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From "Hadoop QA (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-18158) Two running in-memory compaction threads may lose data
Date Tue, 06 Jun 2017 18:29:18 GMT

    [ https://issues.apache.org/jira/browse/HBASE-18158?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16039416#comment-16039416
] 

Hadoop QA commented on HBASE-18158:
-----------------------------------

| (x) *{color:red}-1 overall{color}* |
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|| Vote || Subsystem || Runtime || Comment ||
| {color:blue}0{color} | {color:blue} reexec {color} | {color:blue} 0m 0s {color} | {color:blue}
Docker mode activated. {color} |
| {color:red}-1{color} | {color:red} patch {color} | {color:red} 0m 7s {color} | {color:red}
HBASE-18158 does not apply to master. Rebase required? Wrong Branch? See https://yetus.apache.org/documentation/0.3.0/precommit-patchnames
for help. {color} |
\\
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|| Subsystem || Report/Notes ||
| JIRA Patch URL | https://issues.apache.org/jira/secure/attachment/12871652/HBASE-18158.v2.patch
|
| JIRA Issue | HBASE-18158 |
| Console output | https://builds.apache.org/job/PreCommit-HBASE-Build/7114/console |
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> Two running in-memory compaction threads may lose data
> ------------------------------------------------------
>
>                 Key: HBASE-18158
>                 URL: https://issues.apache.org/jira/browse/HBASE-18158
>             Project: HBase
>          Issue Type: Bug
>    Affects Versions: 2.0.0
>            Reporter: Chia-Ping Tsai
>            Assignee: Chia-Ping Tsai
>             Fix For: 2.0.0
>
>         Attachments: HBASE-18158.v0.patch, HBASE-18158.v1.patch, HBASE-18158.v2.patch,
HBASE-18158.v2.patch
>
>
> {code:title=CompactingMemStore.java|borderStyle=solid}
>   private void stopCompaction() {
>     if (inMemoryFlushInProgress.get()) {
>       compactor.stop();
>       inMemoryFlushInProgress.set(false);
>     }
>   }
> {code}
> The stopCompaction() set inMemoryFlushInProgress to false so there may be two in-memory
compaction threads which execute simultaneously. If there are two running InMemoryFlushRunnable,
the later InMemoryFlushRunnable may change the versionedList. 
> {code:title=MemStoreCompactor.java|borderStyle=solid}
>   public boolean start() throws IOException {
>     if (!compactingMemStore.hasImmutableSegments()) { // no compaction on empty pipeline
>       return false;
>     }
>     // get a snapshot of the list of the segments from the pipeline,
>     // this local copy of the list is marked with specific version
>     versionedList = compactingMemStore.getImmutableSegments();
> {code}
> And the first InMemoryFlushRunnable will use the chagned versionedList to remove the
corresponding segments.
> {code:title=MemStoreCompactor#doCompaction|borderStyle=solid}
>       if (!isInterrupted.get()) {
>         if (resultSwapped = compactingMemStore.swapCompactedSegments(
>             versionedList, result, (action==Action.MERGE))) {
>           // update the wal so it can be truncated and not get too long
>           compactingMemStore.updateLowestUnflushedSequenceIdInWAL(true); // only if greater
>         }
>       }
> {code}
> In conclusion, first InMemoryFlushRunnable will remove the worng segment. And the later
InMemoryFlushRunnable may introduce NPE because first InMemoryFlushRunnable set versionedList
to null after compaction.
> {code}
> Exception in thread "RpcServer.default.FPBQ.Fifo.handler=3,queue=0,port=45712-inmemoryCompactions-1496563908038"
java.lang.NullPointerException
>         at org.apache.hadoop.hbase.regionserver.CompactionPipeline.swap(CompactionPipeline.java:119)
>         at org.apache.hadoop.hbase.regionserver.CompactingMemStore.swapCompactedSegments(CompactingMemStore.java:283)
>         at org.apache.hadoop.hbase.regionserver.MemStoreCompactor.doCompaction(MemStoreCompactor.java:212)
>         at org.apache.hadoop.hbase.regionserver.MemStoreCompactor.start(MemStoreCompactor.java:122)
>         at org.apache.hadoop.hbase.regionserver.CompactingMemStore.flushInMemory(CompactingMemStore.java:388)
>         at org.apache.hadoop.hbase.regionserver.CompactingMemStore$InMemoryFlushRunnable.run(CompactingMemStore.java:500)
>         at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> {code}



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