使用Kafka的High Level Consumer

##为什么使用High Level Consumer

在某些应用场景，我们希望通过多线程读取消息，而我们并不关心从Kafka消费消息的顺序，我们仅仅关心数据能被消费就行。High Level 就是用于抽象这类消费动作的。
消息消费已Consumer Group为单位，每个Consumer Group中可以有多个consumer，每个consumer是一个线程，topic的每个partition同时只能被某一个consumer读取，Consumer Group对应的每个partition都有一个最新的offset的值，存储在zookeeper上的。所以不会出现重复消费的情况。

##设计High Level Consumer High Level Consumer 可以并且应该被使用在多线程的环境，线程模型中线程的数量(也代表group中consumer的数量)和topic的partition数量有关，下面列举一些规则：

当提供的线程数量多于partition的数量，则部分线程将不会接收到消息；
当提供的线程数量少于partition的数量，则部分线程将从多个partition接收消息；
当某个线程从多个partition接收消息时，不保证接收消息的顺序；可能出现从partition3接收5条消息，从partition4接收6条消息，接着又从partition3接收10条消息；
当添加更多线程时，会引起kafka做re-balance, 可能改变partition和线程的对应关系。

##代码示例 ConsumerGroupExample

package com.test.groups;

import kafka.consumer.ConsumerConfig;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;

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;

public class ConsumerGroupExample {
	private final ConsumerConnector consumer;
	private final String topic;
	private  ExecutorService executor;

	public ConsumerGroupExample(String a_zookeeper, String a_groupId, String a_topic) {
		consumer = kafka.consumer.Consumer.createJavaConsumerConnector(
				createConsumerConfig(a_zookeeper, a_groupId));
		this.topic = a_topic;
	}

	public void shutdown() {
		if (consumer != null) consumer.shutdown();
		if (executor != null) executor.shutdown();
	}

	public void run(int a_numThreads) {
		Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
		topicCountMap.put(topic, new Integer(a_numThreads));
		Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap = consumer.createMessageStreams(topicCountMap);
		List<KafkaStream<byte[], byte[]>> streams = consumerMap.get(topic);

		// now launch all the threads
		//
		executor = Executors.newFixedThreadPool(a_numThreads);

		// now create an object to consume the messages
		//
		int threadNumber = 0;
		for (final KafkaStream stream : streams) {
			executor.submit(new ConsumerTest(stream, threadNumber));
			threadNumber++;
		}
	}

	private static ConsumerConfig createConsumerConfig(String a_zookeeper, String a_groupId) {
		Properties props = new Properties();
		props.put("zookeeper.connect", a_zookeeper);
		props.put("group.id", a_groupId);
		props.put("zookeeper.session.timeout.ms", "400");
		props.put("zookeeper.sync.time.ms", "200");
		props.put("auto.commit.interval.ms", "1000");

		return new ConsumerConfig(props);
	}

	public static void main(String[] args) {
		String zooKeeper = args[0];
		String groupId = args[1];
		String topic = args[2];
		int threads = Integer.parseInt(args[3]);

		ConsumerGroupExample example = new ConsumerGroupExample(zooKeeper, groupId, topic);
		example.run(threads);

		try {
			Thread.sleep(10000);
		} catch (InterruptedException ie) {

		}
		example.shutdown();
	}
}

ConsumerTest

package com.test.groups;

import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;

public class ConsumerTest implements Runnable {
	private KafkaStream m_stream;
	private int m_threadNumber;

	public ConsumerTest(KafkaStream a_stream, int a_threadNumber) {
		m_threadNumber = a_threadNumber;
		m_stream = a_stream;
	}

	public void run() {
		ConsumerIterator<byte[], byte[]> it = m_stream.iterator();
		while (it.hasNext())
			System.out.println("Thread " + m_threadNumber + ": " + new String(it.next().message()));
		System.out.println("Shutting down Thread: " + m_threadNumber);
	}
}