Sun Microsystems 820434310 User Manual

Sun GlassFish Enterprise Server

2.1 PerformanceTuning Guide

Sun Microsystems, Inc. 4150 Network Circle Santa Clara, CA 95054 U.S.A.

Part No: 820–4343–10 January 2009

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Contents

Preface ...................................................................................................................................................13

1 Overview of Enterprise Server PerformanceTuning ..................................................................... 17

Process Overview ................................................................................................................................ 17

▼ Performance Tuning Sequence .................................................................................................. 18

Understanding Operational Requirements ..................................................................................... 19

Application Architecture ............................................................................................................ 19

Security Requirements ................................................................................................................ 21

Hardware Resources .................................................................................................................... 22

Administration ............................................................................................................................. 23

General Tuning Concepts .................................................................................................................. 23

Capacity Planning ........................................................................................................................ 24

User Expectations ........................................................................................................................ 25

Further Information ............................................................................................................................ 26

2 TuningYour Application .....................................................................................................................27

Java Programming Guidelines ........................................................................................................... 27

AvoidSerialization and Deserialization .................................................................................... 27

Java Server Page and Servlet Tuning ................................................................................................. 29

Suggested Coding Practices ........................................................................................................30

EJB Performance Tuning .................................................................................................................... 32

Goals .............................................................................................................................................. 32

Monitoring EJB Components .................................................................................................... 32

General Guidelines ...................................................................................................................... 35

Using Local and Remote Interfaces ........................................................................................... 36

Improving Performance of EJB Transactions .......................................................................... 38

Using Special Techniques ........................................................................................................... 39

Contents

Tuning Tips for Specic Types of EJB Components ............................................................... 42

JDBC and Database Access ......................................................................................................... 46

Tuning Message-Driven Beans .................................................................................................. 47

3 Tuningthe Enterprise Server ............................................................................................................. 49

Deployment Settings ........................................................................................................................... 49

Disable Auto-deployment ........................................................................................................... 50

Use Pre-compiled JavaServer Pages ........................................................................................... 50

Disable Dynamic Application Reloading .................................................................................. 50

Logger Settings ..................................................................................................................................... 50

General Settings ........................................................................................................................... 51

Log Levels ...................................................................................................................................... 51

Web Container Settings ...................................................................................................................... 51

Session Properties: Session Timeout ......................................................................................... 51

Manager Properties: Reap Interval ............................................................................................ 52

Disable Dynamic JSP Reloading ................................................................................................ 52

EJB Container Settings ........................................................................................................................ 53

Monitoring the EJB Container ................................................................................................... 53

Tuning the EJB Container ...........................................................................................................53

Java Message Service Settings ............................................................................................................. 58

Transaction Service Settings .............................................................................................................. 58

Monitoring the Transaction Service .......................................................................................... 58

Tuning the Transaction Service ................................................................................................. 59

HTTP Service Settings ........................................................................................................................ 60

Monitoring the HTTP Service .................................................................................................... 60

Connection Queue ....................................................................................................................... 64

Tuning the HTTP Service ........................................................................................................... 64

Tuning HTTP Listener Settings ................................................................................................. 69

ORB Settings ........................................................................................................................................ 70

Overview ....................................................................................................................................... 70

How a Client Connects to the ORB ............................................................................................ 70

Monitoring the ORB .................................................................................................................... 70

Tuning the ORB ........................................................................................................................... 71

Thread Pool Sizing ....................................................................................................................... 74

Examining IIOP Messages .......................................................................................................... 74

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 20094

Contents

Improving ORB Performance with Java Serialization ............................................................. 75

Thread Pool Settings ........................................................................................................................... 76

Tuning Thread Pools (Unix /Linux only) ................................................................................. 76

Resources .............................................................................................................................................. 77

JDBC Connection Pool Settings ................................................................................................. 77

Connector Connection Pool Settings ........................................................................................ 80

4 Tuningthe Java Runtime System ......................................................................................................83

Java Virtual Machine Settings ............................................................................................................ 83

Managing Memory and Garbage Collection .................................................................................... 84

Tuning the Garbage Collector .................................................................................................... 84

Tracing Garbage Collection ........................................................................................................86

Other Garbage Collector Settings .............................................................................................. 86

Tuning the Java Heap .................................................................................................................. 87

Rebasing DLLs on Windows ...................................................................................................... 89

Further Information ............................................................................................................................ 91

5 Tuningthe Operating Systemand Platform ................................................................................... 93

Server Scaling ....................................................................................................................................... 93

Processors ..................................................................................................................................... 93

Memory ......................................................................................................................................... 94

Disk Space ..................................................................................................................................... 94

Networking ................................................................................................................................... 94

Solaris 10 Platform-Specic Tuning Information ........................................................................... 95

Tuning for the Solaris OS ................................................................................................................... 95

Tuning Parameters ...................................................................................................................... 95

File Descriptor Setting ................................................................................................................. 97

Linux Conguration ........................................................................................................................... 97

Tuning for Solaris on x86 ................................................................................................................... 98

File Descriptors ............................................................................................................................ 99

IP Stack Settings ........................................................................................................................... 99

Tuning for Linux platforms ............................................................................................................. 100

File Descriptors .......................................................................................................................... 100

Virtual Memory ......................................................................................................................... 101

Network Interface ...................................................................................................................... 102

Contents

Disk I/O Settings ........................................................................................................................ 102

TCP/IP Settings .......................................................................................................................... 102

Tuning UltraSPARCT1–Based Systems ........................................................................................ 103

Tuning Operating System and TCP Settings .......................................................................... 103

Disk Conguration .................................................................................................................... 105

Network Conguration ............................................................................................................. 105

Start Options ............................................................................................................................... 105

6 Tuningfor High-Availability ............................................................................................................107

Tuning HADB .................................................................................................................................... 107

Disk Use ...................................................................................................................................... 107

Memory Allocation .................................................................................................................... 109

Performance ............................................................................................................................... 110

Operating System Conguration ............................................................................................. 116

Tuning the Enterprise Server for High-Availability ...................................................................... 116

Tuning Session Persistence Frequency .................................................................................... 117

Session Persistence Scope .......................................................................................................... 118

Session Size ................................................................................................................................. 118

Checkpointing Stateful Session Beans ..................................................................................... 119

Conguring the JDBC Connection Pool ................................................................................. 119

Conguring the Load Balancer ........................................................................................................ 120

Enabling the Health Checker .................................................................................................... 120

Index ................................................................................................................................................... 123

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 20096

Figures

FIGURE 1–1 Java EE Application Model ....................................................................................... 20

Tables

TABLE 1–1 PerformanceTuning Roadmap ............................................................................... 17

TABLE 1–2 Factors That Aect Performance ............................................................................. 24

TABLE 3–1 Bean Type Pooling or Caching ................................................................................ 53

TABLE 3–2 EJB Cache and Pool Settings .................................................................................... 56

TABLE 3–3 Tunable ORB Settings ...............................................................................................71

TABLE 3–4 Connection PoolSizing ............................................................................................ 78

TABLE 4–1 Maximum Address Space Per Process .................................................................... 87

TABLE 5–1 Tuning Parameters for Solaris .................................................................................95

TABLE 5–2 Tuning 64–bit Systems for Performance Benchmarking ...................................104

Examples

EXAMPLE 4–1 Heap Conguration on Solaris ................................................................................89

EXAMPLE 4–2 Heap Conguration on Windows ........................................................................... 90

Preface

The Performance Tuning Guide describes how to get the best performance with Enterprise Server.

This preface contains information about and conventions for the entire Sun GlassFish

Enterprise Server documentation set.

Sun GlassFish Enterprise Server Documentation Set

TABLE P–1 Books in the Enterprise Server Documentation Set

Book Title Description

Documentation Center Enterprise Server documentation topics organized by task and subject.

Release Notes Late-breaking information about the software and the documentation. Includes a

comprehensive, table-based summary of the supported hardware, operating system, Java Development Kit (JDKTM), and database drivers.

Quick Start Guide How to get started with the Enterprise Server product.

Installation Guide Installing the software and its components.

Application Deployment Guide Deployment of applications and application components to the Enterprise Server. Includes

information about deployment descriptors.

Developer’s Guide Creating and implementing Java Platform, Enterprise Edition (Java EE platform) applications

intended to run on the Enterprise Server that follow the open Java standards model for Java EE components and APIs. Includes information about developer tools, security, debugging, and creating lifecycle modules.

Java EE 5 Tutorial Using Java EE 5 platform technologies and APIs to develop Java EE applications.

Java WSIT Tutorial Developing web applications using the Web Service Interoperability Technologies (WSIT).

Describes how, when, and why to use the WSIT technologies and the features and options that each technology supports.

Administration Guide System administration for the Enterprise Server, including conguration, monitoring,

security, resource management, and web services management.

Preface

TABLE P–1 Books in the Enterprise Server Documentation Set (Continued)

Book Title Description

High Availability Administration Guide

Administration Reference Editing the Enterprise Server conguration le, domain.xml.

