
name

|

sum

-------+------Teddy | 20000
Paul

| 40000

Mark

| 65000

Kim

| 45000

James | 20000
David | 85000

Allen | 15000
(7 rows)

PostgreSQL - WITH Clause
In PostgreSQL, the WITH query provides a way to write auxiliary statements for use in a
larger query. It helps in breaking down complicated and large queries into simpler forms,
which are easily readable. These statements often referred to as Common Table
Expressions or CTEs, can be thought of as defining temporary tables that exist just for one
query.
The WITH query being CTE query, is particularly useful when subquery is executed multiple
times. It is equally helpful in place of temporary tables. It computes the aggregation once
and allows us to reference it by its name (may be multiple times) in the queries.
The WITH clause must be defined before it is used in the query.

Syntax
The basic syntax of WITH query is as follows −
WITH
name_for_summary_data AS (
SELECT Statement)
SELECT columns
FROM name_for_summary_data
WHERE conditions <=> (
SELECT column
FROM name_for_summary_data)
[ORDER BY columns]

Where

name_for_summary_data

is

the

name

given

to

the

WITH

clause.

The

name_for_summary_data can be the same as an existing table name and will take
precedence.
You can use data-modifying statements (INSERT, UPDATE or DELETE) in WITH. This allows
you to perform several different operations in the same query.

Recursive WITH
Recursive WITH or Hierarchical queries, is a form of CTE where a CTE can reference to itself, i.e., a
WITH query can refer to its own output, hence the name recursive.

Example
Consider the table COMPANY

having records as follows −

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+--------

1 | Paul
2 | Allen
3 | Teddy
4 | Mark
5 | David
6 | Kim
7 | James
(7 rows)

|
|
|
|
|
|
|

32
25
23
25
27
22
24

|
|
|
|
|
|
|

California|
Texas
|
Norway
|
Rich-Mond |
Texas
|
South-Hall|
Houston
|

20000
15000
20000
65000
85000
45000
10000

Now, let us write a query using the WITH clause to select the records from the above
table, as follows −
With CTE AS
(Select
ID
, NAME
, AGE
, ADDRESS
, SALARY
FROM COMPANY )
Select * From CTE;

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+-----------+-------1 | Paul

|

32 | California|

20000

2 | Allen |

25 | Texas

|

15000

3 | Teddy |

23 | Norway

|

20000

4 | Mark

25 | Rich-Mond |

65000

5 | David |

27 | Texas

|

85000

6 | Kim

22 | South-Hall|

45000

24 | Houston

10000

|
|

7 | James |

|

(7 rows)

Now, let us write a query using the RECURSIVE keyword along with the WITH clause, to
find the sum of the salaries less than 20000, as follows −
WITH RECURSIVE t(n) AS (
VALUES (0)
UNION ALL
SELECT SALARY FROM COMPANY WHERE SALARY < 20000
)
SELECT sum(n) FROM t;

The above given PostgreSQL statement will produce the following result −
sum
------25000
(1 row)

Let us write a query using data modifying statements along with the WITH clause, as
shown below.
First, create a table COMPANY1 similar to the table COMPANY. The query in the example
effectively moves rows from COMPANY to COMPANY1. The DELETE in WITH deletes the
specified rows from COMPANY, returning their contents by means of its RETURNING clause;
and then the primary query reads that output and inserts it into COMPANY1 TABLE −
CREATE TABLE COMPANY1(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
);
WITH moved_rows AS (
DELETE FROM COMPANY
WHERE
SALARY >= 30000
RETURNING *
)
INSERT INTO COMPANY1 (SELECT * FROM moved_rows);

The above given PostgreSQL statement will produce the following result −
INSERT 0 3

Now, the records in the tables COMPANY and COMPANY1 are as follows −
testdb=# SELECT * FROM COMPANY;
id | name | age | address
| salary
----+-------+-----+------------+-------1 | Paul | 32 | California | 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
7 | James | 24 | Houston
| 10000
(4 rows)

testdb=# SELECT * FROM COMPANY1;
id | name | age | address | salary
----+-------+-----+-------------+-------4 | Mark | 25 | Rich-Mond
| 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall | 45000
(3 rows)

PostgreSQL - HAVING Clause
The HAVING clause allows us to pick out particular rows where the function's result meets
some condition.
The WHERE clause places conditions on the selected columns, whereas the HAVING clause
places conditions on groups created by the GROUP BY clause.

Syntax
The following is the position of the HAVING clause in a SELECT query −
SELECT
FROM
WHERE
GROUP BY
HAVING
ORDER BY

The HAVING clause must follow the GROUP BY clause in a query and must also precede the
ORDER BY clause if used. The following is the syntax of the SELECT statement, including
the HAVING clause −
SELECT column1, column2
FROM table1, table2
WHERE [ conditions ]
GROUP BY column1, column2
HAVING [ conditions ]
ORDER BY column1, column2

Example
Consider the table COMPANY

having records as follows −

# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following is an example, which would display record for which the name count is less
than 2 −
testdb-# SELECT NAME FROM COMPANY GROUP BY name HAVING count(name) < 2;

This would produce the following result −
name
------Teddy
Paul

Mark
David
Allen
Kim
James
(7 rows)

Now, let us create three more records in COMPANY table using the following INSERT
statements −
INSERT INTO COMPANY VALUES (8, 'Paul', 24, 'Houston', 20000.00);
INSERT INTO COMPANY VALUES (9, 'James', 44, 'Norway', 5000.00);
INSERT INTO COMPANY VALUES (10, 'James', 45, 'Texas', 5000.00);

Now, our table has the following records with duplicate names −
id | name | age | address
| salary
----+-------+-----+--------------+-------1 | Paul | 32 | California
| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond
| 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall
| 45000
7 | James | 24 | Houston
| 10000
8 | Paul | 24 | Houston
| 20000
9 | James | 44 | Norway
|
5000
10 | James | 45 | Texas
|
5000
(10 rows)

The following is the example, which would display record for which the name count is
greater than 1 −
testdb-# SELECT NAME FROM COMPANY GROUP BY name HAVING count(name) > 1;

This would produce the following result −
name
------Paul
James
(2 rows)

PostgreSQL - DISTINCT Keyword
The PostgreSQL DISTINCT keyword is used in conjunction with SELECT statement to
eliminate all the duplicate records and fetching only unique records.
There may be a situation when you have multiple duplicate records in a table. While
fetching such records, it makes more sense to fetch only unique records instead of fetching
duplicate records.

Syntax
The basic syntax of DISTINCT keyword to eliminate duplicate records is as follows −
SELECT DISTINCT column1, column2,.....columnN
FROM table_name
WHERE [condition]

Example
Consider the table COMPANY

having records as follows −

# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

Let us add two more records to this table as follows −
INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (8, 'Paul', 32, 'California', 20000.00 );
INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (9, 'Allen', 25, 'Texas', 15000.00 );

Now, the records in the COMPANY table would be −
id | name | age | address
| salary
----+-------+-----+------------+-------1 | Paul | 32 | California | 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall | 45000
7 | James | 24 | Houston
| 10000
8 | Paul | 32 | California | 20000
9 | Allen | 25 | Texas
| 15000
(9 rows)

First, let us see how the following SELECT query returns duplicate salary records −
testdb=# SELECT name FROM COMPANY;

This would produce the following result −

name
------Paul
Allen
Teddy
Mark
David
Kim
James
Paul
Allen
(9 rows)

Now, let us use DISTINCT keyword with the above SELECT query and see the result −
testdb=# SELECT DISTINCT name FROM COMPANY;

This would produce the following result where we do not have any duplicate entry −
name
------Teddy
Paul
Mark
David
Allen
Kim
James
(7 rows)

PostgreSQL - CONSTRAINTS
Constraints are the rules enforced on data columns on table. These are used to prevent
invalid data from being entered into the database. This ensures the accuracy and reliability
of the data in the database.
Constraints could be column level or table level. Column level constraints are applied only
to one column whereas table level constraints are applied to the whole table. Defining a
data type for a column is a constraint in itself. For example, a column of type DATE
constrains the column to valid dates.
The following are commonly used constraints available in PostgreSQL.
NOT NULL Constraint − Ensures that a column cannot have NULL value.
UNIQUE Constraint − Ensures that all values in a column are different.

PRIMARY Key − Uniquely identifies each row/record in a database table.
FOREIGN Key − Constrains data based on columns in other tables.
CHECK Constraint − The CHECK constraint ensures that all values in a column
satisfy certain conditions.
EXCLUSION Constraint − The EXCLUDE constraint ensures that if any two rows
are compared on the specified column(s) or expression(s) using the specified
operator(s), not all of these comparisons will return TRUE.

NOT NULL Constraint
By default, a column can hold NULL values. If you do not want a column to have a NULL
value, then you need to define such constraint on this column specifying that NULL is now
not allowed for that column. A NOT NULL constraint is always written as a column
constraint.
A NULL is not the same as no data; rather, it represents unknown data.

Example
For example, the following PostgreSQL statement creates a new table called COMPANY1
and adds five columns, three of which, ID and NAME and AGE, specify not to accept NULL
values −
CREATE TABLE COMPANY1(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
);

UNIQUE Constraint
The UNIQUE Constraint prevents two records from having identical values in a particular
column. In the COMPANY table, for example, you might want to prevent two or more
people from having identical age.

Example
For example, the following PostgreSQL statement creates a new table called COMPANY3
and adds five columns. Here, AGE column is set to UNIQUE, so that you cannot have two
records with same age −
CREATE TABLE COMPANY3(
ID INT PRIMARY KEY
NAME
TEXT
AGE
INT

NOT NULL,
NOT NULL,
NOT NULL UNIQUE,

ADDRESS
SALARY

CHAR(50),
REAL
DEFAULT 50000.00

);

PRIMARY KEY Constraint
The PRIMARY KEY constraint uniquely identifies each record in a database table. There can
be more UNIQUE columns, but only one primary key in a table. Primary keys are important
when designing the database tables. Primary keys are unique ids.
We use them to refer to table rows. Primary keys become foreign keys in other tables,
when creating relations among tables. Due to a 'longstanding coding oversight', primary
keys can be NULL in SQLite. This is not the case with other databases
A primary key is a field in a table, which uniquely identifies each row/record in a database
table. Primary keys must contain unique values. A primary key column cannot have NULL
values.
A table can have only one primary key, which may consist of single or multiple fields.
When multiple fields are used as a primary key, they are called a composite key.
If a table has a primary key defined on any field(s), then you cannot have two records
having the same value of that field(s).

Example
You already have seen various examples above where we have created COMAPNY4 table
with ID as primary key −
CREATE TABLE COMPANY4(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
);

FOREIGN KEY Constraint
A foreign key constraint specifies that the values in a column (or a group of columns) must
match the values appearing in some row of another table. We say this maintains the
referential integrity between two related tables. They are called foreign keys because the
constraints are foreign; that is, outside the table. Foreign keys are sometimes called a
referencing key.

Example
For example, the following PostgreSQL statement creates a new table called COMPANY5
and adds five columns.

CREATE TABLE COMPANY6(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
);

For

example,

the

following

PostgreSQL

statement

creates

a

new

table

called

DEPARTMENT1, which adds three columns. The column EMP_ID is the foreign key and
references the ID field of the table COMPANY6.
CREATE TABLE DEPARTMENT1(
ID INT PRIMARY KEY
NOT NULL,
DEPT
CHAR(50) NOT NULL,
EMP_ID
INT
references COMPANY6(ID)
);

CHECK Constraint
The CHECK Constraint enables a condition to check the value being entered into a record.
If the condition evaluates to false, the record violates the constraint and is not entered into
the table.

Example
For example, the following PostgreSQL statement creates a new table called COMPANY5
and adds five columns. Here, we add a CHECK with SALARY column, so that you cannot
have any SALARY as Zero.
CREATE TABLE COMPANY5(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
CHECK(SALARY > 0)
);

EXCLUSION Constraint
Exclusion constraints ensure that if any two rows are compared on the specified columns
or expressions using the specified operators, at least one of these operator comparisons
will return false or null.

Example
For example, the following PostgreSQL statement creates a new table called COMPANY7
and adds five columns. Here, we add an EXCLUDE constraint −
CREATE TABLE COMPANY7(
ID INT PRIMARY KEY

NOT NULL,

NAME
TEXT,
AGE
INT ,
ADDRESS
CHAR(50),
SALARY
REAL,
EXCLUDE USING gist
(NAME WITH =,
AGE WITH <>)
);

Here, USING gist is the type of index to build and use for enforcement.
You need to execute the command CREATE EXTENSION btree_gist, once per
database. This will install the btree_gist extension, which defines the exclusion
constraints on plain scalar data types.

As we have enforced the age has to be same, let us see this by inserting records to the
table −
INSERT INTO COMPANY7 VALUES(1, 'Paul', 32, 'California', 20000.00 );
INSERT INTO COMPANY7 VALUES(2, 'Paul', 32, 'Texas', 20000.00 );
INSERT INTO COMPANY7 VALUES(3, 'Allen', 42, 'California', 20000.00 );

For the first two INSERT statements, the records are added to the COMPANY7 table. For
the third INSERT statement, the following error is displayed −
ERROR: duplicate key value violates unique constraint "company7_pkey"
DETAIL: Key (id)=(3) already exists.

