Below is my error message. When I use python 2.7 in Datastax Spark with the code below it doesn't work. I don't know why. Would be very grateful for some suggestions. Thanks
vi /etc/dse/spark/spark-env.sh
export PYTHONHOME=/usr/local
export PYTHONPATH=/usr/local/lib/python2.7
export PYSPARK_PYTHON=/usr/local/bin/python2.7
Error message:
Error from python worker:
/usr/local/bin/python2.7: /usr/local/lib/python2.7/lib-dynload/_io.so: undefined symbol: _PyCodec_LookupTextEncoding
PYTHONPATH was:
/usr/share/dse/spark/python/lib/pyspark.zip:/usr/share/dse/spark/python/lib/py4j-0.8.2.1-src.zip:/usr/share/dse/spark/lib/spark-core_2.10-1.4.2.2.jar:/usr/local/lib/python2.7
java.io.EOFException
at java.io.DataInputStream.readInt(DataInputStream.java:392)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:163)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:86)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:62)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:130)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:73)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:315)
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.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:70)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Related
I am running a job with 4000 executors to process 3 years of data ~ 1 Petabyte. I run one query per day and process 2-3 days at the same time. Approx after processing 700 days total (~ 7 hours) it fails with some shuffle exception.
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 10259 in stage 447.0 failed 4 times, most recent failure: Lost task 10259.3 in stage 447.0 (TID 1691674, machine0689.datacenter.domain.com, executor 2647): java.io.FileNotFoundException: /data4/yarn/nm/usercache/my_application/appcache/application_1535740315164_66119/blockmgr-10614d00-de24-4b2c-8bd6-2463ab4b358c/2e/temp_shuffle_6d6bae3b-d4c4-44e7-b2de-e0cdd71d35e0 (Read-only file system)
Has anyone seen this error or help figure it out? Here's the spark configuration:
spark.network.timeout=300s
spark.executor.heartbeatInterval=60s
spark.shuffle.service.enabled=true
spark.executor.instances=4000
spark.executor.cores=4
spark.executor.memory=32G
spark.executor.memoryOverhead=4G
spark.driver.cores=8
spark.driver.memory=32G
spark.driver.memoryOverhead=4G
Full StackTrace:
User class threw exception: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:224)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:154)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:225)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:547)
at com.mycompany.filter.Filter.process(Filter.scala:143)
at com.mycompany.filter.Filter$$anonfun$filterDataset$1.apply(Filter.scala:60)
at com.mycompany.filter.Filter$$anonfun$filterDataset$1.apply(Filter.scala:60)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.parallel.ParIterableLike$Foreach.leaf(ParIterableLike.scala:972)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
at scala.collection.parallel.ParIterableLike$Foreach.tryLeaf(ParIterableLike.scala:969)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.internal(Tasks.scala:169)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.internal(Tasks.scala:443)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:149)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 10259 in stage 447.0 failed 4 times, most recent failure: Lost task 10259.3 in stage 447.0 (TID 1691674, machine0689.datacenter.domain.com, executor 2647): java.io.FileNotFoundException: /data4/yarn/nm/usercache/my_application/appcache/application_1535740315164_66119/blockmgr-10614d00-de24-4b2c-8bd6-2463ab4b358c/2e/temp_shuffle_6d6bae3b-d4c4-44e7-b2de-e0cdd71d35e0 (Read-only file system)
at java.io.FileOutputStream.open0(Native Method)
at java.io.FileOutputStream.open(FileOutputStream.java:270)
at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
at org.apache.spark.storage.DiskBlockObjectWriter.initialize(DiskBlockObjectWriter.scala:103)
at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:116)
at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:237)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
The driver stacktrace looks like:
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:194)
... 40 more
Caused by: java.io.FileNotFoundException: /data4/yarn/nm/usercache/my_application/appcache/application_1535740315164_66119/blockmgr-10614d00-de24-4b2c-8bd6-2463ab4b358c/2e/temp_shuffle_6d6bae3b-d4c4-44e7-b2de-e0cdd71d35e0 (Read-only file system)
at java.io.FileOutputStream.open0(Native Method)
at java.io.FileOutputStream.open(FileOutputStream.java:270)
at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
at org.apache.spark.storage.DiskBlockObjectWriter.initialize(DiskBlockObjectWriter.scala:103)
at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:116)
at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:237)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Supply below 2 properties to spark-submit-
spark.yarn.nodemanager.local-dirs=<fs path>
Spark.locak.dir=<fs path>
Read Spark WIKI for more details about these properties.
when I save pyspark Dataframe as parquet file, I got this error:
Py4JJavaError: An error occurred while calling o50.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:224)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:154)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:225)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:547)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 1.0 failed 1 times, most recent failure: Lost task 3.0 in stage 1.0 (TID 4, localhost, executor driver): java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainIntegerDictionary
at org.apache.parquet.column.Dictionary.decodeToLong(Dictionary.java:52)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToLong(ParquetDictionary.java:36)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getLong(OnHeapColumnVector.java:364)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:257)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:197)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:196)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1587)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1586)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1586)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1820)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1769)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1758)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2027)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:194)
... 31 more
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainIntegerDictionary
at org.apache.parquet.column.Dictionary.decodeToLong(Dictionary.java:52)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToLong(ParquetDictionary.java:36)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getLong(OnHeapColumnVector.java:364)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:257)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:197)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:196)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
what is the reason and how can I overcome this error?
