Github user mridulm commented on a diff in the pull request: https://github.com/apache/spark/pull/15861#discussion_r90120144 --- Diff: core/src/main/scala/org/apache/spark/internal/io/SparkHadoopWriter.scala --- @@ -0,0 +1,408 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.internal.io + +import java.text.NumberFormat +import java.util.{Date, Locale} + +import scala.reflect.ClassTag + +import org.apache.hadoop.conf.{Configurable, Configuration} +import org.apache.hadoop.fs.FileSystem +import org.apache.hadoop.mapred._ +import org.apache.hadoop.mapreduce.{JobContext => NewJobContext, OutputFormat => NewOutputFormat, RecordWriter => NewRecordWriter, TaskAttemptContext => NewTaskAttemptContext, TaskAttemptID => NewTaskAttemptID, TaskType} +import org.apache.hadoop.mapreduce.task.{TaskAttemptContextImpl => NewTaskAttemptContextImpl} + +import org.apache.spark.{SerializableWritable, SparkException, TaskContext} +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.executor.OutputMetrics +import org.apache.spark.internal.Logging +import org.apache.spark.internal.io.FileCommitProtocol.TaskCommitMessage +import org.apache.spark.rdd.{HadoopRDD, RDD} +import org.apache.spark.util.{SerializableConfiguration, SerializableJobConf, Utils} + +/** + * A helper object that saves an RDD using a Hadoop OutputFormat + * (from the old mapred API). + */ +private[spark] +object SparkHadoopWriter extends Logging { + import SparkHadoopWriterUtils._ + + /** + * Basic work flow of this command is: + * 1. Driver side setup, prepare the data source and hadoop configuration for the write job to + * be issued. + * 2. Issues a write job consists of one or more executor side tasks, each of which writes all + * rows within an RDD partition. + * 3. If no exception is thrown in a task, commits that task, otherwise aborts that task; If any + * exception is thrown during task commitment, also aborts that task. + * 4. If all tasks are committed, commit the job, otherwise aborts the job; If any exception is + * thrown during job commitment, also aborts the job. + */ + def write[K, V: ClassTag]( + rdd: RDD[(K, V)], + config: HadoopWriteConfigUtil[K, V]): Unit = { + // Extract context and configuration from RDD. + val sparkContext = rdd.context + val stageId = rdd.id + val sparkConf = rdd.conf + + // Set up a job. + val jobTrackerId = createJobTrackerID(new Date()) + val jobContext = config.createJobContext(jobTrackerId, stageId) + config.initOutputFormat(jobContext) + + // Assert the output format/key/value class is set in JobConf. + config.assertConf() + + if (isOutputSpecValidationEnabled(sparkConf)) { + // FileOutputFormat ignores the filesystem parameter + config.checkOutputSpecs(jobContext) + } + + val committer = config.createCommitter(stageId) + committer.setupJob(jobContext) + + // When speculation is on and output committer class name contains "Direct", we should warn + // users that they may loss data if they are using a direct output committer. + // There is an example in https://issues.apache.org/jira/browse/SPARK-10063 to show the bad + // result of using direct output committer with speculation enabled. + if (isSpeculationEnabled(sparkConf) && committer.isDirectOutput) { + val warningMessage = + s"$committer may be an output committer that writes data directly to " + + "the final location. Because speculation is enabled, this output committer may " + + "cause data loss (see the case in SPARK-10063). If possible, please use an output " + + "committer that does not have this behavior (e.g. FileOutputCommitter)." + logWarning(warningMessage) + } + + // Try to write all RDD partitions as a Hadoop OutputFormat. + try { + val ret = sparkContext.runJob(rdd, (context: TaskContext, iter: Iterator[(K, V)]) => { + executeTask( + context = context, + config = config, + jobTrackerId = jobTrackerId, + sparkStageId = context.stageId, + sparkPartitionId = context.partitionId, + sparkAttemptNumber = context.attemptNumber, + committer = committer, + iterator = iter) + }) + + committer.commitJob(jobContext, ret) + logInfo(s"Job ${jobContext.getJobID} committed.") + } catch { + case cause: Throwable => + logError(s"Aborting job ${jobContext.getJobID}.", cause) + committer.abortJob(jobContext) + throw new SparkException("Job aborted.", cause) + } + } + + /** Write a RDD partition out in a single Spark task. */ + private def executeTask[K, V: ClassTag]( + context: TaskContext, + config: HadoopWriteConfigUtil[K, V], + jobTrackerId: String, + sparkStageId: Int, + sparkPartitionId: Int, + sparkAttemptNumber: Int, + committer: FileCommitProtocol, + iterator: Iterator[(K, V)]): TaskCommitMessage = { + // Set up a task. + val taskContext = config.createTaskAttemptContext( + jobTrackerId, sparkStageId, sparkPartitionId, sparkAttemptNumber) + committer.setupTask(taskContext) + + val outputMetricsAndBytesWrittenCallback: Option[(OutputMetrics, () => Long)] = + initHadoopOutputMetrics(context) + + // Initiate the writer. + config.initWriter(taskContext, sparkPartitionId) + var recordsWritten = 0L + + // Write all rows in RDD partition. + try { + val ret = Utils.tryWithSafeFinallyAndFailureCallbacks { + while (iterator.hasNext) { + val pair = iterator.next() + config.write(pair) + + // Update bytes written metric every few records + maybeUpdateOutputMetrics( + outputMetricsAndBytesWrittenCallback, recordsWritten) + recordsWritten += 1 + } + + committer.commitTask(taskContext) + }(catchBlock = { + committer.abortTask(taskContext) + logError(s"Task ${taskContext.getTaskAttemptID} aborted.") + }, finallyBlock = config.closeWriter(taskContext)) + + outputMetricsAndBytesWrittenCallback.foreach { + case (om, callback) => + om.setBytesWritten(callback()) + om.setRecordsWritten(recordsWritten) + } + + ret + } catch { + case t: Throwable => + throw new SparkException("Task failed while writing rows", t) + } + } +} + +/** + * A helper class that reads JobConf from older mapred API, creates output Format/Committer/Writer. + */ +private[spark] +class HadoopMapRedWriteConfigUtil[K, V: ClassTag](conf: SerializableJobConf) + extends HadoopWriteConfigUtil[K, V] with Logging { + + private var outputFormat: Class[_ <: OutputFormat[K, V]] = null + private var writer: RecordWriter[K, V] = null + + private def getConf(): JobConf = conf.value --- End diff -- getConf() -> getConf
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