kafka概念使用简介注意点

使用场景

大数据量、低并发、高可用、订阅消费场景

概念理解

分区个数与消费者个数

分区个数 = 消费者个数 ：最合适状态

分区个数 > 消费者个数 ：某些消费者要承担更多的分区数据消费

分区个数 < 消费者个数  ：浪费资源

当“某些消费者要承担更多的分区数据消费”，消费者接收的数据不能保证全局有序性，但能保证同一分区的数据是有序的

groupId作用

采用同一groupId，分区个数 >= 消费者个数，每个消费者都会消费数据

采用同一groupId，分区个数<消费者个数，某些消费者不会接收数据

采用不同groupId，各个groupId的消费者相互不受影响

命令行使用

启动：.inwindowskafka-server-start.bat .configserver.properties
创建topic：.inwindowskafka-topics.bat --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic lilei
开启生产者：kafka-console-producer.bat --broker-list localhost:9092 --topic lilei
开启消费者：kafka-console-consumer.bat --zookeeper localhost:2181 --topic lilei

java api使用

api 包

<dependency>  
            <groupId>org.apache.kafka</groupId>  
            <artifactId>kafka_2.11</artifactId>  
            <version>1.0.0</version>  
</dependency> 

生产者

package com.lilei.kafka.liei_kafka;

import java.util.Properties;  

import kafka.javaapi.producer.Producer;  
import kafka.producer.KeyedMessage;  
import kafka.producer.ProducerConfig;  
  
public class KafkaProducer {  
    private final Producer<String, String> producer;  
    public final static String TOPIC = "topic3";  
  
    private KafkaProducer() {  
        Properties props = new Properties();  
        // 此处配置的是kafka的端口  
        props.put("metadata.broker.list", "127.0.0.1:9092");  
        props.put("zk.connect", "127.0.0.1:2181");    
  
        // 配置value的序列化类  
        props.put("serializer.class", "kafka.serializer.StringEncoder");  
        // 配置key的序列化类  
        props.put("key.serializer.class", "kafka.serializer.StringEncoder");  
  
        props.put("request.required.acks", "-1");  
  
        producer = new Producer<String, String>(new ProducerConfig(props));  
    }  
  
    void produce() {  
        int messageNo = 0;  
        final int COUNT = Integer.MAX_VALUE;  
  
        while (messageNo < COUNT) {  
            String key = String.valueOf(messageNo);  
            try {
                Thread.sleep(300);
            } catch (InterruptedException e) {
                // TODO Auto-generated catch block
                e.printStackTrace();
            }
            String data = "hello kafka message " + key;  
            producer.send(new KeyedMessage<String, String>(TOPIC, key, data));  
            System.out.println(data);  
            messageNo++;  
        }  
    }  
  
    public static void main(String[] args) {  
        new KafkaProducer().produce();  
    }  
}  

消费者

package com.lilei.kafka.liei_kafka;

import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;

import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
import kafka.message.MessageAndMetadata;
import kafka.serializer.StringDecoder;
import kafka.utils.VerifiableProperties;
  
  
public class KafkaConsumer {  
  
    private final ConsumerConnector consumer;  
  
    private KafkaConsumer() {  
        Properties props = new Properties();  
        // zookeeper 配置  
        props.put("zookeeper.connect", "localhost:2181");  
  
        // group 代表一个消费组  
        props.put("group.id", "vvvxyzv");  
  
        // zk连接超时  
        props.put("zookeeper.session.timeout.ms", "5000");  
        props.put("zookeeper.sync.time.ms", "10000");  
        props.put("rebalance.max.retries", "10");  
        props.put("rebalance.backoff.ms", "2000");  
          
      
        props.put("auto.commit.interval.ms", "1000");  
        props.put("auto.offset.reset", "smallest");  
        // 序列化类  
        props.put("serializer.class", "kafka.serializer.StringEncoder");  
  
        ConsumerConfig config = new ConsumerConfig(props);  
  
        consumer = kafka.consumer.Consumer.createJavaConsumerConnector(config);  
    }  
  
    void consume() {  
        String topic = "topic3";
        
        Map<String, Integer> topicCountMap = new HashMap<String, Integer>();  
        topicCountMap.put(topic, new Integer(1));  
  
        StringDecoder keyDecoder = new StringDecoder(new VerifiableProperties());  
        StringDecoder valueDecoder = new StringDecoder(new VerifiableProperties());  
  
        Map<String, List<KafkaStream<String, String>>> consumerMap = consumer.createMessageStreams(topicCountMap, keyDecoder, valueDecoder);  
        KafkaStream<String, String> stream = consumerMap.get(topic).get(0);  
        ConsumerIterator<String, String> it = stream.iterator();  
        while (it.hasNext())  
        {
            MessageAndMetadata<String,String> mam = it.next();
            
            System.out.println(mam.key()+"---"+mam.message());
        }
//            System.out.println("<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<" + it.next().message() + "<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<");  
    }  
  
    public static void main(String[] args) {  
        new KafkaConsumer().consume();  
    }  
}  

注意点

使用的kafka api版本要注意，在不合适或者存在bug的状态下，会报： kafka.common.ConsumerRebalanceFailedException

监控

java -cp KafkaOffsetMonitor-assembly-0.2.0.jar com.quantifind.kafka.offsetapp.OffsetGetterWeb --zk localhost:2181 --port 8086 --refresh 10.seconds --retain 2.days