Broker的HA策略分为两部分
①同步元数据
②同步消息数据
同步元数据
在Slave启动时，会启动一个定时任务用来从master同步元数据
if (role == BrokerRole.SLAVE) {
if (null != slaveSyncFuture) {
slaveSyncFuture.cancel(false);
}
this.slaveSynchronize.setMasterAddr(null);
slaveSyncFuture = this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
@Override
public void run() {
try {
BrokerController.this.slaveSynchronize.syncAll();
}
catch (Throwable e) {
log.error("ScheduledTask SlaveSynchronize syncAll error.", e);
}
}
}, 1000 * 3, 1000 * 10, TimeUnit.MILLISECONDS);
}
这里设置了定时任务，执行slaveSynchronize的syncAll方法
可以注意在之前会通过setMasterAddr将Master的地址设为null，这是由于在后面会通过另一个定时任务registerBrokerAll来向NameServer获取Master的地址，详见：
SlaveSynchronize的syncAll方法：
public void syncAll() {
this.syncTopicConfig();
this.syncConsumerOffset();
this.syncDelayOffset();
this.syncSubscriptionGroupConfig();
}
这个方法会依次调用四个方法，来同步相应信息：
syncTopicConfig：同步topic的配置信息
syncConsumerOffset：同步Consumer的Offset信息
syncDelayOffset：同步延迟队列信息
syncSubscriptionGroupConfig：同步订阅信息
由于这几个方法的实现是类似的，这里就只看下syncTopicConfig的实现：
syncTopicConfig方法：
private void syncTopicConfig() {
String masterAddrBak = this.masterAddr;
if (masterAddrBak != null && !masterAddrBak.equals(brokerController.getBrokerAddr())) {
try {
TopicConfigSerializeWrapper topicWrapper =
this.brokerController.getBrokerOuterAPI().getAllTopicConfig(masterAddrBak);
if (!this.brokerController.getTopicConfigManager().getDataVersion()
.equals(topicWrapper.getDataVersion())) { this.brokerController.getTopicConfigManager().getDataVersion()
.assignNewOne(topicWrapper.getDataVersion());
this.brokerController.getTopicConfigManager().getTopicConfigTable().clear();
this.brokerController.getTopicConfigManager().getTopicConfigTable()
.putAll(topicWrapper.getTopicConfigTable());
this.brokerController.getTopicConfigManager().persist(); log.info("Update slave topic config from master, {}", masterAddrBak);
}
} catch (Exception e) {
log.error("SyncTopicConfig Exception, {}", masterAddrBak, e);
}
}
}
这里首先获取master的地址masterAddr，由于registerBrokerAll定时任务的存在，即便这一次没有获取到masterAddr，只要节点中有master，总会在后面定时执行时从NameServer中获取到
当获取到master地址后，通过BrokerOuterAPI的getAllTopicConfig方法，向master请求
BrokerOuterAPI的getAllTopicConfig方法：
public TopicConfigSerializeWrapper getAllTopicConfig(
final String addr) throws RemotingConnectException, RemotingSendRequestException,
RemotingTimeoutException, InterruptedException, MQBrokerException {
RemotingCommand request = RemotingCommand.createRequestCommand(RequestCode.GET_ALL_TOPIC_CONFIG, null); RemotingCommand response = this.remotingClient.invokeSync(MixAll.brokerVIPChannel(true, addr), request, 3000);
assert response != null;
switch (response.getCode()) {
case ResponseCode.SUCCESS: {
return TopicConfigSerializeWrapper.decode(response.getBody(), TopicConfigSerializeWrapper.class);
}
default:
break;
} throw new MQBrokerException(response.getCode(), response.getRemark());
}
首先构建GET_ALL_TOPIC_CONFIG求情指令，然后通过remotingClient的invokeSync进行同步发送，注意这里会通过MixAll的brokerVIPChannel方法，得到对应的master地址的VIP通道地址，就是端口号减2，这在我之前的博客中介绍过
有关同步发送在 【RocketMQ中Producer消息的发送源码分析】 中详细介绍过
请求发送给master后，来看看master是怎么处理的
master端在收到请求后会通过AdminBrokerProcessor的processRequest方法判别请求指令：
case RequestCode.GET_ALL_TOPIC_CONFIG:
return this.getAllTopicConfig(ctx, request);
执行getAllTopicConfig方法：
private RemotingCommand getAllTopicConfig(ChannelHandlerContext ctx, RemotingCommand request) {
final RemotingCommand response = RemotingCommand.createResponseCommand(GetAllTopicConfigResponseHeader.class);
// final GetAllTopicConfigResponseHeader responseHeader =
// (GetAllTopicConfigResponseHeader) response.readCustomHeader(); String content = this.brokerController.getTopicConfigManager().encode();