Performance Tuning Guide Tuning the Enterprise Server to improve performance.

Reference Manual Utility commands available with the Enterprise Server; written in man page style. Includes

Setting up clusters, working with node agents, and using load balancers.

the asadmin command line interface.

Default Paths and File Names

The following table describes the default paths and le names that are used in this book.

TABLE P–2 Default Pathsand File Names

Placeholder Description Default Value

as-install Represents the base installation directory for

Enterprise Server.

SolarisTMand Linux installations, non-root user:

user’s-home-directory/SUNWappserver

Solaris and Linux installations, root user:

/opt/SUNWappserver

Windows, all installations:

SystemDrive:\Sun\AppServer

domain-root-dir Represents the directory containing all

domains.

domain-dir Represents the directory for a domain.

In conguration les, you might see domain-dir represented as follows:

${com.sun.aas.instanceRoot}

instance-dir Represents the directory for a server instance. domain-dir/instance-dir

samples-dir Represents the directory containing sample

applications.

docs-dir Represents the directory containing

documentation.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200914

All installations:

as-install/domains/

domain-root-dir/domain-dir

as-install/samples

as-install/docs

Typographic Conventions

The following table describes the typographic changes that are used in this book.

TABLE P–3 TypographicConventions

Typeface Meaning Example

Preface

AaBbCc123 Thenames of commands, les, and

directories, and onscreen computer output

AaBbCc123 Whatyou type, contrasted with onscreen

computer output

AaBbCc123 A placeholder to be replaced with a real

name or value

AaBbCc123 Book titles, new terms, and terms to be

emphasized (note that some emphasized items appear bold online)

Symbol Conventions

The following table explains symbols that might be used in this book.

TABLE P–4 SymbolConventions

Symbol Description Example Meaning

[] Contains optional arguments

and command options.

Edit your .login le.

Use ls -a to list all les.

machine_name% you have mail.

machine_name% su

Password:

The command to remove a le is rm lename.

Read Chapter 6 in the User's Guide.

A cache is a copy that is stored locally.

Do not save the le.

ls [-l] The -l option is not required.

{|} Contains a set of choices for a

required command option.

${ } Indicates a variable

reference.

- Joins simultaneous multiple keystrokes.

+ Joins consecutive multiple

keystrokes.

-d {y|n} The -d option requires that you use either the y argument or the n argument.

${com.sun.javaRoot} References the value of the

com.sun.javaRoot variable.

Control-A Press the Control key while you press

the A key.

Ctrl+A+N Press the Control key, release it, and

then press the subsequent keys.

Preface

TABLE P–4 SymbolConventions (Continued)

Symbol Description Example Meaning

→ Indicates menu item

selection in a graphical user interface.

File → New → Templates From the File menu, choose New.

Documentation, Support, andTraining

The Sun web site provides information about the following additional resources:

■

Documentation (http://www.sun.com/documentation/)

■

Support (http://www.sun.com/support/)

■

Training (http://www.sun.com/training/)

Third-PartyWeb Site References

Third-party URLs are referenced in this document and provide additional, related information.

Note – Sun is not responsible for the availability of third-party web sites mentioned in this

document. Sun does not endorse and is not responsible or liable for any content, advertising, products, or other materials that are available on or through such sites or resources. Sun will not be responsible or liable for any actual or alleged damage or loss caused or alleged to be caused by or in connection with use of or reliance on any such content, goods, or services that are available on or through such sites or resources.

From the New submenu, choose Templates.

Sun WelcomesYour Comments

Sun is interested in improving its documentation and welcomes your comments and suggestions.

To share your comments, go to provide the document title and part number. The part number is a seven-digit or nine-digit number that can be found on the title page of the book or at the top of the document.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200916

http://docs.sun.com and click Feedback. In the online form,

CHAPTER 1

Overview of Enterprise Server Performance Tuning

You can signicantly improve performance of the Sun GlassFish Enterprise Server and of applications deployed to it by adjusting a few deployment and server conguration settings. However, it is important to understand the environment and performance goals. An optimal conguration for a production environment might not be optimal for a development environment.

This chapter discusses the following topics:

■

“Process Overview” on page 17

■

“Understanding Operational Requirements” on page 19

■

“General Tuning Concepts” on page 23

■

“Further Information” on page 26

Process Overview

The following table outlines the overall administration process, and shows where performance tuning ts in the sequence.

TABLE 1–1 PerformanceTuning Roadmap

Step Description of Task Location of Instructions

1 Design: Decide on the high-availability topology

and set up the Application Server and, if you are using HADBfor session persistence, high-availability database (HADB)systems.

2 Capacity Planning: Make sure the systems have

sucient resources to perform well.

Deployment Planning Guide

Process Overview

TABLE 1–1 PerformanceTuning Roadmap (Continued)

Step Description of Task Location of Instructions

3 Installation: If you are using HADB for session

persistence, ensure that the HADB software is installed.

4 Deployment: Install and run your applications.

Familiarize yourself with how to congure and administer the Enterprise Server.

5 Tuning: Tune the following items:

■

Applications

■

Enterprise Server

■

Java Runtime System

■

Operating system and platform

■

High availability features

▼

PerformanceTuningSequence

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:

Tuneyour application, described in

Installation Guide

Application Deployment Guide

Administration Guide

The following chapters:

■

Chapter 2, “Tuning Your Application”

■

Chapter 3, “Tuning the Enterprise Server”

■

Chapter 4, “Tuning the Java Runtime System”

■

Chapter 5, “Tuning the Operating System and Platform”

■

Chapter 6, “Tuning for High-Availability”

Chapter 2,“TuningYourApplication”

Tunethe server, described in Chapter 3,“Tuning the Enterprise Server”Chapter 3,“Tuning the

Enterprise Server”

Tunethe high availability database, described in Chapter 6,“Tuning for High-Availability”

Tunethe Java runtime system, described in Chapter 4,“Tuning the Java Runtime System”

Tunethe operating system, described in Chapter 5,“Tuningthe Operating System and Platform”

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200918

Understanding Operational Requirements

Before you begin to deploy and tune your application on the Application Server, it is important to clearly dene the operational environment. The operational environment is determined by high-level constraints and requirements such as:

■

“Application Architecture” on page 19

■

“Security Requirements” on page 21

■

“Hardware Resources” on page 22

Application Architecture

The Java EE Application model, as shown in the following gure, is very exible; 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.

Understanding Operational Requirements

Chapter 1 • Overview of Enterprise Server Performance Tuning 19

Understanding Operational Requirements

Client-Side

Presentation

Browser

Pure

HTML

Java

Applet

Desktop

Java

Application

Other

Device

Server-Side

Presentation

Web

Server

JSP

Java

Servlet

Server-Side

Business Logic

EJB

Container

EJB

Enterprise

Information

System

J2EE

Client

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 Application Server integrates the web and EJB containers in a single process. Local access to EJB components from servlets is very ecient. 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 Application 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 Application Server deployment, and when deploying a new business application to an existing application server deployment.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200920

J2EE

Platform

J2EE

Platform

Understanding Operational Requirements

Security Requirements

Most business applications require security. This section discusses security considerations and decisions.

User Authentication and Authorization

Application users must be authenticated. The Application Server provides three dierent choices for user authentication: le-based, LDAP, and Solaris.

The default le 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 proles. Small to medium enterprises that do not already use a directory server may nd it advantageous to leverage investment in Solaris security infrastructure.

For more information on security realms, see

GlassFish Enterprise Server 2.1 Administration 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 Sun Java System Directory Server documentation for more information on deployment, sizing, and availability guidelines.

An authenticated user’saccess 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.

Chapter 9, “Conguring Security,” in Sun

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 ow between the browser and Application Server. Online shopping applications encrypt trac 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 Application 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:

Chapter 1 • Overview of Enterprise Server Performance Tuning 21

Understanding Operational Requirements

■

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 signicant amount of static text and image content and some business logic that executes on the Application Server, behind the most secure rewall. Application Server provides secure reverse proxy plugins to enable integration with popular web servers. The Application 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 Application Server support SSL encryption between the web server and application server tier. If SSL 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 Application Server, please refer to

Administration Guide

Chapter 9, “Conguring Security,” in Sun GlassFish Enterprise Server 2.1

Hardware Resources

The type and quantity of hardware resources available greatly inuence performance tuning and site planning.

The Application Server provides excellent vertical scalability. It can scale to eciently 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.

The Application 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 eciently 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 approach requires administration of more application server instances and hardware nodes.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200922

General Tuning Concepts

Administration

A single Application 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 dierent 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.

The Application Server supports virtual server capability for web applications. For example, a web application hosting service provider can host dierent URL domains on a single Application Server process for ecient administration.

For detailed information on administration, see

Administration Guide

GeneralTuning Concepts

Some key concepts that aect 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 ramications of the concept, the third column describes the measurements, and the right most column describes the value sources.