Dropping Constraints
To remove a constraint you need to know its name. If the name is known, it is easy to
drop. Else, you need to find out the system-generated name. The psql command \d table
name can be helpful here. The general syntax is −
ALTER TABLE table_name DROP CONSTRAINT some_name;

PostgreSQL - JOINS
The PostgreSQL Joins clause is used to combine records from two or more tables in a
database. A JOIN is a means for combining fields from two tables by using values common
to each.
Join Types in PostgreSQL are −
The CROSS JOIN
The INNER JOIN
The LEFT OUTER JOIN

The RIGHT OUTER JOIN
The FULL OUTER JOIN

Before we proceed, let us consider two tables, COMPANY and DEPARTMENT. We already
have seen INSERT statements to populate COMPANY table. So just let us assume the list of
records available in COMPANY table −
id | name | age | address
| salary | join_date
----+-------+-----+-----------+--------+----------1 | Paul | 32 | California| 20000 | 2001-07-13
3 | Teddy | 23 | Norway
| 20000 |
4 | Mark | 25 | Rich-Mond | 65000 | 2007-12-13
5 | David | 27 | Texas
| 85000 | 2007-12-13
2 | Allen | 25 | Texas
|
| 2007-12-13
8 | Paul | 24 | Houston
| 20000 | 2005-07-13
9 | James | 44 | Norway
|
5000 | 2005-07-13
10 | James | 45 | Texas
|
5000 | 2005-07-13

Another table is DEPARTMENT, has the following definition −
CREATE TABLE DEPARTMENT(
ID INT PRIMARY KEY
NOT NULL,
DEPT
CHAR(50) NOT NULL,
EMP_ID
INT
NOT NULL
);

Here is the list of INSERT statements to populate DEPARTMENT table −
INSERT INTO DEPARTMENT (ID, DEPT, EMP_ID)
VALUES (1, 'IT Billing', 1 );
INSERT INTO DEPARTMENT (ID, DEPT, EMP_ID)
VALUES (2, 'Engineering', 2 );
INSERT INTO DEPARTMENT (ID, DEPT, EMP_ID)
VALUES (3, 'Finance', 7 );

Finally, we have the following list of records available in DEPARTMENT table −
id | dept
| emp_id
----+-------------+-------1 | IT Billing | 1
2 | Engineering | 2
3 | Finance
| 7

The CROSS JOIN
A CROSS JOIN matches every row of the first table with every row of the second table. If
the input tables have x and y columns, respectively, the resulting table will have x+y
columns. Because CROSS JOINs have the potential to generate extremely large tables,
care must be taken to use them only when appropriate.

The following is the syntax of CROSS JOIN −
SELECT ... FROM table1 CROSS JOIN table2 ...

Based on the above tables, we can write a CROSS JOIN as follows −
testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY CROSS JOIN DEPARTMENT;

The above given query will produce the following result −
emp_id| name

|

dept

------|-------|-------------1 | Paul

| IT Billing

1 | Teddy | IT Billing
1 | Mark

| IT Billing

1 | David | IT Billing
1 | Allen | IT Billing
1 | Paul

| IT Billing

1 | James | IT Billing
1 | James | IT Billing
2 | Paul

| Engineering

2 | Teddy | Engineering
2 | Mark

| Engineering

2 | David | Engineering
2 | Allen | Engineering
2 | Paul

| Engineering

2 | James | Engineering
2 | James | Engineering
7 | Paul

| Finance

7 | Teddy | Finance
7 | Mark

| Finance

7 | David | Finance
7 | Allen | Finance
7 | Paul

| Finance

7 | James | Finance
7 | James | Finance

The INNER JOIN
A INNER JOIN creates a new result table by combining column values of two tables (table1
and table2) based upon the join-predicate. The query compares each row of table1 with
each row of table2 to find all pairs of rows, which satisfy the join-predicate. When the joinpredicate is satisfied, column values for each matched pair of rows of table1 and table2 are
combined into a result row.

An INNER JOIN is the most common type of join and is the default type of join. You can
use INNER keyword optionally.
The following is the syntax of INNER JOIN −
SELECT table1.column1, table2.column2...
FROM table1
INNER JOIN table2
ON table1.common_filed = table2.common_field;

Based on the above tables, we can write an INNER JOIN as follows −
testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −
emp_id | name

| dept

--------+-------+-----------1 | Paul

| IT Billing

2 | Allen | Engineering

The LEFT OUTER JOIN
The OUTER JOIN is an extension of the INNER JOIN. SQL standard defines three types of
OUTER JOINs: LEFT, RIGHT, and FULL and PostgreSQL supports all of these.
In case of LEFT OUTER JOIN, an inner join is performed first. Then, for each row in table
T1 that does not satisfy the join condition with any row in table T2, a joined row is added
with null values in columns of T2. Thus, the joined table always has at least one row for
each row in T1.
The following is the syntax of LEFT OUTER JOIN −
SELECT ... FROM table1 LEFT OUTER JOIN table2 ON conditional_expression ...

Based on the above tables, we can write an inner join as follows −
testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −
emp_id | name

| dept

--------+-------+-----------1 | Paul

| IT Billing

2 | Allen | Engineering
| James |
| David |

| Paul

|

| Mark

|

| Teddy |
| James |

The RIGHT OUTER JOIN
First, an inner join is performed. Then, for each row in table T2 that does not satisfy the
join condition with any row in table T1, a joined row is added with null values in columns of
T1. This is the converse of a left join; the result table will always have a row for each row
in T2.
The following is the syntax of RIGHT OUTER JOIN −
SELECT ... FROM table1 RIGHT OUTER JOIN table2 ON conditional_expression ...

Based on the above tables, we can write an inner join as follows −
testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY RIGHT OUTER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −
emp_id | name

| dept

--------+-------+-------1 | Paul

| IT Billing

2 | Allen | Engineering
7 |

| Finance

The FULL OUTER JOIN
First, an inner join is performed. Then, for each row in table T1 that does not satisfy the
join condition with any row in table T2, a joined row is added with null values in columns of
T2. In addition, for each row of T2 that does not satisfy the join condition with any row in
T1, a joined row with null values in the columns of T1 is added.
The following is the syntax of FULL OUTER JOIN −
SELECT ... FROM table1 FULL OUTER JOIN table2 ON conditional_expression ...

Based on the above tables, we can write an inner join as follows −
testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY FULL OUTER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −
emp_id | name

| dept

--------+-------+---------------

1 | Paul

| IT Billing

2 | Allen | Engineering
7 |

| Finance

| James |
| David |
| Paul

|

| Mark

|

| Teddy |
| James |

PostgreSQL - UNIONS Clause
The PostgreSQL UNION clause/operator is used to combine the results of two or more
SELECT statements without returning any duplicate rows.
To use UNION, each SELECT must have the same number of columns selected, the same
number of column expressions, the same data type, and have them in the same order but
they do not have to be the same length.

Syntax
The basic syntax of UNION is as follows −
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
UNION
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

Here, given condition could be any given expression based on your requirement.

Example
Consider the following two tables, (a) COMPANY
testdb=# SELECT * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000

table is as follows −

7 | James |
(7 rows)

24 | Houston

|

10000

(b) Another table is DEPARTMENT

as follows −

testdb=# SELECT * from DEPARTMENT;
id | dept
| emp_id
----+-------------+-------1 | IT Billing |
1
2 | Engineering |
2
3 | Finance
|
7
4 | Engineering |
3
5 | Finance
|
4
6 | Engineering |
5
7 | Finance
|
6
(7 rows)

Now let us join these two tables using SELECT statement along with UNION clause as
follows −
testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID
UNION
SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;

This would produce the following result −
emp_id | name

|

dept

--------+-------+-------------5 | David | Engineering
6 | Kim

| Finance

2 | Allen | Engineering
3 | Teddy | Engineering
4 | Mark

| Finance

1 | Paul

| IT Billing

7 | James | Finance
(7 rows)

The UNION ALL Clause
The UNION ALL operator is used to combine the results of two SELECT statements
including duplicate rows. The same rules that apply to UNION apply to the UNION ALL
operator as well.

Syntax
The basic syntax of UNION ALL is as follows −
SELECT column1 [, column2 ]
FROM table1 [, table2 ]

[WHERE condition]
UNION ALL
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

Here, given condition could be any given expression based on your requirement.

Example
Now, let us join above-mentioned two tables in our SELECT statement as follows −
testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID
UNION ALL
SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;

This would produce the following result −
emp_id | name

| dept

--------+-------+-------------1 | Paul

| IT Billing

2 | Allen | Engineering
7 | James | Finance
3 | Teddy | Engineering
4 | Mark

| Finance

5 | David | Engineering
6 | Kim

| Finance

1 | Paul

| IT Billing

2 | Allen | Engineering
7 | James | Finance
3 | Teddy | Engineering
4 | Mark

| Finance

5 | David | Engineering
6 | Kim

| Finance

(14 rows)

PostgreSQL - NULL Values
The PostgreSQL NULL is the term used to represent a missing value. A NULL value in a
table is a value in a field that appears to be blank.
A field with a NULL value is a field with no value. It is very important to understand that a
NULL value is different from a zero value or a field that contains spaces.

Syntax
The basic syntax of using NULL while creating a table is as follows −
CREATE TABLE COMPANY(
ID INT PRIMARY KEY

NOT NULL,

NAME

TEXT

NOT NULL,

AGE

INT

NOT NULL,

ADDRESS

CHAR(50),

SALARY

REAL

);

Here, NOT NULL signifies that column should always accept an explicit value of the given
data type. There are two columns where we did not use NOT NULL. Hence, this means
these columns could be NULL.
A field with a NULL value is one that has been left blank during record creation.

Example
The NULL value can cause problems when selecting data, because when comparing an
unknown value to any other value, the result is always unknown and not included in the
final results. Consider the following table, COMPANY
ID
---------1
2
3
4
5
6
7

NAME
---------Paul
Allen
Teddy
Mark
David
Kim
James

AGE
---------32
25
23
25
27
22
24

ADDRESS
---------California
Texas
Norway
Rich-Mond
Texas
South-Hall
Houston

having the following records −

SALARY
---------20000.0
15000.0
20000.0
65000.0
85000.0
45000.0
10000.0

Let us use the UPDATE statement to set few nullable values as NULL as follows −
testdb=# UPDATE COMPANY SET ADDRESS = NULL, SALARY = NULL where ID IN(6,7);

Now, COMPANY table should have the following records −
id | name | age | address
| salary
----+-------+-----+-------------+-------1 | Paul | 32 | California | 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond
| 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 |
|
7 | James | 24 |
|
(7 rows)

Next, let us see the usage of IS NOT NULL operator to list down all the records where
SALARY is not NULL −
testdb=# SELECT ID, NAME, AGE, ADDRESS, SALARY
FROM COMPANY
WHERE SALARY IS NOT NULL;

The above given PostgreSQL statement will produce the following result −
id | name

| age | address

| salary

----+-------+-----+------------+-------1 | Paul

|

32 | California |

20000

2 | Allen |

25 | Texas

|

15000

3 | Teddy |

23 | Norway

|

20000

4 | Mark

25 | Rich-Mond

|

65000

27 | Texas

|

85000

|

5 | David |
(5 rows)

The following is the usage of IS NULL operator which will list down all the records where
SALARY is NULL −
testdb=#

SELECT ID, NAME, AGE, ADDRESS, SALARY
FROM COMPANY
WHERE SALARY IS NULL;

The above given PostgreSQL statement will produce the following result −
id | name

| age | address | salary

----+-------+-----+---------+-------6 | Kim

|

22 |

|

7 | James |

24 |

|

(2 rows)

PostgreSQL - ALIAS Syntax
You can rename a table or a column temporarily by giving another name, which is known
as ALIAS. The use of table aliases means to rename a table in a particular PostgreSQL
statement. Renaming is a temporary change and the actual table name does not change in
the database.
The column aliases are used to rename a table's columns for the purpose of a particular
PostgreSQL query.

Syntax
The basic syntax of table alias is as follows −

SELECT column1, column2....
FROM table_name AS alias_name
WHERE [condition];

The basic syntax of column alias is as follows −
SELECT column_name AS alias_name
FROM table_name
WHERE [condition];

Example
Consider the following two tables, (a) COMPANY

table is as follows −

testdb=# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

(b) Another table is DEPARTMENT

as follows −

id | dept
| emp_id
----+--------------+-------1 | IT Billing
|
1
2 | Engineering |
2
3 | Finance
|
7
4 | Engineering |
3
5 | Finance
|
4
6 | Engineering |
5
7 | Finance
|
6
(7 rows)

Now, following is the usage of TABLE ALIAS where we use C and D as aliases for
COMPANY and DEPARTMENT tables, respectively −
testdb=# SELECT C.ID, C.NAME, C.AGE, D.DEPT
FROM COMPANY AS C, DEPARTMENT AS D
WHERE C.ID = D.EMP_ID;

The above given PostgreSQL statement will produce the following result −
id | name

| age |

dept

----+-------+-----+-----------1 | Paul

|

2 | Allen |

32 | IT Billing
25 | Engineering

7 | James |

24 | Finance

3 | Teddy |

23 | Engineering

4 | Mark

25 | Finance

|

5 | David |

27 | Engineering

6 | Kim

22 | Finance

|

(7 rows)

Let us see an example for the usage of COLUMN ALIAS where COMPANY_ID is an alias of
ID column and COMPANY_NAME is an alias of name column −
testdb=# SELECT C.ID AS COMPANY_ID, C.NAME AS COMPANY_NAME, C.AGE, D.DEPT
FROM COMPANY AS C, DEPARTMENT AS D
WHERE C.ID = D.EMP_ID;

The above given PostgreSQL statement will produce the following result −
company_id | company_name | age | dept
------------+--------------+-----+-----------1

| Paul

|

32 | IT Billing

2

| Allen

|

25 | Engineering

7

| James

|

24 | Finance

3

| Teddy

|

23 | Engineering

4

| Mark

|

25 | Finance

5

| David

|

27 | Engineering

6

| Kim

|

22 | Finance

(7 rows)

PostgreSQL - TRIGGERS
PostgreSQL

Triggers

are

database

callback

functions,

which

are

automatically

performed/invoked when a specified database event occurs.
The following are important points about PostgreSQL triggers −
PostgreSQL trigger can be specified to fire
Before the operation is attempted on a row (before constraints are checked
and the INSERT, UPDATE or DELETE is attempted)
After the operation has completed (after constraints are checked and the
INSERT, UPDATE, or DELETE has completed)
Instead of the operation (in the case of inserts, updates or deletes on a
view)
A trigger that is marked FOR EACH ROW is called once for every row that the
operation modifies. In contrast, a trigger that is marked FOR EACH STATEMENT

only executes once for any given operation, regardless of how many rows it
modifies.
Both, the WHEN clause and the trigger actions, may access elements of the row
being inserted, deleted or updated using references of the form NEW.columnname and OLD.column-name, where column-name is the name of a column
from the table that the trigger is associated with.
If a WHEN clause is supplied, the PostgreSQL statements specified are only
executed for rows for which the WHEN clause is true. If no WHEN clause is
supplied, the PostgreSQL statements are executed for all rows.
If multiple triggers of the same kind are defined for the same event, they will be
fired in alphabetical order by name.
The BEFORE, AFTER or INSTEAD OF keyword determines when the trigger actions
will be executed relative to the insertion, modification or removal of the associated
row.
Triggers are automatically dropped when the table that they are associated with is
dropped.
The table to be modified must exist in the same database as the table or view to
which

the

trigger

is

attached

and

one

must

use

just

tablename,

not

database.tablename.
A CONSTRAINT option when specified creates a constraint trigger. This is the same
as a regular trigger except that the timing of the trigger firing can be adjusted
using SET CONSTRAINTS. Constraint triggers are expected to raise an exception
when the constraints they implement are violated.

