Kafka源码分析Producer读取Metadata的数据结构及Metadata两种更新机制介绍 转

 

问题导读：
1. 什么是多线程异步发送模型？
2. Metadata的线程安全性如何实现？
3. Metadata的数据结构是什么？
4. producer如何读取Metadata？
5. Sender的如何创建?
6. Sender poll()如何更新Metadata？
7. Metadata有哪2种更新机制?
8. 什么是Metadata失效检测?
9. Metadata有哪些其他的更新策略？




解决方案：

多线程异步发送模型

下图是经过源码分析之后，整理出来的Producer端的架构图： 
 
在上一篇我们讲过，Producer有同步发送和异步发送2种策略。在以前的Kafka client api实现中，同步和异步是分开实现的。而在0.9中，同步发送其实是通过异步发送间接实现，其接口如下：

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public class KafkaProducer<K, V> implements Producer<K, V> { ...     public Future<RecordMetadata> send(ProducerRecord<K, V> record, Callback callback)  //异步发送接口      {      ...      } }

要实现同步发送，只要在拿到返回的Future对象之后，直接调用get()就可以了。

基本思路

从上图我们可以看出，异步发送的基本思路就是：send的时候，KafkaProducer把消息放到本地的消息队列RecordAccumulator，然后一个后台线程Sender不断循环，把消息发给Kafka集群。

要实现这个，还得有一个前提条件：就是KafkaProducer/Sender都需要获取集群的配置信息Metadata。所谓Metadata，也就是在上一篇所讲的，Topic/Partion与broker的映射关系：每一个Topic的每一个Partion，得知道其对应的broker列表是什么，其中leader是谁，follower是谁。

 

2个数据流

所以在上图中，有2个数据流： 
Metadata流(A1,A2,A3)：Sender从集群获取信息，然后更新Metadata； KafkaProducer先读取Metadata，然后把消息放入队列。

消息流(B1, B2, B3)：这个很好理解，不再详述。

本篇着重讲述Metadata流，消息流，将在后续详细讲述。

 

Metadata的线程安全性

从上图可以看出，Metadata是多个producer线程读，一个sender线程更新，因此它必须是线程安全的。

Kafka的官方文档上也有说明，KafkaProducer是线程安全的，可以在多线程中调用：

The producer is thread safe and sharing a single producer instance across threads will generally be faster than having multiple instances.

 

从下面代码也可以看出，它的所有public方法都是synchronized:

 

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public final class Metadata {   。。。     public synchronized Cluster fetch() {         return this.cluster;     }     public synchronized long timeToNextUpdate(long nowMs) {        。。。     }     public synchronized int requestUpdate() {       。。。     }     。。。    ｝

 

Metadata的数据结构

 

下面代码列举了Metadata的主要数据结构：一个Cluster对象 + 1堆状态变量。前者记录了集群的配置信息，后者用于控制Metadata的更新策略。

 

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public final class Metadata { ...     private final long refreshBackoffMs;  //更新失败的情况下，下1次更新的补偿时间（这个变量在代码中意义不是太大）     private final long metadataExpireMs; //关键值：每隔多久，更新一次。缺省是600*1000，也就是10分种     private int version;         //每更新成功1次，version递增1。这个变量主要用于在while循环，wait的时候，作为循环判断条件     private long lastRefreshMs;  //上一次更新时间（也包含更新失败的情况）     private long lastSuccessfulRefreshMs; //上一次成功更新的时间（如果每次都成功的话，则2者相等。否则，lastSuccessulRefreshMs < lastRefreshMs)     private Cluster cluster;   //集群配置信息     private boolean needUpdate;  //是否强制刷新 、   ... }   public final class Cluster { ...     private final List<Node> nodes;   //Node也就是Broker     private final Map<TopicPartition, PartitionInfo> partitionsByTopicPartition;  //Topic/Partion和broker list的映射关系     private final Map<String, List<PartitionInfo>> partitionsByTopic;     private final Map<String, List<PartitionInfo>> availablePartitionsByTopic;     private final Map<Integer, List<PartitionInfo>> partitionsByNode;     private final Map<Integer, Node> nodesById; }   public class PartitionInfo {     private final String topic;     private final int partition;     private final Node leader;     private final Node[] replicas;     private final Node[] inSyncReplicas; }

