本教程主要總結SparkStreaming並打包在叢集上提交的方式。

需要先開啟

$ nc -lk 9999

程式碼：

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

object SparkStreamingDemo {
  def main(args: Array[String]) {
    if (args.length < 2) {
      System.err.println("Usage: NetworkWordCount <hostname> <port>")
      System.exit(1)
    }

   // SparkStreamingDemo.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()
  }
 

後面的localhost 9999是輸入引數
// spark-submit  --queue media --class test.SparkStreamingDemo  --master yarn-cluster --executor-memory 2g  --executor-cores 2 --conf spark.yarn.submit.waitAppCompletion=false  ~/home/SparkStreamingDemo-1.0-SNAPSHOT.jar  localhost 9999