GSPTG Performance Tuning Guide

performance-tuning-guide

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GlassFish Server Open Source Edition
Performance Tuning Guide
Release 4.0
May 2013
This book describes how to get the best performance with
GlassFish Server 4.0.
GlassFish Server Open Source Edition Performance Tuning Guide, Release 4.0
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iii
Contents
Preface ................................................................................................................................................................. ix
1 Overview of GlassFish Server Performance Tuning
Process Overview ..................................................................................................................................... 1-1
Performance Tuning Sequence......................................................................................................... 1-2
Understanding Operational Requirements......................................................................................... 1-2
Application Architecture .................................................................................................................. 1-2
Security Requirements....................................................................................................................... 1-3
High Availability Clustering, Load Balancing, and Failover ...................................................... 1-5
Hardware Resources.......................................................................................................................... 1-5
Administration ................................................................................................................................... 1-6
General Tuning Concepts ....................................................................................................................... 1-6
Capacity Planning.............................................................................................................................. 1-7
User Expectations............................................................................................................................... 1-8
Further Information ................................................................................................................................. 1-8
2 Tuning Your Application
Java Programming Guidelines............................................................................................................... 2-1
Avoid Serialization and Deserialization......................................................................................... 2-1
Use
StringBuilder
to Concatenate Strings ................................................................................... 2-2
Assign null to Variables That Are No Longer Needed ................................................................ 2-2
Declare Methods as final Only If Necessary .................................................................................. 2-2
Declare Constants as static final....................................................................................................... 2-2
Avoid Finalizers ................................................................................................................................. 2-3
Declare Method Arguments final .................................................................................................... 2-3
Synchronize Only When Necessary ................................................................................................ 2-3
Use DataHandlers for SOAP Attachments..................................................................................... 2-3
Java Server Page and Servlet Tuning.................................................................................................... 2-3
Suggested Coding Practices.............................................................................................................. 2-4
EJB Performance Tuning ......................................................................................................................... 2-5
Goals..................................................................................................................................................... 2-6
Monitoring EJB Components ........................................................................................................... 2-6
General Guidelines ............................................................................................................................ 2-8
Using Local and Remote Interfaces .............................................................................................. 2-10
Improving Performance of EJB Transactions.............................................................................. 2-11
iv
Using Special Techniques .............................................................................................................. 2-12
Tuning Tips for Specific Types of EJB Components .................................................................. 2-15
JDBC and Database Access............................................................................................................ 2-18
Tuning Message-Driven Beans ..................................................................................................... 2-19
3 Tuning the GlassFish Server
Using the GlassFish Server Performance Tuner................................................................................. 3-1
Deployment Settings ............................................................................................................................... 3-2
Disable Auto-Deployment................................................................................................................ 3-2
Use Pre-compiled JavaServer Pages................................................................................................ 3-2
Disable Dynamic Application Reloading ....................................................................................... 3-3
Logger Settings ......................................................................................................................................... 3-3
General Settings.................................................................................................................................. 3-3
Log Levels ........................................................................................................................................... 3-3
Web Container Settings........................................................................................................................... 3-3
Session Properties: Session Timeout ............................................................................................... 3-3
Manager Properties: Reap Interval.................................................................................................. 3-4
Disable Dynamic JSP Reloading ...................................................................................................... 3-4
EJB Container Settings ............................................................................................................................ 3-4
Monitoring the EJB Container.......................................................................................................... 3-5
Tuning the EJB Container ................................................................................................................. 3-5
Java Message Service Settings ............................................................................................................... 3-9
Transaction Service Settings................................................................................................................... 3-9
Monitoring the Transaction Service ................................................................................................ 3-9
Tuning the Transaction Service..................................................................................................... 3-10
HTTP Service Settings.......................................................................................................................... 3-11
Monitoring the HTTP Service........................................................................................................ 3-11
HTTP Service Access Logging....................................................................................................... 3-14
Network Listener Settings................................................................................................................... 3-14
General Settings............................................................................................................................... 3-14
HTTP Settings.................................................................................................................................. 3-15
File Cache Settings .......................................................................................................................... 3-16
Transport Settings ................................................................................................................................. 3-17
Thread Pool Settings............................................................................................................................. 3-17
Max Thread Pool Size..................................................................................................................... 3-17
Min Thread Pool Size...................................................................................................................... 3-18
ORB Settings .......................................................................................................................................... 3-18
Overview.......................................................................................................................................... 3-18
How a Client Connects to the ORB .............................................................................................. 3-18
Monitoring the ORB........................................................................................................................ 3-19
Tuning the ORB............................................................................................................................... 3-19
Resource Settings .................................................................................................................................. 3-23
JDBC Connection Pool Settings..................................................................................................... 3-23
Connector Connection Pool Settings............................................................................................ 3-26
Load Balancer Settings ......................................................................................................................... 3-26
v
4 Tuning the Java Runtime System
Java Virtual Machine Settings ............................................................................................................... 4-1
Start Options ............................................................................................................................................. 4-2
Tuning High Availability Persistence .................................................................................................. 4-2
Managing Memory and Garbage Collection ...................................................................................... 4-2
Tuning the Garbage Collector.......................................................................................................... 4-2
Tracing Garbage Collection .............................................................................................................. 4-3
Other Garbage Collector Settings .................................................................................................... 4-4
Tuning the Java Heap........................................................................................................................ 4-5
Rebasing DLLs on Windows............................................................................................................ 4-7
Further Information ................................................................................................................................. 4-8
5 Tuning the Operating System and Platform
Server Scaling............................................................................................................................................ 5-1
Processors............................................................................................................................................ 5-1
Memory ............................................................................................................................................... 5-1
Disk Space ........................................................................................................................................... 5-2
Networking......................................................................................................................................... 5-2
UDP Buffer Sizes ................................................................................................................................ 5-2
Solaris 10 Platform-Specific Tuning Information.............................................................................. 5-4
Tuning for the Solaris OS ....................................................................................................................... 5-4
Tuning Parameters............................................................................................................................. 5-4
File Descriptor Setting ....................................................................................................................... 5-6
Tuning for Solaris on x86 ........................................................................................................................ 5-6
File Descriptors................................................................................................................................... 5-6
IP Stack Settings ................................................................................................................................. 5-6
Tuning for Linux platforms .................................................................................................................... 5-7
Startup Files ........................................................................................................................................ 5-7
File Descriptors................................................................................................................................... 5-8
Virtual Memory.................................................................................................................................. 5-9
Network Interface .............................................................................................................................. 5-9
Disk I/O Settings................................................................................................................................ 5-9
TCP/IP Settings............................................................................................................................... 5-10
Tuning UltraSPARC CMT-Based Systems........................................................................................ 5-11
Tuning Operating System and TCP Settings .............................................................................. 5-11
Disk Configuration ......................................................................................................................... 5-11
Network Configuration.................................................................................................................. 5-12
vi
List of Examples
4–1 Heap Configuration on Solaris ................................................................................................. 4-7
4–2 Heap Configuration on Windows ............................................................................................ 4-8
5–1 Setting the UDP Buffer Size in the
/etc/sysctl.conf
File .................................................. 5-4
5–2 Setting the UDP Buffer Size at Runtime.................................................................................. 5-4
vii
List of Figures
1–1 Java EE Application Model ....................................................................................................... 1-3
viii
List of Tables
1–1 Performance Tuning Roadmap................................................................................................ 1-1
1–2 Factors That Affect Performance ............................................................................................. 1-7
3–1 Bean Type Pooling or Caching................................................................................................. 3-5
3–2 Tunable ORB Parameters....................................................................................................... 3-20
3–3 Connection Pool Sizing .......................................................................................................... 3-24
4–1 Maximum Address Space Per Process.................................................................................... 4-5
5–1 Tuning Parameters for Solaris.................................................................................................. 5-5
5–2 Tuning 64-bit Systems for Performance Benchmarking.................................................... 5-11
ix
Preface
The Performance Tuning Guide describes how to get the best performance with
GlassFish Server 4.0.
This preface contains information about and conventions for the entire GlassFish
Server Open Source Edition (GlassFish Server) documentation set.
GlassFish Server 4.0 is developed through the GlassFish project open-source
community at http://glassfish.java.net/. The GlassFish project provides a
structured process for developing the GlassFish Server platform that makes the new
features of the Java EE platform available faster, while maintaining the most important
feature of Java EE: compatibility. It enables Java developers to access the GlassFish
Server source code and to contribute to the development of the GlassFish Server. The
GlassFish project is designed to encourage communication between Oracle engineers
and the community.
Oracle GlassFish Server Documentation Set
Book Title Description
Release Notes Provides late-breaking information about the software and the
documentation and includes a comprehensive, table-based
summary of the supported hardware, operating system, Java
Development Kit (JDK), and database drivers.
Quick Start Guide Explains how to get started with the GlassFish Server product.
Installation Guide Explains how to install the software and its components.
Upgrade Guide Explains how to upgrade to the latest version of GlassFish Server.
This guide also describes differences between adjacent product
releases and configuration options that can result in
incompatibility with the product specifications.
Deployment Planning Guide Explains how to build a production deployment of GlassFish
Server that meets the requirements of your system and enterprise.
Administration Guide Explains how to configure, monitor, and manage GlassFish Server
subsystems and components from the command line by using the
asadmin
utility. Instructions for performing these tasks from the
Administration Console are provided in the Administration
Console online help.
Security Guide Provides instructions for configuring and administering GlassFish
Server security.
Application Deployment
Guide
Explains how to assemble and deploy applications to the
GlassFish Server and provides information about deployment
descriptors.
x
Typographic Conventions
The following table describes the typographic changes that are used in this book.
Application Development
Guide
Explains how to create and implement Java Platform, Enterprise
Edition (Java EE platform) applications that are intended to run
on the GlassFish Server. These applications follow the open Java
standards model for Java EE components and application
programmer interfaces (APIs). This guide provides information
about developer tools, security, and debugging.
Embedded Server Guide Explains how to run applications in embedded GlassFish Server
and to develop applications in which GlassFish Server is
embedded.
High Availability
Administration Guide
Explains how to configure GlassFish Server to provide higher
availability and scalability through failover and load balancing.
Performance Tuning Guide Explains how to optimize the performance of GlassFish Server.
Troubleshooting Guide Describes common problems that you might encounter when
using GlassFish Server and explains how to solve them.
Error Message Reference Describes error messages that you might encounter when using
GlassFish Server.
Reference Manual Provides reference information in man page format for GlassFish
Server administration commands, utility commands, and related
concepts.
Message Queue Release
Notes
Describes new features, compatibility issues, and existing bugs for
Open Message Queue.
Message Queue Technical
Overview
Provides an introduction to the technology, concepts, architecture,
capabilities, and features of the Message Queue messaging
service.
Message Queue
Administration Guide
Explains how to set up and manage a Message Queue messaging
system.
Message Queue Developer's
Guide for JMX Clients
Describes the application programming interface in Message
Queue for programmatically configuring and monitoring
Message Queue resources in conformance with the Java
Management Extensions (JMX).
Message Queue Developer's
Guide for Java Clients
Provides information about concepts and procedures for
developing Java messaging applications (Java clients) that work
with GlassFish Server.
Message Queue Developer's
Guide for C Clients
Provides programming and reference information for developers
working with Message Queue who want to use the C language
binding to the Message Queue messaging service to send, receive,
and process Message Queue messages.
Typeface Meaning Example
AaBbCc123
The names of commands, files,
and directories, and onscreen
computer output
Edit your
.login
file.
Use
ls a
to list all files.
machine_name% you have mail.
AaBbCc123 What you type, contrasted with
onscreen computer output
machine_name%
su
Password:
Book Title Description
xi
Symbol Conventions
The following table explains symbols that might be used in this book.
Default Paths and File Names
The following table describes the default paths and file names that are used in this
book.
AaBbCc123 A placeholder to be replaced with
a real name or value The command to remove a file is
rm
filename.
AaBbCc123 Book titles, new terms, and terms
to be emphasized (note that some
emphasized items appear bold
online)
Read Chapter 6 in the User's Guide.
A cache is a copy that is stored locally.
Do not save the file.
Symbol Description Example Meaning
[ ]
Contains optional
arguments and
command options.
ls [-l]
The
-l
option is not required.
{ | }
Contains a set of
choices for a required
command option.
-d {y|n}
The
-d
option requires that you
use either the
y
argument or the
n
argument.
${ }
Indicates a variable
reference.
${com.sun.javaRoot}
References the value of the
com.sun.javaRoot
variable.
- Joins simultaneous
multiple keystrokes. Control-A Press the Control key while you
press the A key.
+ Joins consecutive
multiple keystrokes. Ctrl+A+N Press the Control key, release it,
and then press the subsequent
keys.
> Indicates menu item
selection in a graphical
user interface.
File > New > Templates From the File menu, choose
New. From the New submenu,
choose Templates.
Placeholder Description Default Value
as-install Represents the base installation
directory for GlassFish Server.
In configuration files, as-install is
represented as follows:
${com.sun.aas.installRoot}
Installations on the Oracle Solaris operating system, Linux
operating system, and Mac OS operating system:
user's-home-directory
/glassfish3/glassfish
Installations on the Windows operating system:
SystemDrive
:\glassfish3\glassfish
as-install-parent Represents the parent of the base
installation directory for GlassFish
Server.
Installations on the Oracle Solaris operating system, Linux
operating system, and Mac operating system:
user's-home-directory
/glassfish3
Installations on the Windows operating system:
SystemDrive
:\glassfish3
domain-root-dir Represents the directory in which a
domain is created by default. as-install
/domains/
Typeface Meaning Example
xii
Documentation, Support, and Training
The Oracle web site provides information about the following additional resources:
■Documentation (http://docs.oracle.com/)
■Support (http://www.oracle.com/us/support/index.html)
■Training (http://education.oracle.com/)
Documentation Accessibility
For information about Oracle's commitment to accessibility, visit the Oracle
Accessibility Program website at
http://www.oracle.com/pls/topic/lookup?ctx=acc&id=docacc.
Access to Oracle Support
Oracle customers have access to electronic support through My Oracle Support. For
information, visit
http://www.oracle.com/pls/topic/lookup?ctx=acc&id=info or visit
http://www.oracle.com/pls/topic/lookup?ctx=acc&id=trs if you are
hearing impaired.
domain-dir Represents the directory in which a
domain's configuration is stored.
In configuration files, domain-dir is
represented as follows:
${com.sun.aas.instanceRoot}
domain-root-dir
/
domain-name
instance-dir Represents the directory for a server
instance. domain-dir
/
instance-name
Placeholder Description Default Value
1
Overview of GlassFish Server Performance Tuning 1-1
1Overview of GlassFish Server Performance
Tuning
You can significantly improve performance of the Oracle GlassFish Server and of
applications deployed to it by adjusting a few deployment and server configuration
settings. However, it is important to understand the environment and performance
goals. An optimal configuration for a production environment might not be optimal
for a development environment.
The following topics are addressed here:
■Process Overview
■Understanding Operational Requirements
■General Tuning Concepts
■Further Information
Process Overview
The following table outlines the overall GlassFish Server 4.0 administration process,
and shows where performance tuning fits in the sequence.
Table 1–1 Performance Tuning Roadmap
Step Description of Task Location of Instructions
1Design: Decide on the high-availability topology
and set up GlassFish Server. GlassFish Server Open Source Edition Deployment Planning
Guide
2Capacity Planning: Make sure the systems have
sufficient resources to perform well. GlassFish Server Open Source Edition Deployment Planning
Guide
3Installation: Configure your DAS, clusters, and
clustered server instances. GlassFish Server Open Source Edition Installation Guide
Understanding Operational Requirements
1-2 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Performance Tuning Sequence
Application developers should tune applications prior to production use. Tuning
applications often produces dramatic performance improvements. System
administrators perform the remaining steps in the following list after tuning the
application, or when application tuning has to wait and you want to improve
performance as much as possible in the meantime.
Ideally, follow this sequence of steps when you are tuning performance:
1. Tune your application, described in Tuning Your Application.
2. Tune the server, described in Tuning the GlassFish Server.
3. Tune the Java runtime system, described in Tuning the Java Runtime System.
4. Tune the operating system, described in Tuning the Operating System and
Platform.
Understanding Operational Requirements
Before you begin to deploy and tune your application on the GlassFish Server, it is
important to clearly define the operational environment. The operational environment
is determined by high-level constraints and requirements such as:
■Application Architecture
■Security Requirements
■High Availability Clustering, Load Balancing, and Failover
■Hardware Resources
■Administration
Application Architecture
The Java EE Application model, as shown in the following figure, is very flexible;
allowing the application architect to split application logic functionally into many
tiers. The presentation layer is typically implemented using servlets and JSP
technology and executes in the web container.
4Deployment: Install and run your applications.
Familiarize yourself with how to configure and
administer the GlassFish Server.
The following books:
■GlassFish Server Open Source Edition Application
Deployment Guide
■GlassFish Server Open Source Edition Administration
Guide
5High Availability Configuration: Configuring
your DAS, clusters, and clustered server
instances for high availability and failover
GlassFish Server Open Source Edition High Availability
Administration Guide
6Performance Tuning: Tune the following items:
■Applications
■GlassFish Server
■Java Runtime System
■Operating system and platform
The following chapters:
■Tuning Your Application
■Tuning the GlassFish Server
■Tuning the Java Runtime System
■Tuning the Operating System and Platform
Table 1–1 (Cont.) Performance Tuning Roadmap
Step Description of Task Location of Instructions
Understanding Operational Requirements
Overview of GlassFish Server Performance Tuning 1-3
Figure 1–1 Java EE Application Model
Moderately complex enterprise applications can be developed entirely using servlets
and JSP technology. More complex business applications often use Enterprise
JavaBeans (EJB) components. The GlassFish Server integrates the Web and EJB
containers in a single process. Local access to EJB components from servlets is very
efficient. However, some application deployments may require EJB components to
execute in a separate process; and be accessible from standalone client applications as
well as servlets. Based on the application architecture, the server administrator can
employ the GlassFish Server in multiple tiers, or simply host both the presentation and
business logic on a single tier.
It is important to understand the application architecture before designing a new
GlassFish Server deployment, and when deploying a new business application to an
existing application server deployment.
Security Requirements
Most business applications require security. This section discusses security
considerations and decisions.
User Authentication and Authorization
Application users must be authenticated. The GlassFish Server provides a number of
choices for user authentication, including file-based, administration, LDAP, certificate,
JDBC, digest, PAM, Solaris, and custom realms.
EJB
Pure
HTML
Browser
Java
Applet
Java
Application
Desktop
J2EE
Client
J2EE
Platform
Other
Device
Client-Side
Presentation
JSP
Web
Server
JSP
Java
Servlet
Server-Side
Presentation
J2EE
Platform
EJB
EJB
Container
EJB
Server-Side
Business Logic
Enterprise
Information
System
Understanding Operational Requirements
1-4 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
The default file based security realm is suitable for developer environments, where
new applications are developed and tested. At deployment time, the server
administrator can choose between the Lighweight Directory Access Protocol (LDAP)
or Solaris security realms. Many large enterprises use LDAP-based directory servers to
maintain employee and customer profiles. Small to medium enterprises that do not
already use a directory server may find it advantageous to leverage investment in
Solaris security infrastructure.
For more information on security realms, see "Administering Authentication Realms"
in GlassFish Server Open Source Edition Security Guide.
The type of authentication mechanism chosen may require additional hardware for the
deployment. Typically a directory server executes on a separate server, and may also
require a backup for replication and high availability. Refer to the Oracle Java System
Directory Server
(http://www.oracle.com/us/products/middleware/identity-managemen
t/oracle-directory-services/index.html) documentation for more
information on deployment, sizing, and availability guidelines.
An authenticated user's access to application functions may also need authorization
checks. If the application uses the role-based Java EE authorization checks, the
application server performs some additional checking, which incurs additional
overheads. When you perform capacity planning, you must take this additional
overhead into account.
Encryption
For security reasons, sensitive user inputs and application output must be encrypted.
Most business-oriented web applications encrypt all or some of the communication
flow between the browser and GlassFish Server. Online shopping applications encrypt
traffic when the user is completing a purchase or supplying private data. Portal
applications such as news and media typically do not employ encryption. Secure
Sockets Layer (SSL) is the most common security framework, and is supported by
many browsers and application servers.
The GlassFish Server supports SSL 2.0 and 3.0 and contains software support for
various cipher suites. It also supports integration of hardware encryption cards for
even higher performance. Security considerations, particularly when using the
integrated software encryption, will impact hardware sizing and capacity planning.
Consider the following when assessing the encryption needs for a deployment:
■What is the nature of the applications with respect to security? Do they encrypt all
or only a part of the application inputs and output? What percentage of the
information needs to be securely transmitted?