Chapter 1 • Overview of Enterprise Server Performance Tuning 23

Sun GlassFish Enterprise Server 2.1

General Tuning Concepts

TABLE 1–2 Factors That Aect Performance

Concept In practice Measurement Value sources

User Load Concurrent

sessions at peak load

Application Scalability

Vertical scalability

Horizontal scalability

Safety Margins High

Transaction rate measured on one CPU

Increase in performance from additional CPUs

Increase in performance from additional servers

availability requirements

Transactions Per Minute (TPM)

Web Interactions Per Second (WIPS)

TPM or WIPS Measured from workload benchmark. Perform at each tier.

Percentage gain per additional CPU

Percentage gain per additional server process and/or hardware node.

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

(Max. number of concurrent users) * (expected response time) / (time between clicks)

Example:

(100 users*2sec)/10sec=20

Based on curve tting 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.

Use a well-tuned single application server instance, as in previous step. Measure how much each additional server instance and hardware node improves performance.

Dierent 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.

Capacity Planning

The previous discussion guides you towards dening 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 conguration.

■

The hardware resources required to sustain specied application load and performance.

You can estimate these values through careful performance benchmarking, using an application with realistic data sets and workloads.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200924

General Tuning Concepts

▼

To Determine Capacity

Determine performance on a single CPU.

First determine the largest load that a single processor can sustain. You can obtain this gure 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 nal deployment.

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 specic 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, Application Server, backend database resources, and operating system so that they do not skew the results.

Determine horizontal scalability.

If suciently 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 benets 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

Chapter 1 • Overview of Enterprise Server Performance Tuning 25

Further Information

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-specic. 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 and Java

Performance BluePrints

■

For details on optimizing EJB components, see Seven Rules for Optimizing Entity Beans

■

For details on proling, see “Proling Tools” in Sun GlassFish Enterprise Server 2.1

Developer’s Guide

■

For more details on the domain.xml le see Sun GlassFish Enterprise Server 2.1

Administration Reference.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200926

CHAPTER 2

TuningYour 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.

This chapter discusses the following topics:

■

“Java Programming Guidelines” on page 27

■

“Java Server Page and Servlet Tuning” on page 29

■

“EJB Performance Tuning” on page 32

Java Programming Guidelines

This section covers issues related to Java coding and performance. The guidelines outlined are not specic to Enterprise Server, but are general rules that are useful in many situations. For a complete discussion of Java coding best practices, see the

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 benecial in some cases.

Use StringBuer to Concatenate Strings

To improve performance, instead of using string concatenation, use StringBuffer.append().

String objects are immutable—they never change after creation. For example, consider the following code:

Java Blueprints.

Java Programming Guidelines

String str = "testing"; str = str + "abc";

The compiler translates this code as:

String str = "testing"; StringBuffer tmp = new StringBuffer(str); tmp.append("abc"); str = tmp.toString();

Therefore, copying is inherently expensive and overusing it can reduce performance signicantly.

Assign null toVariablesThat 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 proling 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 nal 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 nal

The dynamic compiler can perform some constant folding optimizations easily, when you declare constants as static final variables.

AvoidFinalizers

Adding nalizers to code makes the garbage collector more expensive and unpredictable. The virtual machine does not guarantee the time at which nalizers are run. Finalizers may not always be executed, before the program exits. Releasing critical resources in finalize() methods may lead to unpredictable application behavior.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200928

Java Server Page and Servlet Tuning

Declare Method Arguments nal

Declare method arguments final if they are not modied in the method. In general, declare all variables final if they are not modied 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 asjava.util.HashTable.

Use DataHandlers for SOAP Attachments

Using a javax.activation.DataHandler for a SOAP attachment will improve performance.

JAX-RPC species:

■

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 Enterprise 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 conguration settings.

Chapter 2 • TuningYour Application 29

Java Server Page and Servlet Tuning

Suggested Coding Practices

This section provides some tips on coding practices that improve servlet and JSP application performance.

General Guidelines

Follow these general guidelines to increase performance of the presentation tier:

■

Minimize Java synchronization in servlets.

■

Don’t use the single thread model for servlets.

■

Use the servlet’sinit() method to perform expensive one-time initialization.

■

Avoidusing System.out.println() calls.

AvoidShared Modied 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. So, avoid using shared modied class variables, since 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 seven KB.

■

Use the directive <%page session="false"%> in JSP les to prevent the Enterprise Server from automatically creating sessions when they are not necessary.

■

Avoidlarge object graphs in an HttpSession . They force serialization and add computational overhead. Generally, do not store large objects as HttpSession variables.

■

Don’t cache transaction data in 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. The Enterprise Server provides “read-only” bean-managed persistence entity beans for cached access to read-only data.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200930

Java Server Page and Servlet Tuning

Conguration and Deployment Tips

Follow these conguration 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 les.

■

HTTP response times are dependent on how the keep-alive subsystem and the HTTP server is tuned in general. For more information, see

■

Cache servlet results when possible. For more information, see Chapter 8, “Developing Web

and SIP Applications,” in Sun GlassFish Enterprise Server 2.1 Developer’s Guide

■

If an application does not contain any EJB components, deploy the application as a WAR le, not an EAR le.

Optimize SSL

“HTTP Service Settings” on page 60.

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 le. For mor information, see the following table.

Solaris OS Version Library Setting of LD_PRELOAD Environment Variable

10 libumem–3LIB /usr/lib/libumem.so

9 libmtmalloc-3LIB /usr/lib/libmtmalloc.so

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 dene 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 le. 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.

To disable use of the server.policy le, use the Admin Console. Under Congurations > cong-name > JVM Settings (JVM Options) delete the option that contains the following text:

-Djava.security.manager

Chapter 2 • TuningYour Application 31

EJB PerformanceTuning

The Enterprise Server’shigh-performance EJB container has numerous parameters that aect performance. Individual EJB components also have parameters that aect 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—change them to optimize for other system congurations.

This section covers the following topics:

■

“Goals” on page 32

■

“Monitoring EJB Components” on page 32

■

“General Guidelines” on page 35

■

“Using Local and Remote Interfaces” on page 36

■

“Improving Performance of EJB Transactions” on page 38

■

“Using Special Techniques” on page 39

■

“Tuning Tips for Specic Types of EJB Components” on page 42

■

“JDBC and Database Access” on page 46

■

“Tuning Message-Driven Beans” on page 47

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 nite, 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 time-out, commit options, security, and transaction options, are mostly related to the functionality and conguration of the application. Generally, they do not compromise functionality for performance. In some cases, you might be forced to make a “trade-o” decision between functionality and performance. This section oers 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 gives the Bean Cache statistics for a stateful session bean.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200932

EJB PerformanceTuning

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

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

Chapter 2 • TuningYour Application 33

EJB PerformanceTuning

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.

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.

Monitoring Individual EJB Components

To gather method invocation statistics for all methods in a bean, use this command:

asadmin get -m monitorableObject.*

where monitorableObject is a fully-qualied identier 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

■

.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 identiers 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.*

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200934

EJB PerformanceTuning

To nd the possible objects (applications, modules, beans, and methods) and object attributes that can be monitored, use the Admin Console. For more information, see Chapter 18,

“Monitoring Components and Services,” in Sun GlassFish Enterprise Server 2.1 Administration

. Alternatively, use the asadmin list command. For more information, see list(1).

Guide

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 Specic Types of EJB Components” on

page 42

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 congured as read-only

4. Bean Managed Persistence (BMP) entity beans congured as read-only

5. CMP beans

6. BMP beans

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.

Chapter 2 • TuningYour Application 35

EJB PerformanceTuning

■

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 le 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 conguration), then you must generate the stubs for your application explicitly using RMIC. For more information, see

for more details.

Guide

Sun GlassFish Enterprise Server 2.1 Troubleshooting

Remove Unneeded Stateful Session Beans

Removing unneeded stateful session beans avoids passivating them, which requires disk operations.

Cache and Pool TuningTips

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-specic resources: Use the setEntityContext() method to cache bean specic resources and release them using the unSetEntityContext() method.

■

Load related data eciently for container-managed relationships (CMRs). For more information, see

■

Identify read-only beans: Congure read-only entity beans for read only operations. For more information, see

“Pre-fetching Container Managed Relationship (CMR) Beans” on page 44

“Read-Only Entity Beans” on page 43

Using Local and Remote Interfaces

This section describes some considerations when EJB components are used by local and remote clients.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200936

EJB PerformanceTuning

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 signicant 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 ecient, 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 eciency.

Using Pass-By-Reference Semantics

By default, the Enterprise 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 ecient to use pass-by-reference semantics when possible.

Using the remote and local interfaces appropriately means that clients can access EJB components eciently. 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 specication 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 Enterprise 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 specied at the application level, all beans in the application use pass-by-reference semantics when passing arguments to their remote interfaces. When specied at the bean level, all calls to the remote interface of the bean use pass-by-reference

Chapter 2 • TuningYour Application 37

EJB PerformanceTuning

semantics. See “Value Added Features” in Sun GlassFish Enterprise Server 2.1 Developer’s Guide for more details about the pass-by-reference ag.

