Kafka Java Consumer实现(二)

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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>

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