用 Docker 快速搭建 Kafka 集群

版本

•JDK 14•Zookeeper•Kafka

安装 Zookeeper 和 Kafka

Kafka 依赖 Zookeeper，因此咱们须要在安装 Kafka 以前先拥有 Zookeeper。准备以下的 docker-compose.yaml 文件，将文件中的主机地址 192.168.1.100 替换成你本身的环境中的主机地址便可。

version: "3"
services:
  zookeeper:
    image: zookeeper
    build:
      context: ./
    container_name: zookeeper
    ports:
      - 2181:2181
    volumes:
      - ./data/zookeeper/data:/data
      - ./data/zookeeper/datalog:/datalog
      - ./data/zookeeper/logs:/logs
    restart: always
  kafka_node_0:
    depends_on:
      - zookeeper
    build:
      context: ./
    container_name: kafka-node-0
    image: wurstmeister/kafka
    environment:
      KAFKA_BROKER_ID: 0
      KAFKA_ZOOKEEPER_CONNECT: 192.168.1.100:2181
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://192.168.1.100:9092
      KAFKA_LISTENERS: PLAINTEXT://0.0.0.0:9092
      KAFKA_NUM_PARTITIONS: 3
      KAFKA_DEFAULT_REPLICATION_FACTOR: 2
    ports:
      - 9092:9092
    volumes:
      - ./data/kafka/node_0:/kafka
    restart: unless-stopped
  kafka_node_1:
    depends_on:
      - kafka_node_0
    build:
      context: ./
    container_name: kafka-node-1
    image: wurstmeister/kafka
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_ZOOKEEPER_CONNECT: 192.168.1.100:2181
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://192.168.1.100:9093
      KAFKA_LISTENERS: PLAINTEXT://0.0.0.0:9093
      KAFKA_NUM_PARTITIONS: 3
      KAFKA_DEFAULT_REPLICATION_FACTOR: 2
    ports:
      - 9093:9093
    volumes:
      - ./data/kafka/node_1:/kafka
    restart: unless-stopped
  kafka_node_2:
    depends_on:
      - kafka_node_1
    build:
      context: ./
    container_name: kafka-node-2
    image: wurstmeister/kafka
    environment:
      KAFKA_BROKER_ID: 2
      KAFKA_ZOOKEEPER_CONNECT: 192.168.1.100:2181
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://192.168.1.100:9094
      KAFKA_LISTENERS: PLAINTEXT://0.0.0.0:9094
      KAFKA_NUM_PARTITIONS: 3
      KAFKA_DEFAULT_REPLICATION_FACTOR: 2
    ports:
      - 9094:9094
    volumes:
      - ./data/kafka/node_2:/kafka
    restart: unless-stopped

输入 docker-compose up -d 运行脚本文件进行集群构建。等待一下子，获得以下结果即为成功。

SpringBoot 集成 Kafka 集群

建立一个全新的 SpringBoot 工程，在 build.gradle 文件中添加下列依赖。

dependencies {
    ...
    ...
    implementation 'org.springframework.kafka:spring-kafka:2.5.2.RELEASE'
    implementation 'com.alibaba:fastjson:1.2.71'
}

1.在 application.properties 进行 Kafka 相关参数配置。

spring.kafka.bootstrap-servers=192.168.1.100:9092,192.168.1.100:9093,192.168.1.100:9094
spring.kafka.producer.retries=0
spring.kafka.producer.batch-size=16384
spring.kafka.producer.buffer-memory=33554432
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.consumer.auto-offset-reset=latest
spring.kafka.consumer.enable-auto-commit=true
spring.kafka.consumer.auto-commit-interval=100

2.建立消息体类。

public class Message {
    private Long id;
    private String message;
    private Date sendAt;
}

3.建立消息发送者

public class Sender {
    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;
    public void send() {
        Message message = new Message();
        message.setId(System.currentTimeMillis());
        message.setMessage(UUID.randomUUID().toString());
        message.setSendAt(new Date());
        log.info("message = {}", JSON.toJSONString(message));
        kafkaTemplate.send("test", JSON.toJSONString(message));
    }
}

4.建立消息接收者

public class Receiver {
    @KafkaListener(topics = {"test"}, groupId = "test")
    public void listen(ConsumerRecord<?, ?> record) {
        Optional<?> message = Optional.ofNullable(record.value());
        if (message.isPresent()) {
            log.info("receiver record = " + record);
            log.info("receiver message = " + message.get());
        }
    }
}

5.测试消息队列

public class QueueController {
    @Autowired
    private Sender sender;
    @PostMapping("/test")
    public void testQueue() {
        sender.send();
        sender.send();
        sender.send();
    }
}

获得以下日志即为集成成功。

到这里就咱们就成功搭建了一个 Kafka 伪集群，并成功与 SpringBoot 进行整合。

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