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 modied by another source during the invocation.

Improving Performance of EJB Transactions

This section provides some tips to improve performance when using transactions.

Use Container-Managed Transactions

Container-managed transactions are preferred for consistency, and provide better performance.

Don’tEncompass 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 le. Transactions should span the minimum time possible since they lock database rows.

UseTX_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.

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

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200938

EJB PerformanceTuning

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.

Congure JDBC Resources as One-Phase Commit Resources

To improve performance of transactions involving multiple resources, the Application Server uses last agent optimization (LAO), which allows the conguration 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, congure a JDBC resource as a 1PC resource. Nothing special needs to be done to congure 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 congured as 1PC, and all others should be congured as XA.

Use the Least ExpensiveTransaction Attribute

Set the following transaction attributes in the EJB deployment descriptor le (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” on page 39

■

“Request Partitioning” on page 41

VersionConsistency

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).

Chapter 2 • TuningYour Application 39

EJB PerformanceTuning

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 eectively 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 rst 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 modied, 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 modied.

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 modied, because it allows two transactions to use the same EJB component at the same time. Because neither transaction modies 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>

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... </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 specied table is modied. The Application Server requires such a trigger to use version consistency. Having such a trigger also ensures that external applications that modify the EJB data will not conict 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 exibility 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 diering levels of priority assigned to dierent 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

Congure additional threadpools for EJB execution using the Admin Console.

Add the additional threadpool IDs to the Application Server’sORB.

You can do this by editing the domain.xml le or through the Admin Console.

Chapter 2 • TuningYour Application 41

EJB PerformanceTuning

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">

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>

<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>

Restart the Application Server.

Tuning Tips for SpecicTypes of EJB Components

This section provides tips for tuning various specic types of EJB components:

■

“Entity Beans” on page 42

■

“Stateful Session Beans” on page 42

■

“Stateless Session Beans” on page 43

■

“Read-Only Entity Beans” on page 43

■

“Pre-fetching Container Managed Relationship (CMR) Beans” on page 44

Entity Beans

Depending on the usage of a particular entity bean, one should tune max-cache-size so that beans that are used less (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 in numbers.

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

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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 time-out, 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 les 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 signicantly. 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. Application 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 signicantly 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 trac 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:

Chapter 2 • TuningYour Application 43

EJB PerformanceTuning

■

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 reected immediately in an application.

The ejbLoad() method of a read-only bean is handled dierently 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 rst 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 rst access to a bean loads the bean’s state. The rst access after 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.

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For example, you have this relationship dened in the ejb-jar.xml le:

<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>

<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 le 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>

</fetched-with>

</cmr-field-mapping>

</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.

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EJB PerformanceTuning

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 eort to pre-fetch the OrderLines that are not actually needed.

Avoidpre-fetching for specic nder methods; this can often avoid that penalty. For example, consider an order bean has two nder methods: a findByPrimaryKey method that uses the orderlines, and a findByCustomerId method that returns only order information and hence doesn’t use the orderlines. If you’ve enabled CMR pre-fetching for the orderlines, both nder 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

Here are some tips to improve the performance of database access.

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.

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 dierent isolation level.

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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.

Set the database transaction isolation level with the Admin Console on the Resources > JDBC > Connection Pools > PoolName page. For more information on tuning JDBC connection pools,

“JDBC Connection Pool Settings” on page 77 .

see

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.

Caution – Previous to version 8.1, it was possible to reuse a connection with a servlet or EJB

component. That is, the servlet could call getConnection() in its init() method and then continually call getSession() for each servlet invocation. If you use JMS within a global transaction, that no longer works: applications can only call getSession() once for each connection. After than, the connection must be closed (which doesn’t actually close the connection; it merely returns it to the pool). This is a general feature of portable Java EE 1.4 applications; the Sun Java System Application Server enforces that restriction where previous (Java EE 1.3-based) application servers did not.

Tunethe Message-Driven Bean’s Pool Size

The container for message-driven beans (MDB) is dierent 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’spool 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.

You can congure MDB pool settings in the Admin Console at Congurations > cong-name > EJB Container (MDB Settings). You can also set it with asadmin as follows:

asadmin set server.mdb-container.max-pool-size = value

Chapter 2 • TuningYour Application 47

EJB PerformanceTuning

Cache Bean-Specic Resources

Use the setMessageDrivenContext() or ejbCreate() method to cache bean specic 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.

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 specically close the session, or it will stay open, which ties up resources.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200948

CHAPTER 3

Tuning the Enterprise Server

This chapter describes some ways to tune the Enterprise Server for optimum performance, including the following topics:

■

“Deployment Settings” on page 49

■

“Logger Settings” on page 50

■

“Web Container Settings” on page 51

■

“EJB Container Settings” on page 53

■

“Java Message Service Settings” on page 58

■

“Transaction Service Settings” on page 58

■

“HTTP Service Settings” on page 60

■

“ORB Settings” on page 70

■

“Thread Pool Settings” on page 76

■

Resources:

■

“JDBC Connection Pool Settings” on page 77

■

“Connector Connection Pool Settings” on page 80

Deployment Settings

Deployment settings can have signicant impact on performance. Follow these guidelines when conguring deployment settings for best performance:

■

“Disable Auto-deployment” on page 50

■

“Use Pre-compiled JavaServer Pages” on page 50

■

“Disable Dynamic Application Reloading” on page 50

Logger Settings

Disable Auto-deployment

Enabling auto-deployment will adversely aect 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 signicant performance impact.

Disable auto-deployment with the Admin Console under Stand-Alone Instances > server (Admin Server) on the Advanced/Applications Conguration tab.

Use Pre-compiled JavaServer Pages

Compiling JSP les is resource intensive and time consuming. Pre-compiling JSP les before deploying applications on the server will improve application performance. When you do so, only the resulting servlet class les will be deployed.

You can specify to precompile JSP les when you deploy an application through the Admin Console or DeployTool. You can also specify to pre-compile JSP les for a deployed application with the Admin Console under Stand-Alone Instances > server (Admin Server) on the Advanced/ApplicationsConguration tab.

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.

Disable dynamic class reloading for an application that is already deployed with the Admin Console under Stand-Alone Instances > server (Admin Server) on the Advanced/Applications Conguration tab.

Logger Settings

The Application Server produces writes log messages and exception stack trace output to the log le in the logs directory of the instance, appserver-root/domains/domain-name/logs. Naturally, the volume of log activity can impact server performance; particularly in benchmarking situations.

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General Settings

In general, writing to the system log slows down performance slightly; and increased disk access (increasing the log level, decreasing the le rotation limit or time limit) also slows down the application.

Also, make sure that any custom log handler doesn’t log to a slow device like a network le system since this can adversely aect performance.

Log Levels

Set the log level for the server and its subsystems in the Admin Console Logger Settings page, Log Levels tab. The page enables you to specify the default log level for the server (labeled Root), the default log level for javax.enterprise.system subsystems (labeled Server) such as the EJB Container, MDB Container, Web Container, Classloader, JNDI naming system, and Security, and for each individual subsystem.

Log levels vary from FINEST, which provides maximum log information, through SEVERE, which logs only events that interfere with normal program execution. The default log level is INFO. The individual subsystem log level overrides the Server setting, which in turn overrides the Root setting.

For example, the MDB container can produce log messages at a dierent level than server default. To get more debug messages, set the log level to FINE, FINER, or FINEST. For best performance under normal conditions, set the log level to WARNING. Under benchmarking conditions, it is often appropriate to set the log level to SEVERE.

WebContainer Settings

Set Web container properties with the Admin Console at Congurations > cong-name > Web Container.

■

“Session Properties: Session Timeout” on page 51

■

“Manager Properties: Reap Interval” on page 52

■

“Disable Dynamic JSP Reloading” on page 52

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.

Chapter 3 • Tuningthe Enterprise Server 51

Web Container Settings

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 an online auction scenario as follows:

■

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’s20 second rest, the Application 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 le in the config directory for each instance. Change the servlet denition for a JSP le to look like this:

<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>

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200952

EJB Container Settings

The EJB Container has many settings that aect performance. As with other areas, use monitor the EJB Container to track its execution and performance.

Monitoring the EJB Container

Monitoring the EJB container is disabled by default. Enable monitoring with the Admin Console under Congurations > cong-name > Monitoring. 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 signicant performance benets to the EJB container. Set EJB cache and pool settings in the Admin Console Congurations > cong-name > EJB Container (EJB Settings).

The pool settings are valid for stateless session and entity beans while the cache settings are valid for stateful session and entity beans.

EJB Container Settings

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.

TABLE 3–1 Bean Type Poolingor Caching

Bean Type Pooled Cached

Stateless Session Yes No

Stateful Session No Yes

Entity Yes Yes

The dierence 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 congured limits.

Chapter 3 • Tuningthe Enterprise Server 53

EJB Container Settings

Note – If you develop and deploy your EJB components using Sun 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.

Tuningthe 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 trac 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 lled 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 inecient 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.

