cassandra-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Roland Hänel <rol...@haenel.me>
Subject Re: Cassandra cluster runs into OOM when bulk loading data
Date Mon, 26 Apr 2010 19:43:34 GMT
Thanks Chris

2010/4/26 Chris Goffinet <goffinet@digg.com>

> Upgrade to b20 of Sun's version of JVM. This OOM might be related to
> LinkedBlockQueue issues that were fixed.
>
> -Chris
>
>
> 2010/4/26 Roland Hänel <roland@haenel.me>
>
>> 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.
>>
>> Thanks,
>> Roland
>>
>>
>> 2010/4/26 Chris Goffinet <goffinet@digg.com>
>>
>>  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 <roland@haenel.me>
>>>
>>> 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... ;-)
>>>>
>>>>
>>>>
>>>
>>
>

Mime
View raw message