Kafka部署与代码实例

agangliu0400

    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.（本示例基于伪分布式部署）
    1) zk-0
调整配置文件：

clientPort=2181
server.0=127.0.0.1:2888:3888
server.1=127.0.0.1:2889:3889
server.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=0
port=9092
num.network.threads=2
num.io.threads=2
socket.send.buffer.bytes=1048576
socket.receive.buffer.bytes=1048576
socket.request.max.bytes=104857600
log.dir=./logs
num.partitions=2
log.flush.interval.messages=10000
log.flush.interval.ms=1000
log.retention.hours=168
#log.retention.bytes=1073741824
log.segment.bytes=536870912
##replication机制,让每个topic的partitions在kafka-cluster中备份2个
##用来提高cluster的容错能力..
default.replication.factor=1
log.cleanup.interval.mins=10
##zookeeper.connect指定zookeeper的地址，默认情况下将会在zk的“/”目录下
##创建meta信息和路径，为了对znode进行归类，我们可以在connect之后追加路径，比如
##127.0.0.1:2183/kafka
##不过需要注意，此后的producer、consumer都需要带上此根路径
zookeeper.connect=127.0.0.1:2181,127.0.0.1:2182,127.0.0.1:2183
zookeeper.connection.timeout.ms=1000000
    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=1
port=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 &
    仍然可以通过如下指令查看topic的"partition"/"replicas"的分布和存活情况.

> bin/kafka-list-topic.sh --zookeeper localhost:2181
topic: my-replicated-topicpartition: 0leader: 2replicas: 1,2,0isr: 2
topic: testpartition: 0leader: 0replicas: 0isr: 0 
    到目前为止环境已经OK了,那我们就开始展示编程实例吧。[配置参数详解]
 
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。如果kafka client的版本和kafka server的版本不一致,将会有很多异常,比如"broker id not exists"等;因为kafka从0.7升级到0.8之后(正名为2.8.0),client与server通讯的protocol已经改变.

<dependencies>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.14</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.8.2</artifactId>
<version>0.8.0</version>
<exclusions>
<exclusion>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>2.8.2</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>
 
四.Producer端代码
    1) producer.properties文件：此文件放在/resources目录下

#partitioner.class=
##broker列表可以为kafka server的子集,因为producer需要从broker中获取metadata
##尽管每个broker都可以提供metadata,此处还是建议,将所有broker都列举出来
##此值,我们可以在spring中注入过来
##metadata.broker.list=127.0.0.1:9092,127.0.0.1:9093
##,127.0.0.1:9093
##同步,建议为async
producer.type=sync
compression.codec=0
serializer.class=kafka.serializer.StringEncoder
##在producer.type=async时有效
#batch.num.messages=100
    2) KafkaProducerClient.java代码样例

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;
/**
* User: guanqing-liu
*/
public class KafkaProducerClient {
private Producer<String, String> inner;
private String brokerList;//for metadata discovery,spring setter
private String location = "kafka-producer.properties";//spring setter
private String defaultTopic;//spring setter
public void setBrokerList(String brokerList) {
this.brokerList = brokerList;
}
public void setLocation(String location) {
this.location = location;
}
public void setDefaultTopic(String defaultTopic) {
this.defaultTopic = defaultTopic;
}
public KafkaProducerClient(){}
public void init() throws Exception {
Properties properties = new Properties();
properties.load(Thread.currentThread().getContextClassLoader().getResourceAsStream(location));

if(brokerList != null) {
properties.put("metadata.broker.list", brokerList);
}
ProducerConfig config = new ProducerConfig(properties);
inner = new Producer<String, String>(config);
}
public void send(String message){
send(defaultTopic,message);
}
public void send(Collection<String> messages){
send(defaultTopic,messages);
}
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>>();
int i= 0;
for (String entry : messages) {
KeyedMessage<String, String> km = new KeyedMessage<String, String>(topicName,entry);
kms.add(km);
i++;
if(i % 20 == 0){
inner.send(kms);
kms.clear();
}
}
if(!kms.isEmpty()){
inner.send(kms);
}
}
public void close() {
inner.close();
}
/**
* @param args
*/
public static void main(String[] args) {
KafkaProducerClient producer = null;
try {
producer = new KafkaProducerClient();
//producer.setBrokerList("");
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();
}
}
}
}
    3) spring配置

