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接上一篇：RocketMQ入门到入土（四）producer生产消息源码剖析

一、原理

1、消息存在哪了？

消息持久化的地方其实是磁盘上，在如下目录里的commitlog文件夹里。

/root/store/commitlog

源码如下：

// {@link org.apache.rocketmq.store.config.MessageStoreConfig}// 数据存储根目录private String storePathRootDir = System.getProperty("user.home") + File.separator + "store";// commitlog目录private String storePathCommitLog = System.getProperty("user.home") + File.separator + "store" + File.separator + "commitlog";// 每个commitlog文件大小为1GB，超过1GB则创建新的commitlog文件private int mappedFileSizeCommitLog = 1024 * 1024 * 1024;

比如验证下：

[root@iZ2ze84zygpzjw5bfcmh2hZ commitlog]# pwd/root/store/commitlog[root@iZ2ze84zygpzjw5bfcmh2hZ commitlog]# ll -htotal 400K-rw-r--r-- 1 root root 1.0G Jun 30 18:21 00000000000000000000[root@iZ2ze84zygpzjw5bfcmh2hZ commitlog]#

可以清晰的看到文件大小是1.0G，超过1.0G再写入消息的话会自动创建新的commitlog文件。

2、关键类解释

2.1、MappedFile

对应的是commitlog文件，比如上面的00000000000000000000文件。

2.2、MappedFileQueue

是MappedFile 所在的文件夹，对 MappedFile 进行封装成文件队列。

2.3、CommitLog

针对 MappedFileQueue 的封装使用。

二、Broker接收消息

1、调用链

BrokerStartup.start() -》 BrokerController.start() -》 NettyRemotingServer.start() -》 NettyRemotingServer.prepareSharableHandlers() -》 new NettyServerHandler() -》 NettyRemotingAbstract.processMessageReceived() -》 NettyRemotingAbstract.proce***equestCommand() -》 SendMessageProcessor.proce***equest()

2、proce***equest

SendMessageProcessor.proce***equest()
@Overridepublic RemotingCommand proce***equest(ChannelHandlerContext ctx,                                      RemotingCommand request) throws RemotingCommandException {    RemotingCommand response = null;    try {        // 调用asyncProce***equest        response = asyncProce***equest(ctx, request).get();    } catch (InterruptedException | ExecutionException e) {        log.error("process SendMessage error, request : " + request.toString(), e);    }    return response;}

3、asyncProce***equest

public CompletableFuture<RemotingCommand> asyncProce***equest(ChannelHandlerContext ctx,                                                                  RemotingCommand request) throws RemotingCommandException {    final SendMessageContext mqtraceContext;    switch (request.getCode()) {        // 表示消费者发送的消息，发送者消费失败会重新发回队列进行消息重试        case RequestCode.CONSUMER_SEND_MSG_BACK:            return this.asyncConsumerSendMsgBack(ctx, request);        default:            // 解析header，也就是我们Producer发送过来的消息都在request里，给他解析到SendMessageRequestHeader对象里去。            SendMessageRequestHeader requestHeader = parseRequestHeader(request);            if (requestHeader == null) {                return CompletableFuture.completedFuture(null);            }            mqtraceContext = buildMsgContext(ctx, requestHeader);            // 将解析好的参数放到SendMessageContext对象里            this.executeSendMessageHookBefore(ctx, request, mqtraceContext);            if (requestHeader.isBatch()) {                // 批处理消息用                return this.asyncSendBatchMessage(ctx, request, mqtraceContext, requestHeader);            } else {                // 非批处理，我们这里介绍的核心。                return this.asyncSendMessage(ctx, request, mqtraceContext, requestHeader);            }    }}

4、asyncSendMessage

private CompletableFuture<RemotingCommand> asyncSendMessage(ChannelHandlerContext ctx, RemotingCommand request,                                                                SendMessageContext mqtraceContext,                                                                SendMessageRequestHeader requestHeader) {    final byte[] body = request.getBody();    int queueIdInt = requestHeader.getQueueId();    TopicConfig topicConfig = this.brokerController.getTopicConfigManager().selectTopicConfig(requestHeader.getTopic());    // 拼凑message对象    MessageExtBrokerInner msgInner = new MessageExtBrokerInner();    msgInner.setTopic(requestHeader.getTopic());    msgInner.setQueueId(queueIdInt);    msgInner.setBody(body);    msgInner.setFlag(requestHeader.getFlag());    MessageAccessor.setProperties(msgInner, MessageDecoder.string2messageProperties(requestHeader.getProperties()));    msgInner.setPropertiesString(requestHeader.getProperties());    msgInner.setBornTimestamp(requestHeader.getBornTimestamp());    msgInner.setBornHost(ctx.channel().remoteAddress());    msgInner.setStoreHost(this.getStoreHost());    msgInner.setReconsumeTimes(requestHeader.getReconsumeTimes() == null ? 0 : requestHeader.getReconsumeTimes());        CompletableFuture<PutMessageResult> putMessageResult = null;    Map<String, String> origProps = MessageDecoder.string2messageProperties(requestHeader.getProperties());    // 真正接收消息的方法    putMessageResult = this.brokerController.getMessageStore().asyncPutMessage(msgInner);    return handlePutMessageResultFuture(putMessageResult, response, request, msgInner, responseHeader, mqtraceContext, ctx, queueIdInt);}