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■

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 specied 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.

Tuningthe 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 aects 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 trac your server handles, tune the EJB cache size and time-out 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:

Chapter 3 • Tuningthe Enterprise Server 55

Max Cache Size

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

Cache Idle Timeout

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 (rst in, rst out)

■

LRU (least recently used)

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 eld 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.

TABLE 3–2 EJB Cache and Pool Settings

Cache Settings Pool Settings

cacheidletimeoutinseconds

Typeof Bean

Stateful

cacheresizequantity

max- cachesize

XXXXX

Session

Stateless Session

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200956

removaltimeout- inseconds

victimselectionpolicy

refreshperiodinseconds

steadypool-size

poolresizequantity

maxpoolsize

pool-idletimeout-inseconds

XXXX

Refresh period

TABLE 3–2 EJB Cache and Pool Settings (Continued)

Cache Settings Pool Settings

cache-

Typeof Bean

cacheresizequantity

max- cachesize

idletimeoutinseconds

removaltimeout- inseconds

victimselectionpolicy

refreshperiodinseconds

steadypool-size

poolresizequantity

maxpoolsize

pool-idletimeout-inseconds

Entity XXXXX XXXX

Entity Readonly

Message Driven Bean

XXXXXXXXXX

XXX

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 signicant impact on performance.

There are two 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.

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, rst take a look at the cache-hits value using the monitoring command for the bean. If the cache hits are much higher

Chapter 3 • Tuningthe Enterprise Server 57

Java Message Service Settings

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 dierence 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 aects 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

GlassFish Enterprise Server 2.1 Administration Guide

Chapter 4, “Conguring Java Message Service Resources,” in Sun

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.

Monitoring the Transaction Service

Transaction Manager monitoring is disabled by default. Enable monitoring of the transaction service with the Admin Console at Congurations > cong-name > Monitoring.

You can also enable monitoring with these commands:

set serverInstance.transaction-service.monitoringEnabled=true reconfig serverInstance

Viewing Monitoring Information

When you have enabled monitoring of the transaction service, view results

■

With Admin Console at Standalone Instances > server-name (Monitor | Monitor). Select transaction-service from the View dropdown.

■

With this command:

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200958

asadmin get -m serverInstance.transaction-service.*

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 inight (active) transactions.

■

isFrozen Whether transaction system is frozen (true or false)

■

inflight-tx List of inight (active) transactions.

Here is a sample of the output using asadmin:

********** Stats for JTS ************

total-tx-completed = 244283 total-tx-rolled-back = 2640 total-tx-inflight = 702 isFrozen = False inflight-tx = Transaction Id , Status, ElapsedTime(msec) 000000000003C95A_00, Active, 999

Tuning the Transaction Service

Transaction Service Settings

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 conguration.

Disable Distributed Transaction Logging

To disable distributed transaction logging with the Admin Console, go to Congurations > cong-name > Transaction Service. Click on Add Property, and specify:

■

Name: disable-distributed-transaction-logging

■

Value: true

You can also set this property with asadmin, for example:

asadmin set server1.transaction-service.disable-distributed-transaction-logging=true

Setting this attribute to true disables transaction logging, which 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.

Chapter 3 • Tuningthe Enterprise Server 59

HTTP Service Settings

Recover On Restart (AutomaticRecovery)

To set the Recover on Restart attribute with the Admin Console, go to Congurations > cong-name > Transaction Service. Click the Recover check box to set it to true (checked, the default) or false (un-checked).

You can also set automatic recovery with asadmin, for example:

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.

■

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 benet 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 le. Keypointing prevents a process log from growing indenitely.

Frequent keypointing is detrimental to performance. The default value of the Keypoint Interval is 2048, which is sucient in most cases.

HTTP Service Settings

Monitoring and tuning the HTTP server instances that handle client requests are important parts of ensuring peak Enterprise Server performance.

■

“Monitoring the HTTP Service” on page 60

■

“Tuning the HTTP Service” on page 64

■

“Tuning HTTP Listener Settings” on page 69

Monitoring the HTTP Service

Enable monitoring statistics for the HTTP service using either Admin Console or asadmin.In the Admin Console, the monitoring level (LOW or HIGH) has no eect on monitoring the HTTP Service.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200960

HTTP Service Settings

With asadmin, use the following command to list the monitoring parameters available:

list --user admin --port 4848

-m server-instance-name.http-service.*

where server-instance-name is the name of the server instance.

Use the following command to get the values:

get --user admin --port 4848 -m server.http-service.parameter-name.*

where parameter-name is the name of the parameter to monitor.

Statistics collection is enabled by default. Disable it by adding the following property to

domain.xml and restart the server:

Disabling statistics collection will increase performance.

You can also view monitoring statistics with the Admin Console. The information is divided into the following categories:

■

“DNS Cache Information (dns)” on page 61

■

“File Cache Information (le-cache)” on page 63

■

“Keep Alive (keep-alive)” on page 63

DNS Cache Information (dns)

The DNS cache caches IP addresses and DNS names. Your server’s 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

If the DNS cache is disabled, the rest of this section is not displayed.

By default, the DNS cache is o. Enable DNS caching with the Admin Console by setting the DNS value to “Perform DNS lookups on clients accessing the server”.

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 Size of DNS Cache eld of the Performance Tuning page.

Chapter 3 • Tuningthe Enterprise Server 61

HTTP Service Settings

HitRatio

The hit ratio is the number of cache hits divided by the number of cache lookups.

This setting is not tunable.

Note – If you turn o DNS lookups on your server, host name restrictions will not work and IP

addresses will appear instead of host names in log les.

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 specied 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.

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.

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HTTP Service Settings

File Cache Information (le-cache)

The le cache caches static content so that the server handles requests for static content quickly. The le-cache section provides statistics on how your le cache is being used.

For information on tuning the le cache, see

■

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: The maximum age displays the maximum age of a valid cache

“HTTP File Cache” on page 67.

entry.

■

Max Number of Cache Entries

■

Max Number of Open Entries

■

Is File Cached Enabled?: If the cache is disabled, the other statistics are not displayed. The cache is enabled by default.

■

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 Admin Console provides the following performance-related keep-alive statistics:

■

Connections Terminated Due to ClientConnection 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

■

The Time in Seconds Before Idle Connections are Closed

■

Connections Closed Due to Max Keep-alive Being Exceeded

Chapter 3 • Tuningthe Enterprise Server 63

HTTP Service Settings

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.

■

AverageQueuing 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.

Tuning the HTTP Service

The settings for the HTTP service are divided into the following categories in the Admin Console:

■

“Access Log” on page 64

■

“Request Processing” on page 64

■

“Keep Alive” on page 66

■

“HTTP Protocol” on page 67

■

“HTTP File Cache” on page 67

Access Log

When performing benchmarking, ensure that access logging is disabled.

If you need to disable access logging, in HTTP Service click Add Property, and add the following property:

■

name: accessLoggingEnabled

■

value: false

You can set the following access log properties:

■

Rotation (enabled/disabled). Enable rotation to ensure that the logs don’t run out of disk space.

■

Rotation Policy:ime-based or size-based. Size-based is the default.

■

Rotation Interval.

Request Processing

On the Request Processing tab of the HTTP Service page, tune the following HTTP request processing settings:

■

Thread Count

■

Initial Thread Count

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200964

HTTP Service Settings

■

Request Timeout

■

Buer Length

Thread Count

The Thread Count parameter species 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 specied by the Request 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 Thread Count 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.

Initial Thread Count

The Initial Thread Count property species the minimum number of threads the server initiates upon start-up. The default value is 2. Initial Thread Count represents a hard limit for the maximum number of active threads that can run simultaneously, which can become a bottleneck for performance.

Request Timeout

The Request Timeout property species the number of seconds the server waits between accepting a connection to a client and receiving information from it. The default setting is 30 seconds. Under most circumstances, changing this setting is unnecessary. By setting it to less than the default 30 seconds, it is possible to free up threads sooner. However, disconnecting users with slower connections also helps.

Chapter 3 • Tuningthe Enterprise Server 65

HTTP Service Settings

Buer Length

The size (in bytes) of the buer 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 suce. If the request size is large, increase this parameter.

Keep Alive

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 indenitely, the server could become overloaded with connections. On Unix/Linux systems, this could easily lead to a le table overow.

The Application Server’s Keep Alive system 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.

The following HTTP keep alive settings aect performance:

■

Thread Count

■

Max Connections

■

Time Out

■

Keep Alive Query Mean Time

■

Keep Alive Query Max Sleep Time

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 specied 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.

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HTTP Service Settings

Time Out

Time Out 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.

HTTP Protocol

The only HTTP Protocol attribute that signicantly aects performance is DNS Lookup Enabled.

DNS Lookup Enabled

This setting species 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 DS 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—do so with caution.

HTTP File Cache

The Enterprise Server uses a le cache to serve static information faster. The le cache contains information about static les such as HTML, CSS, image, or text les. Enabling the HTTP le cache will improve performance of applications that contain static les.