if (content != null && content.length() > 0) {
try {
response.setBody(content.getBytes(MixAll.DEFAULT_CHARSET));
} catch (UnsupportedEncodingException e) {
log.error("", e); response.setCode(ResponseCode.SYSTEM_ERROR);
response.setRemark("UnsupportedEncodingException " + e);
return response;
}
} else {
log.error("No topic in this broker, client: {}", ctx.channel().remoteAddress());
response.setCode(ResponseCode.SYSTEM_ERROR);
response.setRemark("No topic in this broker");
return response;
} response.setCode(ResponseCode.SUCCESS);
response.setRemark(null); return response;
}
这里会将TopicConfigManager中保存的topicConfigTable：
private final ConcurrentMap<String, TopicConfig> topicConfigTable =
new ConcurrentHashMap<String, TopicConfig>(1024);
将这个map通过encode方法转换成json字符串，再通过Netty发送给slave
回到slave中，在同步发送的情况下，会等待会送响应，收到响应后：
switch (response.getCode()) {
case ResponseCode.SUCCESS: {
return TopicConfigSerializeWrapper.decode(response.getBody(), TopicConfigSerializeWrapper.class);
}
default:
break;
}
通过decode解码，将json字符串转换为map封装在 TopicConfigSerializeWrapper中
回到syncTopicConfig方法中：
得到TopicConfigSerializeWrapper实例后
if (!this.brokerController.getTopicConfigManager().getDataVersion()
.equals(topicWrapper.getDataVersion())) { this.brokerController.getTopicConfigManager().getDataVersion()
.assignNewOne(topicWrapper.getDataVersion());
this.brokerController.getTopicConfigManager().getTopicConfigTable().clear();
this.brokerController.getTopicConfigManager().getTopicConfigTable()
.putAll(topicWrapper.getTopicConfigTable());
this.brokerController.getTopicConfigManager().persist(); log.info("Update slave topic config from master, {}", masterAddrBak);
}
判断版本是否一致，若不一致，会进行替换，这样slave的Topic配置信息就和master保持同步了
其他三种信息的同步同理
同步消息数据
在master启动时，会通过JDK的NIO方式启动一个HA服务线程，用以处理slave的连接：
public void run() {
log.info(this.getServiceName() + " service started"); while (!this.isStopped()) {
try {
this.selector.select(1000);
Set<SelectionKey> selected = this.selector.selectedKeys(); if (selected != null) {
for (SelectionKey k : selected) {
if ((k.readyOps() & SelectionKey.OP_ACCEPT) != 0) {
SocketChannel sc = ((ServerSocketChannel) k.channel()).accept(); if (sc != null) {
HAService.log.info("HAService receive new connection, "
+ sc.socket().getRemoteSocketAddress()); try {
HAConnection conn = new HAConnection(HAService.this, sc);
conn.start();
HAService.this.addConnection(conn);
} catch (Exception e) {
log.error("new HAConnection exception", e);
sc.close();
}
}
} else {
log.warn("Unexpected ops in select " + k.readyOps());
}
} selected.clear();
}
} catch (Exception e) {
log.error(this.getServiceName() + " service has exception.", e);
}
} log.info(this.getServiceName() + " service end");
}
这里就是非常典型的JDK NIO的使用，在侦听到连接取得SocketChannel后，将其封装为HAConnection
public HAConnection(final HAService haService, final SocketChannel socketChannel) throws IOException {
this.haService = haService;
this.socketChannel = socketChannel;
this.clientAddr = this.socketChannel.socket().getRemoteSocketAddress().toString();
this.socketChannel.configureBlocking(false);
this.socketChannel.socket().setSoLinger(false, -1);
this.socketChannel.socket().setTcpNoDelay(true);
this.socketChannel.socket().setReceiveBufferSize(1024 * 64);
this.socketChannel.socket().setSendBufferSize(1024 * 64);
this.writeSocketService = new WriteSocketService(this.socketChannel);
this.readSocketService = new ReadSocketService(this.socketChannel);
this.haService.getConnectionCount().incrementAndGet();
}
在构造方法内进行了对socketChannel的一些配置，还创建了一个WriteSocketService和一个ReadSocketService，这两个是后续处理消息同步的基础
在创建完HAConnection后，调用其start方法：
public void start() {