Syntax
The basic syntax of creating a trigger is as follows −
CREATE

TRIGGER trigger_name [BEFORE|AFTER|INSTEAD OF] event_name

ON table_name
[
-- Trigger logic goes here....
];

Here, event_name could be INSERT, DELETE, UPDATE, and TRUNCATE database
operation on the mentioned table table_name. You can optionally specify FOR EACH ROW
after table name.
The following is the syntax of creating a trigger on an UPDATE operation on one or more
specified columns of a table as follows −

CREATE TRIGGER trigger_name [BEFORE|AFTER] UPDATE OF column_name
ON table_name
[
-- Trigger logic goes here....
];

Example
Let us consider a case where we want to keep audit trial for every record being inserted in
COMPANY table, which we will create newly as follows (Drop COMPANY table if you already
have it).
testdb=# CREATE TABLE COMPANY(
ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
);

To keep audit trial, we will create a new table called AUDIT where log messages will be
inserted whenever there is an entry in COMPANY table for a new record −
testdb=# CREATE TABLE AUDIT(
EMP_ID INT NOT NULL,
ENTRY_DATE TEXT NOT NULL
);

Here, ID is the AUDIT record ID, and EMP_ID is the ID, which will come from COMPANY
table, and DATE will keep timestamp when the record will be created in COMPANY table. So
now, let us create a trigger on COMPANY table as follows −
testdb=# CREATE TRIGGER example_trigger AFTER INSERT ON COMPANY
FOR EACH ROW EXECUTE PROCEDURE auditlogfunc();

Where auditlogfunc() is a PostgreSQL procedure and has the following definition −
CREATE OR REPLACE FUNCTION auditlogfunc() RETURNS TRIGGER AS $example_table$
BEGIN
INSERT INTO AUDIT(EMP_ID, ENTRY_DATE) VALUES (new.ID, current_timestamp);
RETURN NEW;
END;
$example_table$ LANGUAGE plpgsql;

Now, we will start the actual work. Let us start inserting record in COMPANY table which
should result in creating an audit log record in AUDIT table. So let us create one record in
COMPANY table as follows −
testdb=# INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (1, 'Paul', 32, 'California', 20000.00 );

This will create one record in COMPANY table, which is as follows −
id | name | age | address
| salary
----+------+-----+--------------+-------1 | Paul | 32 | California
| 20000

Same time, one record will be created in AUDIT table. This record is the result of a trigger,
which we have created on INSERT operation on COMPANY table. Similarly, you can create
your triggers on UPDATE and DELETE operations based on your requirements.
emp_id |
entry_date
--------+------------------------------1 | 2013-05-05 15:49:59.968+05:30
(1 row)

Listing TRIGGERS
You can list down all the triggers in the current database from pg_trigger table as follows
−
testdb=# SELECT * FROM pg_trigger;

The above given PostgreSQL statement will list down all triggers.
If you want to list the triggers on a particular table, then use AND clause with table name
as follows −
testdb=# SELECT tgname FROM pg_trigger, pg_class WHERE tgrelid=pg_class.oid AND relname='company'

The above given PostgreSQL statement will also list down only one entry as follows −
tgname
----------------example_trigger
(1 row)

Dropping TRIGGERS
The following is the DROP command, which can be used to drop an existing trigger −
testdb=# DROP TRIGGER trigger_name;

PostgreSQL - INDEXES
Indexes are special lookup tables that the database search engine can use to speed up
data retrieval. Simply put, an index is a pointer to data in a table. An index in a database
is very similar to an index in the back of a book.

For example, if you want to reference all pages in a book that discusses a certain topic,
you have to first refer to the index, which lists all topics alphabetically and then refer to
one or more specific page numbers.
An index helps to speed up SELECT queries and WHERE clauses; however, it slows down
data input, with UPDATE and INSERT statements. Indexes can be created or dropped with
no effect on the data.
Creating an index involves the CREATE INDEX statement, which allows you to name the
index, to specify the table and which column or columns to index, and to indicate whether
the index is in ascending or descending order.
Indexes can also be unique, similar to the UNIQUE constraint, in that the index prevents
duplicate entries in the column or combination of columns on which there's an index.

The CREATE INDEX Command
The basic syntax of CREATE INDEX is as follows −
CREATE INDEX index_name ON table_name;

Index Types
PostgreSQL provides several index types: B-tree, Hash, GiST, SP-GiST and GIN. Each
Index type uses a different algorithm that is best suited to different types of queries. By
default, the CREATE INDEX command creates B-tree indexes, which fit the most common
situations.

Single-Column Indexes
A single-column index is one that is created based on only one table column. The basic
syntax is as follows −
CREATE INDEX index_name
ON table_name (column_name);

Multicolumn Indexes
A multicolumn index is defined on more than one column of a table. The basic syntax is as
follows −
CREATE INDEX index_name
ON table_name (column1_name, column2_name);

Whether to create a single-column index or a multicolumn index, take into consideration
the column(s) that you may use very frequently in a query's WHERE clause as filter
conditions.

Should there be only one column used, a single-column index should be the choice. Should
there be two or more columns that are frequently used in the WHERE clause as filters, the
multicolumn index would be the best choice.

Unique Indexes
Unique indexes are used not only for performance, but also for data integrity. A unique
index does not allow any duplicate values to be inserted into the table. The basic syntax is
as follows −
CREATE UNIQUE INDEX index_name
on table_name (column_name);

Partial Indexes
A partial index is an index built over a subset of a table; the subset is defined by a
conditional expression (called the predicate of the partial index). The index contains
entries only for those table rows that satisfy the predicate. The basic syntax is as follows −
CREATE INDEX index_name
on table_name (conditional_expression);

Implicit Indexes
Implicit indexes are indexes that are automatically created by the database server when
an object is created. Indexes are automatically created for primary key constraints and
unique constraints.

Example
The following is an example where we will create an index on COMPANY

table for salary

column −
# CREATE INDEX salary_index ON COMPANY (salary);

Now, let us list down all the indices available on COMPANY table using \d company
command.
# \d company

This will produce the following result, where company_pkey is an implicit index, which got
created when the table was created.
Table "public.company"
Column |
Type
| Modifiers
---------+---------------+----------id
| integer
| not null
name
| text
| not null
age
| integer
| not null

address | character(50) |
salary | real
|
Indexes:
"company_pkey" PRIMARY KEY, btree (id)
"salary_index" btree (salary)

You can list down the entire indexes database wide using the \di command −

The DROP INDEX Command
An index can be dropped using PostgreSQL DROP command. Care should be taken when
dropping an index because performance may be slowed or improved.
The basic syntax is as follows −
DROP INDEX index_name;

You can use following statement to delete previously created index −
# DROP INDEX salary_index;

When Should Indexes be Avoided?
Although indexes are intended to enhance a database's performance, there are times when
they should be avoided. The following guidelines indicate when the use of an index should
be reconsidered −
Indexes should not be used on small tables.
Tables that have frequent, large batch update or insert operations.
Indexes should not be used on columns that contain a high number of NULL
values.
Columns that are frequently manipulated should not be indexed.

PostgreSQL - ALTER TABLE Command
The PostgreSQL ALTER TABLE command is used to add, delete or modify columns in an
existing table.
You would also use ALTER TABLE command to add and drop various constraints on an
existing table.

Syntax
The basic syntax of ALTER TABLE to add a new column in an existing table is as follows −
ALTER TABLE table_name ADD column_name datatype;

The basic syntax of ALTER TABLE to DROP COLUMN in an existing table is as follows −
ALTER TABLE table_name DROP COLUMN column_name;

The basic syntax of ALTER TABLE to change the DATA TYPE of a column in a table is as
follows −
ALTER TABLE table_name ALTER COLUMN column_name TYPE datatype;

The basic syntax of ALTER TABLE to add a NOT NULL constraint to a column in a table is
as follows −
ALTER TABLE table_name MODIFY column_name datatype NOT NULL;

The basic syntax of ALTER TABLE to ADD UNIQUE CONSTRAINT to a table is as follows
−
ALTER TABLE table_name
ADD CONSTRAINT MyUniqueConstraint UNIQUE(column1, column2...);

The basic syntax of ALTER TABLE to ADD CHECK CONSTRAINT to a table is as follows −
ALTER TABLE table_name
ADD CONSTRAINT MyUniqueConstraint CHECK (CONDITION);

The basic syntax of ALTER TABLE to ADD PRIMARY KEY constraint to a table is as follows
−
ALTER TABLE table_name
ADD CONSTRAINT MyPrimaryKey PRIMARY KEY (column1, column2...);

The basic syntax of ALTER TABLE to DROP CONSTRAINT from a table is as follows −
ALTER TABLE table_name
DROP CONSTRAINT MyUniqueConstraint;

If you are using MySQL, the code is as follows −
ALTER TABLE table_name
DROP INDEX MyUniqueConstraint;

The basic syntax of ALTER TABLE to DROP PRIMARY KEY constraint from a table is as
follows −
ALTER TABLE table_name
DROP CONSTRAINT MyPrimaryKey;

If you are using MySQL, the code is as follows −
ALTER TABLE table_name
DROP PRIMARY KEY;

Example
Consider our COMPANY

table has the following records −

id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000

The following is the example to ADD a new column in an existing table −
testdb=# ALTER TABLE COMPANY ADD GENDER char(1);

Now, COMPANY table is changed and the following would be the output from SELECT
statement −
id | name | age | address
| salary | gender
----+-------+-----+-------------+--------+-------1 | Paul | 32 | California | 20000 |
2 | Allen | 25 | Texas
| 15000 |
3 | Teddy | 23 | Norway
| 20000 |
4 | Mark | 25 | Rich-Mond
| 65000 |
5 | David | 27 | Texas
| 85000 |
6 | Kim
| 22 | South-Hall | 45000 |
7 | James | 24 | Houston
| 10000 |
(7 rows)

The following is the example to DROP gender column from existing table −
testdb=# ALTER TABLE COMPANY DROP GENDER;

Now, COMPANY table is changed and the following would be the output from SELECT
statement −
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000

PostgreSQL - TRUNCATE TABLE Command
The PostgreSQL TRUNCATE TABLE command is used to delete complete data from an
existing table. You can also use DROP TABLE command to delete complete table but it

would remove complete table structure from the database and you would need to recreate this table once again if you wish to store some data.
It has the same effect as DELETE on each table, but since it does not actually scan the
tables, it is faster. Furthermore, it reclaims disk space immediately, rather than requiring a
subsequent VACUUM operation. This is most useful on large tables.

Syntax
The basic syntax of TRUNCATE TABLE is as follows −
TRUNCATE TABLE

table_name;

Example
Consider the COMPANY table has the following records −
id | name | age | address
| salary
----+-------+-----+------------+-------1 | Paul | 32 | California | 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall | 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following is the example to truncate −
testdb=# TRUNCATE TABLE COMPANY;

Now, COMPANY table is truncated and the following would be the output of SELECT
statement −
testdb=# SELECT * FROM CUSTOMERS;
id | name | age | address | salary
----+------+-----+---------+-------(0 rows)

PostgreSQL - VIEWS
Views are pseudo-tables. That is, they are not real tables; nevertheless appear as ordinary
tables to SELECT. A view can represent a subset of a real table, selecting certain columns
or certain rows from an ordinary table. A view can even represent joined tables. Because
views are assigned separate permissions, you can use them to restrict table access so that
the users see only specific rows or columns of a table.

A view can contain all rows of a table or selected rows from one or more tables. A view can
be created from one or many tables, which depends on the written PostgreSQL query to
create a view.
Views, which are kind of virtual tables, allow users to do the following −
Structure data in a way that users or classes of users find natural or intuitive.
Restrict access to the data such that a user can only see limited data instead of
complete table.
Summarize data from various tables, which can be used to generate reports.
Since views are not ordinary tables, you may not be able to execute a DELETE, INSERT, or
UPDATE statement on a view. However, you can create a RULE to correct this problem of
using DELETE, INSERT or UPDATE on a view.

Creating Views
The PostgreSQL views are created using the CREATE VIEW statement. The PostgreSQL
views can be created from a single table, multiple tables, or another view.
The basic CREATE VIEW syntax is as follows −
CREATE [TEMP | TEMPORARY] VIEW view_name AS
SELECT column1, column2.....
FROM table_name
WHERE [condition];

You can include multiple tables in your SELECT statement in very similar way as you use
them in normal PostgreSQL SELECT query. If the optional TEMP or TEMPORARY keyword is
present, the view will be created in the temporary space. Temporary views are
automatically dropped at the end of the current session.

Example
Consider, the COMPANY

table is having the following records −

id | name | age | address
| salary
----+-------+-----+------------+-------1 | Paul | 32 | California | 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall | 45000
7 | James | 24 | Houston
| 10000

Now, following is an example to create a view from COMPANY table. This view would be
used to have only few columns from COMPANY table −

testdb=# CREATE VIEW COMPANY_VIEW AS
SELECT ID, NAME, AGE
FROM COMPANY;

Now, you can query COMPANY_VIEW in a similar way as you query an actual table.
Following is the example −
testdb=# SELECT * FROM COMPANY_VIEW;

This would produce the following result −
id | name

| age

----+-------+----1 | Paul

|

32

2 | Allen |

25

3 | Teddy |

23

4 | Mark

|

25

5 | David |

27

6 | Kim

|

22

7 | James |

24

(7 rows)

Dropping Views
To drop a view, simply use the DROP VIEW statement with the view_name. The basic
DROP VIEW syntax is as follows −
testdb=# DROP VIEW view_name;

The following command will delete COMPANY_VIEW view, which we created in the last
section −
testdb=# DROP VIEW COMPANY_VIEW;

PostgreSQL - TRANSACTIONS
A transaction is a unit of work that is performed against a database. Transactions are units
or sequences of work accomplished in a logical order, whether in a manual fashion by a
user or automatically by some sort of a database program.
A transaction is the propagation of one or more changes to the database. For example, if
you are creating a record, updating a record, or deleting a record from the table, then you
are performing transaction on the table. It is important to control transactions to ensure
data integrity and to handle database errors.
Practically, you will club many PostgreSQL queries into a group and you will execute all of
them together as a part of a transaction.