■Are the applications going to be deployed on an application server that is directly
connected to the Internet? Will a web server exist in a demilitarized zone (DMZ)
separate from the application server tier and backend enterprise systems?
A DMZ-style deployment is recommended for high security. It is also useful when
the application has a significant amount of static text and image content and some
business logic that executes on the GlassFish Server, behind the most secure
firewall. GlassFish Server provides secure reverse proxy plugins to enable
integration with popular web servers. The GlassFish Server can also be deployed
and used as a web server in DMZ.
■Is encryption required between the web servers in the DMZ and application
servers in the next tier? The reverse proxy plugins supplied with GlassFish Server
support SSL encryption between the web server and application server tier. If SSL
Understanding Operational Requirements
Overview of GlassFish Server Performance Tuning 1-5
is enabled, hardware capacity planning must be take into account the encryption
policy and mechanisms.
■If software encryption is to be employed:
–What is the expected performance overhead for every tier in the system, given
the security requirements?
–What are the performance and throughput characteristics of various choices?
For information on how to encrypt the communication between web servers and
GlassFish Server, see "Administering Message Security" in GlassFish Server Open Source
Edition Security Guide.
High Availability Clustering, Load Balancing, and Failover
GlassFish Server 4.0 enables multiple GlassFish Server instances to be clustered to
provide high availability through failure protection, scalability, and load balancing.
High availability applications and services provide their functionality continuously,
regardless of hardware and software failures. To make such reliability possible,
GlassFish Server 4.0 provides mechanisms for maintaining application state data
between clustered GlassFish Server instances. Application state data, such as HTTP
session data, stateful EJB sessions, and dynamic cache information, is replicated in real
time across server instances. If any one server instance goes down, the session state is
available to the next failover server, resulting in minimum application downtime and
enhanced transactional security.
GlassFish Server provides the following high availability features:
■High Availability Session Persistence
■High Availability Java Message Service
■RMI-IIOP Load Balancing and Failover
See Tuning High Availability Persistence for high availability persistence tuning
recommendations.
See the GlassFish Server Open Source Edition High Availability Administration Guide for
complete information about configuring high availability clustering, load balancing,
and failover features in GlassFish Server 4.0.
Hardware Resources
The type and quantity of hardware resources available greatly influence performance
tuning and site planning.
GlassFish Server provides excellent vertical scalability. It can scale to efficiently utilize
multiple high-performance CPUs, using just one application server process. A smaller
number of application server instances makes maintenance easier and administration
less expensive. Also, deploying several related applications on fewer application
servers can improve performance, due to better data locality, and reuse of cached data
between co-located applications. Such servers must also contain large amounts of
memory, disk space, and network capacity to cope with increased load.
GlassFish Server can also be deployed on large "farms" of relatively modest hardware
units. Business applications can be partitioned across various server instances. Using
one or more external load balancers can efficiently spread user access across all the
application server instances. A horizontal scaling approach may improve availability,
lower hardware costs and is suitable for some types of applications. However, this
General Tuning Concepts
1-6 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
approach requires administration of more application server instances and hardware
nodes.
Administration
A single GlassFish Server installation on a server can encompass multiple instances. A
group of one or more instances that are administered by a single Administration
Server is called a domain. Grouping server instances into domains permits different
people to independently administer the groups.
You can use a single-instance domain to create a "sandbox" for a particular developer
and environment. In this scenario, each developer administers his or her own
application server, without interfering with other application server domains. A small
development group may choose to create multiple instances in a shared administrative
domain for collaborative development.
In a deployment environment, an administrator can create domains based on
application and business function. For example, internal Human Resources
applications may be hosted on one or more servers in one Administrative domain,
while external customer applications are hosted on several administrative domains in
a server farm.
GlassFish Server supports virtual server capability for web applications. For example,
a web application hosting service provider can host different URL domains on a single
GlassFish Server process for efficient administration.
For detailed information on administration, see the GlassFish Server Open Source Edition
Administration Guide.
General Tuning Concepts
Some key concepts that affect performance tuning are:
■User load
■Application scalability
■Margins of safety
The following table describes these concepts, and how they are measured in practice.
The left most column describes the general concept, the second column gives the
practical ramifications of the concept, the third column describes the measurements,
and the right most column describes the value sources.
General Tuning Concepts
Overview of GlassFish Server Performance Tuning 1-7
Capacity Planning
The previous discussion guides you towards defining a deployment architecture.
However, you determine the actual size of the deployment by a process called capacity
planning. Capacity planning enables you to predict:
■The performance capacity of a particular hardware configuration.
■The hardware resources required to sustain specified application load and
performance.
You can estimate these values through careful performance benchmarking, using an
application with realistic data sets and workloads.
To Determine Capacity
1. Determine performance on a single CPU.
First determine the largest load that a single processor can sustain. You can obtain
this figure by measuring the performance of the application on a single-processor
machine. Either leverage the performance numbers of an existing application with
similar processing characteristics or, ideally, use the actual application and
workload in a testing environment. Make sure that the application and data
resources are tiered exactly as they would be in the final deployment.
Table 1–2 Factors That Affect Performance
Concept In practice Measurement Value sources
User Load Concurrent
sessions at
peak load
Transactions Per Minute
(TPM)
Web Interactions Per
Second (WIPS)
(Max. number of concurrent users) * (expected
response time) / (time between clicks)
Example:
(100 users * 2 sec) / 10 sec = 20
Application
Scalability Transaction
rate
measured on
one CPU
TPM or WIPS Measured from workload benchmark. Perform at
each tier.
Vertical
scalability Increase in
performance
from
additional
CPUs
Percentage gain per
additional CPU Based on curve fitting from benchmark. Perform
tests while gradually increasing the number of
CPUs. Identify the "knee" of the curve, where
additional CPUs are providing uneconomical gains
in performance. Requires tuning as described in this
guide. Perform at each tier and iterate if necessary.
Stop here if this meets performance requirements.
Horizontal
scalability Increase in
performance
from
additional
servers
Percentage gain per
additional server process
and/or hardware node.
Use a well-tuned single application server instance,
as in previous step. Measure how much each
additional server instance and hardware node
improves performance.
Safety
Margins High
availability
requirements
If the system must cope
with failures, size the
system to meet performance
requirements assuming that
one or more application
server instances are non
functional
Different equations used if high availability is
required.
Excess
capacity for
unexpected
peaks
It is desirable to operate a
server at less than its
benchmarked peak, for
some safety margin
80% system capacity utilization at peak loads may
work for most installations. Measure your
deployment under real and simulated peak loads.
Further Information
1-8 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
2. Determine vertical scalability.
Determine how much additional performance you gain when you add processors.
That is, you are indirectly measuring the amount of shared resource contention
that occurs on the server for a specific workload. Either obtain this information
based on additional load testing of the application on a multiprocessor system, or
leverage existing information from a similar application that has already been load
tested.
Running a series of performance tests on one to eight CPUs, in incremental steps,
generally provides a sense of the vertical scalability characteristics of the system.
Be sure to properly tune the application, GlassFish Server, backend database
resources, and operating system so that they do not skew the results.
3. Determine horizontal scalability.
If sufficiently powerful hardware resources are available, a single hardware node
may meet the performance requirements. However for better availability, you can
cluster two or more systems. Employing external load balancers and workload
simulation, determine the performance benefits of replicating one well-tuned
application server node, as determined in step 2.
User Expectations
Application end-users generally have some performance expectations. Often you can
numerically quantify them. To ensure that customer needs are met, you must
understand these expectations clearly, and use them in capacity planning.
Consider the following questions regarding performance expectations:
■What do users expect the average response times to be for various interactions
with the application? What are the most frequent interactions? Are there any
extremely time-critical interactions? What is the length of each transaction,
including think time? In many cases, you may need to perform empirical user
studies to get good estimates.
■What are the anticipated steady-state and peak user loads? Are there are any
particular times of the day, week, or year when you observe or expect to observe
load peaks? While there may be several million registered customers for an online
business, at any one time only a fraction of them are logged in and performing
business transactions. A common mistake during capacity planning is to use the
total size of customer population as the basis and not the average and peak
numbers for concurrent users. The number of concurrent users also may exhibit
patterns over time.
■What is the average and peak amount of data transferred per request? This value
is also application-specific. Good estimates for content size, combined with other
usage patterns, will help you anticipate network capacity needs.
■What is the expected growth in user load over the next year? Planning ahead for
the future will help avoid crisis situations and system downtimes for upgrades.
Further Information
■For more information on Java performance, see Java Performance Documentation
(http://java.sun.com/docs/performance) and Java Performance
BluePrints
(http://java.sun.com/blueprints/performance/index.html).
Further Information
Overview of GlassFish Server Performance Tuning 1-9
■For more information about performance tuning for high availability
configurations, see the GlassFish Server Open Source Edition High Availability
Administration Guide.
■For complete information about using the Performance Tuning features available
through the GlassFish Server Administration Console, refer to the Administration
Console online help.
■For details on optimizing EJB components, see Seven Rules for Optimizing Entity
Beans
(http://java.sun.com/developer/technicalArticles/ebeans/seven
rules/)
■For details on profiling, see "Profiling Tools" in GlassFish Server Open Source Edition
Application Development Guide.
■To view a demonstration video showing how to use the GlassFish Server
Performance Tuner, see the Oracle GlassFish Server 3.1 - Performance Tuner demo
(http://www.youtube.com/watch?v=FavsE2pzAjc).
■To find additional Performance Tuning development information, see the
Performance Tuner in Oracle GlassFish Server 3.1
(http://blogs.oracle.com/jenblog/entry/performance_tuner_in_
oracle_glassfish) blog.
Further Information
1-10 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
2
Tuning Your Application 2-1
2Tuning Your Application
This chapter provides information on tuning applications for maximum performance.
A complete guide to writing high performance Java and Java EE applications is
beyond the scope of this document.
The following topics are addressed here:
■Java Programming Guidelines
■Java Server Page and Servlet Tuning
■EJB Performance Tuning
Java Programming Guidelines
This section covers issues related to Java coding and performance. The guidelines
outlined are not specific to GlassFish Server, but are general rules that are useful in
many situations. For a complete discussion of Java coding best practices, see the Java
Blueprints
(http://www.oracle.com/technetwork/java/javaee/blueprints/index.
html).
The following topics are addressed here:
■Avoid Serialization and Deserialization
■Use
StringBuilder
to Concatenate Strings
■Assign null to Variables That Are No Longer Needed
■Declare Methods as final Only If Necessary
■Declare Constants as static final
■Avoid Finalizers
■Declare Method Arguments final
■Synchronize Only When Necessary
■Use DataHandlers for SOAP Attachments
Avoid Serialization and Deserialization
Serialization and deserialization of objects is a CPU-intensive procedure and is likely
to slow down your application. Use the
transient
keyword to reduce the amount of
data serialized. Additionally, customized
readObject()
and
writeObject()
methods
may be beneficial in some cases.
Java Programming Guidelines
2-2 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Use
StringBuilder
to Concatenate Strings
To improve performance, instead of using string concatenation, use
StringBuilder.append()
.
String objects are immutable - that is, they never change after creation. For example,
consider the following code:
String str = "testing";
str = str + "abc";
str = str + "def";
The compiler translates this code as:
String str = "testing";
StringBuilder tmp = new StringBuilder(str);
tmp.append("abc");
str = tmp.toString();
StringBulder tmp = new StringBuilder(str);
tmp.append("def");
str = tmp.toString();
This copying is inherently expensive and overusing it can reduce performance
significantly. You are far better off writing:
StringBuilder tmp = new StringBuilder("testing");
tmp.append("abc");
tmp.append("def");
String str = tmp.toString();
Assign null to Variables That Are No Longer Needed
Explicitly assigning a null value to variables that are no longer needed helps the
garbage collector to identify the parts of memory that can be safely reclaimed.
Although Java provides memory management, it does not prevent memory leaks or
using excessive amounts of memory.
An application may induce memory leaks by not releasing object references. Doing so
prevents the Java garbage collector from reclaiming those objects, and results in
increasing amounts of memory being used. Explicitly nullifying references to variables
after their use allows the garbage collector to reclaim memory.
One way to detect memory leaks is to employ profiling tools and take memory
snapshots after each transaction. A leak-free application in steady state will show a
steady active heap memory after garbage collections.
Declare Methods as final Only If Necessary
Modern optimizing dynamic compilers can perform inlining and other
inter-procedural optimizations, even if Java methods are not declared
final
. Use the
keyword
final
as it was originally intended: for program architecture reasons and
maintainability.
Only if you are absolutely certain that a method must not be overridden, use the
final
keyword.
Declare Constants as static final
The dynamic compiler can perform some constant folding optimizations easily, when
you declare constants as
static final
variables.
Java Server Page and Servlet Tuning
Tuning Your Application 2-3
Avoid Finalizers
Adding finalizers to code makes the garbage collector more expensive and
unpredictable. The virtual machine does not guarantee the time at which finalizers are
run. Finalizers may not always be executed, before the program exits. Releasing
critical resources in
finalize()
methods may lead to unpredictable application
behavior.
Declare Method Arguments final
Declare method arguments
final
if they are not modified in the method. In general,
declare all variables
final
if they are not modified after being initialized or set to some
value.
Synchronize Only When Necessary
Do not synchronize code blocks or methods unless synchronization is required. Keep
synchronized blocks or methods as short as possible to avoid scalability bottlenecks.
Use the Java Collections Framework for unsynchronized data structures instead of
more expensive alternatives such as
java.util.HashTable
.
Use DataHandlers for SOAP Attachments
Using a
javax.activation.DataHandler
for a SOAP attachment will improve
performance.
JAX-RPC specifies:
■A mapping of certain MIME types to Java types.
■Any MIME type is mappable to a
javax.activation.DataHandler
.
As a result, send an attachment (
.gif
or XML document) as a SOAP attachment to an
RPC style web service by utilizing the Java type mappings. When passing in any of the
mandated Java type mappings (appropriate for the attachment's MIME type) as an
argument for the web service, the JAX-RPC runtime handles these as SOAP
attachments.
For example, to send out an
image/gif
attachment, use
java.awt.Image
, or create a
DataHandler
wrapper over your image. The advantages of using the wrapper are:
■Reduced coding: You can reuse generic attachment code to handle the attachments
because the
DataHandler
determines the content type of the contained data
automatically. This feature is especially useful when using a document style
service. Since the content is known at runtime, there is no need to make calls to
attachment.setContent(stringContent, "image/gif")
, for example.
■Improved Performance: Informal tests have shown that using
DataHandler
wrappers doubles throughput for
image/gif
MIME types, and multiplies
throughput by approximately 1.5 for
text/xml
or
java.awt.Image
for
image/*
types.
Java Server Page and Servlet Tuning
Many applications running on the GlassFish Server use servlets or JavaServer Pages
(JSP) technology in the presentation tier. This section describes how to improve
performance of such applications, both through coding practices and through
deployment and configuration settings.
Java Server Page and Servlet Tuning
2-4 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Suggested Coding Practices
This section provides some tips on coding practices that improve servlet and JSP
application performance.
The following topics are addressed here:
■General Guidelines
■Avoid Shared Modified Class Variables
■HTTP Session Handling
■Configuration and Deployment Tips
General Guidelines
Follow these general guidelines to increase performance of the presentation tier:
■Minimize Java synchronization in servlets.
■Do not use the single thread model for servlets.
■Use the servlet's
init()
method to perform expensive one-time initialization.
■Avoid using
System.out.println()
calls.
Avoid Shared Modified Class Variables
In the servlet multithread model (the default), a single instance of a servlet is created
for each application server instance. All requests for a servlet on that application
instance share the same servlet instance. This can lead to thread contention if there are
synchronization blocks in the servlet code. Therefore, avoid using shared modified
class variables because they create the need for synchronization.
HTTP Session Handling
Follow these guidelines when using HTTP sessions:
■Create sessions sparingly. Session creation is not free. If a session is not required,
do not create one.
■Use
javax.servlet.http.HttpSession.invalidate()
to release sessions when
they are no longer needed.
■Keep session size small, to reduce response times. If possible, keep session size
below 7 kilobytes.
■Use the directive
<%page session="false"%>
in JSP files to prevent the GlassFish
Server from automatically creating sessions when they are not necessary.
■Avoid large object graphs in an
HttpSession
. They force serialization and add
computational overhead. Generally, do not store large objects as
HttpSession
variables.
■Do not cache transaction data in an
HttpSession
. Access to data in an
HttpSession
is not transactional. Do not use it as a cache of transactional data,
which is better kept in the database and accessed using entity beans. Transactions
will rollback upon failures to their original state. However, stale and inaccurate
data may remain in
HttpSession
objects. GlassFish Server provides "read-only"
bean-managed persistence entity beans for cached access to read-only data.
EJB Performance Tuning
Tuning Your Application 2-5
Configuration and Deployment Tips
Follow these configuration tips to improve performance. These tips are intended for
production environments, not development environments.
■To improve class loading time, avoid having excessive directories in the server
CLASSPATH
. Put application-related classes into JAR files.
■HTTP response times are dependent on how the keep-alive subsystem and the
HTTP server is tuned in general. For more information, see HTTP Service Settings.
■Cache servlet results when possible. For more information, see "Developing Web
Applications" in GlassFish Server Open Source Edition Application Development Guide.
■If an application does not contain any EJB components, deploy the application as a
WAR file, not an EAR file.
Optimize SSL Optimize SSL by using routines in the appropriate operating system
library for concurrent access to heap space. The library to use depends on the version
of the Solaris Operating System (SolarisOS) that you are using. To ensure that you use
the correct library, set the
LD_PRELOAD
environment variable to specify the correct
library file. For more information, refer to the following table.
To set the
LD_PRELOAD
environment variable, edit the entry for this environment
variable in the
startserv
script. The
startserv
script is located is located in the
bin/startserv
directory of your domain.
The exact syntax to define an environment variable depends on the shell that you are
using.
Disable Security Manager The security manager is expensive because calls to required
resources must call the
doPrivileged()
method and must also check the resource with
the
server.policy
file. If you are sure that no malicious code will be run on the server
and you do not use authentication within your application, then you can disable the
security manager.
See "Enabling and Disabling the Security Manager" in GlassFish Server Open Source
Edition Application Development Guide for instructions on enabling or disabling the
security manager. If using the GlassFish Server Administration Console, navigate to
the Configurations>configuration-name>Security node and check or uncheck the
Security Manager option as desired. Refer to the Administration Console online help
for more information.
EJB Performance Tuning
The GlassFish Server's high-performance EJB container has numerous parameters that
affect performance. Individual EJB components also have parameters that affect
performance. The value of individual EJB component's parameter overrides the value
of the same parameter for the EJB container. The default values are designed for a
single-processor computer system. Modify these values as appropriate to optimize for
other system configurations.
The following topics are addressed here:
Solaris OS Version Library Setting of
LD_PRELOAD
Environment Variable
10
libumem3LIB /usr/lib/libumem.so
9
libmtmalloc3LIB /usr/lib/libmtmalloc.so
EJB Performance Tuning
2-6 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
■Goals
■Monitoring EJB Components
■General Guidelines
■Using Local and Remote Interfaces
■Improving Performance of EJB Transactions
■Using Special Techniques
■Tuning Tips for Specific Types of EJB Components
■JDBC and Database Access
■Tuning Message-Driven Beans
Goals
The goals of EJB performance tuning are:
■Increased speed: Cache as many beans in the EJB caches as possible to increase
speed (equivalently, decrease response time). Caching eliminates CPU-intensive
operations. However, since memory is finite, as the caches become larger,
housekeeping for them (including garbage collection) takes longer.
■Decreased memory consumption: Beans in the pools or caches consume memory
from the Java virtual machine heap. Very large pools and caches degrade
performance because they require longer and more frequent garbage collection
cycles.
■Improved functional properties: Functional properties such as user timeout,
commit options, security, and transaction options, are mostly related to the
functionality and configuration of the application. Generally, they do not
compromise functionality for performance. In some cases, you might be forced to
make a "trade-off" decision between functionality and performance. This section
offers suggestions in such cases.
Monitoring EJB Components
When the EJB container has monitoring enabled, you can examine statistics for
individual beans based on the bean pool and cache settings.
