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/zookeeperdocker 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
{/// <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 = "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 logicConsole.WriteLine($" - {eventData.EventTime:yyyy-MM-dd HH:mm:ss} 【{eventData.TopicName}】- > 已处理");
}, cts.Token);
在IKafkaService
中已经写了订阅消息的接口,这里也是注入后直接使用即可。
生产者消费者示例
生产者
static async Task Main(string[] args)
{if (args.Length != 2){Console.WriteLine("Usage: .. brokerList topicName");// 127.0.0.1:9092 helloTopicreturn;}var brokerList = args.First();var topicName = args.Last();var config = new ProducerConfig { BootstrapServers = brokerList };using var producer = new ProducerBuilder<string, string>(config).Build();Console.WriteLine("\n-----------------------------------------------------------------------");Console.WriteLine($"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 helloTopicreturn;}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();}
}