[Kafka] - Kafka Java Consumer实现(二)
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)
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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
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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>
