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From "Hadoop QA (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-13408) HBase In-Memory Memstore Compaction
Date Fri, 21 Aug 2015 18:18:46 GMT

    [ https://issues.apache.org/jira/browse/HBASE-13408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14707192#comment-14707192
] 

Hadoop QA commented on HBASE-13408:
-----------------------------------

{color:red}-1 overall{color}.  Here are the results of testing the latest attachment 
  http://issues.apache.org/jira/secure/attachment/12751563/HBASE-13408-trunk-v02.patch
  against master branch at commit bcef28eefaf192b0ad48c8011f98b8e944340da5.
  ATTACHMENT ID: 12751563

    {color:green}+1 @author{color}.  The patch does not contain any @author tags.

    {color:green}+1 tests included{color}.  The patch appears to include 65 new or modified
tests.

    {color:red}-1 patch{color}.  The patch command could not apply the patch.

Console output: https://builds.apache.org/job/PreCommit-HBASE-Build/15205//console

This message is automatically generated.

> HBase In-Memory Memstore Compaction
> -----------------------------------
>
>                 Key: HBASE-13408
>                 URL: https://issues.apache.org/jira/browse/HBASE-13408
>             Project: HBase
>          Issue Type: New Feature
>            Reporter: Eshcar Hillel
>         Attachments: HBASE-13408-trunk-v01.patch, HBASE-13408-trunk-v02.patch, HBaseIn-MemoryMemstoreCompactionDesignDocument-ver02.pdf,
HBaseIn-MemoryMemstoreCompactionDesignDocument.pdf, InMemoryMemstoreCompactionEvaluationResults.pdf,
InMemoryMemstoreCompactionScansEvaluationResults.pdf
>
>
> A store unit holds a column family in a region, where the memstore is its in-memory component.
The memstore absorbs all updates to the store; from time to time these updates are flushed
to a file on disk, where they are compacted. Unlike disk components, the memstore is not compacted
until it is written to the filesystem and optionally to block-cache. This may result in underutilization
of the memory due to duplicate entries per row, for example, when hot data is continuously
updated. 
> Generally, the faster the data is accumulated in memory, more flushes are triggered,
the data sinks to disk more frequently, slowing down retrieval of data, even if very recent.
> In high-churn workloads, compacting the memstore can help maintain the data in memory,
and thereby speed up data retrieval. 
> We suggest a new compacted memstore with the following principles:
> 1.	The data is kept in memory for as long as possible
> 2.	Memstore data is either compacted or in process of being compacted 
> 3.	Allow a panic mode, which may interrupt an in-progress compaction and force a flush
of part of the memstore.
> We suggest applying this optimization only to in-memory column families.
> A design document is attached.
> This feature was previously discussed in HBASE-5311.



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