Set the le cache attributes in the Admin Console under Congurations > cong-name > HTTP Service (HTTP File Cache).

Chapter 3 • Tuningthe Enterprise Server 67

HTTP Service Settings

Max Files Count

Max Files Count determines how many les are in the cache. If the value is too big, the server caches little-needed les, which wastes memory. If the value is too small, the benet of caching is lost. Try dierent values of this attribute to nd the optimal solution for specic applications—generally, the eects will not be great.

Hash Init Size

Hash Init Size aects memory use and search time, but rarely will have a measurable eect on performance.

Max Age

This parameter controls how long cached information is used after a le has been cached. An entry older than the maximum age is replaced by a new entry for the same le.

If your web site’scontent changes infrequently, increase this value for improved performance. Set the maximum age by entering or changing the value in the Maximum Age eld of the File Cache Conguration 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 les are modied) 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 le after the le has been modied.

Small/Medium File Size and File Size Limit

The cache treats small, medium, and large les dierently. The contents of medium les are cached by mapping the le into virtual memory (Unix/Linux platforms). The contents of small les are cached by allocating heap space and reading the le into it. The contents of large les are not cached, although information about large les is cached.

The advantage of distinguishing between small les and medium les is to avoid wasting part of many pages of virtual memory when there are lots of small les. So the Small File Size Limit is typically a slightly lower value than the VM page size.

FileTransmission

When File Transmission is enabled, the server caches open le descriptors for les in the le cache, rather than the le contents. Also, the distinction normally made between small, medium, and large les no longer applies since only the open le descriptor is being cached.

By default, File Transmission is enabled on Windows, and disabled on UNIX. On UNIX, only enable File Transmission for platforms that have the requisite native OS support: HP-UX and AIX. Don’t enable it for other UNIX/Linux platforms.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200968

HTTP Service Settings

Tuning HTTP Listener Settings

Change HTTP listener settings in the Admin Console under Congurations > cong-name > HTTP Service > HTTP Listeners > listener-name.

Network Address

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.

AcceptorThreads

The Acceptor Threads setting species 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 Enterprise 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.

The policy for adding new threads is based on the connection queue state:

■

Each time a new connection is returned, the number of connections waiting in the queue (the backlog of connections) is compared to the number of session threads already created. If it is greater than the number of threads, more threads are scheduled to be added the next time a request completes.

■

The previous backlog is tracked, so that n threads are added (n is the HTTP Service’s Thread Increment parameter) until one of the following is true:

■

The number of threads increases over time.

■

The increase is greater than n.

■

The number of session threads minus the backlog is less than n.

To avoid creating too many threads when the backlog increases suddenly (such as the startup of benchmark loads), the server makes the decision whether more threads are needed only once every 16 or 32 connections, based on how many session threads already exist.

Chapter 3 • Tuningthe Enterprise Server 69

ORB Settings

The Enterprise Server includes a high performance and scalable CORBA Object Request Broker (ORB). The ORB is the foundation of the EJB Container on the server.

Overview

The ORB is primarily used by EJB components via:

■

When a server instance makes a connection to another server instance ORB, the rst 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.

RMI/IIOP path from an application client (or rich client) using the application client container.

RMI/IIOP path from another Enterprise Server instance ORB.

RMI/IIOP path from another vendor’s ORB.

In-process path from the Web Container or MDB (message driven beans) container.

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 Enterprise 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 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 this asadmin command:

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200970

set serverInstance.iiop-service.orb.system.monitoringEnabled=true reconfig serverInstance

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 this 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 this command to get ORB thread pool statistics:

ORB Settings

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 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 table summarizes the tunable ORB parameters.

TABLE 3–3 Tunable ORB Settings

Path ORB modules Server settings

RMI/ IIOP from application client to application server

Chapter 3 • Tuningthe Enterprise Server 71

communication infrastructure, thread pool

steady-thread-pool-size, max-thread-pool-size, idle-thread-timeout-in-seconds

ORB Settings

TABLE 3–3 Tunable ORB Settings (Continued)

RMI/ IIOP from ORB to Enterprise 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

In-process thread pool steady-thread-pool-size, max-thread-pool-size,

steady-thread-pool-size, max-thread-pool-size, idle-thread-timeout-in-seconds

idle-thread-timeout-in-seconds

TunableORB Parameters

Tune the following ORB parameters using the Admin Console:

■

Thread Pool ID: Name of the thread pool to use.

■

Max Message Fragment Size: Messages larger than this number of bytes will be fragmented. In CORBA GIOPv1.2, a Request, Reply, LocateRequest and LocateReply message can be broken into multiple fragments. The rst message is a regular Request or Reply message with more fragments bit in the ags eld set to true. If inter-ORB messages are for the most part larger than the default size (1024 bytes), increase the fragment size to decrease latencies on the network.

■

Total Connections: Maximum number of incoming connections at any time, on all listeners. Protects the server state by allowing nite number of connections. This value equals the maximum number of threads that will actively read from the connection.

■

IIOP Client Authentication Required (true/false)

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’sMax Pool Size to be ten times the size of the current task queue.

The Enterprise Server uses the ORB thread pool to:

■

Execute every ORB request.

■

Trim EJB pools and caches.

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.

Set ORB thread pool attributes under Congurations > cong-name > Thread Pools > thread-pool-ID, where thread-pool-ID is the thread pool ID selected for the ORB. Thread pools have the following attributes that aect performance.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200972

ORB Settings

■

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” on page 74.

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

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 conguration on the client ORB.

-Djava.naming.factory.initial=com.sun.appserv.naming.S1ASCtxFactory

Using multiple connections

Note – The property com.sun.appserv.iiop.orbconnections is not supported in Sun

GlassFish Enterprise Server, version 8.x.

When using the context factory, (com.sun.appserv.naming.S1ASCtxFactory), you can specify the number of connections to open to the server from the client ORB with the property com.sun.appserv.iiop.orbconnections.

The default value is one. Using more than one connection may improve throughput for network-intense applications. The conguration changes are specied on the client ORB(s) by adding the following jvm-options:

-Djava.naming.factory.initial=com.sun.appserv.naming.S1ASCtxFactory

-Dcom.sun.appserv.iiop.orbconnections=value

Chapter 3 • Tuningthe Enterprise Server 73

ORB Settings

Load Balancing

For information on how to congure RMI/IIOP for multiple application server instances in a cluster,

Server 2.1 High AvailabilityAdministration 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 benets. 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).

Chapter 9, “RMI-IIOP Load Balancing and Failover,” in Sun GlassFish Enterprise

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 aect performance and response times signicantly.

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.

Setting the size to a very small value can aect the ability of the server to process requests concurrently, thus aecting 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 aecting response times.

The worker thread pool is also used for the EJB container’shousekeeping 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 Enterprise Server. To make the server save IIOP messages to the server.log le, 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.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200974

ORB Settings

++++++++++++++++++++++++++++++

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

47494f50010200040000014800000005GIOP.......H....

Note – The ag -Dcom.sun.CORBA.ORBdebug=giop generates many debug messages in the logs.

This is used only when you suspect message fragmentation.

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 eciency. On the other hand, if only a few messages are fragmented, it might be more ecient to have a lower fragment size that requires smaller buers for writing messages.

Improving ORB Performance with Java Serialization

It is possible to improve ORB performance by using Java Serialization instead of standard Common Data Representation (CDR) for data for transport over the network. This capability is called Java Serialization over GIOP (General Inter-ORB Protocol), or JSG.

In some cases, JSG can provide better performance throughput than CDR. The performance dierences depend highly on the application. Applications with remote objects having small amounts data transmitted between client and server will most often perform better using JSG.

Chapter 3 • Tuningthe Enterprise Server 75

Thread Pool Settings

▼

To Enable Java Serialization

You must set this property on all servers that you want to use JSG.

In the tree component, expand the Congurations node.

Expand the desired node.

Select the JVM Settings node

In the JVM Settings page, choose the JVM Options tab.

Click Add JVM Option, and enter the following value:

-Dcom.sun.CORBA.encoding.ORBEnableJavaSerialization=true

Click Save

Restart the Application Server.

Using JSG for Application Clients

If an application uses standalone non-web clients (application clients), and you want to use JSG, you must also set a system property for the client applications. A common way to do this is to add the property to the Java command line used to start the client application, for example:

java -Dcom.sun.CORBA.encoding.ORBEnableJavaSerialization=true

-Dorg.omg.CORBA.ORBInitialHost=gollum

-Dorg.omg.CORBA.ORBInitialPort=35309

MyClientProgram

Thread Pool Settings

You can both monitor and tune thread pool settings through the Admin Console. To congure monitoring with the Admin Console, open the page Congurations > cong-name > Monitoring. To view monitoring information with the Admin Console, open the page Stand-Alone Instances > instance-name (Monitor).

Tuning Thread Pools (Unix /Linux only)

Congure thread pool settings through the Admin Console at Congurations > cong-name > Thread Pools.

