一、flume配置

flume要求1.6以上版本

flume-conf.properties文件配置内容，sinks的输出作为kafka的product

flume启动

 bin/flume-ng agent --conf conf --conf-file conf/flume-conf.properties --name a1 -Dflume.root.logger=INFO,console

kafka启动命令

启动Zookeeper server： 

bin/zookeeper-server-start.sh config/zookeeper.properties &

启动Kafka server:

bin/kafka-server-start.sh config/server.properties & 

运行producer： 

bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test

运行consumer： 

bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning 

二、示例

pom.xml代码

1. ZooKeeper

安装参考

2. Kafka

2.1 解压安装

# 确保scala已经安装好，本文安装的是2.11.7
tar -xf kafka_2.11-0.9.0.1.tgz
cd kafka_2.11-0.9.0.1
mkdir logs

vim ~/.bash_profile

export KAFKA_HOME=/home/zkpk/kafka_2.11-0.9.0.1
export PATH=$PATH:$KAFKA_HOME/bin

source ~/.bash_profile

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2.2 配置

2.2.1 server.properties

只设置了以下4项，其他使用默认值

# 当前机器在集群中的唯一标识，和zookeeper的myid性质一样
broker.id=0

host.name=hsm01

# 消息存放的目录，这个目录可以配置为“，”逗号分割的表达式，
# 上面的num.io.threads要大于这个目录的个数这个目录，如果配置多个目录，
# 新创建的topic他把消息持久化的地方是，当前以逗号分割的目录中，
# 那个分区数最少就放那一个
log.dirs=/home/zkpk/kafka_2.11-0.9.0.1/logs

# 配置自定义的ZooKeeper
zookeeper.connect=hsm01:2181,hss01:2181,hss02:2181/kafka

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2.2.2 复制到其他节点

scp -r ~/kafka_2.11-0.9.0.1/ hss01:~/
scp -r ~/kafka_2.11-0.9.0.1/ hss02:~/

# 修改broker.id与host.name
# 配置环境变量

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2.3 启动

kafka-server-start.sh -daemon $KAFKA_HOME/config/server.properties

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2.4 测试

# 创建Topic
kafka-topics.sh --create --zookeeper hsm01:2181/kafka --replication-factor 1 --partitions 1 --topic shuaige

# 创建一个broker，发布者
kafka-console-producer.sh --broker-list hsm01:9092 --topic shuaige

# 创建一个订阅者
kafka-console-consumer.sh --zookeeper hsm01:2181/kafka --topic shuaige --from-beginning

# 查看主题
kafka-topics.sh --zookeeper hsm01:2181/kafka --list 

# 查看主题详情
kafka-topics.sh --describe --zookeeper localhost:2181 --topic test

# 删除主题
kafka-topics.sh --zookeeper localhost:2181 --delete --topic test

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2.5 参考

Kafka【第一篇】Kafka集群搭建

3. Flume

3.1 解压安装

# /home/zkpk目录
tar -xf apache-flume-1.6.0-bin.tar.gz
mv apache-flume-1.6.0-bin/ flume-1.6.0

# 配置环境变量
vim .bash_profile

export FLUME_HOME=/home/zkpk/flume-1.6.0
export PATH=$PATH:$FLUME_HOME/bin

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3.2 配置（与kafka整合）

kafkasink只有在1.6.0以上的flume版本才有。 

3.2.1 flume-env.sh

JAVA_HOME=/opt/jdk1.8.0_45

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3.2.2 kafka-sogolog.properties

# configure agent
a1.sources = f1
a1.channels = c1
a1.sinks = k1

# configure the source
a1.sources.f1.type = netcat
a1.sources.f1.bind = localhost
a1.sources.f1.port = 3333

# configure the sink (kafka)
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.topic = sogolog
a1.sinks.k1.brokerList = hsm01:9092,hss01:9092/kafka
a1.sinks.k1.requiredAcks = 0
a1.sinks.k1.batchSize = 20

# configure the channel
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# bind the source and sink to the channel
a1.sources.f1.channels = c1
a1.sinks.k1.channel = c1

