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Kafka部署与代码实例（转）
来自：http://doc.okbase.net/QING____/archive/19447.html
kafka作为分布式日志收集或系统监控服务，我们有必要在合适的场合使用它。kafka的部署包括zookeeper环境/kafka环境，同时还需要进行一些配置操作.接下来介绍如何使用kafka.
我们使用3个zookeeper实例构建zk集群，使用2个kafka broker构建kafka集群.
其中kafka为0.8V，zookeeper为3.4.5V
一.Zookeeper集群构建
我们有3个zk实例，分别为zk-0,zk-1,zk-2;如果你仅仅是测试使用，可以使用1个zk实例.
1) zk-0
调整配置文件：
clientPort=2181server.0=127.0.0.1:2888:3888server.1=127.0.0.1:2889:3889server.2=127.0.0.1:2890:3890##只需要修改上述配置，其他配置保留默认值
启动zookeeper
./zkServer.sh start
2) zk-1
调整配置文件(其他配置和zk-0一只)：
clientPort=2182##只需要修改上述配置，其他配置保留默认值
启动zookeeper
./zkServer.sh start
3) zk-2
调整配置文件(其他配置和zk-0一只)：
clientPort=2183##只需要修改上述配置，其他配置保留默认值
启动zookeeper
./zkServer.sh start
二. Kafka集群构建
因为Broker配置文件涉及到zookeeper的相关约定，因此我们先展示broker配置文件.我们使用2个kafka broker来构建这个集群环境，分别为kafka-0,kafka-1.
1) kafka-0
在config目录下修改配置文件为：
broker.id=0port=9092num.network.threads=2num.io.threads=2socket.send.buffer.bytes=1048576socket.receive.buffer.bytes=1048576socket.request.max.bytes=104857600log.dir=./logsnum.partitions=2log.flush.interval.messages=10000log.flush.interval.ms=1000log.retention.hours=168#log.retention.bytes=1073741824log.segment.bytes=536870912log.cleanup.interval.mins=10zookeeper.connect=127.0.0.1:2181,127.0.0.1:2182,127.0.0.1:2183zookeeper.connection.timeout.ms=1000000kafka.metrics.polling.interval.secs=5kafka.metrics.reporters=kafka.metrics.KafkaCSVMetricsReporterkafka.csv.metrics.dir=/tmp/kafka_metricskafka.csv.metrics.reporter.enabled=false
因为kafka用scala语言编写，因此运行kafka需要首先准备scala相关环境。
> cd kafka-0> ./sbt update> ./sbt package> ./sbt assembly-package-dependency
其中最后一条指令执行有可能出现异常，暂且不管。 启动kafka broker：
> JMS_PORT=9997 bin/kafka-server-start.sh config/server.properties &
因为zookeeper环境已经正常运行了，我们无需通过kafka来挂载启动zookeeper.如果你的一台机器上部署了多个kafka broker，你需要声明JMS_PORT.
2) kafka-1
broker.id=1port=9093##其他配置和kafka-0保持一致
然后和kafka-0一样执行打包命令，然后启动此broker.
> JMS_PORT=9998 bin/kafka-server-start.sh config/server.properties &
到目前为止环境已经OK了,那我们就开始展示编程实例吧。
三.项目准备
项目基于maven构建，不得不说kafka java客户端实在是太糟糕了；构建环境会遇到很多麻烦。建议参考如下pom.xml;其中各个依赖包必须版本协调一致。
<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"> <modelVersion>4.0.0</modelVersion> <groupId>com.test</groupId> <artifactId>test-kafka</artifactId> <packaging>jar</packaging> <name>test-kafka</name> <url>http://maven.apache.org</url> <version>1.0.0</version> <dependencies> <dependency> <groupId>log4j</groupId> <artifactId>log4j</artifactId> <version>1.2.14</version> </dependency> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka_2.8.0</artifactId> <version>0.8.0-beta1</version> <exclusions> <exclusion> <groupId>log4j</groupId> <artifactId>log4j</artifactId> </exclusion> </exclusions> </dependency> <dependency> <groupId>org.scala-lang</groupId> <artifactId>scala-library</artifactId> <version>2.8.1</version> </dependency> <dependency> <groupId>com.yammer.metrics</groupId> <artifactId>metrics-core</artifactId> <version>2.2.0</version> </dependency> <dependency> <groupId>com.101tec</groupId> <artifactId>zkclient</artifactId> <version>0.3</version> </dependency> </dependencies> <build> <finalName>test-kafka-1.0</finalName> <resources> <resource> <directory>src/main/resources</directory> <filtering>true</filtering> </resource> </resources> <plugins> <plugin> <artifactId>maven-compiler-plugin</artifactId> <version>2.3.2</version> <configuration> <source>1.5</source> <target>1.5</target> <encoding>gb2312</encoding> </configuration> </plugin> <plugin> <artifactId>maven-resources-plugin</artifactId> <version>2.2</version> <configuration> <encoding>gbk</encoding> </configuration> </plugin> </plugins> </build></project>
四.Producer端代码
1) producer.properties文件：此文件放在/resources目录下
#partitioner.class=metadata.broker.list=127.0.0.1:9092,127.0.0.1:9093##,127.0.0.1:9093producer.type=synccompression.codec=0serializer.class=kafka.serializer.StringEncoder##在producer.type=async时有效#batch.num.messages=100
2) LogProducer.java代码样例
