Cameron Zemek created CASSANDRA-18773:
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Summary: Compactions are slow
Key: CASSANDRA-18773
URL: https://issues.apache.org/jira/browse/CASSANDRA-18773
Project: Cassandra
Issue Type: Improvement
Reporter: Cameron Zemek
Attachments: stress.yaml
I have noticed that compactions involving a lot of sstables are very slow (for
example major compactions). I have attached a cassandra stress profile that can
generate such a dataset under ccm. In my local test I have 2567 sstables at 4Mb
each.
I added code to track wall clock time of various parts of the code. One
problematic part is ManyToOne constructor. Tracing through the code for every
partition creating a ManyToOne for all the sstable iterators for each
partition. In my local test get a measy 60Kb/sec read speed, and bottlenecked
on single core CPU (since this code is single threaded) with it spending 85% of
the wall clock time in ManyToOne constructor.
As another datapoint to show its the merge iterator part of the code using the
cfstats from [https://github.com/instaclustr/cassandra-sstable-tools/] which
reads all the sstables but does no merging gets 26Mb/sec read speed.
Tracking back from ManyToOne call I see this in
UnfilteredPartitionIterators::merge
{code:java}
for (int i = 0; i < toMerge.size(); i++)
{
if (toMerge.get(i) == null)
{
if (null == empty)
empty = EmptyIterators.unfilteredRow(metadata,
partitionKey, isReverseOrder);
toMerge.set(i, empty);
}
}
{code}
Not sure what purpose of creating these empty rows are. But on a whim I removed
all these empty iterators before passing to ManyToOne and then all the wall
clock time shifted to CompactionIterator::hasNext() and read speed increased to
1.5Mb/s.
So there are further bottlenecks in this code path it seems, but the first is
this ManyToOne and having to build it for every partition read.
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