spark CodecStreams 源码

spark CodecStreams 代码

文件路径：/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/CodecStreams.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.execution.datasources

import java.io.{InputStream, OutputStream, OutputStreamWriter}
import java.nio.charset.{Charset, StandardCharsets}

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.Path
import org.apache.hadoop.io.compress._
import org.apache.hadoop.mapreduce.JobContext
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat
import org.apache.hadoop.util.ReflectionUtils

import org.apache.spark.TaskContext

object CodecStreams {
  private def getDecompressionCodec(config: Configuration, file: Path): Option[CompressionCodec] = {
    val compressionCodecs = new CompressionCodecFactory(config)
    Option(compressionCodecs.getCodec(file))
  }

  def createInputStream(config: Configuration, file: Path): InputStream = {
    val fs = file.getFileSystem(config)
    val inputStream: InputStream = fs.open(file)

    getDecompressionCodec(config, file)
      .map(codec => codec.createInputStream(inputStream))
      .getOrElse(inputStream)
  }

  /**
   * Creates an input stream from the given path and add a closure for the input stream to be
   * closed on task completion.
   */
  def createInputStreamWithCloseResource(config: Configuration, path: Path): InputStream = {
    val inputStream = createInputStream(config, path)
    Option(TaskContext.get()).foreach(_.addTaskCompletionListener[Unit](_ => inputStream.close()))
    inputStream
  }

  private def getCompressionCodec(
      context: JobContext,
      file: Option[Path] = None): Option[CompressionCodec] = {
    if (FileOutputFormat.getCompressOutput(context)) {
      val compressorClass = FileOutputFormat.getOutputCompressorClass(
        context,
        classOf[GzipCodec])

      Some(ReflectionUtils.newInstance(compressorClass, context.getConfiguration))
    } else {
      file.flatMap { path =>
        val compressionCodecs = new CompressionCodecFactory(context.getConfiguration)
        Option(compressionCodecs.getCodec(path))
      }
    }
  }

  /**
   * Create a new file and open it for writing.
   * If compression is enabled in the [[JobContext]] the stream will write compressed data to disk.
   * An exception will be thrown if the file already exists.
   */
  def createOutputStream(context: JobContext, file: Path): OutputStream = {
    val fs = file.getFileSystem(context.getConfiguration)
    val outputStream: OutputStream = fs.create(file, false)

    getCompressionCodec(context, Some(file))
      .map(codec => codec.createOutputStream(outputStream))
      .getOrElse(outputStream)
  }

  def createOutputStreamWriter(
      context: JobContext,
      file: Path,
      charset: Charset = StandardCharsets.UTF_8): OutputStreamWriter = {
    new OutputStreamWriter(createOutputStream(context, file), charset)
  }

  /** Returns the compression codec extension to be used in a file name, e.g. ".gzip"). */
  def getCompressionExtension(context: JobContext): String = {
    getCompressionCodec(context)
      .map(_.getDefaultExtension)
      .getOrElse("")
  }
}

相关信息

spark 源码目录

相关文章

spark AggregatePushDownUtils 源码

spark ApplyCharTypePadding 源码

spark BasicWriteStatsTracker 源码

spark BucketingUtils 源码

spark CatalogFileIndex 源码

spark DataSource 源码

spark DataSourceStrategy 源码

spark DataSourceUtils 源码

spark DaysWritable 源码

spark FallBackFileSourceV2 源码