For example, the monitoring command below returns the Bean Cache statistics for a
stateful session bean.
asadmin get --user admin --host e4800-241-a --port 4848
-m specjcmp.application.SPECjAppServer.ejb-module.
supplier_jar.stateful-session-bean.BuyerSes.bean-cache.*
The following is a sample of the monitoring output:
resize-quantity = -1
cache-misses = 0
idle-timeout-in-seconds = 0
num-passivations = 0
cache-hits = 59
num-passivation-errors = 0
total-beans-in-cache = 59
num-expired-sessions-removed = 0
max-beans-in-cache = 4096
num-passivation-success = 0
EJB Performance Tuning
Tuning Your Application 2-7
The monitoring command below gives the bean pool statistics for an entity bean:
asadmin get --user admin --host e4800-241-a --port 4848
-m specjcmp.application.SPECjAppServer.ejb-module.
supplier_jar.stateful-entity-bean.ItemEnt.bean-pool.*
idle-timeout-in-seconds = 0
steady-pool-size = 0
total-beans-destroyed = 0
num-threads-waiting = 0
num-beans-in-pool = 54
max-pool-size = 2147483647
pool-resize-quantity = 0
total-beans-created = 255
The monitoring command below gives the bean pool statistics for a stateless bean.
asadmin get --user admin --host e4800-241-a --port 4848
-m
test.application.testEjbMon.ejb-module.slsb.stateless-session-bean.slsb.bean-pool.
*
idle-timeout-in-seconds = 200
steady-pool-size = 32
total-beans-destroyed = 12
num-threads-waiting = 0
num-beans-in-pool = 4
max-pool-size = 1024
pool-resize-quantity = 12
total-beans-created = 42
Tuning the bean involves charting the behavior of the cache and pool for the bean in
question over a period of time.
If too many passivations are happening and the JVM heap remains fairly small, then
the
max-cache-size
or the
cache-idle-timeout-in-seconds
can be increased. If
garbage collection is happening too frequently, and the pool size is growing, but the
cache hit rate is small, then the
pool-idle-timeout-in-seconds
can be reduced to
destroy the instances.
Monitoring Individual EJB Components
To gather method invocation statistics for all methods in a bean, use the following
command:
asadmin get -m monitorableObject.*
where monitorableObject is a fully-qualified identifier from the hierarchy of objects that
can be monitored, shown below.
serverInstance.application.applicationName.ejb-module.moduleName
where moduleName is
x_jar
for module
x.jar
.
■
.stateless-session-bean.beanName .bean-pool .bean-method.methodName
■
.stateful-session-bean.beanName .bean-cache .bean-method.methodName
Note: Specifying a
max-pool-size
of zero (0) means that the pool
is unbounded. The pooled beans remain in memory unless they are
removed by specifying a small interval for
pool-idle-timeout-in-seconds
. For production systems,
specifying the pool as unbounded is NOT recommended.
EJB Performance Tuning
2-8 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
■
.entity-bean.beanName .bean-cache .bean-pool .bean-method.methodName
■
.message-driven-bean.beanName .bean-pool .bean-method.methodName
(methodName = onMessage)
For standalone beans, use this pattern:
serverInstance.application.applicationName.standalone-ejb-module.moduleName
The possible identifiers are the same as for
ejb-module
.
For example, to get statistics for a method in an entity bean, use this command:
asadmin get -m serverInstance.application.appName.ejb-module.moduleName
.entity-bean.beanName.bean-method.methodName.*
For more information about administering the monitoring service in general, see
"Administering the Monitoring Service" in GlassFish Server Open Source Edition
Administration Guide. For information about viewing comprehensive EJB monitoring
statistics, see "EJB Statistics" in GlassFish Server Open Source Edition Administration
Guide.
To configure EJB monitoring using the GlassFish Server Administration Console,
navigate to the Configurations>configuration-name>Monitoring node. After
configuring monitoring, you can view monitoring statistics by navigating to the server
(Admin Server) node and then selecting the Monitor tab. Refer to the Administration
Console online help for instructions on each of these procedures.
Alternatively, to list EJB statistics, use the
asadmin list
subcommand. For more
information, see
list
(1).
For statistics on stateful session bean passivations, use this command:
asadmin get -m serverInstance.application.appName.ejb-module.moduleName
.stateful-session-bean.beanName.bean-cache.*
From the attribute values that are returned, use this command:
num-passivationsnum-passivation-errorsnum-passivation-success
General Guidelines
The following guidelines can improve performance of EJB components. Keep in mind
that decomposing an application into many EJB components creates overhead and can
degrade performance. EJB components are not simply Java objects. They are
components with semantics for remote call interfaces, security, and transactions, as
well as properties and methods.
Use High Performance Beans
Use high-performance beans as much as possible to improve the overall performance
of your application. For more information, see Tuning Tips for Specific Types of EJB
Components.
The types of EJB components are listed below, from the highest performance to the
lowest:
1. Stateless Session Beans and Message Driven Beans
2. Stateful Session Beans
3. Container Managed Persistence (CMP) entity beans configured as read-only
4. Bean Managed Persistence (BMP) entity beans configured as read-only
EJB Performance Tuning
Tuning Your Application 2-9
5. CMP beans
6. BMP beans
For more information about configuring high availability session persistence, see
"Configuring High Availability Session Persistence and Failover" in GlassFish Server
Open Source Edition High Availability Administration Guide. To configure EJB beans
using the GlassFish Server Administration Console, navigate to the
Configurations>configuration-name>EJB Container node and then refer to the
Administration Console online help for detailed instructions.
Use Caching
Caching can greatly improve performance when used wisely. For example:
■Cache EJB references: To avoid a JNDI lookup for every request, cache EJB
references in servlets.
■Cache home interfaces: Since repeated lookups to a home interface can be
expensive, cache references to
EJBHomes
in the
init()
methods of servlets.
■Cache EJB resources: Use
setSessionContext()
or
ejbCreate()
to cache bean
resources. This is again an example of using bean lifecycle methods to perform
application actions only once where possible. Remember to release acquired
resources in the
ejbRemove()
method.
Use the Appropriate Stubs
The stub classes needed by EJB applications are generated dynamically at runtime
when an EJB client needs them. This means that it is not necessary to generate the
stubs or retrieve the client JAR file when deploying an application with remote EJB
components. When deploying an application, it is no longer necessary to specify the
--retrieve
option, which can speed up deployment.
If you have a legacy rich-client application that directly uses the CosNaming service
(not a recommended configuration), then you must generate the stubs for your
application explicitly using RMIC. For more information, see the GlassFish Server Open
Source Edition Troubleshooting Guide for more details.
Remove Unneeded Stateful Session Beans
Removing unneeded stateful session beans avoids passivating them, which requires
disk operations.
Cache and Pool Tuning Tips
Follow these tips when using the EJB cache and pools to improve performance:
■Explicitly call
remove()
: Allow stateful session EJB components to be removed
from the container cache by explicitly calling of the
remove()
method in the client.
■Tune the entity EJB component's pool size: Entity Beans use both the EJB pool and
cache settings. Tune the entity EJB component's pool size to minimize the creation
and destruction of beans. Populating the pool with a non-zero steady size before
hand is useful for getting better response for initial requests.
■Cache bean-specific resources: Use the
setEntityContext()
method to cache bean
specific resources and release them using the
unSetEntityContext()
method.
■Load related data efficiently for container-managed relationships (CMRs). For
more information, see Pre-Fetching Container Managed Relationship (CMR)
Beans.
EJB Performance Tuning
2-10 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
■Identify read-only beans: Configure read-only entity beans for read only
operations. For more information, see Read-Only Entity Beans.
Using Local and Remote Interfaces
This section describes some considerations when EJB components are used by local
and remote clients.
Prefer Local Interfaces
An EJB component can have remote and local interfaces. Clients not located in the
same application server instance as the bean (remote clients) use the remote interface
to access the bean. Calls to the remote interface require marshalling arguments,
transportation of the marshalled data over the network, un-marshaling the arguments,
and dispatch at the receiving end. Thus, using the remote interface entails significant
overhead.
If an EJB component has a local interface, then local clients in the same application
server instance can use it instead of the remote interface. Using the local interface is
more efficient, since it does not require argument marshalling, transportation, and
un-marshalling.
If a bean is to be used only by local clients then it makes sense to provide only the local
interface. If, on the other hand, the bean is to be location-independent, then you
should provide both the remote and local interfaces so that remote clients use the
remote interface and local clients can use the local interface for efficiency.
Using Pass-By-Reference Semantics
By default, the GlassFish Server uses pass-by-value semantics for calling the remote
interface of a bean, even if it is co-located. This can be expensive, since clients using
pass-by-value semantics must copy arguments before passing them to the EJB
component.
However, local clients can use pass-by-reference semantics and thus the local and
remote interfaces can share the passed objects. But this means that the argument
objects must be implemented properly, so that they are shareable. In general, it is more
efficient to use pass-by-reference semantics when possible.
Using the remote and local interfaces appropriately means that clients can access EJB
components efficiently. That is, local clients use the local interface with
pass-by-reference semantics, while remote clients use the remote interface with
pass-by-value semantics.
However, in some instances it might not be possible to use the local interface, for
example when:
■The application predates the EJB 2.0 specification and was written without any
local interfaces.
■There are bean-to-bean calls and the client beans are written without making any
co-location assumptions about the called beans.
For these cases, the GlassFish Server provides a pass-by-reference option that clients
can use to pass arguments by reference to the remote interface of a co-located EJB
component.
You can specify the pass-by-reference option for an entire application or a single EJB
component. When specified at the application level, all beans in the application use
pass-by-reference semantics when passing arguments to their remote interfaces. When
specified at the bean level, all calls to the remote interface of the bean use
EJB Performance Tuning
Tuning Your Application 2-11
pass-by-reference semantics. See "Value Added Features" in GlassFish Server Open
Source Edition Application Development Guide for more details about the
pass-by-reference flag.
To specify that an EJB component will use pass by reference semantics, use the
following tag in the
sun-ejb-jar.xml
deployment descriptor:
<pass-by-reference>true</pass-by-reference>
This avoids copying arguments when the EJB component's methods are invoked and
avoids copying results when methods return. However, problems will arise if the data
is modified by another source during the invocation.
Improving Performance of EJB Transactions
This section provides some tips to improve performance when using transactions.
The following topics are addressed here:
■Use Container-Managed Transactions
■Do Not Encompass User Input Time
■Identify Non-Transactional Methods
■Use
TX_REQUIRED
for Long Transaction Chains
■Use Lowest Cost Database Locking
■Use XA-Capable Data Sources Only When Needed
■Configure JDBC Resources as One-Phase Commit Resources
■Use the Least Expensive Transaction Attribute
Use Container-Managed Transactions
Container-managed transactions are preferred for consistency, and provide better
performance.
Do Not Encompass User Input Time
To avoid resources being held unnecessarily for long periods, a transaction should not
encompass user input or user think time.
Identify Non-Transactional Methods
Declare non-transactional methods of session EJB components with
NotSupported
or
Never
transaction attributes. These attributes can be found in the
ejb-jar.xml
deployment descriptor file. Transactions should span the minimum time possible since
they lock database rows.
Use
TX_REQUIRED
for Long Transaction Chains
For very large transaction chains, use the transaction attribute
TX_REQUIRED.
To ensure
EJB methods in a call chain, use the same transaction.
Use Lowest Cost Database Locking
Use the lowest cost locking available from the database that is consistent with any
transaction. Commit the data after the transaction completes rather than after each
method call.
EJB Performance Tuning
2-12 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Use XA-Capable Data Sources Only When Needed
When multiple database resources, connector resources or JMS resources are involved
in one transaction, a distributed or global transaction needs to be performed. This
requires XA capable resource managers and data sources. Use XA capable data
sources, only when two or more data source are going to be involved in a transaction.
If a database participates in some distributed transactions, but mostly in local or single
database transactions, it is advisable to register two separate JDBC resources and use
the appropriate resource in the application.
Configure JDBC Resources as One-Phase Commit Resources
To improve performance of transactions involving multiple resources, the GlassFish
Server uses last agent optimization (LAO), which allows the configuration of one of
the resources in a distributed transaction as a one-phase commit (1PC) resource. Since
the overhead of multiple-resource transactions is much higher for a JDBC resource
than a message queue, LAO substantially improves performance of distributed
transactions involving one JDBC resource and one or more message queues. To take
advantage of LAO, configure a JDBC resource as a 1PC resource. Nothing special
needs to be done to configure JMS resources.
In global transactions involving multiple JDBC resources, LAO will still improve
performance, however, not as much as for one JDBC resource. In this situation, one of
the JDBC resources should be configured as 1PC, and all others should be configured
as XA.
Use the Least Expensive Transaction Attribute
Set the following transaction attributes in the EJB deployment descriptor file
(
ejb-jar.xml
). Options are listed from best performance to worst. To improve
performance, choose the least expensive attribute that will provide the functionality
your application needs:
1.
NEVER
2.
TX_NOTSUPPORTED
3.
TX_MANDATORY
4.
TX_SUPPORTS
5.
TX_REQUIRED
6.
TX_REQUIRESNEW
Using Special Techniques
Special performance-enhancing techniques are discussed in the following sections:
■Version Consistency
■Request Partitioning
Version Consistency
Note: The technique in section applies only to the EJB 2.1
architecture. In the EJB 3.0 architecture, use the Java Persistence
API (JPA).
EJB Performance Tuning
Tuning Your Application 2-13
Use version consistency to improve performance while protecting the integrity of data
in the database. Since the application server can use multiple copies of an EJB
component simultaneously, an EJB component's state can potentially become
corrupted through simultaneous access.
The standard way of preventing corruption is to lock the database row associated with
a particular bean. This prevents the bean from being accessed by two simultaneous
transactions and thus protects data. However, it also decreases performance, since it
effectively serializes all EJB access.
Version consistency is another approach to protecting EJB data integrity. To use
version consistency, you specify a column in the database to use as a version number.
The EJB lifecycle then proceeds like this:
■The first time the bean is used, the
ejbLoad()
method loads the bean as normal,
including loading the version number from the database.
■The
ejbStore()
method checks the version number in the database versus its
value when the EJB component was loaded.
–If the version number has been modified, it means that there has been
simultaneous access to the EJB component and
ejbStore()
throws a
ConcurrentModificationException
.
–Otherwise,
ejbStore()
stores the data and completes as normal.
The
ejbStore()
method performs this validation at the end of the transaction
regardless of whether any data in the bean was modified.
Subsequent uses of the bean behave similarly, except that the
ejbLoad()
method loads
its initial data (including the version number) from an internal cache. This saves a trip
to the database. When the
ejbStore()
method is called, the version number is checked
to ensure that the correct data was used in the transaction.
Version consistency is advantageous when you have EJB components that are rarely
modified, because it allows two transactions to use the same EJB component at the
same time. Because neither transaction modifies the data, the version number is
unchanged at the end of both transactions, and both succeed. But now the transactions
can run in parallel. If two transactions occasionally modify the same EJB component,
one will succeed and one will fail and can be retried using the new values—which can
still be faster than serializing all access to the EJB component if the retries are
infrequent enough (though now your application logic has to be prepared to perform
the retry operation).
To use version consistency, the database schema for a particular table must include a
column where the version can be stored. You then specify that table in the
sun-cmp-mapping.xml
deployment descriptor for a particular bean:
<entity-mapping>
<cmp-field-mapping>
...
</cmp-field-mapping>
<consistency>
<check-version-of-accessed-instances>
<column-name>OrderTable.VC_VERSION_NUMBER</column-name>
</check-version-of-accessed-instances>
</consistency>
</entity-mapping>
In addition, you must establish a trigger on the database to automatically update the
version column when data in the specified table is modified. The GlassFish Server
requires such a trigger to use version consistency. Having such a trigger also ensures
EJB Performance Tuning
2-14 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
that external applications that modify the EJB data will not conflict with EJB
transactions in progress.
For example, the following DDL illustrates how to create a trigger for the
Order
table:
CREATE TRIGGER OrderTrigger
BEFORE UPDATE ON OrderTable
FOR EACH ROW
WHEN (new.VC_VERSION_NUMBER = old.VC_VERSION_NUMBER)
DECLARE
BEGIN
:NEW.VC_VERSION_NUMBER := :OLD.VC_VERSION_NUMBER + 1;
END;
Request Partitioning
Request partitioning enables you to assign a request priority to an EJB component. This
gives you the flexibility to make certain EJB components execute with higher priorities
than others.
An EJB component which has a request priority assigned to it will have its requests
(services) executed within an assigned threadpool. By assigning a threadpool to its
execution, the EJB component can execute independently of other pending requests. In
short, request partitioning enables you to meet service-level agreements that have
differing levels of priority assigned to different services.
Request partitioning applies only to remote EJB components (those that implement a
remote interface). Local EJB components are executed in their calling thread (for
example, when a servlet calls a local bean, the local bean invocation occurs on the
servlet's thread).
To Enable Request Partitioning Follow this procedure.
1. Configure additional threadpools for EJB execution.
Using the GlassFish Server Administration Console, navigate to the
Configurations>configuration-name>Thread Pools node. Refer to the
Administration Console online help for more information. Alternatively, you can
follow the instructions in "Administering Thread Pools" in GlassFish Server Open
Source Edition Administration Guide.
Configure the threadpools as follows:
a. Add the additional threadpool IDs to the GlassFish Server's ORB.
This can be done on the Configurations>configuration-name>ORB node in the
Administration Console.
For example, enable threadpools named
priority-1
and
priority-2
to the
<orb>
element as follows:
<orb max-connections="1024" message-fragment-size="1024"
use-thread-pool-ids="thread-pool-1,priority-1,priority-2">
b. Include the threadpool ID in the
use-thread-pool-id
element of the EJB
component's
sun-ejb-jar.xml
deployment descriptor.
For example, the following
sun-ejb-jar.xml
deployment descriptor for an
EJB component named "
TheGreeter
" is assigned to a thread pool named
priority-2
:
<sun-ejb-jar>
EJB Performance Tuning
Tuning Your Application 2-15
<enterprise-beans>
<unique-id>1</unique-id>
<ejb>
<ejb-name>TheGreeter</ejb-name>
<jndi-name>greeter</jndi-name>
<use-thread-pool-id>priority-1</use-thread-pool-id>
</ejb>
</enterprise-beans>
</sun-ejb-jar>
2. Restart the GlassFish Server.
Tuning Tips for Specific Types of EJB Components
This section provides tips for tuning various specific types of EJB components:
■Entity Beans
■Stateful Session Beans
■Stateless Session Beans
■Read-Only Entity Beans
■Pre-Fetching Container Managed Relationship (CMR) Beans
These components can all be configured in the GlassFish Server Administration
Console from the Configurations>configuration-name>EJB Container node.
Alternatively, you can perform these configurations by following the instructions in
"RMI-IIOP Load Balancing and Failover" in GlassFish Server Open Source Edition High
Availability Administration Guide.
Entity Beans
Depending on the usage of a particular entity bean, one should tune
max-cache-size
so that the beans that are used less frequently (for example, an order that is created
and never used after the transaction is over) are cached less, and beans that are used
frequently (for example, an item in the inventory that gets referenced very often), are
cached more.
Stateful Session Beans
When a stateful bean represents a user, a reasonable
max-cache-size
of beans is the
expected number of concurrent users on the application server process. If this value is
too low (in relation to the steady load of users), beans would be frequently passivated
and activated, causing a negative impact on the response times, due to CPU intensive
serialization and deserialization as well as disk I/O.
Another important variable for tuning is
cache-idle-timeout-in-seconds
where at
periodic intervals of
cache-idle-timeout-in-seconds
, all the beans in the cache that
have not been accessed for more than
cache-idle-timeout-in-seconds
time, are
passivated. Similar to an HTTP session timeout, the bean is removed after it has not
been accessed for
removal-timeout-in-seconds
. Passivated beans are stored on disk
in serialized form. A large number of passivated beans could not only mean many files
on the disk system, but also slower response time as the session state has to be
de-serialized before the invocation.
Checkpoint only when needed In high availability mode, when using stateful session
beans, consider checkpointing only those methods that alter the state of the bean
EJB Performance Tuning
2-16 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
significantly. This reduces the number of times the bean state has to be checkpointed
into the persistent store.
Stateless Session Beans
Stateless session beans are more readily pooled than entity or the stateful session
beans. Valid values for
steady-pool-size
,
pool-resize-quantity
and
max-pool-size
are the best tunables for these type of beans. Set the
steady-pool-size
to greater than
zero if you want to pre-populate the pool. This way, when the container comes up, it
creates a pool with
steady-pool-size
number of beans. By pre-populating the pool it
is possible to avoid the object creation time during method invocations.
Setting the
steady-pool size
to a very large value can cause unwanted memory
growth and can result in large garbage collection times.
pool-resize-quantity
determines the rate of growth as well as the rate of decay of the pool. Setting it to a
small value is better as the decay behaves like an exponential decay. Setting a small
max-pool-size
can cause excessive object destruction (and as a result excessive object
creation) as instances are destroyed from the pool if the current pool size exceeds
max-pool-size
.