至此我们的消息接收完成了，都封装到了MessageExtBrokerInner对象里。

三、Broker消息存储（持久化）

1、asyncPutMessage

接着上步骤的asyncSendMessage继续看

@Overridepublic CompletableFuture<PutMessageResult> asyncPutMessage(MessageExtBrokerInner msg) {    CompletableFuture<PutMessageResult> putResultFuture = this.commitLog.asyncPutMessage(msg);    putResultFuture.thenAccept((result) -> {        ......    });    return putResultFuture;}

2、commitLog.asyncPutMessage

public CompletableFuture<PutMessageResult> asyncPutMessage(final MessageExtBrokerInner msg) {    // 获取最后一个文件，MappedFile就是commitlog目录下的那个0000000000文件    MappedFile mappedFile = this.mappedFileQueue.getLastMappedFile();    try {        // 追加数据到commitlog        result = mappedFile.appendMessage(msg, this.appendMessageCallback);        switch (result.getStatus()) {            ......        }        // 将内存的数据持久化到磁盘        CompletableFuture<PutMessageStatus> flushResultFuture = submitFlushRequest(result, putMessageResult, msg);    }}

3、appendMessagesInner

public AppendMessageResult appendMessagesInner(final MessageExt messageExt, final AppendMessageCallback cb) {    // 将消息写到内存    return cb.doAppend(this.getFileFromOffset(), byteBuffer, this.fileSize - currentPos, (MessageExtBrokerInner) messageExt);}

4、doAppend

@Overridepublic AppendMessageResult doAppend(final long fileFromOffset, final ByteBuffer byteBuffer, final int maxBlank,                                    final MessageExtBrokerInner msgInner) {    // Initialization of storage space    this.resetByteBuffer(msgStoreItemMemory, msgLen);    // 1 TOTALSIZE    this.msgStoreItemMemory.putInt(msgLen);    // 2 MAGICCODE    this.msgStoreItemMemory.putInt(CommitLog.MESSAGE_MAGIC_CODE);    // 3 BODYCRC    this.msgStoreItemMemory.putInt(msgInner.getBodyCRC());    // 4 QUEUEID    this.msgStoreItemMemory.putInt(msgInner.getQueueId());    // 5 FLAG    this.msgStoreItemMemory.putInt(msgInner.getFlag());    // 6 QUEUEOFFSET    this.msgStoreItemMemory.putLong(queueOffset);    // 7 PHYSICALOFFSET    this.msgStoreItemMemory.putLong(fileFromOffset + byteBuffer.position());    // 8 SYSFLAG    this.msgStoreItemMemory.putInt(msgInner.getSysFlag());    // 9 BORNTIMESTAMP    this.msgStoreItemMemory.putLong(msgInner.getBornTimestamp());    // 10 BORNHOST    this.resetByteBuffer(bornHostHolder, bornHostLength);    this.msgStoreItemMemory.put(msgInner.getBornHostBytes(bornHostHolder));    // 11 STORETIMESTAMP    this.msgStoreItemMemory.putLong(msgInner.getStoreTimestamp());    // 12 STOREHOSTADDRESS    this.resetByteBuffer(storeHostHolder, storeHostLength);    this.msgStoreItemMemory.put(msgInner.getStoreHostBytes(storeHostHolder));    // 13 RECONSUMETIMES    this.msgStoreItemMemory.putInt(msgInner.getReconsumeTimes());    // 14 Prepared Transaction Offset    this.msgStoreItemMemory.putLong(msgInner.getPreparedTransactionOffset());    // 15 BODY    this.msgStoreItemMemory.putInt(bodyLength);    if (bodyLength > 0)        this.msgStoreItemMemory.put(msgInner.getBody());    // 16 TOPIC    this.msgStoreItemMemory.put((byte) topicLength);    this.msgStoreItemMemory.put(topicData);    // 17 PROPERTIES    this.msgStoreItemMemory.putShort((short) propertiesLength);    if (propertiesLength > 0)        this.msgStoreItemMemory.put(propertiesData);    final long beginTimeMills = CommitLog.this.defaultMessageStore.now();    // Write messages to the queue buffer    byteBuffer.put(this.msgStoreItemMemory.array(), 0, msgLen);    return result;}

