生产者每次调用poll()方法时,它总是返回由生产者写入Kafka但还没有消费的消息,如果消费者一致处于运行状态,那么分区消息偏移量就没什么用处,但是如果消费者发生崩溃或者有新的消费者加入群组,就会触发再均衡,完成再均衡之后,每个消费可能分配到新的分区,而不是之前处理的那个,为了能够继续之前的工作,消费者需要读取每个分区最后一次提交的偏移量,然后从偏移量制定的地方开始工作。消费者会往一个__consumer_offser的主题发送消息,消息里包含每个分区的偏移量。
1.同步提交
import org.apache.kafka.clients.consumer.ConsumerRecord; import org.apache.kafka.clients.consumer.ConsumerRecords; import org.apache.kafka.clients.consumer.KafkaConsumer; import java.util.Collections; import java.util.Properties; /** * Created by zhangpeiran on 2018/10/9. */ public class MyConsumer { public static void main(String[] args){ Properties properties = new Properties(); properties.put("bootstrap.servers","ip:9092"); properties.put("key.deserializer","org.apache.kafka.common.serialization.StringDeserializer"); properties.put("value.deserializer","org.apache.kafka.common.serialization.StringDeserializer"); properties.put("group.id","DemoConsumerGroup"); //默认值为latest,当消费者读取的分区没有偏移量或偏移量无效时,消费者将从最新的记录开始读 //当一个消费group第一次订阅主题时,符合这种情况,在Consumer启动之前,Producer生产的数据不会被读取 //置为earliest,表示从分区起始位置读取消息 properties.put("auto.offset.reset","earliest"); //设置手动提交消息偏移 properties.put("enable.auto.commit","false"); //一次拉取的最大消息条数 properties.put("max.poll.records",10); KafkaConsumer<String,String> consumer = new KafkaConsumer<String, String>(properties); consumer.subscribe(Collections.singletonList("Demo3")); int count = 0; try { while (true){ ConsumerRecords<String,String> records = consumer.poll(10); for(ConsumerRecord<String ,String> record : records){ count ++; if(count == 50) consumer.commitSync(); System.out.println(record.topic() + "," + record.partition() + "," + record.offset() + "," + record.key() + "," + record.value()); } System.out.println(count); } } finally { consumer.close(); } } }
说明:在上述例子中,主题Demo3中已经有100条消息,第一次远行Consumer时,在读取到50条消息时,提交一次偏移量,输出的count值为100;第二次不改变消费group,会从51条开始读取,所以输出的count值为50
2. 异步提交,同步提交时,在broker回应指,会一直阻塞、重试,限制应用的吞吐量,因此可以采用异步提交,异步提交失败时不会重试,因为如果提交失败时因为临时的问题导致的,那么后续的提交总户有成功的。
consumer.commitAsync();
3. 同步、异步组合提交,确保消费者在关闭或者再均衡之前提交成功
import org.apache.kafka.clients.consumer.ConsumerRecord; import org.apache.kafka.clients.consumer.ConsumerRecords; import org.apache.kafka.clients.consumer.KafkaConsumer; import java.util.Collections; import java.util.Properties; /** * Created by zhangpeiran on 2018/10/9. */ public class MyConsumer { public static void main(String[] args){ Properties properties = new Properties(); properties.put("bootstrap.servers","ip:9092"); properties.put("key.deserializer","org.apache.kafka.common.serialization.StringDeserializer"); properties.put("value.deserializer","org.apache.kafka.common.serialization.StringDeserializer"); properties.put("group.id","DemoConsumerGroup"); //默认值为latest,当消费者读取的分区没有偏移量或偏移量无效时,消费者将从最新的记录开始读 //当一个消费group第一次订阅主题时,符合这种情况,在Consumer启动之前,Producer生产的数据不会被读取 //置为earliest,表示从分区起始位置读取消息 properties.put("auto.offset.reset","earliest"); //设置手动提交消息偏移 properties.put("enable.auto.commit","false"); //一次拉取的最大消息条数 properties.put("max.poll.records",10); KafkaConsumer<String,String> consumer = new KafkaConsumer<String, String>(properties); consumer.subscribe(Collections.singletonList("Demo3")); int count = 0; try { while (true){ ConsumerRecords<String,String> records = consumer.poll(10); for(ConsumerRecord<String ,String> record : records){ count ++; //if(count == 50) //consumer.commitAsync(); //consumer.commitSync(); System.out.println(record.topic() + "," + record.partition() + "," + record.offset() + "," + record.key() + "," + record.value()); } consumer.commitAsync(); //System.out.println(count); } } finally { try { consumer.commitSync(); } finally { consumer.close(); } //consumer.close(); } } }
原文地址:https://www.cnblogs.com/darange/p/9768791.html
时间: 2024-10-07 15:09:13