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From rxin <...@git.apache.org>
Subject [GitHub] spark pull request #15769: [SPARK-18191][CORE] Port RDD API to use commit pr...
Date Sun, 06 Nov 2016 21:43:16 GMT
Github user rxin commented on a diff in the pull request:

    https://github.com/apache/spark/pull/15769#discussion_r86697162
  
    --- Diff: core/src/main/scala/org/apache/spark/internal/io/SparkHadoopMapReduceWriter.scala
---
    @@ -0,0 +1,242 @@
    +/*
    + * 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, SparkContext, SparkException, TaskContext}
    +import org.apache.spark.deploy.SparkHadoopUtil
    +import org.apache.spark.executor.OutputMetrics
    +import org.apache.spark.internal.Logging
    +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 {
    +      sparkContext.runJob(rdd, (context: TaskContext, iter: Iterator[(K, V)]) => {
    --- End diff --
    
    we need to collect the result coming from the commit protocol here, and pass it into commitJob,
don't we?



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