Daniel Darabos created SPARK-8898:
-------------------------------------
Summary: 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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