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From "Steinmaurer, Thomas" <thomas.steinmau...@dynatrace.com>
Subject Repair of 5GB data vs. disk throughput does not make sense
Date Thu, 26 Apr 2018 12:02:19 GMT
Hello,

yet another question/issue with repair.

Cassandra 2.1.18, 3 nodes, RF=3, vnode=256, data volume ~ 5G per node only. A repair (nodetool
repair -par) issued on a single node at this data volume takes around 36min with an AVG of
~ 15MByte/s disk throughput (read+write) for the entire time-frame, thus processing ~ 32GByte
from a disk perspective so ~ 6 times of the real data volume reported by nodetool status.
Does this make any sense? This is with 4 compaction threads and compaction throughput = 64.
Similar results doing this test a few times, where most/all inconsistent data should be already
sorted out by previous runs.

I know there is e.g. reaper, but the above is a simple use case simply after a single failed
node recovers beyond the 3h hinted handoff window. How should this finish in a timely manner
for > 500G on a recovering node?

I have to admit this is with NFS as storage. I know, NFS might not be the best idea, but with
the above test at ~ 5GB data volume, we see an IOPS rate at ~ 700 at a disk latency of ~ 15ms,
thus I wouldn't treat it as that bad. This all is using/running Cassandra on-premise (at the
customer, so not hosted by us), so while we can make recommendations storage-wise (of course
preferring local disks), it may and will happen that NFS is being in use then.

Why we are using -par in combination with NFS is a different story and related to this issue:
https://issues.apache.org/jira/browse/CASSANDRA-8743. Without switching from sequential to
parallel repair, we basically kill Cassandra.

Throughput-wise, I also don't think it is related to NFS, cause we see similar repair throughput
values with AWS EBS (gp2, SSD based) running regular repairs on small-sized CFs.

Thanks for any input.
Thomas
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