[jira] Commented: (HADOOP-2731) [hbase] Under extreme load, regions become extremely large and eventually cause region servers to become unresponsive

["Billy Pearson (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HADOOP-2731?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12563797#action_12563797 ] 

Billy Pearson commented on HADOOP-2731:
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I am talking on a theory I have about hot spots like this over at
HADOOP-2615

Take a look and see what you thank about the idea on the New idea on compaction process I had and comment if you like it or have anything better.

> [hbase] Under extreme load, regions become extremely large and eventually cause region servers to become unresponsive
> ---------------------------------------------------------------------------------------------------------------------
>
>                 Key: HADOOP-2731
>                 URL: https://issues.apache.org/jira/browse/HADOOP-2731
>             Project: Hadoop Core
>          Issue Type: Bug
>          Components: contrib/hbase
>            Reporter: Bryan Duxbury
>
> When attempting to write to HBase as fast as possible, HBase accepts puts at a reasonably high rate for a while, and then the rate begins to drop off, ultimately culminating in exceptions reaching client code. In my testing, I was able to write about 370 10KB records a second to HBase until I reach around 1 million rows written. At that point, a moderate to large number of exceptions - NotServingRegionException, WrongRegionException, region offline, etc - begin reaching the client code. This appears to be because the retry-and-wait logic in HTable runs out of retries and fails. 
> Looking at mapfiles for the regions from the command line shows that some of the mapfiles are between 1 and 2 GB in size, much more than the stated file size limit. Talking with Stack, one possible explanation for this is that the RegionServer is not choosing to compact files often enough, leading to many small mapfiles, which in turn leads to a few overlarge mapfiles. Then, when the time comes to do a split or "major" compaction, it takes an unexpectedly long time to complete these operations. This translates into errors for the client application.
> If I back off the import process and give the cluster some quiet time, some splits and compactions clearly do take place, because the number of regions go up and the number of mapfiles/region goes down. I can then begin writing again in earnest for a short period of time until the problem begins again.
> Both Marc Harris and myself have seen this behavior.

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