String str = "testing";
str = str + "abc";
str = str + "def";
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Tuning Your Application DRAFT |
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This chapter provides information on tuning applications for maximum performance. A complete guide to writing high performance Java and Java EE applications is beyond the scope of this document.
The following topics are addressed here:
This section covers issues related to Java coding and performance. The
guidelines outlined are not specific to GlassFish Server, but are
general rules that are useful in many situations. For a complete
discussion of Java coding best practices, see the
Java
Blueprints
(http://www.oracle.com/technetwork/java/javaee/blueprints/index.html).
The following topics are addressed here:
Serialization and deserialization of objects is a CPU-intensive
procedure and is likely to slow down your application. Use the
transient keyword to reduce the amount of data serialized.
Additionally, customized readObject() and writeObject() methods may
be beneficial in some cases.
StringBuilder to Concatenate StringsTo improve performance, instead of using string concatenation, use
StringBuilder.append().
String objects are immutable - that is, they never change after creation. For example, consider the following code:
String str = "testing";
str = str + "abc";
str = str + "def";The compiler translates this code as:
String str = "testing";
StringBuilder tmp = new StringBuilder(str);
tmp.append("abc");
str = tmp.toString();
StringBulder tmp = new StringBuilder(str);
tmp.append("def");
str = tmp.toString();This copying is inherently expensive and overusing it can reduce performance significantly. You are far better off writing:
StringBuilder tmp = new StringBuilder("testing");
tmp.append("abc");
tmp.append("def");
String str = tmp.toString();Explicitly assigning a null value to variables that are no longer needed helps the garbage collector to identify the parts of memory that can be safely reclaimed. Although Java provides memory management, it does not prevent memory leaks or using excessive amounts of memory.
An application may induce memory leaks by not releasing object references. Doing so prevents the Java garbage collector from reclaiming those objects, and results in increasing amounts of memory being used. Explicitly nullifying references to variables after their use allows the garbage collector to reclaim memory.
One way to detect memory leaks is to employ profiling tools and take memory snapshots after each transaction. A leak-free application in steady state will show a steady active heap memory after garbage collections.
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.
The dynamic compiler can perform some constant folding optimizations
easily, when you declare constants as static final variables.
Adding finalizers to code makes the garbage collector more expensive and
unpredictable. The virtual machine does not guarantee the time at which
finalizers are run. Finalizers may not always be executed, before the
program exits. Releasing critical resources in finalize() methods may
lead to unpredictable application behavior.
Declare method arguments final if they are not modified in the method.
In general, declare all variables final if they are not modified after
being initialized or set to some value.
Do not synchronize code blocks or methods unless synchronization is required. Keep synchronized blocks or methods as short as possible to avoid scalability bottlenecks. Use the Java Collections Framework for unsynchronized data structures instead of more expensive alternatives such as`java.util.HashTable`.
Using a javax.activation.DataHandler for a SOAP attachment will
improve performance.
JAX-RPC specifies:
A mapping of certain MIME types to Java types.
Any MIME type is mappable to a javax.activation.DataHandler .
As a result, send an attachment (.gif or XML document) as a SOAP
attachment to an RPC style web service by utilizing the Java type
mappings. When passing in any of the mandated Java type mappings
(appropriate for the attachment’s MIME type) as an argument for the web
service, the JAX-RPC runtime handles these as SOAP attachments.
For example, to send out an image/gif attachment, use
java.awt.Image, or create a DataHandler wrapper over your image. The
advantages of using the wrapper are:
Reduced coding: You can reuse generic attachment code to handle the
attachments because the DataHandler determines the content type of the
contained data automatically. This feature is especially useful when
using a document style service. Since the content is known at runtime,
there is no need to make calls to
attachment.setContent(stringContent, "image/gif"), for example.
Improved Performance: Informal tests have shown that using
DataHandler wrappers doubles throughput for image/gif MIME types,
and multiplies throughput by approximately 1.5 for text/xml or
java.awt.Image for image/* types.
