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我们知道kafka是基于TCP连接的。其并没有像很多中间件使用netty作为TCP服务器。而是自己基于Java NIO写了一套。
先看下Kafka Client的网络层架构。
本文主要分析的是Network层。
Network层有两个重要的类：Selector和KafkaChannel。
这两个类和Java NIO层的java.nio.channels.Selector和Channel有点类似。
Selector几个关键字段如下
// jdk nio中的Selector java.nio.channels.Selector nioSelector; // 记录当前Selector的所有连接信息 Map<String, KafkaChannel> channels; // 已发送完成的请求 List<Send> completedSends; // 已收到的请求 List<NetworkReceive> completedReceives; // 还没有完全收到的请求,对上层不可见 Map<KafkaChannel, Deque<NetworkReceive>> stagedReceives; // 作为client端，调用connect连接远端时返回true的连接 Set<SelectionKey> immediatelyConnectedKeys; // 已经完成的连接 List<String> connected; // 一次读取的最大大小 int maxReceiveSize;
从网络层来看kafka是分为client端（producer和consumer，broker作为从时也是client）和server端（broker）的。本文将分析client端是如何建立连接，以及收发数据的。server也是依靠Selector和KafkaChannel进行网络传输。在Network层两端的区别并不大。
kafka的client端启动时会调用Selector#connect（下文中如无特殊注明，均指org.apache.kafka.common.network.Selector）方法建立连接。
public void connect(String id, InetSocketAddress address, int sendBufferSize, int receiveBufferSize) throws IOException {
if (this.channels.containsKey(id))
throw new IllegalStateException("There is already a connection for id " + id);
// 创建一个SocketChannel
SocketChannel socketChannel = SocketChannel.open();
// 设置为非阻塞模式
socketChannel.configureBlocking(false);
// 创建socket并设置相关属性
Socket socket = socketChannel.socket();
socket.setKeepAlive(true);
if (sendBufferSize != Selectable.USE_DEFAULT_BUFFER_SIZE)
socket.setSendBufferSize(sendBufferSize);
if (receiveBufferSize != Selectable.USE_DEFAULT_BUFFER_SIZE)
socket.setReceiveBufferSize(receiveBufferSize);
socket.setTcpNoDelay(true);
boolean connected;
try {
// 调用SocketChannel的connect方法，该方法会向远端发起tcp建连请求
// 因为是非阻塞的，所以该方法返回时，连接不一定已经建立好（即完成3次握手）。连接如果已经建立好则返回true，否则返回false。一般来说server和client在一台机器上，该方法可能返回true。
connected = socketChannel.connect(address);
} catch (UnresolvedAddressException e) {
socketChannel.close();
throw new IOException("Can't resolve address: " + address, e);
} catch (IOException e) {
socketChannel.close();
throw e;
}
// 对CONNECT事件进行注册
SelectionKey key = socketChannel.register(nioSelector, SelectionKey.OP_CONNECT);
KafkaChannel channel;
try {
// 构造一个KafkaChannel
channel = channelBuilder.buildChannel(id, key, maxReceiveSize);
} catch (Exception e) {
...
}
// 将kafkachannel绑定到SelectionKey上
key.attach(channel);
// 放入到map中，id是远端服务器的名称
this.channels.put(id, channel);
// connectct为true代表该连接不会再触发CONNECT事件，所以这里要单独处理
if (connected) {
// OP_CONNECT won't trigger for immediately connected channels
log.debug("Immediately connected to node {}", channel.id());
// 加入到一个单独的集合中
immediatelyConnectedKeys.add(key);
// 取消对该连接的CONNECT事件的监听
key.interestOps(0);
}
}这里的流程和标准的NIO流程差不多，需要单独说下的是socketChannel#connect方法返回true的场景，该方法的注释中有提到
* <p> If this channel is in non-blocking mode then an invocation of this
* method initiates a non-blocking connection operation. If the connection
* is established immediately, as can happen with a local connection, then
* this method returns <tt>true</tt>. Otherwise this method returns
* <tt>false</tt> and the connection operation must later be completed by
* invoking the {@link #finishConnect finishConnect} method.也就是说在非阻塞模式下，对于local connection，连接可能在马上就建立好了，那该方法会返回true，对于这种情况，不会再触发之后的connect事件。因此kafka用一个单独的集合immediatelyConnectedKeys将这些特殊的连接记录下来。在接下来的步骤会进行特殊处理。
之后会调用poll方法对网络事件监听：
public void poll(long timeout) throws IOException {
...
