高吞吐量的分佈式發佈訂閱消息系統Kafka--spring-integration-kafka的應用

時間 2019-11-06

標籤吞吐量分佈式發佈訂閱消息系統 kafka spring integration 應用欄目系統架構简体版

原文原文鏈接

1、概述java

Spring Integration Kafka 是基於 Apache Kafka 和Spring Integration來集成Kafka，對開發配置提供了方便。git

2、配置github

一、spring-kafka-consumer.xmlweb

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
	xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:int="http://www.springframework.org/schema/integration"
	xmlns:int-kafka="http://www.springframework.org/schema/integration/kafka"
	xmlns:task="http://www.springframework.org/schema/task"
	xsi:schemaLocation="http://www.springframework.org/schema/integration/kafka 
                        http://www.springframework.org/schema/integration/kafka/spring-integration-kafka.xsd
                        http://www.springframework.org/schema/integration 
                        http://www.springframework.org/schema/integration/spring-integration.xsd
                        http://www.springframework.org/schema/beans 
                        http://www.springframework.org/schema/beans/spring-beans.xsd
                        http://www.springframework.org/schema/task 
                        http://www.springframework.org/schema/task/spring-task.xsd">

	<!-- topic test conf -->
	<int:channel id="inputFromKafka" >
		<int:dispatcher task-executor="kafkaMessageExecutor" />
	</int:channel>
    <!-- zookeeper配置 能夠配置多個 -->
	<int-kafka:zookeeper-connect id="zookeeperConnect"
		zk-connect="192.168.1.237:2181" zk-connection-timeout="6000"
		zk-session-timeout="6000" zk-sync-time="2000" />
    <!-- channel配置 auto-startup="true"  不然接收不發數據 -->
	<int-kafka:inbound-channel-adapter
		id="kafkaInboundChannelAdapter" kafka-consumer-context-ref="consumerContext"
		auto-startup="true" channel="inputFromKafka">
		<int:poller fixed-delay="1" time-unit="MILLISECONDS" />
	</int-kafka:inbound-channel-adapter>
    <task:executor id="kafkaMessageExecutor" pool-size="8" keep-alive="120" queue-capacity="500" />
	<bean id="kafkaDecoder"
		class="org.springframework.integration.kafka.serializer.common.StringDecoder" />

	<bean id="consumerProperties"
		class="org.springframework.beans.factory.config.PropertiesFactoryBean">
		<property name="properties">
			<props>
				<prop key="auto.offset.reset">smallest</prop>
				<prop key="socket.receive.buffer.bytes">10485760</prop> <!-- 10M -->
				<prop key="fetch.message.max.bytes">5242880</prop>
				<prop key="auto.commit.interval.ms">1000</prop>
			</props>
		</property>
	</bean>
    <!-- 消息接收的BEEN -->
	<bean id="kafkaConsumerService" class="com.sunney.service.impl.KafkaConsumerService" />
    <!-- 指定接收的方法 -->
	<int:outbound-channel-adapter channel="inputFromKafka"
		ref="kafkaConsumerService" method="processMessage" />

	<int-kafka:consumer-context id="consumerContext"
		consumer-timeout="1000" zookeeper-connect="zookeeperConnect"
		consumer-properties="consumerProperties">
		<int-kafka:consumer-configurations>
			<int-kafka:consumer-configuration
				group-id="default1" value-decoder="kafkaDecoder" key-decoder="kafkaDecoder"
				max-messages="5000">
				<!-- 兩個TOPIC配置 -->
				<int-kafka:topic id="mytopic" streams="4" />
				<int-kafka:topic id="sunneytopic" streams="4" />
			</int-kafka:consumer-configuration>
		</int-kafka:consumer-configurations>
	</int-kafka:consumer-context>
</beans>

　　二、spring-kafka-producer.xmlspring

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
	xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:int="http://www.springframework.org/schema/integration"
	xmlns:int-kafka="http://www.springframework.org/schema/integration/kafka"
	xmlns:task="http://www.springframework.org/schema/task"
	xsi:schemaLocation="http://www.springframework.org/schema/integration/kafka http://www.springframework.org/schema/integration/kafka/spring-integration-kafka.xsd
        http://www.springframework.org/schema/integration http://www.springframework.org/schema/integration/spring-integration.xsd
        http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/task http://www.springframework.org/schema/task/spring-task.xsd">
	
   <!-- commons config -->
	<bean id="stringSerializer" class="org.apache.kafka.common.serialization.StringSerializer"/>
	<bean id="kafkaEncoder" class="org.springframework.integration.kafka.serializer.avro.AvroReflectDatumBackedKafkaEncoder">
        <constructor-arg value="java.lang.String" />
    </bean>
	<bean id="producerProperties"
		class="org.springframework.beans.factory.config.PropertiesFactoryBean">
		<property name="properties">
			<props>
				<prop key="topic.metadata.refresh.interval.ms">3600000</prop>
				<prop key="message.send.max.retries">5</prop>
				<prop key="serializer.class">kafka.serializer.StringEncoder</prop>
				<prop key="request.required.acks">1</prop>
			</props>
		</property>
	</bean>
	