Many applications running on the GlassFish Server use servlets or JavaServer Pages (JSP) technology in the presentation tier. This section describes how to improve performance of such applications, both through coding practices and through deployment and configuration settings.
This section provides some tips on coding practices that improve servlet and JSP application performance.
The following topics are addressed here:
Follow these general guidelines to increase performance of the presentation tier:
Minimize Java synchronization in servlets.
Do not use the single thread model for servlets.
Use the servlet’s init() method to perform expensive one-time
initialization.
Avoid using System.out.println() calls.
In the servlet multithread model (the default), a single instance of a servlet is created for each application server instance. All requests for a servlet on that application instance share the same servlet instance. This can lead to thread contention if there are synchronization blocks in the servlet code. Therefore, avoid using shared modified class variables because they create the need for synchronization.
Follow these guidelines when using HTTP sessions:
Create sessions sparingly. Session creation is not free. If a session is not required, do not create one.
Use javax.servlet.http.HttpSession.invalidate() to release sessions
when they are no longer needed.
Keep session size small, to reduce response times. If possible, keep session size below 7 kilobytes.
Use the directive <%page session="false"%> in JSP files to prevent
the GlassFish Server from automatically creating sessions when they are
not necessary.
Avoid large object graphs in an HttpSession. They force
serialization and add computational overhead. Generally, do not store
large objects as HttpSession variables.
Do not cache transaction data in an HttpSession. Access to data in
an HttpSession is not transactional. Do not use it as a cache of
transactional data, which is better kept in the database and accessed
using entity beans. Transactions will rollback upon failures to their
original state. However, stale and inaccurate data may remain in
HttpSession objects. GlassFish Server provides "read-only"
bean-managed persistence entity beans for cached access to read-only
data.
Follow these configuration tips to improve performance. These tips are intended for production environments, not development environments.
To improve class loading time, avoid having excessive directories in
the server CLASSPATH. Put application-related classes into JAR files.
HTTP response times are dependent on how the keep-alive subsystem and the HTTP server is tuned in general. For more information, see HTTP Service Settings.
Cache servlet results when possible. For more information, see "Developing Web Applications" in GlassFish Server Open Source Edition Application Development Guide.
If an application does not contain any EJB components, deploy the application as a WAR file, not an EAR file.
Optimize SSL
Optimize SSL by using routines in the appropriate operating system
library for concurrent access to heap space. The library to use depends
on the version of the Solaris Operating System (SolarisOS) that you are
using. To ensure that you use the correct library, set the LD_PRELOAD
environment variable to specify the correct library file. For more
information, refer to the following table.
| Solaris OS Version | Library | Setting of LD_PRELOAD Environment
Variable |
|---|---|---|
10 |
|
|
9 |
|
|
To set the LD_PRELOAD environment variable, edit the entry for this
environment variable in the startserv script. The startserv script
is located is located in the bin/startserv directory of your domain.
The exact syntax to define an environment variable depends on the shell that you are using.
Disable Security Manager
The security manager is expensive because calls to required resources
must call the doPrivileged() method and must also check the resource
with the server.policy file. If you are sure that no malicious code
will be run on the server and you do not use authentication within your
application, then you can disable the security manager.
See "Enabling and Disabling the Security Manager" in GlassFish Server Open Source Edition Application Development Guide for instructions on enabling or disabling the security manager. If using the GlassFish Server Administration Console, navigate to the Configurations>configuration-name>Security node and check or uncheck the Security Manager option as desired. Refer to the Administration Console online help for more information.
The GlassFish Server’s high-performance EJB container has numerous parameters that affect performance. Individual EJB components also have parameters that affect performance. The value of individual EJB component’s parameter overrides the value of the same parameter for the EJB container. The default values are designed for a single-processor computer system. Modify these values as appropriate to optimize for other system configurations.