// select方法是对java.nio.channels.Selector#select的一个简单封装
int readyKeys = select(timeout);
...
// 如果有就绪的事件或者immediatelyConnectedKeys非空
if (readyKeys > 0 || !immediatelyConnectedKeys.isEmpty()) {
// 对已就绪的事件进行处理，第2个参数为false
pollSelectionKeys(this.nioSelector.selectedKeys(), false, endSelect);
// 对immediatelyConnectedKeys进行处理。第2个参数为true
pollSelectionKeys(immediatelyConnectedKeys, true, endSelect);
}
addToCompletedReceives();
...
}
private void pollSelectionKeys(Iterable<SelectionKey> selectionKeys,
boolean isImmediatelyConnected,
long currentTimeNanos) {
Iterator<SelectionKey> iterator = selectionKeys.iterator();
// 遍历集合
while (iterator.hasNext()) {
SelectionKey key = iterator.next();
// 移除当前元素，要不然下次poll又会处理一遍
iterator.remove();
// 得到connect时创建的KafkaChannel
KafkaChannel channel = channel(key);
...
try {
// 如果当前处理的是immediatelyConnectedKeys集合的元素或处理的是CONNECT事件
if (isImmediatelyConnected || key.isConnectable()) {
// finishconnect中会增加READ事件的监听
if (channel.finishConnect()) {
this.connected.add(channel.id());
this.sensors.connectionCreated.record();
...
} else
continue;
}
// 对于ssl的连接还有些额外的步骤
if (channel.isConnected() && !channel.ready())
channel.prepare();
// 如果是READ事件
if (channel.ready() && key.isReadable() && !hasStagedReceive(channel)) {
NetworkReceive networkReceive;
while ((networkReceive = channel.read()) != null)
addToStagedReceives(channel, networkReceive);
}
// 如果是WRITE事件
if (channel.ready() && key.isWritable()) {
Send send = channel.write();
if (send != null) {
this.completedSends.add(send);
this.sensors.recordBytesSent(channel.id(), send.size());
}
}
// 如果连接失效
if (!key.isValid())
close(channel, true);
} catch (Exception e) {
String desc = channel.socketDescription();
if (e instanceof IOException)
log.debug("Connection with {} disconnected", desc, e);
else
log.warn("Unexpected error from {}; closing connection", desc, e);
close(channel, true);
} finally {
maybeRecordTimePerConnection(channel, channelStartTimeNanos);
}
}
}因为immediatelyConnectedKeys中的连接不会触发CONNNECT事件，所以在poll时会单独对immediatelyConnectedKeys的channel调用finishConnect方法。在明文传输模式下该方法会调用到PlaintextTransportLayer#finishConnect，其实现如下：
public boolean finishConnect() throws IOException {
// 返回true代表已经连接好了
boolean connected = socketChannel.finishConnect();
if (connected)
// 取消监听CONNECt事件，增加READ事件的监听
key.interestOps(key.interestOps() & ~SelectionKey.OP_CONNECT | SelectionKey.OP_READ);
return connected;
}关于immediatelyConnectedKeys更详细的内容可以看看这里。
kafka发送数据分为两个步骤：
1.调用Selector#send将要发送的数据保存在对应的KafkaChannel中，该方法并没有进行真正的网络IO。
// Selector#send
public void send(Send send) {
String connectionId = send.destination();
// 如果所在的连接正在关闭中，则加入到失败集合failedSends中
if (closingChannels.containsKey(connectionId))
this.failedSends.add(connectionId);
else {
KafkaChannel channel = channelOrFail(connectionId, false);
try {
channel.setSend(send);
} catch (CancelledKeyException e) {
this.failedSends.add(connectionId);
