No,  This is the only Stack trace i get.  I have tried DEBUG but didn't
notice much of a log change.

Yes,  I have tried bumping MaxDirectMemorySize to get rid of this error.
It does work if i throw 4G+ memory at it.  However,  I am trying to
understand this behavior so that i can setup this number to appropriate
value.

Regards
Sumit Chawla


On Tue, Mar 6, 2018 at 8:07 AM, Vadim Semenov <va...@datadoghq.com> wrote:

> Do you have a trace? i.e. what's the source of `io.netty.*` calls?
>
> And have you tried bumping `-XX:MaxDirectMemorySize`?
>
> On Tue, Mar 6, 2018 at 12:45 AM, Chawla,Sumit <sumitkcha...@gmail.com>
> wrote:
>
>> Hi All
>>
>> I have a job which processes a large dataset.  All items in the dataset
>> are unrelated.  To save on cluster resources,  I process these items in
>> chunks.  Since chunks are independent of each other,  I start and shut down
>> the spark context for each chunk.  This allows me to keep DAG smaller and
>> not retry the entire DAG in case of failures.   This mechanism used to work
>> fine with Spark 1.6.  Now,  as we have moved to 2.2,  the job started
>> failing with OutOfDirectMemoryError error.
>>
>> 2018-03-03 22:00:59,687 WARN  [rpc-server-48-1]
>> server.TransportChannelHandler 
>> (TransportChannelHandler.java:exceptionCaught(78))
>> - Exception in connection from /10.66.73.27:60374
>>
>> io.netty.util.internal.OutOfDirectMemoryError: failed to allocate
>> 8388608 byte(s) of direct memory (used: 1023410176, max: 1029177344)
>>
>> at io.netty.util.internal.PlatformDependent.incrementMemoryCoun
>> ter(PlatformDependent.java:506)
>>
>> at io.netty.util.internal.PlatformDependent.allocateDirectNoCle
>> aner(PlatformDependent.java:460)
>>
>> at io.netty.buffer.PoolArena$DirectArena.allocateDirect(PoolAre
>> na.java:701)
>>
>> at io.netty.buffer.PoolArena$DirectArena.newChunk(PoolArena.java:690)
>>
>> at io.netty.buffer.PoolArena.allocateNormal(PoolArena.java:237)
>>
>> at io.netty.buffer.PoolArena.allocate(PoolArena.java:213)
>>
>> at io.netty.buffer.PoolArena.allocate(PoolArena.java:141)
>>
>> at io.netty.buffer.PooledByteBufAllocator.newDirectBuffer(Poole
>> dByteBufAllocator.java:271)
>>
>> at io.netty.buffer.AbstractByteBufAllocator.directBuffer(Abstra
>> ctByteBufAllocator.java:177)
>>
>> at io.netty.buffer.AbstractByteBufAllocator.directBuffer(Abstra
>> ctByteBufAllocator.java:168)
>>
>> at io.netty.buffer.AbstractByteBufAllocator.ioBuffer(AbstractBy
>> teBufAllocator.java:129)
>>
>> at io.netty.channel.AdaptiveRecvByteBufAllocator$HandleImpl.
>> allocate(AdaptiveRecvByteBufAllocator.java:104)
>>
>> at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.
>> read(AbstractNioByteChannel.java:117)
>>
>> at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEven
>> tLoop.java:564)
>>
>> I got some clue on what is causing this from https://github.com/netty/
>> netty/issues/6343,  However I am not able to add up numbers on what is
>> causing 1 GB of Direct Memory to fill up.
>>
>> Output from jmap
>>
>>
>> 7: 22230 1422720 io.netty.buffer.PoolSubpage
>>
>> 12: 1370 804640 io.netty.buffer.PoolSubpage[]
>>
>> 41: 3600 144000 io.netty.buffer.PoolChunkList
>>
>> 98: 1440 46080 io.netty.buffer.PoolThreadCache$SubPageMemoryRegionCache
>>
>> 113: 300 40800 io.netty.buffer.PoolArena$HeapArena
>>
>> 114: 300 40800 io.netty.buffer.PoolArena$DirectArena
>>
>> 192: 198 15840 io.netty.buffer.PoolChunk
>>
>> 274: 120 8320 io.netty.buffer.PoolThreadCache$MemoryRegionCache[]
>>
>> 406: 120 3840 io.netty.buffer.PoolThreadCache$NormalMemoryRegionCache
>>
>> 422: 72 3552 io.netty.buffer.PoolArena[]
>>
>> 458: 30 2640 io.netty.buffer.PooledUnsafeDirectByteBuf
>>
>> 500: 36 2016 io.netty.buffer.PooledByteBufAllocator
>>
>> 529: 32 1792 io.netty.buffer.UnpooledUnsafeHeapByteBuf
>>
>> 589: 20 1440 io.netty.buffer.PoolThreadCache
>>
>> 630: 37 1184 io.netty.buffer.EmptyByteBuf
>>
>> 703: 36 864 io.netty.buffer.PooledByteBufAllocator$PoolThreadLocalCache
>>
>> 852: 22 528 io.netty.buffer.AdvancedLeakAwareByteBuf
>>
>> 889: 10 480 io.netty.buffer.SlicedAbstractByteBuf
>>
>> 917: 8 448 io.netty.buffer.UnpooledHeapByteBuf
>>
>> 1018: 20 320 io.netty.buffer.PoolThreadCache$1
>>
>> 1305: 4 128 io.netty.buffer.PoolThreadCache$MemoryRegionCache$Entry
>>
>> 1404: 1 80 io.netty.buffer.PooledUnsafeHeapByteBuf
>>
>> 1473: 3 72 io.netty.buffer.PoolArena$SizeClass
>>
>> 1529: 1 64 io.netty.buffer.AdvancedLeakAwareCompositeByteBuf
>>
>> 1541: 2 64 io.netty.buffer.CompositeByteBuf$Component
>>
>> 1568: 1 56 io.netty.buffer.CompositeByteBuf
>>
>> 1896: 1 32 io.netty.buffer.PoolArena$SizeClass[]
>>
>> 2042: 1 24 io.netty.buffer.PooledUnsafeDirectByteBuf$1
>>
>> 2046: 1 24 io.netty.buffer.UnpooledByteBufAllocator
>>
>> 2051: 1 24 io.netty.buffer.PoolThreadCache$MemoryRegionCache$1
>>
>> 2078: 1 24 io.netty.buffer.PooledHeapByteBuf$1
>>
>> 2135: 1 24 io.netty.buffer.PooledUnsafeHeapByteBuf$1
>>
>> 2302: 1 16 io.netty.buffer.ByteBufUtil$1
>>
>> 2769: 1 16 io.netty.util.internal.__matchers__.io.netty.buffer.ByteBufM
>> atcher
>>
>>
>>
>> My Driver machine has 32 CPUs,  and as of now i have 15 machines in my
>> cluster.   As of now, the error happens on processing 5th or 6th chunk.  I
>> suspect the error is dependent on number of Executors and would happen
>> early if we add more executors.
>>
>>
>> I am trying to come up an explanation of what is filling up the Direct
>> Memory and how to quanitfy it as factor of Number of Executors.  Our
>> cluster is shared cluster,  And we need to understand how much Driver
>> Memory to allocate for most of the jobs.
>>
>>
>>
>>
>>
>> Regards
>> Sumit Chawla
>>
>>
>

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