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概要

Spark应用开发实践性非常强，很多时候可能都会将时间花费在环境的搭建和运行上，如果有一个比较好的指导将会大大的缩短应用开发流程。Spark Streaming中涉及到和许多第三方程序的整合，源码中的例子如何真正跑起来，文档不是很多也不详细。

本篇主要讲述如何运行KafkaWordCount，这个需要涉及Kafka集群的搭建，还是说的越仔细越好。

搭建Kafka集群

步骤1：下载kafka 0.8.1及解压

wget https://www.apache.org/dyn/closer.cgi?path=/kafka/0.8.1.1/kafka_2.10-0.8.1.1.tgztar zvxf kafka_2.10-0.8.1.1.tgzcd kafka_2.10-0.8.1.1

步骤2：启动zookeeper

bin/zookeeper-server-start.sh config/zookeeper.properties

步骤3：修改配置文件config/server.properties，添加如下内容

host.name=localhost# Hostname the broker will advertise to producers and consumers. If not set, it uses the# value for "host.name" if configured.  Otherwise, it will use the value returned from# java.net.InetAddress.getCanonicalHostName().advertised.host.name=localhost

步骤4：启动Kafka server

bin/kafka-server-start.sh config/server.properties

步骤5：创建topic

bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1  --topic test

检验topic创建是否成功

bin/kafka-topics.sh --list --zookeeper localhost:2181

如果正常返回test

步骤6：打开producer，发送消息

bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test ##启动成功后，输入以下内容测试This is a messageThis is another message

 步骤7：打开consumer，接收消息

bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning###启动成功后，如果一切正常将会显示producer端输入的内容This is a messageThis is another message

运行KafkaWordCount

KafkaWordCount源文件位置 examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala

尽管里面有使用说明，见下文，但如果不是事先对Kafka有一定的了解的话，决然不知道这些参数是什么意思，也不知道该如何填写。

/** * Consumes messages from one or more topics in Kafka and does wordcount. * Usage: KafkaWordCount     *    is a list of one or more zookeeper servers that make quorum *    is the name of kafka consumer group *    is a list of one or more kafka topics to consume from *    is the number of threads the kafka consumer should use * * Example: *    `$ bin/run-example  *      org.apache.spark.examples.streaming.KafkaWordCount zoo01,zoo02,zoo03  *      my-consumer-group topic1,topic2 1` */object KafkaWordCount {  def main(args: Array[String]) {    if (args.length < 4) {      System.err.println("Usage: KafkaWordCount    ")      System.exit(1)    }    StreamingExamples.setStreamingLogLevels()    val Array(zkQuorum, group, topics, numThreads) = args    val sparkConf = new SparkConf().setAppName("KafkaWordCount")    val ssc =  new StreamingContext(sparkConf, Seconds(2))    ssc.checkpoint("checkpoint")    val topicpMap = topics.split(",").map((_,numThreads.toInt)).toMap    val lines = KafkaUtils.createStream(ssc, zkQuorum, group, topicpMap).map(_._2)    val words = lines.flatMap(_.split(" "))    val wordCounts = words.map(x => (x, 1L))      .reduceByKeyAndWindow(_ + _, _ - _, Minutes(10), Seconds(2), 2)    wordCounts.print()    ssc.start()    ssc.awaitTermination()  }}

讲清楚了写这篇博客的主要原因之后，来看一看该如何运行KafkaWordCount

步骤1：停止运行刚才的kafka-console-producer和kafka-console-consumer

步骤2：运行KafkaWordCountProducer

bin/run-example org.apache.spark.examples.streaming.KafkaWordCountProducer localhost:9092 test 3 5

解释一下参数的意思，localhost:9092表示producer的地址和端口, test表示topic，3表示每秒发多少条消息，5表示每条消息中有几个单词

步骤3：运行KafkaWordCount

 bin/run-example org.apache.spark.examples.streaming.KafkaWordCount localhost:2181 test-consumer-group test 1

解释一下参数， localhost:2181表示zookeeper的监听地址，test-consumer-group表示consumer-group的名称，必须和$KAFKA_HOME/config/consumer.properties中的group.id的配置内容一致，test表示topic，1表示线程数。