this.readSocketService.start();
this.writeSocketService.start();
}
这里会启动两个线程，分别处理读取slave发送的数据，以及向slave发送数据
到这里，先不急着分析master了，来看看slave端
slave在启动时，会启动HAClient的线程：
public void run() {
log.info(this.getServiceName() + " service started"); while (!this.isStopped()) {
try {
if (this.connectMaster()) { if (this.isTimeToReportOffset()) {
boolean result = this.reportSlaveMaxOffset(this.currentReportedOffset);
if (!result) {
this.closeMaster();
}
} this.selector.select(1000); boolean ok = this.processReadEvent();
if (!ok) {
this.closeMaster();
} if (!reportSlaveMaxOffsetPlus()) {
continue;
} long interval =
HAService.this.getDefaultMessageStore().getSystemClock().now()
- this.lastWriteTimestamp;
if (interval > HAService.this.getDefaultMessageStore().getMessageStoreConfig()
.getHaHousekeepingInterval()) {
log.warn("HAClient, housekeeping, found this connection[" + this.masterAddress
+ "] expired, " + interval);
this.closeMaster();
log.warn("HAClient, master not response some time, so close connection");
}
} else {
this.waitForRunning(1000 * 5);
}
} catch (Exception e) {
log.warn(this.getServiceName() + " service has exception. ", e);
this.waitForRunning(1000 * 5);
}
} log.info(this.getServiceName() + " service end");
}
在这个while循环中，首先通过connectMaster检查是否和master连接了
connectMaster方法：
private boolean connectMaster() throws ClosedChannelException {
if (null == socketChannel) {
String addr = this.masterAddress.get();
if (addr != null) { SocketAddress socketAddress = RemotingUtil.string2SocketAddress(addr);
if (socketAddress != null) {
this.socketChannel = RemotingUtil.connect(socketAddress);
if (this.socketChannel != null) {
this.socketChannel.register(this.selector, SelectionKey.OP_READ);
}
}
} this.currentReportedOffset = HAService.this.defaultMessageStore.getMaxPhyOffset(); this.lastWriteTimestamp = System.currentTimeMillis();
} return this.socketChannel != null;
}
若是socketChannel为null，意味着并没有产生连接，或者连接断开
需要重新根据masterAddress建立网络连接
只要是需要建立连接，都需要通过defaultMessageStore的getMaxPhyOffset方法，获取本地最大的Offset，由currentReportedOffset保存，后续用于向master报告；以及保存了一个时间戳lastWriteTimestamp，用于之后的校对
当确保与master的连接建立成功后，通过isTimeToReportOffset方法，检查是否需要向master报告当前的最大Offset
isTimeToReportOffset方法：
private boolean isTimeToReportOffset() {
long interval =
HAService.this.defaultMessageStore.getSystemClock().now() - this.lastWriteTimestamp;
boolean needHeart = interval > HAService.this.defaultMessageStore.getMessageStoreConfig()
.getHaSendHeartbeatInterval(); return needHeart;
}
这里就通过lastWriteTimestamp和当前时间检查，判断是否达到了报告时间间隔HaSendHeartbeatInterval，默认5s
若是达到了，就需要通过reportSlaveMaxOffset方法，将记录的currentReportedOffset这个最大的offset发送给master
reportSlaveMaxOffset方法：
private boolean reportSlaveMaxOffset(final long maxOffset) {
this.reportOffset.position(0);
this.reportOffset.limit(8);
this.reportOffset.putLong(maxOffset);
this.reportOffset.position(0);
this.reportOffset.limit(8); for (int i = 0; i < 3 && this.reportOffset.hasRemaining(); i++) {
try {
this.socketChannel.write(this.reportOffset);
} catch (IOException e) {
log.error(this.getServiceName()
+ "reportSlaveMaxOffset this.socketChannel.write exception", e);
return false;
}
} return !this.reportOffset.hasRemaining();
}
其中reportOffset是专门用来缓存offset的ByteBuffer
private final ByteBuffer reportOffset = ByteBuffer.allocate(8);
将maxOffset存放在reportOffset中，然后通过socketChannel的write方法，完成向master的发送
其中hasRemaining方法用来检查当前位置是否已经达到缓冲区极限limit，确保reportOffset 中的内容能被完全发送出去
发送成功后，会调用selector的select方法，在超时时间内进行NIO的轮询，等待master的回送
通过这我们可以看出slave在和master建立连接后，会定时向master报告自己当前的offset
来看看master收到offset后是如何处理的：
在master端会通过前面提到的ReadSocketService线程进行处理：
public void run() {