close(channel, false);
}
}
}
//KafkaChannel#setSend
public void setSend(Send send) {
// 如果还有数据没有发送出去则报错
if (this.send != null)
throw new IllegalStateException("Attempt to begin a send operation with prior send operation still in progress.");
// 保存下来
this.send = send;
// 添加对WRITE事件的监听
this.transportLayer.addInterestOps(SelectionKey.OP_WRITE);
}调用Selector#poll，在第一步中已经对该channel注册了WRITE事件的监听，所以在当channel可写时,会调用到pollSelectionKeys将数据真正的发送出去。
private void pollSelectionKeys(Iterable<SelectionKey> selectionKeys,
boolean isImmediatelyConnected,
long currentTimeNanos) {
Iterator<SelectionKey> iterator = selectionKeys.iterator();
// 遍历集合
while (iterator.hasNext()) {
SelectionKey key = iterator.next();
// 移除当前元素，要不然下次poll又会处理一遍
iterator.remove();
// 得到connect时创建的KafkaChannel
KafkaChannel channel = channel(key);
...
try {
...
// 如果是WRITE事件
if (channel.ready() && key.isWritable()) {
// 真正的网络写
Send send = channel.write();
// 一个Send对象可能会被拆成几次发送，write非空代表一个send发送完成
if (send != null) {
// completedSends代表已发送完成的集合
this.completedSends.add(send);
this.sensors.recordBytesSent(channel.id(), send.size());
}
}
...
} catch (Exception e) {
...
} finally {
maybeRecordTimePerConnection(channel, channelStartTimeNanos);
}
}
}当可写时，会调用KafkaChannel#write方法，该方法中会进行真正的网络IO：
public Send write() throws IOException {
Send result = null;
if (send != null && send(send)) {
result = send;
send = null;
}
return result;
}
private boolean send(Send send) throws IOException {
// 最终调用SocketChannel#write进行真正的写
send.writeTo(transportLayer);
if (send.completed())
// 如果写完了，则移除对WRITE事件的监听
transportLayer.removeInterestOps(SelectionKey.OP_WRITE);
return send.completed();
}如果远端有发送数据过来，那调用poll方法时，会对接收到的数据进行处理。
public void poll(long timeout) throws IOException {
...
// select方法是对java.nio.channels.Selector#select的一个简单封装
int readyKeys = select(timeout);
...
// 如果有就绪的事件或者immediatelyConnectedKeys非空
if (readyKeys > 0 || !immediatelyConnectedKeys.isEmpty()) {
// 对已就绪的事件进行处理，第2个参数为false
pollSelectionKeys(this.nioSelector.selectedKeys(), false, endSelect);
// 对immediatelyConnectedKeys进行处理。第2个参数为true
pollSelectionKeys(immediatelyConnectedKeys, true, endSelect);
}
addToCompletedReceives();
...
}
private void pollSelectionKeys(Iterable<SelectionKey> selectionKeys,
boolean isImmediatelyConnected,
long currentTimeNanos) {
Iterator<SelectionKey> iterator = selectionKeys.iterator();
// 遍历集合
while (iterator.hasNext()) {
SelectionKey key = iterator.next();
// 移除当前元素，要不然下次poll又会处理一遍
iterator.remove();
// 得到connect时创建的KafkaChannel
KafkaChannel channel = channel(key);
...
try {
...
// 如果是READ事件
if (channel.ready() && key.isReadable() && !hasStagedReceive(channel)) {
NetworkReceive networkReceive;
// read方法会从网络中读取数据，但可能一次只能读取一个req的部分数据。只有读到一个完整的req的情况下，该方法才返回非null
while ((networkReceive = channel.read()) != null)
// 将读到的请求存在stagedReceives中
addToStagedReceives(channel, networkReceive);
}
...