package com.test.kafka;import java.util.ArrayList;import java.util.Collection;import java.util.List;import java.util.Properties;import kafka.javaapi.producer.Producer;import kafka.producer.KeyedMessage;import kafka.producer.ProducerConfig;public class LogProducer { private Producer<String,String> inner; public LogProducer() throws Exception{ Properties properties = new Properties(); properties.load(ClassLoader.getSystemResourceAsStream("producer.properties")); ProducerConfig config = new ProducerConfig(properties); inner = new Producer<String, String>(config); } public void send(String topicName,String message) { if(topicName == null || message == null){ return; } KeyedMessage<String, String> km = new KeyedMessage<String, String>(topicName,message); inner.send(km); } public void send(String topicName,Collection<String> messages) { if(topicName == null || messages == null){ return; } if(messages.isEmpty()){ return; } List<KeyedMessage<String, String>> kms = new ArrayList<KeyedMessage<String, String>>(); for(String entry : messages){ KeyedMessage<String, String> km = new KeyedMessage<String, String>(topicName,entry); kms.add(km); } inner.send(kms); } public void close(){ inner.close(); } /** * @param args */ public static void main(String[] args) { LogProducer producer = null; try{ producer = new LogProducer(); int i=0; while(true){ producer.send("test-topic", "this is a sample" + i); i++; Thread.sleep(2000); } }catch(Exception e){ e.printStackTrace(); }finally{ if(producer != null){ producer.close(); } } }}
五.Consumer端
1) consumer.properties:文件位于/resources目录下
zookeeper.connect=127.0.0.1:2181,127.0.0.1:2182,127.0.0.1:2183##,127.0.0.1:2182,127.0.0.1:2183# timeout in ms for connecting to zookeeperzookeeper.connectiontimeout.ms=1000000#consumer group idgroup.id=test-group#consumer timeout#consumer.timeout.ms=5000
2) LogConsumer.java代码样例
package com.test.kafka;import java.util.HashMap;import java.util.List;import java.util.Map;import java.util.Properties;import java.util.concurrent.ExecutorService;import java.util.concurrent.Executors;import kafka.consumer.Consumer;import kafka.consumer.ConsumerConfig;import kafka.consumer.ConsumerIterator;import kafka.consumer.KafkaStream;import kafka.javaapi.consumer.ConsumerConnector;import kafka.message.MessageAndMetadata;public class LogConsumer { private ConsumerConfig config; private String topic; private int partitionsNum; private MessageExecutor executor; private ConsumerConnector connector; private ExecutorService threadPool; public LogConsumer(String topic,int partitionsNum,MessageExecutor executor) throws Exception{ Properties properties = new Properties(); properties.load(ClassLoader.getSystemResourceAsStream("consumer.properties")); config = new ConsumerConfig(properties); this.topic = topic; this.partitionsNum = partitionsNum; this.executor = executor; } public void start() throws Exception{ connector = Consumer.createJavaConsumerConnector(config); Map<String,Integer> topics = new HashMap<String,Integer>(); topics.put(topic, partitionsNum); Map<String, List<KafkaStream<byte[], byte[]>>> streams = connector.createMessageStreams(topics); List<KafkaStream<byte[], byte[]>> partitions = streams.get(topic); threadPool = Executors.newFixedThreadPool(partitionsNum); for(KafkaStream<byte[], byte[]> partition : partitions){ threadPool.execute(new MessageRunner(partition)); } } public void close(){ try{ threadPool.shutdownNow(); }catch(Exception e){ // }finally{ connector.shutdown(); } } class MessageRunner implements Runnable{ private KafkaStream<byte[], byte[]> partition; MessageRunner(KafkaStream<byte[], byte[]> partition) { this.partition = partition; } public void run(){ ConsumerIterator<byte[], byte[]> it = partition.iterator(); while(it.hasNext()){ MessageAndMetadata<byte[],byte[]> item = it.next(); System.out.println("partiton:" + item.partition()); System.out.println("offset:" + item.offset()); executor.execute(new String(item.message()));//UTF-8 } } } interface MessageExecutor { public void execute(String message); } /** * @param args */ public static void main(String[] args) { LogConsumer consumer = null; try{ MessageExecutor executor = new MessageExecutor() { public void execute(String message) { System.out.println(message); } }; consumer = new LogConsumer("test-topic", 2, executor); consumer.start(); }catch(Exception e){ e.printStackTrace(); }finally{// if(consumer != null){// consumer.close();// } } }}
在测试时，建议优先启动consumer，然后再启动producer，这样可以实时的观测到最新的消息。
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