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Benedict commented on CASSANDRA-7282:
-------------------------------------
No. You benchmark to isolate performance improvements. These numbers
demonstrate a benefit _to any portion of a workload that fits these
characteristics_. Different use cases will exhibit different ratios of this
effect; some considerable, some not so much. Certainly the read performance
enhancements will be more generally applicable, but being able to fill your
memtables faster and with less garbage is also not a bad thing, even if you end
up bottlenecking on disk. Especially since server characteristics are changing
rapidly, so that disk bottlenecks are disappearing.
As optimisation work goes deeper, isolating the specific portion of work that
is affected is pretty essential to clearly delineating the benefit.
> Faster Memtable map
> -------------------
>
> Key: CASSANDRA-7282
> URL: https://issues.apache.org/jira/browse/CASSANDRA-7282
> Project: Cassandra
> Issue Type: Improvement
> Components: Core
> Reporter: Benedict
> Assignee: Benedict
> Labels: performance
> Fix For: 3.0
>
> Attachments: reads.svg, writes.svg
>
>
> Currently we maintain a ConcurrentSkipLastMap of DecoratedKey -> Partition in
> our memtables. Maintaining this is an O(lg(n)) operation; since the vast
> majority of users use a hash partitioner, it occurs to me we could maintain a
> hybrid ordered list / hash map. The list would impose the normal order on the
> collection, but a hash index would live alongside as part of the same data
> structure, simply mapping into the list and permitting O(1) lookups and
> inserts.
> I've chosen to implement this initial version as a linked-list node per item,
> but we can optimise this in future by storing fatter nodes that permit a
> cache-line's worth of hashes to be checked at once, further reducing the
> constant factor costs for lookups.
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