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https://issues.apache.org/jira/browse/HBASE-16417?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16210737#comment-16210737
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Hadoop QA commented on HBASE-16417:
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| JIRA Issue | HBASE-16417 |
| JIRA Patch URL |
https://issues.apache.org/jira/secure/attachment/12893008/HBASE-16417.09.patch |
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This message was automatically generated.
> In-Memory MemStore Policy for Flattening and Compactions
> --------------------------------------------------------
>
> Key: HBASE-16417
> URL: https://issues.apache.org/jira/browse/HBASE-16417
> Project: HBase
> Issue Type: Sub-task
> Reporter: Anastasia Braginsky
> Assignee: Eshcar Hillel
> Fix For: 3.0.0
>
> Attachments: HBASE-16417 - Adaptive Compaction Policy - 20171001.pdf,
> HBASE-16417 - parameter tuning - 20171001.pdf, HBASE-16417-V01.patch,
> HBASE-16417-benchmarkresults-20161101.pdf,
> HBASE-16417-benchmarkresults-20161110.pdf,
> HBASE-16417-benchmarkresults-20161123.pdf,
> HBASE-16417-benchmarkresults-20161205.pdf,
> HBASE-16417-benchmarkresults-20170309.pdf,
> HBASE-16417-benchmarkresults-20170317.pdf, HBASE-16417.01.patch,
> HBASE-16417.02.patch, HBASE-16417.03.patch, HBASE-16417.04.patch,
> HBASE-16417.05.patch, HBASE-16417.06.patch, HBASE-16417.07.patch,
> HBASE-16417.07.patch, HBASE-16417.08.patch, HBASE-16417.09.patch
>
>
> This Jira explores the performance of different memstore compaction policies.
> It presents the result of write-only workload evaluation as well as read
> performance in read-write workloads.
> We investigate several settings of hardware (SSD, HDD), key distribution
> (Zipf, uniform), with multiple settings of the system, and compare measures
> like write throughput, read latency, write volume, total gc time, etc.
> The submitted patch sets some system properties at the values yielding
> optimal performance. In addition we suggest a new Adaptive memstore
> compaction policy that shows good tradeoffs between write throughput and
> write volume.
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