Properties of Transactions
Transactions have the following four standard properties, usually referred to by the
acronym ACID −
Atomicity − Ensures that all operations within the work unit are completed
successfully; otherwise, the transaction is aborted at the point of failure and
previous operations are rolled back to their former state.
Consistency − Ensures that the database properly changes states upon a
successfully committed transaction.
Isolation − Enables transactions to operate independently of and transparent to
each other.
Durability − Ensures that the result or effect of a committed transaction persists
in case of a system failure.

Transaction Control
The following commands are used to control transactions −
BEGIN TRANSACTION − To start a transaction.
COMMIT − To save the changes, alternatively you can use END TRANSACTION
command.
ROLLBACK − To rollback the changes.
Transactional control commands are only used with the DML commands INSERT, UPDATE
and DELETE only. They cannot be used while creating tables or dropping them because
these operations are automatically committed in the database.

The BEGIN TRANSACTION Command
Transactions can be started using BEGIN TRANSACTION or simply BEGIN command. Such
transactions usually persist until the next COMMIT or ROLLBACK command is encountered.
But a transaction will also ROLLBACK if the database is closed or if an error occurs.
The following is the simple syntax to start a transaction −
BEGIN;
or
BEGIN TRANSACTION;

The COMMIT Command

The COMMIT command is the transactional command used to save changes invoked by a
transaction to the database.
The COMMIT command saves all transactions to the database since the last COMMIT or
ROLLBACK command.
The syntax for COMMIT command is as follows −
COMMIT;
or
END TRANSACTION;

The ROLLBACK Command
The ROLLBACK command is the transactional command used to undo transactions that
have not already been saved to the database.
The ROLLBACK command can only be used to undo transactions since the last COMMIT or
ROLLBACK command was issued.
The syntax for ROLLBACK command is as follows −
ROLLBACK;

Example
Consider the COMPANY

table is having the following records −

id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000

Now, let us start a transaction and delete records from the table having age = 25 and
finally we use ROLLBACK command to undo all the changes.
testdb=# BEGIN;
DELETE FROM COMPANY WHERE AGE = 25;
ROLLBACK;

If you will check COMPANY table is still having the following records −
id | name | age | address
| salary
----+-------+-----+-----------+--------

1
2
3
4
5
6
7

|
|
|
|
|
|
|

Paul
Allen
Teddy
Mark
David
Kim
James

|
|
|
|
|
|
|

32
25
23
25
27
22
24

|
|
|
|
|
|
|

California|
Texas
|
Norway
|
Rich-Mond |
Texas
|
South-Hall|
Houston
|

20000
15000
20000
65000
85000
45000
10000

Now, let us start another transaction and delete records from the table having age = 25
and finally we use COMMIT command to commit all the changes.
testdb=# BEGIN;
DELETE FROM COMPANY WHERE AGE = 25;
COMMIT;

If you will check the COMPANY table, it still has the following records −
id | name | age | address
| salary
----+-------+-----+------------+-------1 | Paul | 32 | California | 20000
3 | Teddy | 23 | Norway
| 20000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall | 45000
7 | James | 24 | Houston
| 10000
(5 rows)

PostgreSQL - LOCKS
Locks or Exclusive Locks or Write Locks prevent users from modifying a row or an entire
table. Rows modified by UPDATE and DELETE are then exclusively locked automatically for
the duration of the transaction. This prevents other users from changing the row until the
transaction is either committed or rolled back.
The only time when users must wait for other users is when they are trying to modify the
same row. If they modify different rows, no waiting is necessary. SELECT queries never
have to wait.
The database performs locking automatically. In certain cases, however, locking must be
controlled manually. Manual locking can be done by using the LOCK command. It allows
specification of a transaction's lock type and scope.

Syntax for LOCK command
The basic syntax for LOCK command is as follows −
LOCK [ TABLE ]
name
IN
lock_mode

name − The name (optionally schema-qualified) of an existing table to lock. If
ONLY is specified before the table name, only that table is locked. If ONLY is not
specified, the table and all its descendant tables (if any) are locked.
lock_mode − The lock mode specifies which locks this lock conflicts with. If no
lock mode is specified, then ACCESS EXCLUSIVE, the most restrictive mode, is
used. Possible values are: ACCESS SHARE, ROW SHARE, ROW EXCLUSIVE, SHARE
UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS
EXCLUSIVE.
Once obtained, the lock is held for the remainder of the current transaction. There is
no UNLOCK TABLE command; locks are always released at the transaction end.

DeadLocks
Deadlocks can occur when two transactions are waiting for each other to finish their
operations. While PostgreSQL can detect them and end them with a ROLLBACK, deadlocks
can still be inconvenient. To prevent your applications from running into this problem,
make sure to design them in such a way that they will lock objects in the same order.

Advisory Locks
PostgreSQL provides means for creating locks that have application-defined meanings.
These are called advisory locks. As the system does not enforce their use, it is up to the
application to use them correctly. Advisory locks can be useful for locking strategies that
are an awkward fit for the MVCC model.
For example, a common use of advisory locks is to emulate pessimistic locking strategies
typical of the so-called "flat file" data management systems. While a flag stored in a table
could be used for the same purpose, advisory locks are faster, avoid table bloat, and are
automatically cleaned up by the server at the end of the session.

Example
Consider the table COMPANY

having records as follows −

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

The following example locks the COMPANY table within the testdb database in ACCESS
EXCLUSIVE mode. The LOCK statement works only in a transaction mode −
testdb=#BEGIN;
LOCK TABLE company1 IN ACCESS EXCLUSIVE MODE;

The above given PostgreSQL statement will produce the following result −
LOCK TABLE

The above message indicates that the table is locked until the transaction ends and to
finish the transaction you will have to either rollback or commit the transaction.

PostgreSQL - Sub Queries
A subquery or Inner query or Nested query is a query within another PostgreSQL query
and embedded within the WHERE clause.
A subquery is used to return data that will be used in the main query as a condition to
further restrict the data to be retrieved.
Subqueries can be used with the SELECT, INSERT, UPDATE and DELETE statements along
with the operators like =, <, >, >=, <=, IN, etc.
There are a few rules that subqueries must follow −
Subqueries must be enclosed within parentheses.
A subquery can have only one column in the SELECT clause, unless multiple
columns are in the main query for the subquery to compare its selected columns.
An ORDER BY cannot be used in a subquery, although the main query can use an
ORDER BY. The GROUP BY can be used to perform the same function as the ORDER
BY in a subquery.
Subqueries that return more than one row can only be used with multiple value
operators, such as the IN, EXISTS, NOT IN, ANY/SOME, ALL operator.
The BETWEEN operator cannot be used with a subquery; however, the BETWEEN
can be used within the subquery.

Subqueries with the SELECT Statement
Subqueries are most frequently used with the SELECT statement. The basic syntax is as
follows −
SELECT column_name [, column_name ]
FROM
table1 [, table2 ]
WHERE column_name OPERATOR
(SELECT column_name [, column_name ]

FROM table1 [, table2 ]
[WHERE])

Example
Consider the COMPANY

table having the following records −

id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

Now, let us check the following sub-query with SELECT statement −
testdb=# SELECT *
FROM COMPANY
WHERE ID IN (SELECT ID
FROM COMPANY
WHERE SALARY > 45000) ;

This would produce the following result −
id | name

| age |

address

| salary

----+-------+-----+-------------+-------4 | Mark

|

5 | David |

25 | Rich-Mond

|

65000

27 | Texas

|

85000

(2 rows)

Subqueries with the INSERT Statement
Subqueries also can be used with INSERT statements. The INSERT statement uses the
data returned from the subquery to insert into another table. The selected data in the
subquery can be modified with any of the character, date, or number functions.
The basic syntax is as follows −
INSERT INTO table_name [ (column1 [, column2 ]) ]
SELECT [ *|column1 [, column2 ] ]
FROM table1 [, table2 ]
[ WHERE VALUE OPERATOR ]

Example
Consider a table COMPANY_BKP, with similar structure as COMPANY table and can be
created using the same CREATE TABLE using COMPANY_BKP as the table name. Now, to

copy complete COMPANY table into COMPANY_BKP, following is the syntax −
testdb=# INSERT INTO COMPANY_BKP
SELECT * FROM COMPANY
WHERE ID IN (SELECT ID
FROM COMPANY) ;

Subqueries with the UPDATE Statement
The subquery can be used in conjunction with the UPDATE statement. Either single or
multiple columns in a table can be updated when using a subquery with the UPDATE
statement.
The basic syntax is as follows −
UPDATE table
SET column_name = new_value
[ WHERE OPERATOR [ VALUE ]
(SELECT COLUMN_NAME
FROM TABLE_NAME)
[ WHERE) ]

Example
Assuming, we have COMPANY_BKP table available, which is backup of the COMPANY table.
The following example updates SALARY by 0.50 times in the COMPANY table for all the
customers, whose AGE is greater than or equal to 27 −
testdb=# UPDATE
SET SALARY =
WHERE AGE IN
WHERE AGE

COMPANY
SALARY * 0.50
(SELECT AGE FROM COMPANY_BKP
>= 27 );

This would affect two rows and finally the COMPANY table would have the following records
−
id | name | age | address
| salary
----+-------+-----+-------------+-------2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond
| 65000
6 | Kim
| 22 | South-Hall | 45000
7 | James | 24 | Houston
| 10000
1 | Paul | 32 | California | 10000
5 | David | 27 | Texas
| 42500
(7 rows)

Subqueries with the DELETE Statement

The subquery can be used in conjunction with the DELETE statement like with any other
statements mentioned above.
The basic syntax is as follows −
DELETE FROM TABLE_NAME
[ WHERE OPERATOR [ VALUE ]
(SELECT COLUMN_NAME
FROM TABLE_NAME)
[ WHERE) ]

Example
Assuming, we have COMPANY_BKP table available, which is a backup of the COMPANY
table.
The following example deletes records from the COMPANY table for all the customers,
whose AGE is greater than or equal to 27 −
testdb=# DELETE FROM COMPANY
WHERE AGE IN (SELECT AGE FROM COMPANY_BKP
WHERE AGE > 27 );

This would affect two rows and finally the COMPANY table would have the following records
−
id | name | age | address
| salary
----+-------+-----+-------------+-------2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond
| 65000
6 | Kim
| 22 | South-Hall | 45000
7 | James | 24 | Houston
| 10000
5 | David | 27 | Texas
| 42500
(6 rows)

PostgreSQL - AUTO INCREMENT
PostgreSQL has the data types smallserial, serial and bigserial; these are not true types,
but merely a notational convenience for creating unique identifier columns. These are
similar to AUTO_INCREMENT property supported by some other databases.
If you wish a serial column to have a unique constraint or be a primary key, it must now be
specified, just like any other data type.
The type name serial creates an integer columns. The type name bigserial creates a bigint
column. bigserial should be used if you anticipate the use of more than 231 identifiers over
the lifetime of the table. The type name smallserial creates a smallint column.

Syntax
The basic usage of SERIAL dataype is as follows −
CREATE TABLE tablename (
colname SERIAL
);

Example
Consider the COMPANY table to be created as follows −
testdb=# CREATE TABLE COMPANY(
ID SERIAL PRIMARY KEY,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL
);

Now, insert the following records into table COMPANY −
INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( 'Paul', 32, 'California', 20000.00 );
INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ('Allen', 25, 'Texas', 15000.00 );
INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ('Teddy', 23, 'Norway', 20000.00 );
INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( 'Mark', 25, 'Rich-Mond ', 65000.00 );
INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( 'David', 27, 'Texas', 85000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( 'Kim', 22, 'South-Hall', 45000.00 );
INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( 'James', 24, 'Houston', 10000.00 );

This will insert seven tuples into the table COMPANY and COMPANY will have the following
records −
id | name | age | address
| salary
----+-------+-----+------------+-------1 | Paul | 32 | California | 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000

6 | Kim
|
7 | James |

22 | South-Hall |
24 | Houston
|

45000
10000

PostgreSQL - PRIVILEGES
Whenever an object is created in a database, an owner is assigned to it. The owner is
usually the one who executed the creation statement. For most kinds of objects, the initial
state is that only the owner (or a superuser) can modify or delete the object. To allow
other roles or users to use it, privileges or permission must be granted.
Different kinds of privileges in PostgreSQL are −
SELECT,
INSERT,
UPDATE,
DELETE,
TRUNCATE,
REFERENCES,
TRIGGER,
CREATE,
CONNECT,
TEMPORARY,
EXECUTE, and
USAGE

Depending on the type of the object (table, function, etc.,), privileges are applied to the
object. To assign privileges to the users, the GRANT command is used.

Syntax for GRANT
Basic syntax for GRANT command is as follows −
GRANT privilege [, ...]
ON object [, ...]
TO { PUBLIC | GROUP group | username }

privilege − values could be: SELECT, INSERT, UPDATE, DELETE, RULE, ALL.
object − The name of an object to which to grant access. The possible objects
are: table, view, sequence
PUBLIC − A short form representing all users.
GROUP group − A group to whom to grant privileges.

username − The name of a user to whom to grant privileges. PUBLIC is a short
form representing all users.
The privileges can be revoked using the REVOKE command.

Syntax for REVOKE
Basic syntax for REVOKE command is as follows −
REVOKE privilege [, ...]
ON object [, ...]
FROM { PUBLIC | GROUP groupname | username }

privilege − values could be: SELECT, INSERT, UPDATE, DELETE, RULE, ALL.
object − The name of an object to which to grant access. The possible objects
are: table, view, sequence
PUBLIC − A short form representing all users.
GROUP group − A group to whom to grant privileges.
username − The name of a user to whom to grant privileges. PUBLIC is a short
form representing all users.

Example
To understand the privileges, let us first create a USER as follows −
testdb=# CREATE USER manisha WITH PASSWORD 'password';
CREATE ROLE

The message CREATE ROLE indicates that the USER "manisha" is created.
Consider the table COMPANY

having records as follows −

testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

Next, let us grant all privileges on a table COMPANY to the user "manisha" as follows −

testdb=# GRANT ALL ON COMPANY TO manisha;
GRANT

The message GRANT indicates that all privileges are assigned to the USER.
Next, let us revoke the privileges from the USER "manisha" as follows −
testdb=# REVOKE ALL ON COMPANY FROM manisha;
REVOKE

The message REVOKE indicates that all privileges are revoked from the USER.
You can even delete the user as follows −
testdb=# DROP USER manisha;
DROP ROLE

The message DROP ROLE indicates USER ‘Manisha’ is deleted from the database.

