堆栈内存溢出
  繁体   English   中英

如何使用镶木地板在火花中读取和写入同一个文件？

[英]how to read and write to the same file in spark using parquet?

 原文  2016-05-05 18:32:52  5   6    apache-spark/ overwrite/ parquet

问题描述

我正在尝试从 spark 中的 parquet 文件中读取数据，与另一个 rdd 进行联合，然后将结果写入我读取过的同一文件中（基本上是覆盖），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，并且 spark 无法再找到该文件。 我已经尝试缓存我从镶木地板上读取的内容，以避免火花需要该文件，但这也不起作用。 非常感谢有关 Hadoop 最佳实践的任何帮助。

6 个解决方案

解决方案1
 3  2020-04-06 03:51:53

由于 spark 进行惰性转换，它基本上首先擦除您的目标目录，然后尝试从源位置读取。 因此，您收到此错误。

解决此问题的一种可能方法是在您的数据框上使用 collect 。 为避免获取 OOM 异常过滤器数据并使用 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被读取。

解决方案2
 2  2022-01-11 09:53:40

这会导致问题，因为您正在读取和写入您尝试覆盖的同一位置，这是 Spark 问题。

解决方法是将写入的数据存储在临时文件夹中，而不是在您正在处理的位置内，并从它作为源读取到您的初始位置。

  1. 从根目录/我的文件夹中读取
  2. 进行数据转换
  3. 将转换后的数据写入 root/mytemp 文件夹
  4. 从 root/mytemp 文件夹读取
  5. 写入根目录/我的文件夹

解决方案3
 0  2019-01-02 19:21:50

您必须在模式下使用覆盖选项，请尝试使用追加

df.repartition(200).write.mode("append").parquet("path/parquet_name")

解决方案4
 0  2019-01-14 03:00:54

刚遇到同样的问题...

您需要在联合之前cache第一个 rdd。 这将确保在您写入之前将其从磁盘读取到内存中。

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

解决方案5
 0  2022-06-22 08:03:30

尝试这个：

Df.write.format("parquet").mode("overwrite").insertInto(file_path)

解决方案6
 -1  2020-09-03 22:44:42

您可以使用 insertinto 而不是 save。 它会起作用的。 df.write.mode("parquet").mode("overwrite").insertInto(file_path)

暂无
暂无

声明:本站的技术帖子网页，遵循CC BY-SA 4.0协议，如果您需要转载，请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

相关问题 如何使用火花流读取.csv文件并使用Scala写入镶木地板文件？ Spark 如何使用同步 API 从数据写入镶木地板文件 如何使用spark（scala）读写（更新）同一个文件 如何使用Spark Core API读取Parquet文件？ 如何使用 spark 读取某些镶木地板文件分区？ 如何使用Spark写入128 MB实木复合地板文件 Spark：如何将Avro或镶木地板文件读取为数据集 如何使用 pyspark 在 Hadoop 中读取 parquet 文件、更改数据类型并写入另一个 Parquet 文件 使用火花读/写镶木地板文件期间的数据格式不一致 spark：读取实木复合地板文件并进行处理
相关标签
 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM