Apache Spark技术实战之1 -- KafkaWordCount
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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.tgz
tar zvxf kafka_2.10-0.8.1.1.tgz
cd 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 message
This 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 message
This 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。