【愚公系列】2023年03月 MES生产制造执行系统-004.Kafka的使用

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发布于 2023-03-16 19:06:21

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文章目录

前言

Kafka是一个分布式流处理平台，主要用于处理实时数据流。它可以用于日志收集、数据流处理、消息队列等场景。在大数据处理、实时数据分析等领域，Kafka被广泛应用。

Kafka的主要功能包括消息发布和订阅、消息存储和消息处理。

Kafka的概念包括生产者、消费者、主题、分区、偏移量等。生产者负责向Kafka发送消息，消费者负责从Kafka接收消息，主题是消息的分类，分区是主题的分片，偏移量是消息在分区中的位置。

Kafka有四个核心的API:

The Producer API 允许一个应用程序发布一串流式的数据到一个或者多个Kafka topic。
The Consumer API 允许一个应用程序订阅一个或多个 topic ，并且对发布给他们的流式数据进行处理。
The Streams API 允许一个应用程序作为一个流处理器，消费一个或者多个topic产生的输入流，然后生产一个输出流到一个或多个topic中去，在输入输出流中进行有效的转换。
The Connector API 允许构建并运行可重用的生产者或者消费者，将Kafka topics连接到已存在的应用程序或者数据系统。比如，连接到一个关系型数据库，捕捉表（table）的所有变更内容。

Kafka官网：https://kafka.apache.org/

Kafka中文文档：https://kafka.apachecn.org/

一、Kafka的使用

1.安装包

Confluent.Kafka

2.注入

if (AppSetting.Kafka.UseConsumer)
    builder.RegisterType<KafkaConsumer<string, string>>().As<IKafkaConsumer<string, string>>().SingleInstance();
if (AppSetting.Kafka.UseProducer)
    builder.RegisterType<KafkaProducer<string, string>>().As<IKafkaProducer<string, string>>().SingleInstance();

3.封装

3.1 IKafkaConsumer和IKafkaProducer

1、IKafkaConsumer

public interface IKafkaConsumer<TKey, TValue> : IDisposable
{
    /// <summary>
    /// 订阅回调模式-消费(持续订阅)
    /// </summary>
    /// <param name="Func">回调函数,若配置为非自动提交(默认为否),则通过回调函数的返回值判断是否提交</param>
    /// <param name="Topic">主题</param>
    void Consume(Func<ConsumeResult<TKey, TValue>, bool> Func, string Topic);

    /// <summary>
    /// 批量订阅回调模式-消费(持续订阅)
    /// </summary>
    /// <param name="Func">回调函数,若配置为非自动提交(默认为否),则通过回调函数的返回值判断是否提交</param>
    /// <param name="Topics">主题集合</param>
    void ConsumeBatch(Func<ConsumeResult<TKey, TValue>, bool> Func, List<string> Topics);

    /// <summary>
    /// 批量消费模式-单次消费(消费出当前Kafka缓存的所有数据,并持续监听 300ms,如无新数据生产,则返回(最多一次消费 100条)
    /// </summary>
    /// <param name="Topic">主题</param>
    /// <param name="TimeOut">持续监听时间,单位ms 默认值:300ms</param>
    /// <param name="MaxRow">最多单次消费行数 默认值:100行</param>
    /// <returns>待消费数据</returns>
    List<ConsumeResult<TKey, TValue>> ConsumeOnce(string Topic, int TimeOut = 300, int MaxRow = 100);

    /// <summary>
    /// 单笔消费模式-单行消费
    /// </summary>
    /// <param name="Topic">主题</param>
    /// <param name="TimeOut">持续监听时间,单位ms 默认值:300ms</param>
    /// <returns>待消费数据</returns>
    ConsumeResult<TKey, TValue> ConsumeOneRow(string Topic, int TimeOut = 300);
}

2、IKafkaProducer

public interface IKafkaProducer<TKey, TValue>
{
    /// <summary>
    /// 生产
    /// </summary>
    /// <param name="Key"></param>
    /// <param name="Value"></param>
    /// <param name="Topic"></param>
    void Produce(TKey Key, TValue Value, string Topic);

