9 Enhancing Performance

9.1.1.1 Caching Annotations

TopLink defines these entity caching annotations:

• @Cache

• @TimeOfDay

• @ExistenceChecking

TopLink also provides a number of persistence unit properties that you can specify to configure the TopLink cache (see "How to Use the Persistence Unit Properties for Caching" in the EclipseLink online documentation, at http://wiki.eclipse.org/Using_EclipseLink_JPA_Extensions_%28ELUG%29#How_to_Use_the_Persistence_Unit_Properties_for_Caching). These properties might compliment or provide an alternative to the usage of annotations.

9.1.1.2 Using the @Cache Annotation

TopLink uses identity maps to cache objects in order to enhance performance, as well as maintain object identity. You can control the cache and its behavior by using the @Cache annotation in your entity classes. Example 9-1 shows how to implement this annotation.

@Entity
 @Table(name="EMPLOYEE")
 @Cache (
     type=CacheType.WEAK,
     isolated=false,
     expiry=600000,
     alwaysRefresh=true,
     disableHits=true,
     coordinationType=INVALIDATE_CHANGED_OBJECTS
     )
 public class Employee implements Serializable {
     ...
 }

For more information on object caching and using the @Cache annotation, see "Using EclipseLink JPA Extensions for Entity Caching" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/Using_EclipseLink_JPA_Extensions_%28ELUG%29#Using_EclipseLink_JPA_Extensions_for_Entity_Caching

9.1.2.1 Read-only Queries

TopLink uses the eclipselink.read-only hint, QueryHint (@QueryHint) to retrieve read-only results back from a query. On nontransactional read operations, where the requested entity types are stored in the shared cache, you can request that the shared instance be returned instead of a detached copy.

For more information on read-only queries, see the documentation for the read-only hint at:

http://wiki.eclipse.org/Using_EclipseLink_JPA_Extensions_%28ELUG%29#Read_Only

9.1.2.2 Join Fetching

Join Fetching enhances performance by enabling the joining and reading of the related objects in the same query as the source object. Enable Join Fetching by using the @JoinFetch annotation, as shown in Example 9-2. This example shows how the @JoinFetch annotation specifies the Employee field managedEmployees.

@Entity
 public class Employee implements Serializable {
     ...
     @OneToMany(cascade=ALL, mappedBy="owner")
     @JoinFetch(value=OUTER)
     public Collection<Employee> getManagedEmployees() {
         return managedEmployees;
     }
     ...
 }

For more details on Join Fetching, see "How to Use the @JoinFetch Annotation" in the EclipseLink online documentation at:

http://wiki.eclipse.org/Using_EclipseLink_JPA_Extensions_%28ELUG%29#How_to_Use_the_.40JoinFetch_Annotation

9.1.2.3 Batch Reading

The eclipselink.batch hint supplies TopLink with batching information so subsequent queries of related objects can be optimized in batches instead of being retrieved one-by-one or in one large joined read. Batch reading is more efficient than joining because it avoids reading duplicate data. Batching is only allowed on queries that have a single object in their select clause.

9.1.2.4 Fetch Size

If you have large queries that return a large number of objects you can improve performance by reducing the number database hits required to satisfy the selection criteria. To do this, use the The eclipselink.jdbc.fetch-size hint. This hint specifies the number of rows that should be fetched from the database when more rows are required (depending on the JDBC driver support level). Most JDBC drivers default to a fetch size of 10, so if you are reading 1000 objects, increasing the fetch size to 256 can significantly reduce the time required to fetch the query's results. The optimal fetch size is not always obvious. Usually, a fetch size of one half or one quarter of the total expected result size is optimal. Note that if you are unsure of the result set size, incorrectly setting a fetch size too large or too small can decrease performance.

9.1.2.5 Pagination

Slow paging can result in significant application overhead; however, TopLink includes a variety of solutions for improving paging results; for example, you can:

• Configure the first and maximum number of rows to retrieve when executing a query.

