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From sankalp kohli <kohlisank...@gmail.com>
Subject Re: Cassandra terminates with OutOfMemory (OOM) error
Date Tue, 25 Jun 2013 20:27:21 GMT
Your young gen is 1/4 of 1.8G which is 450MB. Also in slice queries, the
co-ordinator will get the results from replicas as per consistency level
used and merge the results before returning to the client.
What is the replication in your keyspace and what consistency you are
reading with.
Also 55MB on disk will not mean 55MB in memory. The data is compressed on
disk and also there are other overheads.



On Mon, Jun 24, 2013 at 8:38 PM, Mohammed Guller <mohammed@glassbeam.com>wrote:

>  No deletes. In my test, I am just writing and reading data.
>
>  There is a lot of GC, but only on the younger generation. Cassandra
> terminates before the GC for old generation kicks in.
>
>  I know that our queries are reading an unusual amount of data. However,
> I expected it to throw a timeout exception instead of crashing. Also, don't
> understand why 1.8 Gb heap is getting full when the total data stored in
> the entire Cassandra cluster is less than 55 MB.
>
> Mohammed
>
> On Jun 21, 2013, at 7:30 PM, "sankalp kohli" <kohlisankalp@gmail.com>
> wrote:
>
>   Looks like you are putting lot of pressure on the heap by doing a slice
> query on a large row.
> Do you have lot of deletes/tombstone on the rows? That might be causing a
> problem.
> Also why are you returning so many columns as once, you can use auto
> paginate feature in Astyanax.
>
>  Also do you see lot of GC happening?
>
>
> On Fri, Jun 21, 2013 at 1:13 PM, Jabbar Azam <ajazam@gmail.com> wrote:
>
>> Hello Mohammed,
>>
>>  You should increase the heap space. You should also tune the garbage
>> collection so young generation objects are collected faster, relieving
>> pressure on heap We have been using jdk 7 and it uses G1 as the default
>> collector. It does a better job than me trying to optimise the JDK 6 GC
>> collectors.
>>
>>  Bear in mind though that the OS will need memory, so will the row cache
>> and the filing system. Although memory usage will depend on the workload of
>> your system.
>>
>>  I'm sure you'll also get good advice from other members of the mailing
>> list.
>>
>>  Thanks
>>
>> Jabbar Azam
>>
>>
>> On 21 June 2013 18:49, Mohammed Guller <mohammed@glassbeam.com> wrote:
>>
>>>  We have a 3-node cassandra cluster on AWS. These nodes are running
>>> cassandra 1.2.2 and have 8GB memory. We didn't change any of the default
>>> heap or GC settings. So each node is allocating 1.8GB of heap space. The
>>> rows are wide; each row stores around 260,000 columns. We are reading the
>>> data using Astyanax. If our application tries to read 80,000 columns each
>>> from 10 or more rows at the same time, some of the nodes run out of heap
>>> space and terminate with OOM error. Here is the error message:****
>>>
>>> ** **
>>>
>>> java.lang.OutOfMemoryError: Java heap space****
>>>
>>>         at java.nio.HeapByteBuffer.duplicate(HeapByteBuffer.java:107)***
>>> *
>>>
>>>         at
>>> org.apache.cassandra.db.marshal.AbstractCompositeType.getBytes(AbstractCompositeType.java:50)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.marshal.AbstractCompositeType.getWithShortLength(AbstractCompositeType.java:60)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.marshal.AbstractCompositeType.split(AbstractCompositeType.java:126)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.filter.ColumnCounter$GroupByPrefix.count(ColumnCounter.java:96)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.filter.SliceQueryFilter.collectReducedColumns(SliceQueryFilter.java:164)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.filter.QueryFilter.collateColumns(QueryFilter.java:136)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.filter.QueryFilter.collateOnDiskAtom(QueryFilter.java:84)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.CollationController.collectAllData(CollationController.java:294)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.CollationController.getTopLevelColumns(CollationController.java:65)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.ColumnFamilyStore.getTopLevelColumns(ColumnFamilyStore.java:1363)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.ColumnFamilyStore.getColumnFamily(ColumnFamilyStore.java:1220)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.db.ColumnFamilyStore.getColumnFamily(ColumnFamilyStore.java:1132)
>>> ****
>>>
>>>         at org.apache.cassandra.db.Table.getRow(Table.java:355)****
>>>
>>>         at
>>> org.apache.cassandra.db.SliceFromReadCommand.getRow(SliceFromReadCommand.java:70)
>>> ****
>>>
>>>        at
>>> org.apache.cassandra.service.StorageProxy$LocalReadRunnable.runMayThrow(StorageProxy.java:1052)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.service.StorageProxy$DroppableRunnable.run(StorageProxy.java:1578)
>>> ****
>>>
>>>         at
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
>>> ****
>>>
>>>         at
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
>>> ****
>>>
>>>         at java.lang.Thread.run(Thread.java:722)****
>>>
>>> ** **
>>>
>>> ERROR 02:14:05,351 Exception in thread Thread[Thrift:6,5,main]****
>>>
>>> java.lang.OutOfMemoryError: Java heap space****
>>>
>>>         at java.lang.Long.toString(Long.java:269)****
>>>
>>>         at java.lang.Long.toString(Long.java:764)****
>>>
>>>         at
>>> org.apache.cassandra.dht.Murmur3Partitioner$1.toString(Murmur3Partitioner.java:171)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.service.StorageService.describeRing(StorageService.java:1068)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.thrift.CassandraServer.describe_ring(CassandraServer.java:1192)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.thrift.Cassandra$Processor$describe_ring.getResult(Cassandra.java:3766)
>>> ****
>>>
>>>         at
>>> org.apache.cassandra.thrift.Cassandra$Processor$describe_ring.getResult(Cassandra.java:3754)
>>> ****
>>>
>>>         at
>>> org.apache.thrift.ProcessFunction.process(ProcessFunction.java:32)****
>>>
>>>         at
>>> org.apache.thrift.TBaseProcessor.process(TBaseProcessor.java:34)****
>>>
>>>         at
>>> org.apache.cassandra.thrift.CustomTThreadPoolServer$WorkerProcess.run(CustomTThreadPoolServer.java:199)
>>> ****
>>>
>>>         at
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
>>> ****
>>>
>>>         at
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
>>> ****
>>>
>>>         at java.lang.Thread.run(Thread.java:722)****
>>>
>>> ** **
>>>
>>> The data in each column is less than 50 bytes. After adding all the
>>> column overheads (column name + metadata), it should not be more than 100
>>> bytes. So reading 80,000 columns from 10 rows each means that we are
>>> reading 80,000 * 10 * 100 = 80 MB of data. It is large, but not large
>>> enough to fill up the 1.8 GB heap. So I wonder why the heap is getting
>>> full. If the data request is too big to fill in a reasonable amount of
>>> time, I would expect Cassandra to return a TimeOutException instead of
>>> terminating. ****
>>>
>>> ** **
>>>
>>> One easy solution is to increase the heapsize. However that means
>>> Cassandra can still crash if someone reads 100 rows.  I wonder if there
>>> some other Cassandra setting that I can tweak to prevent the OOM exception?
>>> ****
>>>
>>> ** **
>>>
>>> Thanks,****
>>>
>>> Mohammed****
>>>
>>
>>
>

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