    /// <summary>
    /// 生产 异步
    /// </summary>
    /// <param name="Key"></param>
    /// <param name="Value"></param>
    /// <param name="Topic"></param>
    /// <returns></returns>
    Task ProduceAsync(TKey Key, TValue Value, string Topic);

}

3.2 KafkaConsumer和KafkaProducer

1、KafkaConsumer

/// <summary>
/// 消费者 (Message.Key的数据类型为string、Message.Value的数据类型为string）
/// 消费者实现三种消费方式：1.订阅回调模式 2.批量消费模式 3.单笔消费模式
/// </summary>
/// <typeparam name="TKey">Message.Key 的数据类型</typeparam>
/// <typeparam name="TValue">Message.Value 的数据类型</typeparam>
public class KafkaConsumer<TKey, TValue> : KafkaConfig, IKafkaConsumer<TKey, TValue>
{
    /// <summary>
    ///  Kafka地址(包含端口号)
    /// </summary>
    public string Servers
    {
        get
        {
            return ConsumerConfig.BootstrapServers;
        }
        set
        {
            ConsumerConfig.BootstrapServers = value;
        }
    }

    /// <summary>
    /// 消费者群组
    /// </summary>
    public string GroupId
    {
        get
        {
            return ConsumerConfig.GroupId;
        }
        set
        {
            ConsumerConfig.GroupId = value;
        }
    }

    /// <summary>
    /// 自动提交 默认为 false
    /// </summary>
    public bool EnableAutoCommit
    {
        get
        {
            return ConsumerConfig.EnableAutoCommit ?? false;
        }
        set
        {
            ConsumerConfig.EnableAutoCommit = value;
        }
    }

    /// <summary>
    /// 订阅回调模式-消费(持续订阅)
    /// </summary>
    /// <param name="Func">回调函数,若配置为非自动提交(默认为否),则通过回调函数的返回值判断是否提交</param>
    /// <param name="Topic">主题</param>
    public void Consume(Func<ConsumeResult<TKey, TValue>, bool> Func, string Topic)
    {
        Task.Factory.StartNew(() =>
        {
            var builder = new ConsumerBuilder<TKey, TValue>(ConsumerConfig);
            //设置反序列化方式
            builder.SetValueDeserializer(new KafkaDConverter<TValue>());
            builder.SetErrorHandler((_, e) =>
            {
                Logger.Error(LoggerType.KafkaException, null, null, $"Error:{e.Reason}");
            }).SetStatisticsHandler((_, json) =>
            {
                Console.WriteLine($"-{DateTime.Now:yyyy-MM-dd HH:mm:ss} > 消息监听中..");
            }).SetPartitionsAssignedHandler((c, partitions) =>
            {
                string partitionsStr = string.Join(", ", partitions);
                Console.WriteLine($"-分配的kafka分区:{partitionsStr}");
            }).SetPartitionsRevokedHandler((c, partitions) =>
            {
                string partitionsStr = string.Join(", ", partitions);
                Console.WriteLine($"-回收了kafka的分区:{partitionsStr}");
            });
            using var consumer = builder.Build();
            consumer.Subscribe(Topic);
            while (AppSetting.Kafka.IsConsumerSubscribe) //true
            {
                ConsumeResult<TKey, TValue> result = null;
                try
                {
                    result = consumer.Consume();
                    if (result.IsPartitionEOF) continue;
                    if (Func(result))
                    {
                        if (!(bool)ConsumerConfig.EnableAutoCommit)
                        {
                            //手动提交，如果上面的EnableAutoCommit=true表示自动提交，则无需调用Commit方法
                            consumer.Commit(result);
                        }
                    }
                }
                catch (ConsumeException ex)
                {
                    Logger.Error(LoggerType.KafkaException, $"Topic:{Topic},{ex.Error.Reason}", null, ex.Message + ex.StackTrace);
                }
                catch (Exception ex)
                {
                    Logger.Error(LoggerType.KafkaException, $"Topic:{result.Topic}", null, ex.Message + ex.StackTrace);
                }
            }
        });
    }

