I want to run a Spark Structured Streaming job locally on a single machine. Unfortunately, recovering from an aborted job does not work when the job was aborted while processing data (it fails with the log shown below).
(If the streaming job is aborted while waiting for new data, recovery works and checkpoint data is read correctly).
java.lang.IllegalStateException: Error reading delta file, spark structured streaming with kafka indicates that the reason might be that the local filesystem instead of HDFS is used to store checkpoints, however, checkpoint data is stored in HDFS in this case.
java.lang.IllegalStateException: Error reading delta file hdfs://localhost:9000/user/test/state/0/117/1.delta of HDFSStateStoreProvider[id = (op=0,part=117),dir = hdfs://localhost:9000/user/test/state/0/117]: hdfs://localhost:9000/user/test/state/0/117/1.delta does not exist
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.org$apache$spark$sql$execution$streaming$state$HDFSBackedStateStoreProvider$$updateFromDeltaFile(HDFSBackedStateStoreProvider.scala:427)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$$anonfun$6$$anonfun$apply$1.apply$mcVJ$sp(HDFSBackedStateStoreProvider.scala:384)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$$anonfun$6$$anonfun$apply$1.apply(HDFSBackedStateStoreProvider.scala:383)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$$anonfun$6$$anonfun$apply$1.apply(HDFSBackedStateStoreProvider.scala:383)
at scala.collection.immutable.NumericRange.foreach(NumericRange.scala:73)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$$anonfun$6.apply(HDFSBackedStateStoreProvider.scala:383)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$$anonfun$6.apply(HDFSBackedStateStoreProvider.scala:356)
at org.apache.spark.util.Utils$.timeTakenMs(Utils.scala:535)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.loadMap(HDFSBackedStateStoreProvider.scala:356)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.getStore(HDFSBackedStateStoreProvider.scala:204)
at org.apache.spark.sql.execution.streaming.state.StateStore$.get(StateStore.scala:371)
at org.apache.spark.sql.execution.streaming.state.StateStoreRDD.compute(StateStoreRDD.scala:88)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.FileNotFoundException: File does not exist: /user/test/state/0/117/1.delta
at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:72)
at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:62)
at org.apache.hadoop.hdfs.server.namenode.FSDirStatAndListingOp.getBlockLocations(FSDirStatAndListingOp.java:150)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocations(FSNamesystem.java:1829)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.getBlockLocations(NameNodeRpcServer.java:709)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.getBlockLocations(ClientNamenodeProtocolServerSideTranslatorPB.java:381)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:503)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:989)
at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:871)
at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:817)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1893)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2606)
at sun.reflect.GeneratedConstructorAccessor51.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.ipc.RemoteException.instantiateException(RemoteException.java:106)
at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:73)
at org.apache.hadoop.hdfs.DFSClient.callGetBlockLocations(DFSClient.java:1228)
at org.apache.hadoop.hdfs.DFSClient.getLocatedBlocks(DFSClient.java:1213)
at org.apache.hadoop.hdfs.DFSClient.getLocatedBlocks(DFSClient.java:1201)
at org.apache.hadoop.hdfs.DFSInputStream.fetchLocatedBlocksAndGetLastBlockLength(DFSInputStream.java:306)
at org.apache.hadoop.hdfs.DFSInputStream.openInfo(DFSInputStream.java:272)
at org.apache.hadoop.hdfs.DFSInputStream.<init>(DFSInputStream.java:264)
at org.apache.hadoop.hdfs.DFSClient.open(DFSClient.java:1526)
at org.apache.hadoop.fs.Hdfs.open(Hdfs.java:315)
at org.apache.hadoop.fs.Hdfs.open(Hdfs.java:58)
at org.apache.hadoop.fs.AbstractFileSystem.open(AbstractFileSystem.java:628)
at org.apache.hadoop.fs.FileContext$6.next(FileContext.java:795)
at org.apache.hadoop.fs.FileContext$6.next(FileContext.java:791)
at org.apache.hadoop.fs.FSLinkResolver.resolve(FSLinkResolver.java:90)
at org.apache.hadoop.fs.FileContext.open(FileContext.java:797)
at org.apache.spark.sql.execution.streaming.FileContextBasedCheckpointFileManager.open(CheckpointFileManager.scala:322)
at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.org$apache$spark$sql$execution$streaming$state$HDFSBackedStateStoreProvider$$updateFromDeltaFile(HDFSBackedStateStoreProvider.scala:424)
... 36 more
Caused by: org.apache.hadoop.ipc.RemoteException(java.io.FileNotFoundException): File does not exist: /user/test/state/0/117/1.delta
at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:72)
at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:62)
at org.apache.hadoop.hdfs.server.namenode.FSDirStatAndListingOp.getBlockLocations(FSDirStatAndListingOp.java:150)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocations(FSNamesystem.java:1829)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.getBlockLocations(NameNodeRpcServer.java:709)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.getBlockLocations(ClientNamenodeProtocolServerSideTranslatorPB.java:381)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:503)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:989)
at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:871)
at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:817)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1893)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2606)
at org.apache.hadoop.ipc.Client.call(Client.java:1475)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy22.getBlockLocations(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getBlockLocations(ClientNamenodeProtocolTranslatorPB.java:255)
at sun.reflect.GeneratedMethodAccessor39.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy23.getBlockLocations(Unknown Source)
at org.apache.hadoop.hdfs.DFSClient.callGetBlockLocations(DFSClient.java:1226)
... 51 more
It would be great if someone would know the reason for that.
