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https://issues.apache.org/jira/browse/CASSANDRA-4718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Benedict updated CASSANDRA-4718:
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Attachment: E600M_summary_key_s.svg
E100M_summary_key_s.svg
E10M_summary_key_s.svg
Attached are some graphs of running reads with exponential key distributions
over different key ranges (10M, 100M, 600M) - though over the same dataset
(600M keys), on a 2-node c3.8xlarge cluster, with 1 c3.8xlarge load generator.
All of the thread counts were run for 1M operations. These are the last of a
sequence of test runs as, initially, by far the biggest determining factor was
page cache behaviour - with each iteration the page cache's page retention
algorithm got progressively better at retaining the best subset of the pages to
service the requests. Note also the scales - in particular the 600M test both
are within 1% of each other performance-wise, and I would note that the
variability was greater than 1%, and that in prior runs the positions were
reversed.
> 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, E100M_summary_key_s.svg,
> E10M_summary_key_s.svg, E600M_summary_key_s.svg, PerThreadQueue.java,
> austin_diskbound_read.svg, 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_run1.svg, jason_run2.svg, jason_run3.svg, jason_write.svg, op costs of
> various queues.ods, stress op rate with various queues.ods,
> stress_2014May15.txt, stress_2014May16.txt, 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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