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3.3 启动

启动ZooKeeper服务

$ZOOKEEPER_HOME/bin/zkServer.sh start

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启动kafka

# 启动服务
kafka-server-start.sh -daemon $KAFKA_HOME/config/server.properties

# 创建Topic
kafka-topics.sh --create --zookeeper hsm01:2181/kafka --replication-factor 1 --partitions 1 --topic sogolog

# 创建一个订阅者
kafka-console-consumer.sh --zookeeper hsm01:2181/kafka --topic sogolog --from-beginning

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启动flume

flume-ng agent -n a1 -c conf -f conf/kafka-sogolog.properties -Dflume.root.logger=DEBUG,console

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注：命令中的a1表示配置文件中的Agent的Name，如配置文件中的a1。flume-conf.properties表示配置文件所在配置，需填写准确的配置文件路径。 

3.4 测试

telnet输入

flume采集数据

kafka接收数据

3.5 参考

高可用Hadoop平台－Flume NG实战图解篇

linux安装flume及问题

Flume ng1.6 + kafka 2.11 整合

Flume自定义Hbase Sink的EventSerializer序列化类

Flume 1.6.0 User Guide

org/apache/flume/tools/GetJavaProperty

4. Storm

4.1 安装

Storm安装

4.2 简单测试

4.2.1 pom.xml

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <parent>
        <artifactId>bigdata-demo</artifactId>
        <groupId>com.zw</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <artifactId>storm-demo</artifactId>
    <packaging>jar</packaging>

    <name>storm-demo</name>
    <url>http://maven.apache.org</url>

    <repositories>
        <repository>
            <id>github-releases</id>
            <url>http://oss.sonatype.org/content/repositories/github-releases</url>
        </repository>
        <repository>
            <id>clojars.org</id>
            <url>http://clojars.org/repo</url>
        </repository>
        <repository>
            <id>twitter4j</id>
            <url>http://twitter4j.org/maven2</url>
        </repository>
    </repositories>

    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <storm.version>0.9.7</storm.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.storm</groupId>
            <artifactId>storm-core</artifactId>
            <version>${storm.version}</version>
            <!-- java直接运行时，修改为compile, maven运行时，使用provided -->
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>com.googlecode.json-simple</groupId>
            <artifactId>json-simple</artifactId>
            <version>1.1.1</version>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>3.8.1</version>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <artifactId>maven-assembly-plugin</artifactId>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                    <archive>
                        <manifest>
                            <mainClass></mainClass>
                        </manifest>
                    </archive>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
            <plugin>
                <groupId>com.theoryinpractise</groupId>
                <artifactId>clojure-maven-plugin</artifactId>
                <version>1.3.8</version>
                <extensions>true</extensions>
                <configuration>
                    <sourceDirectories>
                        <sourceDirectory>src/clj</sourceDirectory>
                    </sourceDirectories>
                </configuration>
                <executions>
                    <execution>
                        <id>compile</id>
                        <phase>compile</phase>
                        <goals>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                    <execution>
                        <id>test</id>
                        <phase>test</phase>
                        <goals>
                            <goal>test</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.5.1</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                    <encoding>${project.build.sourceEncoding}</encoding>
                </configuration>
            </plugin>
        </plugins>
    </build>
</project>

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注意storm-core依赖的scope 

4.2.2 HelloWorldSpout.java

package com.zw.storm.helloworld;

import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseRichSpout;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Values;
import backtype.storm.utils.Utils;

import java.util.Map;
import java.util.Random;

/** * Spout起到和外界沟通的作用，他可以从一个数据库中按照某种规则取数据，也可以从分布式队列中取任务 * <p> * 生成一个随机数生成的Tuple * </p> * * Created by zhangws on 16/10/3. */
public class HelloWorldSpout extends BaseRichSpout {
   

    // 用来发射数据的工具类
    private SpoutOutputCollector collector;

    private int referenceRandom;

    private static final int MAX_RANDOM = 10;

    public HelloWorldSpout() {
        final Random rand = new Random();
        referenceRandom = rand.nextInt(MAX_RANDOM);
    }