PostgreSQL - DATE/TIME Functions and
Operators
We had discussed about the Date/Time data types in the chapter Data Types

. Now, let

us see the Date/Time operators and Functions.
The following table lists the behaviors of the basic arithmetic operators −
Operator

Example

Result

+

date '2001-09-28' + integer '7'

date '2001-10-05'

+

date '2001-09-28' + interval '1 hour'

timestamp '2001-09-28 01:00:00'

+

date '2001-09-28' + time '03:00'

timestamp '2001-09-28 03:00:00'

+

interval '1 day' + interval '1 hour'

interval '1 day 01:00:00'

+

timestamp '2001-09-28 01:00' + interval '23
hours'

timestamp '2001-09-29 00:00:00'

+

time '01:00' + interval '3 hours'

time '04:00:00'

-

- interval '23 hours'

interval '-23:00:00'

-

date '2001-10-01' - date '2001-09-28'

integer '3' (days)

-

date '2001-10-01' - integer '7'

date '2001-09-24'

-

date '2001-09-28' - interval '1 hour'

timestamp '2001-09-27 23:00:00'

-

time '05:00' - time '03:00'

interval '02:00:00'

-

time '05:00' - interval '2 hours'

time '03:00:00'

-

timestamp '2001-09-28 23:00' - interval '23
hours'

timestamp '2001-09-28 00:00:00'

-

interval '1 day' - interval '1 hour'

interval '1 day -01:00:00'

-

timestamp '2001-09-29 03:00' - timestamp
'2001-09-27 12:00'

interval '1 day 15:00:00'

*

900 * interval '1 second'

interval '00:15:00'

*

21 * interval '1 day'

interval '21 days'

*

double precision '3.5' * interval '1 hour'

interval '03:30:00'

/

interval '1 hour' / double precision '1.5'

interval '00:40:00'

The following is the list of all important Date and Time related functions available.
S. No.

1

2

3

4

5

6

Function & Description
AGE()

Subtract arguments
CURRENT DATE/TIME()

Current date and time
DATE_PART()

Get subfield (equivalent to extract)
EXTRACT()

Get subfield
ISFINITE()

Test for finite date, time and interval (not +/-infinity)
JUSTIFY

Adjust interval

AGE(timestamp, timestamp), AGE(timestamp)
S. No.
1

Function & Description

AGE(timestamp, timestamp)
When invoked with the TIMESTAMP form of the second argument, AGE()
subtract arguments, producing a "symbolic" result that uses years and months
and is of type INTERVAL.
AGE(timestamp)
2

When invoked with only the TIMESTAMP as argument, AGE() subtracts from
the current_date (at midnight).

Example of the function AGE(timestamp, timestamp) is −
testdb=# SELECT AGE(timestamp '2001-04-10', timestamp '1957-06-13');

The above given PostgreSQL statement will produce the following result −
age
------------------------43 years 9 mons 27 days

Example of the function AGE(timestamp) is −
testdb=# select age(timestamp '1957-06-13');

The above given PostgreSQL statement will produce the following result −
age
-------------------------55 years 10 mons 22 days

CURRENT DATE/TIME()
PostgreSQL provides a number of functions that return values related to the current date
and time. Following are some functions −
S. No.

Function & Description

CURRENT_DATE
1

Delivers current date.
CURRENT_TIME

2

3

Delivers values with time zone.
CURRENT_TIMESTAMP

Delivers values with time zone.
CURRENT_TIME(precision)
4

Optionally takes a precision parameter, which causes the result to be rounded
to that many fractional digits in the seconds field.
CURRENT_TIMESTAMP(precision)

5

Optionally takes a precision parameter, which causes the result to be rounded
to that many fractional digits in the seconds field.
LOCALTIME

6

Delivers values without time zone.
LOCALTIMESTAMP

7

Delivers values without time zone.
LOCALTIME(precision)

8

Optionally takes a precision parameter, which causes the result to be rounded
to that many fractional digits in the seconds field.
LOCALTIMESTAMP(precision)

9

Optionally takes a precision parameter, which causes the result to be rounded
to that many fractional digits in the seconds field.

Examples using the functions from the table above −
testdb=# SELECT CURRENT_TIME;
timetz
-------------------08:01:34.656+05:30
(1 row)

testdb=# SELECT CURRENT_DATE;
date
-----------2013-05-05
(1 row)

testdb=# SELECT CURRENT_TIMESTAMP;
now
-------------------------------

2013-05-05 08:01:45.375+05:30
(1 row)

testdb=# SELECT CURRENT_TIMESTAMP(2);
timestamptz
-----------------------------2013-05-05 08:01:50.89+05:30
(1 row)

testdb=# SELECT LOCALTIMESTAMP;
timestamp
-----------------------2013-05-05 08:01:55.75
(1 row)

PostgreSQL also provides functions that return the start time of the current statement, as
well as the actual current time at the instant the function is called. These functions are −
S. No.

Function & Description

transaction_timestamp()
1

It is equivalent to CURRENT_TIMESTAMP, but is named to clearly reflect what
it returns.
statement_timestamp()

2

It returns the start time of the current statement.
clock_timestamp()

3

It returns the actual current time, and therefore its value changes even within
a single SQL command.
timeofday()

4

It returns the actual current time, but as a formatted text string rather than a
timestamp with time zone value.
now()

5

It is a traditional PostgreSQL equivalent to transaction_timestamp().

DATE_PART(text, timestamp), DATE_PART(text,
interval), DATE_TRUNC(text, timestamp)

S. No.

Function & Description

DATE_PART('field', source)
These functions get the subfields. The field parameter needs to be a string
1

value, not a name.
The valid field names are: century, day, decade, dow, doy, epoch, hour,
isodow, isoyear, microseconds, millennium, milliseconds, minute, month,
quarter, second, timezone, timezone_hour, timezone_minute, week, year.
DATE_TRUNC('field', source)
This function is conceptually similar to the trunc function for numbers. source
is a value expression of type timestamp or interval. field selects to which

2

precision to truncate the input value. The return value is of type timestamp or
interval.
The valid values for field are : microseconds, milliseconds, second, minute,
hour, day, week, month, quarter, year, decade, century, millennium

The following are examples for DATE_PART('field', source) functions −
testdb=# SELECT date_part('day', TIMESTAMP '2001-02-16 20:38:40');
date_part
----------16
(1 row)

testdb=# SELECT date_part('hour', INTERVAL '4 hours 3 minutes');
date_part
----------4
(1 row)

The following are examples for DATE_TRUNC('field', source) functions −
testdb=# SELECT date_trunc('hour', TIMESTAMP '2001-02-16 20:38:40');
date_trunc
--------------------2001-02-16 20:00:00
(1 row)

testdb=# SELECT date_trunc('year', TIMESTAMP '2001-02-16 20:38:40');
date_trunc
--------------------2001-01-01 00:00:00
(1 row)

EXTRACT(field from timestamp), EXTRACT(field from
interval)
The EXTRACT(field FROM source) function retrieves subfields such as year or hour from
date/time values. The source must be a value expression of type timestamp, time, or
interval. The field is an identifier or string that selects what field to extract from the source
value. The EXTRACT function returns values of type double precision.
The following are valid field names (similar to DATE_PART function field names): century,
day,

decade,

dow,

doy,

epoch,

hour,

isodow,

isoyear,

microseconds,

millennium,

milliseconds, minute, month, quarter, second, timezone, timezone_hour, timezone_minute,
week, year.
The following are examples of EXTRACT('field', source) functions −
testdb=# SELECT EXTRACT(CENTURY FROM TIMESTAMP '2000-12-16 12:21:13');
date_part
----------20
(1 row)

testdb=# SELECT EXTRACT(DAY FROM TIMESTAMP '2001-02-16 20:38:40');
date_part
----------16
(1 row)

ISFINITE(date), ISFINITE(timestamp),
ISFINITE(interval)
S. No.

Function & Description

ISFINITE(date)
1

Tests for finite date.
ISFINITE(timestamp)

2

Tests for finite time stamp.
ISFINITE(interval)

3

Tests for finite interval.

The following are the examples of the ISFINITE() functions −

testdb=# SELECT isfinite(date '2001-02-16');
isfinite
---------t
(1 row)

testdb=# SELECT isfinite(timestamp '2001-02-16 21:28:30');
isfinite
---------t
(1 row)

testdb=# SELECT isfinite(interval '4 hours');
isfinite
---------t
(1 row)

JUSTIFY_DAYS(interval), JUSTIFY_HOURS(interval),
JUSTIFY_INTERVAL(interval)
S. No.

Function & Description

JUSTIFY_DAYS(interval)
1

Adjusts interval so 30-day time periods are represented as months. Return the
interval type
JUSTIFY_HOURS(interval)

2

Adjusts interval so 24-hour time periods are represented as days. Return the
interval type
JUSTIFY_INTERVAL(interval)

3

Adjusts interval using JUSTIFY_DAYS and JUSTIFY_HOURS, with additional
sign adjustments. Return the interval type

The following are the examples for the ISFINITE() functions −
testdb=# SELECT justify_days(interval '35 days');
justify_days
-------------1 mon 5 days
(1 row)

testdb=# SELECT justify_hours(interval '27 hours');

justify_hours
---------------1 day 03:00:00
(1 row)

testdb=# SELECT justify_interval(interval '1 mon -1 hour');
justify_interval
-----------------29 days 23:00:00
(1 row)

PostgreSQL - Functions
PostgreSQL functions, also known as Stored Procedures, allow you to carry out operations
that would normally take several queries and round trips in a single function within the
database. Functions allow database reuse as other applications can interact directly with
your stored procedures instead of a middle-tier or duplicating code.
Functions can be created in a language of your choice like SQL, PL/pgSQL, C, Python, etc.

Syntax
The basic syntax to create a function is as follows −
CREATE [OR REPLACE] FUNCTION function_name (arguments)
RETURNS return_datatype AS $variable_name$
DECLARE
declaration;
[...]
BEGIN
< function_body >
[...]
RETURN { variable_name | value }
END; LANGUAGE plpgsql;

Where,
function-name specifies the name of the function.
[OR REPLACE] option allows modifying an existing function.
The function must contain a return statement.
RETURN clause specifies that data type you are going to return from the function.
The return_datatype can be a base, composite, or domain type, or can reference
the type of a table column.
function-body contains the executable part.
The AS keyword is used for creating a standalone function.

plpgsql is the name of the language that the function is implemented in. Here, we
use this option for PostgreSQL, it Can be SQL, C, internal, or the name of a userdefined procedural language. For backward compatibility, the name can be
enclosed by single quotes.

Example
The following example illustrates creating and calling a standalone function. This function
returns the total number of records in the COMPANY table. We will use the COMPANY
table, which has the following records −
testdb# select * from COMPANY;
id | name | age | address
| salary
----+-------+-----+-----------+-------1 | Paul | 32 | California| 20000
2 | Allen | 25 | Texas
| 15000
3 | Teddy | 23 | Norway
| 20000
4 | Mark | 25 | Rich-Mond | 65000
5 | David | 27 | Texas
| 85000
6 | Kim
| 22 | South-Hall| 45000
7 | James | 24 | Houston
| 10000
(7 rows)

Function totalRecords() is as follows −
CREATE OR REPLACE FUNCTION totalRecords ()
RETURNS integer AS $total$
declare
total integer;
BEGIN
SELECT count(*) into total FROM COMPANY;
RETURN total;
END;
$total$ LANGUAGE plpgsql;

When the above query is executed, the result would be −
testdb# CREATE FUNCTION

Now, let us execute a call to this function and check the records in the COMPANY table
testdb=# select totalRecords();

When the above query is executed, the result would be −
totalrecords
-------------7
(1 row)

PostgreSQL - Useful Functions

PostgreSQL built-in functions, also called as Aggregate functions, are used for performing
processing on string or numeric data.
The following is the list of all general-purpose PostgreSQL built-in functions −
PostgreSQL COUNT Function

− The PostgreSQL COUNT aggregate function is

used to count the number of rows in a database table.
PostgreSQL MAX Function

− The PostgreSQL MAX aggregate function allows us

to select the highest (maximum) value for a certain column.
PostgreSQL MIN Function

− The PostgreSQL MIN aggregate function allows us

to select the lowest (minimum) value for a certain column.
PostgreSQL AVG Function

− The PostgreSQL AVG aggregate function selects the

average value for certain table column.
PostgreSQL SUM Function

− The PostgreSQL SUM aggregate function allows

selecting the total for a numeric column.
PostgreSQL ARRAY Functions

− The PostgreSQL ARRAY aggregate function puts

input values, including nulls, concatenated into an array.
PostgreSQL Numeric Functions

− Complete list of PostgreSQL functions required

to manipulate numbers in SQL.
PostgreSQL String Functions

− Complete list of PostgreSQL functions required to

manipulate strings in PostgreSQL.

PostgreSQL - C/C++ Interface
This tutorial is going to use libpqxx library, which is the official C++ client API for
PostgreSQL. The source code for libpqxx is available under the BSD license, so you are free
to download it, pass it on to others, change it, sell it, include it in your own code, and
share your changes with anyone you choose.

Installation
The the latest version of libpqxx is available to be downloaded from the link Download
Libpqxx

. So download the latest version and follow the following steps −

wget http://pqxx.org/download/software/libpqxx/libpqxx-4.0.tar.gz
tar xvfz libpqxx-4.0.tar.gz
cd libpqxx-4.0
./configure
make
make install

Before you start using C/C++ PostgreSQL interface, find the pg_hba.conf file in your
PostgreSQL installation directory and add the following line −
# IPv4 local connections:
host
all
all

127.0.0.1/32

md5

You can start/restart postgres server in case it is not running using the following command
−
[root@host]# service postgresql restart
Stopping postgresql service:
Starting postgresql service:

[
[

OK
OK

]
]

C/C++ Interface APIs
The following are important interface routines which can sufice your requirement to work
with PostgreSQL database from your C/C++ program. If you are looking for a more
sophisticated application then you can look into the libpqxx official documentation, or you
can use commercially available APIs.
S. No.