这一步其实就已经把消息保存到缓冲区里了，也就是msgStoreItemMemory，这里采取的NIO。

private final ByteBuffer msgStoreItemMemory;

5、submitFlushRequest

再次回到【2、commitLog.asyncPutMessage】的submitFlushRequest方法，因为之前的方法是将数据已经写到ByteBuffer缓冲区里了，下一步也就是我们现在这一步就要刷盘了。

public CompletableFuture<PutMessageStatus> submitFlushRequest(AppendMessageResult result, PutMessageResult putMessageResult,                                                              MessageExt messageExt) {    // 同步刷盘    if (FlushDiskType.SYNC_FLUSH == this.defaultMessageStore.getMessageStoreConfig().getFlushDiskType()) {        final GroupCommitService service = (GroupCommitService) this.flushCommitLogService;        if (messageExt.isWaitStoreMsgOK()) {            GroupCommitRequest request = new GroupCommitRequest(result.getWroteOffset() + result.getWroteBytes(),                                                                this.defaultMessageStore.getMessageStoreConfig().getSyncFlushTimeout());            service.putRequest(request);            return request.future();        } else {            service.wakeup();            return CompletableFuture.completedFuture(PutMessageStatus.PUT_OK);        }    }    // 异步刷盘    else {        if (!this.defaultMessageStore.getMessageStoreConfig().isTransientStorePoolEnable()) {                        flushCommitLogService.wakeup();        } else  {            commitLogService.wakeup();        }        return CompletableFuture.completedFuture(PutMessageStatus.PUT_OK);    }}

6、异步刷盘

class FlushRealTimeService extends FlushCommitLogService {    @Override    public void run() {        while (!this.isStopped()) {            try {    // 每隔500ms刷一次盘                if (flushCommitLogTimed) {                    Thread.sleep(500);                } else {                    this.waitForRunning(500);                }                // 调用mappedFileQueue的flush方法                CommitLog.this.mappedFileQueue.flush(flushPhysicQueueLeastPages);            } catch (Throwable e) {            }        }    }}

可看出默认是每隔500毫秒刷一次盘

7、mappedFileQueue.flush

public boolean flush(final int flushLeastPages) {    MappedFile mappedFile = this.findMappedFileByOffset(this.flushedWhere, this.flushedWhere == 0);    if (mappedFile != null) {        // 真正的刷盘操作        int offset = mappedFile.flush(flushLeastPages);    }}

8、mappedFile.flush

public int flush(final int flushLeastPages) {    if (this.isAbleToFlush(flushLeastPages)) {        try {            if (writeBuffer != null || this.fileChannel.position() != 0) {                // 刷盘   NIO                this.fileChannel.force(false);            } else {    // 刷盘  NIO                this.mappedByteBuffer.force();            }        } catch (Throwable e) {            log.error("Error occurred when force data to disk.", e);        }    }    return this.getFlushedPosition();}

至此已经全部结束。

四、总结

面试被问：Broker收到消息后怎么持久化的？

回答者：有两种方式：同步和异步。一般选择异步，同步效率低，但是更可靠。消息存储大致原理是：

核心类MappedFile对应的是每个commitlog文件，MappedFileQueue相当于文件夹，管理所有的文件，还有一个管理者CommitLog对象，他负责提供一些操作。具体的是Broker端拿到消息后先将消息、topic、queue等内容存到ByteBuffer里，然后去持久化到commitlog文件中。commitlog文件大小为1G，超出大小会新创建commitlog文件来存储，采取的nio方式。

