spark HiveFileFormat 源码

  • 2022-10-20
  • 浏览 (289)

spark HiveFileFormat 代码

文件路径:/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveFileFormat.scala

/*
 * 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.execution

import scala.collection.JavaConverters._

import org.apache.hadoop.fs.{FileStatus, Path}
import org.apache.hadoop.hive.ql.exec.Utilities
import org.apache.hadoop.hive.ql.io.{HiveFileFormatUtils, HiveOutputFormat}
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.hive.serde2.typeinfo.TypeInfoUtils
import org.apache.hadoop.io.Writable
import org.apache.hadoop.mapred.{JobConf, Reporter}
import org.apache.hadoop.mapreduce.{Job, TaskAttemptContext}

import org.apache.spark.internal.Logging
import org.apache.spark.internal.config.SPECULATION_ENABLED
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.errors.QueryExecutionErrors
import org.apache.spark.sql.execution.datasources.{FileFormat, OutputWriter, OutputWriterFactory}
import org.apache.spark.sql.hive.{HiveInspectors, HiveTableUtil}
import org.apache.spark.sql.hive.HiveShim.{ShimFileSinkDesc => FileSinkDesc}
import org.apache.spark.sql.sources.DataSourceRegister
import org.apache.spark.sql.types.StructType
import org.apache.spark.util.SerializableJobConf

/**
 * `FileFormat` for writing Hive tables.
 *
 * TODO: implement the read logic.
 */
class HiveFileFormat(fileSinkConf: FileSinkDesc)
  extends FileFormat with DataSourceRegister with Logging {

  def this() = this(null)

  override def shortName(): String = "hive"

  override def inferSchema(
      sparkSession: SparkSession,
      options: Map[String, String],
      files: Seq[FileStatus]): Option[StructType] = {
    throw QueryExecutionErrors.inferSchemaUnsupportedForHiveError()
  }

  override def prepareWrite(
      sparkSession: SparkSession,
      job: Job,
      options: Map[String, String],
      dataSchema: StructType): OutputWriterFactory = {
    val conf = job.getConfiguration
    val tableDesc = fileSinkConf.getTableInfo
    conf.set("mapred.output.format.class", tableDesc.getOutputFileFormatClassName)

    // 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.
    val speculationEnabled = sparkSession.sparkContext.conf.get(SPECULATION_ENABLED)
    val outputCommitterClass = conf.get("mapred.output.committer.class", "")
    if (speculationEnabled && outputCommitterClass.contains("Direct")) {
      val warningMessage =
        s"$outputCommitterClass 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)
    }

    // Add table properties from storage handler to hadoopConf, so any custom storage
    // handler settings can be set to hadoopConf
    HiveTableUtil.configureJobPropertiesForStorageHandler(tableDesc, conf, false)
    Utilities.copyTableJobPropertiesToConf(tableDesc, conf)

    // Avoid referencing the outer object.
    val fileSinkConfSer = fileSinkConf
    new OutputWriterFactory {
      private val jobConf = new SerializableJobConf(new JobConf(conf))
      @transient private lazy val outputFormat =
        jobConf.value.getOutputFormat.asInstanceOf[HiveOutputFormat[AnyRef, Writable]]

      override def getFileExtension(context: TaskAttemptContext): String = {
        Utilities.getFileExtension(jobConf.value, fileSinkConfSer.getCompressed, outputFormat)
      }

      override def newInstance(
          path: String,
          dataSchema: StructType,
          context: TaskAttemptContext): OutputWriter = {
        new HiveOutputWriter(path, fileSinkConfSer, jobConf.value, dataSchema)
      }
    }
  }

  override def supportFieldName(name: String): Boolean = {
    fileSinkConf.getTableInfo.getOutputFileFormatClassName match {
      case "org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat" =>
        !name.matches(".*[ ,;{}()\n\t=].*")
      case "org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat" =>
        try {
          TypeInfoUtils.getTypeInfoFromTypeString(s"struct<$name:int>")
          true
        } catch {
          case _: IllegalArgumentException => false
        }
      case _ => true
    }
  }
}

class HiveOutputWriter(
    val path: String,
    fileSinkConf: FileSinkDesc,
    jobConf: JobConf,
    dataSchema: StructType) extends OutputWriter with HiveInspectors {

  private def tableDesc = fileSinkConf.getTableInfo

  private val serializer = {
    val serializer = tableDesc.getDeserializerClass.getConstructor().
      newInstance().asInstanceOf[Serializer]
    serializer.initialize(jobConf, tableDesc.getProperties)
    serializer
  }

  private val hiveWriter = HiveFileFormatUtils.getHiveRecordWriter(
    jobConf,
    tableDesc,
    serializer.getSerializedClass,
    fileSinkConf,
    new Path(path),
    Reporter.NULL)

  /**
   * Since SPARK-30201 ObjectInspectorCopyOption.JAVA change to ObjectInspectorCopyOption.DEFAULT.
   * The reason is DEFAULT option can convert `UTF8String` to `Text` with bytes and
   * we can compatible with non UTF-8 code bytes during write.
   */
  private val standardOI = ObjectInspectorUtils
    .getStandardObjectInspector(
      tableDesc.getDeserializer(jobConf).getObjectInspector,
      ObjectInspectorCopyOption.DEFAULT)
    .asInstanceOf[StructObjectInspector]

  private val fieldOIs =
    standardOI.getAllStructFieldRefs.asScala.map(_.getFieldObjectInspector).toArray
  private val dataTypes = dataSchema.map(_.dataType).toArray
  private val wrappers = fieldOIs.zip(dataTypes).map { case (f, dt) => wrapperFor(f, dt) }
  private val outputData = new Array[Any](fieldOIs.length)

  override def write(row: InternalRow): Unit = {
    var i = 0
    while (i < fieldOIs.length) {
      outputData(i) = if (row.isNullAt(i)) null else wrappers(i)(row.get(i, dataTypes(i)))
      i += 1
    }
    hiveWriter.write(serializer.serialize(outputData, standardOI))
  }

  override def close(): Unit = {
    // Seems the boolean value passed into close does not matter.
    hiveWriter.close(false)
  }
}

相关信息

spark 源码目录

相关文章

spark CreateHiveTableAsSelectCommand 源码

spark HiveOptions 源码

spark HiveScriptTransformationExec 源码

spark HiveTableScanExec 源码

spark InsertIntoHiveDirCommand 源码

spark InsertIntoHiveTable 源码

spark PruneHiveTablePartitions 源码

spark SaveAsHiveFile 源码

spark V1WritesHiveUtils 源码

0  赞