I use sc.textFile() to read multiple files from S3 in Spark. But, the input S3 path also has a few empty files that give NullPointerException. Is there a way that I can ignore these files?
val inputFile = sc.textfile("s3n://mypath/*file")
val inputRDD = inputFile.map(_.split(",")).map(line => {
//processing
})
Edit: Adding stack trace
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 128 in stage 0.0 failed 1 times, most recent failure: Lost task 128.0 in stage 0.0 (TID 128, localhost): java.lang.NullPointerException
at org.apache.hadoop.fs.s3native.NativeS3FileSystem$NativeS3FsInputStream.read(NativeS3FileSystem.java:130)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.read(DataInputStream.java:100)
at org.apache.hadoop.util.LineReader.fillBuffer(LineReader.java:180)
at org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:216)
at org.apache.hadoop.util.LineReader.readLine(LineReader.java:174)
at org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:209)
at org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:47)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:248)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:216)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:894)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:894)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Related
I have a Pyspark job which reads about 1M record from upstream data source and and tries to add it to SQL. I am using Pyspark 3.1 with Pyspark sql connector and when writing anything over 2K records into SQL it returns me the error that connection closed (: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8.0 failed 4 times, most recent failure: Lost task 0.3 in stage 8.0 (TID 11) (vm-1286783 executor 1): com.microsoft.sqlserver.jdbc.SQLServerException: The connection is closed)
I am not repartitioning the data from upstream when writing to SQL. Also this job will be run on Azure Synapse in Spark Pool.
These are the options I`m using for the SQL connector:
"schemaCheckEnabled": "false",
"url": "test-url",
"hostNameInCertificate": "*.database.windows.net",
"database": "testdb",
"dbtable": "testtable",
"batchsize": "5000",
"tableLock": "true",
"queryTimeout": "0",
"reliabilityLevel": "BEST_EFFORT"
This is the pyspark config:
"driver_cores": 4,
"driver_memory": "20g",
"executor_memory": "32g",
"num_executors": 24,
"executor_cores": 5,
Any help would be appreciated.
This is the complete stack trace:
2022-09-08 05:53:22,146 - __main__ - WARNING - An error occurred while calling o1179.save.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 9.0 failed 4 times, most recent failure: Lost task 1.3 in stage 9.0 (TID 23) (vm-24f65417 executor 2): com.microsoft.sqlserver.jdbc.SQLServerException: The connection is closed.
at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDriverError(SQLServerException.java:234)
at com.microsoft.sqlserver.jdbc.SQLServerConnection.checkClosed(SQLServerConnection.java:1202)
at com.microsoft.sqlserver.jdbc.SQLServerConnection.rollback(SQLServerConnection.java:3442)
at com.microsoft.sqlserver.jdbc.spark.BulkCopyUtils$.savePartition(BulkCopyUtils.scala:68)
at com.microsoft.sqlserver.jdbc.spark.SingleInstanceWriteStrategies$.$anonfun$write$2(BestEffortSingleInstanceStrategy.scala:43)
at com.microsoft.sqlserver.jdbc.spark.SingleInstanceWriteStrategies$.$anonfun$write$2$adapted(BestEffortSingleInstanceStrategy.scala:42)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1027)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1027)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2341)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:498)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:501)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2313)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2262)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2261)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2261)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1132)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1132)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1132)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2500)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2442)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2431)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:908)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2301)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2322)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2341)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2366)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$1(RDD.scala:1027)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:415)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:1025)
at com.microsoft.sqlserver.jdbc.spark.SingleInstanceWriteStrategies$.write(BestEffortSingleInstanceStrategy.scala:42)
at com.microsoft.sqlserver.jdbc.spark.SingleInstanceConnector$.writeInParallel(SingleInstanceConnector.scala:35)
at com.microsoft.sqlserver.jdbc.spark.Connector.write(Connector.scala:80)
at com.microsoft.sqlserver.jdbc.spark.DefaultSource.createRelation(DefaultSource.scala:66)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:218)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:256)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:253)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:214)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:148)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:147)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:1013)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:107)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:181)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:94)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:1013)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:462)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:434)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:303)
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:238)
at java.lang.Thread.run(Thread.java:750)
Caused by: com.microsoft.sqlserver.jdbc.SQLServerException: The connection is closed.
