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https://issues.apache.org/jira/browse/CASSANDRA-15213?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17016070#comment-17016070
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Benedict Elliott Smith commented on CASSANDRA-15213:
----------------------------------------------------
Also fwiw, it looks like the primes 17 and 19 are sufficient, so we can
literally just try either of those. Proof:
{code}
int[] primes = new int[] { 17, 19 };
BitSet sizeWithoutConflict = new BitSet();
for (int prime : primes)
{
for (int size = 1 ; size < 238 ; ++size)
{
BitSet conflict = new BitSet();
boolean hasConflict = false;
for (int i = 0 ; i < size ; ++i)
{
if (conflict.get((i * prime) % size))
hasConflict = true;
conflict.set((i * prime) % size);
}
if (!hasConflict)
sizeWithoutConflict.set(size);
}
}
for (int size = 1 ; size < 238 ; ++size)
{
if (!sizeWithoutConflict.get(size))
System.out.println(size);
}
{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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