    <bean id="kafkaProducerClient" class="com.test.kafka.KafkaProducerClient" init-method="init" destroy-method="close">
<property name="zkConnect" value="${zookeeper_cluster}"></property>
<property name="defaultTopic" value="${kafka_topic}"></property>
</bean>
 
五.Consumer端
1) consumer.properties:文件位于/resources目录下

## 此值可以配置,也可以通过spring注入
##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 zookeeper
zookeeper.connectiontimeout.ms=1000000
#consumer group id
group.id=test-group
#consumer timeout
#consumer.timeout.ms=5000
auto.commit.enable=true
auto.commit.interval.ms=60000
    2) KafkaConsumerClient.java代码样例

package com.test.kafka;
import java.nio.ByteBuffer;
import java.nio.CharBuffer;
import java.nio.charset.Charset;
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.Message;
import kafka.message.MessageAndMetadata;
/**
* User: guanqing-liu
*/
public class KafkaConsumerClient {
private String groupid; //can be setting by spring
private String zkConnect;//can be setting by spring
private String location = "kafka-consumer.properties";//配置文件位置
private String topic;
private int partitionsNum = 1;
private MessageExecutor executor; //message listener
private ExecutorService threadPool;
private ConsumerConnector connector;
private Charset charset = Charset.forName("utf8");
public void setGroupid(String groupid) {
this.groupid = groupid;
}
public void setZkConnect(String zkConnect) {
this.zkConnect = zkConnect;
}
public void setLocation(String location) {
this.location = location;
}
public void setTopic(String topic) {
this.topic = topic;
}
public void setPartitionsNum(int partitionsNum) {
this.partitionsNum = partitionsNum;
}
public void setExecutor(MessageExecutor executor) {
this.executor = executor;
}
public KafkaConsumerClient() {}
//init consumer,and start connection and listener
public void init() throws Exception {
if(executor == null){
throw new RuntimeException("KafkaConsumer,exectuor cant be null!");
}
Properties properties = new Properties();
properties.load(Thread.currentThread().getContextClassLoader().getResourceAsStream(location));
if(groupid != null){
properties.put("groupid", groupid);
}
if(zkConnect != null){
properties.put("zookeeper.connect", zkConnect);
}
ConsumerConfig config = new ConsumerConfig(properties);
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 * 2);
//start
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()) {
// connector.commitOffsets();手动提交offset,当autocommit.enable=false时使用
MessageAndMetadata<byte[], byte[]> item = it.next();
try{
executor.execute(new String(item.message(),charset));// UTF-8,注意异常
}catch(Exception e){
//
}
}
}
public String getContent(Message message){
ByteBuffer buffer = message.payload();
if (buffer.remaining() == 0) {
return null;
}
CharBuffer charBuffer = charset.decode(buffer);
return charBuffer.toString();
}
}
public static interface MessageExecutor {
public void execute(String message);
}
/**
* @param args
*/
public static void main(String[] args) {
KafkaConsumerClient consumer = null;
try {
MessageExecutor executor = new MessageExecutor() {
public void execute(String message) {
System.out.println(message);
}
};
consumer = new KafkaConsumerClient();
consumer.setTopic("test-topic");
consumer.setPartitionsNum(2);
consumer.setExecutor(executor);
consumer.init();
} catch (Exception e) {
e.printStackTrace();
} finally {
if(consumer != null){
consumer.close();
}
}
}
}
3) spring配置(略)
 
    需要提醒的是,上述LogConsumer类中,没有太多的关注异常情况,必须在MessageExecutor.execute()方法中抛出异常时的情况.
    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。