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From "Nikolai Grigoriev (JIRA)" <j...@apache.org>
Subject [jira] [Created] (CASSANDRA-7949) LCS compaction low performance, many pending compactions, nodes are almost idle
Date Tue, 16 Sep 2014 23:45:34 GMT
Nikolai Grigoriev created CASSANDRA-7949:
--------------------------------------------

             Summary: LCS compaction low performance, many pending compactions, nodes are
almost idle
                 Key: CASSANDRA-7949
                 URL: https://issues.apache.org/jira/browse/CASSANDRA-7949
             Project: Cassandra
          Issue Type: Bug
          Components: Core
         Environment: DSE 4.5.1-1, Cassandra 2.0.8
            Reporter: Nikolai Grigoriev


I've been evaluating new cluster of 15 nodes (32 core, 6x800Gb SSD disks + 2x600Gb SAS, 128Gb
RAM, OEL 6.5) and I've built a simulator that creates the load similar to the load in our
future product. Before running the simulator I had to pre-generate enough data. This was done
using Java code and DataStax Java driver. To avoid going deep into details, two tables have
been generated. Each table currently has about 55M rows and between few dozens and few thousands
of columns in each row.

This data generation process was generating massive amount of non-overlapping data. Thus,
the activity was write-only and highly parallel. This is not the type of the traffic that
the system will have ultimately to deal with, it will be mix of reads and updates to the existing
data in the future. This is just to explain the choice of LCS, not mentioning the expensive
SSD disk space.

At some point while generating the data I have noticed that the compactions started to pile
up. I knew that I was overloading the cluster but I still wanted the genration test to complete.
I was expecting to give the cluster enough time to finish the pending compactions and get
ready for real traffic.

However, after the storm of write requests have been stopped I have noticed that the number
of pending compactions remained constant (and even climbed up a little bit) on all nodes.
After trying to tune some parameters (like setting the compaction bandwidth cap to 0) I have
noticed a strange pattern: the nodes were compacting one of the CFs in a single stream using
virtually no CPU and no disk I/O. This process was taking hours. After that it would be followed
by a short burst of few dozens of compactions running in parallel (CPU at 2000%, some disk
I/O - up to 10-20%) and then getting stuck again for many hours doing one compaction at time.
So it looks like this:

# nodetool compactionstats
pending tasks: 3351
          compaction type        keyspace           table       completed           total
     unit  progress
               Compaction      myks     table_list1     66499295588   1910515889913     bytes
    3.48%
Active compaction remaining time :        n/a

# df -h

...
/dev/sdb        1.5T  637G  854G  43% /cassandra-data/disk1
/dev/sdc        1.5T  425G  1.1T  29% /cassandra-data/disk2
/dev/sdd        1.5T  429G  1.1T  29% /cassandra-data/disk3

# find . -name *wm_contacts*Data* | grep -v snapshot | wc -l
1310

Among these files I see:

1043 files of 161Mb (my sstable size is 160Mb)
9 large files - 3 between 1 and 2Gb, 3 of 5-8Gb, 55Gb, 70Gb and 370Gb
263 files of various sized - between few dozens of Kb and 160Mb

I've been running the heavy load for about 1,5days and it's been close to 3 days after that
and the number of pending compactions does not go down.

I have applied one of the not-so-obvious recommendations to disable multithreaded compactions
and that seems to be helping a bit - I see some nodes started to have fewer pending compactions.
About half of the cluster, in fact. But even there I see they are sitting idle most of the
time lazily compacting in one stream with CPU at ~140% and occasionally doing the bursts of
compaction work for few minutes.

I am wondering if this is really a bug or something in the LCS logic that would manifest itself
only in such an edge case scenario where I have loaded lots of unique data quickly.

I'll be attaching the relevant logs shortly.




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