[SPARK-6056] Unlimit offHeap memory use cause RM killing the container

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Not A Problem
• Affects Version/s: 1.2.1
• Component/s: Shuffle, Spark Core
• Assignee: Unassigned
• Reporter: Zhaowei Huang
• Created: 27/Feb/15 07:53
• Updated: 21/Jan/16 16:26
• Resolved: 21/Jan/16 16:26

Description

No matter set the `preferDirectBufs` or limit the number of thread or not ,spark can not limit the use of offheap memory.
At line 269 of the class 'AbstractNioByteChannel' in netty-4.0.23.Final, Netty had allocated a offheap memory buffer with the same size in heap.
So how many buffer you want to transfor, the same size offheap memory will be allocated.
But once the allocated memory size reach the capacity of the overhead momery set in yarn, this executor will be killed.
I wrote a simple code to test it:

test.scala

import org.apache.spark.storage._
import org.apache.spark._
val bufferRdd = sc.makeRDD(0 to 10, 10).map(x=>new Array[Byte](10*1024*1024)).persist
bufferRdd.count
val part =  bufferRdd.partitions(0)
val sparkEnv = SparkEnv.get
val blockMgr = sparkEnv.blockManager
def test = {
        val blockOption = blockMgr.get(RDDBlockId(bufferRdd.id, part.index))
        val resultIt = blockOption.get.data.asInstanceOf[Iterator[Array[Byte]]]
        val len = resultIt.map(_.length).sum
        println(s"[${Thread.currentThread.getId}] get block length = $len")
}

def test_driver(count:Int, parallel:Int)(f: => Unit) = {
    val tpool = new scala.concurrent.forkjoin.ForkJoinPool(parallel)
    val taskSupport  = new scala.collection.parallel.ForkJoinTaskSupport(tpool)
    val parseq = (1 to count).par
    parseq.tasksupport = taskSupport
    parseq.foreach(x=>f)

    tpool.shutdown
    tpool.awaitTermination(100, java.util.concurrent.TimeUnit.SECONDS)
}

progress:
1. bin/spark-shell --master yarn-cilent --executor-cores 40 --num-executors 1
2. :load test.scala in spark-shell
3. use such comman to catch executor on slave node

pid=$(jps|grep CoarseGrainedExecutorBackend |awk '{print $1}');top -b -p $pid|grep $pid

4. test_driver(20,100)(test) in spark-shell
5. watch the output of the command on slave node

If use multi-thread to get len, the physical memery will soon exceed the limit set by spark.yarn.executor.memoryOverhead