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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org