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Understanding EclipseLink, 2.4
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About Handling Stale Data

Stale data is an artifact of caching, in which an object in the cache is not the most recent version committed to the data source. To avoid stale data, implement an appropriate cache locking strategy.

By default, EclipseLink optimizes concurrency to minimize cache locking during read or write operations. Use the default EclipseLink isolation level, unless you have a very specific reason to change it. For more information on isolation levels in EclipseLink, see Shared, Isolated, Protected, Weak, and Read-only Caches.

Cache locking regulates when processes read or write an object. Depending on how you configure it, cache locking determines whether a process can read or write an object that is in use within another process.

A well-managed cache makes your application more efficient. There are very few cases in which you turn the cache off entirely, because the cache reduces database access, and is an important part of managing object identity.

To make the most of your cache strategy and to minimize your application's exposure to stale data, Oracle recommends the following:

Configuring a Locking Policy

Make sure you configure a locking policy so that you can prevent or at least identify when values have already changed on an object you are modifying. Typically, this is done using optimistic locking. EclipseLink offers several locking policies such as numeric version field, time-stamp version field, and some or all fields. Optimistic and pessimistic locking are described in the following sections.

Optimistic Locking

Oracle recommends using EclipseLink optimistic locking. With optimistic locking, all users have read access to the data. When a user attempts to write a change, the application checks to ensure the data has not changed since the user read the data.

You can use version or field locking policies. Oracle recommends using version locking policies. For more information, see Optimistic Version Locking Policies and Optimistic Field Locking Policies.

Pessimistic Locking

With pessimistic locking, the first user who accesses the data with the purpose of updating it locks the data until completing the update. The disadvantage of this approach is that it may lead to reduced concurrency and deadlocks.

Consider using pessimistic locking support at the query level. See Pessimistic Locking Policies.

Configuring the Cache on a Per-Class Basis

If other applications can modify the data used by a particular class, use a weaker style of cache for the class. For example, the SoftCacheWeakIdentityMap or WeakIdentityMap minimizes the length of time the cache maintains an object whose reference has been removed.

Forcing a Cache Refresh when Required on a Per-Query Basis

Any query can include a flag that forces EclipseLink to go to the data source for the most up-to-date version of selected objects and update the cache with this information.

Configuring Cache Invalidation

Using the Descriptor API, you can designate an object as invalid: when any query attempts to read an invalid object, EclipseLink will go to the data source for the most up to date version of that object and update the cache with this information. You can manually designate an object as invalid or use a CacheInvalidationPolicy to control the conditions under which an object is designated invalid. For more information, see About Cache Expiration and Invalidation.

Configuring Cache Coordination

If your application is primarily read-based and the changes are all being performed by the same Java application operating with multiple, distributed sessions, you may consider using the EclipseLink cache coordination feature. Although this will not prevent stale data, it should greatly minimize it. For more information, see About Cache Coordination.

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