    /** * 定义字段id，该id在简单模式下没有用处，但在按照字段分组的模式下有很大的用处。 * <p> * 该declarer变量有很大作用，我们还可以调用declarer.declareStream(); * 来定义stramId，该id可以用来定义更加复杂的流拓扑结构 * </p> * @param outputFieldsDeclarer */
    @Override
    public void declareOutputFields(OutputFieldsDeclarer outputFieldsDeclarer) {
        outputFieldsDeclarer.declare(new Fields("sentence"));
    }

    /** * 初始化collector * * @param map * @param topologyContext * @param spoutOutputCollector */
    @Override
    public void open(Map map, TopologyContext topologyContext,
                     SpoutOutputCollector spoutOutputCollector) {
        this.collector = spoutOutputCollector;
    }

    /** * 每调用一次就可以向storm集群中发射一条数据（一个tuple元组），该方法会被不停的调用 */
    @Override
    public void nextTuple() {
        Utils.sleep(100);
        final Random rand = new Random();
        int instanceRandom = rand.nextInt(MAX_RANDOM);
        if (instanceRandom == referenceRandom) {
            collector.emit(new Values("Hello World"));
        } else {
            collector.emit(new Values("Other Random Word"));
        }
    }
}

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4.2.3 HelloWorldBolt.java

package com.zw.storm.helloworld;

import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseBasicBolt;
import backtype.storm.tuple.Tuple;

/** * 接收喷发节点(Spout)发送的数据进行简单的处理后，发射出去。 * <p> * 用于读取已产生的Tuple并实现必要的统计逻辑 * </p> * * Created by zhangws on 16/10/4. */
public class HelloWorldBolt extends BaseBasicBolt {
   

    private int myCount;

    @Override
    public void execute(Tuple tuple, BasicOutputCollector collector) {
        String test = tuple.getStringByField("sentence");
        if ("Hello World".equals(test)) {
            myCount++;
            System.out.println("==========================: " + myCount);
        }
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer outputFieldsDeclarer) {

    }
}

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4.2.4 HelloWorldTopology.java

package com.zw.storm.helloworld;

import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.StormSubmitter;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.utils.Utils;

/** * mvn compile exec:java -Dexec.classpathScope=compile -Dexec.mainClass=com.zw.storm.helloworld.HelloWorldTopology * Created by zhangws on 16/10/4. */
public class HelloWorldTopology {
   

    public static void main(String[] args) throws Exception {
        TopologyBuilder builder = new TopologyBuilder();
        // 设置喷发节点并分配并发数，该并发数将会控制该对象在集群中的线程数。
        builder.setSpout("randomHelloWorld", new HelloWorldSpout(), 1);
        // 设置数据处理节点并分配并发数。指定该节点接收喷发节点的策略为随机方式。
        builder.setBolt("HelloWorldBolt", new HelloWorldBolt(), 2)
                .shuffleGrouping("randomHelloWorld");

        Config config = new Config();
        config.setDebug(true);

        if (args != null && args.length > 0) {
            config.setNumWorkers(1);
            StormSubmitter.submitTopology(args[0], config, builder.createTopology());
        } else {
            // 这里是本地模式下运行的启动代码。
            config.setMaxTaskParallelism(1);
            LocalCluster cluster = new LocalCluster();
            cluster.submitTopology("test", config, builder.createTopology());
            Utils.sleep(10000);
            cluster.killTopology("test");
            cluster.shutdown();
        }
    }
}

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4.2.5 运行

# maven
mvn compile exec:java -Dexec.classpathScope=compile -Dexec.mainClass=com.zw.storm.helloworld.HelloWorldTopology

# java直接运行
修改storm-core依赖的scope为compile

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结果

...
34568 [Thread-15-HelloWorldBolt] INFO  backtype.storm.daemon.executor - Processing received message source: randomHelloWorld:3, stream: default, id: {}, [Other Random Word]
34671 [Thread-11-randomHelloWorld] INFO  backtype.storm.daemon.task - Emitting: randomHelloWorld default [Hello World]
34671 [Thread-15-HelloWorldBolt] INFO  backtype.storm.daemon.executor - Processing received message source: randomHelloWorld:3, stream: default, id: {}, [Hello World]
==========================: 5
34776 [Thread-11-randomHelloWorld] INFO  backtype.storm.daemon.task - Emitting: randomHelloWorld default [Other Random Word]
34776 [Thread-15-HelloWorldBolt] INFO  backtype.storm.daemon.executor - Processing received message source: randomHelloWorld:3, stream: default, id: {}, [Other Random Word]
34880 [Thread-11-randomHelloWorld] INFO  backtype.storm.daemon.task - Emitting: randomHelloWorld default [Other Random Word]
...