HAConnection.log.info(this.getServiceName() + " service started"); while (!this.isStopped()) {
try {
this.selector.select(1000);
boolean ok = this.processReadEvent();
if (!ok) {
HAConnection.log.error("processReadEvent error");
break;
} long interval = HAConnection.this.haService.getDefaultMessageStore().getSystemClock().now() - this.lastReadTimestamp;
if (interval > HAConnection.this.haService.getDefaultMessageStore().getMessageStoreConfig().getHaHousekeepingInterval()) {
log.warn("ha housekeeping, found this connection[" + HAConnection.this.clientAddr + "] expired, " + interval);
break;
}
} catch (Exception e) {
HAConnection.log.error(this.getServiceName() + " service has exception.", e);
break;
}
} this.makeStop(); writeSocketService.makeStop(); haService.removeConnection(HAConnection.this); HAConnection.this.haService.getConnectionCount().decrementAndGet(); SelectionKey sk = this.socketChannel.keyFor(this.selector);
if (sk != null) {
sk.cancel();
} try {
this.selector.close();
this.socketChannel.close();
} catch (IOException e) {
HAConnection.log.error("", e);
} HAConnection.log.info(this.getServiceName() + " service end");
}
这里的while循环中首先也是通过selector的select方法，在超时时间内进行NIO的轮询
轮询结束后的进一步的处理由processReadEvent来完成：
private boolean processReadEvent() {
int readSizeZeroTimes = 0; if (!this.byteBufferRead.hasRemaining()) {
this.byteBufferRead.flip();
this.processPostion = 0;
} while (this.byteBufferRead.hasRemaining()) {
try {
int readSize = this.socketChannel.read(this.byteBufferRead);
if (readSize > 0) {
readSizeZeroTimes = 0;
this.lastReadTimestamp = HAConnection.this.haService.getDefaultMessageStore().getSystemClock().now();
if ((this.byteBufferRead.position() - this.processPostion) >= 8) {
int pos = this.byteBufferRead.position() - (this.byteBufferRead.position() % 8);
long readOffset = this.byteBufferRead.getLong(pos - 8);
this.processPostion = pos; HAConnection.this.slaveAckOffset = readOffset;
if (HAConnection.this.slaveRequestOffset < 0) {
HAConnection.this.slaveRequestOffset = readOffset;
log.info("slave[" + HAConnection.this.clientAddr + "] request offset " + readOffset);
} HAConnection.this.haService.notifyTransferSome(HAConnection.this.slaveAckOffset);
}
} else if (readSize == 0) {
if (++readSizeZeroTimes >= 3) {
break;
}
} else {
log.error("read socket[" + HAConnection.this.clientAddr + "] < 0");
return false;
}
} catch (IOException e) {
log.error("processReadEvent exception", e);
return false;
}
} return true;
}
}
这个方法其实就是通过socketChannel的read方法，将slave发送过来的数据存入byteBufferRead中
在确保发送过来的数据能达到8字节时，取出long类型的offset值，然后交给HAConnection的slaveAckOffset成员进行保存
其中slaveRequestOffset是用来处理第一次连接时的同步
notifyTransferSome方法是作为同步master时，进行相应的唤醒操作，异步master则没有要求，在后面具体分析
也就是说ReadSocketService这个线程，只是不断地读取并更新slave发送来的offset数据
再来看看WriteSocketService线程是如何进行向slave的发送：
public void run() {
HAConnection.log.info(this.getServiceName() + " service started"); while (!this.isStopped()) {
try {
this.selector.select(1000); if (-1 == HAConnection.this.slaveRequestOffset) {
Thread.sleep(10);
continue;
} if (-1 == this.nextTransferFromWhere) {
if (0 == HAConnection.this.slaveRequestOffset) {
long masterOffset = HAConnection.this.haService.getDefaultMessageStore().getCommitLog().getMaxOffset();
masterOffset =
masterOffset
- (masterOffset % HAConnection.this.haService.getDefaultMessageStore().getMessageStoreConfig()
.getMapedFileSizeCommitLog()); if (masterOffset < 0) {
masterOffset = 0;
} this.nextTransferFromWhere = masterOffset;
} else {
this.nextTransferFromWhere = HAConnection.this.slaveRequestOffset;
} log.info("master transfer data from " + this.nextTransferFromWhere + " to slave[" + HAConnection.this.clientAddr
