5、Storm集成Kafka

1、pom文件依赖

<!--storm相关jar  -->
<dependency>
    <groupId>org.apache.storm</groupId>
    <artifactId>storm-core</artifactId>
    <version>${storm.version}</version>
    <!--排除相关依赖  -->
    <exclusions>
        <exclusion>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-slf4j-impl</artifactId>
        </exclusion>
        <exclusion>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-1.2-api</artifactId>
        </exclusion>
        <exclusion>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-web</artifactId>
        </exclusion>
        <exclusion>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
        </exclusion>
        <exclusion>
            <artifactId>ring-cors</artifactId>
            <groupId>ring-cors</groupId>
        </exclusion>
    </exclusions>
    <!--<scope>provided</scope>--><!--注意本地调试和集群部署-->
</dependency>
<dependency>
    <groupId>org.apache.storm</groupId>
    <artifactId>storm-kafka-client</artifactId>
    <version>1.2.2</version>
    <!--<scope>provided</scope>--><!--注意本地调试和集群部署-->
</dependency>

<!--注:老版本使用的storm-kafka依赖已经被废弃,建议在以后使用storm-kafka-client依赖进行开发,老版本的storm-kafka依赖为:-->
<!--    <dependency> -->
<!--        <groupId>org.apache.storm</groupId> -->
<!--        <artifactId>storm-kafka</artifactId> -->
<!--        <version>1.2.2</version> -->
<!--    </dependency> -->
<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka-clients</artifactId>
    <version>2.1.0</version>
</dependency>

2、Topology

@Component
public class KafkaStormSpoutWordCountTopology {

    public static void main(String[] args) {

        KafkaSpoutConfig.Builder<String,String> builder =
                KafkaSpoutConfig.builder(
                        "192.168.8.101:9092,192.168.8.102:9092,192.168.8.103:9092",
                        "yun01");

        builder.setGroupId("test_storm_wc");

        KafkaSpoutConfig<String, String> kafkaSpoutConfig= builder.build();
        TopologyBuilder topologyBuilder = new TopologyBuilder();
        
        topologyBuilder.setSpout("WordCountKafkaSpout",
                                new KafkaSpout<String,String>(kafkaSpoutConfig),
                                1);

        topologyBuilder.setBolt("ReadKafkaSpoutBolt",
                                new ReadKafkaSpoutBolt()).shuffleGrouping("WordCountKafkaSpout");

        Config config = new Config();


        System.out.println("准备启动kafkaStromTopo");
        LocalCluster cluster= new LocalCluster();
        cluster.submitTopology("kafkaStromTopo", config, topologyBuilder.createTopology());



//        //启动topology的配置信息
//        Config conf = new Config();
//        //TOPOLOGY_DEBUG(setDebug),当他被设置成true的话,storm会记录下每个组件所发射的每条消息
//        //这在本地环境调试topology很有用。但是在线上这么做的话,会影响性能
//        conf.setDebug(false);
//
//        //storm的运行模式有两种:本地模式和分布式模式
//        if(args != null || args.length>0){
//            conf.setNumWorkers(3);
//            //向集群提交topology
//            try {
//                StormSubmitter.submitTopologyWithProgressBar(args[0],conf,topologyBuilder.createTopology());
//            } catch (AlreadyAliveException e) {
//                e.printStackTrace();
//            } catch (InvalidTopologyException e) {
//                e.printStackTrace();
//            } catch (AuthorizationException e) {
//                e.printStackTrace();
//            }
//        }
//        else{
//
//
//            conf.setMaxTaskParallelism(3);
//
//            LocalCluster cluster = new LocalCluster();
//            cluster.submitTopology("word-count",conf,builder.createTopology());
//        }
    }

3、Bolt, 设计拓扑请跟根据自己的业务

public class ReadKafkaSpoutBolt extends BaseBasicBolt {
    @Override
    public void execute(Tuple input, BasicOutputCollector basicOutputCollector) {

        System.out.println(input.getValues().get(4)+"消息接受bolt");
        /*
        input 获取到的值

        0索引代表kafka的topic
        1索引代表kafka的分区
        2索引代表kafka的偏移量
        3索引代表kafka的key值
        4索引代表kafka的value值
        */
    }
    @Override
    public void declareOutputFields(OutputFieldsDeclarer outputFieldsDeclarer) {

    }
}
原文地址:https://www.cnblogs.com/xidianzxm/p/10774655.html