spark RawInputDStream 源码

  • 2022-10-20
  • 浏览 (206)

spark RawInputDStream 代码

文件路径:/streaming/src/main/scala/org/apache/spark/streaming/dstream/RawInputDStream.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.dstream

import java.io.EOFException
import java.net.InetSocketAddress
import java.nio.ByteBuffer
import java.nio.channels.{ReadableByteChannel, SocketChannel}
import java.util.concurrent.ArrayBlockingQueue

import scala.reflect.ClassTag

import org.apache.spark.internal.Logging
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.receiver.Receiver

/**
 * An input stream that reads blocks of serialized objects from a given network address.
 * The blocks will be inserted directly into the block store. This is the fastest way to get
 * data into Spark Streaming, though it requires the sender to batch data and serialize it
 * in the format that the system is configured with.
 */
private[streaming]
class RawInputDStream[T: ClassTag](
    _ssc: StreamingContext,
    host: String,
    port: Int,
    storageLevel: StorageLevel
  ) extends ReceiverInputDStream[T](_ssc) with Logging {

  def getReceiver(): Receiver[T] = {
    new RawNetworkReceiver(host, port, storageLevel).asInstanceOf[Receiver[T]]
  }
}

private[streaming]
class RawNetworkReceiver(host: String, port: Int, storageLevel: StorageLevel)
  extends Receiver[Any](storageLevel) with Logging {

  var blockPushingThread: Thread = null

  def onStart(): Unit = {
    // Open a socket to the target address and keep reading from it
    logInfo("Connecting to " + host + ":" + port)
    val channel = SocketChannel.open()
    channel.configureBlocking(true)
    channel.connect(new InetSocketAddress(host, port))
    logInfo("Connected to " + host + ":" + port)

    val queue = new ArrayBlockingQueue[ByteBuffer](2)

    blockPushingThread = new Thread {
      setDaemon(true)
      override def run(): Unit = {
        var nextBlockNumber = 0
        while (true) {
          val buffer = queue.take()
          nextBlockNumber += 1
          store(buffer)
        }
      }
    }
    blockPushingThread.start()

    val lengthBuffer = ByteBuffer.allocate(4)
    while (true) {
      lengthBuffer.clear()
      readFully(channel, lengthBuffer)
      lengthBuffer.flip()
      val length = lengthBuffer.getInt()
      val dataBuffer = ByteBuffer.allocate(length)
      readFully(channel, dataBuffer)
      dataBuffer.flip()
      logInfo("Read a block with " + length + " bytes")
      queue.put(dataBuffer)
    }
  }

  def onStop(): Unit = {
    if (blockPushingThread != null) blockPushingThread.interrupt()
  }

  /** Read a buffer fully from a given Channel */
  private def readFully(channel: ReadableByteChannel, dest: ByteBuffer): Unit = {
    while (dest.position() < dest.limit()) {
      if (channel.read(dest) == -1) {
        throw new EOFException("End of channel")
      }
    }
  }
}

相关信息

spark 源码目录

相关文章

spark ConstantInputDStream 源码

spark DStream 源码

spark DStreamCheckpointData 源码

spark FileInputDStream 源码

spark FilteredDStream 源码

spark FlatMapValuedDStream 源码

spark FlatMappedDStream 源码

spark ForEachDStream 源码

spark GlommedDStream 源码

spark InputDStream 源码

0  赞