Spark系列--Spark Streaming(二)IDEA编写Spark Streaming--NetWordCount程序

前言

前面介绍了Spark Streaming的相关概念，这里我们使用IDEA编写Spark Streaming基于Socket数据流进行的WordCount。

一、IDEA编写NetWordCount

在原有的SparkCore项目基础上，添加Spark Streaming项目依赖：

<dependency>

    <groupId>org.apache.sparkgroupId>

    <artifactId>spark-streaming_2.11artifactId>

    <version>${spark.version}version>

    

dependency>

NetWordCount完整代码如下：

package com.m.jd.streaming

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

object NetWordCount  {

  def main(args: Array[String]): Unit = {

    val conf = new SparkConf().setMaster("local[*]").setAppName("NetworkWordCount")
    val ssc = new StreamingContext(conf, Seconds(1))

    // Create a DStream that will connect to hostname:port, like localhost:9999
    val lines = ssc.socketTextStream(args(0),args(1).toInt)

    // Split each line into words
    val words = lines.flatMap(_.split(" "))

    //import org.apache.spark.streaming.StreamingContext._ // not necessary since Spark 1.3
    // Count each word in each batch
    val pairs = words.map(word => (word, 1))
    val wordCounts = pairs.reduceByKey(_ + _)

    // Print the first ten elements of each RDD generated in this DStream to the console
    wordCounts.print()

    ssc.start()             // Start the computation
    ssc.awaitTermination()  // Wait for the computation to terminate

    //ssc.stop()

  }
}

二、执行

按照Spark Core中的方式进行打包，并将程序上传到Spark机器上。并运行：

bin/spark-submit --class com.m.jd.streaming.NetWordCount /opt/spark-jar/networdcount-jar-with-dependencies.jar hadoop0 9999

上述命令启动的时候会去监听hadoop0:9999端口，在启动过程中，如果没有先执行

$ nc -lk 9999

会出现类似hadoop0:9999连接被拒绝的日志，所以最好先在hadoop0上执行上述nc命令，如果程序运行时，log日志太多，可以将spark conf目录下的log4j文件里面的日志级别改成WARN。

运行结果如下：

[root@hadoop0 ~]# nc -lk 9999
hadoop kkkk

-------------------------------------------
Time: 1532682169000 ms
-------------------------------------------
(kkkk,1)
(hadoop,1)

更多可以查看官方文档：
http://spark.apache.org/docs/latest/streaming-programming-guide.html#a-quick-example