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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