flume-kafka-storm
flume读取日志数据，然后发送至kafka。
1、flume配置文件
agent.sources = kafkaSource agent.channels = kafkaChannel agent.sinks = kafkaSink agent.sources.kafkaSource.type = exec agent.sources.kafkaSource.command = tail -F /home/hadoop/kafkaData/kafka.log agent.sources.kafkaSource.channels = kafkaChannel agent.sinks.kafkaSink.channel = kafkaChannel agent.sinks.kafkaSink.type = org.apache.flume.sink.kafka.KafkaSink agent.sinks.kafkaSink.topic = stormTopic agent.sinks.kafkaSink.brokerList = 192.168.25.151:9092,192.168.25.152:9092,192.168.25.153:9092 agent.sinks.kafkaSink.kafka.flumeBatchSize = 20 agent.sinks.kafkaSink.kafka.producer.acks = 1 agent.sinks.kafkaSink.kafka.producer.linger.ms = 1 agent.sinks.kafkaSink.kafka.producer.compression.type = snappy agent.sinks.kafkaSink.serializer.class=kafka.serializer.StringEncoder agent.channels.kafkaChannel.type=memory agent.channels.kafkaChannel.capacity=10000 agent.channels.kafkaChannel.transactionCapacity=100
2、启动flume
bin/flume-ng agent --conf-file conf/flume-kafka.conf -c conf/ --name agent -Dflume.root.logger=DEBUG,console
3、需要在flume机器上修改hosts文件，添加上kafka的主机名和ip的映射。
4、在kafka上创建主题
bin/kafka-topics.sh --create --zookeeper hadoop2:2181 --replication-factor 1 --partitions 3 --topic stormTopic
5、模拟生成日志脚本
for((i=0;i<=10000;i++)); do echo "kafka_test-"$i>>/home/hadoop/kafkaData/kafka.log; done
6、在kafka上开启消费者
bin/kafka-console-consumer.sh --zookeeper hadoop2:2181 --from-beginning --topic stormTopic
至此，flum->kafka的数据流走通。
7、整合Storm，将kafka作为stom的spout，将使用KafkaSpout。
1 <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" 2 xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> 3 <modelVersion>4.0.0</modelVersion> 4 <groupId>cn.itcast</groupId> 5 <artifactId>kafkaStorm</artifactId> 6 <version>0.0.1-SNAPSHOT</version> 7 <packaging>jar</packaging> 8 <dependencies> 9 <!-- https://mvnrepository.com/artifact/org.apache.storm/storm-core --> 10 <dependency> 11 <groupId>org.apache.storm</groupId> 12 <artifactId>storm-core</artifactId> 13 <version>1.2.1</version> 14 <scope>provided</scope> 15 </dependency> 16 <dependency> 17 <groupId>org.apache.storm</groupId> 18 <artifactId>storm-kafka</artifactId> 19 <version>1.2.1</version> 20 </dependency> 21 <dependency> 22 <groupId>org.apache.kafka</groupId> 23 <artifactId>kafka_2.12</artifactId> 24 <version>1.0.0</version> 25 <exclusions> 26 <exclusion> 27 <groupId>org.slf4j</groupId> 28 <artifactId>slf4j-log4j12</artifactId> 29 </exclusion> 30 </exclusions> 31 </dependency> 32 <!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients --> 33 <dependency> 34 <groupId>org.apache.kafka</groupId> 35 <artifactId>kafka-clients</artifactId> 36 <version>1.0.0</version> 37 </dependency> 38 39 40 </dependencies> 41 <build> 42 <plugins> 43 <!-- 资源文件拷贝插件 --> 44 <plugin> 45 <groupId>org.apache.maven.plugins</groupId> 46 <artifactId>maven-resources-plugin</artifactId> 47 <version>2.7</version> 48 <configuration> 49 <encoding>UTF-8</encoding> 50 </configuration> 51 </plugin> 52 <!