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https://issues.apache.org/jira/browse/CASSANDRA-15213?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17012330#comment-17012330
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Jordan West commented on CASSANDRA-15213:
-----------------------------------------
My working branch is here:
[https://github.com/jrwest/cassandra/tree/jwest/15213]
I've implemented the binary search replacement. Didn't make an attempt at going
branchless but even as implemented its faster than the existing implementation.
Working on the striping / replacement of {{LongAdder[]}} and will share when
ready.
{code:java}
Trunk:
[java] Benchmark Mode Cnt
Score Error Units
[java] LatencyTrackingBench.benchInsertToDEHR thrpt 5
21887453.678 ± 2108481.285 ops/s
[java] LatencyTrackingBench.benchLatencyMetricsWrite thrpt 5
8908817.316 ± 115453.642 ops/s
15213 (linear search changes only):
[java] Benchmark Mode Cnt
Score Error Units
[java] LatencyTrackingBench.benchInsertToDEHR thrpt 5
24646022.304 ± 1052105.818 ops/s
[java] LatencyTrackingBench.benchLatencyMetricsWrite thrpt 5
9175928.594 ± 269984.204 ops/s
{code}
> DecayingEstimatedHistogramReservoir Inefficiencies
> --------------------------------------------------
>
> Key: CASSANDRA-15213
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15213
> Project: Cassandra
> Issue Type: Bug
> Components: Observability/Metrics
> Reporter: Benedict Elliott Smith
> Assignee: Jordan West
> Priority: Normal
> Fix For: 4.0-beta
>
>
> * {{LongAdder}} introduced to trunk consumes 9MiB of heap without user
> schemas, and this will grow significantly under contention and user schemas
> with many tables. This is because {{LongAdder}} is a very heavy class
> designed for single contended values.
> ** This can likely be improved significantly, without significant loss of
> performance in the contended case, by simply increasing the size of our
> primitive backing array and providing multiple buckets, with each thread
> picking a bucket to increment, or simply multiple backing arrays. Probably a
> better way still to do this would be to introduce some competition detection
> to the update, much like {{LongAdder}} utilises, that increases the number of
> backing arrays under competition.
> ** To save memory this approach could partition the space into chunks that
> are likely to be updated together, so that we do not need to duplicate the
> entire array under competition.
> * Similarly, binary search is costly and a measurable cost as a share of the
> new networking work (without filtering it was > 10% of the CPU used overall).
> We can compute an approximation floor(log2 n / log2 1.2) extremely cheaply,
> to save the random memory access costs.
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