at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDriverError(SQLServerException.java:234)
at com.microsoft.sqlserver.jdbc.SQLServerConnection.checkClosed(SQLServerConnection.java:1202)
at com.microsoft.sqlserver.jdbc.SQLServerConnection.rollback(SQLServerConnection.java:3442)
at com.microsoft.sqlserver.jdbc.spark.BulkCopyUtils$.savePartition(BulkCopyUtils.scala:68)
at com.microsoft.sqlserver.jdbc.spark.SingleInstanceWriteStrategies$.$anonfun$write$2(BestEffortSingleInstanceStrategy.scala:43)
at com.microsoft.sqlserver.jdbc.spark.SingleInstanceWriteStrategies$.$anonfun$write$2$adapted(BestEffortSingleInstanceStrategy.scala:42)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:1027)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:1027)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2341)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:498)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:501)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
I am new to Spark, Scala.
I am trying to perform Triangle Counts in this dataset : DataSet
for a hobby project
This is the code I have written so far :
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.graphx.Edge
import org.apache.spark.graphx.Graph
import org.apache.spark.graphx.Graph.graphToGraphOps
import org.apache.spark.graphx.PartitionStrategy
import org.apache.spark.rdd.RDD
import org.apache.spark.rdd.RDD.rddToPairRDDFunctions
object GraphXApps {
def main(args: Array[String]): Unit = {
val conf = new SparkConf()
.setAppName("GraphXApps")
.setSparkHome(System.getenv("SPARK_HOME"))
.setJars(SparkContext.jarOfClass(this.getClass).toList)
val sc = new SparkContext(conf)
// Load the edges in canonical order and partition the graph for triangle count
val edges: RDD[Edge[String]] =
sc.textFile(args(0)).map { line =>
val fields = line.split("\t")
Edge(fields(0).toLong, fields(1).toLong)
}
val graph : Graph[String, String] = Graph.fromEdges(edges.sortBy(_.srcId, ascending = true, 1), "defaultProperty").partitionBy(PartitionStrategy.RandomVertexCut)
// Find the triangle count for each vertex
val triCounts = graph.triangleCount().vertices
val triCountById = graph.vertices.join(triCounts).map(_._2._2)
// Print the result
println(triCountById.collect().mkString("\n"))
sc.stop()
}
}
But I am getting this error : java.lang.IllegalArgumentException: requirement failed: Invalid initial capacity
Please let me know where I am going wrong. It would be really helpful.
Full Stack Trace
16/10/31 01:03:08 ERROR TaskSetManager: Task 0 in stage 8.0 failed 1 times; aborting job
16/10/31 01:03:08 INFO TaskSchedulerImpl: Removed TaskSet 8.0, whose tasks have all completed, from pool
16/10/31 01:03:08 INFO TaskSchedulerImpl: Cancelling stage 8
16/10/31 01:03:08 INFO DAGScheduler: ShuffleMapStage 8 (mapPartitions at VertexRDDImpl.scala:245) failed in 0.131 s
16/10/31 01:03:08 INFO DAGScheduler: Job 0 failed: collect at GraphXApps.scala:47, took 3.128921 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8.0 failed 1 times, most recent failure: Lost task 0.0 in stage 8.0 (TID 8, localhost): java.lang.IllegalArgumentException: requirement failed: Invalid initial capacity
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:51)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:57)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun$5.apply(TriangleCount.scala:70)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun$5.apply(TriangleCount.scala:69)
at org.apache.spark.graphx.impl.VertexPartitionBaseOps.map(VertexPartitionBaseOps.scala:61)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues$2.apply(VertexRDDImpl.scala:102)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues$2.apply(VertexRDDImpl.scala:102)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$3.apply(VertexRDDImpl.scala:156)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$3.apply(VertexRDDImpl.scala:154)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:332)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:330)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:919)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:668)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:281)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1438)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1437)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1871)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1884)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1897)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1911)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:893)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.collect(RDD.scala:892)
at GraphXApps$.main(GraphXApps.scala:47)
at GraphXApps.main(GraphXApps.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.IllegalArgumentException: requirement failed: Invalid initial capacity
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:51)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:57)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun$5.apply(TriangleCount.scala:70)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun$5.apply(TriangleCount.scala:69)
