1.准备环境
(1) 启动zk
bin/zkServer.sh start
(2)启动kafka
bin/kafka-server-start.sh -daemon config/server.properties
(3)创建topic
bin/kafka-topics.sh --create --topic kafka_streaming_topic --zookeeper bigdata.ibeifeng.com:2181/kafka08 --partitions 1 --replication-factor 1
查看
bin/kafka-topics.sh --list --zookeeper bigdata.ibeifeng.com:2181/kafka08
(4)测试kafka可以正常接收产生的消息,并且消费
生产者
bin/kafka-console-producer.sh --broker-list bigdata.ibeifeng.com:9092 --topic kafka_streaming_topic
消费:
bin/kafka-console-consumer.sh --topic kafka_streaming_topic --zookeeper bigdata.ibeifeng.com:2181/kafka08
(经测试,成功!)
2.开发代码
(1)pom依赖
【参考:http://spark.apache.org/docs/2.1.0/streaming-kafka-0-8-integration.html】
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-8_2.11</artifactId>
<version>2.1.0</version>
</dependency>
(2)代码
package Spark
import org.apache.spark.SparkConf
import org.apache.spark.streaming.dstream.ReceiverInputDStream
import org.apache.spark.streaming.kafka.KafkaUtils
import org.apache.spark.streaming.{Seconds, StreamingContext}
/**
*/
object KafkaReceiverWordCount_product {
def main(args: Array[String]): Unit = {
if(args.length!=4){
System.err.println("Usage: KafkaReceiverWordCount <zkQuorum><group><topics><numThreads>")
}
val Array(zkQuorum,group,topics,numThreads)=args
//因为这个是生产环境,所以注释
val sparkConf=new SparkConf()
val ssc=new StreamingContext(sparkConf,Seconds(5))
val topicMap=topics.split(",").map((_,numThreads.toInt)).toMap
//TODO: Spark streaming如何对接kafka
//参考源码createStream
val messages: ReceiverInputDStream[(String, String)] =KafkaUtils.createStream(ssc,zkQuorum,group,topicMap)
//取第2个
messages.map(_._2).flatMap(_.split(" ")).map((_,1)).reduceByKey(_+_).print()
ssc.start()
ssc.awaitTermination()
}
}
3.测试
(1)jar包放入
/opt/datas/lib/scalaProjectMaven.jar
(2)打开hdfs
(3)提交spark任务
bin/spark-submit \
--class Spark.KafkaReceiverWordCount_product \
--master local[2] \
--name KafkaReceiverWordCount_product \
--packages org.apache.spark:spark-streaming-kafka-0-8_2.11:2.1.0 \
/opt/datas/lib/scalaProjectMaven.jar bigdata.ibeifeng.com:2181/kafka08 test kafka_streaming_topic 1