The following topics are addressed here:
The goals of EJB performance tuning are:
Increased speed: Cache as many beans in the EJB caches as possible to increase speed (equivalently, decrease response time). Caching eliminates CPU-intensive operations. However, since memory is finite, as the caches become larger, housekeeping for them (including garbage collection) takes longer.
Decreased memory consumption: Beans in the pools or caches consume memory from the Java virtual machine heap. Very large pools and caches degrade performance because they require longer and more frequent garbage collection cycles.
Improved functional properties: Functional properties such as user timeout, commit options, security, and transaction options, are mostly related to the functionality and configuration of the application. Generally, they do not compromise functionality for performance. In some cases, you might be forced to make a "trade-off" decision between functionality and performance. This section offers suggestions in such cases.
When the EJB container has monitoring enabled, you can examine statistics for individual beans based on the bean pool and cache settings.
For example, the monitoring command below returns the Bean Cache statistics for a stateful session bean.
asadmin get --user admin --host e4800-241-a --port 4848
-m specjcmp.application.SPECjAppServer.ejb-module.
supplier_jar.stateful-session-bean.BuyerSes.bean-cache.*The following is a sample of the monitoring output:
resize-quantity = -1
cache-misses = 0
idle-timeout-in-seconds = 0
num-passivations = 0
cache-hits = 59
num-passivation-errors = 0
total-beans-in-cache = 59
num-expired-sessions-removed = 0
max-beans-in-cache = 4096
num-passivation-success = 0The 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 = 255The 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 = 42Tuning the bean involves charting the behavior of the cache and pool for the bean in question over a period of time.
If too many passivations are happening and the JVM heap remains fairly
small, then the max-cache-size or the cache-idle-timeout-in-seconds
can be increased. If garbage collection is happening too frequently, and
the pool size is growing, but the cache hit rate is small, then the
pool-idle-timeout-in-seconds can be reduced to destroy the instances.
Note: Specifying a |
To gather method invocation statistics for all methods in a bean, use the following command:
asadmin get -m monitorableObject.*where monitorableObject is a fully-qualified identifier from the hierarchy of objects that can be monitored, shown below.
serverInstance.application.applicationName.ejb-module.moduleNamewhere 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.moduleNameThe possible identifiers are the same as for ejb-module.
For example, to get statistics for a method in an entity bean, use this command:
asadmin get -m serverInstance.application.appName.ejb-module.moduleName
.entity-bean.beanName.bean-method.methodName.*For more information about administering the monitoring service in general, see "Administering the Monitoring Service" in GlassFish Server Open Source Edition Administration Guide. For information about viewing comprehensive EJB monitoring statistics, see "EJB Statistics" in GlassFish Server Open Source Edition Administration Guide.
To configure EJB monitoring using the GlassFish Server Administration Console, navigate to the Configurations>configuration-name>Monitoring node. After configuring monitoring, you can view monitoring statistics by navigating to the server (Admin Server) node and then selecting the Monitor tab. Refer to the Administration Console online help for instructions on each of these procedures.
Alternatively, to list EJB statistics, use the asadmin list
subcommand. For more information, see list(1).
For statistics on stateful session bean passivations, use this command:
asadmin get -m serverInstance.application.appName.ejb-module.moduleName
.stateful-session-bean.beanName.bean-cache.*From the attribute values that are returned, use this command:
num-passivationsnum-passivation-errorsnum-passivation-success
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 as much as possible to improve the overall performance of your application. For more information, see Tuning Tips for Specific Types of EJB Components.
The types of EJB components are listed below, from the highest performance to the lowest:
Stateless Session Beans and Message Driven Beans
Stateful Session Beans
Container Managed Persistence (CMP) entity beans configured as read-only
Bean Managed Persistence (BMP) entity beans configured as read-only
CMP beans
BMP beans
For more information about configuring high availability session persistence, see "Configuring High Availability Session Persistence and Failover" in GlassFish Server Open Source Edition High Availability Administration Guide. To configure EJB beans using the GlassFish Server Administration Console, navigate to the Configurations>configuration-name>EJB Container node and then refer to the Administration Console online help for detailed instructions.
