Kafka4.1.0 队列模式尝鲜

背景

kafka一直以来的消费模型是一个topic下多个partition，每个partition有一个消费者。其中partition的数量决定了消费者的并发度。在KIP-932 的提案中提出了队列模型，在4.0.0版本引入在4.1.0版本为预览版。

使用docker启动

我们使用docker启动一个开启了预览版本的broker。本文使用的native-image

复制代码

docker run -d  \
  -p 9092:9092 \
  --name kafka410 \
  -e KAFKA_NODE_ID=1 \
  -e KAFKA_PROCESS_ROLES=broker,controller \
  -e KAFKA_LISTENERS=PLAINTEXT://:9092,CONTROLLER://:9093 \
  -e KAFKA_ADVERTISED_LISTENERS=PLAINTEXT://localhost:9092 \
  -e KAFKA_CONTROLLER_LISTENER_NAMES=CONTROLLER \
  -e KAFKA_LISTENER_SECURITY_PROTOCOL_MAP=CONTROLLER:PLAINTEXT,PLAINTEXT:PLAINTEXT \
  -e KAFKA_CONTROLLER_QUORUM_VOTERS=1@localhost:9093 \
  -e KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR=1 \
  -e KAFKA_TRANSACTION_STATE_LOG_REPLICATION_FACTOR=1 \
  -e KAFKA_TRANSACTION_STATE_LOG_MIN_ISR=1 \
  -e KAFKA_GROUP_INITIAL_REBALANCE_DELAY_MS=0 \
  -e KAFKA_NUM_PARTITIONS=3 \
  -e KAFKA_GROUP_COORDINATOR_REBALANCE_PROTOCOLS=classic,consumer,share \
  -e KAFKA_UNSTABLE_API_VERSIONS_ENABLE=true \
  -e KAFKA_GROUP_SHARE_ENABLE=true \
  -e KAFKA_SHARE_COORDINATOR_STATE_TOPIC_REPLICATION_FACTOR=1 \
  apache/kafka-native:4.1.1-rc1

KAFKA_GROUP_COORDINATOR_REBALANCE_PROTOCOLS=classic,consumer,share 在rebalance协议中支持share协议
KAFKA_UNSTABLE_API_VERSIONS_ENABLE 解锁未stable的版本限制
KAFKA_GROUP_SHARE_ENABLE 开启共享组消费者模式
KAFKA_SHARE_COORDINATOR_STATE_TOPIC_REPLICATION_FACTOR 共享组（队列）模式使用一个topic来保存消费进度，这个是此topic的副本因子

使用spring-kafka消费

spring boot 使用的4.0.0-rc2
并添加spring-kafka
- implementation 'org.springframework.boot:spring-boot-starter-kafka'

java 复制代码

package cc.sofast.practice.kafkagroupconsumer;

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.boot.CommandLineRunner;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.config.ShareKafkaListenerContainerFactory;
import org.springframework.kafka.core.DefaultShareConsumerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ShareConsumerFactory;
import org.springframework.kafka.listener.ContainerProperties;
import org.springframework.kafka.listener.MessageListener;
import org.springframework.kafka.listener.ShareKafkaMessageListenerContainer;

import java.util.*;

/**
 * @author wxl
 */
@Configuration
public class ShareConsumerConfig {

    private static final Logger log = LoggerFactory.getLogger(ShareConsumerConfig.class);

    @Bean
    public ShareConsumerFactory<String, String> shareConsumerFactory() {
        Map<String, Object> props = new HashMap<>();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG,
                StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,
                StringDeserializer.class);
        return new DefaultShareConsumerFactory<>(props);
    }

        @Bean
    public ShareKafkaMessageListenerContainer<String, String> imageProcessingContainer(
            ShareConsumerFactory<String, String> shareConsumerFactory) {

        ContainerProperties containerProps = new ContainerProperties("image-processing");
        containerProps.setGroupId("image-processors");

        ShareKafkaMessageListenerContainer<String, String> container =
                new ShareKafkaMessageListenerContainer<>(shareConsumerFactory, containerProps);

        container.setConcurrency(10);
        container.setupMessageListener(new MessageListener<String, String>() {
            @Override
            public void onMessage(ConsumerRecord<String, String> record) {
                System.out.println("Received on " + Thread.currentThread().getName() + ": Key: " + record.key() + " Val: " + record.value());
                // Implicit ACCEPT when method completes successfully
            }
        });

        return container;
    }

    @Bean
    public CommandLineRunner commandLineRunner(KafkaTemplate<String, String> template) {
        return new CommandLineRunner() {
            @Override
            public void run(String... args) throws Exception {
                new Timer().schedule(new TimerTask() {
                    @Override
                    public void run() {
                        template.send("image-processing", UUID.randomUUID().toString(), "image-2-" + UUID.randomUUID().toString());
                    }
                }, 3000, 1000);
            }
        };
    }
}

Kafka4.1.0 队列模式尝鲜

背景

使用docker启动

使用spring-kafka消费

参考