bottom line increase executor's non-mem-block memory and reduce indivdiual
starting task size until it all fits.
On Tue, Feb 16, 2016 at 4:09 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote:
> the original exception definitely happens in the task when mahout tries to
> build an entire matrix block out of a partition. Use more tasks, smaller in
> size initially. using par(min=??) will help to repartition to at least ??
> tasks. off-hdfs defaults are just too big for matrix processing. Not sure
> how to do that with command line utility, Pat may help.
>
> On Tue, Feb 16, 2016 at 9:59 AM, Jaume Galí <jg...@konodrac.com> wrote:
>
>> Hi,
>>
>> I did all you suggest but i couldn’t solve the problem yet and i don’t
>> know what else to do.
>>
>> Now I have a machine with 64Gb of Memory Ram, so physical memory should
>> not be a problem any more.
>> I attach input matrix if anybody could try to execute the command it
>> would be great.
>>
>> This is what I tried:
>>
>> - I used this command as Angelo suggested:
>>
>> /opt/mahout/bin/mahout spark-rowsimilarity -i matrix_country_115k.dat -o
>> test_country_115k_output.tmp --maxObservations 500 --maxSimilaritiesPerRow
>> 100 --omitStrength --master local --sparkExecutorMem 10g
>> -D:spark.dynamicAllocation.enabled=true
>> -D:spark.shuffle.service.enabled=true
>>
>> - I increased *MAHOUT_HEAPSIZE *up to 32Gb in two ways:
>>
>>
>> + Mahout script (MAHOUT_HOME/bin/mahout):
>>
>> JAVA=$JAVA_HOME/bin/java
>>
>> JAVA_HEAP_MAX=-Xmx4g
>>
>> MAHOUT_HEAPSIZE=32768
>>
>>
>> + ~/.profile setting environment variables:
>>
>> #Global conf JAVA
>> export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd64
>> export JAVA_OPTS=-Xmx32g
>> export _JAVA_OPTIONS=-Xmx32g
>> export HADOOP_PREFIX=/opt/hadoop
>> export SPARK_HOME=/opt/spark
>> export MAHOUT_HOME=/opt/mahout
>> export MAHOUT_HEAPSIZE=32g
>>
>>
>> I printed trace of memoery following mahout script and this is output:
>>
>> run with heapsize 32768
>>
>> -Xmx32768m
>>
>> So mahout is reading memory parameters fine.
>>
>>
>> I’m glad if you people could guide me about what parameters I have to
>> tune or check in order to solved this issue because I don’t know to do
>>
>> Thank you for advance.
>> Jaume.
>>
>>
>>
>> El 13/2/2016, a las 22:56, Pat Ferrel <p...@occamsmachete.com> escribió:
>>
>> OK, this makes sense. When people see Out of Memory problems they
>> naturally try to give more to the process throwing the exception but what
>> is often happening is that you have given too much to the collection of
>> other processes on the machine so there is not enough to go around and the
>> allocation fails on Spark. In which case you need to allocate less to Spark
>> so you can guarantee it will always be able to get that much.
>>
>>
>> On Feb 13, 2016, at 9:30 AM, Angelo Leto <angl...@gmail.com> wrote:
>>
>> I was able to make it working by setting the executor memory to 10g
>> and with -D:spark.dynamicAllocation.enabled=true :
>>
>> mahout spark-rowsimilarity --input hdfs:/indata/row-similarity.tsv
>> --output rowsim-out --omitStrength --sparkExecutorMem 10g --master
>> yarn-client -D:spark.dynamicAllocation.enabled=true
>> -D:spark.shuffle.service.enabled=true
>>
>>
>> On Sat, Feb 13, 2016 at 2:42 PM, Angelo Leto <angl...@gmail.com> wrote:
>>
>> Hello,
>> I have the same problem described above using spark-rowsimilarity.
>> I have a ~65k lines input file (each row with less than 300 items),
>> and I run the job on a small cluster with 1 master and 2 workers, each
>> machine has 15GB of RAM.
