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.NET Core 下使用 Kafka


安装

CentOS 安装 kafka

下载并解压

# 下载,并解压 $ wget https://archive.apache.org/dist/kafka/2.1.1/kafka_2.12-2.1.1.tgz $ tar -zxvf  kafka_2.12-2.1.1.tgz $ mv kafka_2.12-2.1.1.tgz /data/kafka  # 下载 zookeeper,解压 $ wget https://mirror.bit.edu.cn/apache/zookeeper/zookeeper-3.5.8/apache-zookeeper-3.5.8-bin.tar.gz $ tar -zxvf apache-zookeeper-3.5.8-bin.tar.gz $ mv apache-zookeeper-3.5.8-bin /data/zookeeper 

启动 ZooKeeper

# 复制配置模版 $ cd /data/kafka/conf $ cp zoo_sample.cfg zoo.cfg  # 看看配置需不需要改 $ vim zoo.cfg  # 命令 $ ./bin/zkServer.sh start    # 启动 $ ./bin/zkServer.sh status   # 状态 $ ./bin/zkServer.sh stop     # 停止 $ ./bin/zkServer.sh restart  # 重启  # 使用客户端测试 $ ./bin/zkCli.sh -server localhost:2181 $ quit 

启动 Kafka

# 备份配置 $ cd /data/kafka $ cp config/server.properties config/server.properties_copy  # 修改配置 $ vim /data/kafka/config/server.properties  # 集群配置下,每个 broker 的 id 是必须不同的 # broker.id=0  # 监听地址设置(内网) # listeners=PLAINTEXT://ip:9092  # 对外提供服务的IP、端口 # advertised.listeners=PLAINTEXT://106.75.84.97:9092  # 修改每个topic的默认分区参数num.partitions,默认是1,具体合适的取值需要根据服务器配置进程确定,UCloud.ukafka = 3 # num.partitions=3  # zookeeper 配置 # zookeeper.connect=localhost:2181  # 通过配置启动 kafka $  ./bin/kafka-server-start.sh  config/server.properties&  # 状态查看 $ ps -ef|grep kafka $ jps 

docker下安装Kafka

docker pull wurstmeister/zookeeper docker run -d --name zookeeper -p 2181:2181 wurstmeister/zookeeper 
docker pull wurstmeister/kafka docker run -d --name kafka --publish 9092:9092 --link zookeeper --env KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 --env KAFKA_ADVERTISED_HOST_NAME=192.168.1.111 --env KAFKA_ADVERTISED_PORT=9092 wurstmeister/kafka 

介绍

  • Broker:消息中间件处理节点,一个Kafka节点就是一个broker,多个broker可以组成一个Kafka集群。
  • Topic:一类消息,例如page view日志、click日志等都可以以topic的形式存在,Kafka集群能够同时负责多个topic的分发。
  • Partition:topic物理上的分组,一个topic可以分为多个partition,每个partition是一个有序的队列。
  • Segment:partition物理上由多个segment组成,下面2.2和2.3有详细说明。
  • offset:每个partition都由一系列有序的、不可变的消息组成,这些消息被连续的追加到partition中。partition中的每个消息都有一个连续的序列号叫做offset,用于partition唯一标识一条消息。

.NET Core 下使用 Kafka

kafka partition 和 consumer 数目关系

  • 如果consumer比partition多是浪费,因为kafka的设计是在一个partition上是不允许并发的,所以consumer数不要大于partition数 。
  • 如果consumer比partition少,一个consumer会对应于多个partitions,这里主要合理分配consumer数和partition数,否则会导致partition里面的数据被取的不均匀 。最好partiton数目是consumer数目的整数倍,所以partition数目很重要,比如取24,就很容易设定consumer数目 。
  • 如果consumer从多个partition读到数据,不保证数据间的顺序性,kafka只保证在一个partition上数据是有序的,但多个partition,根据你读的顺序会有不同
  • 增减consumer,broker,partition会导致rebalance,所以rebalance后consumer对应的partition会发生变化

快速开始

在 .NET Core 项目中安装组件

Install-Package Confluent.Kafka 

开源地址:https://github.com/confluentinc/confluent-kafka-dotnet

添加IKafkaService服务接口

public interface IKafkaService {     /// <summary>     /// 发送消息至指定主题     /// </summary>     /// <typeparam name="TMessage"></typeparam>     /// <param name="topicName"></param>     /// <param name="message"></param>     /// <returns></returns>     Task PublishAsync<TMessage>(string topicName, TMessage message) where TMessage : class;      /// <summary>     /// 从指定主题订阅消息     /// </summary>     /// <typeparam name="TMessage"></typeparam>     /// <param name="topics"></param>     /// <param name="messageFunc"></param>     /// <param name="cancellationToken"></param>     /// <returns></returns>     Task SubscribeAsync<TMessage>(IEnumerable<string> topics, Action<TMessage> messageFunc, CancellationToken cancellationToken) where TMessage : class; } 