Related
I am running a spark streaming application for reading data from kafka and dumping it into SQL but I am getting errors in the application, the application runs fin for a long period of time and then fails with the following error code.
log
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1651)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1639)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1638)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1638)
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:1872)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1821)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1810)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:935)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:933)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:933)
at org.apache.spark.sql.execution.streaming.ForeachSink.addBatch(ForeachSink.scala:49)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$3$$anonfun$apply$16.apply(MicroBatchExecution.scala:475)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$3.apply(MicroBatchExecution.scala:473)
at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:271)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:472)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:133)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:121)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:121)
at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:271)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:121)
at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:117)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
Caused by: java.util.ConcurrentModificationException: KafkaConsumer is not safe for multi-threaded access
at org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
at org.apache.kafka.clients.consumer.KafkaConsumer.close(KafkaConsumer.java:1361)
at org.apache.spark.sql.kafka010.CachedKafkaConsumer.close(CachedKafkaConsumer.scala:301)
at org.apache.spark.sql.kafka010.CachedKafkaConsumer$.removeKafkaConsumer(CachedKafkaConsumer.scala:377)
at org.apache.spark.sql.kafka010.CachedKafkaConsumer$.getOrCreate(CachedKafkaConsumer.scala:397)
at org.apache.spark.sql.kafka010.KafkaSourceRDD.compute(KafkaSourceRDD.scala:135)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:105)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
I am using Delta Lake to perform merge operation, for which I am trying to convert my Parquet files to delta format which are partitioned over time:
val source = spark.read.parquet("s3a://data-lake/source/")
source
.write
.option("maxRecordsPerFile",20000)
.mode("overwrite")
.partitionBy("time")
//.option("fs.s3a.committer.name", "partitioned") (I even tried using s3a committers)
.format("delta")
.save("s3a://data-lake/target/")
The data is over around 250G and my spark configs are:
spark.cores.max 420
spark.default.parallelism 10000
spark.delta.logStore.class org.apache.spark.sql.delta.storage.S3SingleDriverLogStore
spark.driver.extraJavaOptions -Xms20g
spark.driver.memory 28g
spark.executor.cores 2
spark.executor.memory 28G
In the logs it shows File Not Found Error and eventually kills executors after running for some time:
20/05/16 11:51:02 WARN TaskSetManager: Lost task 208.0 in stage 2.0 (TID 3294, 172.16.145.25, executor 14): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.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:170)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.FileNotFoundException: No such file or directory: s3a://data-lake/target/time=20190101/part-00208-2c9b5ddd-f2c1-4b8c-9d77-eacb0055ff82.c000.snappy.parquet
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:167)
... 53 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
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:170)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
I tried saving it as parquet format, it does work as expected. But it takes significantly more time to process.
If it's already in parquet, you can copy the folder in s3 to the target place without spark, and initialize it as a delta table with the following line:
import io.delta.DeltaTable
DeltaTable.forPath("s3a://data-lake/target/"))
More info here.
We run a spark streaming application(Spark version - 2.4.3) and we retrieve configuration from postgres DB using scheduled threads. We do this using spark
spark.read().format("jdbc").options(options).load()
Issue is that we notice that during a few iterations, the query is just stuck. With nothing happening. The calls after this one still work and the streaming operations continue. I extracted the thread dump and this is what I got.