Caching can greatly improve performance when used wisely. For example:
Cache EJB references: To avoid a JNDI lookup for every request, cache EJB references in servlets.
Cache home interfaces: Since repeated lookups to a home interface can
be expensive, cache references to EJBHomes in the init() methods of
servlets.
Cache EJB resources: Use setSessionContext() or ejbCreate() to
cache bean resources. This is again an example of using bean lifecycle
methods to perform application actions only once where possible.
Remember to release acquired resources in the ejbRemove() method.
The stub classes needed by EJB applications are generated dynamically at
runtime when an EJB client needs them. This means that it is not
necessary to generate the stubs or retrieve the client JAR file when
deploying an application with remote EJB components. When deploying an
application, it is no longer necessary to specify the --retrieve
option, which can speed up deployment.
If you have a legacy rich-client application that directly uses the CosNaming service (not a recommended configuration), then you must generate the stubs for your application explicitly using RMIC. For more information, see the GlassFish Server Open Source Edition Troubleshooting Guide for more details.
Removing unneeded stateful session beans avoids passivating them, which requires disk operations.
Follow these tips when using the EJB cache and pools to improve performance:
Explicitly call remove(): Allow stateful session EJB components to
be removed from the container cache by explicitly calling of the
remove() method in the client.
Tune the entity EJB component’s pool size: Entity Beans use both the EJB pool and cache settings. Tune the entity EJB component’s pool size to minimize the creation and destruction of beans. Populating the pool with a non-zero steady size before hand is useful for getting better response for initial requests.
Cache bean-specific resources: Use the setEntityContext() method to
cache bean specific resources and release them using the
unSetEntityContext() method.
Load related data efficiently for container-managed relationships (CMRs). For more information, see Pre-Fetching Container Managed Relationship (CMR) Beans.
Identify read-only beans: Configure read-only entity beans for read only operations. For more information, see Read-Only Entity Beans.
This section describes some considerations when EJB components are used by local and remote clients.
An EJB component can have remote and local interfaces. Clients not located in the same application server instance as the bean (remote clients) use the remote interface to access the bean. Calls to the remote interface require marshalling arguments, transportation of the marshalled data over the network, un-marshaling the arguments, and dispatch at the receiving end. Thus, using the remote interface entails significant overhead.
If an EJB component has a local interface, then local clients in the same application server instance can use it instead of the remote interface. Using the local interface is more efficient, since it does not require argument marshalling, transportation, and un-marshalling.
If a bean is to be used only by local clients then it makes sense to provide only the local interface. If, on the other hand, the bean is to be location-independent, then you should provide both the remote and local interfaces so that remote clients use the remote interface and local clients can use the local interface for efficiency.
By default, the GlassFish Server uses pass-by-value semantics for calling the remote interface of a bean, even if it is co-located. This can be expensive, since clients using pass-by-value semantics must copy arguments before passing them to the EJB component.
However, local clients can use pass-by-reference semantics and thus the local and remote interfaces can share the passed objects. But this means that the argument objects must be implemented properly, so that they are shareable. In general, it is more efficient to use pass-by-reference semantics when possible.
Using the remote and local interfaces appropriately means that clients can access EJB components efficiently. That is, local clients use the local interface with pass-by-reference semantics, while remote clients use the remote interface with pass-by-value semantics.
However, in some instances it might not be possible to use the local interface, for example when:
The application predates the EJB 2.0 specification and was written without any local interfaces.
There are bean-to-bean calls and the client beans are written without making any co-location assumptions about the called beans.
For these cases, the GlassFish Server provides a pass-by-reference option that clients can use to pass arguments by reference to the remote interface of a co-located EJB component.