at org.apache.spark.graphx.impl.VertexPartitionBaseOps.map(VertexPartitionBaseOps.scala:61)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues$2.apply(VertexRDDImpl.scala:102)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues$2.apply(VertexRDDImpl.scala:102)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$3.apply(VertexRDDImpl.scala:156)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$3.apply(VertexRDDImpl.scala:154)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:332)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:330)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:919)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:668)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:281)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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)
This appears to be a bug within Spark 2.0 (so far, have tested this against 2.0, 2.0.1, and 2.0.2). Jira [SPARK-18200]: GraphX Invalid initial capacity when running triangleCount has been created to address this.
Your code should work okay with Spark 1.6 as noted in this linked notebook.
But as you noted, it failed in Spark 2.0, as noted in this linked notebook.
In the interim, please try Spark 1.6 or try using GraphFrames, as noted in this linked notebook.
HTH!
I'm attempting to save a Spark RDD as a gzipped text file (or several text files) to an S3 bucket. The S3 bucket is mounted to dbfs. I'm trying to save the file using the following:
rddDataset.saveAsTextFile("/mnt/mymount/myfolder/")
But when trying this, I keep getting the error:
org.apache.spark.SparkException: Job aborted due to stage failure: Task 32 in stage 18.0 failed 4 times, most recent failure: Lost task 32.3 in stage 18.0 (TID 279, ip-10-81-194-225.ec2.internal): java.lang.NullPointerException
However, I do see a few files written to the S3 bucket. I've also tried using rddDataset.repartition(1).saveAsTextFile("/mnt/mymount/myfolder/"), as advised here, but this ended in the same error.
This appears to be similar to this question, so maybe the errors are due to null values in my RDD? But when I try val newRDD = rddDataset.map(line => line).filter(x => x!= null).filter(x => x!=" ").filter(x => x!="") and try to save this RDD, I get the same error.
Additionally, rddDataset.count() throws a similar error. I'm creating rddDataset from a dataframe, which displays all its rows just fine. However, I can reproduce the java.lang.NullPointerException if I convert my original dataframe to an RDD:
val testRDD = df.rdd
testRDD.count()
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 32 in stage 85.0 failed 4 times, most recent failure: Lost task 32.3 in stage 85.0 (TID 1668, ip-10-81-194-241.ec2.internal): java.lang.NullPointerException
I've provided one of the stack traces below:
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1837)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1850)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1927)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scala:1209)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1154)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1154)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1154)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply$mcV$sp(PairRDDFunctions.scala:1060)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply(PairRDDFunctions.scala:1026)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply(PairRDDFunctions.scala:1026)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1026)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$1.apply$mcV$sp(PairRDDFunctions.scala:952)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$1.apply(PairRDDFunctions.scala:952)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$1.apply(PairRDDFunctions.scala:952)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:951)
at org.apache.spark.rdd.RDD$$anonfun$saveAsTextFile$1.apply$mcV$sp(RDD.scala:1457)
at org.apache.spark.rdd.RDD$$anonfun$saveAsTextFile$1.apply(RDD.scala:1436)
at org.apache.spark.rdd.RDD$$anonfun$saveAsTextFile$1.apply(RDD.scala:1436)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1436)
Caused by: java.lang.NullPointerException
Also, when I open up the information tab for the stage after running rddDataset.repartition(200).saveAsTextFile(/mnt/mymount/myfolder)I can find the error details:
java.lang.NullPointerException
at linef9b86491b9da46b9858e22af0cc8257227.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:48)
at linef9b86491b9da46b9858e22af0cc8257227.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:48)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.evalExpr35$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:51)
at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:49)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:46)
at org.apache.spark.scheduler.Task.run(Task.scala:96)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:235)
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)
I wasn't properly handling null values in one of my UDFs while pre-processing the data. Concretely, I had to change one of my UDFs from
val converter = (arg: String) => {
arg.split("").mkString("_").replace(":","_")
}
to
val converter = (arg: String) => {
if (arg == null || arg== "") "" else arg.split("").mkString("_").replace(":","_")
}
Everything seemed to work after that.
