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From Schubert Zhang <zson...@gmail.com>
Subject Re: Cassandra cluster runs into OOM when bulk loading data
Date Tue, 27 Apr 2010 15:58:12 GMT
Seems:
ROW-MUTATION-STAGE   32      3349       63897493
is the clue, too many mutation requests are pending.


Yes, I also think cassandra should add a mechanism to avoid too many
requests pending (in queue).
When the queue is full, just reject the request from client.

Seems https://issues.apache.org/jira/browse/CASSANDRA-685 is what we want.



On Tue, Apr 27, 2010 at 8:16 PM, Eric Yu <sucode@gmail.com> wrote:

> I wrote a script to record the tpstats output every 5 seconds.
> Here is the output just before the jvm OOM:
>
>
> Pool Name                    Active   Pending      Completed
> FILEUTILS-DELETE-POOL             0         0            280
>
> STREAM-STAGE                      0         0              0
> RESPONSE-STAGE                    0         0         245573
>
> ROW-READ-STAGE                    0         0              0
> LB-OPERATIONS                     0         0              0
> MESSAGE-DESERIALIZER-POOL         1  14290091       65943291
> GMFD                              0         0          26670
>
> LB-TARGET                         0         0              0
> CONSISTENCY-MANAGER               0         0              0
> ROW-MUTATION-STAGE               32      3349       63897493
>
> MESSAGE-STREAMING-POOL            0         0              3
> LOAD-BALANCER-STAGE               0         0              0
> FLUSH-SORTER-POOL                 0         0              0
> MEMTABLE-POST-FLUSHER             0         0            420
> FLUSH-WRITER-POOL                 0         0            420
>
> AE-SERVICE-STAGE                  1         1              4
> HINTED-HANDOFF-POOL               0         0             52
>
>
> On Tue, Apr 27, 2010 at 10:53 AM, Chris Goffinet <goffinet@digg.com>wrote:
>
>> I'll work on doing more tests around this. In 0.5 we used a different data
>> structure that required polling. But this does seem problematic.
>>
>>  -Chris
>>
>> On Apr 26, 2010, at 7:04 PM, Eric Yu wrote:
>>
>> I have the same problem here, and I analysised the hprof file with mat, as
>> you said, LinkedBlockQueue used 2.6GB.
>> I think the ThreadPool of cassandra should limit the queue size.
>>
>> cassandra 0.6.1
>>
>> java version
>> $ java -version
>> java version "1.6.0_20"
>> Java(TM) SE Runtime Environment (build 1.6.0_20-b02)
>> Java HotSpot(TM) 64-Bit Server VM (build 16.3-b01, mixed mode)
>>
>> iostat
>> $ iostat -x -l 1
>> Device:         rrqm/s   wrqm/s   r/s   w/s    rkB/s    wkB/s avgrq-sz
>> avgqu-sz   await  svctm  %util
>> sda              81.00  8175.00 224.00 17.00 23984.00  2728.00
>> 221.68     1.01    1.86   0.76  18.20
>>
>> tpstats, of coz, this node is still alive
>> $ ./nodetool -host localhost tpstats
>> Pool Name                    Active   Pending      Completed
>> FILEUTILS-DELETE-POOL             0         0           1281
>> STREAM-STAGE                      0         0              0
>> RESPONSE-STAGE                    0         0      473617241
>> ROW-READ-STAGE                    0         0              0
>> LB-OPERATIONS                     0         0              0
>> MESSAGE-DESERIALIZER-POOL         0         0      718355184
>> GMFD                              0         0         132509
>> LB-TARGET                         0         0              0
>> CONSISTENCY-MANAGER               0         0              0
>> ROW-MUTATION-STAGE                0         0      293735704
>> MESSAGE-STREAMING-POOL            0         0              6
>> LOAD-BALANCER-STAGE               0         0              0
>> FLUSH-SORTER-POOL                 0         0              0
>> MEMTABLE-POST-FLUSHER             0         0           1870
>> FLUSH-WRITER-POOL                 0         0           1870
>> AE-SERVICE-STAGE                  0         0              5
>> HINTED-HANDOFF-POOL               0         0             21
>>
>>
>> On Tue, Apr 27, 2010 at 3:32 AM, Chris Goffinet <goffinet@digg.com>wrote:
>>
>>> 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... ;-)
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>>
>

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