• Perform a query on the database for all of the ID values that match the criteria and then use these values to retrieve specific sets.

• Configure TopLink to return a ScrollableCursor object from a query by using query hints. This returns a database cursor on the query's result set and allows the client to scroll through the results page by page.

For details on improving paging performance, see "How to use EclipseLink Pagination" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/EclipseLink/Examples/JPA/Pagination#How_to_use_EclipseLink_Pagination

9.1.2.6 Cache Usage

TopLink uses a shared cache mechanism that is scoped to the entire persistence unit. When operations are completed in a particular persistence context, the results are merged back into the shared cache so that other persistence contexts can use them. This happens regardless of whether the entity manager and persistence context are created in Java SE or Java EE. Any entity persisted or removed using the entity manager will always be kept consistent with the cache.

You can specify how the query should interact with the TopLink cache by using the eclipselink.cache-usage hint. For more information, see "Cache Usage" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/Using_EclipseLink_JPA_Extensions_%28ELUG%29#Cache_Usage

9.1.3.1 Indirection ("Lazy Loading")

By default, when TopLink retrieves a persistent object, it retrieves all of the dependent objects to which it refers. When you configure indirection (also known as lazy loading, lazy reading, and just-in-time reading) for an attribute mapped with a relationship mapping, TopLink uses an indirection object as a place holder for the referenced object. TopLink defers reading the dependent object until you access that specific attribute. This can result in a significant performance improvement, especially if the application is interested only in the contents of the retrieved object, rather than the objects to which it is related.

TopLink supports a variety of types of indirection, including: value holder indirection, transparent indirect container indirection, and proxy indirection.

9.1.3.2 Read-Only Objects

When you declare a class read-only, clones of that class are neither created nor merged greatly improving performance. You can declare a class as read-only within the context of a unit of work by using the addReadOnlyClass() method.

• To configure a read-only class for a single unit of work, specify that class as the argument to addReadOnlyClass():

  myUnitofWork.addReadOnlyClass(B.class);
  

• To configure multiple classes as read-only, add them to a vector and specify that vector as the argument to addReadOnlyClass():

  myUnitOfWork.addReadOnlyClasses(myVectorOfClasses);
  

For more information on using read-only objects to enhance performance, see "Declaring Read-Only Classes" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/Using_Advanced_Unit_of_Work_API_%28ELUG%29#Declaring_Read-Only_Classes

9.1.3.3 Weaving

Weaving is a technique of manipulating the byte-code of compiled Java classes. The TopLink JPA persistence provider uses weaving to enhance both JPA entities and Plain Old Java Object (POJO) classes for such things as lazy loading, change tracking, fetch groups, and internal optimizations.Weaving can be performed either dynamically at runtime, when entities are loaded, or statically at compile time by post-processing the entity .class files. By default, TopLink uses dynamic weaving whenever possible. This includes inside an Java EE 5/6 application server and in Java SE when the TopLink agent is configured. Dynamic weaving is recommended as it is easy to configure and does not require any changes to a project's build process

For details on how to use weaving to enhance application performance, see "Weaving" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/EclipseLink/UserGuide/JPA/Advanced_JPA_Development/Performance/Weaving

9.1.5.1 Connection Pooling

Establishing a connection to a data source can be time-consuming, so reusing such connections in a connection pool can improve performance. TopLink uses connection pools to manage and share the connections used by server and client sessions. This feature reduces the number of connections required and allows your application to support many clients.

By default, TopLink sessions use internal connection pools. These pools allow you to optimize the creation of read connections for applications that read data only to display it and only infrequently modify data. The also allow you to use Workbench to configure the default (write) and read connection pools and to create additional connection pools for object identity or any other purpose.

In addition to internal connection pools, you can also configure TopLink to use any of these types of connection pools:

• External connection pools; you must use this type of connection pool to integrate with external transaction controller (JTA).

