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From "Benedict (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-10326) Performance is worse in 3.0
Date Thu, 17 Sep 2015 22:25:04 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-10326?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14804638#comment-14804638
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Benedict commented on CASSANDRA-10326:
--------------------------------------

[One more|http://cstar.datastax.com/graph?stats=6dbe3ee4-5d7b-11e5-a4e4-42010af0688f&metric=op_rate&operation=1_user&smoothing=1&show_aggregates=true&xmin=0&xmax=869.99&ymin=0&ymax=145546.5]
([and again|http://cstar.datastax.com/tests/id/1ea46496-5d53-11e5-a4e4-42010af0688f). This
is with compression disabled and again not reversed. Performance is much closer, but random
point queries are still significantly slower. CASSANDRA-10322 makes up a significant chunk
of that, but is still 25% slower.

Notably, 2.2 produces less garbage and more consistent results (the two possibly related).

It's also worth noting these datasets are still in-memory, so it's still quite likely users
with larger than memory datasets will see an improvement (not that we shouldn't strive to
fix this). We should probably run some other tests on that front, although obviously that
takes a lot longer.

> Performance is worse in 3.0
> ---------------------------
>
>                 Key: CASSANDRA-10326
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-10326
>             Project: Cassandra
>          Issue Type: Bug
>            Reporter: Benedict
>            Priority: Critical
>             Fix For: 3.0.x
>
>
> Performance is generally turning out to be worse after 8099, despite a number of unrelated
performance enhancements being delivered. This isn't entirely unexpected, given a great deal
of time was spent optimising the old code, however things appear worse than we had hoped.
> My expectation was that workloads making extensive use of CQL constructs would be faster
post-8099, however the latest tests performed with very large CQL rows, including use of collections,
still exhibit performance below that of 2.1 and 2.2. 
> Eventually, as the dataset size grows large enough and the locality of access is just
right, the reduction in size of our dataset will yield a window during which some users will
perform better due simply to improved page cache hit rates. We seem to see this in some of
the tests. However we should be at least as fast (and really faster) off the bat.
> The following are some large partition benchmark results, with as many as 40K rows per
partition, running LCS. There are a number of parameters we can modify to see how behaviour
changes and under what scenarios we might still be faster, but the picture painted isn't brilliant,
and is consistent, so we should really try and figure out what's up before GA.
> [trades-with-flags (collections), blade11b|http://cstar.datastax.com/graph?stats=f0a17292-5a13-11e5-847a-42010af0688f&metric=op_rate&operation=1_user&smoothing=1&show_aggregates=true&xmin=0&xmax=4387.02&ymin=0&ymax=122951.4]
> [trades-with-flags (collections), blade11|http://cstar.datastax.com/graph?stats=e25aaaa0-5a13-11e5-ae0d-42010af0688f&metric=op_rate&operation=1_user&smoothing=1&show_aggregates=true&xmin=0&xmax=4424.75&ymin=0&ymax=130158.6]
> [trades (no collections), blade11|http://cstar.datastax.com/graph?stats=9b7da48e-570c-11e5-90fe-42010af0688f&metric=op_rate&operation=1_user&smoothing=1&show_aggregates=true&xmin=0&xmax=2682.46&ymin=0&ymax=142547.9]
> [~slebresne]: will you have time to look into this before GA?



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