-- java编译插件 --> 53 <plugin> 54 <groupId>org.apache.maven.plugins</groupId> 55 <artifactId>maven-compiler-plugin</artifactId> 56 <version>3.2</version> 57 <configuration> 58 <source>1.8</source> 59 <target>1.8</target> 60 <encoding>UTF-8</encoding> 61 </configuration> 62 </plugin> 63 <plugin> 64 <groupId>org.apache.maven.plugins</groupId> 65 <artifactId>maven-jar-plugin</artifactId> 66 <version>2.4</version> 67 </plugin> 68 <plugin> 69 <groupId>org.apache.maven.plugins</groupId> 70 <artifactId>maven-assembly-plugin</artifactId> 71 <version>2.4</version> 72 <configuration> 73 <descriptorRefs> 74 <descriptorRef>jar-with-dependencies</descriptorRef> 75 </descriptorRefs> 76 <archive> 77 <manifest> 78 <mainClass>cn.itcast.kafka.Kafka2Storm</mainClass> 79 </manifest> 80 </archive> 81 </configuration> 82 <executions> 83 <execution> 84 <id>make-assembly</id> 85 <phase>package</phase> 86 <goals> 87 <goal>single</goal> 88 </goals> 89 </execution> 90 </executions> 91 </plugin> 92 </plugins> 93 </build> 94 </project>
1 package cn.itcast.kafka; 2 3 import org.apache.storm.Config; 4 import org.apache.storm.LocalCluster; 5 import org.apache.storm.generated.AlreadyAliveException; 6 import org.apache.storm.generated.AuthorizationException; 7 import org.apache.storm.generated.InvalidTopologyException; 8 import org.apache.storm.kafka.BrokerHosts; 9 import org.apache.storm.kafka.KafkaSpout; 10 import org.apache.storm.kafka.SpoutConfig; 11 import org.apache.storm.kafka.ZkHosts; 12 import org.apache.storm.topology.TopologyBuilder; 13 14 public class Kafka2Storm { 15 public static void main(String[] args) 16 throws AlreadyAliveException, InvalidTopologyException, AuthorizationException { 17 TopologyBuilder topologyBuilder = new TopologyBuilder(); 18 BrokerHosts hosts = new ZkHosts("192.168.25.142:2181,192.168.25.143:2181,192.168.25.144:2181"); 19 /** 20 * hosts:用以获取Kafka broker和partition的信息,在zk上获取，此处填写zk的地址 21 * topic:从哪个topic读取消息 zkRoot:进度信息记录于zookeeper的哪个路径下 22 * id:进度记录的id，想要一个新的Spout读取之前的记录，应把它的id设为跟之前的一样 23 */ 24 SpoutConfig spoutConfig = new SpoutConfig(hosts, "stormTopic", "/mykafka", "kafkaSpout"); 25 KafkaSpout kafkaSpout = new KafkaSpout(spoutConfig); 26 topologyBuilder.setSpout("kafkaSpout", kafkaSpout); 27 // 将一行行的文本切分成单词 28 topologyBuilder.setBolt("valueBolt", new ValueBolt(), 1).shuffleGrouping("kafkaSpout"); 29 // 启动topology的配置信息 30 Config config = new Config(); 31 // 定义集群分配多少个工作进程来执行这个topology 32 config.setNumWorkers(3); 33 34 LocalCluster localCluster = new LocalCluster(); 35 localCluster.submitTopology("kafkaStomrTopology", config, 36 topologyBuilder.createTopology()); 37 // 集群模式提交topology 38 // StormSubmitter.submitTopologyWithProgressBar("kafkaStomrTopology", config, topologyBuilder.createTopology()); 39 } 40 }
1 package cn.itcast.kafka; 2 3 import java.util.Map; 4 5 import org.apache.storm.task.OutputCollector; 6 import org.apache.storm.task.TopologyContext; 7 import org.apache.storm.topology.OutputFieldsDeclarer; 8 import org.apache.storm.topology.base.BaseRichBolt; 9 import org.apache.storm.tuple.Tuple; 10 import org.slf4j.Logger; 11 import org.slf4j.LoggerFactory; 12 13 public class ValueBolt extends BaseRichBolt { 14 Logger logger = LoggerFactory.getLogger(ValueBolt.class); 15 16 /** 17 * 18 */ 19 private static final long serialVersionUID = 1L; 20 21 @Override 22 public void prepare(Map stormConf, TopologyContext context, OutputCollector collector) { 23 // TODO Auto-generated method stub 24 25 } 26 27 @Override 28 public void execute(Tuple input) { 29 logger.info(new String((byte[]) input.getValue(0))); 30 } 31 32 @Override 33 public void declareOutputFields(OutputFieldsDeclarer declarer) { 34 // TODO Auto-generated method stub 35 36 } 37 38 }