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Spark Streaming教程

时间:2015-07-13 13:42:31      阅读:2037      评论:0      收藏:0      [点我收藏+]

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废话不说,先来个示例,有个感性认识再介绍。

这个示例来自spark自带的example,基本步骤如下:

(1)使用以下命令输入流消息:

$ nc -lk 9999

(2)在一个新的终端中运行NetworkWordCount,统计上面的词语数量并输出:

$ bin/run-example streaming.NetworkWordCount localhost 9999

(3)在第一步创建的输入流程中敲入一些内容,在第二步创建的终端中会看到统计结果,如:

第一个终端输入的内容:

hello world again

第二个端口的输出

-------------------------------------------
Time: 1436758706000 ms
-------------------------------------------
(again,1)
(hello,1)
(world,1)

简单解释一下,上面的示例通过手工敲入内容,并传给spark streaming统计单词数量,然后将结果打印出来。

附上代码:

package org.apache.spark.examples.streaming

import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.storage.StorageLevel

/**
 * Counts words in UTF8 encoded, ‘\n‘ delimited text received from the network every second.
 *
 * Usage: NetworkWordCount <hostname> <port>
 * <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive data.
 *
 * To run this on your local machine, you need to first run a Netcat server
 *    `$ nc -lk 9999`
 * and then run the example
 *    `$ bin/run-example org.apache.spark.examples.streaming.NetworkWordCount localhost 9999`
 */
object NetworkWordCount {
  def main(args: Array[String]) {
    if (args.length < 2) {
      System.err.println("Usage: NetworkWordCount <hostname> <port>")
      System.exit(1)
    }

    StreamingExamples.setStreamingLogLevels()

    // Create the context with a 1 second batch size
    val sparkConf = new SparkConf().setAppName("NetworkWordCount")
    val ssc = new StreamingContext(sparkConf, Seconds(1))

    // Create a socket stream on target ip:port and count the
    // words in input stream of \n delimited text (eg. generated by ‘nc‘)
    // Note that no duplication in storage level only for running locally.
    // Replication necessary in distributed scenario for fault tolerance.
    val lines = ssc.socketTextStream(args(0), args(1).toInt, StorageLevel.MEMORY_AND_DISK_SER)
    val words = lines.flatMap(_.split(" "))
    val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)
    wordCounts.print()
    ssc.start()
    ssc.awaitTermination()
  }
}

  

Spark Streaming教程

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原文地址:http://www.cnblogs.com/lujinhong2/p/4642498.html

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