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For details on EclipseLink Grid, see Disabling Entity Caching Disable the shared cache for highly volatile entities or for all entities as required. To selectively enable or disable the shared cache, use the shared attribute of the Cache annotation when defining an entity. There are different ways to refresh a cache. The Cache annotation provides the alwaysRefresh and refreshOnlyIfNewer attributes which force all queries that go to the database to refresh the cache. The cache is only actually refreshed if the optimistic lock value in the database is newer than in the cache.

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For details on EclipseLink Grid, see Disabling Entity Caching Disable the shared cache for highly volatile entities or for all entities as required. To selectively enable or disable the shared cache, use the shared attribute of the Cache annotation when defining an entity. There are different ways to refresh a cache. The Cache annotation provides the alwaysRefresh and refreshOnlyIfNewer attributes which force all queries that go to the database to refresh the cache.

The cache is only actually refreshed if the optimistic lock value in the database is newer than in the cache. Cache interface includes methods that remove stale objects if the cache is out of date: The evictAll method invalidates all of the objects in the cache. To actively refresh an object, use the EntityManager. The method refreshes a single object at a time. Another possibility is to use the setHint method to set a query hint that triggers the query to refresh the cache.

Setting Entity Caching Expiration Cache expiration makes a cached object instance invalid after a specified amount of time.

Any attempt to use the object causes the most up-to-date version of the object to be reloaded from the data source. Expiration can help ensure that an application is always using the most recent data.

There are different ways to set expiration. The Cache annotation provides the expiry and expiryTimeOfDay attributes, which remove cache instances after a specific amount of time. The expiry attribute is entered in milliseconds. The default value if no value is specified is -1, which indicates that expiry is disabled. The expiryTimeOfDay attribute is an instance of the org. TimeOfDay interface. Locking is important when multiple servers or multiple applications access the same data and is relevant in both single-server and multiple-server environments.

In a multiple-server environment, locking is still required if an application uses cache refreshing or cache coordination. There are different ways to set optimistic locking. The standard JPA Version annotation is used for single valued value and timestamp based locking. However, for advanced locking features use the OptimisticLocking annotation. The OptimisticLocking annotation specifies the type of optimistic locking to use when updating or deleting entities. Optimistic locking is supported on an Entity or MappedSuperclass annotation.

A delete operation compares only the primary key. The fields that are specified must be mapped and not be primary keys. The version field must be mapped and not be the primary key. The method is set to false by default. Using Cache Coordination Cache coordination synchronizes changes among distributed sessions.

Cache coordination is most useful in application server clusters where maintaining consistent data for all applications is challenging. Moreover, cache consistency becomes increasingly more difficult as the number of servers within an environment increases. Cache coordination works by broadcasting notifications of transactional object changes among sessions EntityManagerFactory or persistence unit in the cluster.

Cache coordination is most useful for applications that are primarily read-based and when changes are performed by the same application operating with multiple, distributed sessions. Cache coordination significantly minimizes stale data, but does not completely eliminate the possibility that stale data might occur because of latency. In addition, cache coordination reduces the number of optimistic lock exceptions encountered in distributed architectures, and reduces the number of failed or repeated transactions in an application.

However, cache coordination in no way eliminates the need for an effective locking policy. To ensure the most current data, use cache coordination with optimistic or pessimistic locking; optimistic locking is preferred. System properties that match the persistence properties are available as well. This data is merged into the receiving cache. The receiving cache invalidates the objects rather than changing any of the data.

This option is the lightest in terms of data sent and processing done in other cluster members. NONE: This option does no cache coordination. The Cache annotation coordinationType attribute is used to specify synchronization. For applications that run outside the cluster, a URL is required. This could be done through the persistence. The final option is to set the URL as a system property on each application server. Synchronous broadcasting ensures that all of the servers are updated before a request returns.

The following example configures synchronous broadcasting. The interface is accessed using the getCommandManager method from the DatabaseSession interface. Data partitioning is supported at the entity level to allow a different set of entity instances for the same class to be stored in a different physical database or different node within a database cluster.

Both regular databases and clustered databases are supported. Data can be partitioned both horizontally and vertically. Partitioning can be enabled on an entity, a relationship, a query, or a persistence unit. To configure data partitioning, use the Partitioned annotation and one or more partitioning policy annotations.

All write or read request for objects with that hash value are sent to the same server. This allows for vertical partitioning. Each server is assigned a range of values. All write or read requests for objects with that value are sent to the same server.

This policy is for replicating data across a cluster of database machines. Only modification queries are replicated. This policy is used for load balancing read queries across a cluster of database machines.

It requires that the full database be replicated on each machine, so it does not support partitioning. The data should either be read-only, or writes should be replicated. UnionPartitioning Sends queries to all connection pools and unions the results.

This is for queries or relationships that span partitions when partitioning is used, such as on a ManyToMany cross partition relationship. Each value is assigned a specific server. Partitioning Partitions access to a database cluster by a custom partitioning policy. A class that extends the PartitioningPolicy class must be provided. Partitioning policies are globally-named objects in a persistence unit and are reusable across multiple descriptors or queries.

Connection pools are defined in the persistence. Partition policies select the appropriate connection based on their particular algorithm. If a transaction modifies data from multiple partitions, JTA should be used to ensure 2-phase commit of the data. An exclusive connection can also be configured in an EntityManager implementation to ensure only a single node is used for a single transaction. The following example partitions the Employee data by location.

The two primary sites, Ottawa and Toronto, are each stored on a separate database. All other locations are stored on the default database. Project is range partitioned by its ID. Each range of ID values are stored on a different database.

To allow the employees and projects to be stored on different databases a union policy is used and the join table is replicated to each database. Oracle RAC also supports table and node partitioning of data. A database cluster allows for any of the data to be accessed from any node in the cluster. However, it is generally more efficient to partition the data access to specific nodes, to reduce cross node communication.

Partitioning can be used in conjunction with a clustered database to reduce cross node communication, and improve scalability. Adhere to the following requirements when using data partitioning with a database cluster: Partition policy should not enable replication, as database cluster makes data available to all nodes.

Partition policy should not use unions, as database cluster returns the complete query result from any node. A DataSource and connection pool should be defined for each node in the cluster.

Usage of an exclusive connection for an EntityManager is recommended to avoid having multiple nodes in a single transaction and avoid 2-phase commit.

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EclipseLink

This section describes how these features improve performance. Read-only Queries EclipseLink uses the eclipselink. 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. Join Fetching Join Fetching enhances performance by enabling the joining and reading of the related objects in the same query as the source object. This example shows how the JoinFetch annotation specifies the Employee field managedEmployees.

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Begin moving content based on dev priorities to new pages. Ideally users of a specific version can find their content with minimal clutter of new version content. Continue to allow community participation in the evolution of the wiki documentation. We should clearly document our expectations however and ensure that all doc pages are watched so content changes are known and verified. Address offline usage of the documentation. This could be PDF or offline caching of specific doc pages. In either case the usability of the produced documentation must be maintained or enhanced.

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