I am using a Future to perform a blocking operation on an RDD like this:
dStreams.foreach(_.foreachRDD { rdd =>
Future{ writeRDD(rdd) }
})
Sometimes I get this error:
org.apache.spark.SparkException: Job aborted due to stage failure: Task creation failed: org.apache.spark.SparkException: Attempted to use BlockRDD[820] at actorStream at Tests.scala:149 after its blocks have been removed!
It seems like Spark is having trouble knowing when this RDD should be deleted.
Why is this happening and what is the solution?
Update:
I think RDDs might be GC'd before they are used. The only working solution so far involves setting
conf.set("spark.streaming.unpersist", "false")
And unpersist()-ing manually.
Full stack trace in case this is a bug:
15/10/12 23:57:23 ERROR org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation: Aborting job.
org.apache.spark.SparkException: Job aborted due to stage failure: Task creation failed: org.apache.spark.SparkException: Attempted to use BlockRDD[765] at actorStream at NxCoreSparkTests.scala:168 after its blocks have been removed!
org.apache.spark.rdd.BlockRDD.assertValid(BlockRDD.scala:83)
org.apache.spark.rdd.BlockRDD.getPreferredLocations(BlockRDD.scala:56)
org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:251)
org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:251)
scala.Option.getOrElse(Option.scala:120)
org.apache.spark.rdd.RDD.preferredLocations(RDD.scala:250)
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1394)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply$mcVI$sp(DAGScheduler.scala:1405)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
scala.collection.immutable.List.foreach(List.scala:318)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1404)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1402)
scala.collection.immutable.List.foreach(List.scala:318)
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1402)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply$mcVI$sp(DAGScheduler.scala:1405)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
scala.collection.immutable.List.foreach(List.scala:318)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1404)
org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1402)
scala.collection.immutable.List.foreach(List.scala:318)
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1402)
org.apache.spark.scheduler.DAGScheduler.getPreferredLocs(DAGScheduler.scala:1368)
org.apache.spark.scheduler.DAGScheduler$$anonfun$16.apply(DAGScheduler.scala:829)
org.apache.spark.scheduler.DAGScheduler$$anonfun$16.apply(DAGScheduler.scala:827)
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
scala.collection.Iterator$class.foreach(Iterator.scala:727)
scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
scala.collection.AbstractIterable.foreach(Iterable.scala:54)
scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
scala.collection.AbstractTraversable.map(Traversable.scala:105)
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:827)
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:772)
org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:757)
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1463)
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1455)
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1444)
org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1280)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1268)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1267)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1267)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:836)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:772)
at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:757)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1463)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1455)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1444)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1813)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1826)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:108)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:108)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:108)
at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57)
at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:57)
at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:69)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:140)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:138)
at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:927)
at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:927)
