Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/16517#discussion_r95298791
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveWriterContainers.scala ---
@@ -1,356 +0,0 @@
-/*
- * 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.sql.hive
-
-import java.text.NumberFormat
-import java.util.{Date, Locale}
-
-import scala.collection.JavaConverters._
-
-import org.apache.hadoop.fs.Path
-import org.apache.hadoop.hive.common.FileUtils
-import org.apache.hadoop.hive.conf.HiveConf.ConfVars
-import org.apache.hadoop.hive.ql.exec.{FileSinkOperator, Utilities}
-import org.apache.hadoop.hive.ql.io.{HiveFileFormatUtils, HiveOutputFormat}
-import org.apache.hadoop.hive.ql.plan.TableDesc
-import org.apache.hadoop.hive.serde2.Serializer
-import
org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspectorUtils,
StructObjectInspector}
-import
org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorUtils.ObjectInspectorCopyOption
-import org.apache.hadoop.io.Writable
-import org.apache.hadoop.mapred._
-import org.apache.hadoop.mapreduce.TaskType
-
-import org.apache.spark._
-import org.apache.spark.internal.Logging
-import org.apache.spark.internal.io.SparkHadoopWriterUtils
-import org.apache.spark.mapred.SparkHadoopMapRedUtil
-import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.execution.UnsafeKVExternalSorter
-import org.apache.spark.sql.hive.HiveShim.{ShimFileSinkDesc =>
FileSinkDesc}
-import org.apache.spark.sql.types._
-import org.apache.spark.util.SerializableJobConf
-import org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter
-
-/**
- * Internal helper class that saves an RDD using a Hive OutputFormat.
- * It is based on `SparkHadoopWriter`.
- */
-private[hive] class SparkHiveWriterContainer(
- @transient private val jobConf: JobConf,
- fileSinkConf: FileSinkDesc,
- inputSchema: Seq[Attribute])
- extends Logging
- with HiveInspectors
- with Serializable {
-
- private val now = new Date()
- private val tableDesc: TableDesc = fileSinkConf.getTableInfo
- // Add table properties from storage handler to jobConf, so any custom
storage
- // handler settings can be set to jobConf
- if (tableDesc != null) {
- HiveTableUtil.configureJobPropertiesForStorageHandler(tableDesc,
jobConf, false)
- Utilities.copyTableJobPropertiesToConf(tableDesc, jobConf)
- }
- protected val conf = new SerializableJobConf(jobConf)
-
- private var jobID = 0
- private var splitID = 0
- private var attemptID = 0
- private var jID: SerializableWritable[JobID] = null
- private var taID: SerializableWritable[TaskAttemptID] = null
-
- @transient private var writer: FileSinkOperator.RecordWriter = null
- @transient protected lazy val committer = conf.value.getOutputCommitter
- @transient protected lazy val jobContext = new
JobContextImpl(conf.value, jID.value)
- @transient private lazy val taskContext = new
TaskAttemptContextImpl(conf.value, taID.value)
- @transient private lazy val outputFormat =
- conf.value.getOutputFormat.asInstanceOf[HiveOutputFormat[AnyRef,
Writable]]
-
- def driverSideSetup() {
- setIDs(0, 0, 0)
- setConfParams()
- committer.setupJob(jobContext)
- }
-
- def executorSideSetup(jobId: Int, splitId: Int, attemptId: Int) {
- setIDs(jobId, splitId, attemptId)
- setConfParams()
- committer.setupTask(taskContext)
- initWriters()
- }
-
- protected def getOutputName: String = {
- val numberFormat = NumberFormat.getInstance(Locale.US)
- numberFormat.setMinimumIntegerDigits(5)
- numberFormat.setGroupingUsed(false)
- val extension = Utilities.getFileExtension(conf.value,
fileSinkConf.getCompressed, outputFormat)
- "part-" + numberFormat.format(splitID) + extension
- }
-
- def close() {
- // Seems the boolean value passed into close does not matter.
- if (writer != null) {
- writer.close(false)
- commit()
- }
- }
-
- def commitJob() {
- committer.commitJob(jobContext)
- }
-
- protected def initWriters() {
- // NOTE this method is executed at the executor side.
- // For Hive tables without partitions or with only static partitions,
only 1 writer is needed.
