云服务器(Linux)安装部署Kafka的详细过程

tar -zxvf kafka_2.12-3.2.0.tgz

vi server.properties

listeners=PLAINTEXT://云服务器内网ip:9092（本地访问用本地ip）
# 如果要提供外网访问则必须配置此项
advertised.listeners=PLAINTEXT://云服务器公网ip:9092（若要远程访问需配置此项为云服务器的公网ip）
# zookeeper连接地址，集群配置格式为ip:port,ip:port,ip:port
zookeeper.connect=云服务器公网ip:2181

1.打开/关闭/重启防火墙

开启防火墙(重启后永久生效)：chkconfig iptables on

关闭防火墙(重启后永久生效)：chkconfig iptables off

开启防火墙(即时生效，重启后失效)：service iptables start

关闭防火墙(即时生效，重启后失效)：service iptables stop

重启防火墙:service iptables restartd

2.查看打开的端口

/etc/init.d/iptables status
3.开启端口

iptables -A INPUT -p tcp --dport 8080 -j ACCEPT
4.保存并重启防火墙
/etc/rc.d/init.d/iptables save
/etc/init.d/iptables restart

1.启动防火墙

systemctl start firewalld
2.禁用防火墙

systemctl stop firewalld
3.设置开机启动

systemctl enable firewalld
4.停止并禁用开机启动

sytemctl disable firewalld
5.重启防火墙

firewall-cmd --reload

6.查看状态

systemctl status firewalld或者 firewall-cmd --state
7.在指定区域打开端口（记得重启防火墙）

firewall-cmd --zone=public --add-port=80/tcp(永久生效再加上 --permanent)

bin/zookeeper-server-start.sh config/zookeeper.properties

bin/kafka-server-start.sh config/server.properties

查询kafka下所有的topic
bin/kafka-topics.sh --list --zookeeper ip:port
因为kafka使用zookeeper作为配置中心，一些topic信息需要查询该kafka对应的zookeeper
创建topic
bin/kafka-topics.sh --create --zookeeper ip:port --replication-factor 1 --partitions 1 --topic test
开启生产者
bin/kafka-console-producer.sh --broker-list cos100:9092 --topic test
开启消费者
bin/kafka-console-consumer.sh --bootstrap-server cos100:9092 --topic test

<dependency>
            <groupId>org.springframework.kafka</groupId>
            <artifactId>spring-kafka</artifactId>
            <version>2.9.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-clients</artifactId>
            <version>3.2.0</version>
        </dependency>

server:
  port: 8080

spring:
  kafka:
    bootstrap-servers: 云服务器外网ip地址:9092
    producer: # 生产者
      retries: 3 # 设置大于0的值，则客户端会将发送失败的记录重新发送
      batch-size: 16384
      buffer-memory: 33554432
      acks: 1
      # 指定消息key和消息体的编解码方式
      key-serializer: org.apache.kafka.common.serialization.StringSerializer
      value-serializer: org.apache.kafka.common.serialization.StringSerializer
    consumer:
      group-id: default-group
      enable-auto-commit: false
      auto-offset-reset: earliest
      key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
    listener:
      # 当每一条记录被消费者监听器（ListenerConsumer）处理之后提交
      # RECORD
      # 当每一批poll()的数据被消费者监听器（ListenerConsumer）处理之后提交
      # BATCH
      # 当每一批poll()的数据被消费者监听器（ListenerConsumer）处理之后，距离上次提交时间大于TIME时提交
      # TIME
      # 当每一批poll()的数据被消费者监听器（ListenerConsumer）处理之后，被处理record数量大于等于COUNT时提交
      # COUNT
      # TIME |　COUNT　有一个条件满足时提交
      # COUNT_TIME
      # 当每一批poll()的数据被消费者监听器（ListenerConsumer）处理之后, 手动调用Acknowledgment.acknowledge()后提交
      # MANUAL
      # 手动调用Acknowledgment.acknowledge()后立即提交，一般使用这种
      # MANUAL_IMMEDIATE
      ack-mode: manual_immediate

@RestController
public class KafkaController {
    private final static String TOPIC_NAME = "test-topic";

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    @RequestMapping("/send")
    public String send(@RequestParam("msg") String msg) {
        kafkaTemplate.send(TOPIC_NAME, "key", msg);
        return String.format("消息 %s 发送成功！", msg);
    }
}

@Component
public class DemoConsumer {
    /**
     * @param record record
     * @KafkaListener(groupId = "testGroup", topicPartitions = {
     * @TopicPartition(topic = "topic1", partitions = {"0", "1"}),
     * @TopicPartition(topic = "topic2", partitions = "0",
     * partitionOffsets = @PartitionOffset(partition = "1", initialOffset = "100"))
     * },concurrency = "6")
     * //concurrency就是同组下的消费者个数，就是并发消费数，必须小于等于分区总数
     */
    @KafkaListener(topics = "test-topic", groupId = "testGroup1")
    public void listentestGroup(ConsumerRecord<String, String> record, Acknowledgment ack) {
        String value = record.value();
        System.out.println("testGroup1 message: " + value);
        System.out.println("testGroup1 record: " + record);
        //手动提交offset，一般是提交一个banch，幂等性防止重复消息
        // === 每条消费完确认性能不好！
        ack.acknowledge();
    }

    //配置多个消费组
    @KafkaListener(topics = "test--topic", groupId = "testGroup2")
    public void listentestGroup2(ConsumerRecord<String, String> record, Acknowledgment ack) {
        String value = record.value();
        System.out.println("testGroup2 message: " + value);
        System.out.println("testGroup2 record: " + record);
        //手动提交offset
        ack.acknowledge();
    }
}