accumulo-notifications mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Keith Turner (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (ACCUMULO-3067) scan performance degrades after compaction
Date Thu, 21 Aug 2014 15:11:11 GMT

    [ https://issues.apache.org/jira/browse/ACCUMULO-3067?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14105445#comment-14105445
] 

Keith Turner commented on ACCUMULO-3067:
----------------------------------------

I wonder if loading the iterators using different class loaders would make a difference. 
Using different class loaders yields different instances of the class.  The question is, would
these different class instances be optimized independently?  Also are the iterators coming
from the same class loader now?  I think the system iterators would come from the same class
loader.

> scan performance degrades after compaction
> ------------------------------------------
>
>                 Key: ACCUMULO-3067
>                 URL: https://issues.apache.org/jira/browse/ACCUMULO-3067
>             Project: Accumulo
>          Issue Type: Bug
>          Components: tserver
>         Environment: Macbook Pro 2.6 GHz Intel Core i7, 16GB RAM, SSD, OSX 10.9.4, single
tablet server process, single client process
>            Reporter: Adam Fuchs
>         Attachments: Screen Shot 2014-08-19 at 4.19.37 PM.png, accumulo_query_perf_test.tar.gz,
jit_log_during_compaction.txt
>
>
> I've been running some scan performance tests on 1.6.0, and I'm running into an interesting
situation in which query performance starts at a certain level and then degrades by ~15% after
an event. The test follows roughly the following scenario:
>  # Single tabletserver instance
>  # Load 100M small (~10byte) key/values into a tablet and let it finish major compacting
>  # Disable the garbage collector (this makes the time to _the event_ longer)
>  # Restart the tabletserver
>  # Repeatedly scan from the beginning to the end of the table in a loop
>  # Something happens on the tablet server, like one of {idle compaction of metadata table,
forced flush of metadata table, forced compaction of metadata table, forced flush of trace
table}
>  # Observe that scan rates dropped by 15-20%
>  # Observe that restarting the scan will not improve performance back to original level.
Performance only gets better upon restarting the tablet server.
> I've been able to get this not to happen by removing iterators from the iterator tree.
It doesn't seem to matter which iterators, but removing a certain number both improves performance
(significantly) and eliminates the degradation problem. The default iterator tree includes:

>  * SourceSwitchingIterator
>  ** VersioningIterator
>  *** SynchronizedIterator
>  **** VisibilityFilter
>  ***** ColumnQualifierFilter
>  ****** ColumnFamilySkippingIterator
>  ******* DeletingIterator
>  ******** StatsIterator
>  ********* MultiIterator
>  ********** MemoryIterator
>  ********** ProblemReportingIterator
>  *********** HeapIterator
>  ************ RFile.LocalityGroupReader
> We can eliminate the weird condition by narrowing the set of iterators to:
>  * SourceSwitchingIterator
>  ** VisibilityFilter
>  *** ColumnFamilySkippingIterator
>  **** DeletingIterator
>  ***** StatsIterator
>  ****** MultiIterator
>  ******* MemoryIterator
>  ******* ProblemReportingIterator
>  ******** HeapIterator
>  ********* RFile.LocalityGroupReader
> There are other combinations that also perform much better than the default. I haven't
been able to isolate this problem to a single iterator, despite removing each iterator one
at a time.
> Anybody know what might be happening here? Best theory so far: the JVM learns that iterators
can be used in a different way after a compaction, and some JVM optimization like JIT compilation,
branch prediction, or automatic inlining stops happening.



--
This message was sent by Atlassian JIRA
(v6.2#6252)

Mime
View raw message