.NET Core下使用Kafka的方法步骤

安装

CentOS安装 kafka

Kafka : http://kafka.apache.org/downloads

ZooLeeper : https://zookeeper.apache.org/releases.html

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。

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
{
  /// 
  /// 发送消息至指定主题
  /// 
  /// 
  /// 
  /// 
  /// 
  Task PublishAsync(string topicName, TMessage message) where TMessage : class;

  /// 
  /// 从指定主题订阅消息
  /// 
  /// 
  /// 
  /// 
  /// 
  /// 
  Task SubscribeAsync(IEnumerable topics, Action messageFunc, CancellationToken cancellationToken) where TMessage : class;
}

实现 IKafkaService

public class KafkaService : IKafkaService
{
  public async Task PublishAsync(string topicName, TMessage message) where TMessage : class
  {
    var config = new ProducerConfig
    {
      BootstrapServers = "127.0.0.1:9092"
    };
    using var producer = new ProducerBuilder(config).Build();
    await producer.ProduceAsync(topicName, new Message
    {
      Key = Guid.NewGuid().ToString(),
      Value = message.SerializeToJson()
    });
  }

  public async Task SubscribeAsync(IEnumerable topics, Action 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(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(consumeResult.Message.Value);
   }
   catch (Exception ex)
   {
     var errorMessage = $" - {DateTime.Now:yyyy-MM-dd HH:mm:ss}【Exception 消息反序列化失败，Value：{consumeResult.Message.Value}】 ：{ex.StackTrace?.ToString()}";
     Console.WriteLine(errorMessage);
     messageResult = null;
   }
   if (messageResult != null)
   {
     messageFunc(messageResult);
     try
     {
consumer.Commit(consumeResult);
     }
     catch (KafkaException e)
     {
Console.WriteLine(e.Message);
     }
   }
 }
 catch (ConsumeException e)
 {
   Console.WriteLine($"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(topics, async (eventData) =>
{
  // Your logic

  Console.WriteLine($" - {eventData.EventTime:yyyy-MM-dd HH:mm:ss} 【{eventData.TopicName}】- > 已处理");
}, cts.Token);

在 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(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");
  Console.WriteLine("To create a kafka message with a null key and UTF-8 encoded value:");
  Console.WriteLine("> value");
  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
      {
 Key = key,
 Value = val
      });

      Console.WriteLine($"delivered to: {deliveryResult.TopicPartitionOffset}");
    }
    catch (ProduceException e)
    {
      Console.WriteLine($"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(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();
  }
}

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.NET Core下使用Kafka的方法步骤

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