如何使用镶木地板在spark中读取和写入相同的文件？

时间：2016-05-05 18:32:52

标签： apache-spark overwrite parquet

我试图从spark中的镶木地板文件中读取，与另一个rdd进行联合，然后将结果写入我读过的同一个文件中（基本上覆盖），这会引发以下错误：

 couldnt write parquet to file: An error occurred while calling o102.parquet.
: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
TungstenExchange hashpartitioning(billID#42,200), None
+- Union
   :- Scan ParquetRelation[units#35,price#36,priceSold#37,orderingTime#38,itemID#39,storeID#40,customerID#41,billID#42,sourceRef#43] InputPaths: hdfs://master-wat:8020/user/root/dataFile/parquet/general/NPM61LKK1C/Billbody
   +- Project [units#22,price#23,priceSold#24,orderingTime#25,itemID#26,storeID#27,customerID#28,billID#29,2 AS sourceRef#30]
      +- Scan ExistingRDD[units#22,price#23,priceSold#24,orderingTime#25,itemID#26,storeID#27,customerID#28,billID#29] 

    at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:49)
    at org.apache.spark.sql.execution.Exchange.doExecute(Exchange.scala:247)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
    at org.apache.spark.sql.execution.Sort.doExecute(Sort.scala:64)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
    at org.apache.spark.sql.execution.Window.doExecute(Window.scala:245)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
    at org.apache.spark.sql.execution.Filter.doExecute(basicOperators.scala:70)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
    at org.apache.spark.sql.execution.Project.doExecute(basicOperators.scala:46)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
    at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
    at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
    at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelation.scala:109)
    at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:108)
    at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:108)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
    at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:108)
    at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
    at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
    at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
    at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
    at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
    at org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:256)
    at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:148)
    at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:139)
    at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:334)
    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:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
    at py4j.Gateway.invoke(Gateway.java:259)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:209)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.FileNotFoundException: File does not exist: /user/root/dataFile/parquet/general/NPM61LKK1C/Billbody/part-r-00000-c51e45d3-6824-4fc2-9510-802e5379a86f.gz.parquet
    at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:66)
    at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:56)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocationsUpdateTimes(FSNamesystem.java:1934)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocationsInt(FSNamesystem.java:1875)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocations(FSNamesystem.java:1855)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocations(FSNamesystem.java:1827)
    at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.getBlockLocations(NameNodeRpcServer.java:566)
    at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.getBlockLocations(AuthorizationProviderProxyClientProtocol.java:88)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.getBlockLocations(ClientNamenodeProtocolServerSideTranslatorPB.java:361)
    at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
    at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2086)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2082)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1693)
    at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2080)

    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    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:1222)
    at org.apache.hadoop.hdfs.DFSClient.getLocatedBlocks(DFSClient.java:1210)
    at org.apache.hadoop.hdfs.DFSClient.getBlockLocations(DFSClient.java:1260)
    at org.apache.hadoop.hdfs.DistributedFileSystem$1.doCall(DistributedFileSystem.java:220)
    at org.apache.hadoop.hdfs.DistributedFileSystem$1.doCall(DistributedFileSystem.java:216)
    at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
    at org.apache.hadoop.hdfs.DistributedFileSystem.getFileBlockLocations(DistributedFileSystem.java:216)
    at org.apache.hadoop.hdfs.DistributedFileSystem.getFileBlockLocations(DistributedFileSystem.java:208)
    at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.getSplits(FileInputFormat.java:395)
    at org.apache.parquet.hadoop.ParquetInputFormat.getSplits(ParquetInputFormat.java:294)
    at org.apache.spark.sql.execution.datasources.parquet.ParquetRelation$$anonfun$buildInternalScan$1$$anon$1.getPartitions(ParquetRelation.scala:363)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
    at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:66)
    at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:66)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
    at scala.collection.AbstractTraversable.map(Traversable.scala:105)
    at org.apache.spark.rdd.UnionRDD.getPartitions(UnionRDD.scala:66)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
    at org.apache.spark.ShuffleDependency.<init>(Dependency.scala:91)
    at org.apache.spark.sql.execution.Exchange.prepareShuffleDependency(Exchange.scala:220)
    at org.apache.spark.sql.execution.Exchange$$anonfun$doExecute$1.apply(Exchange.scala:254)
    at org.apache.spark.sql.execution.Exchange$$anonfun$doExecute$1.apply(Exchange.scala:248)
    at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:48)
    ... 56 more
Caused by: org.apache.hadoop.ipc.RemoteException(java.io.FileNotFoundException): File does not exist: /user/root/dataFile/parquet/general/NPM61LKK1C/Billbody/part-r-00000-c51e45d3-6824-4fc2-9510-802e5379a86f.gz.parquet
    at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:66)
    at org.apache.hadoop.hdfs.server.namenode.INodeFile.valueOf(INodeFile.java:56)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocationsUpdateTimes(FSNamesystem.java:1934)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocationsInt(FSNamesystem.java:1875)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocations(FSNamesystem.java:1855)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getBlockLocations(FSNamesystem.java:1827)
    at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.getBlockLocations(NameNodeRpcServer.java:566)
    at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.getBlockLocations(AuthorizationProviderProxyClientProtocol.java:88)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.getBlockLocations(ClientNamenodeProtocolServerSideTranslatorPB.java:361)
    at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
    at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2086)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2082)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1693)
    at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2080)

