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https://issues.apache.org/jira/browse/CASSANDRA-4718?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13999045#comment-13999045
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Jason Brown edited comment on CASSANDRA-4718 at 5/15/14 10:40 PM:
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Adding more fuel to the testing fire, i took a first pass at having a large of
amount of data on disk (~2x the memory size of each box), and running the read
tests - see attached file: stress_2014May15.txt. I cleared the page cache
before switching to each branch from for the reads, and then performed 3 rounds
of stress. The goal here was to see how the sep branch compared with
cassandra-2.1 when doing most of the reads from disk (with a cold page cache,
or where the cache is constantly churning due to new blocks being pulled in).
The short story is the sep branch performs slightly worse the current
cassandra-2.1 (which includes CASSANDRA-5663) on both ops/s and latencies.
I'm going to do one more test where I preload a good chunk of the data into the
page cache, then run the stress - hopefully to emulate the case where most
reads come from the page cache and some go to disk. Will try to use a less
naive key distribution alg, to ensure that we hit the hot keys, which is
provided by stress.
was (Author: jasobrown):
Adding more fuel to the testing fire, i took a first pass at having a large of
amount of data on disk (~2x the memory size of each box), and running the read
tests - see attached file: stress_2014May15.txt. I cleared the page cache
before switching to each branch from for the reads, and then performed 3 rounds
of stress. The goal here was to see how the sep branch compared with
cassandra-2.1 when doing most of the reads from disk (with a cold page cache,
or where the cache is constantly churning due to new blocks being pulled in).
The short story is the sep branch performs slightly worse the current
cassandra-2.1 (which includes CASSANDRA-5663) on both ops/s and latencies.
I'm going to do one more test where I preload a good chunk of the data into the
page cache, then run the stress - hopefully to emulate the case where most
reads come from the page cache and some go to disk. Will me to use a less naive
key distribution alg, to ensure that we hit the hot keys, which is provided by
stress.
> 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, stress_2014May15.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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