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From Roland Hänel <>
Subject Re: Cassandra cluster runs into OOM when bulk loading data
Date Mon, 26 Apr 2010 19:30:27 GMT
Cassandra Version 0.6.1
OpenJDK Server VM (build 14.0-b16, mixed mode)
Import speed is about 10MB/s for the full cluster; if a compaction is going
on the individual node is I/O limited
tpstats: caught me, didn't know this. I will set up a test and try to catch
a node during the critical time.


2010/4/26 Chris Goffinet <>

> Which version of Cassandra?
> Which version of Java JVM are you using?
> What do your I/O stats look like when bulk importing?
> When you run `nodeprobe -host XXXX tpstats` is any thread pool backing up
> during the import?
> -Chris
> 2010/4/26 Roland Hänel <>
> I have a cluster of 5 machines building a Cassandra datastore, and I load
>> bulk data into this using the Java Thrift API. The first ~250GB runs fine,
>> then, one of the nodes starts to throw OutOfMemory exceptions. I'm not using
>> and row or index caches, and since I only have 5 CF's and some 2,5 GB of RAM
>> allocated to the JVM (-Xmx2500M), in theory, that should happen. All inserts
>> are done with consistency level ALL.
>> I hope with this I have avoided all the 'usual dummy errors' that lead to
>> OOM's. I have begun to troubleshoot the issue with JMX, however, it's
>> difficult to catch the JVM in the right moment because it runs well for
>> several hours before this thing happens.
>> One thing gets to my mind, maybe one of the experts could confirm or
>> reject this idea for me: is it possible that when one machine slows down a
>> little bit (for example because a big compaction is going on), the memtables
>> don't get flushed to disk as fast as they are building up under the
>> continuing bulk import? That would result in a downward spiral, the system
>> gets slower and slower on disk I/O, but since more and more data arrives
>> over Thrift, finally OOM.
>> I'm using the "periodic" commit log sync, maybe also this could create a
>> situation where the commit log writer is too slow to catch up with the data
>> intake, resulting in ever growing memory usage?
>> Maybe these thoughts are just bullshit. Let me now if so... ;-)

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