Kafka Java Producer代碼實例詳解

根據業務需要可以使用Kafka提供的Java Producer API進行產生數據，并將產生的數據發送到Kafka對應Topic的對應分區中，入口類為：Producer

Kafka的Producer API主要提供下列三個方法：

public void send(KeyedMessage<K,V> message) 發送單條數據到Kafka集群 public void send(List<KeyedMessage<K,V>> messages) 發送多條數據(數據集)到Kafka集群 public void close() 關閉Kafka連接資源

一、JavaKafkaProducerPartitioner：自定義的數據分區器，功能是：決定輸入的key/value鍵值對的message發送到Topic的那個分區中，返回分區id，范圍:[0,分區數量); 這里的實現比較簡單，根據key中的數字決定分區的值。具體代碼如下：

import kafka.producer.Partitioner;import kafka.utils.VerifiableProperties;/** * Created by gerry on 12/21. */public class JavaKafkaProducerPartitioner implements Partitioner { /** * 無參構造函數 */ public JavaKafkaProducerPartitioner() { this(new VerifiableProperties()); } /** * 構造函數，必須給定 * * @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：通過Kafka提供的API進行數據產生操作的測試類；具體代碼如下：

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表示不等待結果返回<br/> * 1表示等待至少有一個服務器返回數據接收標識<br/> * -1表示必須接收到所有的服務器返回標識，及同步寫入<br/> * */ props.put('request.required.acks', '0'); /** * 內部發送數據是異步還是同步 * sync：同步, 默認 * async：異步 */ props.put('producer.type', 'async'); /** * 設置序列化的類 * 可選：kafka.serializer.StringEncoder * 默認：kafka.serializer.DefaultEncoder */ props.put('serializer.class', 'kafka.serializer.StringEncoder'); /** * 設置分區類 * 根據key進行數據分區 * 默認是：kafka.producer.DefaultPartitioner ==> 安裝key的hash進行分區 * 可選:kafka.serializer.ByteArrayPartitioner ==> 轉換為字節數組后進行hash分區 */ props.put('partitioner.class', 'JavaKafkaProducerPartitioner'); // 重試次數 props.put('message.send.max.retries', '3'); // 異步提交的時候(async)，并發提交的記錄數 props.put('batch.num.messages', '200'); // 設置緩沖區大小，默認10KB props.put('send.buffer.bytes', '102400'); // 2. 構建Kafka Producer Configuration上下文 ProducerConfig config = new ProducerConfig(props); // 3. 構建Producer對象 final Producer<String, String> producer = new Producer<String, String>(config); // 4. 發送數據到服務器，并發線程發送 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()) { // 發送數據 KeyedMessage message = generateKeyedMessage(); producer.send(message); System.out.println('發送數據:' + 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. 等待執行完成 long sleepMillis = 600000; try { Thread.sleep(sleepMillis); } catch (InterruptedException e) { e.printStackTrace(); } flag.set(false); // 6. 關閉資源 pool.shutdown(); try { pool.awaitTermination(6, TimeUnit.SECONDS); } catch (InterruptedException e) { } finally { producer.close(); // 最后之后調用 } } /** * 產生一個消息 * * @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); } /** * 產生一個給定長度的字符串 * * @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依賴配置如下

<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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