I am using Pyspark 2.3.0
The data frame has around 200 million Rows
Following is the configuration to run spark
pyspark --num-executors 20 --executor-memory 8G
--executor-cores 5 --driver-memory 10G --driver-cores 3
UnsupportedOperationException sounds like you have a version mismatch error. You should confirm that the spark version you are using is built against the same version of Hadoop you are using.
For the spark version look at what you downloaded from the spark website. They provide different binaries built for Hadoop 2.7 and Hadoop 2.6.
For the hadoop version you can run this command:
hadoop version
Something simple as writing partitioned text files fails.
dataDF.write.partitionBy("year", "month", "date").mode(SaveMode.Append).text("s3://data/test2/events/")
Exception -
16/07/06 02:15:05 ERROR datasources.DynamicPartitionWriterContainer: Aborting task.
java.io.IOException: File already exists:s3://path/1839dd1ed38a.gz
at com.amazon.ws.emr.hadoop.fs.s3n.S3NativeFileSystem.create(S3NativeFileSystem.java:614)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:913)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:894)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:791)
at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.create(EmrFileSystem.java:177)
at org.apache.hadoop.mapreduce.lib.output.TextOutputFormat.getRecordWriter(TextOutputFormat.java:135)
at org.apache.spark.sql.execution.datasources.text.TextOutputWriter.<init>(DefaultSource.scala:156)
at org.apache.spark.sql.execution.datasources.text.TextRelation$$anon$1.newInstance(DefaultSource.scala:125)
at org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:129)
at org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer.newOutputWriter$1(WriterContainer.scala:424)
at org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer.writeRows(WriterContainer.scala:356)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
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)
16/07/06 02:15:05 INFO output.DirectFileOutputCommitter: Nothing to clean up on abort since there are no temporary files written
16/07/06 02:15:05 ERROR datasources.DynamicPartitionWriterContainer: Task attempt attempt_201607060215_0004_m_001709_3 aborted.
16/07/06 02:15:05 ERROR executor.Executor: Exception in task 1709.3 in stage 4.0 (TID 12093)
org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer.writeRows(WriterContainer.scala:414)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
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)
Caused by: java.io.IOException: File already exists:s3://path/a984-1839dd1ed38a.gz
at com.amazon.ws.emr.hadoop.fs.s3n.S3NativeFileSystem.create(S3NativeFileSystem.java:614)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:913)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:894)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:791)
at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.create(EmrFileSystem.java:177)
at org.apache.hadoop.mapreduce.lib.output.TextOutputFormat.getRecordWriter(TextOutputFormat.java:135)
at org.apache.spark.sql.execution.datasources.text.TextOutputWriter.<init>(DefaultSource.scala:156)
at org.apache.spark.sql.execution.datasources.text.TextRelation$$anon$1.newInstance(DefaultSource.scala:125)
at org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:129)
at org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer.newOutputWriter$1(WriterContainer.scala:424)
at org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer.writeRows(WriterContainer.scala:356)
... 8 more
After lot of wasted man hours, answering my question with solution that worked for me, among other trouble shootings.
TLDR;
Set spark.speculation to false, as follow :
conf = new SparkConf().set(“spark.speculation“,”false”)
More details here and here.
I am running a spark-streaming job to stream data from HDFS.
The job fails frequently once or twice a day, showing multiple errors in the log files.
I want to know, when does the spark-streaming job Fails/Exits, after so and so conditions/ retries are performed?
Exception in yarn log :-
16/05/10 02:22:35 ERROR RetryingBlockFetcher: Exception while beginning fetch of 1 outstanding blocks (after 3 retries)
java.io.IOException: Failed to connect to spark-prod-02-w-8.c.orion-0010.internal/10.240.0.255:41259
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:191)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:156)
at org.apache.spark.network.netty.NettyBlockTransferService$$anon$1.createAndStart(NettyBlockTransferService.scala:78)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:140)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.access$200(RetryingBlockFetcher.java:43)
at org.apache.spark.network.shuffle.RetryingBlockFetcher$1.run(RetryingBlockFetcher.java:170)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused: spark-prod-02-w-8.c.orion-0010.internal/10.240.0.255:41259
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:744)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:208)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:287)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:116)
16/05/10 02:22:35 ERROR Executor: Exception in task 1.1 in stage 105394.0 (TID 762765)
java.lang.Exception: Could not compute split, block input-0-1462846937000 not found
at org.apache.spark.rdd.BlockRDD.compute(BlockRDD.scala:51)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
spark RecoverableKafkaWordCount several minutes , when I restart throw this exception:
15/12/04 15:27:27 WARN [task-result-getter-0] TaskSetManager: Lost task 0.0 in stage 3.0 (TID 56, 192.168.0.2): java.lang.Exception: Could not compute split, block input-0-1449191870000 not found
at org.apache.spark.rdd.BlockRDD.compute(BlockRDD.scala:51)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:70)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
if we use Recoverable Spark App use this function:
StreamingContext.getOrCreate(PropertyLoader.getValue("spark.checkpoint_directory"), createContext)
but I find that KafkaUtils.createStream normal KafkaInputDStream will will lead to this problem this maybe be a bug, just use DirectKafkaInputDStream instead