Hi all,
I have an issue where I'm able to run my code in standalone mode but not on
my cluster. I've isolated it to a few things but am at a lost at how to
debug this. Below is the code. Any suggestions would be much appreciated
Thanks!
1) RDD size is causing the problem. The code below as is fails but if I swap
smallSample for samples, the code runs end to end on both cluster and
standalone.
2) The error I get is:
rg.apache.spark.SparkException: Job aborted due to stage failure: Task 3.0:1
failed 4 times, most recent failure: TID 12 on host
ip-10-251-14-74.us-west-2.compute.internal failed for unknown reason
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1044)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1028)
Code:
val smallSample = sc.parallelize(Array("foo word", "bar word", "baz word"))
val samples = sc.textFile("s3n://geonames") // 64MB, 2849439 Lines of short
strings
val counts = new collection.mutable.HashMap[String, Int].withDefaultValue(0)
samples.toArray.foreach(counts(_) += 1)
val result = samples.map(
l => (l, counts.get(l))
)
result.count
Settings (with or without Kryo doesn't matter):
export SPARK_JAVA_OPTS="-Xms5g -Xmx10g -XX:MaxPermSize=10g"
export SPARK_MEM=10g
spark.akka.frameSize 40
#spark.serializer org.apache.spark.serializer.KryoSerializer
#spark.kryoserializer.buffer.mb 1000
spark.executor.memory 58315m
spark.executor.extraLibraryPath /root/ephemeral-hdfs/lib/native/
spark.executor.extraClassPath /root/ephemeral-hdfs/conf
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