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via nabble.com by Unknown author, 1 year ago
worker. >> >> >> On Mon, Mar 24, 2014 at 1:39 AM, Kane < > wrote: Got a bit further, i think out of memory error was caused by setting spark.spill to false. Now i have this error, is there an easy way to increase file limit for spark, cluster-wide?: java.io.FileNotFoundException: /tmp/spark-local-20140324074221-b8f1/01/temp_1ab674f9-4556-4239-9f21-688dfc9f17d2 (Too many open files)
cluster.ClusterTaskSetManager: Loss was due to
> java.io.FileNotFoundException
> java.io.FileNotFoundException:
> /tmp/spark-local-20140417145643-a055/3c/shuffle_1_218_1157 (Too many
> open files)
>
> ulimit -n tells me I can open 32000 files. Here's a plot of lsof on a
> worker node during a failed .distinct():
> http://i.imgur.com/wyBHmzz.png , you can see tasks fail when Spark
> tries to open 32000 files.
>
> I never ran into this in 0.7.3. Is there a parameter I can set to tell
> Spark to use less than 32000 files?
>
> On Mon, Mar 24, 2014 at 10:23 AM, Aaron Davidson <
> wrote:
>> Look up setting ulimit, though note the distinction between soft and hard
>> limits, and that updating your hard limit may require changing
>> /etc/security/limits.confand restarting each worker.
>>
>>
>> On Mon, Mar 24, 2014 at 1:39 AM, Kane <
> wrote:
 Got a bit further, i think out of memory error was caused by setting
 spark.spill to false. Now i have this error, is there an easy way to
 increase file limit for spark, cluster-wide?:
 java.io.FileNotFoundException:
 /tmp/spark-local-20140324074221-b8f1/01/temp_1ab674f9-4556-4239-9f21-688dfc9f17d2
 (Too many open files)	at java.io.FileOutputStream.openAppend(Native Method)	at java.io.FileOutputStream.(FileOutputStream.java:192)	at org.apache.spark.storage.DiskBlockObjectWriter.open(BlockObjectWriter.scala:113)	at org.apache.spark.storage.DiskBlockObjectWriter.write(BlockObjectWriter.scala:174)	at org.apache.spark.util.collection.ExternalAppendOnlyMap.spill(ExternalAppendOnlyMap.scala:191)	at org.apache.spark.util.collection.ExternalAppendOnlyMap.insert(ExternalAppendOnlyMap.scala:141)	at org.apache.spark.Aggregator.combineValuesByKey(Aggregator.scala:59)	at org.apache.spark.rdd.PairRDDFunctions$$anonfun$1.apply(PairRDDFunctions.scala:95)	at org.apache.spark.rdd.PairRDDFunctions$$anonfun$1.apply(PairRDDFunctions.scala:94)	at org.apache.spark.rdd.RDD$$anonfun$3.apply(RDD.scala:471)	at org.apache.spark.rdd.RDD$$anonfun$3.apply(RDD.scala:471)	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:34)	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:241)	at org.apache.spark.rdd.RDD.iterator(RDD.scala:232)	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:161)	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:102)	at org.apache.spark.scheduler.Task.run(Task.scala:53)	at org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:213)	at org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:49)	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)	at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)	at java.lang.Thread.run(Thread.java:662)