实现IKafkaService

public class KafkaService : IKafkaService {     public async Task PublishAsync<TMessage>(string topicName, TMessage message) where TMessage : class     {         var config = new ProducerConfig         {             BootstrapServers = "127.0.0.1:9092"         };         using var producer = new ProducerBuilder<string, string>(config).Build();         await producer.ProduceAsync(topicName, new Message<string, string>         {             Key = Guid.NewGuid().ToString(),             Value = message.SerializeToJson()         });     }      public async Task SubscribeAsync<TMessage>(IEnumerable<string> topics, Action<TMessage> messageFunc, CancellationToken cancellationToken) where TMessage : class     {         var config = new ConsumerConfig         {             BootstrapServers = "127.0.0.1:9092",             GroupId = "crow-consumer",             EnableAutoCommit = false,             StatisticsIntervalMs = 5000,             SessionTimeoutMs = 6000,             AutoOffsetReset = AutoOffsetReset.Earliest,             EnablePartitionEof = true         };         //const int commitPeriod = 5;         using var consumer = new ConsumerBuilder<Ignore, string>(config)                              .SetErrorHandler((_, e) =>                              {                                  Console.WriteLine($"Error: {e.Reason}");                              })                              .SetStatisticsHandler((_, json) =>                              {                                  Console.WriteLine($" - {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}");                              })                              .Build();         consumer.Subscribe(topics);         try         {             while (true)             {                 try                 {                     var consumeResult = consumer.Consume(cancellationToken);                     Console.WriteLine($"Consumed message '{consumeResult.Message?.Value}' at: '{consumeResult?.TopicPartitionOffset}'.");                     if (consumeResult.IsPartitionEOF)                     {                         Console.WriteLine($" - {DateTime.Now:yyyy-MM-dd HH:mm:ss} 已经到底了:{consumeResult.Topic}, partition {consumeResult.Partition}, offset {consumeResult.Offset}.");                         continue;                     }                     TMessage messageResult = null;                     try                     {                         messageResult = JsonConvert.DeserializeObject<TMessage>(consumeResult.Message.Value);                     }                     catch (Exception ex)                     {                         var errorMessage = $" - {DateTime.Now:yyyy-MM-dd HH:mm:ss}【Exception 消息反序列化失败,Value:{consumeResult.Message.Value}】 :{ex.StackTrace?.ToString()}";                         Console.WriteLine(errorMessage);                         messageResult = null;                     }                     if (messageResult != null/* && consumeResult.Offset % commitPeriod == 0*/)                     {                         messageFunc(messageResult);                         try                         {                             consumer.Commit(consumeResult);                         }                         catch (KafkaException e)                         {                             Console.WriteLine(e.Message);                         }                     }                 }                 catch (ConsumeException e)                 {                     Console.WriteLine($"Consume error: {e.Error.Reason}");                 }             }         }         catch (OperationCanceledException)         {             Console.WriteLine("Closing consumer.");             consumer.Close();         }         await Task.CompletedTask;     } } 

注入IKafkaService,在需要使用的地方直接调用即可。

public class MessageService : IMessageService, ITransientDependency {     private readonly IKafkaService _kafkaService;     public MessageService(IKafkaService kafkaService)     {         _kafkaService = kafkaService;     }      public async Task RequestTraceAdded(XxxEventData eventData)     {         await _kafkaService.PublishAsync(eventData.TopicName, eventData);     } } 

以上相当于一个生产者,当我们消息队列发出后,还需一个消费者进行消费,所以可以使用一个控制台项目接收消息来处理业务。

var cts = new CancellationTokenSource(); Console.CancelKeyPress += (_, e) => {     e.Cancel = true;     cts.Cancel(); };  await kafkaService.SubscribeAsync<XxxEventData>(topics, async (eventData) => {     // Your logic      Console.WriteLine($" - {eventData.EventTime:yyyy-MM-dd HH:mm:ss} 【{eventData.TopicName}】- > 已处理"); }, cts.Token); 