Since threads on Unix/Linux are always operating system (OS)-scheduled, as opposed to user-scheduled, Unix/Linux users do not need to use native thread pools. Therefore, this option

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200976

Resources

is not oered in a Unix/Linux user interface. However, it is possible to edit the OS-scheduled thread pools and add new thread pools, if needed, using the Admin Console.

■

“JDBC Connection Pool Settings” on page 77

■

“Connector Connection Pool Settings” on page 80

JDBC Connection Pool Settings

For optimum performance of database-intensive applications, tune the JDBC Connection Pools managed by the Enterprise 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.

Monitoring JDBC Connection Pools

Statistics-gathering is enabled by default for JDBC Connection Pools. 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 the statistics, use these commands:

asadmin get --monitor=true serverInstance.resources.jdbc-connection-pool.*asadmin get

--monitor=true serverInstance.resources.jdbc-connection-pool. poolName.* *

TuningJDBC Connection Pools

Set JDBC Connection Pool attributes with the Admin Console under Resources > JDBC > Connection Pools > PoolName. The following attributes aect performance:

■

“Pool Size Settings” on page 78

Chapter 3 • Tuningthe Enterprise Server 77

Initial and Mimimum Pool Size

■

Pool Size Settings

The following settings control the size of the connection pool:

“Timeout Settings” on page 78 “Isolation Level Settings” on page 79 “Connection Validation Settings” on page 79

Initial and

Size of the pool when created, and its minimum allowable size.

Mimimum Pool Size

Maximum Pool

Upper limit of size of the pool.

Size

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 pros and cons to consider when sizing connection pools.

TABLE 3–4 Connection PoolSizing

Connection pool Pros Cons

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 fulll requests.

Requests will spend less (or no) time in the queue

Slower access on the connection table.

Timeout Settings

There are two timeout settings:

■

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 indenitely.

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.

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Pool Resize Quantity

■

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.

Keep this timeout shorter than the database server timeout (if such timeouts are congured on the database), to prevent accumulation of unusable connection in Enterprise 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

Two settings control the connection pool’s transaction isolation level on the database server:

■

Transaction Isolation Level: species the transaction isolation level of the pooled database connections. If this parameter is unspecied, 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 specied by the Transaction Isolation Level parameter. Applicable only when the Transaction Isolation Level is specied. The default value is true.

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.

Avoidspecifying Transaction Isolation Level. If that is not possible, consider setting Isolation Level Guaranteed to false and make sure applications do not programmatically alter the connections’ isolation level.

If you must specify 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 ValidationSettings

The following settings determine whether and how the pool performs connection validation.

Chapter 3 • Tuningthe Enterprise Server 79

Connection Validation Required

Validation Method Typeof connection validation to perform. Must be one of:

Table Name Table name to query when Validation Method is “table.”

Close All Connections On Any Failure

If true, the pool validates connections (checks to nd out if they are usable) before providing them to an application.

If possible, keep the default value, false. 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.

■

auto-commit: attempt to perform an auto-commit on the connection.

■

metadata: attempt to get metadata from the connection.

■

table (performing a query on a specied table). Must also set Table Name. You may have to use this method if the JDBC driver caches calls to setAutoCommit() and getMetaData().

Whether to close all connections in the pool if a single validation check fails. The default is false. 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,

Pools” on page 77

“Tuning JDBC Connection

Transaction Support

You may be able to improve performance by overriding the default transaction support specied 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

In the Admin Console, specify transaction support when you create a new connector connection pool, and when you edit a connector connection pool at Resources > Connectors > Connector Connection Pools.

Also set transaction support using asadmin. For example, the following asadmin command could be used to create a connector connection pool “TESTPOOL” with the transaction-support as “LOCAL”.

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“Congure JDBC Resources as One-Phase Commit Resources” on page 39

asadmin> create-connector-connection-pool --raname jdbcra

--connectiondefinition javax.sql.DataSource

-transactionsupport LocalTransaction TESTPOOL

Close All Connections On Any Failure

Chapter 3 • Tuningthe Enterprise Server 81

CHAPTER 4

Tuning the Java Runtime System

This chapter discusses the following topics:

■

“Java Virtual Machine Settings” on page 83

■

“Managing Memory and Garbage Collection” on page 84

■

“Further Information” on page 91

JavaVirtual Machine Settings

J2SE 5.0 provides two implementations of the HotSpot Java virtual machine (JVM):

■

The client VM is tuned for reducing start-up 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 Application Server uses the JVM setting appropriate to the purpose:

■

Developer Prole, targeted at application developers, uses the -client JVM ag to optimize startup performance and conserve memory resources.

■

Enterprise Prole, targeted at production deployments, uses the default JVM startup mode. By default, Application Server uses the client Hotspot VM. However, if a server VM is needed, it can be specied by creating a <jvm-option> named “-server.”

You can override the default by changing the JVM settings in the Admin Console under Congurations > cong-name > JVM Settings (JVM Options).

For more information on server-class machine detection in J2SE 5.0, see

Detection .

For more information on JVMs, see

JavaTM Virtual Machines.

Server-Class Machine

Managing Memory and Garbage Collection

The eciency of any application depends on how well memory and garbage collection are managed. The following sections provide information on optimizing memory and allocation functions:

■

“Goals” on page 32

■

“Tracing Garbage Collection” on page 86

■

“Other Garbage Collector Settings” on page 86

■

“Tuning the Java Heap” on page 87

■

“Rebasing DLLs on Windows” on page 89

■

“Further Information” on page 91

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 eciency 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 lls up less quickly. So, it is garbage collected less frequently; and each collection 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.

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Managing Memory and Garbage Collection

When the new generation lls up, it triggers a minor collection in which the surviving objects are moved to the old generation. When the old generation lls 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 signicantly aects execution proles.

Choosing the Garbage Collection Algorithm

Pauses during a full GC of more than four seconds can cause intermittent failures in persisting session data into HADB.

While GC is going on, the Application Server isn’t running. If the pause is long enough, the HADB times out the existing connections. Then, when the application server resumes its activities, the HADB generates errors when the application server attempts to use those connections to persist session data. It generates errors like, “Failed to store session data,” “Transaction Aborted,” or “Failed to connect to HADB server.”

To prevent that problem, use the CMS collector as the GC algorithm. This collector can cause a drop in throughput for heavily utilized systems, because it is running more or less constantly. But it prevents the long pauses that can occur when the garbage collector runs infrequently.

▼

To use the CMS collector

Make sure that the system is not using 100 percent of its CPU.

Congure HADB timeouts, as described in the AdministrationGuide.

Congure 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” on

page 91

For detailed information on tuning the garbage collector, see Tuning Garbage Collection with

the 5.0 Java Virtual Machine

Chapter 4 • Tuningthe Java Runtime System 85

Managing Memory and Garbage Collection

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.

A particular generation size makes a trade-o 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 ag:

[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 rst 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 nal gure is the amount of time that the GC took. This example shows three minor collections and one major collection. In the rst 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 le

Other Garbage Collector Settings

For applications that do not dynamically generate and load classes, the size of the permanent generation has no eect on GC performance. For applications that dynamically generate and load classes (for example, JSP applications), the size of the permanent generation does aect GC performance, since lling the permanent generation can trigger a Full GC. Tune the maximum permanent generation with the -XX:MaxPermSize option.

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Managing Memory and 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 ag -XX:+DisableExplicitGC.

The Enterprise 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 species explicit collection once per hour

instead of the default rate of once per minute.

To specify the attributes for the Java virtual machine, use the Admin Console and set the property under cong-name > JVM settings (JVM options).

Tuning the Java Heap

This section discusses topics related to tuning the Java Heap for performance.

■

“Guidelines for Java Heap Sizing” on page 87

■

“Heap Tuning Parameters” on page 88

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:

TABLE 4–1 Maximum Address Space Per Process

Operating System Maximum Address Space

Per Process

Redhat Linux 32 bit 2 GB

Redhat Linux 64 bit 3 GB

Windows 98/2000/NT/Me/XP 2 GB

Solaris x86 (32 bit) 4 GB

Solaris 32 bit 4 GB

Solaris 64 bit Terabytes

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 proling 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

Chapter 4 • Tuningthe Java Runtime System 87

Managing Memory and Garbage Collection

memory structures. The dierence between the 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 dierent garbage collector. In general, for long-running server applications, use the J2SE throughput collector on machines with multiple processors (-XX:+AggressiveHeap) and as large a heap as you can t in the free memory of your machine.

Heap TuningParameters

You can control the heap size with the following JVM parameters:

■

-Xmsvalue

■

-Xmxvalue

■

-XX:MinHeapFreeRatio=minimum

■

-XX:MaxHeapFreeRatio=maximum

■

-XX:NewRatio=ratio

■

-XX:NewSize=size

■

-XX:MaxNewSize=size

■

-XX:+AggressiveHeap

The -Xms and -Xmx parameters dene the minimum and maximum heap sizes, respectively. Since GC occurs when the generations ll 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 specic 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 xed heap size. When the heap grows or shrinks, the JVM must recalculate the old and new generation sizes to maintain a predened 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 Enterprise 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 suciently large enough to hold many long-lived objects.