• Default (write) and read connection pools;

• Sequence connection pools; Use these types of pools when your application requires table sequencing (that is, non-native sequencing) and you are using an external transaction controller. Application-specific connection pools; These are connection pools that you can create and use for any application purpose, provided you are using internal TopLink connection pools in a session.

For more information on using connection pools with TopLink, see the following topics in the EclipseLink online documentation:

• "Connection Pools", at:

  http://wiki.eclipse.org/Introduction_to_Data_Access_%28ELUG%29#Connection_Pools

• "Introduction to the Internal Connection Pool Creation", at:

  http://wiki.eclipse.org/Creating_an_Internal_Connection_Pool_%28ELUG%29#Introduction_to_the_Internal_Connection_Pool_Creation

9.1.5.2 Parameterized SQL and Statement Caching

Parameterized SQL can prevent the overall length of an SQL query from exceeding the statement length limit that your JDBC driver or database server imposes. Using parameterized SQL along with prepared statement caching can improve performance by reducing the number of times the database SQL engine parses and prepares SQL for a frequently called query

By default, TopLink enables parameterized SQL but not prepared statement caching. You should enable statement caching either in TopLink when using an internal connection pool or in the data source when using an external connection pool and want to specify a statement cache size appropriate for your application.

To enable parameterized SQL, add this line to the persistence.xml file that is in the same path as your domain classes:

<property name="eclipselink.jdbc.bind-parameters" value="true"/>

To disable parameterized SQL, change value= to false.

For more information on using parameterized SQL and statement caching, see "How to Use Parameterized SQL (Parameter Binding) and Prepared Statement Caching for Optimization" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#How_to_Use_Parameterized_SQL_.28Parameter_Binding.29_and_Prepared_Statement_Caching_for_Optimization

9.1.5.3 Batch Writing

Batch writing helps optimize transactions with multiple write operations. Batch writing is enabled by using the TopLink JDBC extension batch-writing. You set one of the following parameter this property into the session at deployment time:

• JDBC; Use JDBC batch writing.

• Buffered; Do not use either JDBC batch writing nor native platform batch writing.

• Oracle-JDBC; Use both JDBC batch writing and Oracle native platform batch writing and use OracleJDBC in your property map.

• None; Disable batch writing.

For more information on batch writing, see "How to Use EclipseLink JPA Extensions for JDBC Connection Communication" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/Using_EclipseLink_JPA_Extensions_%28ELUG%29#Using_EclipseLink_JPA_Extensions_for_JDBC

9.2.2.1 Enabling the TopLink Profiler

The TopLink performance profiler is an instance of org.eclipse.persistence.tools.profiler.PerformanceProfiler class. To enable it, add the following line to the persistence.xml file:

<property name="eclipselink.profiler" value="PerformanceProfiler.logProfiler"/>

In addition to enabling the TopLink profiler, The PerformanceProfiler class public API also provides the functionality describes in Table 9-2:

9.2.2.2 Accessing and Interpreting Profiler Results

You can see profiling results by opening the profile log in a text reader, such as Notepad.

The profiler output file indicates the health of a TopLink-enabled application.

Example 9-4 shows an sample of the TopLink profiler output.

Begin Profile of{
ReadAllQuery(com.demos.employee.domain.Employee)
Profile(ReadAllQuery,# of obj=12, time=139923809,sql execute=21723809,
prepare=49523809, row fetch=39023809, time/obj=11623809,obj/sec=8)
} End Profile

Example 9-4 shows the following information about the query:

• ReadAllQuery(com.demos.employee.domain.Employee): specific query profiled, and its arguments.

• Profile(ReadAllQuery: start of the profile and the type of query.

• # of obj=12: number of objects involved in the query.

• time=139923809: total execution time of the query (in milliseconds).

• sql execute=21723809: total time spent executing the SQL statement.