java.net.SocketInputStream.socketRead0(Native Method)
java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
java.net.SocketInputStream.read(SocketInputStream.java:171)
java.net.SocketInputStream.read(SocketInputStream.java:141)
sun.security.ssl.InputRecord.readFully(InputRecord.java:465)
sun.security.ssl.InputRecord.read(InputRecord.java:503)
sun.security.ssl.SSLSocketImpl.readRecord(SSLSocketImpl.java:975) => holding Monitor(java.lang.Object#1651260651})
sun.security.ssl.SSLSocketImpl.readDataRecord(SSLSocketImpl.java:933)
sun.security.ssl.AppInputStream.read(AppInputStream.java:105) => holding Monitor(sun.security.ssl.AppInputStream#1497069430})
org.postgresql.core.VisibleBufferedInputStream.readMore(VisibleBufferedInputStream.java:143)
org.postgresql.core.VisibleBufferedInputStream.ensureBytes(VisibleBufferedInputStream.java:112)
org.postgresql.core.VisibleBufferedInputStream.read(VisibleBufferedInputStream.java:71)
org.postgresql.core.PGStream.ReceiveChar(PGStream.java:282)
org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:1803)
org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:255) => holding Monitor(org.postgresql.core.v3.QueryExecutorImpl#2049145458})
org.postgresql.jdbc2.AbstractJdbc2Statement.execute(AbstractJdbc2Statement.java:570)
org.postgresql.jdbc2.AbstractJdbc2Statement.executeWithFlags(AbstractJdbc2Statement.java:420)
org.postgresql.jdbc2.AbstractJdbc2Statement.executeQuery(AbstractJdbc2Statement.java:305)
org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:304)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
org.apache.spark.scheduler.Task.run(Task.scala:121)
org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
java.lang.Thread.run(Thread.java:748)
Any idea why this happens?
We encountered an error when run spark-submit command on AWS EMR cluster.
Our spark job previously was running on HDP cluster without any additional configuration in a scala code. When we start the job all executors throw errors about connection to Zookeeper node that don't exist on core nodes of EMR.
Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 8, ip-10-239-130-44.ec2.internal, executor 3): org.apache.hadoop.hbase.client.RetriesExhaustedException: Can't get the location for replica 0
at org.apache.hadoop.hbase.client.RpcRetryingCallerWithReadReplicas.getRegionLocations(RpcRetryingCallerWithReadReplicas.java:332)
at org.apache.hadoop.hbase.client.ScannerCallableWithReplicas.call(ScannerCallableWithReplicas.java:153)
at org.apache.hadoop.hbase.client.ScannerCallableWithReplicas.call(ScannerCallableWithReplicas.java:58)
at org.apache.hadoop.hbase.client.RpcRetryingCallerImpl.callWithoutRetries(RpcRetryingCallerImpl.java:192)
at org.apache.hadoop.hbase.client.ClientScanner.call(ClientScanner.java:269)
at org.apache.hadoop.hbase.client.ClientScanner.loadCache(ClientScanner.java:437)
at org.apache.hadoop.hbase.client.ClientScanner.nextWithSyncCache(ClientScanner.java:312)
at org.apache.hadoop.hbase.client.ClientScanner.next(ClientScanner.java:597)
at org.apache.spark.sql.execution.datasources.hbase.HBaseTableScanRDD$$anon$2.hasNext(HBaseTableScan.scala:286)
at scala.collection.Iterator$JoinIterator.hasNext(Iterator.scala:217)
at scala.collection.Iterator$ConcatIterator.hasNext(Iterator.scala:192)
at org.apache.spark.sql.execution.datasources.hbase.HBaseTableScanRDD$$anon$3.hasNext(HBaseTableScan.scala:314)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
at org.apache.spark.sql.execution.columnar.CachedRDDBuilder$$anonfun$1$$anon$1.hasNext(InMemoryRelation.scala:142)
at org.apache.spark.storage.memory.MemoryStore.putIterator(MemoryStore.scala:221)
at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:299)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1165)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1156)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1091)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1156)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:882)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
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)
Caused by: java.io.IOException: org.apache.zookeeper.KeeperException$ConnectionLossException: KeeperErrorCode = ConnectionLoss for /hbase/meta-region-server
at org.apache.hadoop.hbase.client.ConnectionImplementation.get(ConnectionImplementation.java:2009)
at org.apache.hadoop.hbase.client.ConnectionImplementation.locateMeta(ConnectionImplementation.java:785)
at org.apache.hadoop.hbase.client.ConnectionImplementation.locateRegion(ConnectionImplementation.java:752)
at org.apache.hadoop.hbase.client.ConnectionImplementation.relocateRegion(ConnectionImplementation.java:735)
at org.apache.hadoop.hbase.client.ConnectionImplementation.locateRegionInMeta(ConnectionImplementation.java:927)
at org.apache.hadoop.hbase.client.ConnectionImplementation.locateRegion(ConnectionImplementation.java:755)
