Consumer Group
- consumers join in the group with same group id.
- the maximum parallelism is the number of consumers not partitions.
- Kafka allocates partitions of the topic to the users in the group, to ensure that one user, one partition.
- Kafka ensures message only read by one consumer in the group.
- consumers can check the message in sequence of stored message in logs.
rebalancd consumers
import java.util.Properties;
import java.util.Arrays;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.ConsumerRecord;
public class ConsumerGroup{
public static void main(String[] args)throws Exception{
if(args.length < 2){
System.out.println("Usage: consumer <topic> <groupname>");
return;
}
String topic = args[0].toString();
String group = args[1].toString();
Properties props = new Properties();
props.put("bootstrap.servers","10.131.18.138:9092");
props.put("group.id",group);
props.put("enable.auto.commit","true");
props.put("auto.commit.interval.ms","1000");
props.put("session.timeout.ms","30000");
props.put("key.deserializer","org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer","org.apache.kafka.common.serialization.StringDeserilaizer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<String, String>(props);
consumer.subscribe(Arrays.asList(topic));
System.out.println("Subscribed to topic");
for(String item: Arrays.asList(topic)){
System.out.println(item);
}
while(true){
ConsumerRecords<String, String> records = consumer.poll(100);
for(ConsumerRecord<String, String> record : records){
System.out.printf("offset = %d, key = %s value = %s\n", record.offset(), record.key(), record.value());
}
}
}
}
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