kafka 高级应用 springboot2.1 (2) 手动创建topic
作者：互联网
依赖：
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
</dependency>
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<String, Object> producerConfigs() {
Map<String, Object> 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, "LZ4");//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<String, Object> 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<String, String> producerFactory() {
return new DefaultKafkaProducerFactory<>(producerConfigs());
}
@Bean
public KafkaTemplate<String, String> kafkaTemplate() {
return new KafkaTemplate<>(producerFactory());
}
@Bean
public Map<String, Object> consumerConfigs() {
Map<String, Object> 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<Integer, String> 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//cankao :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<String, Object> 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<String, String> 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<String> topics = listTopics.names().get();
for (String topic : topics) {
System.err.println(topic);
}
}
标签：springboot2.1,spring,kafka,topic,props,put,org,CONFIG 来源： https://www.cnblogs.com/lshan/p/11544111.html