Read-Only Entity Beans
Read-only entity beans cache data from the database. GlassFish Server supports
read-only beans that use both bean-managed persistence (BMP) and
container-managed persistence (CMP). Of the two types, CMP read-only beans
provide significantly better performance. In the EJB lifecycle, the EJB container calls
the
ejbLoad()
method of a read-only bean once. The container makes multiple copies
of the EJB component from that data, and since the beans do not update the database,
the container never calls the
ejbStore()
method. This greatly reduces database traffic
for these beans.
If there is a bean that never updates the database, use a read-only bean in its place to
improve performance. A read-only bean is appropriate if either:
■Database rows represented by the bean do not change.
■The application can tolerate using out-of-date values for the bean.
For example, an application might use a read-only bean to represent a list of best-seller
books. Although the list might change occasionally in the database (say, from another
bean entirely), the change need not be reflected immediately in an application.
The
ejbLoad()
method of a read-only bean is handled differently for CMP and BMP
beans. For CMP beans, the EJB container calls
ejbLoad()
only once to load the data
from the database; subsequent uses of the bean just copy that data. For BMP beans, the
EJB container calls
ejbLoad()
the first time a bean is used in a transaction. Subsequent
uses of that bean within the transaction use the same values. The container calls
ejbLoad()
for a BMP bean that doesn't run within a transaction every time the bean is
used. Therefore, read-only BMP beans still make a number of calls to the database.
To create a read-only bean, add the following to the EJB deployment descriptor
sun-ejb-jar.xml
:
<is-read-only-bean>true</is-read-only-bean>
<refresh-period-in-seconds>600</refresh-period-in-seconds>
Refresh Period An important parameter for tuning read-only beans is the refresh
period, represented by the deployment descriptor entity
refresh-period-in-seconds
.
For CMP beans, the first access to a bean loads the bean's state. The first access after
EJB Performance Tuning
Tuning Your Application 2-17
the refresh period reloads the data from the database. All subsequent uses of the bean
uses the newly refreshed data (until another refresh period elapses). For BMP beans,
an
ejbLoad()
method within an existing transaction uses the cached data unless the
refresh period has expired (in which case, the container calls
ejbLoad()
again).
This parameter enables the EJB component to periodically refresh its "snapshot" of the
database values it represents. If the refresh period is less than or equal to 0, the bean is
never refreshed from the database (the default behavior if no refresh period is given).
Pre-Fetching Container Managed Relationship (CMR) Beans
If a container-managed relationship (CMR) exists in your application, loading one
bean will load all its related beans. The canonical example of CMR is an
order-orderline relationship where you have one
Order
EJB component that has
related
OrderLine
EJB components. In previous releases of the application server, to
use all those beans would require multiple database queries: one for the
Order
bean
and one for each of the
OrderLine
beans in the relationship.
In general, if a bean has n relationships, using all the data of the bean would require
n+1 database accesses. Use CMR pre-fetching to retrieve all the data for the bean and
all its related beans in one database access.
For example, you have this relationship defined in the
ejb-jar.xml
file:
<relationships>
<ejb-relation>
<description>Order-OrderLine</description>
<ejb-relation-name>Order-OrderLine</ejb-relation-name>
<ejb-relationship-role>
<ejb-relationship-role-name>
Order-has-N-OrderLines
</ejb-relationship-role-name>
<multiplicity>One</multiplicity>
<relationship-role-source>
<ejb-name>OrderEJB</ejb-name>
</relationship-role-source>
<cmr-field>
<cmr-field-name>orderLines</cmr-field-name>
<cmr-field-type>java.util.Collection</cmr-field-type>
</cmr-field>
</ejb-relationship-role>
</ejb-relation>
</relationships>
When a particular
Order
is loaded, you can load its related
OrderLines
by adding this
to the
sun-cmp-mapping.xml
file for the application:
<entity-mapping>
<ejb-name>Order</ejb-name>
<table-name>...</table-name>
<cmp-field-mapping>...</cmp-field-mapping>
<cmr-field-mapping>
<cmr-field-name>orderLines</cmr-field-name>
<column-pair>
<column-name>OrderTable.OrderID</column-name>
<column-name>OrderLineTable.OrderLine_OrderID</column-name>
</column-pair>
<fetched-with>
<default>
</fetched-with>
</cmr-field-mapping>
EJB Performance Tuning
2-18 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
</entity-mappping>
Now when an
Order
is retrieved, the CMP engine issues SQL to retrieve all related
OrderLines
with a
SELECT
statement that has the following
WHERE
clause:
OrderTable.OrderID = OrderLineTable.OrderLine_OrderID
This clause indicates an outer join. These
OrderLines
are pre-fetched.
Pre-fetching generally improves performance because it reduces the number of
database accesses. However, if the business logic often uses
Orders
without
referencing their
OrderLines
, then this can have a performance penalty, that is, the
system has spent the effort to pre-fetch the
OrderLines
that are not actually needed.
Avoid pre-fetching for specific finder methods; this can often avoid that penalty. For
example, consider an order bean has two finder methods: a
findByPrimaryKey
method
that uses the
Orderlines
, and a
findByCustomerId
method that returns only order
information and therefore does not use the
Orderlines
. If you have enabled CMR
pre-fetching for the
Orderlines
, both finder methods will pre-fetch the
Orderlines
.
However, you can prevent pre-fetching for the
findByCustomerId
method by
including this information in the
sun-ejb-jar.xml
descriptor:
<ejb>
<ejb-name>OrderBean</ejb-name>
...
<cmp>
<prefetch-disabled>
<query-method>
<method-name>findByCustomerId</method-name>
</query-method>
</prefetch-disabled>
</cmp>
</ejb>
JDBC and Database Access
The following are some tips to improve the performance of database access:
■Use JDBC Directly
■Encapsulate Business Logic in Entity EJB Components
■Close Connections
■Minimize the Database Transaction Isolation Level
Use JDBC Directly
When dealing with large amounts of data, such as searching a large database, use
JDBC directly rather than using Entity EJB components.
Encapsulate Business Logic in Entity EJB Components
Combine business logic with the Entity EJB component that holds the data needed for
that logic to process.
Close Connections
To ensure that connections are returned to the pool, always close the connections after
use.
EJB Performance Tuning
Tuning Your Application 2-19
Minimize the Database Transaction Isolation Level
Use the default isolation level provided by the JDBC driver rather than calling
setTransactionIsolationLevel()
, unless you are certain that your application
behaves correctly and performs better at a different isolation level.
Reduce the database transaction isolation level when appropriate. Reduced isolation
levels reduce work in the database tier, and could lead to better application
performance. However, this must be done after carefully analyzing the database table
usage patterns.
To set the database transaction isolation level using the GlassFish Server
Administration Console, navigate to the Resources>JDBC>JDBC Connection
Pools>pool-name node. Refer to the Administration Console online help for complete
instructions. Alternatively, follow the instructions in "Administering Database
Connectivity" in GlassFish Server Open Source Edition Administration Guide. For more
information on tuning JDBC connection pools, see JDBC Connection Pool Settings.
Tuning Message-Driven Beans
This section provides some tips to improve performance when using JMS with
message-driven beans (MDBs).
Use
getConnection()
JMS connections are served from a connection pool. This means that calling
getConnection()
on a Queue connection factory is fast.
Tune the Message-Driven Bean's Pool Size
The container for message-driven beans (MDB) is different than the containers for
entity and session beans. In the MDB container, sessions and threads are attached to
the beans in the MDB pool. This design makes it possible to pool the threads for
executing message-driven requests in the container.
Tune the Message-Driven bean's pool size to optimize the concurrent processing of
messages. Set the size of the MDB pool to, based on all the parameters of the server
(taking other applications into account). For example, a value greater than 500 is
generally too large.
To configure MDB pool settings in the GlassFish Server Administration Console,
navigate to the Configurations>configuration-name>EJB Container node and then select
the MDB Settings tab. Refer to the Administration Console online help for more
information. Alternatively, you can set the MDB pool size by using the following
asadmin set
subcommand:
asadmin set server.mdb-container.max-pool-size = value
Cache Bean-Specific Resources
Use the
setMessageDrivenContext()
or
ejbCreate()
method to cache bean specific
resources, and release those resources from the
ejbRemove()
method.
Limit Use of JMS Connections
When designing an application that uses JMS connections make sure you use a
methodology that sparingly uses connections, by either pooling them or using the
same connection for multiple sessions.
EJB Performance Tuning
2-20 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
The JMS connection uses two threads and the sessions use one thread each. Since these
threads are not taken from a pool and the resultant objects aren't pooled, you could
run out of memory during periods of heavy usage.
One workaround is to move
createTopicConnection
into the
init
of the servlet.
Make sure to specifically close the session, or it will stay open, which ties up resources.
3
Tuning the GlassFish Server 3-1
3Tuning the GlassFish Server
This chapter describes some ways to tune your GlassFish Server installation for
optimum performance.
Note that while this chapter describes numerous interactions with both the GlassFish
Server Administration Console and the command-line interface, it is not intended to
provide exhaustive descriptions of either. For complete information about using the
Administration Console, refer to the Administration Console online help. For complete
information about using the GlassFish Server command-line interface, refer to the
other titles in the GlassFish Server documentation set at
http://download.oracle.com/docs/cd/E18930_01/index.htm.
The following topics are addressed here:
■Using the GlassFish Server Performance Tuner
■Deployment Settings
■Logger Settings
■Web Container Settings
■EJB Container Settings
■Java Message Service Settings
■Transaction Service Settings
■HTTP Service Settings
■Network Listener Settings
■Transport Settings
■Thread Pool Settings
■ORB Settings
■Resource Settings
■Load Balancer Settings
Using the GlassFish Server Performance Tuner
You can significantly improve the performance of GlassFish Server and the
applications deployed on it by adjusting a few deployment and server configuration
settings. These changes can be made manually, as described in this chapter, or by
using the built-in Performance Tuner in the GlassFish Server Administration Console.
The Performance Tuner recommends server settings to suit the needs of your
GlassFish Server deployment. It helps you reach an optimal configuration, although
Deployment Settings
3-2 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
finer tuning might be needed in case of specific requirements. You can configure
performance tuning for the entire domain, or for individual GlassFish Server instances
or clusters. The Tuner performs a static analysis of GlassFish Server resources and
throughput requirements. Note that no dynamic inspection of the system is
performed.
For complete information about using the Performance Tuning features available
through the GlassFish Server Administration Console, refer to the Administration
Console online help. You may also want to refer to the following resources for
additional information:
■To view a demonstration video showing how to use the GlassFish Server
Performance Tuner, see the Oracle GlassFish Server 3.1 - Performance Tuner demo
(http://www.youtube.com/watch?v=FavsE2pzAjc).
■To find additional Performance Tuning development information, see the
Performance Tuner in Oracle GlassFish Server 3.1
(http://blogs.oracle.com/jenblog/entry/performance_tuner_in_
oracle_glassfish) blog.
Deployment Settings
Deployment settings can have significant impact on performance. Follow these
guidelines when configuring deployment settings for best performance:
■Disable Auto-Deployment
■Use Pre-compiled JavaServer Pages
■Disable Dynamic Application Reloading
Disable Auto-Deployment
Enabling auto-deployment will adversely affect deployment, though it is a
convenience in a development environment. For a production system, disable
auto-deploy to optimize performance. If auto-deployment is enabled, then the Reload
Poll Interval setting can have a significant performance impact.
To enable or disable auto-deployment from the GlassFish Server Administration
Console, navigate to the Domain node and then click the Applications Configuration
tab. Refer to the Administration Console for further instructions. Alternatively, refer to
"To Deploy an Application or Module Automatically" in GlassFish Server Open Source
Edition Application Deployment Guide for instructions on enabling or disabling
auto-deployment.
Use Pre-compiled JavaServer Pages
Compiling JSP files is resource intensive and time consuming. Pre-compiling JSP files
before deploying applications on the server will improve application performance.
When you do so, only the resulting servlet class files will be deployed.
You can specify to precompile JSP files when you deploy an application through the
Administration Console or
deploy
subcommand. You can also specify to pre-compile
JSP files for a deployed application with the Administration Console. Navigate to the
Domain node and then click the Applications Configuration tab. Refer to the
Administration Console for further instructions.
Web Container Settings
Tuning the GlassFish Server 3-3
Disable Dynamic Application Reloading
If dynamic reloading is enabled, the server periodically checks for changes in
deployed applications and automatically reloads the application with the changes.
Dynamic reloading is intended for development environments and is also
incompatible with session persistence. To improve performance, disable dynamic class
reloading.
You can use the Administration Console to disable dynamic class reloading for an
application that is already deployed. Navigate to the Domain node and then click the
Applications Configuration tab. Refer to the Administration Console for further
instructions.
Logger Settings
The GlassFish Server produces writes log messages and exception stack trace output to
the log file in the logs directory of the instance, domain-dir
/logs
. The volume of log
activity can impact server performance; particularly in benchmarking situations.
General Settings
In general, writing to the system log slows down performance slightly; and increased
disk access (increasing the log level, decreasing the file rotation limit or time limit) also
slows down the application.
Also, make sure that any custom log handler does not log to a slow device like a
network file system since this can adversely affect performance.
Log Levels
Set the log level for the server and its subsystems in the GlassFish Server
Administration Console. Navigate to the Configurations>configuration-name>Logger
Settings page, and follow the instructions in the online help. Alternatively, you can
configure logging by following the instructions in "Administering the Logging
Service" in GlassFish Server Open Source Edition Administration Guide.
Web Container Settings
Set Web container settings in the GlassFish Server Administration Console by
navigating to the Configurations>configuration-name>Web Container node. Follow the
instructions in the online help for more information. Alternatively, you can configure
Web container settings by following the instructions in "Administering Web
Applications" in GlassFish Server Open Source Edition Administration Guide.
■Session Properties: Session Timeout
■Manager Properties: Reap Interval
■Disable Dynamic JSP Reloading
Session Properties: Session Timeout
Session timeout determines how long the server maintains a session if a user does not
explicitly invalidate the session. The default value is 30 minutes. Tune this value
according to your application requirements. Setting a very large value for session
timeout can degrade performance by causing the server to maintain too many sessions
in the session store. However, setting a very small value can cause the server to
reclaim sessions too soon.
EJB Container Settings
3-4 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Manager Properties: Reap Interval
Modifying the reap interval can improve performance, but setting it without
considering the nature of your sessions and business logic can cause data
inconsistency, especially for time-based persistence-frequency.
For example, if you set the reap interval to 60 seconds, the value of session data will be
recorded every 60 seconds. But if a client accesses a servlet to update a value at 20
second increments, then inconsistencies will result.
For example, consider the following online auction scenario:
■Bidding starts at $5, in 60 seconds the value recorded will be $8 (three 20 second
intervals).
■During the next 40 seconds, the client starts incrementing the price. The value the
client sees is $10.
■During the client's 20 second rest, the GlassFish Server stops and starts in 10
seconds. As a result, the latest value recorded at the 60 second interval ($8) is be
loaded into the session.
■The client clicks again expecting to see $11; but instead sees is $9, which is
incorrect.
■So, to avoid data inconsistencies, take into the account the expected behavior of
the application when adjusting the reap interval.
Disable Dynamic JSP Reloading
On a production system, improve web container performance by disabling dynamic
JSP reloading. To do so, edit the
default-web.xml
file in the
config
directory for each
instance. Change the servlet definition for a JSP file to look like this:
<servlet>
<servlet-name>jsp</servlet-name>
<servlet-class>org.apache.jasper.servlet.JspServlet</servlet-class>
<init-param>
<param-name>development</param-name>
<param-value>false</param-value>
</init-param>
<init-param>
<param-name>xpoweredBy</param-name>
<param-value>true</param-value>
</init-param>
<init-param>
<param-name>genStrAsCharArray</param-name>
<param-value>true</param-value>
</init-param> <load-on-startup>3</load-on-startup>
</servlet>
EJB Container Settings
The EJB Container has many settings that affect performance. As with other areas, use
monitor the EJB Container to track its execution and performance.
You can configure most EJB container settings from the GlassFish Server
Administration Console by navigating to the Configurations>configuration-name>EJB
Container node and then following the instructions in the online help.
EJB Container Settings
Tuning the GlassFish Server 3-5
Monitoring the EJB Container
Monitoring the EJB container is disabled by default. You can enable EJB monitoring
through the GlassFish Server Administration Console by navagating to the the
Configurations>configuration-name>Monitoring node and then following the
instructions in the online help. Set the monitoring level to LOW for to monitor all
deployed EJB components, EJB pools, and EJB caches. Set the monitoring level to
HIGH to also monitor EJB business methods.
Tuning the EJB Container
The EJB container caches and pools EJB components for better performance. Tuning
the cache and pool properties can provide significant performance benefits to the EJB
container.
The pool settings are valid for stateless session and entity beans while the cache
settings are valid for stateful session and entity beans.
The following topics are addressed here:
■Overview of EJB Pooling and Caching
■Tuning the EJB Pool
■Tuning the EJB Cache
■Pool and Cache Settings for Individual EJB Components
■Commit Option
Overview of EJB Pooling and Caching
Both stateless session beans and entity beans can be pooled to improve server
performance. In addition, both stateful session beans and entity beans can be cached to
improve performance.
The difference between a pooled bean and a cached bean is that pooled beans are all
equivalent and indistinguishable from one another. Cached beans, on the contrary,
contain conversational state in the case of stateful session beans, and are associated
with a primary key in the case of entity beans. Entity beans are removed from the pool
and added to the cache on
ejbActivate()
and removed from the cache and added to
the pool on
ejbPassivate()
.
ejbActivate()
is called by the container when a needed
entity bean is not in the cache.
ejbPassivate()
is called by the container when the
cache grows beyond its configured limits.
Table 3–1 Bean Type Pooling or Caching
Bean Type Pooled Cached
Stateless Session Yes No
Stateful Session No Yes
Entity Yes Yes
Note: If you develop and deploy your EJB components using
Oracle Java Studio, then you need to edit the individual bean
descriptor settings for bean pool and bean cache. These settings
might not be suitable for production-level deployment.
EJB Container Settings
3-6 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Tuning the EJB Pool
A bean in the pool represents the pooled state in the EJB lifecycle. This means that the
bean does not have an identity. The advantage of having beans in the pool is that the
time to create a bean can be saved for a request. The container has mechanisms that
create pool objects in the background, to save the time of bean creation on the request
path.
Stateless session beans and entity beans use the EJB pool. Keeping in mind how you
use stateless session beans and the amount of traffic your server handles, tune the pool
size to prevent excessive creation and deletion of beans.
EJB Pool Settings An individual EJB component can specify cache settings that override
those of the EJB container in the
<bean-pool>
element of the EJB component's
sun-ejb-jar.xml
deployment descriptor.
The EJB pool settings are:
■Initial and Minimum Pool Size: the initial and minimum number of beans
maintained in the pool. Valid values are from 0 to
MAX_INTEGER,
and the default
value is 8. The corresponding EJB deployment descriptor attribute is
steady-pool-size.
Set this property to a number greater than zero for a moderately loaded system.
Having a value greater than zero ensures that there is always a pooled instance to
process an incoming request.
■Maximum Pool Size: the maximum number of connections that can be created to
satisfy client requests. Valid values are from zero to
MAX_INTEGER
., and the default
is 32. A value of zero means that the size of the pool is unbounded. The potential
implication is that the JVM heap will be filled with objects in the pool. The
corresponding EJB deployment descriptor attribute is
max-pool-size
.
Set this property to be representative of the anticipated high load of the system.
An very large pool wastes memory and can slow down the system. A very small
pool is also inefficient due to contention.
■Pool Resize Quantity: the number of beans to be created or deleted when the
cache is being serviced by the server. Valid values are from zero to
MAX_INTEGER
and default is 16. The corresponding EJB deployment descriptor attribute is
resize-quantity
.
Be sure to re-calibrate the pool resize quantity when you change the maximum
pool size, to maintain an equilibrium. Generally, a larger maximum pool size
should have a larger pool resize quantity.
■Pool Idle Timeout: the maximum time that a stateless session bean, entity bean, or
message-driven bean is allowed to be idle in the pool. After this time, the bean is
destroyed if the bean in case is a stateless session bean or a message driver bean.
This is a hint to server. The default value is 600 seconds. The corresponding EJB
deployment descriptor attribute is
pool-idle-timeout-in-seconds
.
If there are more beans in the pool than the maximum pool size, the pool drains
back to initial and minimum pool size, in steps of pool resize quantity at an
interval specified by the pool idle timeout. If the resize quantity is too small and
the idle timeout large, you will not see the pool draining back to steady size
quickly enough.