• prepare=49523809: total time spent preparing the SQL statement.

• row fetch=39023809: total time spent fetching rows from the database.

• time/obj=116123809: number of nanoseconds spent on each object.

• obj/sec=8: number of objects handled per second.

9.2.4.1 Identifying General Performance Optimizations

Avoid overriding TopLink default behavior unless your application requires it. Some of these defaults are suitable for a development environment; you should change these defaults to suit your production environment (see "Optimizing for a Production Environment" in the EclipseLink online documentation at http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#Optimizing_for_a_Production_Environment).

Use the Workbench rather than manual coding. These tools are not only easy to use: the default configuration they export to deployment XML (and the code it generates, if required) represents best practices optimized for most applications.

9.2.4.2 Schema

Optimization is an important consideration when you design your database schema and object model. Most performance issues occur when the object model or database schema is too complex, as this can make the database slow and difficult to query. This is most likely to happen if you derive your database schema directly from a complex object model.

To optimize performance, design the object model and database schema together. However, allow each model to be designed optimally: do not require a direct one-to-one correlation between the two.

"Optimizing Schema", in the EclipseLink online documentation (http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#Optimizing_Schema) includes four schema optimization scenarios that should help you design schema that provides the desired performance.

9.2.4.3 Mappings and Descriptors

If you find performance bottlenecks in your mapping and descriptors, try these solutions:

• Always use indirection (lazy loading). It is not only critical in optimizing database access, but also allows TopLink to make several other optimizations including optimizing its cache access and unit of work processing. See "Configuring Indirection (Lazy Loading)" in the EclipseLink online documentation, at:

  http://wiki.eclipse.org/Configuring_a_Mapping_%28ELUG%29#Configuring_Indirection_.28Lazy_Loading.29

• Avoid using method access in your TopLink mappings, especially if you have expensive or potentially dangerous side-effect code in your get or set methods; use the default direct attribute access instead. See "Configuring Method or Direct Field Accessing at the Mapping Level" in the EclipseLink online documentation, at:

  http://wiki.eclipse.org/Configuring_a_Descriptor_%28ELUG%29#Configuring_Cache_Existence_Checking_at_the_Descriptor_Level

• Avoid using the existence checking option checkCacheThenDatabase on descriptors, unless required by the application. The default existence checking behavior offers better performance. See "Configuring Cache Existence Checking at the Descriptor Level" in the EclipseLink online documentation, at:

  http://wiki.eclipse.org/Configuring_a_Mapping_%28ELUG%29#Configuring_Method_or_Direct_Field_Accessing_at_the_Mapping_Level

• Avoid expensive initialization in the default constructor that TopLink uses to instantiate objects. Instead, use lazy initialization or use an TopLink instantiation policy to configure the descriptor to use a different constructor. See Configuring Instantiation Policy" in the EclipseLink online documentation, at:

  http://wiki.eclipse.org/Configuring_a_Descriptor_%28ELUG%29#Configuring_Instantiation_Policy

9.2.4.4 Sessions

If you suspect that session performance hindering your application, try these solutions:

• Use a server session in a server environment instead of a database session.

• Use the TopLink client session instead of remote session. A client session is appropriate for most multiuser Java EE application server environments.

• Do not pool client sessions. Pooling sessions offers no performance gains.

• Increase the size of your session read and write connection pools to the desired number of concurrent threads (for example, 50). You can configure this in TopLink when you are using an internal connection pool or in the data source when you are using an external connection pool.

For a list of additional resources, see "Optimizing Sessions" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#Optimizing_Sessions

9.2.4.5 Cache

You can often improve cache performance by implementing cache coordination. Cache coordination allows multiple, possibly distributed instances of a session to broadcast object changes among each other so that each session's cache can be kept up-to-date. For detailed information on optimizing cache behavior, see "Optimizing Cache" in the EclipseLink online documentation, at:

http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#Optimizing_Cache

9.2.4.6 Data Access

Depending on the type of data source your application accesses, TopLink offers a variety of Login options that you can use to tune the performance of low level data reads and writes. For optimizing higher-level data reads and writes, "Optimizing Data Access" (in the EclipseLink online documentation at http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#Optimizing_Data_Access) offers several techniques to improve data access performance for your application. These techniques show you how to:

• Optimize JDBC driver properties.

