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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2015/07/08 17:06:04 UTC
[jira] [Commented] (SPARK-8898) Jets3t hangs with more than 1 core
[ https://issues.apache.org/jira/browse/SPARK-8898?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14618747#comment-14618747 ]
Sean Owen commented on SPARK-8898:
----------------------------------
Yeah, this is a jets3t problem. You will have to manage to update it in your build or get EC2 + Hadoop 2 to work, which I think can be done. At least, this is just a subset of "EC2 should support Hadoop 2" and/or that the EC2 support should move out of Spark anyway. I don't know there's another action to take in Spark.
> Jets3t hangs with more than 1 core
> ----------------------------------
>
> Key: SPARK-8898
> URL: https://issues.apache.org/jira/browse/SPARK-8898
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
> Affects Versions: 1.4.0
> Environment: S3
> Reporter: Daniel Darabos
>
> If I have an RDD that reads from S3 ({{newAPIHadoopFile}}), and try to write this to S3 ({{saveAsNewAPIHadoopFile}}), it hangs if I have more than 1 core per executor.
> It sounds like a race condition, but so far I have seen it trigger 100% of the time. From a race for taking a limited number of connections I would expect it to succeed at least on 1 task at least some of the time. But I never saw a single completed task, except when running with 1-core executors.
> All executor threads hang with one of the following two stack traces:
> {noformat:title=Stack trace 1}
> java.lang.Thread.State: WAITING (on object monitor)
> at java.lang.Object.wait(Native Method)
> - waiting on <0x00000007759cae70> (a org.apache.commons.httpclient.MultiThreadedHttpConnectionManager$ConnectionPool)
> at org.apache.commons.httpclient.MultiThreadedHttpConnectionManager.doGetConnection(MultiThreadedHttpConnectionManager.java:518)
> - locked <0x00000007759cae70> (a org.apache.commons.httpclient.MultiThreadedHttpConnectionManager$ConnectionPool)
> at org.apache.commons.httpclient.MultiThreadedHttpConnectionManager.getConnectionWithTimeout(MultiThreadedHttpConnectionManager.java:416)
> at org.apache.commons.httpclient.HttpMethodDirector.executeMethod(HttpMethodDirector.java:153)
> at org.apache.commons.httpclient.HttpClient.executeMethod(HttpClient.java:397)
> at org.apache.commons.httpclient.HttpClient.executeMethod(HttpClient.java:323)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.performRequest(RestS3Service.java:342)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.performRestHead(RestS3Service.java:718)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.getObjectImpl(RestS3Service.java:1599)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.getObjectDetailsImpl(RestS3Service.java:1535)
> at org.jets3t.service.S3Service.getObjectDetails(S3Service.java:1987)
> at org.jets3t.service.S3Service.getObjectDetails(S3Service.java:1332)
> at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.retrieveMetadata(Jets3tNativeFileSystemStore.java:107)
> at sun.reflect.GeneratedMethodAccessor6.invoke(Unknown Source)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:164)
> at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:83)
> at org.apache.hadoop.fs.s3native.$Proxy8.retrieveMetadata(Unknown Source)
> at org.apache.hadoop.fs.s3native.NativeS3FileSystem.getFileStatus(NativeS3FileSystem.java:414)
> at org.apache.hadoop.fs.FileSystem.exists(FileSystem.java:1332)
> at org.apache.hadoop.fs.s3native.NativeS3FileSystem.create(NativeS3FileSystem.java:341)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:851)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:832)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:731)
> at org.apache.hadoop.mapreduce.lib.output.TextOutputFormat.getRecordWriter(TextOutputFormat.java:128)
> at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1030)
> at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1014)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63)
> at org.apache.spark.scheduler.Task.run(Task.scala:70)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> {noformat:title=Stack trace 2}
> java.lang.Thread.State: WAITING (on object monitor)
> at java.lang.Object.wait(Native Method)
> - waiting on <0x00000007759cae70> (a org.apache.commons.httpclient.MultiThreadedHttpConnectionManager$ConnectionPool)
> at org.apache.commons.httpclient.MultiThreadedHttpConnectionManager.doGetConnection(MultiThreadedHttpConnectionManager.java:518)
> - locked <0x00000007759cae70> (a org.apache.commons.httpclient.MultiThreadedHttpConnectionManager$ConnectionPool)
> at org.apache.commons.httpclient.MultiThreadedHttpConnectionManager.getConnectionWithTimeout(MultiThreadedHttpConnectionManager.java
> :416)
> at org.apache.commons.httpclient.HttpMethodDirector.executeMethod(HttpMethodDirector.java:153)
> at org.apache.commons.httpclient.HttpClient.executeMethod(HttpClient.java:397)
> at org.apache.commons.httpclient.HttpClient.executeMethod(HttpClient.java:323)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.performRequest(RestS3Service.java:342)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.performRestGet(RestS3Service.java:752)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.getObjectImpl(RestS3Service.java:1601)
> at org.jets3t.service.impl.rest.httpclient.RestS3Service.getObjectImpl(RestS3Service.java:1544)
> at org.jets3t.service.S3Service.getObject(S3Service.java:2072)
> at org.jets3t.service.S3Service.getObject(S3Service.java:1310)
> at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.retrieve(Jets3tNativeFileSystemStore.java:122)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:164)
> at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:83)
> at org.apache.hadoop.fs.s3native.$Proxy8.retrieve(Unknown Source)
> at org.apache.hadoop.fs.s3native.NativeS3FileSystem.open(NativeS3FileSystem.java:564)
> at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:711)
> at org.apache.hadoop.mapreduce.lib.input.LineRecordReader.initialize(LineRecordReader.java:75)
> at org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:133)
> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:104)
> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:66)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63)
> at org.apache.spark.scheduler.Task.run(Task.scala:70)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> This is running the ancient 0.7.1 version of Jets3t that comes with Spark. (Theoretically Spark built with newer Hadoop profiles would use Jets3t 0.9.3, but I could not get the {{spark-ec2}} script to install one of these builds.) I could not find documentation for this version, but based on the current docs and the 0.7.1 source code I tried putting this into a {{jets3t.properties}} file (which on the classpath of the driver and the executors):
> {noformat}
> httpclient.max-connections=10000
> httpclient.max-connections-per-host=10000
> http.connection-manager.max-total=10000
> http.connection-manager.max-per-host=10000
> {noformat}
> It didn't help.
> It's very simple to reproduce from the {{spark-shell}}. It's a bit messy because I have to create a HadoopConfiguration to pass in the access key and the password. But I can add it to the ticket if it would be useful.
> I understand that this is probably a Jets3t configuration issue. But I hope Spark could use a newer version or provide defaults such that this would work better.
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