+ "], and slave request " + HAConnection.this.slaveRequestOffset);
} if (this.lastWriteOver) { long interval =
HAConnection.this.haService.getDefaultMessageStore().getSystemClock().now() - this.lastWriteTimestamp; if (interval > HAConnection.this.haService.getDefaultMessageStore().getMessageStoreConfig()
.getHaSendHeartbeatInterval()) { // Build Header
this.byteBufferHeader.position(0);
this.byteBufferHeader.limit(headerSize);
this.byteBufferHeader.putLong(this.nextTransferFromWhere);
this.byteBufferHeader.putInt(0);
this.byteBufferHeader.flip(); this.lastWriteOver = this.transferData();
if (!this.lastWriteOver)
continue;
}
} else {
this.lastWriteOver = this.transferData();
if (!this.lastWriteOver)
continue;
} SelectMappedBufferResult selectResult =
HAConnection.this.haService.getDefaultMessageStore().getCommitLogData(this.nextTransferFromWhere);
if (selectResult != null) {
int size = selectResult.getSize();
if (size > HAConnection.this.haService.getDefaultMessageStore().getMessageStoreConfig().getHaTransferBatchSize()) {
size = HAConnection.this.haService.getDefaultMessageStore().getMessageStoreConfig().getHaTransferBatchSize();
} long thisOffset = this.nextTransferFromWhere;
this.nextTransferFromWhere += size; selectResult.getByteBuffer().limit(size);
this.selectMappedBufferResult = selectResult; // Build Header
this.byteBufferHeader.position(0);
this.byteBufferHeader.limit(headerSize);
this.byteBufferHeader.putLong(thisOffset);
this.byteBufferHeader.putInt(size);
this.byteBufferHeader.flip(); this.lastWriteOver = this.transferData();
} else { HAConnection.this.haService.getWaitNotifyObject().allWaitForRunning(100);
}
} catch (Exception e) { HAConnection.log.error(this.getServiceName() + " service has exception.", e);
break;
}
} HAConnection.this.haService.getWaitNotifyObject().removeFromWaitingThreadTable(); if (this.selectMappedBufferResult != null) {
this.selectMappedBufferResult.release();
} this.makeStop(); readSocketService.makeStop(); haService.removeConnection(HAConnection.this); SelectionKey sk = this.socketChannel.keyFor(this.selector);
if (sk != null) {
sk.cancel();
} try {
this.selector.close();
this.socketChannel.close();
} catch (IOException e) {
HAConnection.log.error("", e);
} HAConnection.log.info(this.getServiceName() + " service end");
}
这里一开始会对slaveRequestOffset进行一次判断，当且仅当slaveRequestOffset初始化的时候是才是-1
也就是说当slave还没有发送过来offset时，WriteSocketService线程只会干等
当slave发送来offset后
首先对nextTransferFromWhere进行了判断，nextTransferFromWhere和slaveRequestOffset一样，在初始化的时候为-1
也就代表着master和slave刚刚建立连接，并没有进行过一次消息的同步！
此时会对修改了的slaveRequestOffset进行判断
若是等于0，说明slave没有任何消息的历史记录，那么此时master会取得自身的MaxOffset，根据这个MaxOffset，通过：
masterOffset = masterOffset
- (masterOffset % HAConnection.this.haService.getDefaultMessageStore().getMessageStoreConfig()
.getMapedFileSizeCommitLog() /* 1G */);
计算出最后一个文件开始的offset
也就是说，当slave没有消息的历史记录，master只会从本地最后一个CommitLog文件开始的地方，将消息数据发送给slave
若是slave有数据，就从slave发送来的offset的位置起，进行发送，通过nextTransferFromWhere记录这个offset值
接着对lastWriteOver进行了判断，lastWriteOver是一个状态量，用来表示上次发送是否传输完毕，初始化是true
若是true，这里会进行一次时间检查，lastWriteTimestamp记录最后一次发送的时间
一次来判断是否超过了时间间隔haSendHeartbeatInterval（默认5s）
也就是说至少有5s，master没有向slave发送任何消息
那么此时就会发送一个心跳包
其中byteBufferHeader是一个12字节的ByteBuffer：
private final int headerSize = 8 + 4;
private final ByteBuffer byteBufferHeader = ByteBuffer.allocate(headerSize);
这里就简单地构造了一个心跳包，后续通过transferData方法来完成数据的发送
若是lastWriteOver为false，则表示上次数据没有发送完，就需要通过transferData方法，将剩余数据继续发送，只要没发送完，只会重复循环，直到发完
先继续往下看，下面就是发送具体的消息数据了：
首先根据nextTransferFromWhere，也就是刚才保存的offset，通过DefaultMessageStore的getCommitLogData方法，其实际上调用的是CommitLog的getData方法，这个方法在