 

producer读取Metadata

 

下面是send函数的源码，可以看到，在send之前，会先读取metadata。如果metadata读不到，会一直阻塞在那，直到超时，抛出TimeoutException

 

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//KafkaProducer     public Future<RecordMetadata> send(ProducerRecord<K, V> record, Callback callback) {         try {      long waitedOnMetadataMs = waitOnMetadata(record.topic(), this.maxBlockTimeMs);  //拿不到topic的配置信息，会一直阻塞在这，直到抛异常        ... //拿到了，执行下面的send逻辑      } catch()      {}  }   //KafkaProducer     private long waitOnMetadata(String topic, long maxWaitMs) throws InterruptedException {         if (!this.metadata.containsTopic(topic))             this.metadata.add(topic);           if (metadata.fetch().partitionsForTopic(topic) != null)             return 0;   //取到topic的配置信息，直接返回           long begin = time.milliseconds();         long remainingWaitMs = maxWaitMs;         while (metadata.fetch().partitionsForTopic(topic) == null) { //取不到topic的配置信息，一直死循环wait，直到超时，抛TimeoutException             log.trace("Requesting metadata update for topic {}.", topic);             int version = metadata.requestUpdate(); //把needUpdate置为true             sender.wakeup(); //唤起sender               metadata.awaitUpdate(version, remainingWaitMs); //metadata的关键函数             long elapsed = time.milliseconds() - begin;             if (elapsed >= maxWaitMs)                 throw new TimeoutException("Failed to update metadata after " + maxWaitMs + " ms.");             if (metadata.fetch().unauthorizedTopics().contains(topic))                 throw new TopicAuthorizationException(topic);             remainingWaitMs = maxWaitMs - elapsed;         }         return time.milliseconds() - begin;     }   //Metadata     public synchronized void awaitUpdate(final int lastVersion, final long maxWaitMs) throws InterruptedException {         if (maxWaitMs < 0) {             throw new IllegalArgumentException("Max time to wait for metadata updates should not be < 0 milli seconds");         }         long begin = System.currentTimeMillis();         long remainingWaitMs = maxWaitMs;         while (this.version <= lastVersion) {  //当Sender成功更新meatadata之后，version加1。否则会循环，一直wait             if (remainingWaitMs != 0                 wait(remainingWaitMs);  //线程的wait机制，wait和synchronized的配合使用             long elapsed = System.currentTimeMillis() - begin;             if (elapsed >= maxWaitMs)  //wait时间超出了最长等待时间                 throw new TimeoutException("Failed to update metadata after " + maxWaitMs + " ms.");             remainingWaitMs = maxWaitMs - elapsed;         }     }

 

总结：从上面代码可以看出，producer wait metadata的时候，有2个条件：

（1） while (metadata.fetch().partitionsForTopic(topic) == null)

（2）while (this.version <= lastVersion)

 

有wait就会有notify，notify在Sender更新Metadata的时候发出。

 

Sender的创建

 

下面是KafkaProducer的构造函数，从代码可以看出，Sender就是KafkaProducer中创建的一个Thread.

 