• Optimize data format.

• Use batch writing for optimization.

• Use Outer-Join Reading with Inherited Subclasses.

• Use Parameterized SQL (Parameter Binding) and Prepared Statement Caching for Optimization.

9.2.4.7 Queries

TopLink provides an extensive query API for reading, writing, and updating data. "Optimizing Queries" (in the EclipseLink online documentation at http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#Optimizing_Queries) offers several techniques to improve query performance for your application. These techniques show you how to:

• Use parameterized SQL and prepared statement caching for optimization.

• Use named queries for optimization.

• Use batch and join reading for optimization.

• Use partial object queries and fetch groups for optimization.

• Use read-only queries for optimization.

• Use JDBC fetch size for optimization.

• Use cursored streams and scrollable cursors for optimization.

• Use result set pagination for optimization.

It also includes links to read and write optimization examples.

9.2.4.8 Unit of Work

To obtain optimal performance when using a unit of work, consider the following tips:

• Register objects with a unit of work only if objects are eligible for change. If you register objects that will not change, the unit of work needlessly clones and processes those objects.

• Avoid the cost of existence checking when you are registering a new or existing object. For more information, see "How to Use Registration and Existence Checking" in the EclipseLink online documentation at:

  http://wiki.eclipse.org/Using_Advanced_Unit_of_Work_API_%28ELUG%29#How_to_Use_Registration_and_Existence_Checking

• Avoid the cost of change set calculation on a class you know will not change by telling the unit of work that the class is read-only. For more information, see "Declaring Read-Only Classes" in the EclipseLink online documentation at:

  http://wiki.eclipse.org/Using_Advanced_Unit_of_Work_API_%28ELUG%29#Declaring_Read-Only_Classes

• Avoid the cost of change set calculation on an object read by a ReadAllQuery in a unit of work that you do not intend to change by unregistering the object. For more information, see "How to Unregister Working Clones" in the EclipseLink online documentation at:

  http://wiki.eclipse.org/Using_Advanced_Unit_of_Work_API_%28ELUG%29#How_to_Unregister_Working_Clones

• Before using conforming queries, be sure that it is necessary. For alternatives, see "Using Conforming Queries and Descriptors" in the EclipseLink online documentation at:

  http://wiki.eclipse.org/Using_Advanced_Unit_of_Work_API_%28ELUG%29#Using_Conforming_Queries_and_Descriptors

• Enable weaving and change tracking to greatly improve transactional performance. For more information, see "Optimizing Using Weaving" in the EclipseLink online documentation at:

  http://wiki.eclipse.org/Optimizing_the_EclipseLink_Application_%28ELUG%29#Optimizing_Using_Weaving

If your performance measurements show that you have a performance problem during unit of work commit, consider using object level or attribute level change tracking, depending on the type of objects involved and how they typically change. For more information, see "Unit of Work and Change Policy" in the EclipseLink online documentation at:

http://wiki.eclipse.org/Introduction_to_EclipseLink_Transactions_%28ELUG%29#Unit_of_Work_and_Change_Policy

9.2.4.9 Application Server and Database Optimization

To optimize the application server and database performance, consider these techniques:

• Configuring your application server and database correctly can have a big impact on performance and scalability. Ensure that you correctly optimize these key components of your application in addition to your TopLink application and persistence.

• For your application or Java EE server, ensure your memory, thread pool and connection pool sizes are sufficient for your server's expected load, and that your JVM has been configured optimally.

• Ensure that your database has been configured correctly for optimal performance and its expected load.