【RocketMQ中Broker的启动源码分析（二）】中关于消息调度（ReputMessageService）时详细介绍过
根据offset找到对应的CommitLog文件，将其从offset对应起始处所有数据读入ByteBuffer中，由SelectMappedBufferResult封装
这里若是master已将将所有本地数据同步给了slave，那么得到的SelectMappedBufferResult就会为null，会调用：
HAConnection.this.haService.getWaitNotifyObject().allWaitForRunning(100);
将自身阻塞，超时等待100ms，要么一直等到超时时间到了，要么就会在后面所讲的同步双传中被同步master唤醒
在得到SelectMappedBufferResult后，这里会对读取到的数据大小进行一次判断，若是大于haTransferBatchSize（默认32K），将size改为32K，实际上就是对发送数据大小的限制，大于32K会切割，每次最多只允许发送32k
通过thisOffset记录nextTransferFromWhere即offset
更新nextTransferFromWhere值，以便下一次定位
还会将读取到的数据结果selectResult交给selectMappedBufferResult保存
然后构建消息头，这里就和心跳包格式一样，前八字节存放offset，后四字节存放数据大小
最后调用transferData方法，进行发送：
private boolean transferData() throws Exception {
int writeSizeZeroTimes = 0;
// Write Header
while (this.byteBufferHeader.hasRemaining()) {
int writeSize = this.socketChannel.write(this.byteBufferHeader);
if (writeSize > 0) {
writeSizeZeroTimes = 0;
this.lastWriteTimestamp = HAConnection.this.haService.getDefaultMessageStore().getSystemClock().now();
} else if (writeSize == 0) {
if (++writeSizeZeroTimes >= 3) {
break;
}
} else {
throw new Exception("ha master write header error < 0");
}
} if (null == this.selectMappedBufferResult) {
return !this.byteBufferHeader.hasRemaining();
} writeSizeZeroTimes = 0; // Write Body
if (!this.byteBufferHeader.hasRemaining()) {
while (this.selectMappedBufferResult.getByteBuffer().hasRemaining()) {
int writeSize = this.socketChannel.write(this.selectMappedBufferResult.getByteBuffer());
if (writeSize > 0) {
writeSizeZeroTimes = 0;
this.lastWriteTimestamp = HAConnection.this.haService.getDefaultMessageStore().getSystemClock().now();
} else if (writeSize == 0) {
if (++writeSizeZeroTimes >= 3) {
break;
}
} else {
throw new Exception("ha master write body error < 0");
}
}
} boolean result = !this.byteBufferHeader.hasRemaining() && !this.selectMappedBufferResult.getByteBuffer().hasRemaining(); if (!this.selectMappedBufferResult.getByteBuffer().hasRemaining()) {
this.selectMappedBufferResult.release();
this.selectMappedBufferResult = null;
} return result;
}
首先将byteBufferHeader中的12字节消息头通过socketChannel的write方法发送出去
然后将selectMappedBufferResult中的ByteBuffer的消息数据发送出去
若是selectMappedBufferResult等于null，说明是心跳包，只发送消息头
无论发送什么都会将时间记录在lastWriteTimestamp中，以便后续发送心跳包的判断
看到这里其实就会发现WriteSocketService线程开启后，只要slave向master发出了第一个offset后，WriteSocketService线程都会不断地将对应位置自己本地的CommitLog文件中的内容发送给slave，直到完全同步后，WriteSocketService线程才会稍微缓缓，进入阻塞100ms以及每隔五秒发一次心跳包的状态
但是只要当Producer向master发送来消息后，由刷盘线程完成持久化后，WriteSocketService线程又会忙碌起来，此时也才是体现同步双写和异步复制的时候
先不急着说这个，来看看slave接收到消息是如何处理的：
是在HAClient的线程中的processReadEvent方法处理的：
private boolean processReadEvent() {
int readSizeZeroTimes = 0;
while (this.byteBufferRead.hasRemaining()) {
try {
int readSize = this.socketChannel.read(this.byteBufferRead);
if (readSize > 0) {
lastWriteTimestamp = HAService.this.defaultMessageStore.getSystemClock().now();
readSizeZeroTimes = 0;
boolean result = this.dispatchReadRequest();
if (!result) {
log.error("HAClient, dispatchReadRequest error");
return false;
}
} else if (readSize == 0) {
if (++readSizeZeroTimes >= 3) {
break;
}
} else {
log.info("HAClient, processReadEvent read socket < 0");
return false;
}
} catch (IOException e) {
log.info("HAClient, processReadEvent read socket exception", e);
return false;
}
} return true;
}
在socketChannel通过read方法将master发送的数据读取到byteBufferRead缓冲区后，由dispatchReadRequest方法做进一步处理
dispatchReadRequest方法：
private boolean dispatchReadRequest() {
final int msgHeaderSize = 8 + 4; // phyoffset + size
int readSocketPos = this.byteBufferRead.position(); while (true) {