API & Description

pqxx::connection C( const std::string & dbstring )
This is a typedef which will be used to connect to the database. Here, dbstring
provides required parameters to connect to the datbase, for example dbname
1

= testdb user = postgres password=pass123 hostaddr=127.0.0.1
port=5432.
If connection is setup successfully then it creates C with connection object
which provides various useful function public function.
C.is_open()

2

The method is_open() is a public method of connection object and returns
boolean value. If connection is active, then this method returns true otherwise
it returns false.
C.disconnect()

3

4

This method is used to disconnect an opened database connection.
pqxx::work W( C )
This is a typedef which will be used to create a transactional object using
connection C, which ultimately will be used to execute SQL statements in

transactional mode.
If transaction object gets created successfully, then it is assigned to variable W
which will be used to access public methods related to transactional object.
W.exec(const std::string & sql)
5

This public method from transactional object will be used to execute SQL
statement.
W.commit()

6

This public method from transactional object will be used to commit the
transaction.
W.abort()

7

This public method from transactional object will be used to rollback the
transaction.
pqxx::nontransaction N( C )
This is a typedef which will be used to create a non-transactional object using
connection C, which ultimately will be used to execute SQL statements in non-

8

transactional mode.
If transaction object gets created successfully, then it is assigned to variable N
which will be used to access public methods related to non-transactional
object.
N.exec(const std::string & sql)

9

This public method from non-transactional object will be used to execute SQL
statement and returns a result object which is actually an interator holding all
the returned records.

Connecting To Database
The following C code segment shows how to connect to an existing database running on
local machine at port 5432. Here, I used backslash \ for line continuation.
#include 
#include 
using namespace std;

using namespace pqxx;
int main(int argc, char* argv[]) {
try {
connection C("dbname = testdb user = postgres password = cohondob \
hostaddr = 127.0.0.1 port = 5432");
if (C.is_open()) {
cout << "Opened database successfully: " << C.dbname() << endl;
} else {
cout << "Can't open database" << endl;
return 1;
}
C.disconnect ();
} catch (const std::exception &e) {
cerr << e.what() << std::endl;
return 1;
}
}

Now, let us compile and run the above program to connect to our database testdb, which
is already available in your schema and can be accessed using user postgres and password
pass123.
You can use the user ID and password based on your database setting. Remember to keep
the -lpqxx and -lpq in the given order! Otherwise, the linker will complain bitterly about
the missing functions with names starting with "PQ."
$g++ test.cpp -lpqxx -lpq
$./a.out
Opened database successfully: testdb

Create a Table
The following C code segment will be used to create a table in previously created database
−
#include 
#include 
using namespace std;
using namespace pqxx;
int main(int argc, char* argv[]) {
char * sql;
try {
connection C("dbname = testdb user = postgres password = cohondob \
hostaddr = 127.0.0.1 port = 5432");
if (C.is_open()) {
cout << "Opened database successfully: " << C.dbname() << endl;
} else {
cout << "Can't open database" << endl;
return 1;
}

/* Create SQL statement */
sql = "CREATE TABLE COMPANY(" \
"ID INT PRIMARY KEY
NOT NULL," \
"NAME
TEXT
NOT NULL," \
"AGE
INT
NOT NULL," \
"ADDRESS
CHAR(50)," \
"SALARY
REAL );";
/* Create a transactional object. */
work W(C);
/* Execute SQL query */
W.exec( sql );
W.commit();
cout << "Table created successfully" << endl;
C.disconnect ();
} catch (const std::exception &e) {
cerr << e.what() << std::endl;
return 1;
}
return 0;
}

When the above given program is compiled and executed, it will create COMPANY table in
your testdb database and will display the following statements −
Opened database successfully: testdb
Table created successfully

INSERT Operation
The following C code segment shows how we can create records in our COMPANY table
created in above example −
#include 
#include 
using namespace std;
using namespace pqxx;
int main(int argc, char* argv[]) {
char * sql;
try {
connection C("dbname = testdb user = postgres password = cohondob \
hostaddr = 127.0.0.1 port = 5432");
if (C.is_open()) {
cout << "Opened database successfully: " << C.dbname() << endl;
} else {
cout << "Can't open database" << endl;
return 1;
}
/* Create SQL statement */
sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "
"VALUES (1, 'Paul', 32, 'California', 20000.00 ); " \

\

"INSERT
"VALUES
"INSERT
"VALUES
"INSERT
"VALUES

INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) " \
(2, 'Allen', 25, 'Texas', 15000.00 ); "
\
INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)" \
(3, 'Teddy', 23, 'Norway', 20000.00 );" \
INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)" \
(4, 'Mark', 25, 'Rich-Mond ', 65000.00 );";

/* Create a transactional object. */
work W(C);
/* Execute SQL query */
W.exec( sql );
W.commit();
cout << "Records created successfully" << endl;
C.disconnect ();
} catch (const std::exception &e) {
cerr << e.what() << std::endl;
return 1;
}
return 0;
}

When the above given program is compiled and executed, it will create given records in
COMPANY table and will display the following two lines −
Opened database successfully: testdb
Records created successfully

SELECT Operation
The following C code segment shows how we can fetch and display records from our
COMPANY table created in above example −
#include 
#include 
using namespace std;
using namespace pqxx;
int main(int argc, char* argv[]) {
char * sql;
try {
connection C("dbname = testdb user = postgres password = cohondob \
hostaddr = 127.0.0.1 port = 5432");
if (C.is_open()) {
cout << "Opened database successfully: " << C.dbname() << endl;
} else {
cout << "Can't open database" << endl;
return 1;
}
/* Create SQL statement */
sql = "SELECT * from COMPANY";
/* Create a non-transactional object. */

nontransaction N(C);
/* Execute SQL query */
result R( N.exec( sql ));
/* List down all the records */
for (result::const_iterator c = R.begin(); c != R.end(); ++c) {
cout << "ID = " << c[0].as() << endl;
cout << "Name = " << c[1].as() << endl;
cout << "Age = " << c[2].as() << endl;
cout << "Address = " << c[3].as() << endl;
cout << "Salary = " << c[4].as() << endl;
}
cout << "Operation done successfully" << endl;
C.disconnect ();
} catch (const std::exception &e) {
cerr << e.what() << std::endl;
return 1;
}
return 0;
}

When the above given program is compiled and executed, it will produce the following
result −
Opened database successfully: testdb
ID = 1
Name = Paul
Age = 32
Address = California
Salary = 20000
ID = 2
Name = Allen
Age = 25
Address = Texas
Salary = 15000
ID = 3
Name = Teddy
Age = 23
Address = Norway
Salary = 20000
ID = 4
Name = Mark
Age = 25
Address = Rich-Mond
Salary = 65000
Operation done successfully

UPDATE Operation

The following C code segment shows how we can use the UPDATE statement to update any
record and then fetch and display updated records from our COMPANY table −
#include 
#include 
using namespace std;
using namespace pqxx;
int main(int argc, char* argv[]) {
char * sql;
try {
connection C("dbname = testdb user = postgres password = cohondob \
hostaddr = 127.0.0.1 port = 5432");
if (C.is_open()) {
cout << "Opened database successfully: " << C.dbname() << endl;
} else {
cout << "Can't open database" << endl;
return 1;
}
/* Create a transactional object. */
work W(C);
/* Create SQL UPDATE statement */
sql = "UPDATE COMPANY set SALARY = 25000.00 where ID=1";
/* Execute SQL query */
W.exec( sql );
W.commit();
cout << "Records updated successfully" << endl;
/* Create SQL SELECT statement */
sql = "SELECT * from COMPANY";
/* Create a non-transactional object. */
nontransaction N(C);
/* Execute SQL query */
result R( N.exec( sql ));
/* List down all the records */
for (result::const_iterator c = R.begin(); c != R.end(); ++c) {
cout << "ID = " << c[0].as() << endl;
cout << "Name = " << c[1].as() << endl;
cout << "Age = " << c[2].as() << endl;
cout << "Address = " << c[3].as() << endl;
cout << "Salary = " << c[4].as() << endl;
}
cout << "Operation done successfully" << endl;
C.disconnect ();
} catch (const std::exception &e) {
cerr << e.what() << std::endl;
return 1;
}
return 0;
}

When the above given program is compiled and executed, it will produce the following
result −
Opened database successfully: testdb
Records updated successfully
ID = 2
Name = Allen
Age = 25
Address = Texas
Salary = 15000
ID = 3
Name = Teddy
Age = 23
Address = Norway
Salary = 20000
ID = 4
Name = Mark
Age = 25
Address = Rich-Mond
Salary = 65000
ID = 1
Name = Paul
Age = 32
Address = California
Salary = 25000
Operation done successfully

DELETE Operation
The following C code segment shows how we can use the DELETE statement to delete any
record and then fetch and display remaining records from our COMPANY table −
#include 
#include 
using namespace std;
using namespace pqxx;
int main(int argc, char* argv[]) {
char * sql;
try {
connection C("dbname = testdb user = postgres password = cohondob \
hostaddr = 127.0.0.1 port = 5432");
if (C.is_open()) {
cout << "Opened database successfully: " << C.dbname() << endl;
} else {
cout << "Can't open database" << endl;
return 1;

}
/* Create a transactional object. */
work W(C);
/* Create SQL DELETE statement */
sql = "DELETE from COMPANY where ID = 2";
/* Execute SQL query */
W.exec( sql );
W.commit();
cout << "Records deleted successfully" << endl;
/* Create SQL SELECT statement */
sql = "SELECT * from COMPANY";
/* Create a non-transactional object. */
nontransaction N(C);
/* Execute SQL query */
result R( N.exec( sql ));
/* List down all the records */
for (result::const_iterator c = R.begin(); c != R.end(); ++c) {
cout << "ID = " << c[0].as() << endl;
cout << "Name = " << c[1].as() << endl;
cout << "Age = " << c[2].as() << endl;
cout << "Address = " << c[3].as() << endl;
cout << "Salary = " << c[4].as() << endl;
}
cout << "Operation done successfully" << endl;
C.disconnect ();
} catch (const std::exception &e) {
cerr << e.what() << std::endl;
return 1;
}
return 0;
}

When the above given program is compiled and executed, it will produce the following
result −
Opened database successfully: testdb
Records deleted successfully
ID = 3
Name = Teddy
Age = 23
Address = Norway
Salary = 20000
ID = 4
Name = Mark
Age = 25
Address = Rich-Mond
Salary = 65000
ID = 1
Name = Paul

Age = 32
Address = California
Salary = 25000
Operation done successfully

PostgreSQL - JAVA Interface
Installation
Before we start using PostgreSQL in our Java programs, we need to make sure that we
have PostgreSQL JDBC and Java set up on the machine. You can check Java tutorial for
Java installation on your machine. Now let us check how to set up PostgreSQL JDBC driver.
Download the latest version of postgresql-(VERSION).jdbc.jar from postgresqljdbc

repository.

Add downloaded jar file postgresql-(VERSION).jdbc.jar in your class path, or you
can use it along with -classpath option as explained below in the examples.
The following section assumes you have little knowledge about Java JDBC concepts. If you
do not have, then it is suggested to spent half and hour with JDBC Tutorial

to become

comfortable with concepts explained below.

Connecting To Database
The following Java code shows how to connect to an existing database. If the database
does not exist, then it will be created and finally a database object will be returned.
import java.sql.Connection;
import java.sql.DriverManager;
public class PostgreSQLJDBC {
public static void main(String args[]) {
Connection c = null;
try {
Class.forName("org.postgresql.Driver");
c = DriverManager
.getConnection("jdbc:postgresql://localhost:5432/testdb",
"postgres", "123");
} catch (Exception e) {
e.printStackTrace();
System.err.println(e.getClass().getName()+": "+e.getMessage());
System.exit(0);
}
System.out.println("Opened database successfully");
}
}

Before you compile and run above program, find pg_hba.conf file in your PostgreSQL
installation directory and add the following line −

# IPv4 local connections:
host
all
all

127.0.0.1/32

md5

You can start/restart the postgres server in case it is not running using the following
command −
[root@host]# service postgresql restart
Stopping postgresql service:
Starting postgresql service:

[
[

OK
OK

]
]

Now, let us compile and run the above program to connect with testdb. Here, we are using
postgres as user ID and 123 as password to access the database. You can change this as
per your database configuration and setup. We are also assuming current version of JDBC
driver postgresql-9.2-1002.jdbc3.jar is available in the current path.
C:\JavaPostgresIntegration>javac PostgreSQLJDBC.java
C:\JavaPostgresIntegration>java -cp c:\tools\postgresql-9.2-1002.jdbc3.jar;C:\JavaPostgresIntegra
Open database successfully

Create a Table
The following Java program will be used to create a table in previously opened database.
Make sure you do not have this table already in your target database.
import java.sql.*;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.Statement;

public class PostgreSQLJDBC {
public static void main( String args[] ) {
Connection c = null;
Statement stmt = null;
try {
Class.forName("org.postgresql.Driver");
c = DriverManager
.getConnection("jdbc:postgresql://localhost:5432/testdb",
"manisha", "123");
System.out.println("Opened database successfully");
stmt = c.createStatement();
String sql = "CREATE TABLE COMPANY " +
"(ID INT PRIMARY KEY
NOT NULL," +
" NAME
TEXT
NOT NULL, " +
" AGE
INT
NOT NULL, " +
" ADDRESS
CHAR(50), " +
" SALARY
REAL)";
stmt.executeUpdate(sql);
stmt.close();
c.close();
} catch ( Exception e ) {

System.err.println( e.getClass().getName()+": "+ e.getMessage() );
System.exit(0);
}
System.out.println("Table created successfully");
}
}

When a program is compiled and executed, it will create the COMPANY table in testdb
database and will display the following two lines −
Opened database successfully
Table created successfully

INSERT Operation
The following Java program shows how we can create records in our COMPANY table
created in above example −
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.Statement;
public class PostgreSQLJDBC {
public static void main(String args[]) {
Connection c = null;
Statement stmt = null;
try {
Class.forName("org.postgresql.Driver");
c = DriverManager
.getConnection("jdbc:postgresql://localhost:5432/testdb",
"manisha", "123");
c.setAutoCommit(false);
System.out.println("Opened database successfully");
stmt = c.createStatement();
String sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "
+ "VALUES (1, 'Paul', 32, 'California', 20000.00 );";
stmt.executeUpdate(sql);
sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "
+ "VALUES (2, 'Allen', 25, 'Texas', 15000.00 );";
stmt.executeUpdate(sql);
sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "
+ "VALUES (3, 'Teddy', 23, 'Norway', 20000.00 );";
stmt.executeUpdate(sql);
sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "
+ "VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 );";
stmt.executeUpdate(sql);
stmt.close();
c.commit();
c.close();
} catch (Exception e) {
System.err.println( e.getClass().getName()+": "+ e.getMessage() );
System.exit(0);

