我有一个 8 小时的工作(spark 2.0.0)，它使用标准方法将结果写出到 Parquet :
processed_images_df.write.format("parquet").save(s3_output_path)
它执行 10000 个任务并将结果写入 _temporary 文件夹，并在最后一步(在所有任务完成后)从 _temporary 文件夹复制 Parquet 文件，但在复制大约 2-3000 个文件后，它失败并显示以下内容(第一我以为这是暂时的 s3 故障，但我重新运行了 3 次并得到相同的错误):
org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelationCommand.scala:149)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:86)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:86)
at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:487)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:211)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:194)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:211)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.http.NoHttpResponseException: s3-bucket.s3.amazonaws.com:443 failed to respond
at org.apache.http.impl.conn.DefaultHttpResponseParser.parseHead(DefaultHttpResponseParser.java:143)
at org.apache.http.impl.conn.DefaultHttpResponseParser.parseHead(DefaultHttpResponseParser.java:57)
at org.apache.http.impl.io.AbstractMessageParser.parse(AbstractMessageParser.java:261)
at org.apache.http.impl.AbstractHttpClientConnection.receiveResponseHeader(AbstractHttpClientConnection.java:283)
at org.apache.http.impl.conn.DefaultClientConnection.receiveResponseHeader(DefaultClientConnection.java:259)
at org.apache.http.impl.conn.AbstractClientConnAdapter.receiveResponseHeader(AbstractClientConnAdapter.java:232)
at org.apache.http.protocol.HttpRequestExecutor.doReceiveResponse(HttpRequestExecutor.java:272)
at org.apache.http.protocol.HttpRequestExecutor.execute(HttpRequestExecutor.java:124)
at org.apache.http.impl.client.DefaultRequestDirector.tryExecute(DefaultRequestDirector.java:686)
at org.apache.http.impl.client.DefaultRequestDirector.execute(DefaultRequestDirector.java:488)
at org.apache.http.impl.client.AbstractHttpClient.doExecute(AbstractHttpClient.java:884)
at org.apache.http.impl.client.CloseableHttpClient.execute(CloseableHttpClient.java:82)
at org.apache.http.impl.client.CloseableHttpClient.execute(CloseableHttpClient.java:55)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.performRequest(RestStorageService.java:326)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.performRequest(RestStorageService.java:277)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.performRestPut(RestStorageService.java:1143)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.copyObjectImpl(RestStorageService.java:2117)
at org.jets3t.service.StorageService.copyObject(StorageService.java:898)
at org.jets3t.service.StorageService.copyObject(StorageService.java:943)
at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.copy(Jets3tNativeFileSystemStore.java:320)
at sun.reflect.GeneratedMethodAccessor40.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:190)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:103)
at org.apache.hadoop.fs.s3native.$Proxy20.copy(Unknown Source)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem.rename(NativeS3FileSystem.java:645)
at org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:345)
at org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:362)
at org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJob(FileOutputCommitter.java:310)
at org.apache.parquet.hadoop.ParquetOutputCommitter.commitJob(ParquetOutputCommitter.java:46)
at org.apache.spark.sql.execution.datasources.BaseWriterContainer.commitJob(WriterContainer.scala:222)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelationCommand.scala:144)
... 29 more
最佳答案
我为这个问题找到的解决方案是将 Hadoop 更新到 2.7 并设置
spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version 2
在 Spark 1.6 中有一个直接写入 s3 的 fileoutputcommiter 的替代版本，但它在 spark 2.0.0 中被弃用:https://issues.apache.org/jira/browse/SPARK-10063
关于apache-spark - Apache Spark 写入 s3 无法从临时文件夹移动 Parquet 文件，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/39778587/