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Date: Sat, 7 Nov 2015 01:18:10 +0000 (UTC)
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Subject: [jira] [Commented] (HBASE-14463) Severe performance downgrade when
 parallel reading a single key from BucketCache
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    [ https://issues.apache.org/jira/browse/HBASE-14463?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14994825#comment-14994825 ] 

Hadoop QA commented on HBASE-14463:
-----------------------------------

{color:green}+1 overall{color}.  Here are the results of testing the latest attachment 
  http://issues.apache.org/jira/secure/attachment/12771116/14463-branch-1-v12.txt
  against branch-1 branch at commit 263a0adf79105b9dc166e21c3f5159ade6e2d0a7.
  ATTACHMENT ID: 12771116

    {color:green}+1 @author{color}.  The patch does not contain any @author tags.

    {color:green}+1 tests included{color}.  The patch appears to include 8 new or modified tests.

    {color:green}+1 hadoop versions{color}. The patch compiles with all supported hadoop versions (2.4.0 2.4.1 2.5.0 2.5.1 2.5.2 2.6.0 2.6.1 2.7.0 2.7.1)

    {color:green}+1 javac{color}.  The applied patch does not increase the total number of javac compiler warnings.

    {color:green}+1 protoc{color}.  The applied patch does not increase the total number of protoc compiler warnings.

    {color:green}+1 javadoc{color}.  The javadoc tool did not generate any warning messages.

    {color:green}+1 checkstyle{color}.  The applied patch does not increase the total number of checkstyle errors

    {color:green}+1 findbugs{color}.  The patch does not introduce any  new Findbugs (version 2.0.3) warnings.

    {color:green}+1 release audit{color}.  The applied patch does not increase the total number of release audit warnings.

    {color:green}+1 lineLengths{color}.  The patch does not introduce lines longer than 100

  {color:green}+1 site{color}.  The mvn post-site goal succeeds with this patch.

    {color:green}+1 core tests{color}.  The patch passed unit tests in .

Test results: https://builds.apache.org/job/PreCommit-HBASE-Build/16438//testReport/
Release Findbugs (version 2.0.3) 	warnings: https://builds.apache.org/job/PreCommit-HBASE-Build/16438//artifact/patchprocess/newFindbugsWarnings.html
Checkstyle Errors: https://builds.apache.org/job/PreCommit-HBASE-Build/16438//artifact/patchprocess/checkstyle-aggregate.html

  Console output: https://builds.apache.org/job/PreCommit-HBASE-Build/16438//console

This message is automatically generated.

> Severe performance downgrade when parallel reading a single key from BucketCache
> --------------------------------------------------------------------------------
>
>                 Key: HBASE-14463
>                 URL: https://issues.apache.org/jira/browse/HBASE-14463
>             Project: HBase
>          Issue Type: Bug
>    Affects Versions: 0.98.14, 1.1.2
>            Reporter: Yu Li
>            Assignee: Yu Li
>             Fix For: 2.0.0, 1.2.0, 1.3.0, 0.98.17
>
>         Attachments: 14463-branch-1-v12.txt, GC_with_WeakObjectPool.png, HBASE-14463.patch, HBASE-14463_v11.patch, HBASE-14463_v12.patch, HBASE-14463_v12.patch, HBASE-14463_v2.patch, HBASE-14463_v3.patch, HBASE-14463_v4.patch, HBASE-14463_v5.patch, TestBucketCache-new_with_IdLock.png, TestBucketCache-new_with_IdReadWriteLock.png, TestBucketCache_with_IdLock-latest.png, TestBucketCache_with_IdLock.png, TestBucketCache_with_IdReadWriteLock-latest.png, TestBucketCache_with_IdReadWriteLock-resolveLockLeak.png, TestBucketCache_with_IdReadWriteLock.png, pe_use_same_keys.patch, test-results.tar.gz
>
>
> We store feature data of online items in HBase, do machine learning on these features, and supply the outputs to our online search engine. In such scenario we will launch hundreds of yarn workers and each worker will read all features of one item(i.e. single rowkey in HBase), so there'll be heavy parallel reading on a single rowkey.
> We were using LruCache but start to try BucketCache recently to resolve gc issue, and just as titled we have observed severe performance downgrade. After some analytics we found the root cause is the lock in BucketCache#getBlock, as shown below
> {code}
>       try {
>         lockEntry = offsetLock.getLockEntry(bucketEntry.offset());
>         // ...
>         if (bucketEntry.equals(backingMap.get(key))) {
>           // ...
>           int len = bucketEntry.getLength();
>           Cacheable cachedBlock = ioEngine.read(bucketEntry.offset(), len,
>               bucketEntry.deserializerReference(this.deserialiserMap));
> {code}
> Since ioEnging.read involves array copy, it's much more time-costed than the operation in LruCache. And since we're using synchronized in IdLock#getLockEntry, parallel read dropping on the same bucket would be executed in serial, which causes a really bad performance.
> To resolve the problem, we propose to use ReentranceReadWriteLock in BucketCache, and introduce a new class called IdReadWriteLock to implement it.


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