Brokers failed repeatedly leaving behind page-cache in memory, which caused 
broker restarts to fail with OOM every time.
After manually cleaning up page-cache, I was able to restart the broker. 
However, still wondering what could have caused this state in the first place.  

Any ideas?


-Zakee

> On Dec 14, 2016, at 12:03 PM, Zakee <kzak...@netzero.net> wrote:
> 
> Recently, we have seen our brokers crash with below errors, any idea what 
> might be wrong here?  The brokers have been running for long with the same 
> hosts/configs without this issue before. Is this something to do with new 
> version 0.10.0.1 (which we upgraded recently) or could it be a h/w issue?  10 
> hosts are dedicated for one broker per host. Each host has 128 gb RAM and 
> 20TB of storage mounts. Any pointers will help...
> 
> 
> [2016-12-12 02:49:58,134] FATAL [app=broker] [ReplicaFetcherThread-15-15] 
> [ReplicaFetcherThread-15-15], Disk error while replicating data for 
> mytopic-19 (kafka.server.ReplicaFetcherThread)
> kafka.common.KafkaStorageException: I/O exception in append to log ’ 
> mytopic-19'
>       at kafka.log.Log.append(Log.scala:349)
>       at 
> kafka.server.ReplicaFetcherThread.processPartitionData(ReplicaFetcherThread.scala:130)
>       at 
> kafka.server.ReplicaFetcherThread.processPartitionData(ReplicaFetcherThread.scala:42)
>       at 
> kafka.server.AbstractFetcherThread$$anonfun$processFetchRequest$2$$anonfun$apply$mcV$sp$1$$anonfun$apply$2.apply(AbstractFetcherThread.scala:159)
>       at 
> kafka.server.AbstractFetcherThread$$anonfun$processFetchRequest$2$$anonfun$apply$mcV$sp$1$$anonfun$apply$2.apply(AbstractFetcherThread.scala:141)
>       at scala.Option.foreach(Option.scala:257)
>       at 
> kafka.server.AbstractFetcherThread$$anonfun$processFetchRequest$2$$anonfun$apply$mcV$sp$1.apply(AbstractFetcherThread.scala:141)
>       at 
> kafka.server.AbstractFetcherThread$$anonfun$processFetchRequest$2$$anonfun$apply$mcV$sp$1.apply(AbstractFetcherThread.scala:138)
>       at 
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>       at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
>       at 
> kafka.server.AbstractFetcherThread$$anonfun$processFetchRequest$2.apply$mcV$sp(AbstractFetcherThread.scala:138)
>       at 
> kafka.server.AbstractFetcherThread$$anonfun$processFetchRequest$2.apply(AbstractFetcherThread.scala:138)
>       at 
> kafka.server.AbstractFetcherThread$$anonfun$processFetchRequest$2.apply(AbstractFetcherThread.scala:138)
>       at kafka.utils.CoreUtils$.inLock(CoreUtils.scala:234)
>       at 
> kafka.server.AbstractFetcherThread.processFetchRequest(AbstractFetcherThread.scala:136)
>       at 
> kafka.server.AbstractFetcherThread.doWork(AbstractFetcherThread.scala:103)
>       at kafka.utils.ShutdownableThread.run(ShutdownableThread.scala:63)
> Caused by: java.io.IOException: Map failed
>       at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:907)
>       at 
> kafka.log.AbstractIndex$$anonfun$resize$1.apply(AbstractIndex.scala:116)
>       at 
> kafka.log.AbstractIndex$$anonfun$resize$1.apply(AbstractIndex.scala:106)
>       at kafka.utils.CoreUtils$.inLock(CoreUtils.scala:234)
>       at kafka.log.AbstractIndex.resize(AbstractIndex.scala:106)
>       at 
> kafka.log.AbstractIndex$$anonfun$trimToValidSize$1.apply$mcV$sp(AbstractIndex.scala:160)
>       at 
> kafka.log.AbstractIndex$$anonfun$trimToValidSize$1.apply(AbstractIndex.scala:160)
>       at 
> kafka.log.AbstractIndex$$anonfun$trimToValidSize$1.apply(AbstractIndex.scala:160)
>       at kafka.utils.CoreUtils$.inLock(CoreUtils.scala:234)
>       at kafka.log.AbstractIndex.trimToValidSize(AbstractIndex.scala:159)
>       at kafka.log.Log.roll(Log.scala:772)
>       at kafka.log.Log.maybeRoll(Log.scala:742)
>       at kafka.log.Log.append(Log.scala:405)
>       ... 16 more
> Caused by: java.lang.OutOfMemoryError: Map failed
>       at sun.nio.ch.FileChannelImpl.map0(Native Method)
>       at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:904)
>       ... 28 more
> 
> 
> Thanks
> -Zakee

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