I have added:
SparkConf conf = new
SparkConf().setAppName("app").setExecutorEnv("spark.executor.memory", "8g")
.setMaster("spark://10.0.100.120:7077");
but it did not change a thing
> On Jul 13, 2016, at 9:14 PM, Jean Georges Perrin <j...@jgp.net> wrote:
>
> Hi,
>
> I have a Java memory issue with Spark. The same application working on my 8GB
> Mac crashes on my 72GB Ubuntu server...
>
> I have changed things in the conf file, but it looks like Spark does not
> care, so I wonder if my issues are with the driver or executor.
>
> I set:
>
> spark.driver.memory 20g
> spark.executor.memory 20g
> And, whatever I do, the crash is always at the same spot in the app, which
> makes me think that it is a driver problem.
>
> The exception I get is:
>
> 16/07/13 20:36:30 WARN TaskSetManager: Lost task 0.0 in stage 7.0 (TID 208,
> micha.nc.rr.com): java.lang.OutOfMemoryError: Java heap space
> at java.nio.HeapCharBuffer.<init>(HeapCharBuffer.java:57)
> at java.nio.CharBuffer.allocate(CharBuffer.java:335)
> at java.nio.charset.CharsetDecoder.decode(CharsetDecoder.java:810)
> at org.apache.hadoop.io.Text.decode(Text.java:412)
> at org.apache.hadoop.io.Text.decode(Text.java:389)
> at org.apache.hadoop.io.Text.toString(Text.java:280)
> at
> org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$org$apache$spark$sql$execution$datasources$json$JSONRelation$$createBaseRdd$1.apply(JSONRelation.scala:105)
> at
> org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$org$apache$spark$sql$execution$datasources$json$JSONRelation$$createBaseRdd$1.apply(JSONRelation.scala:105)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144)
> at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.aggregate(TraversableOnce.scala:201)
> at scala.collection.AbstractIterator.aggregate(Iterator.scala:1157)
> at
> org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$23.apply(RDD.scala:1135)
> at
> org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$23.apply(RDD.scala:1135)
> at
> org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$24.apply(RDD.scala:1136)
> at
> org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$24.apply(RDD.scala:1136)
> 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$20.apply(RDD.scala:710)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
>
> I have set a small memory "dumper" in my app. At the beginning, it says:
>
> ** Free ......... 1,413,566
> ** Allocated .... 1,705,984
> ** Max .......... 16,495,104
> **> Total free ... 16,202,686
> Just before the crash, it says:
>
> ** Free ......... 1,461,633
> ** Allocated .... 1,786,880
> ** Max .......... 16,495,104
> **> Total free ... 16,169,857
>
>
>
>
