java自己手动控制kafka的offset

java自己手动控制kafka的offset，让每个消费者和对应的patition建立对应的流来读取kafka上面的数据，如果comsumer得到数据，那么kafka就会自动去维护该comsumer的offset，例如在获取到kafka的消息后正准备入库（未入库），但是消费者挂了，那么如果让kafka自动去维护offset，它就会认为这条数据已经被消费了，那么会造成数据丢失。

但是kafka可以让你自己去手动提交，如果在上面的场景中，那么需要我们手动commit，如果comsumer挂了 那么程序就不会执行commit这样的话 其他同group的消费者又可以消费这条数据，保证数据不丢，先要做如下设置：

//设置不自动提交，自己手动更新offset
properties.put("enable.auto.commit", "false");

使用如下api提交：

consumer.commitSync();

注意：

刚做了个测试，如果我从kafka中取出5条数据，分别为1,2,3,4,5，如果消费者在执行一些逻辑在执行1,2,3，4的时候都失败了未提交commit，然后消费5做逻辑成功了提交了commit，那么offset也会被移动到5那一条数据那里，1,2,3,4 相当于也会丢失

如果是做消费者取出数据执行一些操作，全部都失败的话，然后重启消费者，这些数据会从失败的时候重新开始读取

所以消费者还是应该自己做容错机制

测试项目结构如下:

其中ConsumerThreadNew类：

package com.lijie.kafka;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * 
 *                       
 * @Filename ConsumerThreadNew.java
 *
 * @Description 
 *
 * @Version 1.0
 *
 * @Author Lijie
 *
 * @Email lijiewj39069@touna.cn
 *       
 * @History
 *

Author: Lijie
*
Date: 2017年3月21日
*
Version: 1.0
*
Content: create
* */ public class ConsumerThreadNew implements Runnable { private static Logger LOG = LoggerFactory.getLogger(ConsumerThreadNew.class); //KafkaConsumer kafka生产者 private KafkaConsumer consumer; //消费者名字 private String name; //消费的topic组 private List topics; //构造函数 public ConsumerThreadNew(KafkaConsumer consumer, String topic, String name) { super(); this.consumer = consumer; this.name = name; this.topics = Arrays.asList(topic); } @Override public void run() { consumer.subscribe(topics); List<>> buffer = new ArrayList<>(); // 批量提交数量 final int minBatchSize = 1; while (true) { ConsumerRecords records = consumer.poll(100); for (ConsumerRecord record : records) { LOG.info("消费者的名字为:" + name + ",消费的消息为：" + record.value()); buffer.add(record); } if (buffer.size() >= minBatchSize) { //这里就是处理成功了然后自己手动提交 consumer.commitSync(); LOG.info("提交完毕"); buffer.clear(); } } } }

MyConsume类如下：

package com.lijie.kafka;

import java.util.Properties;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * 
 *                       
 * @Filename MyConsume.java
 *
 * @Description 
 *
 * @Version 1.0
 *
 * @Author Lijie
 *
 * @Email lijiewj39069@touna.cn
 *       
 * @History
 *

Author: Lijie
*
Date: 2017年3月21日
*
Version: 1.0
*
Content: create
* */ public class MyConsume { private static Logger LOG = LoggerFactory.getLogger(MyConsume.class); public MyConsume() { // TODO Auto-generated constructor stub } public static void main(String[] args) { Properties properties = new Properties(); properties.put("bootstrap.servers", "10.0.4.141:19093,10.0.4.142:19093,10.0.4.143:19093"); //设置不自动提交，自己手动更新offset properties.put("enable.auto.commit", "false"); properties.put("auto.offset.reset", "latest"); properties.put("zookeeper.connect", "10.0.4.141:2181,10.0.4.142:2181,10.0.4.143:2181"); properties.put("session.timeout.ms", "30000"); properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer"); properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer"); properties.put("group.id", "lijieGroup"); properties.put("zookeeper.connect", "192.168.80.123:2181"); properties.put("auto.commit.interval.ms", "1000"); ExecutorService executor = Executors.newFixedThreadPool(5); //执行消费 for (int i = 0; i < 7; i++) { executor.execute(new ConsumerThreadNew(new KafkaConsumer(properties), "lijietest", "消费者" + (i + 1))); } } }

MyProducer类如下：

package com.lijie.kafka;

import java.util.Properties;

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;

/**
 * 
 *                       
 * @Filename MyProducer.java
 *
 * @Description 
 *
 * @Version 1.0
 *
 * @Author Lijie
 *
 * @Email lijiewj39069@touna.cn
 *       
 * @History
 *

Author: Lijie
*
Date: 2017年3月21日
*
Version: 1.0
*
Content: create
* */ public class MyProducer { private static Properties properties; private static KafkaProducer pro; static { //配置 properties = new Properties(); properties.put("bootstrap.servers", "10.0.4.141:19093,10.0.4.142:19093,10.0.4.143:19093"); //序列化类型 properties .put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer"); properties.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer"); //创建生产者 pro = new KafkaProducer<>(properties); } public static void main(String[] args) throws Exception { produce("lijietest"); } public static void produce(String topic) throws Exception { //模拟message // String value = UUID.randomUUID().toString(); for (int i = 0; i < 10000; i++) { //封装message ProducerRecord pr = new ProducerRecord(topic, i + ""); //发送消息 pro.send(pr); Thread.sleep(1000); } } }

pom文件如下：

    4.0.0
    lijie-kafka-offset
    lijie-kafka-offset
    0.0.1-SNAPSHOT
    
        
            org.apache.kafka
            kafka_2.11
            0.10.1.1
        
        
            org.apache.hadoop
            hadoop-common
            2.2.0
        
        
            org.apache.hadoop
            hadoop-hdfs
            2.2.0
        
        
            org.apache.hadoop
            hadoop-client
            2.2.0
        
        
            org.apache.hbase
            hbase-client
            1.0.3
        
        
            org.apache.hbase
            hbase-server
            1.0.3
        
        
            org.apache.hadoop
            hadoop-hdfs
            2.2.0
        
        
            jdk.tools
            jdk.tools
            1.7
            system
            ${JAVA_HOME}/lib/tools.jar
        
        
            org.apache.httpcomponents
            httpclient
            4.3.6
        
    
    
        
            
                org.apache.maven.plugins
                maven-compiler-plugin
                
                    1.7
                    1.7