- writer = HiveFileFormatUtils.getHiveRecordWriter(
- conf.value,
- fileSinkConf.getTableInfo,
- conf.value.getOutputValueClass.asInstanceOf[Class[Writable]],
- fileSinkConf,
- FileOutputFormat.getTaskOutputPath(conf.value, getOutputName),
- Reporter.NULL)
- }
-
- protected def commit() {
- SparkHadoopMapRedUtil.commitTask(committer, taskContext, jobID,
splitID)
- }
-
- def abortTask(): Unit = {
- if (committer != null) {
- committer.abortTask(taskContext)
- }
- logError(s"Task attempt $taskContext aborted.")
- }
-
- private def setIDs(jobId: Int, splitId: Int, attemptId: Int) {
- jobID = jobId
- splitID = splitId
- attemptID = attemptId
-
- jID = new
SerializableWritable[JobID](SparkHadoopWriterUtils.createJobID(now, jobId))
- taID = new SerializableWritable[TaskAttemptID](
- new TaskAttemptID(new TaskID(jID.value, TaskType.MAP, splitID),
attemptID))
- }
-
- private def setConfParams() {
- conf.value.set("mapred.job.id", jID.value.toString)
- conf.value.set("mapred.tip.id", taID.value.getTaskID.toString)
- conf.value.set("mapred.task.id", taID.value.toString)
- conf.value.setBoolean("mapred.task.is.map", true)
- conf.value.setInt("mapred.task.partition", splitID)
- }
-
- def newSerializer(tableDesc: TableDesc): Serializer = {
- val serializer =
tableDesc.getDeserializerClass.newInstance().asInstanceOf[Serializer]
- serializer.initialize(null, tableDesc.getProperties)
- serializer
- }
-
- protected def prepareForWrite() = {
- val serializer = newSerializer(fileSinkConf.getTableInfo)
- val standardOI = ObjectInspectorUtils
- .getStandardObjectInspector(
- fileSinkConf.getTableInfo.getDeserializer.getObjectInspector,
- ObjectInspectorCopyOption.JAVA)
- .asInstanceOf[StructObjectInspector]
-
- val fieldOIs =
standardOI.getAllStructFieldRefs.asScala.map(_.getFieldObjectInspector).toArray
- val dataTypes = inputSchema.map(_.dataType)
- val wrappers = fieldOIs.zip(dataTypes).map { case (f, dt) =>
wrapperFor(f, dt) }
- val outputData = new Array[Any](fieldOIs.length)
- (serializer, standardOI, fieldOIs, dataTypes, wrappers, outputData)
- }
-
- // this function is executed on executor side
- def writeToFile(context: TaskContext, iterator: Iterator[InternalRow]):
Unit = {
- val (serializer, standardOI, fieldOIs, dataTypes, wrappers,
outputData) = prepareForWrite()
- executorSideSetup(context.stageId, context.partitionId,
context.attemptNumber)
-
- iterator.foreach { row =>
- var i = 0
- while (i < fieldOIs.length) {
- outputData(i) = if (row.isNullAt(i)) null else
wrappers(i)(row.get(i, dataTypes(i)))
- i += 1
- }
- writer.write(serializer.serialize(outputData, standardOI))
- }
-
- close()
- }
-}
-
-private[hive] object SparkHiveWriterContainer {
- 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 (outputPath == null || fs == null) {
- throw new IllegalArgumentException("Incorrectly formatted output
path")
- }
- outputPath.makeQualified(fs.getUri, fs.getWorkingDirectory)
- }
-}
-
-private[spark] object SparkHiveDynamicPartitionWriterContainer {
- val SUCCESSFUL_JOB_OUTPUT_DIR_MARKER =
"mapreduce.fileoutputcommitter.marksuccessfuljobs"
-}
-
-private[spark] class SparkHiveDynamicPartitionWriterContainer(
- jobConf: JobConf,
- fileSinkConf: FileSinkDesc,
- dynamicPartColNames: Array[String],
- inputSchema: Seq[Attribute])
- extends SparkHiveWriterContainer(jobConf, fileSinkConf, inputSchema) {
-
- import SparkHiveDynamicPartitionWriterContainer._
-
- private val defaultPartName = jobConf.get(
- ConfVars.DEFAULTPARTITIONNAME.varname,
ConfVars.DEFAULTPARTITIONNAME.defaultStrVal)
-
- override protected def initWriters(): Unit = {
- // do nothing
- }
-
- override def close(): Unit = {
- // do nothing
- }
-
- override def commitJob(): Unit = {
- // This is a hack to avoid writing _SUCCESS mark file. In lower
versions of Hadoop (e.g. 1.0.4),
--- End diff --
This hack is no longer needed, as we don't support hadoop 1.x now.
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