本节将展示storm作为kafka的消费者。
1、前提约束
- 已安装kafka
https://www.jianshu.com/p/1a7b9970d073 - 已安装storm
https://www.jianshu.com/p/ecf194750433
假设kafka和storm所在服务器的ip为192.168.100.141,且已关闭防火墙。
kafka的安装目录为:/root/kafka_2.11-2.2.1
storm的安装目录为:/root/apache-storm-1.2.1
2、操作步骤
- 在idea或者eclipse中创建一个maven项目,加入以下依赖:
<dependency>
<groupId>org.apache.storm</groupId>
<artifactId>storm-core</artifactId>
<exclusions>
<exclusion>
<groupId>org.slf4j</groupId>
<artifactId>log4j-over-slf4j</artifactId>
</exclusion>
</exclusions>
<version>1.2.1</version>
</dependency>
<dependency>
<groupId>org.apache.storm</groupId>
<artifactId>storm-kafka-client</artifactId>
<version>1.1.1</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>0.10.0.0</version>
</dependency>
<dependency>
<groupId>org.apache.storm</groupId>
<artifactId>storm-kafka</artifactId>
<version>1.2.1</version>
</dependency>
- 在项目的src/main/java文件夹下创建PrintBolt.java
import org.apache.storm.topology.BasicOutputCollector;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.base.BaseBasicBolt;
import org.apache.storm.tuple.Tuple;
public class PrintBolt extends BaseBasicBolt {
/**
* execute会被storm一直调用
*
* @param tuple
* @param basicOutputCollector
*/
public void execute(Tuple tuple, BasicOutputCollector basicOutputCollector) {
System.err.println(tuple.getValue(4));
}
public void declareOutputFields(OutputFieldsDeclarer outputFieldsDeclarer) {
}
}
- 在项目的src/main/java文件夹下创建MainTopology.java
import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.StormSubmitter;
import org.apache.storm.kafka.spout.KafkaSpout;
import org.apache.storm.kafka.spout.KafkaSpoutConfig;
import org.apache.storm.topology.TopologyBuilder;
public class MainTopology {
public static void main(String[] args) throws Exception {
TopologyBuilder builder = new TopologyBuilder();
KafkaSpoutConfig.Builder<String, String> kafkaBuilder = KafkaSpoutConfig.builder("192.168.100.141:9092", "kafka-storm");
// 设置kafka属于哪个组
kafkaBuilder.setGroupId("testgroup");
// 创建kafkaspoutConfig
KafkaSpoutConfig<String, String> build = kafkaBuilder.build();
// 通过kafkaspoutConfig获得kafkaspout
KafkaSpout<String, String> kafkaSpout = new KafkaSpout<String, String>(build);
// 设置5个线程接收数据
builder.setSpout("kafkaSpout", kafkaSpout, 1);
// 设置2个线程处理数据
builder.setBolt("printBolt", new PrintBolt(), 1).localOrShuffleGrouping("kafkaSpout");
Config config = new Config();
if (args.length > 0) {
// 集群提交模式
config.setDebug(false);
StormSubmitter.submitTopology(args[0], config, builder.createTopology());
} else {
// 本地测试模式
config.setDebug(true);
// 设置2个进程
config.setNumWorkers(2);
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("kafkaSpout", config, builder.createTopology());
}
}
}
- 启动该main方法
- 在192.168.100.141服务器上执行以下命令:
# 启动zookeeper
cd /root/zookeeper-3.4.11
./zkServer.sh start
# 启动kafka
cd /root/kafka_2.11-2.2.1
bin/kafka-server-start.sh config/server.properties
# 创建topic
bin/kafka-topics.sh --create --bootstrap-server 192.168.100.141:9092 --replication-factor 1 --partitions 1 --topic kafka-storm
# 启动storm的nimbus和supervisor
cd /root/apache-storm-1.2.1
./storm nimbus
./storm supervisor
# 启动kafka的生产者
bin/kafka-console-producer.sh --broker-list 192.1100.141:9092 --topic kafka-storm
- 测试
(1)在192.168.100.141的生产者命令行中输入字符串,在idea或者eclipse的命令行中就能看到该字符串。
(2)也可以把上述项目打包,假设该包名称为kafka-maven-1.0-SNAPSHOT.jar,上传到/root/apache-storm-1.2.1,以集群的方式启动,注意这个过程可能缺少jar包,需要上传到/root/apache-storm-1.2.1/lib。
cd /root/apache-storm-1.2.1/bin
./storm jar kafka-maven-1.0-SNAPSHOT.jar MainTopology wordcount
在192.168.100.141的生产者命令行中输入字符串,在apache-storm-1.2.1的日志文件中也能看到输入的字符串。
以上就是kafka与storm整合的过程。
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