    /// <summary>
    /// 批量订阅回调模式-消费(持续订阅)
    /// </summary>
    /// <param name="Func">回调函数,若配置为非自动提交(默认为否),则通过回调函数的返回值判断是否提交</param>
    /// <param name="Topic">主题</param>
    public void ConsumeBatch(Func<ConsumeResult<TKey, TValue>, bool> Func, List<string> Topics)
    {
        Task.Factory.StartNew(() =>
        {
            var builder = new ConsumerBuilder<TKey, TValue>(ConsumerConfig);
            //设置反序列化方式
            builder.SetValueDeserializer(new KafkaDConverter<TValue>());
            builder.SetErrorHandler((_, e) =>
            {
                Logger.Error(LoggerType.KafkaException, null, null, $"Error:{e.Reason}");
            }).SetStatisticsHandler((_, json) =>
            {
                Console.WriteLine($"-{DateTime.Now:yyyy-MM-dd HH:mm:ss} > 消息监听中..");
            }).SetPartitionsAssignedHandler((c, partitions) =>
            {
                string partitionsStr = string.Join(", ", partitions);
                Console.WriteLine($"-分配的kafka分区:{partitionsStr}");
            }).SetPartitionsRevokedHandler((c, partitions) =>
            {
                string partitionsStr = string.Join(", ", partitions);
                Console.WriteLine($"-回收了kafka的分区:{partitionsStr}");
            });
            using var consumer = builder.Build();
            consumer.Subscribe(Topics);
            while (AppSetting.Kafka.IsConsumerSubscribe) //true
            {
                ConsumeResult<TKey, TValue> result = null;
                try
                {
                    result = consumer.Consume();
                    if (result.IsPartitionEOF) continue;
                    if (Func(result))
                    {
                        if (!(bool)ConsumerConfig.EnableAutoCommit)
                        {
                            //手动提交，如果上面的EnableAutoCommit=true表示自动提交，则无需调用Commit方法
                            consumer.Commit(result);
                        }
                    }
                }
                catch (ConsumeException ex)
                {
                    Logger.Error(LoggerType.KafkaException, $"Topic:{Topics.ToArray()},{ex.Error.Reason}", null, ex.Message + ex.StackTrace);
                }
                catch (Exception ex)
                {
                    Logger.Error(LoggerType.KafkaException, $"Topic:{result.Topic}", null, ex.Message + ex.StackTrace);
                }
            }
        });
    }

    /// <summary>
    /// 批量消费模式-单次消费(消费出当前Kafka缓存的所有数据,并持续监听 300ms,如无新数据生产,则返回(最多一次消费 100条)
    /// </summary>
    /// <param name="Topic">主题</param>
    /// <param name="TimeOut">持续监听时间,单位ms 默认值:300ms</param>
    /// <param name="MaxRow">最多单次消费行数 默认值:100行</param>
    /// <returns>待消费数据</returns>
    public List<ConsumeResult<TKey, TValue>> ConsumeOnce(string Topic, int TimeOut = 300, int MaxRow = 100)
    {
        var builder = new ConsumerBuilder<TKey, TValue>(ConsumerConfig);
        //设置反序列化方式
        builder.SetValueDeserializer(new KafkaDConverter<TValue>());
        using var consumer = builder.Build();
        consumer.Subscribe(Topic);
        List<ConsumeResult<TKey, TValue>> Res = new List<ConsumeResult<TKey, TValue>>();
        while (true)
        {
            try
            {
                var result = consumer.Consume(TimeSpan.FromMilliseconds(TimeOut));
                if (result == null) break;
                else
                {
                    Res.Add(result);
                    //手动提交，如果上面的EnableAutoCommit=true表示自动提交，则无需调用Commit方法
                    consumer.Commit();
                }
                if (Res.Count > MaxRow) break;
            }
            catch (Exception ex)
            {
                Logger.Error(LoggerType.KafkaException, $"Topic:{Topic}", null, ex.Message + ex.StackTrace);
                return null;
            }
        }
        return Res;
    }