To size the Java heap:

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Managing Memory and Garbage Collection

■

Decide the total amount of memory you can aord for the JVM. Accordingly, graph your own performance metric against young generation sizes to nd the best setting.

■

Make plenty of memory available to the young generation. The default is calculated from NewRatio and the -Xmx setting.

■

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

EXAMPLE 4–1 Heap Conguration on Solaris

Java HotSpot VM Options.

This is an exmple heap conguration used by Enterprise 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 overows 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 Application 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 Application Server DLLs.

Chapter 4 • Tuningthe Java Runtime System 89

Managing Memory and Garbage Collection

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 Application Server DLLs to prevent relocations at load time and increase the available process memory for the Java heap.

There are a few Application 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 Application Server.

▼

To rebase the Application Server’s DLLs

BeforeYouBegin

To perform rebasing, you need:

■

Windows 2000

■

Visual Studio and the Microsoft Framework SDK rebase utility

Make install_dir\ bin the default directory.

cd install_dir\bin

Example 4–2

Further Information

For more information on tuning the JVM, see:

■

Java HotSpot VM Options

■

Frequently Asked Questions About the Java HotSpot Virtual Machine

■

Performance Documentation for the Java HotSpot VM

■

Java performance web page

■

Monitoring and Management for the Java Platform (J2SE 5.0)

■

The jvmstat monitoring utility

Further Information

Chapter 4 • Tuningthe Java Runtime System 91

CHAPTER 5

Tuning the Operating System and Platform

This chapter discusses tuning the operating system (OS) for optimum performance. It discusses the following topics:

■

“Server Scaling” on page 93

■

“Solaris 10 Platform-Specic Tuning Information” on page 95

■

“Tuning for the Solaris OS” on page 95

■

“Linux Conguration” on page 97

■

“Tuning for Solaris on x86” on page 98

■

“Tuning for Linux platforms” on page 100

■

“Tuning UltraSPARCT1–Based Systems” on page 103

Server Scaling

This section provides recommendations for optimal performance scaling server for the following server subsystems:

■

“Processors” on page 93

■

“Memory” on page 94

■

“Disk Space” on page 94

■

“Networking” on page 94

Processors

The Enterprise Server automatically takes advantage of multiple CPUs. In general, the eectiveness 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

Server Scaling

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 Sun Java System Application Server Release Notes for specic memory recommendations for each supported operating system.

Disk Space

It is best to have enough disk space for the OS, document tree, and log les. In most cases 2GB total is sucient.

Put the OS, swap/paging le, Enterprise Server logs, and document tree each on separate hard drives. This way, if the log les ll up the log drive, the OS does not suer. Also, its easy to tell if the OS paging le is causing drive activity, for example.

OS vendors generally provide specic recommendations for how much swap or paging space to allocate. Based on Sun testing, Enterprise 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

■

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 les 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:

r / t

peak

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 conguring multiple 100BaseT interfaces, or look at Gigabit Ethernet technology.

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200994

) the server needs to handle.

peak

Solaris 10 Platform-SpecicTuning Information

SolarisTMDynamic 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://www.opensolaris.org/os/community/dtrace/dtracetoolkit/)

Tuning for the Solaris OS

■

“Tuning Parameters” on page 95

■

“File Descriptor Setting” on page 97

Tuning Parameters

Tuning Solaris TCP/IP settings benets programs that open and close many sockets. Since the Enterprise Server operates with a small xed set of connections, the performance gain might not be signicant.

Tuningfor the Solaris OS

The following table shows Solaris tuning parameters that aect performance and scalability benchmarking. These values are examples of how to tune your system for best performance.

TABLE 5–1 Tuning Parameters for Solaris

Parameter Scope Default TunedValue Comments

rlim_fd_max /etc/system 65536 65536 Limit of process open le

descriptors. Set to account for expected load (for associated sockets, les, 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 innite so the performance runs won’t be hit by lack of buer space. Set on clients too. Note that setting sq_max_size to 0 might not be optimal for production systems with high network trac.

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.

Chapter 5 • Tuningthe Operating System and Platform 95

Tuningfor the Solaris OS

TABLE 5–1 Tuning Parametersfor Solaris (Continued)

Parameter Scope Default TunedValue Comments

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 trac web sites, lower this

value.

tcp_rexmit_interval_initial ndd /dev/tcp 3000 3000 Ifretransmission 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 buer.

tcp_recv_hiwat ndd /dev/tcp 8129 32768 Size of receive buer.

tcp_conn_hash_size ndd /dev/tcp 512 8192 Sizeof connection hash table. See

“Sizing the Connection Hash Table” on page 96

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 ecient, 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 eective at boot time.

Use the following command to get the current number of TCP connections.

netstat -nP tcp|wc -l

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Linux Conguration

File Descriptor Setting

On the Solaris OS, setting the maximum number of open les property using ulimit has the biggest impact on eorts 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.

Linux Conguration

The following parameters must be added to the /etc/rc.d/rc.local le that gets executed during system start-up.

<-- 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

Chapter 5 • Tuningthe Operating System and Platform 97

Tuningfor Solaris on x86

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 "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 le 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

For further information on tuning Solaris system see the Solaris Tunable Parameters Reference Manual.

Tuning for Solaris on x86

The following are some options to consider when tuning Solaris on x86 for Application Server and HADB:

■

“File Descriptors” on page 100

■

“IP Stack Settings” on page 99

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 200998

Tuningfor Solaris on x86

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 le:

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 aect the le descriptors.

IP Stack Settings

Add (or edit) the following lines in the /etc/system le:

set ip:tcp_squeue_wput=1 set ip:tcp_squeue_close=1 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 le 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

Chapter 5 • Tuningthe Operating System and Platform 99

Tuningfor Linux platforms

Tuning for Linux platforms

To tune for maximum performance on Linux, you need to make adjustments to the following:

■

“File Descriptors” on page 100

■

“Virtual Memory” on page 101

■

“Network Interface” on page 102

■

“Disk I/O Settings” on page 102

■

“TCP/IP Settings” on page 102

File Descriptors

You may need to increase the number of le descriptors from the default. Having a higher number of le 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 le 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 les permitted:

fs.file-max = 65535

Note: The parameter is not proc.sys.fs.file-max, as one might expect.

To list the available parameters that can be modied using sysctl:

sysctl -a

To load new values from the sysctl.conf le:

sysctl -p /etc/sysctl.conf

To check and modify limits per shell, use the following command:

limit

The output will look something like this:

Sun GlassFish Enterprise Server 2.1 PerformanceTuning Guide • January 2009100

Sun Microsystems 820434310 User Manual

Specifications and Main Features

Frequently Asked Questions

User Manual

Preface

Sun GlassFish Enterprise Server Documentation Set

Default Paths and File Names

Typographic Conventions

Symbol Conventions

Documentation, Support, andTraining

Third-PartyWeb Site References

Sun WelcomesYour Comments

Overview of Enterprise Server Performance Tuning

Process Overview

PerformanceTuningSequence

Understanding Operational Requirements

Application Architecture

Security Requirements

User Authentication and Authorization

Encryption

Hardware Resources

General Tuning Concepts

Administration

Capacity Planning

To Determine Capacity

User Expectations

Further Information

TuningYour Application

Java Programming Guidelines

Avoid Serialization and Deserialization

Assign null toVariablesThat Are No Longer Needed

AvoidFinalizers

Java Server Page and Servlet Tuning

Synchronize Only When Necessary

Use DataHandlers for SOAP Attachments

Suggested Coding Practices

General Guidelines

HTTP Session Handling

Optimize SSL

Disable Security Manager

EJB PerformanceTuning

Goals

Monitoring EJB Components

Monitoring Individual EJB Components

General Guidelines

Use High Performance Beans

Use Caching

Use the Appropriate Stubs

Remove Unneeded Stateful Session Beans

Cache and Pool TuningTips

Using Local and Remote Interfaces

Prefer Local Interfaces

Using Pass-By-Reference Semantics

Improving Performance of EJB Transactions

Use Container-Managed Transactions

Don’tEncompass User Input Time

Identify Non-Transactional Methods

UseTX_REQUIRED for Long Transaction Chains

Use Lowest Cost Database Locking

Use XA-Capable Data Sources Only When Needed

Use the Least ExpensiveTransaction Attribute

Using Special Techniques

VersionConsistency

Request Partitioning

To enable request partitioning

Entity Beans

Stateful Session Beans

Checkpoint only when needed

Stateless Session Beans

Read-Only Entity Beans

Refresh period

Pre-fetching Container Managed Relationship (CMR) Beans

JDBC and Database Access

Use JDBC Directly

Encapsulate Business Logic in Entity EJB Components

Close Connections

Minimize the Database Transaction Isolation Level

Tuning Message-Driven Beans

Use getConnection()

Tunethe Message-Driven Bean’s Pool Size