Hello,
I have to write the aggregated output stored in DF(about 3GB) in a single
file for that I have tried using repartition(1) as well as coalesce(1).
My Job is failing with the following Exception:
ExecutorLostFailure (executor 32 exited caused by one of the running tasks)
Reason: Remote RPC client disassociated. Likely due to containers exceeding
thresholds, or network issues. Check driver logs for WARN messages.
ava.lang.OutOfMemoryError
at
java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at
net.jpountz.lz4.LZ4BlockOutputStream.flushBufferedData(LZ4BlockOutputStream.java:220)
at
net.jpountz.lz4.LZ4BlockOutputStream.write(LZ4BlockOutputStream.java:173)
at java.io.DataOutputStream.write(DataOutputStream.java:107)
at
org.apache.spark.sql.catalyst.expressions.UnsafeRow.writeToStream(UnsafeRow.java:554)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:258)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at
org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Could you please suggest something? I have sufficient memory in executors
and the driver as well.
Kind Regards,
Sachit Murarka