    /// <summary>
    /// 单笔消费模式-单行消费
    /// </summary>
    /// <param name="Topic">主题</param>
    /// <param name="TimeOut">持续监听时间,单位ms 默认值:300ms</param>
    /// <returns>待消费数据</returns>
    public ConsumeResult<TKey, TValue> ConsumeOneRow(string Topic, int TimeOut = 300)
    {
        var builder = new ConsumerBuilder<TKey, TValue>(ConsumerConfig);
        //设置反序列化方式
        builder.SetValueDeserializer(new KafkaDConverter<TValue>());
        using var consumer = builder.Build();
        consumer.Subscribe(Topic);
        try
        {
            var result = consumer.Consume(TimeSpan.FromMilliseconds(TimeOut));
            if (result != null)
            {
                //手动提交，如果上面的EnableAutoCommit=true表示自动提交，则无需调用Commit方法
                consumer.Commit();
            }
            return result;
        }
        catch (Exception ex)
        {
            Logger.Error(LoggerType.KafkaException, $"Topic:{Topic}", null, ex.Message + ex.StackTrace);
            return null;
        }
    }

    public void Dispose()
    {
        //if (_cache != null)
        //    _cache.Dispose();
        GC.SuppressFinalize(this);
    }
}

2、KafkaProducer

/// <summary>
/// 生产者 控制器或Service里面构造函数注入即可调用
/// Message.Key的数据类型为string、Message.Value的数据类型为string
/// </summary>
/// <typeparam name="TKey">Message.Key 的数据类型</typeparam>
/// <typeparam name="TValue">Message.Value 的数据类型</typeparam>
public class KafkaProducer<TKey, TValue> : KafkaConfig, IKafkaProducer<TKey, TValue>
{
    /// <summary>
    /// 构造生产者
    /// </summary>
    public KafkaProducer()
    {

    }

    /// <summary>
    ///  Kafka地址(包含端口号)
    /// </summary>
    public string Servers
    {
        get
        {
            return ProducerConfig.BootstrapServers;
        }
        set
        {
            ProducerConfig.BootstrapServers = value;
        }
    }

    /// <summary>
    /// 生产
    /// </summary>
    /// <param name="Key">Message.Key 做消息指定分区投放有用的</param>
    /// <param name="Value">Message.Value</param>
    /// <param name="Topic">主题</param>
    public void Produce(TKey Key, TValue Value, string Topic)
    {
        var producerBuilder = new ProducerBuilder<TKey, TValue>(ProducerConfig);
        producerBuilder.SetValueSerializer(new KafkaConverter<TValue>());//设置序列化方式
        using var producer = producerBuilder.Build();
        try
        {
            producer.Produce(Topic, new Message<TKey, TValue>
            {
                Key = Key,
                Value = Value
            }, (result) =>
            {
                if (result.Error.IsError)
                    Logger.Error(LoggerType.KafkaException, $"Topic:{Topic},ServerIp:{KafkaHelper.GetServerIp()},ServerName:{KafkaHelper.GetServerName()}", null, $"Delivery Error:{result.Error.Reason}");
            });//Value = JsonConvert.SerializeObject(value)
        }
        catch (ProduceException<Null, string> ex)
        {
            Logger.Error(LoggerType.KafkaException, $"Topic:{Topic},Delivery failed: {ex.Error.Reason}", null, ex.Message + ex.StackTrace);
        }
    }

