分布式消息队列kafka系列介绍 — 核心API介绍及实例
原文地址:http://www.inter12.org/archives/834
一 PRODUCER的API
1.Producer的创建,依赖于ProducerConfig
public Producer(ProducerConfig config);
2.单个或是批量的消息发送
public void send(KeyedMessage<K,V> message);
public void send(List<KeyedMessage<K,V>> messages);
3.关闭Producer到所有broker的连接
public void close();
二 CONSUMER的高层API
主要是Consumer和ConsumerConnector,这里的Consumer是ConsumerConnector的静态工厂类
class Consumer {
public static kafka.javaapi.consumer.ConsumerConnector createJavaConsumerConnector(config: ConsumerConfig);
}
具体的消息的消费都是在ConsumerConnector中
创建一个消息处理的流,包含所有的topic,并根据指定的Decoder
public <K,V> Map<String, List<KafkaStream<K,V>>>
createMessageStreams(Map<String, Integer> topicCountMap, Decoder<K> keyDecoder, Decoder<V> valueDecoder);
创建一个消息处理的流,包含所有的topic,使用默认的Decoder
public Map<String, List<KafkaStream<byte[], byte[]>>> createMessageStreams(Map<String, Integer> topicCountMap);
获取指定消息的topic,并根据指定的Decoder
public <K,V> List<KafkaStream<K,V>>
createMessageStreamsByFilter(TopicFilter topicFilter, int numStreams, Decoder<K> keyDecoder, Decoder<V> valueDecoder);
获取指定消息的topic,使用默认的Decoder
public List<KafkaStream<byte[], byte[]>> createMessageStreamsByFilter(TopicFilter topicFilter);
提交偏移量到这个消费者连接的topic
public void commitOffsets();
关闭消费者
public void shutdown();
高层的API中比较常用的就是public List<KafkaStream<byte[], byte[]>> createMessageStreamsByFilter(TopicFilter topicFilter);和public void commitOffsets();
三 CONSUMER的简单API–SIMPLECONSUMER
批量获取消息
public FetchResponse fetch(request: kafka.javaapi.FetchRequest);
获取topic的元信息
public kafka.javaapi.TopicMetadataResponse send(request: kafka.javaapi.TopicMetadataRequest);
获取目前可用的偏移量
public kafka.javaapi.OffsetResponse getOffsetsBefore(request: OffsetRequest);
关闭连接
public void close();
对于大部分应用来说,高层API就已经足够使用了,但是若是想做更进一步的控制的话,可以使用简单的API,例如消费者重启的情况下,希望得到最新的offset,就该使用SimpleConsumer.
四 KAFKA HADOOP CONSUMER API
提供了一个可水平伸缩的解决方案来结合hadoop的使用参见
https://github.com/linkedin/camus/tree/camus-kafka-0.8/
五 实战
maven依赖:
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.10</artifactId>
<version>0.8.0</version>
</dependency> 生产者代码: import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig; import java.util.Properties; /**
* <pre>
* Created by zhaoming on 14-5-4 下午3:23
* </pre>
*/
public class KafkaProductor { public static void main(String[] args) throws InterruptedException { Properties properties = new Properties();
properties.put("zk.connect", "127.0.0.1:2181");
properties.put("metadata.broker.list", "localhost:9092"); properties.put("serializer.class", "kafka.serializer.StringEncoder"); ProducerConfig producerConfig = new ProducerConfig(properties);
Producer<String, String> producer = new Producer<String, String>(producerConfig); // 构建消息体
KeyedMessage<String, String> keyedMessage = new KeyedMessage<String, String>("test-topic", "test-message");
producer.send(keyedMessage); Thread.sleep(1000); producer.close();
} } 消费端代码
import java.io.UnsupportedEncodingException;
import java.util.List;
import java.util.Properties;
import java.util.concurrent.TimeUnit; import kafka.consumer.*;
import kafka.javaapi.consumer.ConsumerConnector;
import kafka.message.MessageAndMetadata; import org.apache.commons.collections.CollectionUtils; /**
* <pre>
* Created by zhaoming on 14-5-4 下午3:32
* </pre>
*/
public class kafkaConsumer { public static void main(String[] args) throws InterruptedException, UnsupportedEncodingException { Properties properties = new Properties();
properties.put("zookeeper.connect", "127.0.0.1:2181");
properties.put("auto.commit.enable", "true");
properties.put("auto.commit.interval.ms", "60000");
properties.put("group.id", "test-group"); ConsumerConfig consumerConfig = new ConsumerConfig(properties); ConsumerConnector javaConsumerConnector = Consumer.createJavaConsumerConnector(consumerConfig); //topic的过滤器
Whitelist whitelist = new Whitelist("test-topic");
List<KafkaStream<byte[], byte[]>> partitions = javaConsumerConnector.createMessageStreamsByFilter(whitelist); if (CollectionUtils.isEmpty(partitions)) {
System.out.println("empty!");
TimeUnit.SECONDS.sleep(1);
} //消费消息
for (KafkaStream<byte[], byte[]> partition : partitions) { ConsumerIterator<byte[], byte[]> iterator = partition.iterator();
while (iterator.hasNext()) {
MessageAndMetadata<byte[], byte[]> next = iterator.next();
System.out.println("partiton:" + next.partition());
System.out.println("offset:" + next.offset());
System.out.println("message:" + new String(next.message(), "utf-8"));
} } }
}
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