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4.3 与Kafka集成

4.3.1 pom.xml

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <parent>
        <artifactId>bigdata-demo</artifactId>
        <groupId>com.zw</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <artifactId>kafka2storm</artifactId>
    <packaging>jar</packaging>

    <name>kafka2storm</name>
    <url>http://maven.apache.org</url>

    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <storm.version>0.9.7</storm.version>
        <kafka.version>0.9.0.1</kafka.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.storm</groupId>
            <artifactId>storm-core</artifactId>
            <version>${storm.version}</version>
            <!-- java直接运行时，修改为 compile, maven运行时，使用 provided -->
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.storm</groupId>
            <artifactId>storm-kafka</artifactId>
            <version>${storm.version}</version>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>3.8.1</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka_2.11</artifactId>
            <version>${kafka.version}</version>
            <exclusions>
                <exclusion>
                    <groupId>org.apache.zookeeper</groupId>
                    <artifactId>zookeeper</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.slf4j</groupId>
                    <artifactId>slf4j-log4j12</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>log4j</groupId>
                    <artifactId>log4j</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <artifactId>maven-assembly-plugin</artifactId>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

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4.3.2 MessageScheme.java

package com.zw.kafka.storm;

import backtype.storm.spout.Scheme;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Values;

import java.io.UnsupportedEncodingException;
import java.util.List;

/** * 对kafka出来的数据转换成字符串 * <p> * KafkaSpout是Storm中自带的Spout, * 使用KafkaSpout时需要子集实现Scheme接口，它主要负责从消息流中解析出需要的数据 * </p> * * Created by zhangws on 16/10/2. */
public class MessageScheme implements Scheme {
   

    public List<Object> deserialize(byte[] bytes) {
        try {
            String msg = new String(bytes, "UTF-8");
            return new Values(msg);
        } catch (UnsupportedEncodingException e) {
            e.printStackTrace();
        }
        return null;
    }

    public Fields getOutputFields() {
        return new Fields("msg");
    }
}

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4.3.3 SequenceBolt.java

package com.zw.kafka.storm;

import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseBasicBolt;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values;

import java.io.DataOutputStream;
import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;

/** * 把输出保存到一个文件中 * <p> * 把输出的消息放到文件kafkastorm.out中 * </p> * * Created by zhangws on 16/10/2. */
public class SequenceBolt extends BaseBasicBolt {
   

    /** * Process the input tuple and optionally emit new tuples based on the input tuple. * <p> * All acking is managed for you. Throw a FailedException if you want to fail the tuple. * * @param input * @param collector */
    public void execute(Tuple input, BasicOutputCollector collector) {
        String word = (String) input.getValue(0);
        System.out.println("==============" + word);

        //写文件
        try {
            DataOutputStream out_file = new DataOutputStream(new FileOutputStream("/home/zkpk/kafkastorm.out"));
            out_file.writeUTF(word);
            out_file.close();
        } catch (FileNotFoundException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        }

        collector.emit(new Values(word));
    }

    /** * Declare the output schema for all the streams of this topology. * * @param declarer this is used to declare output stream ids, output fields, and whether or not each output stream is a direct stream */
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        declarer.declare(new Fields("message"));
    }
}

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4.3.4 KafkaTopology.java

package com.zw.kafka.storm;

import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.StormSubmitter;
import backtype.storm.spout.SchemeAsMultiScheme;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.utils.Utils;
import storm.kafka.BrokerHosts;
import storm.kafka.KafkaSpout;
import storm.kafka.SpoutConfig;
import storm.kafka.ZkHosts;
import storm.kafka.bolt.KafkaBolt;

import java.util.HashMap;
import java.util.Map;

