Kafka Java Producer代码实例详解

根据业务需要可以使用Kafka提供的Java Producer API进行产生数据，并将产生的数据发送到Kafka对应Topic的对应分区中，入口类为：Producer

Kafka的Producer API主要提供下列三个方法：

public void send(KeyedMessage<K,V> message) 发送单条数据到Kafka集群 public void send(List<KeyedMessage<K,V>> messages) 发送多条数据(数据集)到Kafka集群 public void close() 关闭Kafka连接资源

一、JavaKafkaProducerPartitioner：自定义的数据分区器，功能是：决定输入的key/value键值对的message发送到Topic的那个分区中，返回分区id，范围:[0,分区数量); 这里的实现比较简单，根据key中的数字决定分区的值。具体代码如下：

import kafka.producer.Partitioner;import kafka.utils.VerifiableProperties;/** * Created by gerry on 12/21. */public class JavaKafkaProducerPartitioner implements Partitioner { /** * 无参构造函数 */ public JavaKafkaProducerPartitioner() { this(new VerifiableProperties()); } /** * 构造函数，必须给定 * * @param properties 上下文 */ public JavaKafkaProducerPartitioner(VerifiableProperties properties) { // nothings } @Override public int partition(Object key, int numPartitions) { int num = Integer.valueOf(((String) key).replaceAll('key_', '').trim()); return num % numPartitions; }}

二、 JavaKafkaProducer：通过Kafka提供的API进行数据产生操作的测试类；具体代码如下：

import kafka.javaapi.producer.Producer;import kafka.producer.KeyedMessage;import kafka.producer.ProducerConfig;import org.apache.log4j.Logger;import java.util.Properties;import java.util.concurrent.ExecutorService;import java.util.concurrent.Executors;import java.util.concurrent.TimeUnit;import java.util.concurrent.atomic.AtomicBoolean;import java.util.concurrent.ThreadLocalRandom;/** * Created by gerry on 12/21. */public class JavaKafkaProducer { private Logger logger = Logger.getLogger(JavaKafkaProducer.class); public static final String TOPIC_NAME = 'test'; public static final char[] charts = 'qazwsxedcrfvtgbyhnujmikolp1234567890'.toCharArray(); public static final int chartsLength = charts.length; public static void main(String[] args) { String brokerList = '192.168.187.149:9092'; brokerList = '192.168.187.149:9092,192.168.187.149:9093,192.168.187.149:9094,192.168.187.149:9095'; brokerList = '192.168.187.146:9092'; Properties props = new Properties(); props.put('metadata.broker.list', brokerList); /** * 0表示不等待结果返回<br/> * 1表示等待至少有一个服务器返回数据接收标识<br/> * -1表示必须接收到所有的服务器返回标识，及同步写入<br/> * */ props.put('request.required.acks', '0'); /** * 内部发送数据是异步还是同步 * sync：同步, 默认 * async：异步 */ props.put('producer.type', 'async'); /** * 设置序列化的类 * 可选：kafka.serializer.StringEncoder * 默认：kafka.serializer.DefaultEncoder */ props.put('serializer.class', 'kafka.serializer.StringEncoder'); /** * 设置分区类 * 根据key进行数据分区 * 默认是：kafka.producer.DefaultPartitioner ==> 安装key的hash进行分区 * 可选:kafka.serializer.ByteArrayPartitioner ==> 转换为字节数组后进行hash分区 */ props.put('partitioner.class', 'JavaKafkaProducerPartitioner'); // 重试次数 props.put('message.send.max.retries', '3'); // 异步提交的时候(async)，并发提交的记录数 props.put('batch.num.messages', '200'); // 设置缓冲区大小，默认10KB props.put('send.buffer.bytes', '102400'); // 2. 构建Kafka Producer Configuration上下文 ProducerConfig config = new ProducerConfig(props); // 3. 构建Producer对象 final Producer<String, String> producer = new Producer<String, String>(config); // 4. 发送数据到服务器，并发线程发送 final AtomicBoolean flag = new AtomicBoolean(true); int numThreads = 50; ExecutorService pool = Executors.newFixedThreadPool(numThreads); for (int i = 0; i < 5; i++) { pool.submit(new Thread(new Runnable() {@Overridepublic void run() { while (flag.get()) { // 发送数据 KeyedMessage message = generateKeyedMessage(); producer.send(message); System.out.println('发送数据:' + message); // 休眠一下 try { int least = 10; int bound = 100; Thread.sleep(ThreadLocalRandom.current().nextInt(least, bound)); } catch (InterruptedException e) { e.printStackTrace(); } } System.out.println(Thread.currentThread().getName() + ' shutdown....');} }, 'Thread-' + i)); } // 5. 等待执行完成 long sleepMillis = 600000; try { Thread.sleep(sleepMillis); } catch (InterruptedException e) { e.printStackTrace(); } flag.set(false); // 6. 关闭资源 pool.shutdown(); try { pool.awaitTermination(6, TimeUnit.SECONDS); } catch (InterruptedException e) { } finally { producer.close(); // 最后之后调用 } } /** * 产生一个消息 * * @return */ private static KeyedMessage<String, String> generateKeyedMessage() { String key = 'key_' + ThreadLocalRandom.current().nextInt(10, 99); StringBuilder sb = new StringBuilder(); int num = ThreadLocalRandom.current().nextInt(1, 5); for (int i = 0; i < num; i++) { sb.append(generateStringMessage(ThreadLocalRandom.current().nextInt(3, 20))).append(' '); } String message = sb.toString().trim(); return new KeyedMessage(TOPIC_NAME, key, message); } /** * 产生一个给定长度的字符串 * * @param numItems * @return */ private static String generateStringMessage(int numItems) { StringBuilder sb = new StringBuilder(); for (int i = 0; i < numItems; i++) { sb.append(charts[ThreadLocalRandom.current().nextInt(chartsLength)]); } return sb.toString(); }}

三、Pom.xml依赖配置如下

<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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