Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/15769#discussion_r86859239
--- Diff:
core/src/main/scala/org/apache/spark/internal/io/SparkHadoopMapReduceWriter.scala
---
@@ -0,0 +1,243 @@
+/*
+ * 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.SimpleDateFormat
+import java.util.{Date, Locale}
+
+import scala.reflect.ClassTag
+import scala.util.DynamicVariable
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.{JobConf, JobID}
+import org.apache.hadoop.mapreduce._
+import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl
+
+import org.apache.spark.{SparkConf, 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.RDD
+import org.apache.spark.util.{SerializableConfiguration, Utils}
+
+/**
+ * A helper object that saves an RDD using a Hadoop OutputFormat
+ * (from the newer mapreduce API, not the old mapred API).
+ */
+private[spark]
+object SparkHadoopMapReduceWriter extends Logging {
+
+ /**
+ * 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)],
+ hadoopConf: Configuration): Unit = {
+ // Extract context and configuration from RDD.
+ val sparkContext = rdd.context
+ val stageId = rdd.id
+ val sparkConf = rdd.conf
+ val conf = new SerializableConfiguration(hadoopConf)
+
+ // Set up a job.
+ val jobTrackerId = SparkHadoopWriterUtils.createJobTrackerID(new
Date())
+ val jobAttemptId = new TaskAttemptID(jobTrackerId, stageId,
TaskType.MAP, 0, 0)
+ val jobContext = new TaskAttemptContextImpl(conf.value, jobAttemptId)
+ val format = jobContext.getOutputFormatClass
+
+ if (SparkHadoopWriterUtils.isOutputSpecValidationEnabled(sparkConf)) {
+ // FileOutputFormat ignores the filesystem parameter
+ val jobFormat = format.newInstance
+ jobFormat.checkOutputSpecs(jobContext)
+ }
+
+ val committer = FileCommitProtocol.instantiate(
+ className = classOf[HadoopMapReduceCommitProtocol].getName,
+ jobId = stageId.toString,
+ outputPath = conf.value.get("mapred.output.dir"),
+ isAppend = false).asInstanceOf[HadoopMapReduceCommitProtocol]
+ 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.
+ if (SparkHadoopWriterUtils.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,
+ jobTrackerId = jobTrackerId,
+ sparkStageId = context.stageId,
+ sparkPartitionId = context.partitionId,
+ sparkAttemptNumber = context.attemptNumber,
+ committer = committer,
+ hadoopConf = conf.value,
+ outputFormat = format.asInstanceOf[Class[OutputFormat[K, V]]],
+ 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,
+ jobTrackerId: String,
+ sparkStageId: Int,
+ sparkPartitionId: Int,
+ sparkAttemptNumber: Int,
+ committer: FileCommitProtocol,
+ hadoopConf: Configuration,
+ outputFormat: Class[_ <: OutputFormat[K, V]],
+ iterator: Iterator[(K, V)]): TaskCommitMessage = {
+ // Set up a task.
+ val attemptId = new TaskAttemptID(jobTrackerId, sparkStageId,
TaskType.REDUCE,
+ sparkPartitionId, sparkAttemptNumber)
+ val taskContext = new TaskAttemptContextImpl(hadoopConf, attemptId)
+ committer.setupTask(taskContext)
+
+ val outputMetricsAndBytesWrittenCallback: Option[(OutputMetrics, () =>
Long)] =
+ SparkHadoopWriterUtils.initHadoopOutputMetrics(context)
+
+ // Initiate the writer.
+ val taskFormat = outputFormat.newInstance
+ val writer = taskFormat.getRecordWriter(taskContext)
+ .asInstanceOf[RecordWriter[K, V]]
+ require(writer != null, "Unable to obtain RecordWriter")
+ var recordsWritten = 0L
+
+ // Write all rows in RDD partition.
+ try {
+ Utils.tryWithSafeFinallyAndFailureCallbacks {
+ while (iterator.hasNext) {
+ val pair = iterator.next()
+ writer.write(pair._1, pair._2)
+
+ // Update bytes written metric every few records
+ SparkHadoopWriterUtils.maybeUpdateOutputMetrics(
+ outputMetricsAndBytesWrittenCallback, recordsWritten)
+ recordsWritten += 1
+ }
+
+ committer.commitTask(taskContext)
+ }(catchBlock = {
+ committer.abortTask(taskContext)
+ logError(s"Task ${taskContext.getTaskAttemptID} aborted.")
+ }, finallyBlock = writer.close(taskContext))
+ } catch {
+ case t: Throwable =>
+ throw new SparkException("Task failed while writing rows", t)
+ } finally {
+ outputMetricsAndBytesWrittenCallback.foreach { case (om, callback) =>
+ om.setBytesWritten(callback())
+ om.setRecordsWritten(recordsWritten)
+ }
+ }
+ }
+}
+
+private[spark]
+object SparkHadoopWriterUtils {
+ def createJobID(time: Date, id: Int): JobID = {
+ val jobtrackerID = createJobTrackerID(time)
+ new JobID(jobtrackerID, id)
+ }
+
+ def createJobTrackerID(time: Date): String = {
+ new SimpleDateFormat("yyyyMMddHHmmss", Locale.US).format(time)
+ }
+
+ def createPathFromString(path: String, conf: JobConf): Path = {
+ if (path == null) {
+ throw new IllegalArgumentException("Output path is null")
+ }
+ val outputPath = new Path(path)
+ val fs = outputPath.getFileSystem(conf)
+ if (fs == null) {
+ throw new IllegalArgumentException("Incorrectly formatted output
path")
+ }
+ outputPath.makeQualified(fs.getUri, fs.getWorkingDirectory)
+ }
+
+ // Note: this needs to be a function instead of a 'val' so that the
disableOutputSpecValidation
+ // setting can take effect:
+ def isOutputSpecValidationEnabled(conf: SparkConf): Boolean = {
+ val validationDisabled = disableOutputSpecValidation.value
+ val enabledInConf =
conf.getBoolean("spark.hadoop.validateOutputSpecs", true)
+ enabledInConf && !validationDisabled
+ }
+
+ def isSpeculationEnabled(conf: SparkConf): Boolean = {
+ conf.getBoolean("spark.speculation", false)
+ }
+
+ // TODO: these don't seem like the right abstractions.
+ // We should abstract the duplicate code in a less awkward way.
+
+ // return type: (output metrics, bytes written callback), defined only
if the latter is defined
+ def initHadoopOutputMetrics(
+ context: TaskContext): Option[(OutputMetrics, () => Long)] = {
+ val bytesWrittenCallback =
SparkHadoopUtil.get.getFSBytesWrittenOnThreadCallback()
+ bytesWrittenCallback.map { b =>
+ (context.taskMetrics().outputMetrics, b)
+ }
+ }
+
+ def maybeUpdateOutputMetrics(
+ outputMetricsAndBytesWrittenCallback: Option[(OutputMetrics, () =>
Long)],
+ recordsWritten: Long): Unit = {
+ if (recordsWritten % RECORDS_BETWEEN_BYTES_WRITTEN_METRIC_UPDATES ==
0) {
+ outputMetricsAndBytesWrittenCallback.foreach { case (om, callback) =>
+ om.setBytesWritten(callback())
+ om.setRecordsWritten(recordsWritten)
+ }
+ }
+ }
+
+ val RECORDS_BETWEEN_BYTES_WRITTEN_METRIC_UPDATES = 256
--- End diff --
private and move it to top of the object ?
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