/** * 配置kafka提交topology到storm的代码 * <p> * topic1的含义kafka接收生产者过来的数据所需要的topic; * topic2是KafkaBolt也就是storm中的bolt生成的topic，当然这里topic2这行配置可以省略， * 是没有任何问题的，类似于一个中转的东西 * </p> * Created by zhangws on 16/10/2. */
public class KafkaTopology {
   

    private static final String BROKER_ZK_LIST = "hsm01:2181,hss01:2181,hss02:2181";
    private static final String ZK_PATH = "/kafka/brokers";

    public static void main(String[] args) throws Exception {
        // 配置Zookeeper地址
        BrokerHosts brokerHosts = new ZkHosts(BROKER_ZK_LIST, ZK_PATH);
        // 配置Kafka订阅的Topic，以及zookeeper中数据节点目录和名字
        SpoutConfig spoutConfig = new SpoutConfig(brokerHosts, "sogolog", "/kafka", "kafka");

        // 配置KafkaBolt中的kafka.broker.properties
        Config conf = new Config();
        Map<String, String> map = new HashMap<String, String>();

        // 配置Kafka broker地址
        map.put("metadata.broker.list", "hsm01:9092");
        // serializer.class为消息的序列化类
        map.put("serializer.class", "kafka.serializer.StringEncoder");
        conf.put("kafka.broker.properties", map);
        // 配置KafkaBolt生成的topic
        conf.put("topic", "topic2");

        spoutConfig.scheme = new SchemeAsMultiScheme(new MessageScheme());
// spoutConfig.scheme = new SchemeAsMultiScheme(new StringScheme());

        TopologyBuilder builder = new TopologyBuilder();
        builder.setSpout("kafka-spout", new KafkaSpout(spoutConfig), 1);
        builder.setBolt("kafka-bolt", new SequenceBolt()).shuffleGrouping("kafka-spout");
        builder.setBolt("kafka-bolt2", new KafkaBolt<String, Integer>()).shuffleGrouping("kafka-bolt");

        String name = KafkaTopology.class.getSimpleName();
        if (args != null && args.length > 0) {
            // Nimbus host name passed from command line
            conf.put(Config.NIMBUS_HOST, args[0]);
            conf.setNumWorkers(2);
            StormSubmitter.submitTopology(name, conf, builder.createTopology());
        } else {
            //本地模式运行
            conf.setMaxTaskParallelism(3);
            LocalCluster cluster = new LocalCluster();
            cluster.submitTopology(name, conf, builder.createTopology());
            Utils.sleep(60000);
            cluster.killTopology(name);
            cluster.shutdown();
        }
    }
}

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4.3.5 拷贝kafka依赖jar包到storm lib

cp ~/kafka_2.11-0.9.0.1/libs/kafka_2.11-0.9.0.1.jar ~/storm-0.9.7/lib/
cp ~/kafka_2.11-0.9.0.1/libs/scala-library-2.11.7.jar ~/storm-0.9.7/lib/
cp ~/kafka_2.11-0.9.0.1/libs/metrics-core-2.2.0.jar ~/storm-0.9.7/lib/
cp ~/kafka_2.11-0.9.0.1/libs/log4j-1.2.17.jar ~/storm-0.9.7/lib/
# cp ~/kafka_2.11-0.9.0.1/libs/slf4j-api-1.7.6.jar ~/storm-0.9.7/lib/
cp ~/kafka_2.11-0.9.0.1/libs/jopt-simple-3.2.jar ~/storm-0.9.7/lib/

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4.3.2 运行

启动ZooKeeper与storm集群。

启动kafka

kafka-server-start.sh -daemon $KAFKA_HOME/config/server.properties

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运行kafkatopology

storm jar /home/zkpk/doc/kafka2storm-1.0-SNAPSHOT-jar-with-dependencies.jar com.zw.kafka.storm.KafkaTopology hsm01

