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Posted to common-issues@hadoop.apache.org by "Steve Loughran (Jira)" <ji...@apache.org> on 2020/08/15 13:00:03 UTC
[jira] [Commented] (HADOOP-17201) Spark job with s3acommitter stuck
at the last stage
[ https://issues.apache.org/jira/browse/HADOOP-17201?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17178252#comment-17178252 ]
Steve Loughran commented on HADOOP-17201:
-----------------------------------------
possibilities
* could be HADOOP-16823. Large DeleteObject requests are their own Thundering Herd. Is your bucket versioned, and how many files are being created here?
* you've had some auth failure etc and this is how it surfaces.
# Can you try with Hadoop 3.3.0? That's got HADOOP-16823 in
# otherwise, could you do a run with the log org.apache.hadoop.fs.s3a.S3AFileSystem at debug? That should give us the stack trace when retries happen.
One thing which surprises me is that I wouldn't expect that stack trace when writing through the magic committer: That's finalising the multipart upload at the end of the parquet file write; the way the magic one works is we delay that until job commit. Try running org.apache.hadoop.fs.s3a.commit at debug too
hadoop s3guard bucket-info will print out the committer info for a bucket so you can verify all is wired up on the hadoop side -but those extra spark wiring bits can be tricky
Also log at debug
org.apache.hadoop.mapreduce.lib.output.PathOutputCommitterFactory
org.apache.hadoop.fs.s3a.commit
> Spark job with s3acommitter stuck at the last stage
> ---------------------------------------------------
>
> Key: HADOOP-17201
> URL: https://issues.apache.org/jira/browse/HADOOP-17201
> Project: Hadoop Common
> Issue Type: Bug
> Components: fs/s3
> Affects Versions: 3.2.1
> Environment: we are on spark 2.4.5/hadoop 3.2.1 with s3a committer.
> spark.hadoop.fs.s3a.committer.magic.enabled: 'true'
> spark.hadoop.fs.s3a.committer.name: magic
> Reporter: Dyno
> Priority: Major
> Attachments: exec-120.log, exec-125.log, exec-25.log, exec-31.log, exec-36.log, exec-44.log, exec-5.log, exec-64.log, exec-7.log
>
>
> usually our spark job took 1 hour or 2 to finish, occasionally it runs for more than 3 hour and then we know it's stuck and usually the executor has stack like this
> {{
> "Executor task launch worker for task 78620" #265 daemon prio=5 os_prio=0 tid=0x00007f73e0005000 nid=0x12d waiting on condition [0x00007f74cb291000]
> java.lang.Thread.State: TIMED_WAITING (sleeping)
> at java.lang.Thread.sleep(Native Method)
> at org.apache.hadoop.fs.s3a.Invoker.retryUntranslated(Invoker.java:349)
> at org.apache.hadoop.fs.s3a.Invoker.retryUntranslated(Invoker.java:285)
> at org.apache.hadoop.fs.s3a.S3AFileSystem.deleteObjects(S3AFileSystem.java:1457)
> at org.apache.hadoop.fs.s3a.S3AFileSystem.removeKeys(S3AFileSystem.java:1717)
> at org.apache.hadoop.fs.s3a.S3AFileSystem.deleteUnnecessaryFakeDirectories(S3AFileSystem.java:2785)
> at org.apache.hadoop.fs.s3a.S3AFileSystem.finishedWrite(S3AFileSystem.java:2751)
> at org.apache.hadoop.fs.s3a.WriteOperationHelper.lambda$finalizeMultipartUpload$1(WriteOperationHelper.java:238)
> at org.apache.hadoop.fs.s3a.WriteOperationHelper$$Lambda$210/1059071691.execute(Unknown Source)
> at org.apache.hadoop.fs.s3a.Invoker.once(Invoker.java:109)
> at org.apache.hadoop.fs.s3a.Invoker.lambda$retry$3(Invoker.java:265)
> at org.apache.hadoop.fs.s3a.Invoker$$Lambda$23/586859139.execute(Unknown Source)
> at org.apache.hadoop.fs.s3a.Invoker.retryUntranslated(Invoker.java:322)
> at org.apache.hadoop.fs.s3a.Invoker.retry(Invoker.java:261)
> at org.apache.hadoop.fs.s3a.WriteOperationHelper.finalizeMultipartUpload(WriteOperationHelper.java:226)
> at org.apache.hadoop.fs.s3a.WriteOperationHelper.completeMPUwithRetries(WriteOperationHelper.java:271)
> at org.apache.hadoop.fs.s3a.S3ABlockOutputStream$MultiPartUpload.complete(S3ABlockOutputStream.java:660)
> at org.apache.hadoop.fs.s3a.S3ABlockOutputStream$MultiPartUpload.access$200(S3ABlockOutputStream.java:521)
> at org.apache.hadoop.fs.s3a.S3ABlockOutputStream.close(S3ABlockOutputStream.java:385)
> at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.close(FSDataOutputStream.java:72)
> at org.apache.hadoop.fs.FSDataOutputStream.close(FSDataOutputStream.java:101)
> at org.apache.parquet.hadoop.util.HadoopPositionOutputStream.close(HadoopPositionOutputStream.java:64)
> at org.apache.parquet.hadoop.ParquetFileWriter.end(ParquetFileWriter.java:685)
> at org.apache.parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:122)
> at org.apache.parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:165)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.close(ParquetOutputWriter.scala:42)
> at org.apache.spark.sql.execution.datasources.FileFormatDataWriter.releaseResources(FileFormatDataWriter.scala:57)
> at org.apache.spark.sql.execution.datasources.FileFormatDataWriter.commit(FileFormatDataWriter.scala:74)
> at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:247)
> at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:242)
> at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
> at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:248)
> at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:170)
> at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:123)
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> Locked ownable synchronizers:
> - <0x00000003a57332e0> (a java.util.concurrent.ThreadPoolExecutor$Worker)
> }}
> captured jstack on the stuck executors in case it's useful.
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