	<!-- topic test config  -->
	
	<int:channel id="kafkaTopicTest">
		<int:queue />
	</int:channel>
	
	<int-kafka:outbound-channel-adapter
		id="kafkaOutboundChannelAdapterTopicTest" kafka-producer-context-ref="producerContextTopicTest"
		auto-startup="true" channel="kafkaTopicTest" order="3">
		<int:poller fixed-delay="1000" time-unit="MILLISECONDS"
			receive-timeout="1" task-executor="taskExecutor" />
	</int-kafka:outbound-channel-adapter>
	<task:executor id="taskExecutor" pool-size="5"
		keep-alive="120" queue-capacity="500" />
	<!-- <bean id="kafkaEncoder"
		class="org.springframework.integration.kafka.serializer.avro.AvroSpecificDatumBackedKafkaEncoder">
		<constructor-arg value="com.company.AvroGeneratedSpecificRecord" />
	</bean> -->
	<int-kafka:producer-context id="producerContextTopicTest"
		producer-properties="producerProperties">
		<int-kafka:producer-configurations>
		    <!-- 多個topic配置 -->
			<int-kafka:producer-configuration
				broker-list="192.168.1.237:9090,192.168.1.237:9091,192.168.1.237:9092"
				key-serializer="stringSerializer"
                value-class-type="java.lang.String"
                value-serializer="stringSerializer"
				topic="mytopic" />
			<int-kafka:producer-configuration
				broker-list="192.168.1.237:9090,192.168.1.237:9091,192.168.1.237:9092"
				key-serializer="stringSerializer"
                value-class-type="java.lang.String"
                value-serializer="stringSerializer"
				topic="sunneytopic"/>
		</int-kafka:producer-configurations>
	</int-kafka:producer-context>
</beans>

　　三、發消息接口 KafkaServiceapache

package com.sunney.service;

/**
 * 類KafkaService.java的實現描述：發消息接口類
 * @author Sunney 2016年4月30日 上午11:30:53
 */
public interface KafkaService {
    /**
     * 發消息
     * @param topic 主題
     * @param obj 發送內容
     */
    public void sendUserInfo(String topic, Object obj);
}

　　四、發消息實現類 KafkaServiceImpl json

package com.sunney.service.impl;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.integration.kafka.support.KafkaHeaders;
import org.springframework.integration.support.MessageBuilder;
import org.springframework.messaging.MessageChannel;
import org.springframework.stereotype.Service;

import com.sunney.service.KafkaService;

/**
 * 類KafkaServiceImpl.java的實現描述：發消息實現類 
 * @author Sunney 2016年4月30日 上午11:31:13
 */
@Service("kafkaService")
public class KafkaServiceImpl  implements KafkaService{

    @Autowired
    @Qualifier("kafkaTopicTest")
    MessageChannel channel;

    public void sendUserInfo(String topic, Object obj) {
        channel.send(MessageBuilder.withPayload(obj)
                                    .setHeader(KafkaHeaders.TOPIC,topic)
                                    .build());
    }

}

　　五、消費接收類KafkaConsumerService session

package com.sunney.service.impl;

import java.util.Collection;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import com.alibaba.fastjson.JSON;
import com.sunney.service.UserDto;

/**
 * 類KafkaConsumerService.java的實現描述：消費接收類
 * 
 * @author Sunney 2016年4月30日 上午11:46:14
 */
public class KafkaConsumerService {

    static final Logger logger = LoggerFactory.getLogger(KafkaConsumerService.class);

    public void processMessage(Map<String, Map<Integer, String>> msgs) {
        logger.info("===============processMessage===============");
        for (Map.Entry<String, Map<Integer, String>> entry : msgs.entrySet()) {
            logger.info("============Topic:" + entry.getKey());
            LinkedHashMap<Integer, String> messages = (LinkedHashMap<Integer, String>) entry.getValue();
            Set<Integer> keys = messages.keySet();
            for (Integer i : keys)
                logger.info("======Partition:" + i);
            Collection<String> values = messages.values();
            for (Iterator<String> iterator = values.iterator(); iterator.hasNext();) {
                String message = "["+iterator.next()+"]";
                logger.info("=====message:" + message);
                List<UserDto> userList = JSON.parseArray(message, UserDto.class);  
                logger.info("=====userList.size:" + userList.size());

            }

        }
    }

}

　　六、pomsocket

<dependencies>
		<dependency>
			<groupId>org.springframework.boot</groupId>
			<artifactId>spring-boot-starter-web</artifactId>
		</dependency>
		<dependency>
			<groupId>org.springframework.integration</groupId>
			<artifactId>spring-integration-kafka</artifactId>
			<version>1.3.0.RELEASE</version>
		</dependency>
		<dependency>
			<groupId>junit</groupId>
			<artifactId>junit</artifactId>
			<version>4.11</version>
			<scope>test</scope>
		</dependency>
		<dependency>
			<groupId> org.apache.avro</groupId>
			<artifactId>avro</artifactId>
			<version>1.7.7</version>
		</dependency>
		<dependency>
			<groupId>com.alibaba</groupId>
			<artifactId>fastjson</artifactId>
			<version>1.2.7</version>
		</dependency>
	</dependencies>

　　6、源代碼地址：https://github.com/sunney2010/kafka-demospring-boot

7、遇到的問題

一、消費端口收不到消息

spring-kafka-consumer.xml的auto-startup設置爲true