EJB Container Settings
Tuning the GlassFish Server 3-7
Tuning the EJB Cache
A bean in the cache represents the ready state in the EJB lifecycle. This means that the
bean has an identity (for example, a primary key or session ID) associated with it.
Beans moving out of the cache have to be passivated or destroyed according to the EJB
lifecycle. Once passivated, a bean has to be activated to come back into the cache.
Entity beans are generally stored in databases and use some form of query language
semantics to load and store data. Session beans have to be serialized when storing
them upon passivation onto the disk or a database; and similarly have to be
deserialized upon activation.
Any incoming request using these "ready" beans from the cache avoids the overhead
of creation, setting identity, and potentially activation. So, theoretically, it is good to
cache as many beans as possible. However, there are drawbacks to caching:
■Memory consumed by all the beans affects the heap available in the Virtual
Machine.
■Increasing objects and memory taken by cache means longer, and possibly more
frequent, garbage collection.
■The application server might run out of memory unless the heap is carefully tuned
for peak loads.
Keeping in mind how your application uses stateful session beans and entity beans,
and the amount of traffic your server handles, tune the EJB cache size and timeout
settings to minimize the number of activations and passivations.
EJB Cache Settings An individual EJB component can specify cache settings that
override those of the EJB container in the
<bean-cache>
element of the EJB
component's
sun-ejb-jar.xml
deployment descriptor.
The EJB cache settings are:
■Max Cache Size: Maximum number of beans in the cache. Make this setting
greater than one. The default value is 512. A value of zero indicates the cache is
unbounded, which means the size of the cache is governed by Cache Idle Timeout
and Cache Resize Quantity. The corresponding EJB deployment descriptor
attribute is
max-cache-size
.
■Cache Resize Quantity: Number of beans to be created or deleted when the cache
is serviced by the server. Valid values are from zero to MAX_INTEGER, and the
default is 16. The corresponding EJB deployment descriptor attribute is
resize-quantity
.
■Removal Timeout: Amount of time that a stateful session bean remains passivated
(idle in the backup store). If a bean was not accessed after this interval of time,
then it is removed from the backup store and will not be accessible to the client.
The default value is 60 minutes. The corresponding EJB deployment descriptor
attribute is
removal-timeout-in-seconds
.
■Removal Selection Policy: Algorithm used to remove objects from the cache. The
corresponding EJB deployment descriptor attribute is
victim-selection-policy
.
Choices are:
–NRU (not recently used). This is the default, and is actually pseudo-random
selection policy.
–FIFO (first in, first out)
–LRU (least recently used)
EJB Container Settings
3-8 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
■Cache Idle Timeout: Maximum time that a stateful session bean or entity bean is
allowed to be idle in the cache. After this time, the bean is passivated to the
backup store. The default value is 600 seconds. The corresponding EJB
deployment descriptor attribute is
cache-idle-timeout-in-seconds
.
■Refresh period: Rate at which a read-only-bean is refreshed from the data source.
Zero (0) means that the bean is never refreshed. The default is 600 seconds. The
corresponding EJB deployment descriptor attribute is
refresh-period-in-seconds
. Note: this setting does not have a custom field in the
Admin Console. To set it, use the Add Property button in the Additional
Properties section.
Pool and Cache Settings for Individual EJB Components
Individual EJB pool and cache settings in the
sun-ejb-jar.xml
deployment descriptor
override those of the EJB container. The following table lists the cache and pool
settings for each type of EJB component.
Commit Option
The commit option controls the action taken by the EJB container when an EJB
component completes a transaction. The commit option has a significant impact on
performance.
The following are the possible values for the commit option:
■Commit option B: When a transaction completes, the bean is kept in the cache and
retains its identity. The next invocation for the same primary key can use the
cached instance. The EJB container will call the bean's
ejbLoad()
method before
the method invocation to synchronize with the database.
■Commit option C: When a transaction completes, the EJB container calls the
bean's
ejbPassivate()
method, the bean is disassociated from its primary key and
returned to the free pool. The next invocation for the same primary key will have
to get a free bean from the pool, set the
PrimaryKey
on this instance, and then call
ejbActivate()
on the instance. Again, the EJB container will call the bean's
ejbLoad()
before the method invocation to synchronize with the database.
Cache or Pool Setting
Stateful
Session
Bean
Stateless
Session
Bean Entity Bean
Entity
Read-Only
Bean
Message
Driven Bean
cache-resize-quantity
XXX
max-cache-size
XXX
cache-idle-timeout-in-seconds
XXX
removal-timeout-in-seconds
XXX
victim-selection-policy
XXX
refresh-period-in-seconds
X
steady-pool-size
XXX
pool-resize-quantity
XXXX
max-pool-size
XXXX
pool-idle-timeout-in-seconds
XXXX
Transaction Service Settings
Tuning the GlassFish Server 3-9
Option B avoids
ejbAcivate()
and
ejbPassivate()
calls. So, in most cases it performs
better than option C since it avoids some overhead in acquiring and releasing objects
back to pool.
However, there are some cases where option C can provide better performance. If the
beans in the cache are rarely reused and if beans are constantly added to the cache,
then it makes no sense to cache beans. With option C is used, the container puts beans
back into the pool (instead of caching them) after method invocation or on transaction
completion. This option reuses instances better and reduces the number of live objects
in the JVM, speeding garbage collection.
Determining the Best Commit Option To determine whether to use commit option B or
commit option C, first take a look at the cache-hits value using the monitoring
command for the bean. If the cache hits are much higher than cache misses, then
option B is an appropriate choice. You might still have to change the
max-cache-size
and
cache-resize-quantity
to get the best result.
If the cache hits are too low and cache misses are very high, then the application is not
reusing the bean instances and hence increasing the cache size (using
max-cache-size
)
will not help (assuming that the access pattern remains the same). In this case you
might use commit option C. If there is no great difference between cache-hits and
cache-misses then tune
max-cache-size
, and probably
cache-idle-timeout-in-seconds
.
Java Message Service Settings
The Type attribute that determines whether the Java Message Service (JMS) is on local
or remote system affects performance. Local JMS performance is better than remote
JMS performance. However, a remote cluster can provide failover capabilities and can
be administrated together, so there may be other advantages of using remote JMS. For
more information on using JMS, see "Administering the Java Message Service (JMS)"
in GlassFish Server Open Source Edition Administration Guide.
Transaction Service Settings
The transaction manager makes it possible to commit and roll back distributed
transactions.
A distributed transactional system writes transactional activity into transaction logs so
that they can be recovered later. But writing transactional logs has some performance
penalty.
The following topics are addressed here:
■Monitoring the Transaction Service
■Tuning the Transaction Service
Monitoring the Transaction Service
Transaction Manager monitoring is disabled by default. Enable monitoring of the
transaction service through the GlassFish Server Administration Console by
navigating to the Configurations>configuration-name>Monitoring node. Refer to the
Administration Console for complete instructions.
You can also enable monitoring with these commands:
set serverInstance.transaction-service.monitoringEnabled=true
reconfig serverInstance
Transaction Service Settings
3-10 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Viewing Monitoring Information
To view monitoring information for the transaction service in the GlassFish Server
Administration Console, navigate to the server (Admin Server) node and then select
the Monitor tab.
The following statistics are gathered on the transaction service:
■
total-tx-completed
Completed transactions.
■
total-tx-rolled-back
Total rolled back transactions.
■
total-tx-inflight
Total inflight (active) transactions.
■
isFrozen
Whether transaction system is frozen (true or false)
■
inflight-tx
List of inflight (active) transactions.
Tuning the Transaction Service
This property can be used to disable the transaction logging, where the performance is
of utmost importance more than the recovery. This property, by default, won't exist in
the server configuration.
Most Transaction Service tuning tasks can be performed through the GlassFish Server
Administration Console by navigating to the
Configurations>configuration-name>Transaction Service node and then following the
instructions in the online help. Alternatively, you can follow the instructions in
"Administering Transactions" in GlassFish Server Open Source Edition Administration
Guide.
Disable Distributed Transaction Logging
You can disable transaction logging through the Administration Console or by using
the following
asadmin set
subcommand:
asadmin set
server1.transaction-service.disable-distributed-transaction-logging=true
Disabling transaction logging can improve performance. Setting it to false (the
default), makes the transaction service write transactional activity to transaction logs
so that transactions can be recovered. If Recover on Restart is checked, this property is
ignored.
Set this property to true only if performance is more important than transaction
recovery.
Recover On Restart (Automatic Recovery)
You can set the Recover on Restart attribute through the Administration Console or by
entering the following
asadmin set
subcommand:
asadmin set server1.transaction-service.automatic-recovery=false
When Recover on Restart is true, the server will always perform transaction logging,
regardless of the Disable Distributed Transaction Logging attribute.
If Recover on Restart is false, then:
■If Disable Distributed Transaction Logging is false (the default), then the server
will write transaction logs.
HTTP Service Settings
Tuning the GlassFish Server 3-11
■If Disable Distributed Transaction Logging is true, then the server will not write
transaction logs.
Not writing transaction logs will give approximately twenty percent improvement
in performance, but at the cost of not being able to recover from any interrupted
transactions. The performance benefit applies to transaction-intensive tests. Gains
in real applications may be less.
Keypoint Interval
The keypoint interval determines how often entries for completed transactions are
removed from the log file. Keypointing prevents a process log from growing
indefinitely.
Frequent keypointing is detrimental to performance. The default value of the Keypoint
Interval is 2048, which is sufficient in most cases.
HTTP Service Settings
Tuning the monitoring and access logging settings for the HTTP server instances that
handle client requests are important parts of ensuring peak GlassFish Server
performance.
The following topics are addressed here:
■Monitoring the HTTP Service
■HTTP Service Access Logging
Monitoring the HTTP Service
Disabling the collection of monitoring statistics can increase overall GlassFish Server
performance. You can enable or disable monitoring statistics collection for the HTTP
service using either the Administration Console or
asadmin
subcommands.
Refer to "Administering the Monitoring Service" in GlassFish Server Open Source Edition
Administration Guide for complete instructions on configuring the monitoring service
using
asadmin
subcommands.
If using the Administration Console, click the
Configurations>configuration-name>Monitoring node for the configuration for which
you want to enable or disable monitoring for selected components. Refer to the
Administration Console online help for complete instructions.
For instructions on viewing comprehensive monitoring statistics using
asadmin
subcommands, see "Viewing Comprehensive Monitoring Data" in GlassFish Server
Open Source Edition Administration Guide. If using the Administration Console, you can
view monitoring statistics by navigating to the server (Admin Server) node, and then
clicking the Monitor tab. Refer to the online help for configuring different views of the
available monitoring statistics.
When viewing monitoring statistics, some key performance-related information to
review includes the following:
■DNS Cache Information (dns)
■File Cache Information (file-cache)
■Keep Alive (keep-alive)
■Connection Queue
HTTP Service Settings
3-12 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
DNS Cache Information (dns)
The DNS cache caches IP addresses and DNS names. The DNS cache is disabled by
default. In the DNS Statistics for Process ID All page under Monitor in the web-based
Administration interface the following statistics are displayed:
■Enabled
■CacheEntries (CurrentCacheEntries / MaxCacheEntries)
■HitRatio
■Caching DNS Entries
■Limit DNS Lookups to Asynchronous
■Enabled
■NameLookups
■AddrLookups
■LookupsInProgress
Enabled If the DNS cache is disabled, the rest of this section is not displayed.
By default, the DNS cache is off. Enable DNS caching in the Administration Console
by clicking the Configurations>configuration-name>Network Config>http-listener-name
node. Click the HTTP tab and enable the DNS Lookup option.
CacheEntries (CurrentCacheEntries / MaxCacheEntries) The number of current cache entries
and the maximum number of cache entries. A single cache entry represents a single IP
address or DNS name lookup. Make the cache as large as the maximum number of
clients that access your web site concurrently. Note that setting the cache size too high
is a waste of memory and degrades performance.
Set the maximum size of the DNS cache by entering or changing the value in the in the
Administration Console by clicking the Configurations>configuration-name>Network
Config>http-listener-name node. Click the File tab and set the desired options.
HitRatio The hit ratio is the number of cache hits divided by the number of cache
lookups.
This setting is not tunable.
Caching DNS Entries It is possible to also specify whether to cache the DNS entries. If
you enable the DNS cache, the server can store hostname information after receiving
it. If the server needs information about the client in the future, the information is
cached and available without further querying. specify the size of the DNS cache and
an expiration time for DNS cache entries. The DNS cache can contain 32 to 32768
entries; the default value is 1024. Values for the time it takes for a cache entry to expire
can range from 1 second to 1 year specified in seconds; the default value is 1200
seconds (20 minutes).
Limit DNS Lookups to Asynchronous Do not use DNS lookups in server processes because
they are resource-intensive. If you must include DNS lookups, make them
asynchronous.
Note: If you turn off DNS lookups on your server, host name
restrictions will not work and IP addresses will appear instead of
host names in log files.
HTTP Service Settings
Tuning the GlassFish Server 3-13
Enabled If asynchronous DNS is disabled, the rest of this section will not be displayed.
NameLookups The number of name lookups (DNS name to IP address) that have been
done since the server was started. This setting is not tunable.
AddrLookups The number of address loops (IP address to DNS name) that have been
done since the server was started. This setting is not tunable.
LookupsInProgress The current number of lookups in progress.
File Cache Information (file-cache)
The file cache caches static content so that the server handles requests for static content
quickly. The file-cache section provides statistics on how your file cache is being used.
For information about tuning the file cache, see File Cache Settings.
The Monitoring page lists the following file cache statistics:
■Number of Hits on Cached File Content
■Number of Cache Entries
■Number of Hits on Cached File Info
■Heap Space Used for Cache
■Number of Misses on Cached File Content
■Cache Lookup Misses
■Number of Misses on Cached File Content
■Max Age of a Cache Entry
■Max Number of Cache Entries
■Max Number of Open Entries
■Is File Cached Enabled?
■Maximum Memory Map to be Used for Cache
■Memory Map Used for cache
■Cache Lookup Hits
■Open Cache Entries: The number of current cache entries and the maximum
number of cache entries are both displayed. A single cache entry represents a
single URI. This is a tunable setting.
■Maximum Heap Space to be Used for Cache
Keep Alive (keep-alive)
The following are statistics related to the Keep Alive system. The most important
settings you can tune here relate to HTTP Timeout. See Timeout for more information.
■Connections Terminated Due to Client Connection Timed Out
■Max Connection Allowed in Keep-alive
■Number of Hits
■Connections in Keep-alive Mode
■Connections not Handed to Keep-alive Thread Due to too Many Persistent
Connections
Network Listener Settings
3-14 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
■The Time in Seconds Before Idle Connections are Closed
■Connections Closed Due to Max Keep-alive Being Exceeded
Connection Queue
■Total Connections Queued: Total connections queued is the total number of times
a connection has been queued. This includes newly accepted connections and
connections from the keep-alive system.
■Average Queuing Delay: Average queueing delay is the average amount of time a
connection spends in the connection queue. This represents the delay between
when a request connection is accepted by the server, and a request processing
thread (also known as a session) begins servicing the request.
HTTP Service Access Logging
Accessing Logging can be tuned using several
asadmin
subcommands. Refer to
"Administering the Monitoring Service" in GlassFish Server Open Source Edition
Administration Guide for information about using these subcommands.
If using the Administration Console, Access Logging is configured from the
Configurations>configuration-name>HTTP Service page. Refer to the Administration
Console online help for complete instructions about the options on this page.
To enable or disable access logging, check or uncheck the Access Logging Enabled
checkbox. Access Logging is disabled by default.
When performing benchmarking, ensure that Access Logging is disabled. If Access
Logging is enabled, it is recommended that you also enable Rotation to ensure that the
logs do not run out of disk space.
Network Listener Settings
You can tune Network Listener settings from the command line by using the
instructions in "Administering HTTP Network Listeners" in GlassFish Server Open
Source Edition Administration Guide.
If using the Administration Console, navigate to the Configurations
>configuration-name>Network Config>Network Listeners>listener-name node, and then
click the tab for the desired configuration page. Refer to the online help for complete
instructions about the options on these tabs.
GlassFish Server Network Listener performance can be enhanced by modifying
settings on the following Edit Network Listener tabs in the Administration Console:
■General Settings
■HTTP Settings
■File Cache Settings
General Settings
For machines with only one network interface card (NIC), set the network address to
the IP address of the machine (for example, 192.18.80.23 instead of default 0.0.0.0). If
you specify an IP address other than 0.0.0.0, the server will make one less system call
per connection. Specify an IP address other than 0.0.0.0 for best possible performance.
If the server has multiple NIC cards then create multiple listeners for each NIC.
Network Listener Settings
Tuning the GlassFish Server 3-15
HTTP Settings
The following settings on the HTTP tab can significantly affect performance:
■Max Connections
■DNS Lookup Enabled
■Timeout
■Header Buffer Length
Max Connections
Max Connections controls the number of requests that a particular client can make
over a keep-alive connection. The range is any positive integer, and the default is 256.
Adjust this value based on the number of requests a typical client makes in your
application. For best performance specify quite a large number, allowing clients to
make many requests.
The number of connections specified by Max Connections is divided equally among
the keep alive threads. If Max Connections is not equally divisible by Thread Count,
the server can allow slightly more than Max Connections simultaneous keep alive
connections.
DNS Lookup Enabled
This setting specifies whether the server performs DNS (domain name service)
lookups on clients that access the server. When DNS lookup is not enabled, when a
client connects, the server knows the client's IP address but not its host name (for
example, it knows the client as 198.95.251.30, rather than
www.xyz.com
). When DNS
lookup is enabled, the server will resolve the client's IP address into a host name for
operations like access control, common gateway interface (CGI) programs, error
reporting, and access logging.
If the server responds to many requests per day, reduce the load on the DNS or NIS
(Network Information System) server by disabling DNS lookup. Enabling DNS lookup
will increase the latency and load on the system, so modify this setting with caution.
Timeout
Timeout determines the maximum time (in seconds) that the server holds open an
HTTP keep alive connection. A client can keep a connection to the server open so that
multiple requests to one server can be serviced by a single network connection. Since
the number of open connections that the server can handle is limited, a high number of
open connections will prevent new clients from connecting.
The default time out value is 30 seconds. Thus, by default, the server will close the
connection if idle for more than 30 seconds. The maximum value for this parameter is
300 seconds (5 minutes).
The proper value for this parameter depends upon how much time is expected to
elapse between requests from a given client. For example, if clients are expected to
make requests frequently then, set the parameter to a high value; likewise, if clients are
expected to make requests rarely, then set it to a low value.
Both HTTP 1.0 and HTTP 1.1 support the ability to send multiple requests across a
single HTTP session. A server can receive hundreds of new HTTP requests per second.
If every request was allowed to keep the connection open indefinitely, the server could
become overloaded with connections. On Unix/Linux systems, this could easily lead
to a file table overflow.
Network Listener Settings
3-16 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
The GlassFish Server's Keep Alive system, which is affected by the Timeout setting,
addresses this problem. A waiting keep alive connection has completed processing the
previous request, and is waiting for a new request to arrive on the same connection.
The server maintains a counter for the maximum number of waiting keep-alive
connections. If the server has more than the maximum waiting connections open when
a new connection waits for a keep-alive request, the server closes the oldest
connection. This algorithm limits the number of open waiting keep-alive connections.
If your system has extra CPU cycles, incrementally increase the keep alive settings and
monitor performance after each increase. When performance saturates (stops
improving), then stop increasing the settings.
Header Buffer Length
The size (in bytes) of the buffer used by each of the request processing threads for
reading the request data from the client.
Adjust the value based on the actual request size and observe the impact on
performance. In most cases the default should suffice. If the request size is large,
increase this parameter.
File Cache Settings
The GlassFish Server uses a file cache to serve static information faster. The file cache
contains information about static files such as HTML, CSS, image, or text files.
Enabling the HTTP file cache will improve performance of applications that contain
static files.
The following settings on the File Cache tab can significantly affect performance:
■Max File Count
■Max Age
Max File Count
Max File Count determines how many files are in the cache. If the value is too big, the
server caches little-needed files, which wastes memory. If the value is too small, the
benefit of caching is lost. Try different values of this attribute to find the optimal
solution for specific applications—generally, the effects will not be great.
Max Age
This parameter controls how long cached information is used after a file has been
cached. An entry older than the maximum age is replaced by a new entry for the same
file.
If your Web site's content changes infrequently, increase this value for improved
performance. Set the maximum age by entering or changing the value in the
Maximum Age field of the File Cache Configuration page in the web-based Admin
Console for the HTTP server node and selecting the File Caching Tab.
