`spark.worker.cleanup.enabled=true` doesn't work for YARN.
On Fri, Jul 27, 2018 at 8:52 AM dineshdharme <dineshdha...@gmail.com> wrote:
>
> I am trying to do few (union + reduceByKey) operations on a hiearchical
> dataset in a iterative fashion in rdd. The first few loops run fine but on
> the subsequent loops, the operations ends up using the whole scratch space
> provided to it.
>
> I have set the spark scratch directory, i.e. SPARK_LOCAL_DIRS , to be one
> having 100 GB space.
> The heirarchical dataset, whose size is (< 400kB), remains constant
> throughout the iterations.
> I have tried the worker cleanup flag but it has no effect i.e.
> "spark.worker.cleanup.enabled=true"
>
>
>
> Error :
> Caused by: java.io.IOException: No space left on device
> at java.io.FileOutputStream.writeBytes(Native Method)
> at java.io.FileOutputStream.write(FileOutputStream.java:326)
> at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
> at java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
> at java.io.DataOutputStream.writeLong(DataOutputStream.java:224)
> at
> org.apache.spark.shuffle.IndexShuffleBlockResolver$$anonfun$writeIndexFileAndCommit$1$$anonfun$apply$mcV$sp$1.apply$mcVJ$sp(IndexShuffleBlockResolver.scala:151)
> at
> org.apache.spark.shuffle.IndexShuffleBlockResolver$$anonfun$writeIndexFileAndCommit$1$$anonfun$apply$mcV$sp$1.apply(IndexShuffleBlockResolver.scala:149)
> at
> org.apache.spark.shuffle.IndexShuffleBlockResolver$$anonfun$writeIndexFileAndCommit$1$$anonfun$apply$mcV$sp$1.apply(IndexShuffleBlockResolver.scala:149)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofLong.foreach(ArrayOps.scala:246)
> at
> org.apache.spark.shuffle.IndexShuffleBlockResolver$$anonfun$writeIndexFileAndCommit$1.apply$mcV$sp(IndexShuffleBlockResolver.scala:149)
> at
> org.apache.spark.shuffle.IndexShuffleBlockResolver$$anonfun$writeIndexFileAndCommit$1.apply(IndexShuffleBlockResolver.scala:145)
> at
> org.apache.spark.shuffle.IndexShuffleBlockResolver$$anonfun$writeIndexFileAndCommit$1.apply(IndexShuffleBlockResolver.scala:145)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
> at
> org.apache.spark.shuffle.IndexShuffleBlockResolver.writeIndexFileAndCommit(IndexShuffleBlockResolver.scala:153)
> at
> org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:73)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> at org.apache.spark.scheduler.Task.run(Task.scala:109)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
>
>
> What I am trying to do (High Level):
>
> I have a dataset of 5 different csv ( Parent, Child1, Child2, Child21,
> Child22 ) which are related in a hierarchical fashion as shown below.
>
> Parent-> Child1 -> Child2  -> Child21
>
> Parent-> Child1 -> Child2  -> Child22
>
> Each element in the tree has 14 columns (elementid, parentelement_id, cat1,
> cat2, num1, num2,....., num10)
>
> I am trying to aggregate the values of one column of Child21 into Child1
> (i.e. 2 levels up). I am doing the same for another column value of Child22
> into Child1. Then I am merging these aggregated values at the same Child1
> level.
>
> This is present in the code at location :
>
> spark.rddexample.dummyrdd.tree.child1.events.Function1
>
>
> Code which replicates the issue:
>
> 1] https://github.com/dineshdharme/SparkRddShuffleIssue
>
>
>
> Steps to reproduce the issue :
>
> 1] Clone the above repository.
>
> 2] Put the csvs in the "issue-data" folder in the above repository at a
> hadoop location "hdfs:///tree/dummy/data/"
>
> 3] Set the spark scratch directory (SPARK_LOCAL_DIRS) to a folder which has
> large space. (> 100 GB)
>
> 4] Run "sbt assembly"
>
> 5] Run the following command at the project location
>
> /path/to/spark-2.3.0-bin-hadoop2.7/bin/spark-submit \
> --class spark.rddexample.dummyrdd.FunctionExecutor \
> --master local[2] \
> --deploy-mode client \
> --executor-memory 2G \
> --driver-memory 2G \
> target/scala-2.11/rdd-shuffle-assembly-0.1.0.jar \
> 20 \
> hdfs:///tree/dummy/data/ \
> hdfs:///tree/dummy/results/
>
>
>
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