Kafka提供了两种Consumer API，分别是：High Level Consumer API 和 Lower Level Consumer API(Simple Consumer API)
High Level Consumer API：高度抽象的Kafka消费者API；将底层具体获取数据、更新offset、设置偏移量等操作屏蔽掉，直接将操作数据流的处理工作提供给编写程序的人员。优点是：操作简单；缺点：可操作性太差，无法按照自己的业务场景选择处理方式。(入口类：ConsumerConnector)
Lower Level Consumer API：通过直接操作底层API获取数据的方式获取Kafka中的数据，需要自行给定分区、偏移量等属性。优点：可操作性强；缺点：代码相对而言比较复杂。(入口类：SimpleConsumer)
这里主要将High Level Consumer API使用Java代码实现并测试：
Lower Level Consumer API详见博客：[Kafka] - Kafka Java Consumer实现(一)
========================================================================
一、JavaKafkaConsumerHighAPI：使用Kafka High Level Consumer API多线程读取数据的相关API实现，具体代码如下：
import kafka.consumer.*;
import kafka.javaapi.consumer.ConsumerConnector;
import kafka.message.MessageAndMetadata;
import kafka.serializer.StringDecoder;
import kafka.utils.VerifiableProperties; 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 java.util.concurrent.TimeUnit; /**
* 自定义简单Kafka消费者， 使用高级API
* Created by gerry on 12/21.
*/
public class JavaKafkaConsumerHighAPI implements Runnable {
/**
* Kafka数据消费对象
*/
private ConsumerConnector consumer; /**
* Kafka Topic名称
*/
private String topic; /**
* 线程数量，一般就是Topic的分区数量
*/
private int numThreads; /**
* 线程池
*/
private ExecutorService executorPool; /**
* 构造函数
*
* @param topic Kafka消息Topic主题
* @param numThreads 处理数据的线程数/可以理解为Topic的分区数
* @param zookeeper Kafka的Zookeeper连接字符串
* @param groupId 该消费者所属group ID的值
*/
public JavaKafkaConsumerHighAPI(String topic, int numThreads, String zookeeper, String groupId) {
// 1. 创建Kafka连接器
this.consumer = Consumer.createJavaConsumerConnector(createConsumerConfig(zookeeper, groupId));
// 2. 数据赋值
this.topic = topic;
this.numThreads = numThreads;
} @Override
public void run() {
// 1. 指定Topic
Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
topicCountMap.put(this.topic, this.numThreads); // 2. 指定数据的解码器
StringDecoder keyDecoder = new StringDecoder(new VerifiableProperties());
StringDecoder valueDecoder = new StringDecoder(new VerifiableProperties()); // 3. 获取连接数据的迭代器对象集合
/**
* Key: Topic主题
* Value: 对应Topic的数据流读取器，大小是topicCountMap中指定的topic大小
*/
Map<String, List<KafkaStream<String, String>>> consumerMap = this.consumer.createMessageStreams(topicCountMap, keyDecoder, valueDecoder); // 4. 从返回结果中获取对应topic的数据流处理器
List<KafkaStream<String, String>> streams = consumerMap.get(this.topic); // 5. 创建线程池
this.executorPool = Executors.newFixedThreadPool(this.numThreads); // 6. 构建数据输出对象
int threadNumber = 0;
for (final KafkaStream<String, String> stream : streams) {
this.executorPool.submit(new ConsumerKafkaStreamProcesser(stream, threadNumber));
threadNumber++;
}
} public void shutdown() {
// 1. 关闭和Kafka的连接，这样会导致stream.hashNext返回false
if (this.consumer != null) {
this.consumer.shutdown();
} // 2. 关闭线程池，会等待线程的执行完成
if (this.executorPool != null) {
// 2.1 关闭线程池
this.executorPool.shutdown(); // 2.2. 等待关闭完成, 等待五秒
try {
if (!this.executorPool.awaitTermination(5, TimeUnit.SECONDS)) {
System.out.println("Timed out waiting for consumer threads to shut down, exiting uncleanly!!");
}
} catch (InterruptedException e) {
System.out.println("Interrupted during shutdown, exiting uncleanly!!");
}
} } /**
* 根据传入的zk的连接信息和groupID的值创建对应的ConsumerConfig对象
*
* @param zookeeper zk的连接信息，类似于：<br/>
* hadoop-senior01.ibeifeng.com:2181,hadoop-senior02.ibeifeng.com:2181/kafka
* @param groupId 该kafka consumer所属的group id的值， group id值一样的kafka consumer会进行负载均衡
* @return Kafka连接信息
*/
private ConsumerConfig createConsumerConfig(String zookeeper, String groupId) {
// 1. 构建属性对象
Properties prop = new Properties();
// 2. 添加相关属性
prop.put("group.id", groupId); // 指定分组id
prop.put("zookeeper.connect", zookeeper); // 指定zk的连接url
prop.put("zookeeper.session.timeout.ms", "400"); //
prop.put("zookeeper.sync.time.ms", "200");
prop.put("auto.commit.interval.ms", "1000");
// 3. 构建ConsumerConfig对象
return new ConsumerConfig(prop);
} /**
* Kafka消费者数据处理线程
*/
public static class ConsumerKafkaStreamProcesser implements Runnable {
// Kafka数据流
private KafkaStream<String, String> stream;
// 线程ID编号
private int threadNumber; public ConsumerKafkaStreamProcesser(KafkaStream<String, String> stream, int threadNumber) {
this.stream = stream;
this.threadNumber = threadNumber;
} @Override
public void run() {
// 1. 获取数据迭代器
ConsumerIterator<String, String> iter = this.stream.iterator();
// 2. 迭代输出数据
while (iter.hasNext()) {
// 2.1 获取数据值
MessageAndMetadata value = iter.next(); // 2.2 输出
System.out.println(this.threadNumber + ":" + ":" + value.offset() + value.key() + ":" + value.message());
}
// 3. 表示当前线程执行完成
System.out.println("Shutdown Thread:" + this.threadNumber);
}
}
}
二、JavaKafkaConsumerHighAPITest：测试类
/**
* Created by ibf on 12/21.
*/
public class JavaKafkaConsumerHighAPITest {
public static void main(String[] args) {
String zookeeper = "192.168.187.146:2181";
String groupId = "group1";
String topic = "test2";
int threads = 1; JavaKafkaConsumerHighAPI example = new JavaKafkaConsumerHighAPI(topic, threads, zookeeper, groupId);
new Thread(example).start(); // 执行10秒后结束
int sleepMillis = 600000;
try {
Thread.sleep(sleepMillis);
} catch (InterruptedException e) {
e.printStackTrace();
}
// 关闭
example.shutdown();
}
}
三、运行测试截图
Kafka相关命令可以参考博客[Kafka] - Kafka基本操作命令, 测试截图如下：
至此，开发基本完成
========================================================
四、Kafka Pom文件依赖
<properties>
<kafka.version>0.8.2.1</kafka.version>
</properties> <dependencies>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.10</artifactId>
<version>${kafka.version}</version>
</dependency>
</dependencies>