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private KafkaProducer(ProducerConfig config, Serializer<K> keySerializer, Serializer<V> valueSerializer) {         try {         ...                     this.metadata = new Metadata(retryBackoffMs, config.getLong(ProducerConfig.METADATA_MAX_AGE_CONFIG)); //构造metadata   this.metadata.update(Cluster.bootstrap(addresses), time.milliseconds()); //往metadata中，填入初始的，配置的node列表               ChannelBuilder channelBuilder = ClientUtils.createChannelBuilder(config.values());               NetworkClient client = new NetworkClient(                     new Selector(config.getLong(ProducerConfig.CONNECTIONS_MAX_IDLE_MS_CONFIG), this.metrics, time, "producer", metricTags, channelBuilder),                     this.metadata,                     clientId,                     config.getInt(ProducerConfig.MAX_IN_FLIGHT_REQUESTS_PER_CONNECTION),                     config.getLong(ProducerConfig.RECONNECT_BACKOFF_MS_CONFIG),                     config.getInt(ProducerConfig.SEND_BUFFER_CONFIG),                     config.getInt(ProducerConfig.RECEIVE_BUFFER_CONFIG),                 this.sender = new Sender(client,  //构造一个sender。sender本身实现的是Runnable接口                     this.metadata,                     this.accumulator,                     config.getInt(ProducerConfig.MAX_REQUEST_SIZE_CONFIG),                     (short) parseAcks(config.getString(ProducerConfig.ACKS_CONFIG)),                     config.getInt(ProducerConfig.RETRIES_CONFIG),                     this.metrics,                     new SystemTime(),                     clientId,                     this.requestTimeoutMs);               String ioThreadName = "kafka-producer-network-thread" + (clientId.length() > 0 ? " | " + clientId : "");             this.ioThread = new KafkaThread(ioThreadName, this.sender, true);             this.ioThread.start();  //一个线程，开启sender

 

Sender poll()更新Metadata

 