Set the maximum age based on whether the content is updated (existing files are
modified) on a regular schedule or not. For example, if content is updated four times a
day at regular intervals, you could set the maximum age to 21600 seconds (6 hours).
Otherwise, consider setting the maximum age to the longest time you are willing to
serve the previous version of a content file after the file has been modified.
Thread Pool Settings
Tuning the GlassFish Server 3-17
Transport Settings
The Acceptor Threads property for the Transport service specifies how many threads
you want in accept mode on a listen socket at any time. It is a good practice to set this
to less than or equal to the number of CPUs in your system.
In the GlassFish Server, acceptor threads on an HTTP Listener accept connections and
put them onto a connection queue. Session threads then pick up connections from the
queue and service the requests. The server posts more session threads if required at
the end of the request.
See "Administering HTTP Network Listeners" in GlassFish Server Open Source Edition
Administration Guide for instructions on modifying the Acceptor Threads property. If
using the Administration Console, the Acceptor Threads property is available on the
Configurations>configuration-name>Network Config>Transports>tcp page.
Thread Pool Settings
You can tune thread pool settings by following the instructions in "Administering
Thread Pools" in GlassFish Server Open Source Edition Administration Guide. If using the
Administration Console Thread Pool settings are available on the
Configurations>configuration-name>Thread Pools>thread-pool-name page.
The following thread pool settings can have significant effects on GlassFish Server
performance:
■Max Thread Pool Size
■Min Thread Pool Size
Max Thread Pool Size
The Max Thread Pool Size parameter specifies the maximum number of simultaneous
requests the server can handle. The default value is 5. When the server has reached the
limit or request threads, it defers processing new requests until the number of active
requests drops below the maximum amount. Increasing this value will reduce HTTP
response latency times.
In practice, clients frequently connect to the server and then do not complete their
requests. In these cases, the server waits a length of time specified by the Timeout
parameter.
Also, some sites do heavyweight transactions that take minutes to complete. Both of
these factors add to the maximum simultaneous requests that are required. If your site
is processing many requests that take many seconds, you might need to increase the
number of maximum simultaneous requests.
Adjust the thread count value based on your load and the length of time for an
average request. In general, increase this number if you have idle CPU time and
requests that are pending; decrease it if the CPU becomes overloaded. If you have
many HTTP 1.0 clients (or HTTP 1.1 clients that disconnect frequently), adjust the
timeout value to reduce the time a connection is kept open.
Suitable Request Max Thread Pool Size values range from 100 to 500, depending on
the load. If your system has extra CPU cycles, keep incrementally increasing thread
count and monitor performance after each incremental increase. When performance
saturates (stops improving), then stop increasing thread count.
ORB Settings
3-18 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Min Thread Pool Size
The Min Thread Pool Size property specifies the minimum number of threads the
server initiates upon startup. The default value is 2. Min Thread Pool Size represents a
hard limit for the maximum number of active threads that can run simultaneously,
which can become a bottleneck for performance.
Specifying the same value for minimum and maximum threads allows GlassFish
Server to use a slightly more optimized thread pool. This configuration should be
considered unless the load on the server varies quite significantly.
ORB Settings
The GlassFish Server includes a high performance and scalable CORBA Object
Request Broker (ORB). The ORB is the foundation of the EJB Container on the server.
For complete instructions on configuring ORB settings, refer to "Administering the
Object Request Broker (ORB)" in GlassFish Server Open Source Edition Administration
Guide. Also refer to "RMI-IIOP Load Balancing and Failover" in GlassFish Server Open
Source Edition High Availability Administration Guide. You can also configure most ORB
settings through the GlassFish Server Administration Console by navigating to the
Configurations>configuration-name> ORB node and then following the instructions in
the Administration Console online help.
The following topics are addressed here:
■Overview
■How a Client Connects to the ORB
■Monitoring the ORB
■Tuning the ORB
Overview
The ORB is primarily used by EJB components via:
■RMI/IIOP path from an application client (or rich client) using the application
client container.
■RMI/IIOP path from another GlassFish Server instance ORB.
■RMI/IIOP path from another vendor's ORB.
■In-process path from the Web Container or MDB (message driven beans)
container.
When a server instance makes a connection to another server instance ORB, the first
instance acts as a client ORB. SSL over IIOP uses a fast optimized transport with
high-performance native implementations of cryptography algorithms.
It is important to remember that EJB local interfaces do not use the ORB. Using a local
interface passes all arguments by reference and does not require copying any objects.
How a Client Connects to the ORB
A rich client Java program performs a new
initialContext()
call which creates a
client side ORB instance. This in turn creates a socket connection to the GlassFish
Server IIOP port. The reader thread is started on the server ORB to service IIOP
requests from this client. Using the
initialContext
, the client code does a lookup of
an EJB deployed on the server. An IOR which is a remote reference to the deployed
ORB Settings
Tuning the GlassFish Server 3-19
EJB on the server is returned to the client. Using this object reference, the client code
invokes remote methods on the EJB.
InitialContext
lookup for the bean and the method invocations translate the
marshalling application request data in Java into IIOP message(s) that are sent on the
socket connection that was created earlier on to the server ORB. The server then
creates a response and sends it back on the same connection. This data in the response
is then un-marshalled by the client ORB and given back to the client code for
processing. The Client ORB shuts down and closes the connection when the rich client
application exits.
Monitoring the ORB
ORB statistics are disabled by default. To gather ORB statistics, enable monitoring
with the following
asadmin
command:
set serverInstance.iiop-service.orb.system.monitoringEnabled=true
reconfig serverInstance
If using the Administration Console, you can enable ORB monitoring on the
Configurations>configuration-name>Monitoring page. To view ORB monitoring
statistics through the Administration Console, navigate to the server (Admin Server)
page and click the Monitor tab. Refer to the Administration Console online help for
complete instructions.
The following statistics are of particular interest when tuning the ORB:
■Connection Statistics
■Thread Pools
Connection Statistics
The following statistics are gathered on ORB connections:
■
total-inbound-connections
: Total inbound connections to ORB.
■
total-outbound-connections
: Total outbound connections from ORB.
Use the following command to get ORB connection statistics:
asadmin get --monitor
serverInstance.iiop-service.orb.system.orb-connection.*
Thread Pools
The following statistics are gathered on ORB thread pools:
■
thread-pool-size
: Number of threads in ORB thread pool.
■
waiting-thread-count
: Number of thread pool threads waiting for work to arrive.
Use the following command to display ORB thread pool statistics:
asadmin get --monitor
serverInstance.iiop-service.orb.system.orb-thread-pool.*
Tuning the ORB
Tune ORB performance by setting ORB parameters and ORB thread pool parameters.
You can often decrease response time by leveraging load-balancing, multiple shared
ORB Settings
3-20 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
connections, thread pool and message fragment size. You can improve scalability by
load balancing between multiple ORB servers from the client, and tuning the number
of connection between the client and the server.
The following topics are addressed here:
■Tunable ORB Parameters
■ORB Thread Pool Parameters
■Client ORB Properties
■Thread Pool Sizing
■Examining IIOP Messages
Tunable ORB Parameters
You can tune ORB parameters using the instructions in "Administering the Object
Request Broker (ORB)" in GlassFish Server Open Source Edition Administration Guide. If
using the Administration Console, navigate to the
Configurations>configuration-name>ORB node and refer to the online help.
The following table summarizes the tunable ORB parameters.
ORB Thread Pool Parameters
The ORB thread pool contains a task queue and a pool of threads. Tasks or jobs are
inserted into the task queue and free threads pick tasks from this queue for execution.
Do not set a thread pool size such that the task queue is always empty. It is normal for
a large application's Max Pool Size to be ten times the size of the current task queue.
The GlassFish Server uses the ORB thread pool to:
■Execute every ORB request
■Trim EJB pools and caches
■Execute MDB requests
Thus, even when one is not using ORB for remote-calls (via RMI/ IIOP), set the size of
the threadpool to facilitate cleaning up the EJB pools and caches.
You can set ORB thread pool attributes using the instructions in "Administering
Thread Pools" in GlassFish Server Open Source Edition Administration Guide. If using the
Administration Console, navigate to Configurations>configuration-name> Thread
Table 3–2 Tunable ORB Parameters
Path ORB Modules Server Settings
RMI/ IIOP from application client to
application server communication
infrastructure, thread pool steady-thread-pool-size,
max-thread-pool-size,
idle-thread-timeout-in-seconds
RMI/ IIOP from ORB to GlassFish
Server communication
infrastructure, thread pool steady-thread-pool-size,
max-thread-pool-size,
idle-thread-timeout-in-seconds
RMI/ IIOP from a vendor ORB parts of communication
infrastructure, thread pool steady-thread-pool-size,
max-thread-pool-size,
idle-thread-timeout-in-seconds
In-process thread pool steady-thread-pool-size,
max-thread-pool-size,
idle-thread-timeout-in-seconds
ORB Settings
Tuning the GlassFish Server 3-21
Pools>thread-pool-name, where thread-pool-name is the thread pool ID selected for the
ORB. Thread pools have the following attributes that affect performance.
■Minimum Pool Size: The minimum number of threads in the ORB thread pool. Set
to the average number of threads needed at a steady (RMI/ IIOP) load.
■Maximum Pool Size: The maximum number of threads in the ORB thread pool.
■Idle Timeout: Number of seconds to wait before removing an idle thread from
pool. Allows shrinking of the thread pool.
■Number of Work Queues
In particular, the maximum pool size is important to performance. For more
information, see Thread Pool Sizing.
Client ORB Properties
Specify the following properties as command-line arguments when launching the
client program. You do this by using the following syntax when starting the Java VM:
-Dproperty=value
The following topics are addressed here:
■Controlling Connections Between Client and Server ORB
■Load Balancing
Controlling Connections Between Client and Server ORB When using the default JDK ORB
on the client, a connection is established from the client ORB to the application server
ORB every time an initial context is created. To pool or share these connections when
they are opened from the same process by adding to the configuration on the client
ORB.
-Djava.naming.factory.initial=com.sun.enterprise.naming.SerialInitContextFactory
Load Balancing For information on how to configure HTTP load balancing, see
"Configuring HTTP Load Balancing" in GlassFish Server Open Source Edition High
Availability Administration Guide.
For information on how to configure RMI/IIOP for multiple application server
instances in a cluster, "RMI-IIOP Load Balancing and Failover" in GlassFish Server Open
Source Edition High Availability Administration Guide.
When tuning the client ORB for load-balancing and connections, consider the number
of connections opened on the server ORB. Start from a low number of connections and
then increase it to observe any performance benefits. A connection to the server
translates to an ORB thread reading actively from the connection (these threads are not
pooled, but exist currently for the lifetime of the connection).
Thread Pool Sizing
After examining the number of inbound and outbound connections as explained
above, tune the size of the thread pool appropriately. This can affect performance and
response times significantly.
The size computation takes into account the number of client requests to be processed
concurrently, the resource (number of CPUs and amount of memory) available on the
machine and the response times required for processing the client requests.
ORB Settings
3-22 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Setting the size to a very small value can affect the ability of the server to process
requests concurrently, thus affecting the response times since requests will sit longer
in the task queue. On the other hand, having a large number of worker threads to
service requests can also be detrimental because they consume system resources,
which increases concurrency. This can mean that threads take longer to acquire shared
structures in the EJB container, thus affecting response times.
The worker thread pool is also used for the EJB container's housekeeping activity such
as trimming the pools and caches. This activity needs to be accounted for also when
determining the size. Having too many ORB worker threads is detrimental for
performance since the server has to maintain all these threads. The idle threads are
destroyed after the idle thread timeout period.
Examining IIOP Messages
It is sometimes useful to examine the IIOP messages passed by the GlassFish Server.
To make the server save IIOP messages to the
server.log
file, set the JVM option
-Dcom.sun.CORBA.ORBDebug=giop
. Use the same option on the client ORB.
The following is an example of IIOP messages saved to the server log. Note: in the
actual output, each line is preceded by the timestamp, such as
[29/Aug/2002:22:41:43] INFO (27179): CORE3282: stdout
.
++++++++++++++++++++++++++++++
Message(Thread[ORB Client-side Reader, conn to 192.18.80.118:1050,5,main]):
createFromStream: type is 4 <
MessageBase(Thread[ORB Client-side Reader, conn to 192.18.80.118:1050,5,main]):
Message GIOP version: 1.2
MessageBase(Thread[ORB Client-side Reader, conn to 192.18.80.118:1050,5,main]):
ORB Max GIOP Version: 1.2
Message(Thread[ORB Client-side Reader, conn to 192.18.80.118:1050,5,main]):
createFromStream: message construction complete.
com.sun.corba.ee.internal.iiop.MessageMediator
(Thread[ORB Client-side Reader, conn to 192.18.80.118:1050,5,main]): Received
message:
----- Input Buffer -----
Current index: 0
Total length : 340
47 49 4f 50 01 02 00 04 0 0 00 01 48 00 00 00 05 GIOP.......H....
In this sample output above, the
createFromStream
type is shown as
4
. This implies
that the message is a fragment of a bigger message. To avoid fragmented messages,
increase the fragment size. Larger fragments mean that messages are sent as one unit
and not as fragments, saving the overhead of multiple messages and corresponding
processing at the receiving end to piece the messages together.
If most messages being sent in the application are fragmented, increasing the fragment
size is likely to improve efficiency. On the other hand, if only a few messages are
fragmented, it might be more efficient to have a lower fragment size that requires
smaller buffers for writing messages.
Note: The flag
-Dcom.sun.CORBA.ORBdebug=giop
generates many
debug messages in the logs. This is used only when you suspect
message fragmentation.
Resource Settings
Tuning the GlassFish Server 3-23
Resource Settings
Tuning JDBC and connector resources can significantly improve GlassFish Server
performance.
The following topics are addressed here:
■JDBC Connection Pool Settings
■Connector Connection Pool Settings
JDBC Connection Pool Settings
For optimum performance of database-intensive applications, tune the JDBC
Connection Pools managed by the GlassFish Server. These connection pools maintain
numerous live database connections that can be reused to reduce the overhead of
opening and closing database connections. This section describes how to tune JDBC
Connection Pools to improve performance.
J2EE applications use JDBC Resources to obtain connections that are maintained by the
JDBC Connection Pool. More than one JDBC Resource is allowed to refer to the same
JDBC Connection Pool. In such a case, the physical connection pool is shared by all the
resources.
Refer to "Administering Database Connectivity" in GlassFish Server Open Source Edition
Administration Guide for more information about managing JDBC connection pools.
The following topics are addressed here:
■Monitoring JDBC Connection Pools
■Tuning JDBC Connection Pools
Monitoring JDBC Connection Pools
Statistics-gathering is disabled by default for JDBC Connection Pools. Refer to for
instructions on enabling JDBC monitoring in "Administering the Monitoring Service"
in GlassFish Server Open Source Edition Administration Guide. If using the
Administration Console, JDBC monitoring can be enabled on the
Configurations>configuration-name>Monitoring page.
The following attributes are monitored:
■
numConnFailedValidation (count)
Number of connections that failed validation.
■
numConnUsed (range)
Number of connections that have been used.
■
numConnFree (count)
Number of free connections in the pool.
■
numConnTimedOut (bounded range)
Number of connections in the pool that have
timed out.
To get JDBC monitoring statistics, use the following commands:
asadmin get --monitor=true
serverInstance.resources.jdbc-connection-pool.*asadmin get
--monitor=true serverInstance.resources.jdbc-connection-pool. poolName.* *
To view JDBC monitoring statistics through the Administration Console, navigate to
the server (Admin Server) page and click the Monitor tab. Refer to the Administration
Console online help for complete instructions.
Resource Settings
3-24 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Tuning JDBC Connection Pools
Refer to "Administering Database Connectivity" in GlassFish Server Open Source Edition
Administration Guide for instructions on configuring JDBC connection pools. If using
the GlassFish Server Administration Console by navigating to the
Resources>JDBC>JDBC Connection Pools>jdbc-pool-name page and then clicking the
desired tab.
The following JDBC properites affect GlassFish Server performance:
■Pool Size Settings
■Timeout Settings
■Isolation Level Settings
■Connection Validation Settings
Pool Size Settings Pool Size settings can be configured in the Pool Settings section on
the General tab in the Edit JDBC Connection Pool page.
The following settings control the size of the connection pool:
■Initial and Mimimum Pool Size: Size of the pool when created, and its minimum
allowable size.
■Maximum Pool Size: Upper limit of size of the pool.
■Pool Resize Quantity: Number of connections to be removed when the idle
timeout expires. Connections that have idled for longer than the timeout are
candidates for removal. When the pool size reaches the initial and minimum pool
size, removal of connections stops.
The following table summarizes advantages and disadvantages to consider when
sizing connection pools.
Timeout Settings The following JDBC timeout settings can be configured on the in the
Pool Settings section on the General tab in the Edit JDBC Connection Pool page.
■Max Wait Time: Amount of time the caller (the code requesting a connection) will
wait before getting a connection timeout. The default is 60 seconds. A value of
zero forces caller to wait indefinitely.
To improve performance set Max Wait Time to zero (0). This essentially blocks the
caller thread until a connection becomes available. Also, this allows the server to
alleviate the task of tracking the elapsed wait time for each request and increases
performance.
■Idle Timeout: Maximum time in seconds that a connection can remain idle in the
pool. After this time, the pool can close this connection. This property does not
control connection timeouts on the database server.
Table 3–3 Connection Pool Sizing
Connection Pool Advantages Disadvantages
Small Connection pool Faster access on the connection table. May not have enough connections to satisfy
requests.
Requests may spend more time in the queue.
Large Connection pool More connections to fulfill requests.
Requests will spend less (or no) time in the
queue
Slower access on the connection table.
Resource Settings
Tuning the GlassFish Server 3-25
Keep this timeout shorter than the database server timeout (if such timeouts are
configured on the database), to prevent accumulation of unusable connection in
GlassFish Server.
For best performance, set Idle Timeout to zero (0) seconds, so that idle connections
will not be removed. This ensures that there is normally no penalty in creating
new connections and disables the idle monitor thread. However, there is a risk
that the database server will reset a connection that is unused for too long.
Isolation Level Settings The following JDBC Isolation Level settings can be configured in
the Transaction section on the General tab in the Edit JDBC Connection Pool page.
■Transaction Isolation: Specifies the transaction isolation level of the pooled
database connections. If this parameter is unspecified, the pool uses the default
isolation level provided by the JDBC Driver.
■Isolation Level Guaranteed: Guarantees that every connection obtained from the
pool has the isolation specified for the Transaction Isolation level. Applicable only
when the Transaction Isolation level is specified. The default value is Guaranteed.
This setting can have some performance impact on some JDBC drivers. Set to false
when certain that the application does not change the isolation level before
returning the connection.
Avoid specifying the Transaction Isolation level. If that is not possible, consider
disabling the Isolation Level Guaranteed option and then make sure applications do
not programmatically alter the connections; isolation level.
If you must specify a Transaction Isolation level, specify the best-performing level
possible. The isolation levels listed from best performance to worst are:
1.
READ_UNCOMMITTED
2.
READ_COMMITTED
3.
REPEATABLE_READ
4.
SERIALIZABLE
Choose the isolation level that provides the best performance, yet still meets the
concurrency and consistency needs of the application.
Connection Validation Settings JDBC Connection Validation settings can be configured in
the Connection Validation section on the Advanced tab in the Edit JDBC Connection
Pool page.
■Connection Validation Required: If enabled, the pool validates connections
(checks to find out if they are usable) before providing them to an application.
If possible, keep this option disabled. Requiring connection validation forces the
server to apply the validation algorithm every time the pool returns a connection,
which adds overhead to the latency of
getConnection()
. If the database
connectivity is reliable, you can omit validation.
■Validation Method: Specifies the type of connection validation to perform. Must
be one of the following:
–
auto-commit
: Attempt to perform an auto-commit on the connection.
–
metadata
: Attempt to get metadata from the connection.
–
table
: Performing the query on a specified table. If this option is selected,
Table Name must also be set. Choosing this option may be necessary if the
JDBC driver caches calls to
setAutoCommit()
and
getMetaData()
.
Load Balancer Settings
3-26 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
–
custom-validation
: Define a custom validation method.
■Table Name: Name of the table to query when the Validation Method is set to
table
.
■Close All Connections On Any Failure: Specify whether all connections in the
pool should be closed if a single validation check fails. This option is disabled by
default. One attempt will be made to re-establish failed connections.
Connector Connection Pool Settings
From a performance standpoint, connector connection pools are similar to JDBC
connection pools. Follow all the recommendations in the previous section, Tuning
JDBC Connection Pools.
