Hi,
I have a single node (192G RAM) stand-alone spark, with memory
configuration like this in spark-env.sh
SPARK_WORKER_MEMORY=180g
SPARK_MEM=180g
In spark-shell I have a program like this:
val file = sc.textFile("/localpath") //file size is 40G
file.cache()
val output = file.map(line => extract something from line)
output.saveAsTextFile (...)
When I run this program again and again, or keep trying file.unpersist()
--> file.cache() --> output.saveAsTextFile(), the run time varies a lot,
from 1 min to 3 min to 50+ min. Whenever the run-time is more than 1 min,
from the stage monitoring GUI I observe big GC pause (some can be 10+
min). Of course when run-time is "normal", say ~1 min, no significant GC
is observed. The behavior seems somewhat random.
Is there any JVM tuning I should do to prevent this long GC pause from
happening?
I used java-1.6.0-openjdk.x86_64, and my spark-shell process is something
like this:
root 10994 1.7 0.6 196378000 1361496 pts/51 Sl+ 22:06 0:12
/usr/lib/jvm/java-1.6.0-openjdk.x86_64/bin/java -cp
::/home/wtan/scala/spark-1.0.0-bin-hadoop1/conf:/home/wtan/scala/spark-1.0.0-bin-hadoop1/lib/spark-assembly-1.0.0-hadoop1.0.4.jar:/home/wtan/scala/spark-1.0.0-bin-hadoop1/lib/datanucleus-core-3.2.2.jar:/home/wtan/scala/spark-1.0.0-bin-hadoop1/lib/datanucleus-rdbms-3.2.1.jar:/home/wtan/scala/spark-1.0.0-bin-hadoop1/lib/datanucleus-api-jdo-3.2.1.jar
-XX:MaxPermSize=128m -Djava.library.path= -Xms180g -Xmx180g
org.apache.spark.deploy.SparkSubmit spark-shell --class
org.apache.spark.repl.Main
Best regards,
Wei
---------------------------------
Wei Tan, PhD
Research Staff Member
IBM T. J. Watson Research Center
http://researcher.ibm.com/person/us-wtan