}
System.out.println("Records created successfully");
}
}

When the above program is compiled and executed, it will create given records in
COMPANY table and will display the following two lines −
Opened database successfully
Records created successfully

SELECT Operation
The following Java program shows how we can fetch and display records from our
COMPANY table created in above example −
import
import
import
import

java.sql.Connection;
java.sql.DriverManager;
java.sql.ResultSet;
java.sql.Statement;

public class PostgreSQLJDBC {
public static void main( String args[] ) {
Connection c = null;
Statement stmt = null;
try {
Class.forName("org.postgresql.Driver");
c = DriverManager
.getConnection("jdbc:postgresql://localhost:5432/testdb",
"manisha", "123");
c.setAutoCommit(false);
System.out.println("Opened database successfully");
stmt = c.createStatement();
ResultSet rs = stmt.executeQuery( "SELECT * FROM COMPANY;" );
while ( rs.next() ) {
int id = rs.getInt("id");
String name = rs.getString("name");
int age = rs.getInt("age");
String address = rs.getString("address");
float salary = rs.getFloat("salary");
System.out.println( "ID = " + id );
System.out.println( "NAME = " + name );
System.out.println( "AGE = " + age );
System.out.println( "ADDRESS = " + address );
System.out.println( "SALARY = " + salary );
System.out.println();
}
rs.close();
stmt.close();
c.close();
} catch ( Exception e ) {
System.err.println( e.getClass().getName()+": "+ e.getMessage() );
System.exit(0);
}
System.out.println("Operation done successfully");

}
}

When the program is compiled and executed, it will produce the following result −
Opened database successfully
ID = 1
NAME = Paul
AGE = 32
ADDRESS = California
SALARY = 20000.0
ID = 2
NAME = Allen
AGE = 25
ADDRESS = Texas
SALARY = 15000.0
ID = 3
NAME = Teddy
AGE = 23
ADDRESS = Norway
SALARY = 20000.0
ID = 4
NAME = Mark
AGE = 25
ADDRESS = Rich-Mond
SALARY = 65000.0
Operation done successfully

UPDATE Operation
The following Java code shows how we can use the UPDATE statement to update any
record and then fetch and display updated records from our COMPANY table −
import
import
import
import

java.sql.Connection;
java.sql.DriverManager;
java.sql.ResultSet;
java.sql.Statement;

public class PostgreSQLJDBC {
public static void main( String args[] ) {
Connection c = null;
Statement stmt = null;
try {

Class.forName("org.postgresql.Driver");
c = DriverManager
.getConnection("jdbc:postgresql://localhost:5432/testdb",
"manisha", "123");
c.setAutoCommit(false);
System.out.println("Opened database successfully");
stmt = c.createStatement();
String sql = "UPDATE COMPANY set SALARY = 25000.00 where ID=1;";
stmt.executeUpdate(sql);
c.commit();
ResultSet rs = stmt.executeQuery( "SELECT * FROM COMPANY;" );
while ( rs.next() ) {
int id = rs.getInt("id");
String name = rs.getString("name");
int age = rs.getInt("age");
String address = rs.getString("address");
float salary = rs.getFloat("salary");
System.out.println( "ID = " + id );
System.out.println( "NAME = " + name );
System.out.println( "AGE = " + age );
System.out.println( "ADDRESS = " + address );
System.out.println( "SALARY = " + salary );
System.out.println();
}
rs.close();
stmt.close();
c.close();
} catch ( Exception e ) {
System.err.println( e.getClass().getName()+": "+ e.getMessage() );
System.exit(0);
}
System.out.println("Operation done successfully");
}
}

When the program is compiled and executed, it will produce the following result −
Opened database successfully
ID = 2
NAME = Allen
AGE = 25
ADDRESS = Texas
SALARY = 15000.0
ID = 3
NAME = Teddy
AGE = 23
ADDRESS = Norway
SALARY = 20000.0
ID = 4
NAME = Mark

AGE = 25
ADDRESS = Rich-Mond
SALARY = 65000.0
ID = 1
NAME = Paul
AGE = 32
ADDRESS = California
SALARY = 25000.0
Operation done successfully

DELETE Operation
The following Java code shows how we can use the DELETE statement to delete any record
and then fetch and display remaining records from our COMPANY table −
import
import
import
import

java.sql.Connection;
java.sql.DriverManager;
java.sql.ResultSet;
java.sql.Statement;

public class PostgreSQLJDBC6 {
public static void main( String args[] ) {
Connection c = null;
Statement stmt = null;
try {
Class.forName("org.postgresql.Driver");
c = DriverManager
.getConnection("jdbc:postgresql://localhost:5432/testdb",
"manisha", "123");
c.setAutoCommit(false);
System.out.println("Opened database successfully");
stmt = c.createStatement();
String sql = "DELETE from COMPANY where ID = 2;";
stmt.executeUpdate(sql);
c.commit();
ResultSet rs = stmt.executeQuery( "SELECT * FROM COMPANY;" );
while ( rs.next() ) {
int id = rs.getInt("id");
String name = rs.getString("name");
int age = rs.getInt("age");
String address = rs.getString("address");
float salary = rs.getFloat("salary");
System.out.println( "ID = " + id );
System.out.println( "NAME = " + name );
System.out.println( "AGE = " + age );
System.out.println( "ADDRESS = " + address );
System.out.println( "SALARY = " + salary );
System.out.println();
}

rs.close();
stmt.close();
c.close();
} catch ( Exception e ) {
System.err.println( e.getClass().getName()+": "+ e.getMessage() );
System.exit(0);
}
System.out.println("Operation done successfully");
}
}

When the program is compiled and executed, it will produce the following result −
Opened database successfully
ID = 3
NAME = Teddy
AGE = 23
ADDRESS = Norway
SALARY = 20000.0
ID = 4
NAME = Mark
AGE = 25
ADDRESS = Rich-Mond
SALARY = 65000.0
ID = 1
NAME = Paul
AGE = 32
ADDRESS = California
SALARY = 25000.0
Operation done successfully

PostgreSQL - PHP Interface
Installation
The PostgreSQL extension is enabled by default in the latest releases of PHP 5.3.x. It is
possible to disable it by using --without-pgsql at compile time. Still you can use yum
command to install PHP -PostgreSQL interface −
yum install php-pgsql

Before you start using the PHP PostgreSQL interface, find the pg_hba.conf file in your
PostgreSQL installation directory and add the following line −
# IPv4 local connections:
host
all
all

127.0.0.1/32

md5

You can start/restart the postgres server, in case it is not running, using the following
command −
[root@host]# service postgresql restart
Stopping postgresql service:
Starting postgresql service:

[
[

OK
OK

]
]

Windows users must enable php_pgsql.dll in order to use this extension. This DLL is
included with Windows distributions in the latest releases of PHP 5.3.x
For detailed installation instructions, kindly check our PHP tutorial and its official website.

PHP Interface APIs
The following are important PHP routines, which can suffice your requirement to work with
PostgreSQL database from your PHP program. If you are looking for a more sophisticated
application, then you can look into the PHP official documentation.
S. No.

API & Description

resource pg_connect ( string $connection_string [, int $connect_type
])
This opens a connection to a PostgreSQL database specified by the
1

connection_string.
If PGSQL_CONNECT_FORCE_NEW is passed as connect_type, then a new
connection is created in case of a second call to pg_connect(), even if the
connection_string is identical to an existing connection.
bool pg_connection_reset ( resource $connection )

2

This routine resets the connection. It is useful for error recovery. Returns
TRUE on success or FALSE on failure.
int pg_connection_status ( resource $connection )

3

This

routine

returns

the

status

of

the

specified

connection.

Returns

PGSQL_CONNECTION_OK or PGSQL_CONNECTION_BAD.
string pg_dbname ([ resource $connection ] )
4

This routine returns the name of the database that the given PostgreSQL
connection resource.

5

resource pg_prepare ([ resource $connection ], string $stmtname,

string $query )
This submits a request to create a prepared statement with the given
parameters and waits for completion.
resource pg_execute ([ resource $connection ], string $stmtname,
array $params )
6

This routine sends a request to execute a prepared statement with given
parameters and waits for the result.
resource pg_query ([ resource $connection ], string $query )

7

This routine executes the query on the specified database connection.
array pg_fetch_row ( resource $result [, int $row ] )

8

This routine fetches one row of data from the result associated with the
specified result resource.
array pg_fetch_all ( resource $result )

9

This routine returns an array that contains all rows (records) in the result
resource.
int pg_affected_rows ( resource $result )

10

This routine returns the number of rows affected by INSERT, UPDATE, and
DELETE queries.
int pg_num_rows ( resource $result )

11

This routine returns the number of rows in a PostgreSQL result resource for
example number of rows returned by SELECT statement.
bool pg_close ([ resource $connection ] )

12

This routine closes the non-persistent connection to a PostgreSQL database
associated with the given connection resource.
string pg_last_error ([ resource $connection ] )

13

14

This routine returns the last error message for a given connection.
string pg_escape_literal ([ resource $connection ], string $data )

This routine escapes a literal for insertion into a text field.
string pg_escape_string ([ resource $connection ], string $data )
15

This routine escapes a string for querying the database.

Connecting to Database
The following PHP code shows how to connect to an existing database on a local machine
and finally a database connection object will be returned.


Now, let us run the above given program to open our database testdb: if the database is
successfully opened, then it will give the following message −
Opened database successfully

Create a Table
The following PHP program will be used to create a table in a previously created database
−


When the above given program is executed, it will create COMPANY table in your testdb
and it will display the following messages −
Opened database successfully
Table created successfully

INSERT Operation
The following PHP program shows how we can create records in our COMPANY table
created in above example −


When the above given program is executed, it will create the given records in COMPANY
table and will display the following two lines −
Opened database successfully
Records created successfully

SELECT Operation
The following PHP program shows how we can fetch and display records from our
COMPANY table created in above example −


When the above given program is executed, it will produce the following result. Keep a
note that fields are returned in the sequence they were used while creating table.
Opened database successfully
ID = 1
NAME = Paul
ADDRESS = California

SALARY =

20000

ID = 2
NAME = Allen
ADDRESS = Texas
SALARY =

15000

ID = 3
NAME = Teddy
ADDRESS = Norway
SALARY =

20000

ID = 4
NAME = Mark
ADDRESS = Rich-Mond
SALARY =

65000

Operation done successfully

UPDATE Operation
The following PHP code shows how we can use the UPDATE statement to update any
record and then fetch and display updated records from our COMPANY table −


When the above given program is executed, it will produce the following result −
Opened database successfully
Record updated successfully
ID = 2
NAME = Allen
ADDRESS = 25
SALARY =

15000

ID = 3
NAME = Teddy
ADDRESS = 23
SALARY =

20000

ID = 4
NAME = Mark
ADDRESS = 25
SALARY =

65000

ID = 1
NAME = Paul
ADDRESS = 32
SALARY =

25000

Operation done successfully

DELETE Operation
The following PHP code shows how we can use the DELETE statement to delete any record
and then fetch and display the remaining records from our COMPANY table −


When the above given program is executed, it will produce the following result −
Opened database successfully
Record deleted successfully
ID = 3
NAME = Teddy
ADDRESS = 23
SALARY =

20000

ID = 4
NAME = Mark
ADDRESS = 25
SALARY =

65000

ID = 1
NAME = Paul
ADDRESS = 32

SALARY =

25000

Operation done successfully

PostgreSQL - Perl Interface
Installation
The PostgreSQL can be integrated with Perl using Perl DBI module, which is a database
access module for the Perl programming language. It defines a set of methods, variables
and conventions that provide a standard database interface.
Here are simple steps to install DBI module on your Linux/Unix machine −
$
$
$
$
$
$

wget http://search.cpan.org/CPAN/authors/id/T/TI/TIMB/DBI-1.625.tar.gz
tar xvfz DBI-1.625.tar.gz
cd DBI-1.625
perl Makefile.PL
make
make install

If you need to install SQLite driver for DBI, then it can be installed as follows −
$
$
$
$
$
$

wget http://search.cpan.org/CPAN/authors/id/T/TU/TURNSTEP/DBD-Pg-2.19.3.tar.gz
tar xvfz DBD-Pg-2.19.3.tar.gz
cd DBD-Pg-2.19.3
perl Makefile.PL
make
make install

Before you start using Perl PostgreSQL interface, find the pg_hba.conf file in your
PostgreSQL installation directory and add the following line −
# IPv4 local connections:
host
all
all

127.0.0.1/32

md5

You can start/restart the postgres server, in case it is not running, using the following
command −
[root@host]# service postgresql restart
Stopping postgresql service:
Starting postgresql service:

[
[

OK
OK

]
]

DBI Interface APIs
Following are the important DBI routines, which can suffice your requirement to work with
SQLite database from your Perl program. If you are looking for a more sophisticated
application, then you can look into Perl DBI official documentation.

S. No.

API & Description

DBI→connect($data_source, "userid", "password", \%attr)
Establishes a database connection, or session, to the requested $data_source.
1

Returns a database handle object if the connection succeeds.
Datasource

has

the

form

like

DBI:Pg:dbname=$database;host=127.0.0.1;port=5432

:
Pg

is

PostgreSQL driver name and testdb is the name of database.
$dbh→do($sql)
This routine prepares and executes a single SQL statement. Returns the
2

number of rows affected or undef on error. A return value of -1 means the
number of rows is not known, not applicable, or not available. Here $dbh is a
handle returned by DBI→connect() call.
$dbh→prepare($sql)

3

This routine prepares a statement for later execution by the database engine
and returns a reference to a statement handle object.
$sth→execute()
This routine performs whatever processing is necessary to execute the

4

prepared statement. An undef is returned if an error occurs. A successful
execute always returns true regardless of the number of rows affected. Here
$sth is a statement handle returned by $dbh→prepare($sql) call.
$sth→fetchrow_array()

5

This routine fetches the next row of data and returns it as a list containing the
field values. Null fields are returned as undef values in the list.
$DBI::err

6

This is equivalent to $h→err, where $h is any of the handle types like $dbh,
$sth, or $drh. This returns native database engine error code from the last
driver method called.

7

$DBI::errstr
This is equivalent to $h→errstr, where $h is any of the handle types like $dbh,
$sth, or $drh. This returns the native database engine error message from the

last DBI method called.
$dbh->disconnect()
8

This routine closes a database connection previously opened by a call to
DBI→connect().