>> I tried to increase executor and driver memory:
>> --sparkExecutorMem 15g
>> -D:spark.driver.memory=15g
>>
>> but I get the OutOfMemoryError exception:
>>
>> 16/02/13 13:00:36 ERROR Executor: Exception in task 0.0 in stage 12.0
>> (TID 12)
>> java.lang.OutOfMemoryError: GC overhead limit exceeded
>> at
>> org.apache.mahout.math.OrderedIntDoubleMapping.growTo(OrderedIntDoubleMapping.java:86)
>> at
>> org.apache.mahout.math.OrderedIntDoubleMapping.set(OrderedIntDoubleMapping.java:118)
>> [...]
>>
>> Thanks for any hint.
>> Angelo
>>
>> On Fri, Feb 12, 2016 at 10:15 PM, Pat Ferrel <p...@occamsmachete.com>
>> wrote:
>>
>> You have to set the executor memory. BTW you have given the driver all
>> memory on the machine.
>>
>> On Feb 10, 2016, at 9:30 AM, Jaume Galí <jg...@konodrac.com> wrote:
>>
>> Hi again,
>> (Sorry for my delay but we didn’t have machine to test your thoughts
>> about memory issue.)
>>
>> The problem still happening testing with an input matrix of 100k rows by
>> 300 items, I increase memory as you suggest but nothing changed. I attached
>> spark_env.sh and new specs of machine
>>
>> Machine specs:
>>
>> m3.xlarge AWS (Ivy Bridge, 15Gb ram, 2x40gb HD)
>>
>> This is my spark-env.sh:
>>
>> #!/usr/bin/env bash
>> # Licensed to ...
>>
>> export SPARK_HOME=${SPARK_HOME:-/usr/lib/spark}
>> export SPARK_LOG_DIR=${SPARK_LOG_DIR:-/var/log/spark}
>> export HADOOP_HOME=${HADOOP_HOME:-/usr/lib/hadoop}
>> export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-/etc/hadoop/conf}
>> export HIVE_CONF_DIR=${HIVE_CONF_DIR:-/etc/hive/conf}
>>
>> export STANDALONE_SPARK_MASTER_HOST=ip-10-12-17-235.eu <
>> http://ip-10-12-17-235.eu/>-west-1.compute.internal
>> export SPARK_MASTER_PORT=7077
>> export SPARK_MASTER_IP=$STANDALONE_SPARK_MASTER_HOST
>> export SPARK_MASTER_WEBUI_PORT=8080
>>
>> export SPARK_WORKER_DIR=${SPARK_WORKER_DIR:-/var/run/spark/work}
>> export SPARK_WORKER_PORT=7078
>> export SPARK_WORKER_WEBUI_PORT=8081
>>
>> export HIVE_SERVER2_THRIFT_BIND_HOST=0.0.0.0
>> export HIVE_SERVER2_THRIFT_PORT=10001
>>
>> export SPARK_DRIVER_MEMORY=15G
>> export SPARK_DAEMON_JAVA_OPTS="$SPARK_DAEMON_JAVA_OPTS
>> -XX:OnOutOfMemoryError='kill -9 %p’”
>>
>> Log:
>>
>> Exception in thread "main" org.apache.spark.SparkException: Job aborted
>> due to stage failure: Task 0 in stage 12.0 failed 1 times, most recent
>> failure: Lost task 0.0 in stage 12.0 (TID 24, localhost):
>> java.lang.OutOfMemoryError: GC overhead limit exceeded
>> …….
>> …..
>> ..
>> .
>>
>> Driver stacktrace:
>> Caused by: java.lang.OutOfMemoryError: GC overhead limit exceeded
>> …….
>> …..
>> ...
>> ..
>> .
>>
>>
>> Thanks for advance
>>
>> El 2/2/2016, a las 7:48, Pat Ferrel <p...@occamsmachete.com <
>> mailto:p...@occamsmachete.com <p...@occamsmachete.com>>> escribió:
>>
>> You probably need to increase your driver memory and 8g will not work.
>> 16g is probably the smallest stand alone machine that will work since the
>> driver and executors run on it.