    /// <summary>
    /// 生产异步
    /// </summary>
    /// <param name="Key">Message.Key</param>
    /// <param name="Value">Message.Value</param>
    /// <param name="Topic">主题</param>
    /// <returns></returns>
    public async Task ProduceAsync(TKey Key, TValue Value, string Topic)
    {
        var producerBuilder = new ProducerBuilder<TKey, TValue>(ProducerConfig);
        producerBuilder.SetValueSerializer(new KafkaConverter<TValue>());
        using var producer = producerBuilder.Build();
        try
        {
            var dr = await producer.ProduceAsync(Topic, new Message<TKey, TValue>
            {
                Key = Key,
                Value = Value
            });
            //Console.WriteLine($"Delivered '{dr.Value}' to '{dr.TopicPartitionOffset}'");
        }
        catch (ProduceException<Null, string> ex)
        {
            Logger.Error(LoggerType.KafkaException, $"Topic:{Topic},ServerIp:{KafkaHelper.GetServerIp()},ServerName:{KafkaHelper.GetServerName()},Delivery failed: {ex.Error.Reason}", null, ex.Message + ex.StackTrace);
        }
    }
}

3.3 KafkaConfig配置类

/// <summary>
/// 配置类
/// </summary>
public class KafkaConfig
{
    /// <summary>
    /// 构造配置类
    /// </summary>
    protected KafkaConfig()
    {
        ProducerConfig = new ProducerConfig()
        {
            BootstrapServers = AppSetting.Kafka.ProducerSettings.BootstrapServers,// "192.168.20.241:9092",
        };

        ConsumerConfig = new ConsumerConfig()
        {
            BootstrapServers = AppSetting.Kafka.ConsumerSettings.BootstrapServers,
            GroupId = AppSetting.Kafka.ConsumerSettings.GroupId,
            AutoOffsetReset = AutoOffsetReset.Earliest,//当各分区下有已提交的offset时，从提交的offset开始消费；无提交的offset时，从头开始消费
            EnableAutoCommit = false,
            //Kafka配置安全认证
            //SecurityProtocol = SecurityProtocol.SaslPlaintext,
            //SaslMechanism = SaslMechanism.Plain,
            //SaslUsername = AppSetting.Kafka.ConsumerSettings.SaslUsername,
            //SaslPassword = AppSetting.Kafka.ConsumerSettings.SaslPassword,
        };
    }

    /// <summary>
    /// 消费者配置文件
    /// </summary>
    public ConsumerConfig ConsumerConfig;

    /// <summary>
    /// 生产者配置文件
    /// </summary>
    public ProducerConfig ProducerConfig;
}

3.4 KafkaHelper帮助类

namespace KafkaManager
{
    /// <summary>
    /// 辅助类
    /// </summary>
    public class KafkaHelper
    {
        /// <summary>
        /// 获取当前应用程式名称(仅控制台应用程序和Windows应用程序可用)
        /// </summary>
        /// <returns></returns>
        public static string GetApplicationName()
        {
            try
            {
                return Assembly.GetEntryAssembly().GetName().Name;
            }
            catch
            {
                return "Kafka_Test";
            }
        }

        /// <summary>
        /// 获取服务器名称
        /// </summary>
        /// <returns></returns>
        public static string GetServerName()
        {
            return Dns.GetHostName();
        }

        /// <summary>
        /// 获取服务器IP
        /// </summary>
        /// <returns></returns>
        public static string GetServerIp()
        {
            IPHostEntry ips = Dns.GetHostEntry(Dns.GetHostName());
            foreach (var ip in ips.AddressList)
            {
                if (Regex.IsMatch(ip.ToString(), @"^10\.((25[0-5]|2[0-4]\d|1\d{2}|\d?\d)\.){2}(25[0-5]|2[0-4]\d|1\d{2}|\d?\d)$"))
                {
                    return ip.ToString();
                };
            }
            return "127.0.0.1";
        }

        /// <summary>  
        /// 将c# DateTime时间格式转换为Unix时间戳格式(毫秒级)  
        /// </summary>  
        /// <returns>long</returns>  
        public static long GetTimeStamp()
        {
            DateTime time = DateTime.Now;
            long t = (time.Ticks - 621356256000000000) / 10000;
            return t;
        }
    }