IKafkaService中已经写了订阅消息的接口,这里也是注入后直接使用即可。

生产者消费者示例

生产者

static async Task Main(string[] args) {     if (args.Length != 2)     {         Console.WriteLine("Usage: .. brokerList topicName");         // 127.0.0.1:9092 helloTopic         return;     }      var brokerList = args.First();     var topicName = args.Last();      var config = new ProducerConfig { BootstrapServers = brokerList };      using var producer = new ProducerBuilder<string, string>(config).Build();      Console.WriteLine("n-----------------------------------------------------------------------");     Console.WriteLine($"Producer {producer.Name} producing on topic {topicName}.");     Console.WriteLine("-----------------------------------------------------------------------");     Console.WriteLine("To create a kafka message with UTF-8 encoded key and value:");     Console.WriteLine("> key value<Enter>");     Console.WriteLine("To create a kafka message with a null key and UTF-8 encoded value:");     Console.WriteLine("> value<enter>");     Console.WriteLine("Ctrl-C to quit.n");      var cancelled = false;      Console.CancelKeyPress += (_, e) =>     {         e.Cancel = true;         cancelled = true;     };      while (!cancelled)     {         Console.Write("> ");          var text = string.Empty;          try         {             text = Console.ReadLine();         }         catch (IOException)         {             break;         }          if (string.IsNullOrWhiteSpace(text))         {             break;         }          var key = string.Empty;         var val = text;          var index = text.IndexOf(" ");         if (index != -1)         {             key = text.Substring(0, index);             val = text.Substring(index + 1);         }          try         {             var deliveryResult = await producer.ProduceAsync(topicName, new Message<string, string>             {                 Key = key,                 Value = val             });              Console.WriteLine($"delivered to: {deliveryResult.TopicPartitionOffset}");         }         catch (ProduceException<string, string> e)         {             Console.WriteLine($"failed to deliver message: {e.Message} [{e.Error.Code}]");         }     } } 

消费者

static void Main(string[] args) {     if (args.Length != 2)     {         Console.WriteLine("Usage: .. brokerList topicName");         // 127.0.0.1:9092 helloTopic         return;     }      var brokerList = args.First();     var topicName = args.Last();      Console.WriteLine($"Started consumer, Ctrl-C to stop consuming");      var cts = new CancellationTokenSource();     Console.CancelKeyPress += (_, e) =>     {         e.Cancel = true;         cts.Cancel();     };      var config = new ConsumerConfig     {         BootstrapServers = brokerList,         GroupId = "consumer",         EnableAutoCommit = false,         StatisticsIntervalMs = 5000,         SessionTimeoutMs = 6000,         AutoOffsetReset = AutoOffsetReset.Earliest,         EnablePartitionEof = true     };      const int commitPeriod = 5;      using var consumer = new ConsumerBuilder<Ignore, string>(config)                          .SetErrorHandler((_, e) =>                          {                              Console.WriteLine($"Error: {e.Reason}");                          })                          .SetStatisticsHandler((_, json) =>                          {                              Console.WriteLine($" - {DateTime.Now:yyyy-MM-dd HH:mm:ss} > monitoring..");                              //Console.WriteLine($"Statistics: {json}");                          })                          .SetPartitionsAssignedHandler((c, partitions) =>                          {                              Console.WriteLine($"Assigned partitions: [{string.Join(", ", partitions)}]");                          })                          .SetPartitionsRevokedHandler((c, partitions) =>                          {                              Console.WriteLine($"Revoking assignment: [{string.Join(", ", partitions)}]");                          })                          .Build();     consumer.Subscribe(topicName);      try     {         while (true)         {             try             {                 var consumeResult = consumer.Consume(cts.Token);                  if (consumeResult.IsPartitionEOF)                 {                     Console.WriteLine($"Reached end of topic {consumeResult.Topic}, partition {consumeResult.Partition}, offset {consumeResult.Offset}.");                      continue;                 }                  Console.WriteLine($"Received message at {consumeResult.TopicPartitionOffset}: {consumeResult.Message.Value}");                  if (consumeResult.Offset % commitPeriod == 0)                 {                     try                     {                         consumer.Commit(consumeResult);                     }                     catch (KafkaException e)                     {                         Console.WriteLine($"Commit error: {e.Error.Reason}");                     }                 }             }             catch (ConsumeException e)             {                 Console.WriteLine($"Consume error: {e.Error.Reason}");             }         }     }     catch (OperationCanceledException)     {         Console.WriteLine("Closing consumer.");         consumer.Close();     } } 

.NET Core 下使用 Kafka

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