五、补充：同步/异步刷盘

1、关键类

2、图解

3、同步刷盘

3.1、源码

// {@link org.apache.rocketmq.store.CommitLog#submitFlushRequest()}// Synchronization flushif (FlushDiskType.SYNC_FLUSH == this.defaultMessageStore.getMessageStoreConfig().getFlushDiskType()) {    // 同步刷盘service -> GroupCommitService    final GroupCommitService service = (GroupCommitService) this.flushCommitLogService;    if (messageExt.isWaitStoreMsgOK()) {        // 数据准备        GroupCommitRequest request = new GroupCommitRequest(result.getWroteOffset() + result.getWroteBytes(),                                                 this.defaultMessageStore.getMessageStoreConfig().getSyncFlushTimeout());        // 将数据对象放到requestsWrite里        service.putRequest(request);        return request.future();    } else {        service.wakeup();        return CompletableFuture.completedFuture(PutMessageStatus.PUT_OK);    }}

putRequest

public synchronized void putRequest(final GroupCommitRequest request) {    synchronized (this.requestsWrite) {        this.requestsWrite.add(request);    }    // 这里很关键！！！，给他设置成true。然后计数器-1。下面run方法的时候才会进行交换数据且return    if (hasNotified.compareAndSet(false, true)) {        waitPoint.countDown(); // notify    }}

run

public void run() {    while (!this.isStopped()) {        try {            // 是同步还是异步的关键方法，也就是说组不阻塞全看这里。            this.waitForRunning(10);            // 真正的刷盘逻辑            this.doCommit();        } catch (Exception e) {            CommitLog.log.warn(this.getServiceName() + " service has exception. ", e);        }    }}

waitForRunning

protected volatile AtomicBoolean hasNotified = new AtomicBoolean(false);// 其实就是CountDownLatchprotected final CountDownLatch2 waitPoint = new CountDownLatch2(1);protected void waitForRunning(long interval) {    // 如果是true，且给他改成false成功的话，则onWaitEnd()且return，但是默认是false，也就是默认情况下这个if不会进。    if (hasNotified.compareAndSet(true, false)) {        this.onWaitEnd();        return;    }    //entry to wait    waitPoint.reset();    try {        // 等待，默认值是1，也就是waitPoint.countDown()一次后就会激活这里。        waitPoint.await(interval, TimeUnit.MILLISECONDS);    } catch (InterruptedException e) {        log.error("Interrupted", e);    } finally {        // 给状态值设置成false        hasNotified.set(false);        this.onWaitEnd();    }}

3.2、总结

总结下同步刷盘的主要流程：

核心类是GroupCommitService，核心方法 是waitForRunning。
•先调用putRequest方法将hasNotified变为true，且进行notify，也就是waitPoint.countDown()。
•其次是run方法里的waitForRunning()，waitForRunning()判断hasNotified是不是true，是true则交换数据然后return掉，也就是不进行await阻塞，直接return。
•最后上一步return了，没有阻塞，那么顺理成章的调用doCommit进行真正意义的刷盘。

4、异步刷盘

4.1、源码

核心类是：FlushRealTimeService

// {@link org.apache.rocketmq.store.CommitLog#submitFlushRequest()}// Asynchronous flushif (!this.defaultMessageStore.getMessageStoreConfig().isTransientStorePoolEnable()) {    flushCommitLogService.wakeup();} else  {    commitLogService.wakeup();}return CompletableFuture.completedFuture(PutMessageStatus.PUT_OK);

run

// {@link org.apache.rocketmq.store.CommitLog.FlushRealTimeService#run()}class FlushRealTimeService extends FlushCommitLogService {    @Override    public void run() {        while (!this.isStopped()) {            try {    // 每隔500ms刷一次盘                if (flushCommitLogTimed) {                    Thread.sleep(500);       
} else {                    // 根上面同步刷盘调用的是同一个方法，区别在于这里没有将hasNotified变为true，也就是还是默认的false，那么waitForRunning方法内部的第一个判断就不会走，就不会return掉，就会进行下面的await方法阻塞，默认阻塞时间是500毫秒。也就是默认500ms刷一次盘。                    this.waitForRunning(500);                }                // 调用mappedFileQueue的flush方法                CommitLog.this.mappedFileQueue.flush(flushPhysicQueueLeastPages);            } catch (Throwable e) {            }        }    }}

4.2、总结

核心类#方法：FlushRealTimeService#run()
•判断flushCommitLogTimed是不是true，默认false，是true则直接sleep(500ms)然后进行mappedFileQueue.flush()刷盘。
•若是false，则进入waitForRunning(500)，这里是和同步刷盘的区别关键所在，同步刷盘之前将hasNotified变为true了，所以直接一套小连招：return+doCommit了 ，异步这里直接调用的waitForRunning(500)，在这之前没任何对hasNotified的操作，所以不会return，而是会继续走下面的waitPoint.await(500, TimeUnit.MILLISECONDS);进行阻塞500毫秒，500毫秒后自动唤醒然后进行flush刷盘。也就是异步刷盘的话默认500ms刷盘一次。