Transaction Support
You may be able to improve performance by overriding the default transaction
support specified for each connector connection pool.
For example, consider a case where an Enterprise Information System (EIS) has a
connection factory that supports local transactions with better performance than
global transactions. If a resource from this EIS needs to be mixed with a resource
coming from another resource manager, the default behavior forces the use of XA
transactions, leading to lower performance. However, by changing the EIS's connector
connection pool to use LocalTransaction transaction support and leveraging the Last
Agent Optimization feature previously described, you could leverage the
better-performing EIS LocalTransaction implementation. For more information on
LAO, see Configure JDBC Resources as One-Phase Commit Resources.
You can specify transaction support when you create or edit a connector connection
pool.
Also set transaction support using
asadmin
. For example, the following
asadmin
command could be used to create a connector connection pool
TESTPOOL
with
transaction-support
set to
LOCAL
.
asadmin> create-connector-connection-pool --raname jdbcra
--connectiondefinition javax.sql.DataSource
-transactionsupport LocalTransaction
TESTPOOL
Load Balancer Settings
GlassFish Server Open Source Edition is compatible with the Apache HTTP server
mod_jk
module for load balancing.
GlassFish Server load balancing configurations can vary widely depending on the
needs of your enterprise and are beyond the scope of this Performance Tuning Guide.
For complete information about configuring load balancing in GlassFish Server, refer
to the following documentation:
■"Configuring HTTP Load Balancing" in GlassFish Server Open Source Edition High
Availability Administration Guide
■"RMI-IIOP Load Balancing and Failover" in GlassFish Server Open Source Edition
High Availability Administration Guide
4
Tuning the Java Runtime System 4-1
4Tuning the Java Runtime System
The following topics are addressed here:
■Java Virtual Machine Settings
■Start Options
■Tuning High Availability Persistence
■Managing Memory and Garbage Collection
■Further Information
Java Virtual Machine Settings
Java SE 6.0 provides two implementations of the HotSpot Java virtual machine (JVM):
■The client VM is tuned for reducing startup time and memory footprint. Invoke it
by using the
-client
JVM command-line option.
■The server VM is designed for maximum program execution speed. Invoke it by
using the
-server
JVM command-line option.
By default, the GlassFish Server uses the JVM setting appropriate to the purpose:
■Developer Profile, targeted at application developers, uses the
-client
JVM flag to
optimize startup performance and conserve memory resources.
■Enterprise Profile, targeted at production deployments, uses the
-server
JVM flag
to maximize program execution speed.
You can override the default JVM options by following the instructions in
"Administering JVM Options" in GlassFish Server Open Source Edition Administration
Guide. If using the Administration Console, navigate to the
Configurations>configuration-name>JVM Settings node, and then click the JVM
Options tab. Refer to the online help for complete information about the settings on
this page.
For more information on server-class machine detection in Java SE 6.0, see
Server-Class Machine Detection
(http://download.oracle.com/javase/6/docs/technotes/guides/vm/se
rver-class.html).
For more information on JVMs, see Java Virtual Machines
(http://download.oracle.com/javase/6/docs/).
Start Options
4-2 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Start Options
In some situations, performance can be improved by using large page sizes. For
Ultrasparc CMT systems, include the
-XX:+UseLargePages
and
-XX:LargePageSizeInBytes=256m
arguments with your JVM tuning.
Tuning High Availability Persistence
If session
s1
and
s2
need to be replicated to an instance (backup server), the
replication module batches the replication messages to be sent to that instance instead
of sending separate replication messages. This improves performance. In
configurations in which a lot of session replication is performed, you may find better
performance by tuning the
org.shoal.cache.transmitter.max.batch.size
system
property. This property determines the number of replication messages that constitute
one batch.
The default value for this property is
20
. You can try setting it as high as
90
,
depending on system loads. Like all system properties, this property is set with the
-D
flag in your Java arguments.
Managing Memory and Garbage Collection
The efficiency of any application depends on how well memory and garbage collection
are managed. The following sections provide information on optimizing memory and
allocation functions:
■Tuning the Garbage Collector
■Tracing Garbage Collection
■Other Garbage Collector Settings
■Tuning the Java Heap
■Rebasing DLLs on Windows
Tuning the Garbage Collector
Garbage collection (GC) reclaims the heap space previously allocated to objects no
longer needed. The process of locating and removing the dead objects can stall any
application and consume as much as 25 percent throughput.
Almost all Java Runtime Environments come with a generational object memory
system and sophisticated GC algorithms. A generational memory system divides the
heap into a few carefully sized partitions called generations. The efficiency of a
generational memory system is based on the observation that most of the objects are
short lived. As these objects accumulate, a low memory condition occurs forcing GC to
take place.
The heap space is divided into the old and the new generation. The new generation
includes the new object space (eden), and two survivor spaces. The JVM allocates new
objects in the eden space, and moves longer lived objects from the new generation to
the old generation.
The young generation uses a fast copying garbage collector which employs two
semi-spaces (survivor spaces) in the eden, copying surviving objects from one survivor
space to the second. Objects that survive multiple young space collections are tenured,
meaning they are copied to the tenured generation. The tenured generation is larger
and fills up less quickly. So, it is garbage collected less frequently; and each collection
Managing Memory and Garbage Collection
Tuning the Java Runtime System 4-3
takes longer than a young space only collection. Collecting the tenured space is also
referred to as doing a full generation collection.
The frequent young space collections are quick (a few milliseconds), while the full
generation collection takes a longer (tens of milliseconds to a few seconds, depending
upon the heap size).
Other GC algorithms, such as the Concurrent Mark Sweep (CMS) algorithm, are
incremental. They divide the full GC into several incremental pieces. This provides a
high probability of small pauses. This process comes with an overhead and is not
required for enterprise web applications.
When the new generation fills up, it triggers a minor collection in which the surviving
objects are moved to the old generation. When the old generation fills up, it triggers a
major collection which involves the entire object heap.
Both HotSpot and Solaris JDK use thread local object allocation pools for lock-free,
fast, and scalable object allocation. So, custom object pooling is not often required.
Consider pooling only if object construction cost is high and significantly affects
execution profiles.
Choosing the Garbage Collection Algorithm
The default collector for Java server class machines will optimize for throughput but
be tolerant of somewhat long pause times. If you would prefer to have minimal pause
times at the expense of some throughput and increased CPU usage, consider using the
CMS collector.
To use the CMS collector Follow this procedure.
1. Make sure that the system is not using 100 percent of its CPU.
2. Configure the CMS collector in the server instance.
To do this, add the following JVM options:
■
-XX:+UseConcMarkSweepGC
■
-XX:SoftRefLRUPolicyMSPerMB=1
Additional Information
Use the
jvmstat
utility to monitor HotSpot garbage collection. (See Further
Information.)
For detailed information on tuning the garbage collector, see Java SE 6 HotSpot Virtual
Machine Garbage Collection Tuning
(http://www.oracle.com/technetwork/java/javase/gc-tuning-6-14052
3.html).
Tracing Garbage Collection
The two primary measures of garbage collection performance are throughput and
pauses. Throughput is the percentage of the total time spent on other activities apart
from GC. Pauses are times when an application appears unresponsive due to GC.
Two other considerations are footprint and promptness. Footprint is the working size of
the JVM process, measured in pages and cache lines. Promptness is the time between
when an object becomes dead, and when the memory becomes available. This is an
important consideration for distributed systems.
Managing Memory and Garbage Collection
4-4 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
A particular generation size makes a trade-off between these four metrics. For
example, a large young generation likely maximizes throughput, but at the cost of
footprint and promptness. Conversely, using a small young generation and
incremental GC will minimize pauses, and thus increase promptness, but decrease
throughput.
JVM diagnostic output will display information on pauses due to garbage collection. If
you start the server in verbose mode (use the command
asadmin start-domain
--verbose
domain), then the command line argument
-verbose:gc
prints information
for every collection. Here is an example of output of the information generated with
this JVM flag:
[GC 50650K->21808K(76868K), 0.0478645 secs]
[GC 51197K->22305K(76868K), 0.0478645 secs]
[GC 52293K->23867K(76868K), 0.0478645 secs]
[Full GC 52970K->1690K(76868K), 0.54789968 secs]
On each line, the first number is the combined size of live objects before GC, the
second number is the size of live objects after GC, the number in parenthesis is the
total available space, which is the total heap minus one of the survivor spaces. The
final figure is the amount of time that the GC took. This example shows three minor
collections and one major collection. In the first GC, 50650 KB of objects existed before
collection and 21808 KB of objects after collection. This means that 28842 KB of objects
were dead and collected. The total heap size is 76868 KB. The collection process
required 0.0478645 seconds.
Other useful monitoring options include:
■
-XX:+PrintGCDetails
for more detailed logging information
■
-Xloggc:file
to save the information in a log file
Other Garbage Collector Settings
To specify the attributes for the Java virtual machine, use the Administration Console
and set the property under config-name > JVM settings (JVM options).
Setting the Maximum Permanent Generation
For applications that do not dynamically generate and load classes, the size of the
permanent generation does not affect GC performance. For applications that
dynamically generate and load classes (for example, JSP applications), the size of the
permanent generation does affect GC performance, since filling the permanent
generation can trigger a Full GC. Tune the maximum permanent generation with the
-XX:MaxPermSize
option.
Disabling Explicit Garbage Collection
Although applications can explicitly invoke GC with the
System.gc()
method, doing
so is a bad idea since this forces major collections, and inhibits scalability on large
systems. It is best to disable explicit GC by using the flag
-XX:+DisableExplicitGC
.
Managing Memory and Garbage Collection
Tuning the Java Runtime System 4-5
Setting the Frequency of Full Garbage Collection
GlassFish Server uses RMI in the Administration module for monitoring. Garbage
cannot be collected in RMI-based distributed applications without occasional local
collections, so RMI forces a periodic full collection. Control the frequency of these
collections with the property
-sun.rmi.dgc.client.gcInterval
. For example,
- java
-Dsun.rmi.dgc.client.gcInterval=3600000
specifies explicit collection once per
hour instead of the default rate of once per minute.
Tuning the Java Heap
This section discusses topics related to tuning the Java Heap for performance.
■Guidelines for Java Heap Sizing
■Heap Tuning Parameters
Guidelines for Java Heap Sizing
Maximum heap size depends on maximum address space per process. The following
table shows the maximum per-process address values for various platforms:
Maximum heap space is always smaller than maximum address space per process,
because the process also needs space for stack, libraries, and so on. To determine the
maximum heap space that can be allocated, use a profiling tool to examine the way
memory is used. Gauge the maximum stack space the process uses and the amount of
memory taken up libraries and other memory structures. The difference between the
Note: On Windows systems, setting the
-XX:+DisableExplicitGC
option might prevent the renaming or removal of open application
files. As a result, deployment, redeployment, or other operations
that attempt to rename or delete files might fail.
Application files can remain open because the files have been used
by class loaders to find classes or resources, or have been opened
explicitly by GlassFish Server or application code but never
explicitly closed. On Windows systems, open files cannot be
renamed or deleted. To overcome this limitation, GlassFish Server
uses the
System.gc()
method to garbage collect the Java object that
corresponds to an open file. When the Java object that corresponds
to an open file is garbage collected, the object's
finalize
method
closes the open channel to the file. GlassFish Server can then delete
or rename the file.
Table 4–1 Maximum Address Space Per Process
Operating System
Maximum Address Space Per
Process
Oracle/Redhat/Ubuntu Linux 32-bit 4 GB
Oracle/Redhat/Ubuntu Linux 64-bit Terabytes
Windows XP/2008/7 2 GB
Solaris x86 (32-bit) 4 GB
Solaris 32-bit 4 GB
Solaris 64-bit Terabytes
Managing Memory and Garbage Collection
4-6 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
maximum address space and the total of those values is the amount of memory that
can be allocated to the heap.
You can improve performance by increasing your heap size or using a different
garbage collector. In general, for long-running server applications, use the Java SE
throughput collector on machines with multiple processors (
-XX:+AggressiveHeap
)
and as large a heap as you can fit in the free memory of your machine.
Heap Tuning Parameters
You can control the heap size with the following JVM parameters:
■
-Xms
value
■
-Xmx
value
■
-XX:MinHeapFreeRatio=
minimum
■
-XX:MaxHeapFreeRatio=
maximum
■
-XX:NewRatio=
ratio
■
-XX:NewSize=
size
■
-XX:MaxNewSize=
size
■
-XX:+AggressiveHeap
The
-Xms
and
-Xmx
parameters define the minimum and maximum heap sizes,
respectively. Since GC occurs when the generations fill up, throughput is inversely
proportional to the amount of the memory available. By default, the JVM grows or
shrinks the heap at each GC to try to keep the proportion of free space to the living
objects at each collection within a specific range. This range is set as a percentage by
the parameters
-XX:MinHeapFreeRatio=
minimum and
-XX:MaxHeapFreeRatio=
maximum; and the total size bounded by
-Xms
and
-Xmx
.
Set the values of
-Xms
and
-Xmx
equal to each other for a fixed heap size. When the
heap grows or shrinks, the JVM must recalculate the old and new generation sizes to
maintain a predefined
NewRatio
.
The
NewSize
and
MaxNewSize
parameters control the new generation's minimum and
maximum size. Regulate the new generation size by setting these parameters equal.
The bigger the younger generation, the less often minor collections occur. The size of
the young generation relative to the old generation is controlled by
NewRatio
. For
example, setting
-XX:NewRatio=3
means that the ratio between the old and young
generation is 1:3, the combined size of eden and the survivor spaces will be fourth of
the heap.
By default, the GlassFish Server is invoked with the Java HotSpot Server JVM. The
default
NewRatio
for the Server JVM is 2: the old generation occupies 2/3 of the heap
while the new generation occupies 1/3. The larger new generation can accommodate
many more short-lived objects, decreasing the need for slow major collections. The old
generation is still sufficiently large enough to hold many long-lived objects.
To size the Java heap:
■Decide the total amount of memory you can afford for the JVM. Accordingly,
graph your own performance metric against young generation sizes to find the
best setting.
■Make plenty of memory available to the young generation. The default is
calculated from
NewRatio
and the
-Xmx
setting.
Managing Memory and Garbage Collection
Tuning the Java Runtime System 4-7
■Larger eden or younger generation spaces increase the spacing between full GCs.
But young space collections could take a proportionally longer time. In general,
keep the eden size between one fourth and one third the maximum heap size. The
old generation must be larger than the new generation.
For up-to-date defaults, see Java HotSpot VM Options
(http://www.oracle.com/technetwork/java/javase/tech/vmoptions-js
p-140102.html).
Example 4–1 Heap Configuration on Solaris
This is an exmple heap configuration used by GlassFish Server on Solaris for large
applications:
-Xms3584m
-Xmx3584m
-verbose:gc
-Dsun.rmi.dgc.client.gcInterval=3600000
Survivor Ratio Sizing The
SurvivorRatio
parameter controls the size of the two survivor
spaces. For example,
-XX:SurvivorRatio=6
sets the ratio between each survivor space
and eden to be 1:6, each survivor space will be one eighth of the young generation. The
default for Solaris is 32. If survivor spaces are too small, copying collection overflows
directly into the old generation. If survivor spaces are too large, they will be empty. At
each GC, the JVM determines the number of times an object can be copied before it is
tenured, called the tenure threshold. This threshold is chosen to keep the survivor
space half full.
Use the option
-XX:+PrintTenuringDistribution
to show the threshold and ages of
the objects in the new generation. It is useful for observing the lifetime distribution of
an application.
Rebasing DLLs on Windows
When the JVM initializes, it tries to allocate its heap using the
-Xms
setting. The base
addresses of GlassFish Server DLLs can restrict the amount of contiguous address
space available, causing JVM initialization to fail. The amount of contiguous address
space available for Java memory varies depending on the base addresses assigned to
the DLLs. You can increase the amount of contiguous address space available by
rebasing the GlassFish Server DLLs.
To prevent load address collisions, set preferred base addresses with the rebase utilty
that comes with Visual Studio and the Platform SDK. Use the rebase utility to reassign
the base addresses of the GlassFish Server DLLs to prevent relocations at load time
and increase the available process memory for the Java heap.
There are a few GlassFish Server DLLs that have non-default base addresses that can
cause collisions. For example:
■The
nspr
libraries have a preferred address of 0x30000000.
■The
icu
libraries have the address of 0x4A?00000.
Move these libraries near the system DLLs (
msvcrt.dll
is at
0x78000000
) to increase
the available maximum contiguous address space substantially. Since rebasing can be
done on any DLL, rebase to the DLLs after installing the GlassFish Server.
Further Information
4-8 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
To rebase the GlassFish Server's DLLs
Before You Begin
To perform rebasing, you need:
■Windows 2000
■Visual Studio and the Microsoft Framework SDK rebase utility
1. Make as-install\
bin
the default directory.
cd as-install\bin
2. Enter this command:
rebase -b 0x6000000 *.dll
3. Use the
dependencywalker
utility to make sure the DLLs were rebased correctly.
For more information, see the Dependency Walker website
(http://www.dependencywalker.com).
4. Increase the size for the Java heap, and set the JVM Option accordingly on the JVM
Settings page in the Admin Console.
5. Restart the GlassFish Server.
Example 4–2 Heap Configuration on Windows
This is an example heap configuration used by Oracle GlassFish Server for heavy
server-centric applications, on Windows, as set in the
domain.xml
file.
<jvm-options> -Xms1400m </jvm-options>
<jvm-options> -Xmx1400m </jvm-options>
See Also
For more information on rebasing, see MSDN documentation for rebase utility
(http://msdn.microsoft.com/library/default.asp?url=/library/en-u
s/tools/tools/rebase.asp).
Further Information
For more information on tuning the JVM, see:
■Java HotSpot VM Options
(http://www.oracle.com/technetwork/java/javase/tech/vmoptions
-jsp-140102.html)
■Frequently Asked Questions About the Java HotSpot Virtual Machine
(http://www.oracle.com/technetwork/java/hotspotfaq-138619.htm
l)
■Performance Documentation for the Java HotSpot VM
(http://www.oracle.com/technetwork/java/javase/tech/index-jsp
-136373.html)
■Java performance web page
(http://java.sun.com/javase/technologies/performance.jsp)
Further Information
Tuning the Java Runtime System 4-9
■Monitoring and Managing Java SE 6 Platform Applications
(http://java.sun.com/developer/technicalArticles/J2SE/monitor
ing/)
■The jvmstat monitoring utility
(http://java.sun.com/performance/jvmstat/)
Further Information
4-10 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
5
Tuning the Operating System and Platform 5-1
5Tuning the Operating System and Platform
This chapter discusses tuning the operating system (OS) for optimum performance. It
discusses the following topics:
■Server Scaling
■Solaris 10 Platform-Specific Tuning Information
■Tuning for the Solaris OS
■Tuning for Solaris on x86
■Tuning for Linux platforms
■Tuning UltraSPARC CMT-Based Systems
Server Scaling
This section provides recommendations for optimal performance scaling server for the
following server subsystems:
■Processors
■Memory
■Disk Space
■Networking
■UDP Buffer Sizes
Processors
The GlassFish Server automatically takes advantage of multiple CPUs. In general, the
effectiveness of multiple CPUs varies with the operating system and the workload, but
more processors will generally improve dynamic content performance.
Static content involves mostly input/output (I/O) rather than CPU activity. If the
server is tuned properly, increasing primary memory will increase its content caching
and thus increase the relative amount of time it spends in I/O versus CPU activity.
Studies have shown that doubling the number of CPUs increases servlet performance
by 50 to 80 percent.
Memory
See the section Hardware and Software Requirements in the GlassFish Server Release
Notes for specific memory recommendations for each supported operating system.
Server Scaling
5-2 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
Disk Space
It is best to have enough disk space for the OS, document tree, and log files. In most
cases 2GB total is sufficient.
Put the OS, swap/paging file, GlassFish Server logs, and document tree each on
separate hard drives. This way, if the log files fill up the log drive, the OS does not
suffer. Also, its easy to tell if the OS paging file is causing drive activity, for example.
OS vendors generally provide specific recommendations for how much swap or
paging space to allocate. Based on Oracle testing, GlassFish Server performs best with
swap space equal to RAM, plus enough to map the document tree.
Networking
To determine the bandwidth the application needs, determine the following values:
■The number of peak concurrent users (N peak) the server needs to handle.
■The average request size on your site, r. The average request can include multiple
documents. When in doubt, use the home page and all its associated files and
graphics.
■Decide how long, t, the average user will be willing to wait for a document at peak
utilization.
Then, the bandwidth required is:
Npeakr / t
For example, to support a peak of 50 users with an average document size of 24
Kbytes, and transferring each document in an average of 5 seconds, requires 240
Kbytes (1920 Kbit/s). So the site needs two T1 lines (each 1544 Kbit/s). This
bandwidth also allows some overhead for growth.