at org.apache.hadoop.hbase.client.RpcRetryingCallerWithReadReplicas.getRegionLocations(RpcRetryingCallerWithReadReplicas.java:325)
... 46 more
Caused by: org.apache.zookeeper.KeeperException$ConnectionLossException: KeeperErrorCode = ConnectionLoss for /hbase/meta-region-server
at org.apache.zookeeper.KeeperException.create(KeeperException.java:99)
at org.apache.zookeeper.KeeperException.create(KeeperException.java:51)
at org.apache.hadoop.hbase.zookeeper.ReadOnlyZKClient$ZKTask$1.exec(ReadOnlyZKClient.java:189)
at org.apache.hadoop.hbase.zookeeper.ReadOnlyZKClient.run(ReadOnlyZKClient.java:323)
... 1 more
The Spark command:
spark-submit \
--conf spark.yarn.appMasterEnv.SPARK_HOME=/usr/lib/spark \
--conf spark.executor.memory=4g \
--conf spark.executor.cores=2 \
--class app_name \
--master yarn \
--deploy-mode client \
--jars ... -s hbase -i 13181_qatopilot -o /home/hadoop/s/d 2> last_ja-datascience.log
It seems that spark executor tried to connect on it's localhost to the port 2181 when actually Zookeeper node don't exist on executor:
20/02/02 09:00:19 WARN ClientCnxn: Session 0x0 for server null, unexpected error, closing socket connection and attempting reconnect
java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at org.apache.zookeeper.ClientCnxnSocketNIO.doTransport(ClientCnxnSocketNIO.java:361)
at org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1081)
20/02/02 09:00:19 WARN ReadOnlyZKClient: 0x19a6f47f to localhost:2181 failed for get of /hbase/hbaseid, code = CONNECTIONLOSS, retries = 28
20/02/02 09:00:20 INFO ClientCnxn: Opening socket connection to server localhost/127.0.0.1:2181. Will not attempt to authenticate using SASL (unknown error)
20/02/02 09:00:20 WARN ClientCnxn: Session 0x0 for server null, unexpected error, closing socket connection and attempting reconnect
java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at org.apache.zookeeper.ClientCnxnSocketNIO.doTransport(ClientCnxnSocketNIO.java:361)
at org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1081)
I am able to connect to Vertica through EMR (Spark), count and print schema but not able to read the data. Able to telnet from EMR.
My Vertica version
Vertica Database
09.02.0104
vertica.jar
09.01.0100
Spark-shell command
spark-shell --jars /home/hadoop/vertica-9.0.1_spark2.1_scala2.11.jar,/home/hadoop/vertica-
jdbc-9.0.1-7.jar
Query to read the Vertica table
val source = spark.read.format("com.vertica.spark.datasource.DefaultSource").option("host",
"verticaHost").option("port", "port").option("db", "DataBase?ssl=true").option("dbschema",
"Schemna").option("user", "user").option("password", "password").option("table",
"table").option("numPartitions", "1").option("queryTimeout", "500").load()
I also added .option("query", "select * from schema.table limit 100") and counted but it gave full count of the table instead of 100.
Output
source.printSchema() --> works, gets the schema information
source.count() --> works, gets the count.
source.show() --> Throws below error.
Error
java.sql.SQLNonTransientConnectionException: [Vertica][VJDBC](100176) Failed to connect to host xxxxxx on port xxxx. Reason: Failed to establish a connection to the primary server or any backup address.
at com.vertica.io.ProtocolStream.<init>(Unknown Source)
at com.vertica.core.VConnection.tryConnect(Unknown Source)
at com.vertica.core.VConnection.connect(Unknown Source)
at com.vertica.jdbc.common.BaseConnectionFactory.doConnect(Unknown Source)
at com.vertica.jdbc.common.AbstractDriver.connect(Unknown Source)
at java.sql.DriverManager.getConnection(DriverManager.java:664)
at java.sql.DriverManager.getConnection(DriverManager.java:208)
at com.vertica.spark.datasource.VerticaDataSourceRDD$.getConnector(VerticaRDD.scala:176)
at com.vertica.spark.datasource.VerticaDataSourceRDD$$anonfun$scanTable$1.apply(VerticaRDD.scala:205)
at com.vertica.spark.datasource.VerticaDataSourceRDD$$anonfun$scanTable$1.apply(VerticaRDD.scala:205)
at com.vertica.spark.datasource.VerticaDataSourceRDD$$anon$1.<init>(VerticaRDD.scala:338)
at com.vertica.spark.datasource.VerticaDataSourceRDD.compute(VerticaRDD.scala:330)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: com.vertica.support.exceptions.NonTransientConnectionException: [Vertica][VJDBC](100176) Failed to connect to host xxxxxx on port xxxx. Reason: Failed to establish a connection to the primary server or any backup address.
... 31 more
Caused by: java.io.IOException: Failed to establish a connection to the primary server or any backup address.
at com.vertica.io.VStream.establishConnection(Unknown Source)
at com.vertica.io.VStream.<init>(Unknown Source)
... 31 more
Caused by: java.net.ConnectException: Connection timed out (Connection timed out)
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:589)
at java.net.Socket.connect(Socket.java:538)
... 33 more
How can it count and print schema but not read it. Thanks in advance!