at org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:197)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:146)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:137)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:304)
at vscan.NxCoreSparkDbUtil$.writeToParquetByDay(NxCoreSparkTapeReader.scala:210)
at vscan.NxCoreSparkGoogleHDFS$$anonfun$6$$anonfun$apply$3$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(NxCoreSparkTests.scala:190)
at vscan.NxCoreSparkGoogleHDFS$$anonfun$6$$anonfun$apply$3$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(NxCoreSparkTests.scala:188)
at vscan.NxCoreSparkGoogleHDFS$$anonfun$6$$anonfun$apply$3$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(NxCoreSparkTests.scala:188)
at vscan.NxCoreSparkGoogleHDFS$.retry(NxCoreSparkTests.scala:217)
at vscan.NxCoreSparkGoogleHDFS$.retry(NxCoreSparkTests.scala:219)
at vscan.NxCoreSparkGoogleHDFS$.retry(NxCoreSparkTests.scala:219)
at vscan.NxCoreSparkGoogleHDFS$.retry(NxCoreSparkTests.scala:219)
at vscan.NxCoreSparkGoogleHDFS$.retry(NxCoreSparkTests.scala:219)
at vscan.NxCoreSparkGoogleHDFS$$anonfun$6$$anonfun$apply$3$$anonfun$1.apply$mcV$sp(NxCoreSparkTests.scala:188)
at vscan.NxCoreSparkGoogleHDFS$$anonfun$6$$anonfun$apply$3$$anonfun$1.apply(NxCoreSparkTests.scala:185)
at vscan.NxCoreSparkGoogleHDFS$$anonfun$6$$anonfun$apply$3$$anonfun$1.apply(NxCoreSparkTests.scala:185)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Attempted to use BlockRDD[765] at actorStream at NxCoreSparkTests.scala:168 after its blocks have been removed!
at org.apache.spark.rdd.BlockRDD.assertValid(BlockRDD.scala:83)
at org.apache.spark.rdd.BlockRDD.getPreferredLocations(BlockRDD.scala:56)
at org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:251)
at org.apache.spark.rdd.RDD$$anonfun$preferredLocations$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.preferredLocations(RDD.scala:250)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1394)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply$mcVI$sp(DAGScheduler.scala:1405)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1404)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1402)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1402)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply$mcVI$sp(DAGScheduler.scala:1405)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2$$anonfun$apply$2.apply(DAGScheduler.scala:1404)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1404)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal$2.apply(DAGScheduler.scala:1402)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1402)
at org.apache.spark.scheduler.DAGScheduler.getPreferredLocs(DAGScheduler.scala:1368)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$16.apply(DAGScheduler.scala:829)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$16.apply(DAGScheduler.scala:827)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:827)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:772)
at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:757)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1463)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1455)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1444)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
15/10/12 23:57:24 ERROR org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer: Job job_201510122357_0000 aborted.
I think the problem is that, before your code inside writeRDD(rdd) executes ( since it is in a Future ), the rdd ( or the micro-batch RDD ) is already reclaimed by Apache Spark memory-management or BlockManager.
Therefore, this error
org.apache.spark.SparkException: Job aborted due to stage failure: Task creation failed: org.apache.spark.SparkException: Attempted to use BlockRDD[820] at actorStream at Tests.scala:149 after its blocks have been removed!
You can fix this by first collecting the micro-batch collection and then passing it to writeRDD() function. Something like this:
dStreams.foreach(_.foreachRDD { rdd =>
val coll = rdd.collect()
Future{ writeCollection(coll) }
})
I am trying to load a (very big) serialized RDD of objects into the memory of a cluster of ec2 nodes, and then do some extraction on those objects and store the resulting RDD on disk (as object files). Unluckily I get SocketException: Connection reset once and SocketTimeoutException: Read timed out a few times.
Here is the relevant part of my code:
val pairsLocation = args(0)
val pairsRDD = sc.objectFile[Pair](pairLocation)
// taking individual objects out of "Pair" objects (containing two of those simple objects)
val extracted = pairsRDD.filter(myFunc(_._1)).