The server's network interface card must support more than the WAN to which it is
connected. For example, if you have up to three T1 lines, you can get by with a
10BaseT interface. Up to a T3 line (45 Mbit/s), you can use 100BaseT. But if you have
more than 50 Mbit/s of WAN bandwidth, consider configuring multiple 100BaseT
interfaces, or look at Gigabit Ethernet technology.
UDP Buffer Sizes
GlassFish Server uses User Datagram Protocol (UDP) for the transmission of multicast
messages to GlassFish Server instances in a cluster. For peak performance from a
GlassFish Server cluster that uses UDP multicast, limit the need to retransmit UDP
messages. To limit the need to retransmit UDP messages, set the size of the UDP
buffer to avoid excessive UDP datagram loss.
To Determine an Optimal UDP Buffer Size
The size of UDP buffer that is required to prevent excessive UDP datagram loss
depends on many factors, such as:
■The number of instances in the cluster
■The number of instances on each host
■The number of processors
■The amount of memory
■The speed of the hard disk for virtual memory
Server Scaling
Tuning the Operating System and Platform 5-3
If only one instance is running on each host in your cluster, the default UDP buffer
size should suffice. If several instances are running on each host, determine whether
the UDP buffer is large enough by testing for the loss of UDP packets.
1. Ensure that no GlassFish Server clusters are running.
If necessary, stop any running clusters as explained in "To Stop a Cluster" in
GlassFish Server Open Source Edition High Availability Administration Guide.
2. Determine the absolute number of lost UDP packets when no clusters are running.
How you determine the number of lost packets depends on the operating system.
For example:
■On Linux systems, use the
netstat -su
command and look for the
packet
receive errors
count in the
Udp
section.
■On AIX systems, use the
netstat -s
command and look for the
fragments
dropped (dup or out of space)
count in the
ip
section.
3. Start all the clusters that are configured for your installation of GlassFish Server.
Start each cluster as explained in "To Start a Cluster" in GlassFish Server Open
Source Edition High Availability Administration Guide.
4. Determine the absolute number of lost UDP packets after the clusters are started.
5. If the difference in the number of lost packets is significant, increase the size of the
UDP buffer.
To Set the UDP Buffer Size on Linux Systems
On Linux systems, a default UDP buffer size is set for the client, but not for the server.
Therefore, on Linux systems, the UDP buffer size might have to be increased. Setting
the UDP buffer size involves setting the following kernel parameters:
■
net.core.rmem_max
■
net.core.wmem_max
■
net.core.rmem_default
■
net.core.wmem_default
Set the kernel parameters in the
/etc/sysctl.conf
file or at runtime.
If you set the parameters in the
/etc/sysctl.conf
file, the settings are preserved
when the system is rebooted. If you set the parameters at runtime, the settings are not
preserved when the system is rebooted.
■To set the parameters in the
/etc/sysctl.conf
file, add or edit the following lines
in the file:
net.core.rmem_max=rmem-max
net.core.wmem_max=wmem-max
net.core.rmem_default=rmem-default
net.core.wmem_default=wmem-default
Note: On Linux systems, the default UDP buffer size might be
insufficient even if only one instance is running on each host. In
this situation, set the UDP buffer size as explained in To Set the
UDP Buffer Size on Linux Systems.
Solaris 10 Platform-Specific Tuning Information
5-4 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
■To set the parameters at runtime, use the sysctl command.
$ /sbin/sysctl -w net.core.rmem_max=rmem-max \
net.core.wmem_max=wmem-max \
net.core.rmem_default=rmem-default \
net.core.wmem_default=wmem-default
Example 5–1 Setting the UDP Buffer Size in the
/etc/sysctl.conf
File
This example shows the lines in the
/etc/sysctl.conf
file for setting the kernel
parameters for controlling the UDP buffer size to 524288.
net.core.rmem_max=524288
net.core.wmem_max=524288
net.core.rmem_default=524288
net.core.wmem_default=524288
Example 5–2 Setting the UDP Buffer Size at Runtime
This example sets the kernel parameters for controlling the UDP buffer size to 524288
at runtime.
$ /sbin/sysctl -w net.core.rmem_max=524288 \
net.core.wmem_max=52428 \
net.core.rmem_default=52428 \
net.core.wmem_default=524288
net.core.rmem_max = 524288
net.core.wmem_max = 52428
net.core.rmem_default = 52428
net.core.wmem_default = 524288
Solaris 10 Platform-Specific Tuning Information
Solaris Dynamic Tracing (DTrace) is a comprehensive dynamic tracing framework for
the Solaris Operating System (OS). You can use the DTrace Toolkit to monitor the
system. The DTrace Toolkit is available through the OpenSolaris project from the
DTraceToolkit page
(http://hub.opensolaris.org/bin/view/Community+Group+dtrace/dtra
cetoolkit).
Tuning for the Solaris OS
■Tuning Parameters
■File Descriptor Setting
Tuning Parameters
Tuning Solaris TCP/IP settings benefits programs that open and close many sockets.
Since the GlassFish Server operates with a small fixed set of connections, the
performance gain might not be significant.
The following table shows Solaris tuning parameters that affect performance and
scalability benchmarking. These values are examples of how to tune your system for
best performance.
Tuning for the Solaris OS
Tuning the Operating System and Platform 5-5
Sizing the Connection Hash Table
The connection hash table keeps all the information for active TCP connections. Use
the following command to get the size of the connection hash table:
ndd -get /dev/tcp tcp_conn_hash
This value does not limit the number of connections, but it can cause connection
hashing to take longer. The default size is 512.
To make lookups more efficient, set the value to half of the number of concurrent TCP
connections that are expected on the server. You can set this value only in
/etc/system
, and it becomes effective at boot time.
Use the following command to get the current number of TCP connections.
netstat -nP tcp|wc -l
Table 5–1 Tuning Parameters for Solaris
Parameter Scope Default
Tuned
Value Comments
rlim_fd_max /etc/system
65536 65536 Limit of process open file descriptors. Set to
account for expected load (for associated
sockets, files, and pipes if any).
rlim_fd_cur /etc/system
1024 8192
sq_max_size /etc/system
2 0 Controls streams driver queue size; setting to
0 makes it infinite so the performance runs
won't be hit by lack of buffer space. Set on
clients too. Note that setting
sq_max_size
to 0
might not be optimal for production systems
with high network traffic.
tcp_close_wait_interval ndd /dev/tcp
240000 60000 Set on clients too.
tcp_time_wait_interval ndd /dev/tcp
240000 60000 Set on clients too.
tcp_conn_req_max_q ndd /dev/tcp
128 1024
tcp_conn_req_max_q0 ndd /dev/tcp
1024 4096
tcp_ip_abort_interval ndd /dev/tcp
480000 60000
tcp_keepalive_interval ndd /dev/tcp
7200000 900000 For high traffic web sites, lower this value.
tcp_rexmit_interval_
initial
ndd /dev/tcp
3000 3000 If retransmission is greater than 30-40%, you
should increase this value.
tcp_rexmit_interval_max ndd /dev/tcp
240000 10000
tcp_rexmit_interval_min ndd /dev/tcp
200 3000
tcp_smallest_anon_port ndd /dev/tcp
32768 1024 Set on clients too.
tcp_slow_start_initial ndd /dev/tcp
1 2 Slightly faster transmission of small amounts
of data.
tcp_xmit_hiwat ndd /dev/tcp
8129 32768 Size of transmit buffer.
tcp_recv_hiwat ndd /dev/tcp
8129 32768 Size of receive buffer.
tcp_conn_hash_size ndd /dev/tcp
512 8192 Size of connection hash table. See Sizing the
Connection Hash Table.
Tuning for Solaris on x86
5-6 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
File Descriptor Setting
On the Solaris OS, setting the maximum number of open files property using
ulimit
has the biggest impact on efforts to support the maximum number of RMI/IIOP
clients.
To increase the hard limit, add the following command to
/etc/system
and reboot it
once:
set rlim_fd_max = 8192
Verify this hard limit by using the following command:
ulimit -a -H
Once the above hard limit is set, increase the value of this property explicitly (up to
this limit) using the following command:
ulimit -n 8192
Verify this limit by using the following command:
ulimit -a
For example, with the default
ulimit
of 64, a simple test driver can support only 25
concurrent clients, but with
ulimit
set to 8192, the same test driver can support 120
concurrent clients. The test driver spawned multiple threads, each of which performed
a JNDI lookup and repeatedly called the same business method with a think (delay)
time of 500 ms between business method calls, exchanging data of about 100 KB. These
settings apply to RMI/IIOP clients on the Solaris OS.
Tuning for Solaris on x86
The following are some options to consider when tuning Solaris on x86 for GlassFish
Server:
■File Descriptors
■IP Stack Settings
Some of the values depend on the system resources available. After making any
changes to
/etc/system
, reboot the machines.
File Descriptors
Add (or edit) the following lines in the
/etc/system
file:
set rlim_fd_max=65536
set rlim_fd_cur=65536
set sq_max_size=0
set tcp:tcp_conn_hash_size=8192
set autoup=60
set pcisch:pci_stream_buf_enable=0
These settings affect the file descriptors.
IP Stack Settings
Add (or edit) the following lines in the
/etc/system
file:
set ip:tcp_squeue_wput=1
set ip:tcp_squeue_close=1
Tuning for Linux platforms
Tuning the Operating System and Platform 5-7
set ip:ip_squeue_bind=1
set ip:ip_squeue_worker_wait=10
set ip:ip_squeue_profile=0
These settings tune the IP stack.
To preserve the changes to the file between system reboots, place the following
changes to the default TCP variables in a startup script that gets executed when the
system reboots:
ndd -set /dev/tcp tcp_time_wait_interval 60000
ndd -set /dev/tcp tcp_conn_req_max_q 16384
ndd -set /dev/tcp tcp_conn_req_max_q0 16384
ndd -set /dev/tcp tcp_ip_abort_interval 60000
ndd -set /dev/tcp tcp_keepalive_interval 7200000
ndd -set /dev/tcp tcp_rexmit_interval_initial 4000
ndd -set /dev/tcp tcp_rexmit_interval_min 3000
ndd -set /dev/tcp tcp_rexmit_interval_max 10000
ndd -set /dev/tcp tcp_smallest_anon_port 32768
ndd -set /dev/tcp tcp_slow_start_initial 2
ndd -set /dev/tcp tcp_xmit_hiwat 32768
ndd -set /dev/tcp tcp_recv_hiwat 32768
Tuning for Linux platforms
To tune for maximum performance on Linux, you need to make adjustments to the
following:
■Startup Files
■File Descriptors
■Virtual Memory
■Network Interface
■Disk I/O Settings
■TCP/IP Settings
Startup Files
The following parameters must be added to the
/etc/rc.d/rc.local
file that gets
executed during system startup.
<-- begin
#max file count updated ~256 descriptors per 4Mb.
Specify number of file descriptors based on the amount of system RAM.
echo "6553"> /proc/sys/fs/file-max
#inode-max 3-4 times the file-max
#file not present!!!!!
#echo"262144"> /proc/sys/fs/inode-max
#make more local ports available
echo 1024 25000> /proc/sys/net/ipv4/ip_local_port_range
#increase the memory available with socket buffers
echo 2621143> /proc/sys/net/core/rmem_max
echo 262143> /proc/sys/net/core/rmem_default
#above configuration for 2.4.X kernels
echo 4096 131072 262143> /proc/sys/net/ipv4/tcp_rmem
echo 4096 13107262143> /proc/sys/net/ipv4/tcp_wmem
#disable "RFC2018 TCP Selective Acknowledgements," and
Tuning for Linux platforms
5-8 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
"RFC1323 TCP timestamps" echo 0> /proc/sys/net/ipv4/tcp_sack
echo 0> /proc/sys/net/ipv4/tcp_timestamps
#double maximum amount of memory allocated to shm at runtime
echo "67108864"> /proc/sys/kernel/shmmax
#improve virtual memory VM subsystem of the Linux
echo "100 1200 128 512 15 5000 500 1884 2"> /proc/sys/vm/bdflush
#we also do a sysctl
sysctl -p /etc/sysctl.conf
-- end -->
Additionally, create an
/etc/sysctl.conf
file and append it with the following
values:
<-- begin
#Disables packet forwarding
net.ipv4.ip_forward = 0
#Enables source route verification
net.ipv4.conf.default.rp_filter = 1
#Disables the magic-sysrq key
kernel.sysrq = 0
fs.file-max=65536
vm.bdflush = 100 1200 128 512 15 5000 500 1884 2
net.ipv4.ip_local_port_range = 1024 65000
net.core.rmem_max= 262143
net.core.rmem_default = 262143
net.ipv4.tcp_rmem = 4096 131072 262143
net.ipv4.tcp_wmem = 4096 131072 262143
net.ipv4.tcp_sack = 0
net.ipv4.tcp_timestamps = 0
kernel.shmmax = 67108864
File Descriptors
You may need to increase the number of file descriptors from the default. Having a
higher number of file descriptors ensures that the server can open sockets under high
load and not abort requests coming in from clients.
Start by checking system limits for file descriptors with this command:
cat /proc/sys/fs/file-max
8192
The current limit shown is 8192. To increase it to 65535, use the following command
(as root):
echo "65535"> /proc/sys/fs/file-max
To make this value to survive a system reboot, add it to
/etc/sysctl.conf
and specify
the maximum number of open files permitted:
fs.file-max = 65535
Note that the parameter is not
proc.sys.fs.file-max
, as one might expect.
To list the available parameters that can be modified using
sysctl
:
sysctl -a
To load new values from the
sysctl.conf
file:
sysctl -p /etc/sysctl.conf
Tuning for Linux platforms
Tuning the Operating System and Platform 5-9
To check and modify limits per shell, use the following command:
limit
The output will look something like this:
cputime unlimited
filesize unlimited
datasize unlimited
stacksize 8192 kbytes
coredumpsize 0 kbytes
memoryuse unlimited
descriptors 1024
memorylocked unlimited
maxproc 8146
openfiles 1024
The
openfiles
and
descriptors
show a limit of 1024. To increase the limit to 65535 for
all users, edit
/etc/security/limits.conf
as root, and modify or add the
nofile
setting (number of file) entries:
* soft nofile 65535
* hard nofile 65535
The character "
*
" is a wildcard that identifies all users. You could also specify a user ID
instead.
Then edit
/etc/pam.d/login
and add the line:
session required /lib/security/pam_limits.so
On Red Hat, you also need to edit
/etc/pam.d/sshd
and add the following line:
session required /lib/security/pam_limits.so
On many systems, this procedure will be sufficient. Log in as a regular user and try it
before doing the remaining steps. The remaining steps might not be required,
depending on how pluggable authentication modules (PAM) and secure shell (SSH)
are configured.
Virtual Memory
To change virtual memory settings, add the following to
/etc/rc.local
:
echo 100 1200 128 512 15 5000 500 1884 2> /proc/sys/vm/bdflush
For more information, view the man pages for
bdflush
.
Network Interface
To ensure that the network interface is operating in full duplex mode, add the
following entry into
/etc/rc.local
:
mii-tool -F 100baseTx-FD eth0
where eth0 is the name of the network interface card (NIC).
Disk I/O Settings
Tuning for Linux platforms
5-10 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
To tune disk I/O performance for non SCSI disks
1. Test the disk speed.
Use this command:
/sbin/hdparm -t /dev/hdX
2. Enable direct memory access (DMA).
Use this command:
/sbin/hdparm -d1 /dev/hdX
3. Check the speed again using the
hdparm
command.
Given that DMA is not enabled by default, the transfer rate might have improved
considerably. In order to do this at every reboot, add the
/sbin/hdparm -d1
/dev/hdX
line to
/etc/conf.d/local.start
,
/etc/init.d/rc.local
, or whatever
the startup script is called.
For information on SCSI disks, see: System Tuning for Linux Servers — SCSI
(http://people.redhat.com/alikins/system_tuning.html#scsi).
TCP/IP Settings
To tune the TCP/IP settings
1. Add the following entry to
/etc/rc.local
echo 30> /proc/sys/net/ipv4/tcp_fin_timeout
echo 60000> /proc/sys/net/ipv4/tcp_keepalive_time
echo 15000> /proc/sys/net/ipv4/tcp_keepalive_intvl
echo 0> /proc/sys/net/ipv4/tcp_window_scaling
2. Add the following to
/etc/sysctl.conf
# Disables packet forwarding
net.ipv4.ip_forward = 0
# Enables source route verification
net.ipv4.conf.default.rp_filter = 1
# Disables the magic-sysrq key
kernel.sysrq = 0
net.ipv4.ip_local_port_range = 1204 65000
net.core.rmem_max = 262140
net.core.rmem_default = 262140
net.ipv4.tcp_rmem = 4096 131072 262140
net.ipv4.tcp_wmem = 4096 131072 262140
net.ipv4.tcp_sack = 0
net.ipv4.tcp_timestamps = 0
net.ipv4.tcp_window_scaling = 0
net.ipv4.tcp_keepalive_time = 60000
net.ipv4.tcp_keepalive_intvl = 15000
net.ipv4.tcp_fin_timeout = 30
3. Add the following as the last entry in
/etc/rc.local
sysctl -p /etc/sysctl.conf
4. Reboot the system.
5. Use this command to increase the size of the transmit buffer:
Tuning UltraSPARC CMT-Based Systems
Tuning the Operating System and Platform 5-11
tcp_recv_hiwat ndd /dev/tcp 8129 32768
Tuning UltraSPARC CMT-Based Systems
Use a combination of tunable parameters and other parameters to tune UltraSPARC
CMT-based systems. These values are an example of how you might tune your system
to achieve the desired result.
Tuning Operating System and TCP Settings
The following table shows the operating system tuning for Solaris 10 used when
benchmarking for performance and scalability on UtraSPARC CMT-based systems
(64-bit systems).
Note that the IPGE driver version is 1.25.25.
Disk Configuration
If HTTP access is logged, follow these guidelines for the disk:
Table 5–2 Tuning 64-bit Systems for Performance Benchmarking
Parameter Scope
Default
Value
Tuned
Value Comments
rlim_fd_max /etc/system
65536 260000 Process open file descriptors limit; should
account for the expected load (for the
associated sockets, files, pipes if any).
hires_tick /etc/system
1
sq_max_size /etc/system
2 0 Controls streams driver queue size; setting
to 0 makes it infinite so the performance
runs won't be hit by lack of buffer space.
Set on clients too. Note that setting
sq_max_
size
to 0 might not be optimal for
production systems with high network
traffic.
ip:ip_squeue_bind
0
ip:ip_squeue_fanout
1
ipge:ipge_taskq_disable /etc/system
0
ipge:ipge_tx_ring_size /etc/system
2048
ipge:ipge_srv_fifo_depth /etc/system
2048
ipge:ipge_bcopy_thresh /etc/system
384
ipge:ipge_dvma_thresh /etc/system
384
ipge:ipge_tx_syncq /etc/system
1
tcp_conn_req_max_q ndd /dev/tcp
128 3000
tcp_conn_req_max_q0 ndd /dev/tcp
1024 3000
tcp_max_buf ndd /dev/tcp
4194304
tcp_cwnd_max ndd/dev/tcp
2097152
tcp_xmit_hiwat ndd /dev/tcp
8129 400000 To increase the transmit buffer.
tcp_recv_hiwat ndd /dev/tcp
8129 400000 To increase the receive buffer.
Tuning UltraSPARC CMT-Based Systems
5-12 GlassFish Server Open Source Edition 4.0 Performance Tuning Guide
■Write access logs on faster disks or attached storage.
■If running multiple instances, move the logs for each instance onto separate disks
as much as possible.
■Enable the disk read/write cache. Note that if you enable write cache on the disk,
some writes might be lost if the disk fails.
■Consider mounting the disks with the following options, which might yield better
disk performance:
nologging
,
directio
,
noatime
.
Network Configuration
If more than one network interface card is used, make sure the network interrupts are
not all going to the same core. Run the following script to disable interrupts:
allpsr=`/usr/sbin/psrinfo | grep -v off-line | awk '{ print $1 }'`
set $allpsr
numpsr=$#
while [ $numpsr -gt 0 ];
do
shift
numpsr=`expr $numpsr - 1`
tmp=1
while [ $tmp -ne 4 ];
do
/usr/sbin/psradm -i $1
shift
numpsr=`expr $numpsr - 1`
tmp=`expr $tmp + 1`
done
done
Put all network interfaces into a single group. For example:
$ifconfig ipge0 group webserver
$ifconfig ipge1 group webserver

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