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https://issues.apache.org/jira/browse/CASSANDRA-15213?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Benedict updated CASSANDRA-15213:
---------------------------------
Description:
* {{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.
> DecayingEstimatedHistogramReservoir Inefficiencies
> --------------------------------------------------
>
> Key: CASSANDRA-15213
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15213
> Project: Cassandra
> Issue Type: Bug
> Components: Observability/Metrics
> Reporter: Benedict
> Priority: Normal
>
> * {{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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