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)

nabble.com | 4 months ago
  1. 0

    Apache Spark User List - distinct on huge dataset

    nabble.com | 4 months ago
    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)
  2. 0

    spark streaming loading multiple files or a directory in java

    tagwith.com | 1 year ago
    cluster.ClusterTaskSetManager: Loss was due to spark.SparkException: File ./someJar.jar exists and ... After reading some document on http://spark.apache.org/docs/0.8.0/cluster-overview.html, I got some question that I want to clarify. Take this example from Spark: JavaSparkContext spark = new ... I already have a cluster of 3 machines (ubuntu1,ubuntu2,ubuntu3 by VM virtualbox) running Hadoop 1.0.0. I installed spark on each of these machines. ub1 is my master node and the other nodes are ... How can we copy one spark TextArea to another spark textarea while keeping the formatting. I can retrieve the text but how i can keep the format. What I am trying achieve is I have two spark text ... When I run this code through Spark REPL : val sc = new SparkContext("local[4]" , "") val x = sc.parallelize(List( ("a" , "b" , 1) , ("a" , "b" , 1) , ("c" , "b" , 1) , ("a" , "d" , 1))) val ...
  3. 0

    Spark with Cassandra: Failed to register spark.kryo.registrator

    Google Groups | 3 years ago | Robin Chen
    cluster.ClusterTaskSetManager: Lost TID 0 (task 0.0:0) 13/10/28 12:12:36 INFO cluster.ClusterTaskSetManager: Loss was due to java.io.EOFException java.io.EOFException
  4. Speed up your debug routine!

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  5. 0

    pyspark memory usage

    Google Groups | 3 years ago | Евгений Шишкин
    cluster.ClusterTaskSetManager: Loss was due to org.apache.spark.SparkException org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
  6. 0

    HDFS, Hadoop 2.2 and Spark error

    Google Groups | 3 years ago | Richard Conway
    cluster.ClusterTaskSetManager: Lost TID 3 (task 0.0:1) 14/01/02 12:19:24 WARN cluster.ClusterTaskSetManager: Loss was due to java.lang. NoSuchMethodError java.lang.NoSuchMethodError: org.apache.commons.io.IOUtils.closeQuietly(Ljava/io /Closeable;)V at org.apache.hadoop.hdfs.DFSInputStream.getBlockReader(DFSInputStream.j ava:1052) at org.apache.hadoop.hdfs.DFSInputStream.blockSeekTo(DFSInputStream.java :533) at org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream .java:749)

    Root Cause Analysis

    1. 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()
    2. Java RT
      FileOutputStream.<init>
      1. java.io.FileOutputStream.openAppend(Native Method)
      2. java.io.FileOutputStream.<init>(FileOutputStream.java:192)
      2 frames
    3. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.storage.DiskBlockObjectWriter.open(BlockObjectWriter.scala:113)
      2. org.apache.spark.storage.DiskBlockObjectWriter.write(BlockObjectWriter.scala:174)
      3. org.apache.spark.util.collection.ExternalAppendOnlyMap.spill(ExternalAppendOnlyMap.scala:191)
      4. org.apache.spark.util.collection.ExternalAppendOnlyMap.insert(ExternalAppendOnlyMap.scala:141)
      5. org.apache.spark.Aggregator.combineValuesByKey(Aggregator.scala:59)
      6. org.apache.spark.rdd.PairRDDFunctions$$anonfun$1.apply(PairRDDFunctions.scala:95)
      7. org.apache.spark.rdd.PairRDDFunctions$$anonfun$1.apply(PairRDDFunctions.scala:94)
      8. org.apache.spark.rdd.RDD$$anonfun$3.apply(RDD.scala:471)
      9. org.apache.spark.rdd.RDD$$anonfun$3.apply(RDD.scala:471)
      10. org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:34)
      11. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:241)
      12. org.apache.spark.rdd.RDD.iterator(RDD.scala:232)
      13. org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:161)
      14. org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:102)
      15. org.apache.spark.scheduler.Task.run(Task.scala:53)
      16. org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:213)
      17. org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:49)
      18. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)
      18 frames
    4. Java RT
      Thread.run
      1. java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
      2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
      3. java.lang.Thread.run(Thread.java:662)
      3 frames