spark HdfsUtils 源码

  • 2022-10-20
  • 浏览 (538)

spark HdfsUtils 代码

文件路径:/streaming/src/main/scala/org/apache/spark/streaming/util/HdfsUtils.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.streaming.util

import java.io.{FileNotFoundException, IOException}

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs._

import org.apache.spark.deploy.SparkHadoopUtil

private[streaming] object HdfsUtils {

  def getOutputStream(path: String, conf: Configuration): FSDataOutputStream = {
    val dfsPath = new Path(path)
    val dfs = getFileSystemForPath(dfsPath, conf)
    // If the file exists and we have append support, append instead of creating a new file
    val stream: FSDataOutputStream = {
      if (dfs.isFile(dfsPath)) {
        if (conf.getBoolean("dfs.support.append", true) ||
            conf.getBoolean("hdfs.append.support", false) ||
            dfs.isInstanceOf[RawLocalFileSystem]) {
          dfs.append(dfsPath)
        } else {
          throw new IllegalStateException("File exists and there is no append support!")
        }
      } else {
        // we don't want to use hdfs erasure coding, as that lacks support for append and hflush
        SparkHadoopUtil.createFile(dfs, dfsPath, false)
      }
    }
    stream
  }

  def getInputStream(path: String, conf: Configuration): FSDataInputStream = {
    val dfsPath = new Path(path)
    val dfs = getFileSystemForPath(dfsPath, conf)
    try {
      dfs.open(dfsPath)
    } catch {
      case _: FileNotFoundException =>
        null
      case e: IOException =>
        // If we are really unlucky, the file may be deleted as we're opening the stream.
        // This can happen as clean up is performed by daemon threads that may be left over from
        // previous runs.
        if (!dfs.getFileStatus(dfsPath).isFile) null else throw e
    }
  }

  def checkState(state: Boolean, errorMsg: => String): Unit = {
    if (!state) {
      throw new IllegalStateException(errorMsg)
    }
  }

  /** Get the locations of the HDFS blocks containing the given file segment. */
  def getFileSegmentLocations(
      path: String, offset: Long, length: Long, conf: Configuration): Array[String] = {
    val dfsPath = new Path(path)
    val dfs = getFileSystemForPath(dfsPath, conf)
    val fileStatus = dfs.getFileStatus(dfsPath)
    val blockLocs = Option(dfs.getFileBlockLocations(fileStatus, offset, length))
    blockLocs.map(_.flatMap(_.getHosts)).getOrElse(Array.empty)
  }

  def getFileSystemForPath(path: Path, conf: Configuration): FileSystem = {
    // For local file systems, return the raw local file system, such calls to flush()
    // actually flushes the stream.
    val fs = path.getFileSystem(conf)
    fs match {
      case localFs: LocalFileSystem => localFs.getRawFileSystem
      case _ => fs
    }
  }

  /** Check if the file exists at the given path. */
  def checkFileExists(path: String, conf: Configuration): Boolean = {
    val hdpPath = new Path(path)
    val fs = getFileSystemForPath(hdpPath, conf)
    try {
      fs.getFileStatus(hdpPath).isFile
    } catch {
      case _: FileNotFoundException => false
    }
  }
}

相关信息

spark 源码目录

相关文章

spark BatchedWriteAheadLog 源码

spark FileBasedWriteAheadLog 源码

spark FileBasedWriteAheadLogRandomReader 源码

spark FileBasedWriteAheadLogReader 源码

spark FileBasedWriteAheadLogSegment 源码

spark FileBasedWriteAheadLogWriter 源码

spark RateLimitedOutputStream 源码

spark RawTextHelper 源码

spark RawTextSender 源码

spark RecurringTimer 源码

0  赞