    #region 实现消息序列化和反序列化
    public class KafkaConverter<T> : ISerializer<T>
    {
        /// <summary>
        /// 序列化数据成字节
        /// </summary>
        /// <param name="data"></param>
        /// <param name="context"></param>
        /// <returns></returns>
        public byte[] Serialize(T data, SerializationContext context)
        {
            var json = JsonConvert.SerializeObject(data);
            return Encoding.UTF8.GetBytes(json);
        }
    }

    public class KafkaDConverter<T> : IDeserializer<T>
    {
        /// <summary>
        /// 反序列化字节数据成实体数据
        /// </summary>
        /// <param name="data"></param>
        /// <param name="isNull"></param>
        /// <param name="context"></param>
        /// <returns></returns>
        public T Deserialize(ReadOnlySpan<byte> data, bool isNull, SerializationContext context)
        {
            if (isNull) return default(T);

            var json = Encoding.UTF8.GetString(data.ToArray());
            try
            {
                return JsonConvert.DeserializeObject<T>(json);
            }
            catch
            {
                return default(T);
            }
        }
    }
    #endregion

    #region 日志类
    /// <summary>
    /// 默认日志类 可自行构造使用
    /// </summary>
    public class KafkaLogModel
    {
        /// <summary>
        /// 构造默认日志类(设置默认值 ServerIp,ServerName,TimeStamp,ApplicationVersion)
        /// </summary>
        public KafkaLogModel()
        {
            ServerIp = KafkaHelper.GetServerIp();
            ServerName = KafkaHelper.GetServerName();
            TimeStamp = DateTime.Now;
            ApplicationName = KafkaHelper.GetApplicationName();
            ApplicationVersion = "V1.0.0";
        }

        /// <summary>
        /// 程式名称(默认获取当前程式名称,Web应用 默认为 ISD_Kafka)
        /// </summary>
        public string ApplicationName { get; set; }

        /// <summary>
        /// 程式版本(默认为V1.0.0)
        /// </summary>
        public string ApplicationVersion { get; set; }

        /// <summary>
        /// 发生时间(默认为当前时间)
        /// </summary>
        public DateTime TimeStamp { get; set; }

        /// <summary>
        /// 开始时间
        /// </summary>
        public DateTime BeginDate { get; set; }

        /// <summary>
        /// 结束时间
        /// </summary>
        public DateTime EndDate { get; set; }

        /// <summary>
        /// 服务器IP(默认抓取当前服务器IP)
        /// </summary>
        public string ServerIp { get; set; }

        /// <summary>
        /// 服务器名称(默认抓取当前服务器名称)
        /// </summary>
        public string ServerName { get; set; }

        /// <summary>
        /// 客户端IP
        /// </summary>
        public string ClientIp { get; set; }

        /// <summary>
        /// 模块(页面路径)
        /// </summary>
        public string Module { get; set; }

        /// <summary>
        /// 操作人
        /// </summary>
        public string Operator { get; set; }

        /// <summary>
        /// 操作类型 如:Query,Add,Update,Delete,Export等,可自定义
        /// </summary>
        public string OperationType { get; set; }

        /// <summary>
        /// 操作状态 如:http请求使用200,404,503等,其他操作 1:成功,0失败等 可自定义
        /// </summary>
        public string Status { get; set; }

        /// <summary>
        /// 其他信息
        /// </summary>
        public string Message { get; set; }
    }
    #endregion
}

4.使用

#region kafka使用
if (AppSetting.Kafka.UseConsumer)
{
    using var scope = host.Services.CreateScope();
    var testConsumer = scope.ServiceProvider.GetService<IKafkaConsumer<string, string>>();
    testConsumer.Consume(res =>
    {
        Console.WriteLine($"recieve:{DateTime.Now.ToLongTimeString()}  value:{res.Message.Value}");

        bool bl = DataHandle.AlarmData(res.Message.Value);

        return bl;
    }, AppSetting.Kafka.Topics.TestTopic);
}
#endregion

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原始发表：2023-03-13，如有侵权请联系 cloudcommunity@tencent.com 删除

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