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From aaron morton <aa...@thelastpickle.com>
Subject Re: cassandra unexpected shutdown
Date Wed, 24 Aug 2011 09:38:25 GMT
First thing is are you on 0.8 ? It has some automagical memory management that is both automatic
and magical http://thelastpickle.com/2011/05/04/How-are-Memtables-measured/

Secondly if you are OOM'ing you need to look at how much memory your schema is taking. See
the link above, or just use 0.8

Thirdly, try to reduce the cache as Adi noted. 

Finally try to work out when it's OOM'ing. Is it during a compaction, a repair, during peak
load or just regular operations. With 1TB of data i'd be taking a look at the compaction or
repair processes to see whats happening GC wise. Also check the GC settings as described in
cassandra-env.sh

Hope that helps. 
 
-----------------
Aaron Morton
Freelance Cassandra Developer
@aaronmorton
http://www.thelastpickle.com

On 24/08/2011, at 12:38 PM, Ernst D Schoen-René wrote:

> Thanks,
>    We had already been running cassandra with a larger heap size, but it meant that java
took way too long between garbage collections.  The advice I'd found was to set the heap size
at the 8 we're running at.  It was ok for a while, but now some nodes crash.  It's definitely
our experience that adding more memory per node actually makes things worse eventually, as
java starts eating up too many resources for it to handle.
> 
> 
> On 8/23/11 5:28 PM, Adi wrote:
>> 2011/8/23 Ernst D Schoen-René<ernst@peoplebrowsr.com>:
>>> Hi,
>>>  I'm running a 16-node cassandra cluster, with a reasonably large amount of
>>> data per node (~1TB).  Nodes have 16G ram, but heap is set to 8G.
>>> 
>>> The nodes keep stopping with this output in the log.  Any ideas?
>>> 
>>> ERROR [Thread-85] 2011-08-23 21:00:38,723 AbstractCassandraDaemon.java (line
>>> 113) Fatal exception in thread Thread[Thread-85,5,main]
>>> java.lang.OutOfMemoryError: Java heap space
>>> ERROR [ReadStage:568] 2011-08-23 21:00:38,723 AbstractCassandraDaemon.java
>>> (line 113) Fatal exception in thread Thread[ReadStage:568,5,main]
>>> java.lang.OutOfMemoryError: Java heap space
>>>  INFO [HintedHandoff:1] 2011-08-23 21:00:38,720 HintedHandOffManager.java
>>> (line 320) Started hinted handoff for endpoint /10.28.0.184
>>>  INFO [GossipStage:2] 2011-08-23 21:00:50,751 Gossiper.java (line 606)
>>> InetAddress /10.29.20.67 is now UP
>>> ERROR [Thread-34] 2011-08-23 21:00:50,525 AbstractCassandraDaemon.java (line
>>> 113) Fatal exception in thread Thread[Thread-34,5,main]
>>> java.util.concurrent.RejectedExecutionException: ThreadPoolExecutor has shut
>>> down
>>>    at
>>> org.apache.cassandra.concurrent.DebuggableThreadPoolExecutor$1.rejectedExecution(DebuggableThreadPoolExecutor.java:73)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:767)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:658)
>>>    at
>>> org.apache.cassandra.net.MessagingService.receive(MessagingService.java:444)
>>>    at
>>> org.apache.cassandra.net.IncomingTcpConnection.run(IncomingTcpConnection.java:117)
>>> ERROR [Thread-36] 2011-08-23 21:00:50,518 AbstractCassandraDaemon.java (line
>>> 113) Fatal exception in thread Thread[Thread-36,5,main]
>>> java.util.concurrent.RejectedExecutionException: ThreadPoolExecutor has shut
>>> down
>>>    at
>>> org.apache.cassandra.concurrent.DebuggableThreadPoolExecutor$1.rejectedExecution(DebuggableThreadPoolExecutor.java:73)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:767)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:658)
>>>    at
>>> org.apache.cassandra.net.MessagingService.receive(MessagingService.java:444)
>>>    at
>>> org.apache.cassandra.net.IncomingTcpConnection.run(IncomingTcpConnection.java:117)
>>>  INFO [GossipTasks:1] 2011-08-23 21:00:50,466 Gossiper.java (line 620)
>>> InetAddress /10.29.20.67 is now dead.
>>>  INFO [HintedHandoff:1] 2011-08-23 21:00:50,751 HintedHandOffManager.java
>>> (line 376) Finished hinted handoff of 0 rows to endpoint /10.28.0.184
>>> ERROR [Thread-33] 2011-08-23 21:01:05,048 AbstractCassandraDaemon.java (line
>>> 113) Fatal exception in thread Thread[Thread-33,5,main]
>>> java.util.concurrent.RejectedExecutionException: ThreadPoolExecutor has shut
>>> down
>>>    at
>>> org.apache.cassandra.concurrent.DebuggableThreadPoolExecutor$1.rejectedExecution(DebuggableThreadPoolExecutor.java:73)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:767)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:658)
>>>    at
>>> org.apache.cassandra.net.MessagingService.receive(MessagingService.java:444)
>>>    at
>>> org.apache.cassandra.net.IncomingTcpConnection.run(IncomingTcpConnection.java:117)
>>> ERROR [Thread-128] 2011-08-23 21:01:05,048 AbstractCassandraDaemon.java
>>> (line 113) Fatal exception in thread Thread[Thread-128,5,main]
>>> java.util.concurrent.RejectedExecutionException: ThreadPoolExecutor has shut
>>> down
>>>    at
>>> org.apache.cassandra.concurrent.DebuggableThreadPoolExecutor$1.rejectedExecution(DebuggableThreadPoolExecutor.java:73)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:767)
>>>    at
>>> java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:658)
>>>    at
>>> org.apache.cassandra.net.MessagingService.receive(MessagingService.java:444)
>>>    at
>>> org.apache.cassandra.net.IncomingTcpConnection.run(IncomingTcpConnection.java:117)
>>> root@cass1:~#
>>> 
>>> 
>> 
>> You can try the  cargo cult solution of upping the heap to 12GB and
>> see if the nodes stabilize. We have a 4-node cluster with 2-3 TB data
>> per node and that was the heap at which it the nodes were managing to
>> serve requests without running out of memory. Ultimately we ordered
>> more memory and are running it with 24 GB heap and the cluster has
>> been stable without complains.
>> Other things you can do for reducing memory usage if they are
>> appropriate for your read/write profile:
>> a) reduce memtable throughput(most reduction in mem footprint)
>> b) disable row caching
>> c) reduce/disable key caching(least reduction)
>> Ultimately you will have to tune based on your
>> 1)  row sizes
>> 2) read/write load
>> 
>> -Adi
> 


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