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https://issues.apache.org/jira/browse/HBASE-17215?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16720779#comment-16720779
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Hudson commented on HBASE-17215:
--------------------------------

SUCCESS: Integrated in Jenkins build HBase-1.3-IT #509 (See 
[https://builds.apache.org/job/HBase-1.3-IT/509/])
HBASE-20557 Backport HBASE-17215 to branch-1 (apurtell: rev 
30b1dc00b47a0289a721cd0f932d9cdd8422534e)
* (edit) 
hbase-server/src/main/java/org/apache/hadoop/hbase/master/cleaner/HFileCleaner.java
* (edit) 
hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/RSRpcServices.java
* (edit) hbase-server/src/main/java/org/apache/hadoop/hbase/master/HMaster.java
* (edit) 
hbase-server/src/test/java/org/apache/hadoop/hbase/master/cleaner/TestHFileCleaner.java


> Separate small/large file delete threads in HFileCleaner to accelerate 
> archived hfile cleanup speed
> ---------------------------------------------------------------------------------------------------
>
>                 Key: HBASE-17215
>                 URL: https://issues.apache.org/jira/browse/HBASE-17215
>             Project: HBase
>          Issue Type: Improvement
>            Reporter: Yu Li
>            Assignee: Yu Li
>            Priority: Major
>             Fix For: 2.0.0
>
>         Attachments: HBASE-17215.patch, HBASE-17215.v2.patch, 
> HBASE-17215.v3.patch
>
>
> When using PCIe-SSD the flush speed will be really quick, and although we 
> have per CF flush, we still have the 
> {{hbase.regionserver.optionalcacheflushinterval}} setting and some other 
> mechanism to avoid data kept in memory for too long to flush small hfiles. In 
> our online environment we found the single thread cleaner kept cleaning 
> earlier flushed small files while large files got no chance, which caused 
> disk full then many other problems.
> Deleting hfiles in parallel with too many threads will also increase the 
> workload of namenode, so here we propose to separate large/small hfile 
> cleaner threads just like we do for compaction, and it turned out to work 
> well in our cluster.



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