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From "Pavel Yaskevich (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-4718) More-efficient ExecutorService for improved throughput
Date Wed, 14 May 2014 16:53:24 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-4718?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13997754#comment-13997754
] 

Pavel Yaskevich commented on CASSANDRA-4718:
--------------------------------------------

bq. What about writes, that's a pretty big scenario this helps improve 

The latest Ryan's numbers are from write workload.

bq. Well, except that we expect in general for recent data to be accessed most often, or data
to be accessed according to a zipf distribution, and in both of these cases caching helps
to keep a significant portion of the data we're accessing in memory. Also, more users are
getting incredibly performant SSDs that can respond to queries in time horizons measured in
microseconds, and as this becomes the norm the distinction also becomes less important.

I always thought that Zipf's law is for the scientific data, is it not? SSD could be performant
but you can't get the full speed yet as close as you can get currently is 3.13+ with multiqueue
support enabled.

bq. Right, but we've always targetted "total data larger than memory, hot data more or less
fits." So I absolutely think this ticket is relevant for a lot of use cases.

Exactly, "hot data more or less fits" so the problem is that once you get into page page reclaim
and disk reads (even SSDs), improvements maid here are no longer doing anything helpful, I
think that would be clearly visible on the benchmarks to come.

> More-efficient ExecutorService for improved throughput
> ------------------------------------------------------
>
>                 Key: CASSANDRA-4718
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-4718
>             Project: Cassandra
>          Issue Type: Improvement
>            Reporter: Jonathan Ellis
>            Assignee: Benedict
>            Priority: Minor
>              Labels: performance
>             Fix For: 2.1.0
>
>         Attachments: 4718-v1.patch, PerThreadQueue.java, aws.svg, aws_read.svg, backpressure-stress.out.txt,
baq vs trunk.png, belliotsmith_branches-stress.out.txt, jason_read.svg, jason_read_latency.svg,
jason_write.svg, op costs of various queues.ods, stress op rate with various queues.ods, v1-stress.out
>
>
> Currently all our execution stages dequeue tasks one at a time.  This can result in contention
between producers and consumers (although we do our best to minimize this by using LinkedBlockingQueue).
> One approach to mitigating this would be to make consumer threads do more work in "bulk"
instead of just one task per dequeue.  (Producer threads tend to be single-task oriented by
nature, so I don't see an equivalent opportunity there.)
> BlockingQueue has a drainTo(collection, int) method that would be perfect for this. 
However, no ExecutorService in the jdk supports using drainTo, nor could I google one.
> What I would like to do here is create just such a beast and wire it into (at least)
the write and read stages.  (Other possible candidates for such an optimization, such as the
CommitLog and OutboundTCPConnection, are not ExecutorService-based and will need to be one-offs.)
> AbstractExecutorService may be useful.  The implementations of ICommitLogExecutorService
may also be useful. (Despite the name these are not actual ExecutorServices, although they
share the most important properties of one.)



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