int diff = this.byteBufferRead.position() - this.dispatchPostion;
if (diff >= msgHeaderSize) {
long masterPhyOffset = this.byteBufferRead.getLong(this.dispatchPostion);
int bodySize = this.byteBufferRead.getInt(this.dispatchPostion + 8); long slavePhyOffset = HAService.this.defaultMessageStore.getMaxPhyOffset(); if (slavePhyOffset != 0) {
if (slavePhyOffset != masterPhyOffset) {
log.error("master pushed offset not equal the max phy offset in slave, SLAVE: "
+ slavePhyOffset + " MASTER: " + masterPhyOffset);
return false;
}
} if (diff >= (msgHeaderSize + bodySize)) {
byte[] bodyData = new byte[bodySize];
this.byteBufferRead.position(this.dispatchPostion + msgHeaderSize);
this.byteBufferRead.get(bodyData); HAService.this.defaultMessageStore.appendToCommitLog(masterPhyOffset, bodyData); this.byteBufferRead.position(readSocketPos);
this.dispatchPostion += msgHeaderSize + bodySize; if (!reportSlaveMaxOffsetPlus()) {
return false;
} continue;
}
} if (!this.byteBufferRead.hasRemaining()) {
this.reallocateByteBuffer();
} break;
} return true;
}
这里就首先将12字节的消息头取出来
masterPhyOffset：8字节offset ，bodySize ：4字节消息大小
根据master发来的masterPhyOffset会和自己本地的slavePhyOffset进行校验，以便安全备份
之后就会将byteBufferRead中存放在消息头后面的消息数据取出来，调用appendToCommitLog方法持久化到的CommitLog中
public boolean appendToCommitLog(long startOffset, byte[] data) {
if (this.shutdown) {
log.warn("message store has shutdown, so appendToPhyQueue is forbidden");
return false;
} boolean result = this.commitLog.appendData(startOffset, data);
if (result) {
this.reputMessageService.wakeup();
} else {
log.error("appendToPhyQueue failed " + startOffset + " " + data.length);
} return result;
}
实际上调用了commitLog的appendData方法将其写入磁盘，这个方法我在前面博客中介绍过
在完成写入后，需要唤醒reputMessageService消息调度，以便Consumer的消费
关于消息调度详见 【RocketMQ中Broker的启动源码分析（二）】
当然前面说过master还会发送心跳消息，但这里明显没对心跳消息进行处理，只是appendToCommitLog调用时，传入了一个大小为0的byte数组，显然有些不合理，想不通
在完成后，还会调用reportSlaveMaxOffsetPlus方法：
private boolean reportSlaveMaxOffsetPlus() {
boolean result = true;
long currentPhyOffset = HAService.this.defaultMessageStore.getMaxPhyOffset();
if (currentPhyOffset > this.currentReportedOffset) {
this.currentReportedOffset = currentPhyOffset;
result = this.reportSlaveMaxOffset(this.currentReportedOffset);
if (!result) {
this.closeMaster();
log.error("HAClient, reportSlaveMaxOffset error, " + this.currentReportedOffset);
}
} return result;
}
由于完成了写入，那么此时获取到的offset肯定比currentReportedOffset中保存的大，然后再次通过reportSlaveMaxOffset方法，将当前的offset报告给master
这其实上已经完成了异步master的异步复制过程
再来看看同步双写是如何实现的：
和刷盘一样，都是在Producer发送完消息，Broker进行完消息的存储后进行的
在CommitLog的handleHA方法：
public void handleHA(AppendMessageResult result, PutMessageResult putMessageResult, MessageExt messageExt) {
if (BrokerRole.SYNC_MASTER == this.defaultMessageStore.getMessageStoreConfig().getBrokerRole()) {
HAService service = this.defaultMessageStore.getHaService();
if (messageExt.isWaitStoreMsgOK()) {
// Determine whether to wait
if (service.isSlaveOK(result.getWroteOffset() + result.getWroteBytes())) {
GroupCommitRequest request = new GroupCommitRequest(result.getWroteOffset() + result.getWroteBytes());
service.putRequest(request);
service.getWaitNotifyObject().wakeupAll();
boolean flushOK =
request.waitForFlush(this.defaultMessageStore.getMessageStoreConfig().getSyncFlushTimeout());
if (!flushOK) {
log.error("do sync transfer other node, wait return, but failed, topic: " + messageExt.getTopic() + " tags: "
+ messageExt.getTags() + " client address: " + messageExt.getBornHostNameString());
putMessageResult.setPutMessageStatus(PutMessageStatus.FLUSH_SLAVE_TIMEOUT);
}
}
// Slave problem
else {
// Tell the producer, slave not available