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public void run() {         // main loop, runs until close is called         while (running) {             try {                 run(time.milliseconds());             } catch (Exception e) {                 log.error("Uncaught error in kafka producer I/O thread: ", e);             }         }        。。。     }       public void run(long now) {         Cluster cluster = metadata.fetch(); 。。。         RecordAccumulator.ReadyCheckResult result = this.accumulator.ready(cluster, now);   //遍历消息队列中所有的消息，找出对应的，已经ready的Node           if (result.unknownLeadersExist)  //如果一个ready的node都没有，请求更新metadata             this.metadata.requestUpdate();     。。。        //client的2个关键函数，一个发送ClientRequest，一个接收ClientResponse。底层调用的是NIO的poll。关于nio, 后面会详细介绍         for (ClientRequest request : requests)             client.send(request, now);           this.client.poll(pollTimeout, now);     }   //NetworkClient     public List<ClientResponse> poll(long timeout, long now) {         long metadataTimeout = metadataUpdater.maybeUpdate(now); //关键点：每次poll的时候判断是否要更新metadata           try {             this.selector.poll(Utils.min(timeout, metadataTimeout, requestTimeoutMs));         } catch (IOException e) {             log.error("Unexpected error during I/O", e);         }           // process completed actions         long updatedNow = this.time.milliseconds();         List<ClientResponse> responses = new ArrayList<>();         handleCompletedSends(responses, updatedNow);         handleCompletedReceives(responses, updatedNow);   //在返回的handler中，会处理metadata的更新         handleDisconnections(responses, updatedNow);         handleConnections();         handleTimedOutRequests(responses, updatedNow);           // invoke callbacks         for (ClientResponse response : responses) {             if (response.request().hasCallback()) {                 try {                     response.request().callback().onComplete(response);                 } catch (Exception e) {                     log.error("Uncaught error in request completion:", e);                 }             }         }           return responses;     }    //DefaultMetadataUpdater          @Override         public long maybeUpdate(long now) {             // should we update our metadata?             long timeToNextMetadataUpdate = metadata.timeToNextUpdate(now);             long timeToNextReconnectAttempt = Math.max(this.lastNoNodeAvailableMs + metadata.refreshBackoff() - now, 0);             long waitForMetadataFetch = this.metadataFetchInProgress ? Integer.MAX_VALUE : 0;             // if there is no node available to connect, back off refreshing metadata             long metadataTimeout = Math.max(Math.max(timeToNextMetadataUpdate, timeToNextReconnectAttempt),                     waitForMetadataFetch);               if (metadataTimeout == 0) {                 // highly dependent on the behavior of leastLoadedNode.                 Node node = leastLoadedNode(now);  //找到负载最小的Node                 maybeUpdate(now, node); //把更新Metadata的请求，发给这个Node             }               return metadataTimeout;         }           private void maybeUpdate(long now, Node node) {             if (node == null) {                 log.debug("Give up sending metadata request since no node is available");                 // mark the timestamp for no node available to connect                 this.lastNoNodeAvailableMs = now;                 return;             }             String nodeConnectionId = node.idString();               if (canSendRequest(nodeConnectionId)) {                 Set<String> topics = metadata.needMetadataForAllTopics() ? new HashSet<String>() : metadata.topics();                 this.metadataFetchInProgress = true;                 ClientRequest metadataRequest = request(now, nodeConnectionId, topics);  //关键点：发送更新Metadata的Request                 log.debug("Sending metadata request {} to node {}", metadataRequest, node.id());                 doSend(metadataRequest, now); //这里只是异步发送，返回的response在上面的handleCompletedReceives里面处理             } else if (connectionStates.canConnect(nodeConnectionId, now)) {                 log.debug("Initialize connection to node {} for sending metadata request", node.id());                 initiateConnect(node, now);               } else { // connected, but can't send more OR connecting                 this.lastNoNodeAvailableMs = now;             }         }        private void handleCompletedReceives(List<ClientResponse> responses, long now) {         for (NetworkReceive receive : this.selector.completedReceives()) {             String source = receive.source();             ClientRequest req = inFlightRequests.completeNext(source);             ResponseHeader header = ResponseHeader.parse(receive.payload());             // Always expect the response version id to be the same as the request version id             short apiKey = req.request().header().apiKey();             short apiVer = req.request().header().apiVersion();             Struct body = (Struct) ProtoUtils.responseSchema(apiKey, apiVer).read(receive.payload());             correlate(req.request().header(), header);             if (!metadataUpdater.maybeHandleCompletedReceive(req, now, body))                 responses.add(new ClientResponse(req, now, false, body));         }     }             @Override         public boolean maybeHandleCompletedReceive(ClientRequest req, long now, Struct body) {             short apiKey = req.request().header().apiKey();             if (apiKey == ApiKeys.METADATA.id && req.isInitiatedByNetworkClient()) {                 handleResponse(req.request().header(), body, now);                 return true;             }             return false;         }   //关键函数         private void handleResponse(RequestHeader header, Struct body, long now) {             this.metadataFetchInProgress = false;             MetadataResponse response = new MetadataResponse(body);             Cluster cluster = response.cluster();   //从response中，拿到一个新的cluster对象             if (response.errors().size() > 0) {                 log.warn("Error while fetching metadata with correlation id {} : {}", header.correlationId(), response.errors());             }               if (cluster.nodes().size() > 0) {                 this.metadata.update(cluster, now);   //更新metadata，用新的cluster覆盖旧的cluster             } else {                 log.trace("Ignoring empty metadata response with correlation id {}.", header.correlationId());                 this.metadata.failedUpdate(now);  //更新metadata失败，做失败处理逻辑             }         }     //更新成功，version+1, 同时更新其它字段     public synchronized void update(Cluster cluster, long now) {         this.needUpdate = false;         this.lastRefreshMs = now;         this.lastSuccessfulRefreshMs = now;         this.version += 1;           for (Listener listener: listeners)             listener.onMetadataUpdate(cluster);  //如果有人监听了metadata的更新，通知他们           this.cluster = this.needMetadataForAllTopics ? getClusterForCurrentTopics(cluster) : cluster;    //新的cluster覆盖旧的cluster           notifyAll();  //通知所有的阻塞的producer线程           log.debug("Updated cluster metadata version {} to {}", this.version, this.cluster);     }   //更新失败，只更新lastRefreshMs     public synchronized void failedUpdate(long now) {         this.lastRefreshMs = now;     }

 

从上面可以看出，Metadata的更新，是在while循环，每次调用client.poll()的时候更新的。

更新机制又有以下2种：

 

