springboot下 kafka 手动创建topic并指定分区(partition)数及分区副本(replica)数

依赖：

 

       
            org.springframework.boot
            spring-boot-starter-web
        

        

        
            org.springframework.kafka
            spring-kafka
        

 

application.properties:

 

### kafka configure
spring.kafka.bootstrap-servers=10.160.3.70:9092
spring.kafka.consumer.group-id=sea-test
spring.kafka.consumer.enable-auto-commit=false
spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.max-poll-records=2000
#spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
#spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.producer.retries=3
spring.kafka.producer.batch-size=16384
spring.kafka.producer.buffer-memory=33554432
spring.kafka.producer.linger=10
#spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
#spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer

 

 

KafkaConfig:

package com.icil.topic.config;

import java.util.HashMap;
import java.util.Map;

import org.apache.kafka.clients.admin.AdminClient;
import org.apache.kafka.clients.admin.AdminClientConfig;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.config.KafkaListenerContainerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaAdmin;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;
import org.springframework.kafka.listener.ContainerProperties;

import com.google.common.collect.Maps;

@Configuration
@EnableKafka
public class KafkaConfig {

    @Value("${spring.kafka.bootstrap-servers}")
    private String bootstrapServers;

    @Value("${spring.kafka.consumer.group-id}")
    private String groupId;

    @Value("${spring.kafka.consumer.enable-auto-commit}")
    private Boolean autoCommit;

    @Value("${spring.kafka.consumer.auto-offset-reset}")
    private String autoOffsetReset;

    @Value("${spring.kafka.consumer.max-poll-records}")
    private Integer maxPollRecords;
    
    @Value("${spring.kafka.producer.linger}")
    private int linger;

    @Value("${spring.kafka.producer.retries}")
    private Integer retries;

    @Value("${spring.kafka.producer.batch-size}")
    private Integer batchSize;

    @Value("${spring.kafka.producer.buffer-memory}")
    private Integer bufferMemory;


    //cankao :https://blog.csdn.net/tmeng521/article/details/90901925
    public Map producerConfigs() {
         
        Map props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        //设置重试次数
        props.put(ProducerConfig.RETRIES_CONFIG, retries);
        //达到batchSize大小的时候会发送消息
        props.put(ProducerConfig.BATCH_SIZE_CONFIG, batchSize);
        //延时时间，延时时间到达之后计算批量发送的大小没达到也发送消息
        props.put(ProducerConfig.LINGER_MS_CONFIG, linger);
        //缓冲区的值
        props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, bufferMemory);
        //序列化手段
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        //producer端的消息确认机制,-1和all都表示消息不仅要写入本地的leader中还要写入对应的副本中
        props.put(ProducerConfig.ACKS_CONFIG, "-1");//单个brok 推荐使用'1'
        //单条消息的最大值以字节为单位,默认值为1048576
        props.put(ProducerConfig.LINGER_MS_CONFIG, 10485760);
        //设置broker响应时间，如果broker在60秒之内还是没有返回给producer确认消息，则认为发送失败
        props.put(ProducerConfig.REQUEST_TIMEOUT_MS_CONFIG, 60000);
        //指定拦截器(value为对应的class)
        //props.put(ProducerConfig.INTERCEPTOR_CLASSES_CONFIG, "com.te.handler.KafkaProducerInterceptor");
        //设置压缩算法(默认是木有压缩算法的)
        props.put(ProducerConfig.COMPRESSION_TYPE_CONFIG, "snappy");//snappy
        return props;
    }
    
    
    
    @Bean //创建一个kafka管理类，相当于rabbitMQ的管理类rabbitAdmin,没有此bean无法自定义的使用adminClient创建topic
    public KafkaAdmin kafkaAdmin() {
        Map props = new HashMap<>();
        //配置Kafka实例的连接地址                                                                   
        //kafka的地址，不是zookeeper
        props.put(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        KafkaAdmin admin = new KafkaAdmin(props);
        return admin;
    }
 