You can specify the pass-by-reference option for an entire application or a single EJB component. When specified at the application level, all beans in the application use pass-by-reference semantics when passing arguments to their remote interfaces. When specified at the bean level, all calls to the remote interface of the bean use pass-by-reference semantics. See "Value Added Features" in GlassFish Server Open Source Edition Application Development Guide for more details about the pass-by-reference flag.
To specify that an EJB component will use pass by reference semantics,
use the following tag in the sun-ejb-jar.xml deployment descriptor:
<pass-by-reference>true</pass-by-reference>This avoids copying arguments when the EJB component’s methods are invoked and avoids copying results when methods return. However, problems will arise if the data is modified by another source during the invocation.
This section provides some tips to improve performance when using transactions.
The following topics are addressed here:
Container-managed transactions are preferred for consistency, and provide better performance.
To avoid resources being held unnecessarily for long periods, a transaction should not encompass user input or user think time.
Declare non-transactional methods of session EJB components with
NotSupported or Never transaction attributes. These attributes can
be found in the ejb-jar.xml deployment descriptor file. Transactions
should span the minimum time possible since they lock database rows.
TX_REQUIRED for Long Transaction ChainsFor very large transaction chains, use the transaction attribute
TX_REQUIRED. To ensure EJB methods in a call chain, use the same
transaction.
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.
When multiple database resources, connector resources or JMS resources are involved in one transaction, a distributed or global transaction needs to be performed. This requires XA capable resource managers and data sources. Use XA capable data sources, only when two or more data source are going to be involved in a transaction. If a database participates in some distributed transactions, but mostly in local or single database transactions, it is advisable to register two separate JDBC resources and use the appropriate resource in the application.
To improve performance of transactions involving multiple resources, the GlassFish Server uses last agent optimization (LAO), which allows the configuration of one of the resources in a distributed transaction as a one-phase commit (1PC) resource. Since the overhead of multiple-resource transactions is much higher for a JDBC resource than a message queue, LAO substantially improves performance of distributed transactions involving one JDBC resource and one or more message queues. To take advantage of LAO, configure a JDBC resource as a 1PC resource. Nothing special needs to be done to configure JMS resources.
In global transactions involving multiple JDBC resources, LAO will still improve performance, however, not as much as for one JDBC resource. In this situation, one of the JDBC resources should be configured as 1PC, and all others should be configured as XA.
Set the following transaction attributes in the EJB deployment
descriptor file (ejb-jar.xml). Options are listed from best
performance to worst. To improve performance, choose the least expensive
attribute that will provide the functionality your application needs:
NEVER
TX_NOTSUPPORTED
TX_MANDATORY
TX_SUPPORTS
TX_REQUIRED
TX_REQUIRESNEW
Special performance-enhancing techniques are discussed in the following sections:
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). |
Use version consistency to improve performance while protecting the integrity of data in the database. Since the application server can use multiple copies of an EJB component simultaneously, an EJB component’s state can potentially become corrupted through simultaneous access.
The standard way of preventing corruption is to lock the database row associated with a particular bean. This prevents the bean from being accessed by two simultaneous transactions and thus protects data. However, it also decreases performance, since it effectively serializes all EJB access.
Version consistency is another approach to protecting EJB data integrity. To use version consistency, you specify a column in the database to use as a version number. The EJB lifecycle then proceeds like this:
The first time the bean is used, the ejbLoad() method loads the bean
as normal, including loading the version number from the database.
The ejbStore() method checks the version number in the database
versus its value when the EJB component was loaded.
If the version number has been modified, it means that there has been
simultaneous access to the EJB component and ejbStore() throws a
ConcurrentModificationException.
Otherwise, ejbStore() stores the data and completes as normal.
The ejbStore() method performs this validation at the end of the
transaction regardless of whether any data in the bean was modified.
