EclipseLink is an advanced, object- persistence and persistence, supporting the JPA (Java Persistence API) specification and a native API. Refer to the EclipseLink Documentation Center. Please see the EclipseLink Solutions Guide and Understanding EclipseLink ( Concepts Search the EclipseLink JPA documentation wiki.
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This section describes tuning the default internal cache that is provided by EclipseLink. Although this tutorial does not include EclipseLink-specific information, it does contain useful information to help you implement JPA 2. Visit the EclipseLink forum. That’s where JPA comes in. There is not a single tuning parameter that sets a particular database transaction isolation level in a JPA application that uses EclipseLink.
Optimistic All users have read access to the data. Java Persistence specification for complete information about JPA http: Understanding EclipseLink Concepts 2.
Consult your use case scenarios to determine is using these parameters is appropriate for your environment:. We are in the process of updating it to a much more usable JPA focused set of wiki pages.
Oracle supports the locking policies shown in Table 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.
If frequent concurrent updates to the same rows are expected, pessimistic locking may be faster than optimistic locking that is getting a lot of concurrent access exceptions and retries. Doug Clarke 2 6. Where appropriate, this documentation provides links to the pertinent section of the specification.
This chapter includes the following sections: Table shows the cache configuration options.
For the license of dependent libraries included within a distribution please refer to the about. Pessimistic The eclipselin user who accesses the data with the purpose of updating it locks the data until completing the update. This allows clustered application deployments to scale beyond database-bound operations.
It associates the object data member with its data source representation and defines the means of performing the two-way conversion between object and data source.
The student example is intended to provide a simple example of using JPA-RS with a single entity persistence unit in a web application.
No Locking In general, no locking is faster, but may not meet your needs for data consistency. Batch fetching has three types: For more information on performance tuning in these areas, see the following: Oracle Toplink can be integrated with Oracle Coherence.
EclipseLink Comprehensive open-source Java persistence solution addressing relational, XML, and database web services. This section lists a few features in EclipseLink that can help you analyze your JPA application performance:. In EclipseLink, there’re differents kinds of sessions.
You can also force queries to go to the database with disableHits.
When a user attempts to make a change, the application checks to ensure the data has not changed since the user read the data. For more information on using Partioned and other partitioning policy annotations, see “Partitioning Annotations” at http: I have been having a terrible time trying to get EclipseLink to work, even though everyone says how great it is compared to Hibernate.
EclipseLink, JPA, and Oracle Coherence
But I’d like to point out that wasted time and frustration when learning new technologies is just part of the job specification for a Software Engineer. Java Persistence specification for complete information about JPA http: The data store is available in the PriceTarget. EclipseLink defers reading the dependent object until you access that specific attribute.
If infrequent concurrent updates to the same rows are expected, then optimistic locking may provide the best performance while providing data consistency guarantees. A mapping corresponds to a single data member of a domain object. Can you let us know what you are trying to do and doucmentation can provide direct assistance or point you into the docs at the most appropriate content.
Always use sequence number pre-allocation for best performance for inserts. Join Fetching Join fetching is a query optimization feature that enables a single query for a class to return the data to build the instances of that class and its related objects. In the case when you are not concerned about stale data, you should use optimistic locking; this automatically refresh stale objects in the cache on locking errors. For optimal performance use read-only on any query where the resulting objects are not changed.
For more information, see “Configuring a Locking Policy” at http: In this example, Eclipselihk events docmuentation date and time information. Documentatioj this case you should also use optimistic locking, which automatically refresh stale objects when a locking error occurs.
And, joining works on queries that not work with batch fetching. In general, no locking is faster, but may not meet your needs for data consistency. While the chapter provides common performance tuning considerations and related documentation resources, it is not meant to be comprehensive list of areas to tune.