putMessageResult.setPutMessageStatus(PutMessageStatus.SLAVE_NOT_AVAILABLE);
}
}
} }
这里就会检查Broker的类型，看以看到只对SYNC_MASTER即同步master进行了操作
这个操作过程其实就和同步刷盘类似
根据Offset+WroteBytes创建一条记录GroupCommitRequest，然后会将添加在List中
然后调用getWaitNotifyObject的wakeupAll方法，把阻塞中的所有WriteSocketService线程唤醒
因为master和slave是一对多的关系，那么这里就会有多个slave连接，也就有多个WriteSocketService线程，保证消息能同步到所有slave中
在唤醒WriteSocketService线程工作后，调用request的waitForFlush方法，将自身阻塞，预示着同步复制的真正开启
在HAService开启时，还开启了一个GroupTransferService线程：
public void run() {
log.info(this.getServiceName() + " service started"); while (!this.isStopped()) {
try {
this.waitForRunning(10);
this.doWaitTransfer();
} catch (Exception e) {
log.warn(this.getServiceName() + " service has exception. ", e);
}
} log.info(this.getServiceName() + " service end");
}
这里的工作原理和同步刷盘GroupCommitService基本一致，相似的地方我就不仔细分析了
GroupTransferService同样保存两张List：
private volatile List<CommitLog.GroupCommitRequest> requestsWrite = new ArrayList<>();
private volatile List<CommitLog.GroupCommitRequest> requestsRead = new ArrayList<>();
由这两张List做一个类似JVM新生代的复制算法
在handleHA方法中，就会将创建的GroupCommitRequest记录添加在requestsWrite这个List中
其中doWaitTransfer方法：
private void doWaitTransfer() {
synchronized (this.requestsRead) {
if (!this.requestsRead.isEmpty()) {
for (CommitLog.GroupCommitRequest req : this.requestsRead) {
boolean transferOK = HAService.this.push2SlaveMaxOffset.get() >= req.getNextOffset();
for (int i = 0; !transferOK && i < 5; i++) {
this.notifyTransferObject.waitForRunning(1000);
transferOK = HAService.this.push2SlaveMaxOffset.get() >= req.getNextOffset();
} if (!transferOK) {
log.warn("transfer messsage to slave timeout, " + req.getNextOffset());
} req.wakeupCustomer(transferOK);
} this.requestsRead.clear();
}
}
}
和刷盘一样，这里会通过复制算法，将requestsWrite和requestsRead进行替换，那么这里的requestsRead实际上就存放着刚才添加的记录
首先取出记录中的NextOffset和push2SlaveMaxOffset比较
push2SlaveMaxOffset值是通过slave发送过来的，在之前说过的ReadSocketService线程中的：
HAConnection.this.haService.notifyTransferSome(HAConnection.this.slaveAckOffset);
notifyTransferSome方法：
public void notifyTransferSome(final long offset) {
for (long value = this.push2SlaveMaxOffset.get(); offset > value; ) {
boolean ok = this.push2SlaveMaxOffset.compareAndSet(value, offset);
if (ok) {
this.groupTransferService.notifyTransferSome();
break;
} else {
value = this.push2SlaveMaxOffset.get();
}
}
}
即便也多个slave连接，这里的push2SlaveMaxOffset永远会记录最大的那个offset
所以在doWaitTransfer中，根据当前NextOffset（完成写入后master本地的offset），进行判断
其实这里主要要考虑到WriteSocketService线程的工作原理，只要本地文件有更新，那么就会向slave发送数据，所以这里由于HA同步是发生在刷盘后的，那么就有可能在这个doWaitTransfer执行前，有slave已经将数据进行了同步，并且向master报告了自己offset，更新了push2SlaveMaxOffset的值
那么
boolean transferOK = HAService.this.push2SlaveMaxOffset.get() >= req.getNextOffset();
```
这个判断就会为真，意味着节点中已经有了备份，所以就会直接调用
req.wakeupCustomer(transferOK);
以此来唤醒刚才在handleHA方法中的阻塞
若是判断为假，就说明没有一个slave完成同步，就需要
for (int i = 0; !transferOK && i < 5; i++) {
this.notifyTransferObject.waitForRunning(1000);
transferOK = HAService.this.push2SlaveMaxOffset.get() >= req.getNextOffset();
}
通过waitForRunning进行阻塞，超时等待，最多五次等待，超过时间会向Producer发送FLUSH_SLAVE_TIMEOUT
若是在超时时间内，有slave完成了同步，并向master发送了offset后，在notifyTransferSome方法中：
public void notifyTransferSome(final long offset) {
for (long value = this.push2SlaveMaxOffset.get(); offset > value; ) {
boolean ok = this.push2SlaveMaxOffset.compareAndSet(value, offset);
if (ok) {
this.groupTransferService.notifyTransferSome();
break;
} else {
value = this.push2SlaveMaxOffset.get();
}
}
}
就会更新push2SlaveMaxOffset，并通过notifyTransferSome唤醒上面所说的阻塞
然后再次判断push2SlaveMaxOffset和getNextOffset
成功后唤醒刚才在handleHA方法中的阻塞，同步master的主从复制也就结束
由于同步master的刷盘是在主从复制前发生的，所以同步双写意味着master和slave都会完成消息的持久化
至此，RocketMQ中Broker的HA策略分析到此结束