Connecting to Database
The following Perl code shows how to connect to an existing database. If the database
does not exist, then it will be created and finally a database object will be returned.
#!/usr/bin/perl
use DBI;
use strict;
my
my
my
my
my
my

$driver = "Pg";
$database = "testdb";
$dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";
$userid = "postgres";
$password = "pass123";
$dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })
or die $DBI::errstr;

print "Opened database successfully\n";

Now, let us run the above given program to open our database testdb; if the database is
successfully opened then it will give the following message −
Open database successfully

Create a Table
The following Perl program will be used to create a table in previously created database −
#!/usr/bin/perl
use DBI;
use strict;
my
my
my
my
my
my

$driver
= "Pg";
$database = "testdb";
$dsn = "DBI:$driver:dbname=$database;host=127.0.0.1;port=5432";
$userid = "postgres";
$password = "pass123";
$dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })
or die $DBI::errstr;
print "Opened database successfully\n";
my $stmt = qq(CREATE TABLE COMPANY
(ID INT PRIMARY KEY
NOT NULL,

NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL););
my $rv = $dbh->do($stmt);
if($rv < 0) {
print $DBI::errstr;
} else {
print "Table created successfully\n";
}
$dbh->disconnect();

When the above given program is executed, it will create COMPANY table in your testdb
and it will display the following messages −
Opened database successfully
Table created successfully

INSERT Operation
The following Perl program shows how we can create records in our COMPANY table
created in above example −
#!/usr/bin/perl
use DBI;
use strict;
my
my
my
my
my
my

$driver
= "Pg";
$database = "testdb";
$dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";
$userid = "postgres";
$password = "pass123";
$dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })
or die $DBI::errstr;
print "Opened database successfully\n";
my $stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (1, 'Paul', 32, 'California', 20000.00 ));
my $rv = $dbh->do($stmt) or die $DBI::errstr;
$stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (2, 'Allen', 25, 'Texas', 15000.00 ));
$rv = $dbh->do($stmt) or die $DBI::errstr;
$stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (3, 'Teddy', 23, 'Norway', 20000.00 ));
$rv = $dbh->do($stmt) or die $DBI::errstr;
$stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 ););
$rv = $dbh->do($stmt) or die $DBI::errstr;
print "Records created successfully\n";
$dbh->disconnect();

When the above given program is executed, it will create given records in COMPANY table
and will display the following two lines −
Opened database successfully
Records created successfully

SELECT Operation
The following Perl program shows how we can fetch and display records from our
COMPANY table created in above example −
#!/usr/bin/perl
use DBI;
use strict;
my
my
my
my
my
my

$driver
= "Pg";
$database = "testdb";
$dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";
$userid = "postgres";
$password = "pass123";
$dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })
or die $DBI::errstr;
print "Opened database successfully\n";
my $stmt = qq(SELECT id, name, address, salary
my $sth = $dbh->prepare( $stmt );
my $rv = $sth->execute() or die $DBI::errstr;
if($rv < 0) {
print $DBI::errstr;
}
while(my @row = $sth->fetchrow_array()) {
print "ID = ". $row[0] . "\n";
print "NAME = ". $row[1] ."\n";
print "ADDRESS = ". $row[2] ."\n";
print "SALARY = ". $row[3] ."\n\n";
}
print "Operation done successfully\n";
$dbh->disconnect();

from COMPANY;);

When the above given program is executed, it will produce the following result −
Opened database successfully
ID = 1
NAME = Paul
ADDRESS = California
SALARY =

20000

ID = 2
NAME = Allen
ADDRESS = Texas
SALARY =

15000

ID = 3
NAME = Teddy
ADDRESS = Norway
SALARY =

20000

ID = 4
NAME = Mark
ADDRESS = Rich-Mond
SALARY =

65000

Operation done successfully

UPDATE Operation
The following Perl code shows how we can use the UPDATE statement to update any record
and then fetch and display updated records from our COMPANY table −
#!/usr/bin/perl
use DBI;
use strict;
my
my
my
my
my
my

$driver
= "Pg";
$database = "testdb";
$dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";
$userid = "postgres";
$password = "pass123";
$dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })
or die $DBI::errstr;
print "Opened database successfully\n";
my $stmt = qq(UPDATE COMPANY set SALARY = 25000.00 where ID=1;);
my $rv = $dbh->do($stmt) or die $DBI::errstr;
if( $rv < 0 ) {
print $DBI::errstr;
}else{
print "Total number of rows updated : $rv\n";
}
$stmt = qq(SELECT id, name, address, salary from COMPANY;);
my $sth = $dbh->prepare( $stmt );
$rv = $sth->execute() or die $DBI::errstr;
if($rv < 0) {
print $DBI::errstr;
}
while(my @row = $sth->fetchrow_array()) {
print "ID = ". $row[0] . "\n";
print "NAME = ". $row[1] ."\n";
print "ADDRESS = ". $row[2] ."\n";
print "SALARY = ". $row[3] ."\n\n";
}
print "Operation done successfully\n";
$dbh->disconnect();

When the above given program is executed, it will produce the following result −
Opened database successfully
Total number of rows updated : 1
ID = 1
NAME = Paul
ADDRESS = California
SALARY =

25000

ID = 2
NAME = Allen
ADDRESS = Texas
SALARY =

15000

ID = 3
NAME = Teddy
ADDRESS = Norway
SALARY =

20000

ID = 4
NAME = Mark
ADDRESS = Rich-Mond
SALARY =

65000

Operation done successfully

DELETE Operation
The following Perl code shows how we can use the DELETE statement to delete any record
and then fetch and display the remaining records from our COMPANY table −
#!/usr/bin/perl
use DBI;
use strict;
my
my
my
my
my
my

$driver
= "Pg";
$database = "testdb";
$dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";
$userid = "postgres";
$password = "pass123";
$dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })
or die $DBI::errstr;
print "Opened database successfully\n";
my $stmt = qq(DELETE from COMPANY where ID=2;);
my $rv = $dbh->do($stmt) or die $DBI::errstr;
if( $rv < 0 ) {
print $DBI::errstr;

} else{
print "Total number of rows deleted : $rv\n";
}
$stmt = qq(SELECT id, name, address, salary from COMPANY;);
my $sth = $dbh->prepare( $stmt );
$rv = $sth->execute() or die $DBI::errstr;
if($rv < 0) {
print $DBI::errstr;
}
while(my @row = $sth->fetchrow_array()) {
print "ID = ". $row[0] . "\n";
print "NAME = ". $row[1] ."\n";
print "ADDRESS = ". $row[2] ."\n";
print "SALARY = ". $row[3] ."\n\n";
}
print "Operation done successfully\n";
$dbh->disconnect();

When the above given program is executed, it will produce the following result −
Opened database successfully
Total number of rows deleted : 1
ID = 1
NAME = Paul
ADDRESS = California
SALARY =

25000

ID = 3
NAME = Teddy
ADDRESS = Norway
SALARY =

20000

ID = 4
NAME = Mark
ADDRESS = Rich-Mond
SALARY =

65000

Operation done successfully

PostgreSQL - Python Interface
Installation
The PostgreSQL can be integrated with Python using psycopg2 module. sycopg2 is a
PostgreSQL database adapter for the Python programming language. psycopg2 was written
with the aim of being very small and fast, and stable as a rock. You do not need to install
this module separately because it is shipped, by default, along with Python version 2.5.x
onwards.

If you do not have it installed on your machine then you can use yum command to install it
as follows −
$yum install python-psycopg2

To use psycopg2 module, you must first create a Connection object that represents the
database and then optionally you can create cursor object which will help you in executing
all the SQL statements.

Python psycopg2 module APIs
The following are important psycopg2 module routines, which can suffice your requirement
to work with PostgreSQL database from your Python program. If you are looking for a
more sophisticated application, then you can look into Python psycopg2 module's official
documentation.
S. No.

API & Description

psycopg2.connect(database="testdb",

user="postgres",

password="cohondob", host="127.0.0.1", port="5432")
1

This API opens a connection to the PostgreSQL database. If database is
opened successfully, it returns a connection object.
connection.cursor()

2

This routine creates a cursor which will be used throughout of your database
programming with Python.
cursor.execute(sql [, optional parameters])
This routine executes an SQL statement. The SQL statement may be

3

parameterized (i.e., placeholders instead of SQL literals). The psycopg2
module supports placeholder using %s sign
For example:cursor.execute("insert into people values (%s, %s)", (who, age))
cursor.executemany(sql, seq_of_parameters)

4

This routine executes an SQL command against all parameter sequences or
mappings found in the sequence sql.

5

cursor.callproc(procname[, parameters])
This routine executes a stored database procedure with the given name. The
sequence of parameters must contain one entry for each argument that the

procedure expects.
cursor.rowcount
6

This read-only attribute which returns the total number of database rows that
have been modified, inserted, or deleted by the last last execute*().
connection.commit()

7

This method commits the current transaction. If you do not call this method,
anything you did since the last call to commit() is not visible from other
database connections.
connection.rollback()

8

This method rolls back any changes to the database since the last call to
commit().
connection.close()

9

This method closes the database connection. Note that this does not
automatically call commit(). If you just close your database connection
without calling commit() first, your changes will be lost!
cursor.fetchone()

10

This method fetches the next row of a query result set, returning a single
sequence, or None when no more data is available.
cursor.fetchmany([size=cursor.arraysize])

11

This routine fetches the next set of rows of a query result, returning a list. An
empty list is returned when no more rows are available. The method tries to
fetch as many rows as indicated by the size parameter.
cursor.fetchall()

12

This routine fetches all (remaining) rows of a query result, returning a list. An
empty list is returned when no rows are available.

Connecting to Database

The following Python code shows how to connect to an existing database. If the database
does not exist, then it will be created and finally a database object will be returned.
#!/usr/bin/python
import psycopg2
conn = psycopg2.connect(database="testdb", user = "postgres", password = "pass123", host = "127.0
print "Opened database successfully"

Here, you can also supply database testdb as name and if database is successfully
opened, then it will give the following message −
Open database successfully

Create a Table
The following Python program will be used to create a table in previously created database
−
#!/usr/bin/python
import psycopg2
conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127
print "Opened database successfully"
cur = conn.cursor()
cur.execute('''CREATE TABLE COMPANY
(ID INT PRIMARY KEY
NOT NULL,
NAME
TEXT
NOT NULL,
AGE
INT
NOT NULL,
ADDRESS
CHAR(50),
SALARY
REAL);''')
print "Table created successfully"
conn.commit()
conn.close()

When the above given program is executed, it will create COMPANY table in your test.db
and it will display the following messages −
Opened database successfully
Table created successfully

INSERT Operation
The following Python program shows how we can create records in our COMPANY table
created in the above example −

#!/usr/bin/python
import psycopg2
conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127
print "Opened database successfully"
cur = conn.cursor()
cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \
VALUES (1, 'Paul', 32, 'California', 20000.00 )");
cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \
VALUES (2, 'Allen', 25, 'Texas', 15000.00 )");
cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \
VALUES (3, 'Teddy', 23, 'Norway', 20000.00 )");
cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \
VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 )");
conn.commit()
print "Records created successfully";
conn.close()

When the above given program is executed, it will create given records in COMPANY table
and will display the following two lines −
Opened database successfully
Records created successfully

SELECT Operation
The following Python program shows how we can fetch and display records from our
COMPANY table created in the above example −
#!/usr/bin/python
import psycopg2
conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127
print "Opened database successfully"
cur = conn.cursor()
cur.execute("SELECT id, name, address, salary
rows = cur.fetchall()
for row in rows:
print "ID = ", row[0]
print "NAME = ", row[1]
print "ADDRESS = ", row[2]
print "SALARY = ", row[3], "\n"
print "Operation done successfully";
conn.close()

from COMPANY")

When the above given program is executed, it will produce the following result −
Opened database successfully
ID =

1

NAME =

Paul

ADDRESS =
SALARY =
ID =

California
20000.0

2

NAME =

Allen

ADDRESS =

Texas

SALARY =

15000.0

ID =

3

NAME =

Teddy

ADDRESS =

Norway

SALARY =

20000.0

ID =

4

NAME =

Mark

ADDRESS =
SALARY =

Rich-Mond
65000.0

Operation done successfully

UPDATE Operation
The following Python code shows how we can use the UPDATE statement to update any
record and then fetch and display updated records from our COMPANY table −
#!/usr/bin/python
import psycopg2
conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127
print "Opened database successfully"
cur = conn.cursor()
cur.execute("UPDATE COMPANY set SALARY = 25000.00 where ID = 1")
conn.commit()
print "Total number of rows updated :", cur.rowcount
cur.execute("SELECT id, name, address, salary
rows = cur.fetchall()
for row in rows:
print "ID = ", row[0]
print "NAME = ", row[1]

from COMPANY")

print "ADDRESS = ", row[2]
print "SALARY = ", row[3], "\n"
print "Operation done successfully";
conn.close()

When the above given program is executed, it will produce the following result −
Opened database successfully
Total number of rows updated : 1
ID =

1

NAME =

Paul

ADDRESS =
SALARY =
ID =

California
25000.0

2

NAME =

Allen

ADDRESS =

Texas

SALARY =

15000.0

ID =

3

NAME =

Teddy

ADDRESS =

Norway

SALARY =

20000.0

ID =

4

NAME =

Mark

ADDRESS =
SALARY =

Rich-Mond
65000.0

Operation done successfully

DELETE Operation
The following Python code shows how we can use the DELETE statement to delete any
record and then fetch and display the remaining records from our COMPANY table −
#!/usr/bin/python
import psycopg2
conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127
print "Opened database successfully"
cur = conn.cursor()
cur.execute("DELETE from COMPANY where ID=2;")
conn.commit()

print "Total number of rows deleted :", cur.rowcount
cur.execute("SELECT id, name, address, salary
rows = cur.fetchall()
for row in rows:
print "ID = ", row[0]
print "NAME = ", row[1]
print "ADDRESS = ", row[2]
print "SALARY = ", row[3], "\n"

from COMPANY")

print "Operation done successfully";
conn.close()

When the above given program is executed, it will produce the following result −
Opened database successfully
Total number of rows deleted : 1
ID =

1

NAME =

Paul

ADDRESS =
SALARY =
ID =

California
20000.0

3

NAME =

Teddy

ADDRESS =

Norway

SALARY =

20000.0

ID =

4

NAME =

Mark

ADDRESS =
SALARY =

Rich-Mond
65000.0

Operation done successfully

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