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kafka源码调试 mac kafka源码剖析

在上一篇,我们从使用方式和策略上,对消息队列做了一个宏观描述。从本篇开始,我们将深入到源码内部,仔细分析Kafka到底是如何实现一个分布式消息队列。我们的分析将从Producer端开始。

从Kafka 0.8.2开始,发布了一套新的Java版的client api, KafkaProducer/KafkaConsumer,替代之前的scala版的api。本系列的分析将只针对这套Java版的api。

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: 

kafka源码调试 mac kafka源码剖析,kafka源码调试 mac kafka源码剖析_数据结构与算法,第1张

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:


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
     {     ...
     }
}1234567

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:


public final class Metadata {
  。。。    public synchronized Cluster fetch() {        return this.cluster;
    }    public synchronized long timeToNextUpdate(long nowMs) {
       。。。
    }    public synchronized int requestUpdate() {
      。。。
    }
    。。。    
}12345678910111213

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。

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;
}123456789101112131415161718192021222324252627282930


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

//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;
        }
    }12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152


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.


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metadatathis.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sender12345678910111213

1415161718192021222324252627282930313233



Sender poll()更新Metadata

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;
    }123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172


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

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);
        }
    }123456789101112131415

条件2:poll里面IO的时候,连接断掉了


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
    }12345678



条件3:有请求超时

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
    }1234567891011


条件4:发消息的时候,有partition的leader没找到


public void run(long now) {
        Cluster cluster = metadata.fetch();
        RecordAccumulator.ReadyCheckResult result = this.accumulator.ready(cluster, now);        if (result.unknownLeadersExist)            this.metadata.requestUpdate();123456


条件5:返回的response和请求对不上的时候


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);12345678

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。


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