go的kafka生产和消费-kafka深入-利志分享

go的kafka生产和消费

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之前有一篇文件聊了聊如何生产不丢失数据，消费不丢失数据。这一篇我们来看下go如何通过参数配置来处理生产和消费的。

关于go的client，官方推荐有个如下几个：
https://github.com/Shopify/sarama
https://github.com/stealthly/go_kafka_client
https://github.com/stealthly/siesta
https://github.com/optiopay/kafka
https://github.com/nuance/kafka

我这里使用的就是官方推荐的第一个sarama，目前star的量7.2
go的生产端：关于生产端上篇文章也说过最核心的参数是：

// 发送完数据需要leader和follow都确认
    	mqConfig.Producer.RequiredAcks = sarama.WaitForAll
		
关于go的生产端核心就是确保写入的数据都到leader和follow。代码参考如下：

package main
    
    import (
    	"fmt"
    	"github.com/Shopify/sarama"
    	"strings"
    	"time"
    )
    
    var KafkaProducer sarama.SyncProducer
    
    func InitKafkaProducer(addressList string) {
    	var err error
    	mqConfig := sarama.NewConfig()
    	// 设置producer
    	// 发送完数据需要leader和follow都确认
    	mqConfig.Producer.RequiredAcks = sarama.WaitForAll
    	// Partition选择随机
    	mqConfig.Producer.Partitioner = sarama.NewRandomPartitioner
    	// 成功交付的消息将在success channel返回
    	mqConfig.Producer.Return.Successes = true
    	// 配置版本
    	mqConfig.Version = sarama.V0_10_2_1
    	kafkaClient, err := sarama.NewClient(strings.Split(addressList, ","), mqConfig)
    	if err != nil {
    		panic(err)
    	}
    	// 客户端生产者
    	KafkaProducer, err = sarama.NewSyncProducerFromClient(kafkaClient)
    	if err != nil {
    		panic(err)
    	}
    }
    
    func sendKafkaMessage(content, topic string) {
    	msg := &sarama.ProducerMessage{
    		Topic:     topic,
    		Value:     sarama.StringEncoder(content),
    		Timestamp: time.Now(),
    	}
    	partition, offset, err := KafkaProducer.SendMessage(msg)
    	if err != nil {
    		return
    	}
    	fmt.Printf("sendKafkaMessage", topic, partition, offset)
    }
    
    func main() {
    	addressList := "127.0.0.1:9092"
    	InitKafkaProducer(addressList)
    	content := "sdfsdfrer"
    	topic := "test"
    	sendKafkaMessage(content, topic)
    }
	
关于go的消费端就是手动提交offset，我们要保证写入数据库，保存成功之后提交offset，这样数据肯定是不会存在丢失的情况。下面我们来看下实现的代码：

package main
    
    import (
    	"fmt"
    	"github.com/Shopify/sarama"
    	cluster "github.com/bsm/sarama-cluster"
    	"strings"
    	"time"
    )
    
    var consumerClient *cluster.Consumer
    
    // 初始化kafka配置消费信息
    func InitKafkaConsumer(addressList string, consumerGroup string, topicList []string) {
    	var err error
    	clusterCfg := cluster.NewConfig()
    
    	clusterCfg.Consumer.Return.Errors = true
    	clusterCfg.Consumer.Offsets.Initial = sarama.OffsetOldest
    	clusterCfg.Consumer.Offsets.AutoCommit.Enable = false
    	clusterCfg.Group.Return.Notifications = true
    	//这行代码是因为github.com/bsm/sarama-cluster不维护了，库会有bug，我这里只是写个demo，将就着用
    	clusterCfg.Consumer.Offsets.CommitInterval = 1 * time.Second
    	clusterCfg.Version = sarama.V0_10_2_1
    	// kafka消费端
    	if err = clusterCfg.Validate(); err != nil {
    		msg := fmt.Sprintf("Kafka consumer config invalidate. config: %v. err: %v", *clusterCfg, err)
    		panic(msg)
    	}
    	consumerClient, err = cluster.NewConsumer(strings.Split(addressList, ","), consumerGroup, topicList, clusterCfg)
    	if err != nil {
    		msg := fmt.Sprintf("Create kafka consumer error: %v. config: %v", err, clusterCfg)
    		panic(msg)
    	}
    
    }
    
    func main() {
    	addressList := "127.0.0.1:9092"
    	consumerGroup := "my_go"
    	topicList := []string{"test"}
    	InitKafkaConsumer(addressList, consumerGroup, topicList)
    	go func() {
    		for {
    			select {
    			case msg, ok := <-consumerClient.Messages():
    				if ok {
    					//这里目前我是打印数据，线上可能是写入数据到db，写入成功之后我们手动提交offset
    					fmt.Println(string(msg.Value))
    					//这里是临时保存offset
    					consumerClient.MarkOffset(msg, "")
    					//手动提交offset
    					consumerClient.CommitOffsets()
    				}
    			case err, more := <-consumerClient.Errors():
    				if more {
    					fmt.Printf("consumerClient error %v\n", err)
    				}
    			case ntf, more := <-consumerClient.Notifications():
    				if more {
    					fmt.Printf("consumerClient Notifications %v \n", ntf)
    				}
    			}
    		}
    	}()
    	time.Sleep(10 * time.Hour)
    }

感觉本站内容不错，读后有收获？

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