Subsequent uses of the bean behave similarly, except that the
ejbLoad() method loads its initial data (including the version number)
from an internal cache. This saves a trip to the database. When the
ejbStore() method is called, the version number is checked to ensure
that the correct data was used in the transaction.
Version consistency is advantageous when you have EJB components that are rarely modified, because it allows two transactions to use the same EJB component at the same time. Because neither transaction modifies the data, the version number is unchanged at the end of both transactions, and both succeed. But now the transactions can run in parallel. If two transactions occasionally modify the same EJB component, one will succeed and one will fail and can be retried using the new values—which can still be faster than serializing all access to the EJB component if the retries are infrequent enough (though now your application logic has to be prepared to perform the retry operation).
To use version consistency, the database schema for a particular table
must include a column where the version can be stored. You then specify
that table in the sun-cmp-mapping.xml deployment descriptor for a
particular bean:
<entity-mapping>
<cmp-field-mapping>
...
</cmp-field-mapping>
<consistency>
<check-version-of-accessed-instances>
<column-name>OrderTable.VC_VERSION_NUMBER</column-name>
</check-version-of-accessed-instances>
</consistency>
</entity-mapping>In addition, you must establish a trigger on the database to automatically update the version column when data in the specified table is modified. The GlassFish Server requires such a trigger to use version consistency. Having such a trigger also ensures that external applications that modify the EJB data will not conflict with EJB transactions in progress.
For example, the following DDL illustrates how to create a trigger for
the Order table:
CREATE TRIGGER OrderTrigger
BEFORE UPDATE ON OrderTable
FOR EACH ROW
WHEN (new.VC_VERSION_NUMBER = old.VC_VERSION_NUMBER)
DECLARE
BEGIN
:NEW.VC_VERSION_NUMBER := :OLD.VC_VERSION_NUMBER + 1;
END;Request partitioning enables you to assign a request priority to an EJB component. This gives you the flexibility to make certain EJB components execute with higher priorities than others.
An EJB component which has a request priority assigned to it will have its requests (services) executed within an assigned threadpool. By assigning a threadpool to its execution, the EJB component can execute independently of other pending requests. In short, request partitioning enables you to meet service-level agreements that have differing levels of priority assigned to different services.
Request partitioning applies only to remote EJB components (those that implement a remote interface). Local EJB components are executed in their calling thread (for example, when a servlet calls a local bean, the local bean invocation occurs on the servlet’s thread).
To Enable Request Partitioning
Follow this procedure.
Configure additional threadpools for EJB execution.
Using the GlassFish Server Administration Console, navigate to the
Configurations>configuration-name>Thread Pools node. Refer to the
Administration Console online help for more information. Alternatively,
you can follow the instructions in "Administering
Thread Pools" in GlassFish Server Open Source Edition Administration
Guide.
Configure the threadpools as follows:
Add the additional threadpool IDs to the GlassFish Server’s ORB.
This can be done on the Configurations>configuration-name>ORB node in
the Administration Console.
For example, enable threadpools named priority-1 and priority-2 to
the <orb> element as follows:
<orb max-connections="1024" message-fragment-size="1024"
use-thread-pool-ids="thread-pool-1,priority-1,priority-2">
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 GlassFish Server.
This section provides tips for tuning various specific types of EJB components:
These components can all be configured in the GlassFish Server Administration Console from the Configurations>configuration-name>EJB Container node. Alternatively, you can perform these configurations by following the instructions in "RMI-IIOP Load Balancing and Failover" in GlassFish Server Open Source Edition High Availability Administration Guide.
Depending on the usage of a particular entity bean, one should tune
max-cache-size so that the beans that are used less frequently (for
example, an order that is created and never used after the transaction
is over) are cached less, and beans that are used frequently (for
example, an item in the inventory that gets referenced very often), are
cached more.