>>
>> On Feb 1, 2016, at 1:24 AM, jg...@konodrac.com <mailto:jg...@konodrac.com
>> <jg...@konodrac.com>> wrote:
>>
>> Hello everybody,
>>
>> We are experimenting problems when we use "mahout spark-rowsimilarity”
>> operation. We have an input matrix with 100k rows and 100 items and process
>> throws an exception about “Exception in task 0.0 in stage 13.0 (TID 13)
>> java.lang.OutOfMemoryError: Java heap space” and we try to increase JAVA
>> HEAP MEMORY, MAHOUT HEAP MEMORY and spark.driver.memory.
>>
>> Environment versions:
>> Mahout: 0.11.1
>> Spark: 1.6.0.
>>
>> Mahout command line:
>> /opt/mahout/bin/mahout spark-rowsimilarity -i 50k_rows__50items.dat -o
>> test_output.tmp --maxObservations 500 --maxSimilaritiesPerRow 100
>> --omitStrength --master local --sparkExecutorMem 8g
>>
>> This process is running on a machine with following specifications:
>> Mem RAM: 8gb
>> CPU with 8 cores
>>
>> .profile file:
>> export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd64
>> export HADOOP_HOME=/opt/hadoop-2.6.0
>> export SPARK_HOME=/opt/spark
>> export MAHOUT_HOME=/opt/mahout
>>
>> export MAHOUT_HEAPSIZE=8192
>>
>> Throws exception:
>>
>> 16/01/22 11:45:06 ERROR Executor: Exception in task 0.0 in stage 13.0
>> (TID 13)
>> java.lang.OutOfMemoryError: Java heap space
>> at org.apache.mahout.math.DenseMatrix.<init>(DenseMatrix.java:66)
>> at
>> org.apache.mahout.sparkbindings.drm.package$$anonfun$blockify$1.apply(package.scala:70)
>> at
>> org.apache.mahout.sparkbindings.drm.package$$anonfun$blockify$1.apply(package.scala:59)
>> at
>> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
>> at
>> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>> at org.apache.spark.scheduler.Task.run(Task.scala:89)
>> at
>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>> 16/01/22 11:45:06 WARN NettyRpcEndpointRef: Error sending message
>> [message = Heartbeat(driver,[Lscala.Tuple2;@12498227,BlockManagerId(driver,
>> localhost, 42107))] in 1 attempts
>> org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [120
>> seconds]. This timeout is controlled by spark.rpc.askTimeout
>> at org.apache.spark.rpc.RpcTimeout.org
>> $apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48)
>> at
>> org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63)
>> at
>> org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
>> at
>> scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
>> at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
>> at
>> org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:101)
>> at
>> org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:77)
>> at org.apache.spark.executor.Executor.org
>> $apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:448)
>> at
>> org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply$mcV$sp(Executor.scala:468)
>> at
>> org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:468)
>> at
>> org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:468)
>> at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1741)
>> at org.apache.spark.executor.Executor$$anon$1.run(Executor.scala:468)
>> at
>> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
>> at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:304)
>> at
>> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178)
>> at
>> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>> 16/01/22 11:45:06 WARN NettyRpcEndpointRef: Error sending message
>> [message = Heartbeat(driver,[Lscala.Tuple2;@12498227,BlockManagerId(driver,
>> localhost, 42107))] in 1 attempts
>> org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [120
>> seconds]. This timeout is controlled by spark.rpc.askTimeout
>> at org.apache.spark.rpc.RpcTimeout.org
>> $apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48)
>> at
>> org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63)
>> at
>> org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
>> at
>> scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
>> at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
>> at
>> org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:101)
>> at
>> org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:77)
>> at org.apache.spark.executor.Executor.org
>> $apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:448)
>> at
>> org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply$mcV$sp(Executor.scala:468)
>> at
>> org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:468)
>> at
>> org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:468)
>> at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1741)
>> at org.apache.spark.executor.Executor$$anon$1.run(Executor.scala:468)
>> at
>> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
>> at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:304)
>> at
>> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178)
>> at
>> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>> Caused by: java.util.concurrent.TimeoutException: Futures timed out after
>> [120 seconds]
>> at
>> scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219)
>> at
>> scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
>> at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107)
>> at
>> scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
>> at scala.concurrent.Await$.result(package.scala:107)
>> at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
>> ...
>>
>> Can you please advise?
>>
>>
>> Thanks for advance.
>> Cheers.
>>
>>
>>
>>
>>
>>
>>
>>
>
