[Spark]Spark-streaming通过Receiver方式实时消费Kafka流程(Yarn-cluster)
1.启动zookeeper
2.启动kafka服务(broker)
[root@master kafka_2.11-0.10.2.1]# ./bin/kafka-server-start.sh config/server.properties
3.启动kafka的producer(前提:已经创建好topic
[root@master kafka_2.11-0.10.2.1]# ./bin/kafka-console-producer.sh --broker-list master:9092 --topic test
4.启动kafka的consumer
[root@master kafka_2.11-0.10.2.1]#./bin/kafka-console-consumer.sh --zookeeper master:2181 --topic test --from-beginning
5.打jar包,将带有依赖的jar包上传到集群上
mvn clean assembly:assembly
6.编写启动脚本,启动任务 sh run_receiver.sh
/usr/local/src/spark-2.0.2-bin-hadoop2.6/bin/spark-submit\
--class com.skyell.streaming.ReceiverFromKafka\
--master yarn-cluster \
--executor-memory 1G \
--total-executor-cores 2 \
--files $HIVE_HOME/conf/hive-site.xml \
./Spark8Pro-2.0-SNAPSHOT-jar-with-dependencies.jar
监控任务及查看日志
关闭spark streaming任务
yarn application -kill application_1539421032843_0093
数据驱动变革-云将 个人博客地址
数据驱动变革-云将skyell。用Flask+Nginx+uWsgi搭建的个人博客:http://www.skyell.cn/