SparkStreaming整合Kafka--Receiver方式

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package com.zoujc.sparkstreaming

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


/**
  * Spark Streaming 基于 Receiver 对接Kafka
  */
object KafkaReceiver {
   def main(args: Array[String]): Unit = {
      if (args.length != 4) {
         System.err.println("Usage: KafkaReceiver <zkQuorum> <groupId> <topics> <numPartitions>")
         System.exit(1)
      }
      val Array(zkQuorum, groupId, topics, numPartitions) = args

      val sparkConf = new SparkConf().setAppName("KafkaReceiver").setMaster("local[3]")
      val ssc = new StreamingContext(sparkConf, Seconds(2))

      /**  Create an input stream that pulls messages from Kafka Brokers.
        *  @param ssc       StreamingContext object
        *  @param zkQuorum  Zookeeper quorum (hostname:port,hostname:port,..)
        *  @param groupId   The group id for this consumer
        *  @param topics    Map of (topic_name to numPartitions) to consume. Each partition is consumed in its own thread
        *  @param storageLevel  Storage level to use for storing the received objects
        *                      (default: StorageLevel.MEMORY_AND_DISK_SER_2)
        *  @return DStream of (Kafka message key, Kafka message value)
        */
      val topicMap = topics.split(",").map((_,numPartitions.toInt)).toMap
      val message = KafkaUtils.createStream(ssc,zkQuorum,groupId,topicMap)

      message.print()
      message.map(_._2).flatMap(_.split(" ")).map((_,1)).reduceByKey(_+_).print()

      ssc.start()
      ssc.awaitTermination()
   }
}