Metadata的2种更新机制

 

(1)周期性的更新: 每隔一段时间更新一次，这个通过 Metadata的lastRefreshMs, lastSuccessfulRefreshMs 这2个字段来实现

对应的ProducerConfig配置项为：

metadata.max.age.ms //缺省300000，即10分钟1次

(2) 失效检测，强制更新：检查到metadata失效以后，调用metadata.requestUpdate()强制更新。 requestUpdate()函数里面其实什么都没做，就是把needUpdate置成了false

每次poll的时候，都检查这2种更新机制，达到了，就触发更新。

那如何判定Metadata失效了呢？这个在代码中很分散，有很多地方，会判定Metadata失效。

 

Metadata失效检测

 

条件1：initConnect的时候

 

 

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private void initiateConnect(Node node, long now) {       String nodeConnectionId = node.idString();       try {           log.debug("Initiating connection to node {} at {}:{}.", node.id(), node.host(), node.port());           this.connectionStates.connecting(nodeConnectionId, now);           selector.connect(nodeConnectionId,                            new InetSocketAddress(node.host(), node.port()),                            this.socketSendBuffer,                            this.socketReceiveBuffer);       } catch (IOException e) {           connectionStates.disconnected(nodeConnectionId, now);           metadataUpdater.requestUpdate(); //判定metadata失效           log.debug("Error connecting to node {} at {}:{}:", node.id(), node.host(), node.port(), e);       }   }

 

条件2：poll里面IO的时候，连接断掉了

 

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private void handleDisconnections(List<ClientResponse> responses, long now) {      for (String node : this.selector.disconnected()) {          log.debug("Node {} disconnected.", node);          processDisconnection(responses, node, now);      }      if (this.selector.disconnected().size() > 0)          metadataUpdater.requestUpdate();  //判定metadata失效  }

 

条件3：有请求超时

 

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private void handleTimedOutRequests(List<ClientResponse> responses, long now) {        List<String> nodeIds = this.inFlightRequests.getNodesWithTimedOutRequests(now, this.requestTimeoutMs);        for (String nodeId : nodeIds) {            this.selector.close(nodeId);            log.debug("Disconnecting from node {} due to request timeout.", nodeId);            processDisconnection(responses, nodeId, now);        }          if (nodeIds.size() > 0)            metadataUpdater.requestUpdate();  //判定metadata失效    }

 

条件4：发消息的时候，有partition的leader没找到

 

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public void run(long now) {         Cluster cluster = metadata.fetch();         RecordAccumulator.ReadyCheckResult result = this.accumulator.ready(cluster, now);           if (result.unknownLeadersExist)             this.metadata.requestUpdate();

 

条件5：返回的response和请求对不上的时候

 

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private void handleProduceResponse(ClientResponse response, Map<TopicPartition, RecordBatch> batches, long now) {        int correlationId = response.request().request().header().correlationId();        if (response.wasDisconnected()) {            log.trace("Cancelled request {} due to node {} being disconnected", response, response.request()                                                                                                  .request()                                                                                                  .destination());            for (RecordBatch batch : batches.values())                completeBatch(batch, Errors.NETWORK_EXCEPTION, -1L, correlationId, now);

 

总之1句话：发生各式各样的异常，数据不同步，都认为metadata可能出问题了，要求更新。

 

Metadata其他的更新策略

 

除了上面所述，Metadata的更新，还有以下几个特点：

1.更新请求MetadataRequest是nio异步发送的，在poll的返回中，处理MetadataResponse的时候，才真正更新Metadata。

这里有个关键点：Metadata的cluster对象，每次是整个覆盖的，而不是局部更新。所以cluster内部不用加锁。

2.更新的时候，是从metadata保存的所有Node，或者说Broker中，选负载最小的那个，也就是当前接收请求最少的那个。向其发送MetadataRequest请求，获取新的Cluster对象。

 

文章转自About云(http://www.aboutyun.com/thread-19917-1-1.html)，原文位于csdn，作者：travi