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创建一个订阅者

kafka-console-consumer.sh --zookeeper hsm01:2181/kafka --topic topic2 --from-beginning

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启动kafka生产者

kafka-console-producer.sh --broker-list hsm01:9092 --topic sogolog

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结果

# 生产者
[zkpk@hsm01 ~]$ kafka-console-producer.sh --broker-list hsm01:9092 --topic sogolog
nihao
hello storm-kafka
你好，storm-kafka

# 经过storm处理的消费者
[zkpk@hsm01 ~]$ kafka-console-consumer.sh --zookeeper hsm01:2181/kafka --topic topic2 --from-beginning
nihao
hello storm-kafka
你好，storm-kafka

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4.4 参考

storm-starter IDE 下的调试经历

kafka与storm集成测试问题小结

Storm集成Kafka应用的开发

KafkaSpout 引起的 log4j 的问题

<dependencies>

    <dependency>

        <groupId>org.apache.storm</groupId>

        <artifactId>storm-core</artifactId>

        <version>1.0.2</version>

        <!-- 由于storm环境中有该jar，所以不用pack到最终的task.jar中 -->

        <scope>provided</scope>

    </dependency>

    <dependency>

        <groupId>org.apache.storm</groupId>

        <artifactId>storm-kafka</artifactId>

        <version>1.0.2</version>

    </dependency>

    <dependency>

        <groupId>org.apache.commons</groupId>

        <artifactId>commons-lang3</artifactId>

        <version>3.3.2</version>

    </dependency>

    <!-- kafka目前已经有2.10了，但是我用了，任务执行报错，目前只能用kafka_2.9.2，我kafka服务端也是用最新的2.10版本 -->

    <dependency>

        <groupId>org.apache.kafka</groupId>

        <artifactId>kafka_2.9.2</artifactId>

        <version>0.8.2.2</version>

        <!-- 排除以下jar，由于storm服务端有log4j,避免冲突报错-->

        <exclusions>

            <exclusion>

                <groupId>org.apache.zookeeper</groupId>

                <artifactId>zookeeper</artifactId>

            </exclusion>

            <exclusion>

                <groupId>log4j</groupId>

                <artifactId>log4j<artifactId>

            </exclusion>

            <exclusion>

                <groupId>org.slf4j</groupId>

                <artifactId>slf4j-log4j12</artifactId>

            </exclusion>

        </exclusions>

    </dependency>

    <dependency>

        <groupId>org.elasticsearch</groupId>

        <artifactId>elasticsearch</artifactId>

        <version>1.4.4</version>

        <exclusions>

            <exclusion>

                <groupId>log4j</groupId>

                <artifactId>log4j<artifactId>

            </exclusion>

            <exclusion>

                <groupId>org.slf4j</groupId>

                <artifactId>slf4j-log4j12</artifactId>

            </exclusion>

        </exclusions>

    </dependency>

</dependencies>

<build>

    <plugins>

        <plugin>

            <artifactId>maven-compiler-plugin</artifactId>

            <configuration>

                <encoding>utf-8</encoding>

                <source>1.8</source>

                <target>1.8</target>

            </configuration>

        </plugin>

        <plugin>

            <artifactId>maven-assembly-plugin</artifactId>

            <configuration>

                <archive>

                    <manifest><manifest>

                </archive>

                <descriptorRefs>

                    <descriptorRef>jar-with-dependencies</descriptorRef>

                </descriptorRefs>

                <encoding>utf-8</encoding>

            </configuration>

        </plugin>

    </plugins>

5. Flume、Kafka与Storm集成测试

# 启动经过storm处理的订阅者
kafka-console-consumer.sh --zookeeper hsm01:2181/kafka --topic topic2

# 运行kafkatopology
storm jar /home/zkpk/doc/kafka2storm-1.0-SNAPSHOT-jar-with-dependencies.jar com.zw.kafka.storm.KafkaTopology hsm01

# 启动flume
flume-ng agent -n a1 -c conf -f /home/zkpk/flume-1.6.0/conf/kafka-sogolog.properties -Dflume.root.logger=DEBUG,console

# 复制文件到flume监视目录
cp test.log  flume/

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