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https://issues.apache.org/jira/browse/SPARK-3633?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14208318#comment-14208318
]
Cristian Opris commented on SPARK-3633:
---------------------------------------
This looks like a memory leak in ConnectionManager where responses
(BufferMessage) are retained by the TimerTask waiting for ACK even after the
Future completes with Success, please see the
Possibly related to
https://github.com/apache/spark/commit/76fa0eaf515fd6771cdd69422b1259485debcae5
+------------------------------------------------------+--------------+----------------------+-------------------------+
| Class | Objects |
Shallow Size | Retained Size |
+------------------------------------------------------+--------------+----------------------+-------------------------+
| java.util.TaskQueue | 1 0 % |
24 0 % | 885,048,168 100 % |
| java.util.TimerTask[] | 1 0 % |
2,064 0 % | 885,048,144 99 % |
| org.apache.spark.network.ConnectionManager$$anon$5 | 286 5 % |
13,728 0 % | ~ 885,046,080 99 % |
| org.apache.spark.network.BufferMessage | 572 10 % |
36,608 0 % | ~ 885,018,624 99 % |
| scala.concurrent.impl.Promise$DefaultPromise | 286 5 % |
4,576 0 % | ~ 884,968,288 99 % |
| scala.util.Success | 286 5 % |
4,576 0 % | ~ 884,963,712 99 % |
| scala.collection.mutable.ArrayBuffer | 572 10 % |
13,728 0 % | ~ 884,915,768 99 % |
| java.lang.Object[] | 572 10 % |
45,760 0 % | ~ 884,902,040 99 % |
| java.nio.HeapByteBuffer | 286 5 % |
13,728 0 % | ~ 884,856,280 99 % |
| byte[] | 286 5 % |
884,842,552 99 % | ~ 884,842,552 99 % |
| java.net.InetSocketAddress | 572 10 % |
9,152 0 % | ~ 66,248 0 % |
| java.net.InetSocketAddress$InetSocketAddressHolder | 572 10 % |
13,728 0 % | ~ 57,096 0 % |
| java.net.Inet4Address | 286 5 % |
6,864 0 % | ~ 43,368 0 % |
| java.net.InetAddress$InetAddressHolder | 286 5 % |
6,864 0 % | ~ 36,504 0 % |
| java.lang.String | 285 5 % |
6,840 0 % | ~ 29,640 0 % |
| char[] | 285 5 % |
22,800 0 % | ~ 22,800 0 % |
| java.lang.Object | 286 5 % |
4,576 0 % | ~ 4,576 0 % |
+------------------------------------------------------+--------------+----------------------+-------------------------+
Generated by YourKit Java Profiler 2014 build 14110 12-Nov-2014 17:44:32
> Fetches failure observed after SPARK-2711
> -----------------------------------------
>
> Key: SPARK-3633
> URL: https://issues.apache.org/jira/browse/SPARK-3633
> Project: Spark
> Issue Type: Bug
> Components: Block Manager
> Affects Versions: 1.1.0
> Reporter: Nishkam Ravi
> Priority: Critical
>
> Running a variant of PageRank on a 6-node cluster with a 30Gb input dataset.
> Recently upgraded to Spark 1.1. The workload fails with the following error
> message(s):
> {code}
> 14/09/19 12:10:38 WARN TaskSetManager: Lost task 51.0 in stage 2.1 (TID 552,
> c1705.halxg.cloudera.com): FetchFailed(BlockManagerId(1,
> c1706.halxg.cloudera.com, 49612, 0), shuffleId=3, mapId=75, reduceId=120)
> 14/09/19 12:10:38 INFO DAGScheduler: Resubmitting failed stages
> {code}
> In order to identify the problem, I carried out change set analysis. As I go
> back in time, the error message changes to:
> {code}
> 14/09/21 12:56:54 WARN TaskSetManager: Lost task 35.0 in stage 3.0 (TID 519,
> c1706.halxg.cloudera.com): java.io.FileNotFoundException:
> /var/lib/jenkins/workspace/tmp/spark-local-20140921123257-68ee/1c/temp_3a1ade13-b48a-437a-a466-673995304034
> (Too many open files)
> java.io.FileOutputStream.open(Native Method)
> java.io.FileOutputStream.<init>(FileOutputStream.java:221)
>
> org.apache.spark.storage.DiskBlockObjectWriter.open(BlockObjectWriter.scala:117)
>
> org.apache.spark.storage.DiskBlockObjectWriter.write(BlockObjectWriter.scala:185)
>
> org.apache.spark.util.collection.ExternalAppendOnlyMap.spill(ExternalAppendOnlyMap.scala:197)
>
> org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:145)
> org.apache.spark.Aggregator.combineValuesByKey(Aggregator.scala:58)
>
> org.apache.spark.shuffle.hash.HashShuffleWriter.write(HashShuffleWriter.scala:51)
>
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
>
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> org.apache.spark.scheduler.Task.run(Task.scala:54)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:199)
>
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> java.lang.Thread.run(Thread.java:745)
> {code}
> All the way until Aug 4th. Turns out the problem changeset is 4fde28c.
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