    at org.apache.hadoop.ipc.Client.call(Client.java:1468)
    at org.apache.hadoop.ipc.Client.call(Client.java:1399)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)
    at com.sun.proxy.$Proxy20.getBlockLocations(Unknown Source)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getBlockLocations(ClientNamenodeProtocolTranslatorPB.java:254)
    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.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
    at com.sun.proxy.$Proxy21.getBlockLocations(Unknown Source)
    at org.apache.hadoop.hdfs.DFSClient.callGetBlockLocations(DFSClient.java:1220)
    ... 92 more

我假设这意味着在写入文件时，联合需要原始文件，而火花不能再找到该文件。 我试过缓存我从镶木地板上读到的东西，以避免需要文件的火花，但这也没有用。任何有关Hadoop的最佳实践的帮助都非常感谢。

4 个答案:

答案 0 :(得分：2)

由于spark会进行延迟转换，因此基本上首先会擦除目标目录，然后再尝试从源位置读取。因此，您会收到此错误。

一种克服此问题的可能方法是在数据框上使用collect。为了避免获取OOM异常过滤器数据，请使用collect（）[1]。这将强制DAG首先读取数据并指定输出到驱动程序。因此，您的数据将在被覆盖之前先被读取。

答案 1 :(得分：0)

您必须在模式下使用覆盖选项，请尝试使用附加代替

  sequencer = MidiSystem.getSequencer(false);
  sequencer.open();
  Sequence sequence = MidiSystem.getSequence(midiFile);
  sequencer.setSequence(sequence);

  // outDevice=Java synth (Gervill)
  // or
  // outDevice=Edirol UA-25 (USB)
  Receiver outDeviceReceiver = outDevice.getReceiver();
  Transmitter seqTransmitter = sequencer.getTransmitter();
  seqTransmitter.setReceiver(outDeviceReceiver);

  int startLoopTick = 0;
  int endLoopTick = -1;  // Loop at end of sequence
  sequencer.setLoopStartPoint(startLoopTick);
  sequencer.setLoopEndPoint(endLoopTick);
  sequencer.setLoopCount(Sequencer.LOOP_CONTINUOUSLY);

  // if outDevice==Edirol there is a slight delay between loops
  sequencer.start();

答案 2 :(得分：0)

只是遇到了同样的问题...

您需要在联合之前先cache第一个命令。这样可以确保在写入磁盘之前将其从磁盘读取到内存中。

val cached = first.cache()
cached.union(second).write.mode("overwrite").parquet("...")

答案 3 :(得分：0)

您可以使用insertinto代替save。会的。 Df.write.mode（“ parquet”）。mode（“ overwrite”）。insertInto（file_path）

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