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https://issues.apache.org/jira/browse/HBASE-7842?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13594212#comment-13594212
 ] 

Hadoop QA commented on HBASE-7842:
----------------------------------

{color:red}-1 overall{color}.  Here are the results of testing the latest 
attachment 
  http://issues.apache.org/jira/secure/attachment/12572222/HBASE-7842-2.patch
  against trunk revision .

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

    {color:green}+1 tests included{color}.  The patch appears to include 4 new 
or modified tests.

    {color:green}+1 hadoop2.0{color}.  The patch compiles against the hadoop 
2.0 profile.

    {color:green}+1 javadoc{color}.  The javadoc tool did not generate any 
warning messages.

    {color:green}+1 javac{color}.  The applied patch does not increase the 
total number of javac compiler warnings.

    {color:green}+1 findbugs{color}.  The patch does not introduce any new 
Findbugs (version 1.3.9) warnings.

    {color:green}+1 release audit{color}.  The applied patch does not increase 
the total number of release audit warnings.

    {color:green}+1 lineLengths{color}.  The patch does not introduce lines 
longer than 100

     {color:red}-1 core tests{color}.  The patch failed these unit tests:
                       
org.apache.hadoop.hbase.regionserver.TestDefaultCompactSelection

Test results: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//testReport/
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-prefix-tree.html
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-client.html
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-common.html
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-protocol.html
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-server.html
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-hadoop1-compat.html
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-examples.html
Findbugs warnings: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//artifact/trunk/patchprocess/newPatchFindbugsWarningshbase-hadoop-compat.html
Console output: 
https://builds.apache.org/job/PreCommit-HBASE-Build/4686//console

This message is automatically generated.
                
> Add compaction policy that explores more storefile groups
> ---------------------------------------------------------
>
>                 Key: HBASE-7842
>                 URL: https://issues.apache.org/jira/browse/HBASE-7842
>             Project: HBase
>          Issue Type: New Feature
>          Components: Compaction
>            Reporter: Elliott Clark
>            Assignee: Elliott Clark
>         Attachments: HBASE-7842-0.patch, HBASE-7842-2.patch
>
>
> Some workloads that are not as stable can have compactions that are too large 
> or too small using the current storefile selection algorithm.
> Currently:
> * Find the first file that Size(fi) <= Sum(0, i-1, FileSize(fx))
> * Ensure that there are the min number of files (if there aren't then bail 
> out)
> * If there are too many files keep the larger ones.
> I would propose something like:
> * Find all sets of storefiles where every file satisfies 
> ** FileSize(fi) <= Sum(0, i-1, FileSize(fx))
> ** Num files in set =< max
> ** Num Files in set >= min
> * Then pick the set of files that maximizes ((# storefiles in set) / 
> Sum(FileSize(fx)))
> The thinking is that the above algorithm is pretty easy reason about, all 
> files satisfy the ratio, and should rewrite the least amount of data to get 
> the biggest impact in seeks.

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