When a stateful bean represents a user, a reasonable max-cache-size of
beans is the expected number of concurrent users on the application
server process. If this value is too low (in relation to the steady load
of users), beans would be frequently passivated and activated, causing a
negative impact on the response times, due to CPU intensive
serialization and deserialization as well as disk I/O.
Another important variable for tuning is cache-idle-timeout-in-seconds
where at periodic intervals of cache-idle-timeout-in-seconds, all the
beans in the cache that have not been accessed for more than
cache-idle-timeout-in-seconds time, are passivated. Similar to an HTTP
session timeout, the bean is removed after it has not been accessed for
removal-timeout-in-seconds. Passivated beans are stored on disk in
serialized form. A large number of passivated beans could not only mean
many files on the disk system, but also slower response time as the
session state has to be de-serialized before the invocation.
Checkpoint only when needed
In high availability mode, when using stateful session beans, consider checkpointing only those methods that alter the state of the bean significantly. This reduces the number of times the bean state has to be checkpointed into the persistent store.
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 cache data from the database. GlassFish Server
supports read-only beans that use both bean-managed persistence (BMP)
and container-managed persistence (CMP). Of the two types, CMP read-only
beans provide significantly better performance. In the EJB lifecycle,
the EJB container calls the ejbLoad() method of a read-only bean once.
The container makes multiple copies of the EJB component from that data,
and since the beans do not update the database, the container never
calls the ejbStore() method. This greatly reduces database traffic for
these beans.
If there is a bean that never updates the database, use a read-only bean in its place to improve performance. A read-only bean is appropriate if either:
Database rows represented by the bean do not change.
The application can tolerate using out-of-date values for the bean.
For example, an application might use a read-only bean to represent a list of best-seller books. Although the list might change occasionally in the database (say, from another bean entirely), the change need not be reflected immediately in an application.
The ejbLoad() method of a read-only bean is handled differently for
CMP and BMP beans. For CMP beans, the EJB container calls ejbLoad()
only once to load the data from the database; subsequent uses of the
bean just copy that data. For BMP beans, the EJB container calls
ejbLoad() the first time a bean is used in a transaction. Subsequent
uses of that bean within the transaction use the same values. The
container calls ejbLoad() for a BMP bean that doesn’t run within a
transaction every time the bean is used. Therefore, read-only BMP beans
still make a number of calls to the database.
To create a read-only bean, add the following to the EJB deployment
descriptor sun-ejb-jar.xml:
<is-read-only-bean>true</is-read-only-bean>
<refresh-period-in-seconds>600</refresh-period-in-seconds>Refresh Period
An important parameter for tuning read-only beans is the refresh period,
represented by the deployment descriptor entity
refresh-period-in-seconds. For CMP beans, the first access to a bean
loads the bean’s state. The first access after 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).
If a container-managed relationship (CMR) exists in your application,
loading one bean will load all its related beans. The canonical example
of CMR is an order-orderline relationship where you have one Order EJB
component that has related OrderLine EJB components. In previous
releases of the application server, to use all those beans would require
multiple database queries: one for the Order bean and one for each of
the OrderLine beans in the relationship.
In general, if a bean has n relationships, using all the data of the bean would require n+1 database accesses. Use CMR pre-fetching to retrieve all the data for the bean and all its related beans in one database access.