} catch (Exception e) {
...
} finally {
maybeRecordTimePerConnection(channel, channelStartTimeNanos);
}
}
}
private void addToStagedReceives(KafkaChannel channel, NetworkReceive receive) {
if (!stagedReceives.containsKey(channel))
stagedReceives.put(channel, new ArrayDeque<NetworkReceive>());
Deque<NetworkReceive> deque = stagedReceives.get(channel);
deque.add(receive);
}在之后的addToCompletedReceives方法中会对该集合进行处理。
private void addToCompletedReceives() {
if (!this.stagedReceives.isEmpty()) {
Iterator<Map.Entry<KafkaChannel, Deque<NetworkReceive>>> iter = this.stagedReceives.entrySet().iterator();
while (iter.hasNext()) {
Map.Entry<KafkaChannel, Deque<NetworkReceive>> entry = iter.next();
KafkaChannel channel = entry.getKey();
// 对于client端来说该isMute返回为false，server端则依靠该方法保证消息的顺序
if (!channel.isMute()) {
Deque<NetworkReceive> deque = entry.getValue();
addToCompletedReceives(channel, deque);
if (deque.isEmpty())
iter.remove();
}
}
}
}
private void addToCompletedReceives(KafkaChannel channel, Deque<NetworkReceive> stagedDeque) {
// 将每个channel的第一个NetworkReceive加入到completedReceives
NetworkReceive networkReceive = stagedDeque.poll();
this.completedReceives.add(networkReceive);
this.sensors.recordBytesReceived(channel.id(), networkReceive.payload().limit());
}读出数据后，会先放到stagedReceives集合中，然后在addToCompletedReceives方法中对于每个channel都会从stagedReceives取出一个NetworkReceive（如果有的话），放入到completedReceives中。
这样做的原因有两点：
对于SSL的连接来说，其数据内容是加密的，所以不能精准的确定本次需要读取的数据大小，只能尽可能的多读，这样会导致可能会比请求的数据读的要多。那如果该channel之后没有数据可以读，会导致多读的数据将不会被处理。
kafka需要确保一个channel上request被处理的顺序是其发送的顺序。因此对于每个channel而言，每次poll上层最多只能看见一个请求，当该请求处理完成之后，再处理其他的请求。在sever端，每次poll后都会将该channel给mute掉，即不再从该channel上读取数据。当处理完成之后，才将该channelunmute，即之后可以从该socket上读取数据。而client端则是通过InFlightRequests#canSendMore控制。
代码中关于这段逻辑的注释如下：
/* In the "Plaintext" setting, we are using socketChannel to read & write to the network. But for the "SSL" setting, * we encrypt the data before we use socketChannel to write data to the network, and decrypt before we return the responses. * This requires additional buffers to be maintained as we are reading from network, since the data on the wire is encrypted * we won't be able to read exact no.of bytes as kafka protocol requires. We read as many bytes as we can, up to SSLEngine's * application buffer size. This means we might be reading additional bytes than the requested size. * If there is no further data to read from socketChannel selector won't invoke that channel and we've have additional bytes * in the buffer. To overcome this issue we added "stagedReceives" map which contains per-channel deque. When we are * reading a channel we read as many responses as we can and store them into "stagedReceives" and pop one response during * the poll to add the completedReceives. If there are any active channels in the "stagedReceives" we set "timeout" to 0 * and pop response and add to the completedReceives. * Atmost one entry is added to "completedReceives" for a channel in each poll. This is necessary to guarantee that * requests from a channel are processed on the broker in the order they are sent. Since outstanding requests added * by SocketServer to the request queue may be processed by different request handler threads, requests on each * channel must be processed one-at-a-time to guarantee ordering. */
本文分析了kafka network层的实现，在阅读kafka源码时，如果不把network层搞清楚会比较迷，比如req/resp的顺序保障机制、真正进行网络IO的不是send方法等等。
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