Springboot集成Kafka實現producer和consumer的示例代碼

1、先解決依賴

springboot相關的依賴我們就不提了，和kafka相關的只依賴一個spring-kafka集成包

org.springframework.kafka

spring-kafka

1.1.1.RELEASE

這裡我們先把配置文件展示一下

#============== kafka ===================

kafka.consumer.zookeeper.connect=10.93.21.21:2181

kafka.consumer.servers=10.93.21.21:9092

kafka.consumer.enable.auto.commit=true

kafka.consumer.session.timeout=6000

kafka.consumer.auto.commit.interval=100

kafka.consumer.auto.offset.reset=latest

kafka.consumer.topic=test

kafka.consumer.group.id=test

kafka.consumer.concurrency=10

kafka.producer.servers=10.93.21.21:9092

kafka.producer.retries=0

kafka.producer.batch.size=4096

kafka.producer.linger=1

kafka.producer.buffer.memory=40960

2、Configuration：Kafka producer

1）通過@Configuration、@EnableKafka，聲明Config並且打開KafkaTemplate能力。

2）通過@Value注入application.properties配置文件中的kafka配置。

3）生成bean，@Bean

package com.kangaroo.sentinel.collect.configuration;

import java.util.HashMap;

import java.util.Map;

import org.apache.kafka.clients.producer.ProducerConfig;

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.core.DefaultKafkaProducerFactory;

import org.springframework.kafka.core.KafkaTemplate;

import org.springframework.kafka.core.ProducerFactory;

@Configuration

@EnableKafka

public class KafkaProducerConfig {

@Value("${kafka.producer.servers}")

private String servers;

@Value("${kafka.producer.retries}")

private int retries;

@Value("${kafka.producer.batch.size}")

private int batchSize;

@Value("${kafka.producer.linger}")

private int linger;

@Value("${kafka.producer.buffer.memory}")

private int bufferMemory;

public Map producerConfigs() {

Map props = new HashMap<>();

props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, servers);

props.put(ProducerConfig.RETRIES_CONFIG, retries);

props.put(ProducerConfig.BATCH_SIZE_CONFIG, batchSize);

props.put(ProducerConfig.LINGER_MS_CONFIG, linger);

props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, bufferMemory);

props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);

props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);

return props;

}

public ProducerFactory producerFactory() {

return new DefaultKafkaProducerFactory<>(producerConfigs());

}

@Bean

public KafkaTemplate kafkaTemplate() {

return new KafkaTemplate(producerFactory());

}

}

實驗我們的producer，寫一個Controller。想topic=test，key=key，發送消息message

package com.kangaroo.sentinel.collect.controller;

import com.kangaroo.sentinel.common.response.Response;

import com.kangaroo.sentinel.common.response.ResultCode;

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

import org.springframework.beans.factory.annotation.Autowired;

import org.springframework.kafka.core.KafkaTemplate;

import org.springframework.web.bind.annotation.*;

import javax.servlet.http.HttpServletRequest;

import javax.servlet.http.HttpServletResponse;

@RestController

@RequestMapping("/kafka")

public class CollectController {

protected final Logger logger = LoggerFactory.getLogger(this.getClass());

@Autowired

private KafkaTemplate kafkaTemplate;

@RequestMapping(value = "/send", method = RequestMethod.GET)

public Response sendKafka(HttpServletRequest request, HttpServletResponse response) {

try {

String message = request.getParameter("message");

logger.info("kafka的消息={}"， message);

kafkaTemplate.send("test", "key", message);

logger.info("發送kafka成功.");

return new Response(ResultCode.SUCCESS, "發送kafka成功", null);

} catch (Exception e) {

logger.error("發送kafka失敗", e);

return new Response(ResultCode.EXCEPTION, "發送kafka失敗", null);

}

}

}

3、configuration：kafka consumer

1）通過@Configuration、@EnableKafka，聲明Config並且打開KafkaTemplate能力。

2）通過@Value注入application.properties配置文件中的kafka配置。

3）生成bean，@Bean

package com.kangaroo.sentinel.collect.configuration;

import org.apache.kafka.clients.consumer.ConsumerConfig;

import org.apache.kafka.common.serialization.StringDeserializer;

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.ConsumerFactory;

import org.springframework.kafka.core.DefaultKafkaConsumerFactory;

import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;

import java.util.HashMap;

import java.util.Map;

@Configuration

@EnableKafka

public class KafkaConsumerConfig {

@Value("${kafka.consumer.servers}")

private String servers;

@Value("${kafka.consumer.enable.auto.commit}")

private boolean enableAutoCommit;

@Value("${kafka.consumer.session.timeout}")

private String sessionTimeout;

@Value("${kafka.consumer.auto.commit.interval}")

private String autoCommitInterval;

@Value("${kafka.consumer.group.id}")

private String groupId;

@Value("${kafka.consumer.auto.offset.reset}")

private String autoOffsetReset;

@Value("${kafka.consumer.concurrency}")

private int concurrency;

@Bean

public KafkaListenerContainerFactory> kafkaListenerContainerFactory() {

ConcurrentKafkaListenerContainerFactory factory = new ConcurrentKafkaListenerContainerFactory<>();

factory.setConsumerFactory(consumerFactory());

factory.setConcurrency(concurrency);

factory.getContainerProperties().setPollTimeout(1500);

return factory;

}

public ConsumerFactory consumerFactory() {

return new DefaultKafkaConsumerFactory<>(consumerConfigs());

}

public Map consumerConfigs() {

Map propsMap = new HashMap<>();

propsMap.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, servers);

propsMap.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, enableAutoCommit);

propsMap.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, autoCommitInterval);

propsMap.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, sessionTimeout);

propsMap.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);

propsMap.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);

propsMap.put(ConsumerConfig.GROUP_ID_CONFIG, groupId);

propsMap.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, autoOffsetReset);

return propsMap;

}

@Bean

public Listener listener() {

return new Listener();

}

}

new Listener()生成一個bean用來處理從kafka讀取的數據。Listener簡單的實現demo如下：只是簡單的讀取並打印key和message值

@KafkaListener中topics屬性用於指定kafka topic名稱，topic名稱由消息生產者指定，也就是由kafkaTemplate在發送消息時指定。

package com.kangaroo.sentinel.collect.configuration;

import org.apache.kafka.clients.consumer.ConsumerRecord;

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

import org.springframework.kafka.annotation.KafkaListener;

public class Listener {

protected final Logger logger = LoggerFactory.getLogger(this.getClass());

@KafkaListener(topics = {"test"})

public void listen(ConsumerRecord, ?> record) {

logger.info("kafka的key: " + record.key());

logger.info("kafka的value: " + record.value().toString());

}

}

tips:

1）我沒有介紹如何安裝配置kafka，配置kafka時最好用完全bind網絡ip的方式，而不是localhost或者127.0.0.1

2）最好不要使用kafka自帶的zookeeper部署kafka，可能導致訪問不通。

3）理論上consumer讀取kafka應該是通過zookeeper，但是這裡我們用的是kafkaserver的地址，為什麼沒有深究。

4）定義監聽消息配置時，GROUP_ID_CONFIG配置項的值用於指定消費者組的名稱，如果同組中存在多個監聽器對象則只有一個監聽器對象能收到消息。

以上就是本文的全部內容，希望對大家的學習有所幫助，喜歡小編文章的可以關注並轉發哦~~~

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