For example, you have this relationship defined in the ejb-jar.xml
file:
<relationships>
<ejb-relation>
<description>Order-OrderLine</description>
<ejb-relation-name>Order-OrderLine</ejb-relation-name>
<ejb-relationship-role>
<ejb-relationship-role-name>
Order-has-N-OrderLines
</ejb-relationship-role-name>
<multiplicity>One</multiplicity>
<relationship-role-source>
<ejb-name>OrderEJB</ejb-name>
</relationship-role-source>
<cmr-field>
<cmr-field-name>orderLines</cmr-field-name>
<cmr-field-type>java.util.Collection</cmr-field-type>
</cmr-field>
</ejb-relationship-role>
</ejb-relation>
</relationships>When a particular Order is loaded, you can load its related
OrderLines by adding this to the sun-cmp-mapping.xml file for the
application:
<entity-mapping>
<ejb-name>Order</ejb-name>
<table-name>...</table-name>
<cmp-field-mapping>...</cmp-field-mapping>
<cmr-field-mapping>
<cmr-field-name>orderLines</cmr-field-name>
<column-pair>
<column-name>OrderTable.OrderID</column-name>
<column-name>OrderLineTable.OrderLine_OrderID</column-name>
</column-pair>
<fetched-with>
<default>
</fetched-with>
</cmr-field-mapping>
</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_OrderIDThis clause indicates an outer join. These OrderLines are pre-fetched.
Pre-fetching generally improves performance because it reduces the
number of database accesses. However, if the business logic often uses
Orders without referencing their OrderLines, then this can have a
performance penalty, that is, the system has spent the effort to
pre-fetch the OrderLines that are not actually needed.
Avoid pre-fetching for specific finder methods; this can often avoid
that penalty. For example, consider an order bean has two finder
methods: a findByPrimaryKey method that uses the Orderlines, and a
findByCustomerId method that returns only order information and
therefore does not use the Orderlines. If you have enabled CMR
pre-fetching for the Orderlines, both finder methods will pre-fetch
the Orderlines. However, you can prevent pre-fetching for the
findByCustomerId method by including this information in the
sun-ejb-jar.xml descriptor:
<ejb>
<ejb-name>OrderBean</ejb-name>
...
<cmp>
<prefetch-disabled>
<query-method>
<method-name>findByCustomerId</method-name>
</query-method>
</prefetch-disabled>
</cmp>
</ejb>The following are some tips to improve the performance of database access:
When dealing with large amounts of data, such as searching a large database, use JDBC directly rather than using Entity EJB components.
Combine business logic with the Entity EJB component that holds the data needed for that logic to process.
To ensure that connections are returned to the pool, always close the connections after use.
Use the default isolation level provided by the JDBC driver rather than
calling setTransactionIsolationLevel(), unless you are certain that
your application behaves correctly and performs better at a different
isolation level.
Reduce the database transaction isolation level when appropriate. Reduced isolation levels reduce work in the database tier, and could lead to better application performance. However, this must be done after carefully analyzing the database table usage patterns.
To set the database transaction isolation level using the GlassFish Server Administration Console, navigate to the Resources>JDBC>JDBC Connection Pools>pool-name node. Refer to the Administration Console online help for complete instructions. Alternatively, follow the instructions in "Administering Database Connectivity" in GlassFish Server Open Source Edition Administration Guide. For more information on tuning JDBC connection pools, see JDBC Connection Pool Settings.
This section provides some tips to improve performance when using JMS with message-driven beans (MDBs).
getConnection()JMS connections are served from a connection pool. This means that
calling getConnection() on a Queue connection factory is fast.
The container for message-driven beans (MDB) is different than the containers for entity and session beans. In the MDB container, sessions and threads are attached to the beans in the MDB pool. This design makes it possible to pool the threads for executing message-driven requests in the container.
Tune the Message-Driven bean’s pool size to optimize the concurrent processing of messages. Set the size of the MDB pool to, based on all the parameters of the server (taking other applications into account). For example, a value greater than 500 is generally too large.
To configure MDB pool settings in the GlassFish Server Administration
Console, navigate to the Configurations>configuration-name>EJB Container
node and then select the MDB Settings tab. Refer to the Administration
Console online help for more information. Alternatively, you can set the
MDB pool size by using the following asadmin set subcommand:
asadmin set server.mdb-container.max-pool-size = valueUse the setMessageDrivenContext() or ejbCreate() method to cache
bean specific resources, and release those resources from the
ejbRemove() method.
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 specifically close the session, or it will stay open, which ties up resources.
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