[
https://issues.apache.org/jira/browse/OPENJPA-637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jeremy Bauer updated OPENJPA-637:
---------------------------------
Attachment: CacheImplTest.jar
I've attached a standalone test for running some tests using various cache
implementations and configurations. It behaves similarly to the benchmark that
exposed this problem. The test allows configuration of number of threads, max
data size, max cache size, whether external locking is enabled, and the cache
implementation type.
This test is showing similar results as to what I've previously posted; a write
lock causing contention when the cache becomes full. When the external write
lock (a reentrant lock over and above internal cache locking) is enabled and
the data size is ~5000 entries larger than the max cache size performance drops
significantly. The external lock simulates the reentrant lock used by
DataCacheStoreManager to ensure the cache does not get updated with an old
version of data.
This test should provide a better idea of what I'm seeing. Aside, there is an
option to run directly with java.util.concurrent.ConcurrentHashMap and it
performs very well - although there is no null masking or maximum size on the
cache.
To get a list of options: java -cp
CacheImplTest.jar;commons-collections-3.2.jar cachetest.Main
Patrick - What behavior/environment does your benchmark test? Is it possible
that your cache size is very near the size of your data so you are not hitting
the problem?
> Significant performance degradation when data cache is enabled
> --------------------------------------------------------------
>
> Key: OPENJPA-637
> URL: https://issues.apache.org/jira/browse/OPENJPA-637
> Project: OpenJPA
> Issue Type: Bug
> Components: datacache, lib
> Affects Versions: 1.2.0
> Reporter: Jeremy Bauer
> Attachments: CacheImplTest.jar, OPENJPA-637.patch
>
>
> Performance testing is showing a severe data cache performance degradation
> when moving from 1.0.x OpenJPA code to 1.2.0 level code. Profiling showed
> the problem to be in the new random eviction scheme which runs when the cache
> reaches its maximum number of entries. This code was changed significantly
> when OpenJPA moved to Java 5 java.util.concurrent.ConcurrentHashMap and away
> from the OpenJPA implementation of ConcurrentHashMap. A macro-benchmark
> showed a 20% performance degradation from base 1.2.0 code when the cache
> reaches its maximum size; prompting eviction in order to add new cache
> entries.
> I've found that the new random eviction code appears to be improved in the
> very recent 666903 commit, but data cache performance remains considerably
> slower than the 1.0.x implementation. Profiles with the 666903 changes show
> test threads to be waiting on the reentrant write lock in the CacheMap
> wrapper (which now wrappers a max size capable, null handling, subclass of
> java.util.concurrent.ConcurrentHashMap). Investigation is underway to
> determine whether the write lock is necessary (ie. can
> java.util.conncurrentConcurrentHashMap manage the cache without the need for
> external locking) and/or if changes could be made which would result in a
> significant reduction in contention for the lock. Any thoughts/ideas on that
> would be extremely helpful.
> Performance tests run with the 1.2.0 code base, using the OpenJPA version of
> ConcurrentHashMap (instead of the Java 5
> java.util.concurrent.ConcurrentHashMap-based implementation) have shown that
> performance of the data cache is significantly better when the legacy OpenJPA
> implementation is used. Based on the results, it appears that OpenJPA should
> be using the the legacy ConcurrentHashMap instead of the Java 5-based
> implementation -- or the new Java 5-based implementation needs to be improved
> considerably in order to perform as well as 1.0.x.
> I am opening this as a 1.2.0 issue, although it very likely affects 1.1.x as
> well. Testing has not been performed on 1.1.x to confirm the problem exists
> on that release.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