flatMap(x => List(x._1, x._2)).distinct
val savePath = "s3 URI"
extracted.saveAsObjectFile(savePath)
Here are the details of the errors (warnings) I get:
15/03/12 18:40:27 WARN scheduler.TaskSetManager: Lost task 574.0 in stage 0.0 (TID 574, ip-10-45-14-27.us-west-2.compute.internal):
java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:196)
at java.net.SocketInputStream.read(SocketInputStream.java:122)
at sun.security.ssl.InputRecord.readFully(InputRecord.java:442)
at sun.security.ssl.InputRecord.readV3Record(InputRecord.java:554)
at sun.security.ssl.InputRecord.read(InputRecord.java:509)
at sun.security.ssl.SSLSocketImpl.readRecord(SSLSocketImpl.java:934)
at sun.security.ssl.SSLSocketImpl.readDataRecord(SSLSocketImpl.java:891)
at sun.security.ssl.AppInputStream.read(AppInputStream.java:102)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:273)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at org.apache.commons.httpclient.ContentLengthInputStream.read(ContentLengthInputStream.java:170)
at java.io.FilterInputStream.read(FilterInputStream.java:133)
at org.apache.commons.httpclient.AutoCloseInputStream.read(AutoCloseInputStream.java:108)
at org.jets3t.service.io.InterruptableInputStream.read(InterruptableInputStream.java:76)
at org.jets3t.service.impl.rest.httpclient.HttpMethodReleaseInputStream.read(HttpMethodReleaseInputStream.java:136)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem$NativeS3FsInputStream.read(NativeS3FileSystem.java:98)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:275)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at org.apache.hadoop.io.DataOutputBuffer$Buffer.write(DataOutputBuffer.java:63)
at org.apache.hadoop.io.DataOutputBuffer.write(DataOutputBuffer.java:101)
at org.apache.hadoop.io.SequenceFile$Reader.next(SequenceFile.java:1988)
at org.apache.hadoop.io.SequenceFile$Reader.next(SequenceFile.java:2120)
at org.apache.hadoop.mapred.SequenceFileRecordReader.next(SequenceFileRecordReader.java:76)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:244)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:210)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:202)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:58)
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:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
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)
15/03/12 18:42:16 WARN scheduler.TaskSetManager: Lost task 380.0 in stage 0.0 (TID 380, ip-10-47-3-111.us-west-2.compute.internal):
java.net.SocketTimeoutException: Read timed out
at java.net.SocketInputStream.socketRead0(Native Method)
at java.net.SocketInputStream.read(SocketInputStream.java:152)
at java.net.SocketInputStream.read(SocketInputStream.java:122)
at sun.security.ssl.InputRecord.readFully(InputRecord.java:442)
at sun.security.ssl.InputRecord.readV3Record(InputRecord.java:554)
at sun.security.ssl.InputRecord.read(InputRecord.java:509)
at sun.security.ssl.SSLSocketImpl.readRecord(SSLSocketImpl.java:934)
at sun.security.ssl.SSLSocketImpl.readDataRecord(SSLSocketImpl.java:891)
at sun.security.ssl.AppInputStream.read(AppInputStream.java:102)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:273)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at org.apache.commons.httpclient.ContentLengthInputStream.read(ContentLengthInputStream.java:170)
at java.io.FilterInputStream.read(FilterInputStream.java:133)
at org.apache.commons.httpclient.AutoCloseInputStream.read(AutoCloseInputStream.java:108)
at org.jets3t.service.io.InterruptableInputStream.read(InterruptableInputStream.java:76)
at org.jets3t.service.impl.rest.httpclient.HttpMethodReleaseInputStream.read(HttpMethodReleaseInputStream.java:136)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem$NativeS3FsInputStream.read(NativeS3FileSystem.java:98)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:275)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at org.apache.hadoop.io.DataOutputBuffer$Buffer.write(DataOutputBuffer.java:63)
at org.apache.hadoop.io.DataOutputBuffer.write(DataOutputBuffer.java:101)
at org.apache.hadoop.io.SequenceFile$Reader.next(SequenceFile.java:1988)
at org.apache.hadoop.io.SequenceFile$Reader.next(SequenceFile.java:2120)
at org.apache.hadoop.mapred.SequenceFileRecordReader.next(SequenceFileRecordReader.java:76)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:244)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:210)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:202)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:58)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
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)