    @Bean  //kafka客户端，在spring中创建这个bean之后可以注入并且创建topic,用于集群环境，创建对个副本
    public AdminClient adminClient() {
        return AdminClient.create(kafkaAdmin().getConfig());
    }

    

    @Bean
    public ProducerFactory producerFactory() {
        return new DefaultKafkaProducerFactory<>(producerConfigs());
    }

    @Bean
    public KafkaTemplate kafkaTemplate() {
        return new KafkaTemplate<>(producerFactory());
    }

    
    
    
    
    @Bean
    public Map consumerConfigs() {
        Map props = Maps.newHashMap();
        props.put(ConsumerConfig.GROUP_ID_CONFIG, groupId);
        props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, autoCommit);
        props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, autoOffsetReset);
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        props.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG, maxPollRecords);
//        props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, 180000);
//        props.put(ConsumerConfig.REQUEST_TIMEOUT_MS_CONFIG, 900000);
//        props.put(ConsumerConfig.MAX_POLL_INTERVAL_MS_CONFIG, 900000);
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        return props;
    }


    @Bean
    public KafkaListenerContainerFactory batchFactory() {
        ConcurrentKafkaListenerContainerFactory factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(new DefaultKafkaConsumerFactory<>(consumerConfigs()));
        //设置为批量消费，每个批次数量在Kafka配置参数中设置ConsumerConfig.MAX_POLL_RECORDS_CONFIG
        factory.setBatchListener(true);
        // set the retry template
//        factory.setRetryTemplate(retryTemplate());
        factory.getContainerProperties().setAckMode(ContainerProperties.AckMode.MANUAL);
        return factory;
    }


}

 

 

如果topic需要初始化：可以配置// 参考 :https://blog.csdn.net/tmeng521/article/details/90901925

 

@Configuration
public class KafkaInitialConfiguration {
 
    //创建TopicName为topic.quick.initial的Topic并设置分区数为8以及副本数为1
    @Bean//通过bean创建(bean的名字为initialTopic)
    public NewTopic initialTopic() {
        return new NewTopic("topic.quick.initial",8, (short) 1 );
    }
    /**
     * 此种@Bean的方式，如果topic的名字相同，那么会覆盖以前的那个
     * @return
     */
//    //修改后|分区数量会变成11个 注意分区数量只能增加不能减少
    @Bean
    public NewTopic initialTopic2() {
        return new NewTopic("topic.quick.initial",11, (short) 1 );
    }
    @Bean //创建一个kafka管理类，相当于rabbitMQ的管理类rabbitAdmin,没有此bean无法自定义的使用adminClient创建topic
    public KafkaAdmin kafkaAdmin() {
        Map props = new HashMap<>();
        //配置Kafka实例的连接地址                                                                    //kafka的地址，不是zookeeper
        props.put(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG, "127.0.0.1:9092");
        KafkaAdmin admin = new KafkaAdmin(props);
        return admin;
    }
 
    @Bean  //kafka客户端，在spring中创建这个bean之后可以注入并且创建topic
    public AdminClient adminClient() {
        return AdminClient.create(kafkaAdmin().getConfig());
    }
    
 
}

 

test 手动创建topic ,手动查看所有topic

 

  @Autowired // adminClien需要自己生成配置bean
    private AdminClient adminClient;
    
    
     @Autowired
        private KafkaTemplate kafkaTemplate;
 
    @Test//自定义手动创建topic和分区
    public void testCreateTopic() throws InterruptedException {
        // 这种是手动创建 //10个分区，一个副本
        // 分区多的好处是能快速的处理并发量，但是也要根据机器的配置
        NewTopic topic = new NewTopic("topic.manual.create", 10, (short) 1);
        adminClient.createTopics(Arrays.asList(topic));
        Thread.sleep(1000);
    }
    
    
    /**
     * 获取所有的topic
     * @throws Exception
     */
    @Test
    public void getAllTopic() throws Exception {
        ListTopicsResult listTopics = adminClient.listTopics();
         Set topics = listTopics.names().get();
         
         for (String topic : topics) {
             System.err.println(topic);
            
        }
    }