Return-Path: X-Original-To: apmail-hbase-issues-archive@www.apache.org Delivered-To: apmail-hbase-issues-archive@www.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id 3E16918493 for ; Sat, 7 Nov 2015 00:41:12 +0000 (UTC) Received: (qmail 66955 invoked by uid 500); 7 Nov 2015 00:41:11 -0000 Delivered-To: apmail-hbase-issues-archive@hbase.apache.org Received: (qmail 66833 invoked by uid 500); 7 Nov 2015 00:41:11 -0000 Mailing-List: contact issues-help@hbase.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list issues@hbase.apache.org Received: (qmail 66772 invoked by uid 99); 7 Nov 2015 00:41:11 -0000 Received: from arcas.apache.org (HELO arcas) (140.211.11.28) by apache.org (qpsmtpd/0.29) with ESMTP; Sat, 07 Nov 2015 00:41:11 +0000 Received: from arcas.apache.org (localhost [127.0.0.1]) by arcas (Postfix) with ESMTP id 2C5922C1F51 for ; Sat, 7 Nov 2015 00:41:11 +0000 (UTC) Date: Sat, 7 Nov 2015 00:41:11 +0000 (UTC) From: "Hudson (JIRA)" To: issues@hbase.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Commented] (HBASE-14463) Severe performance downgrade when parallel reading a single key from BucketCache MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/HBASE-14463?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14994787#comment-14994787 ] Hudson commented on HBASE-14463: -------------------------------- FAILURE: Integrated in HBase-Trunk_matrix #440 (See [https://builds.apache.org/job/HBase-Trunk_matrix/440/]) HBASE-14463 Severe performance downgrade when parallel reading a single (tedyu: rev 263a0adf79105b9dc166e21c3f5159ade6e2d0a7) * hbase-server/src/test/java/org/apache/hadoop/hbase/util/TestIdReadWriteLock.java * hbase-server/src/test/java/org/apache/hadoop/hbase/io/hfile/bucket/TestBucketCache.java * hbase-server/src/test/java/org/apache/hadoop/hbase/io/hfile/CacheTestUtils.java * hbase-server/src/main/java/org/apache/hadoop/hbase/io/hfile/bucket/BucketCache.java * hbase-server/src/main/java/org/apache/hadoop/hbase/util/IdReadWriteLock.java > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332)