[
https://issues.apache.org/jira/browse/HBASE-14463?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14996106#comment-14996106
]
Hadoop QA commented on HBASE-14463:
-----------------------------------
{color:red}-1 overall{color}. Here are the results of testing the latest
attachment
http://issues.apache.org/jira/secure/attachment/12771270/HBASE-14463.branch-0.98.patch
against 0.98 branch at commit 1cbcf1175e6ce497936f12c60fb2e897833ace39.
ATTACHMENT ID: 12771270
{color:green}+1 @author{color}. The patch does not contain any @author
tags.
{color:green}+1 tests included{color}. The patch appears to include 10 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:red}-1 javadoc{color}. The javadoc tool appears to have generated
28 warning messages.
{color:red}-1 checkstyle{color}. The applied patch generated
3891 checkstyle errors (more than the master's current 3890 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/16453//testReport/
Release Findbugs (version 2.0.3) warnings:
https://builds.apache.org/job/PreCommit-HBASE-Build/16453//artifact/patchprocess/newFindbugsWarnings.html
Checkstyle Errors:
https://builds.apache.org/job/PreCommit-HBASE-Build/16453//artifact/patchprocess/checkstyle-aggregate.html
Javadoc warnings:
https://builds.apache.org/job/PreCommit-HBASE-Build/16453//artifact/patchprocess/patchJavadocWarnings.txt
Console output:
https://builds.apache.org/job/PreCommit-HBASE-Build/16453//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.branch-0.98.patch, 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
