I'm using Parallel GC.
rxin wrote
> Are you using G1 GC? G1 sometimes uses a lot more memory than the size
> allocated.
> 
> 
> On Sun, Jan 22, 2017 at 12:58 AM StanZhai <

> mail@

> > wrote:
> 
>> Hi all,
>>
>>
>>
>> We just upgraded our Spark from 1.6.2 to 2.1.0.
>>
>>
>>
>> Our Spark application is started by spark-submit with config of
>>
>> `--executor-memory 35G` in standalone model, but the actual use of memory
>> up
>>
>> to 65G after a full gc(jmap -histo:live $pid) as follow:
>>
>>
>>
>> test@c6 ~ $ ps aux | grep CoarseGrainedExecutorBackend
>>
>> test      181941  181 34.7 94665384 68836752 ?   Sl   09:25 711:21
>>
>> /home/test/service/jdk/bin/java -cp
>>
>>
>> /home/test/service/hadoop/share/hadoop/common/hadoop-lzo-0.4.20-SNAPSHOT.jar:/home/test/service/hadoop/share/hadoop/common/hadoop-lzo-0.4.20-SNAPSHOT.jar:/home/test/service/spark/conf/:/home/test/service/spark/jars/*:/home/test/service/hadoop/etc/hadoop/
>>
>> -Xmx35840M -Dspark.driver.port=47781 -XX:+PrintGCDetails
>>
>> -XX:+PrintGCDateStamps -Xloggc:./gc.log -verbose:gc
>>
>> org.apache.spark.executor.CoarseGrainedExecutorBackend --driver-url
>>
>> spark://

> CoarseGrainedScheduler@.xxx

> :47781 --executor-id 1
>>
>> --hostname test-192 --cores 36 --app-id app-20170122092509-0017
>> --worker-url
>>
>> spark://Worker@test-192:33890
>>
>>
>>
>> Our Spark jobs are all sql.
>>
>>
>>
>> The exceed memory looks like off-heap memory, but the default value of
>>
>> `spark.memory.offHeap.enabled` is `false`.
>>
>>
>>
>> We didn't find the problem in Spark 1.6.x, what causes this in Spark
>> 2.1.0?
>>
>>
>>
>> Any help is greatly appreicated!
>>
>>
>>
>> Best,
>>
>> Stan
>>
>>
>>
>>
>>
>>
>>
>> --
>>
>> View this message in context:
>> http://apache-spark-developers-list.1001551.n3.nabble.com/Executors-exceed-maximum-memory-defined-with-executor-memory-in-Spark-2-1-0-tp20697.html
>>
>> Sent from the Apache Spark Developers List mailing list archive at
>> Nabble.com.
>>
>>
>>
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>>
>>





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