ThingsBoard 二次开发之源码分析 5-如何接收 MQTT 连接
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ThingsBoard源码分析5-如何接收MQTT连接
1. MQTT server
需要接收设备的MQTT连接，那么thingsboard中必然有MQTT服务器，MQTT服务器创建的类是MqttTransportService；
基于netty的mqtt server,添加了MqttTransportServerInitializer的处理类，并向ChannelPipeline添加了netty的MqttDecoder和MqttEncoder让我们可以忽略MQTT消息的编解码工作，重要的是添加了MqttTransportHandler；
2. MqttTransportHandler处理连接
此例中，我们首先需要创建租户，租户管理员，并添加设备，使用MQTT Box模拟硬件设备，拷贝ACCESS TOKEN做为MQTT Box的Username开始连接我们的thingsboard后台
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由于没有使用ssl,收到连接请求以后，便会调用
private void processAuthTokenConnect(ChannelHandlerContext ctx, MqttConnectMessage msg) {
String userName = msg.payload().userName();
log.info("[{}] Processing connect msg for client with user name: {}!", sessionId, userName);
if (StringUtils.isEmpty(userName)) {
ctx.writeAndFlush(createMqttConnAckMsg(CONNECTION_REFUSED_BAD_USER_NAME_OR_PASSWORD));
ctx.close();
} else {
//取出userName,构造protobuf的类(方便传输与解析)，交给transportService处理。此时会使用到源码解析第三篇DefaultTransportService的解析的相关信息了解process的处理。参阅下方①的详细解析。
transportService.process(ValidateDeviceTokenRequestMsg.newBuilder().setToken(userName).build(),
new TransportServiceCallback<ValidateDeviceCredentialsResponseMsg>() {
@Override
public void onSuccess(ValidateDeviceCredentialsResponseMsg msg) {
onValidateDeviceResponse(msg, ctx);
}
@Override
public void onError(Throwable e) {
log.trace("[{}] Failed to process credentials: {}", address, userName, e);
ctx.writeAndFlush(createMqttConnAckMsg(MqttConnectReturnCode.CONNECTION_REFUSED_SERVER_UNAVAILABLE));
ctx.close();
}
});
}
}
-
DefaultTransportService的process方法构造了异步任务，成功调用onSuccess的Consumer,失败调用onFailure的Consumer； -
将验证用户的任务交由
transportApiRequestTemplate.send
public ListenableFuture<Response> send(Request request) {
if (tickSize > maxPendingRequests) {
return Futures.immediateFailedFuture(new RuntimeException("Pending request map is full!"));
}
UUID requestId = UUID.randomUUID();
request.getHeaders().put(REQUEST_ID_HEADER, uuidToBytes(requestId));
//由第三篇文章的分析得出，此topic时tb_transport.api.responses.localHostName
request.getHeaders().put(RESPONSE_TOPIC_HEADER, stringToBytes(responseTemplate.getTopic()));
request.getHeaders().put(REQUEST_TIME, longToBytes(System.currentTimeMillis()));
//参阅第一篇基础知识的介绍，来自谷歌的库，settableFuture，可设置结果的完成
SettableFuture<Response> future = SettableFuture.create();
ResponseMetaData<Response> responseMetaData = new ResponseMetaData<>(tickTs + maxRequestTimeout, future);
//将future放到pendingRequests中②
pendingRequests.putIfAbsent(requestId, responseMetaData);
log.trace("[{}] Sending request, key [{}], expTime [{}]", requestId, request.getKey(), responseMetaData.expTime);
//将消息发送给消息队列topic是tb_transport.api.requests
requestTemplate.send(TopicPartitionInfo.builder().topic(requestTemplate.getDefaultTopic()).build(), request, new TbQueueCallback() {
@Override
public void onSuccess(TbQueueMsgMetadata metadata) {
log.trace("[{}] Request sent: {}", requestId, metadata);
}
@Override
public void onFailure(Throwable t) {
pendingRequests.remove(requestId);
future.setException(t);
}
});
return future;
}
- 根据第三篇
TbCoreTransportApiService的分析，我们发现DefaultTbQueueResponseTemplate的成员变量requestTemplate即consumer刚好是订阅的tb_transport.api.requests的消息：
......
requests.forEach(request -> {
long currentTime = System.currentTimeMillis();
long requestTime = bytesToLong(request.getHeaders().get(REQUEST_TIME));
if (requestTime + requestTimeout >= currentTime) {
byte[] requestIdHeader = request.getHeaders().get(REQUEST_ID_HEADER);
if (requestIdHeader == null) {
log.error("[{}] Missing requestId in header", request);
return;
}
//获取response的topic，可以做到消息从哪来，处理好以后回哪里去，此时的topic是tb_transport.api.responses.localHostName
byte[] responseTopicHeader = request.getHeaders().get(RESPONSE_TOPIC_HEADER);
if (responseTopicHeader == null) {
log.error("[{}] Missing response topic in header", request);
return;
}
UUID requestId = bytesToUuid(requestIdHeader);
String responseTopic = bytesToString(responseTopicHeader);
try {
pendingRequestCount.getAndIncrement();
//调用handler进行处理消息
AsyncCallbackTemplate.withCallbackAndTimeout(handler.handle(request),
response -> {
pendingRequestCount.decrementAndGet();
response.getHeaders().put(REQUEST_ID_HEADER, uuidToBytes(requestId));
//handler.hande处理的结果返回给发送方topic是tb_transport.api.responses.localHostName
responseTemplate.send(TopicPartitionInfo.builder().topic(responseTopic).build(), response, null);
},
e -> {
pendingRequestCount.decrementAndGet();
if (e.getCause() != null && e.getCause() instanceof TimeoutException) {
log.warn("[{}] Timeout to process the request: {}", requestId, request, e);
} else {
log.trace("[{}] Failed to process the request: {}", requestId, request, e);
}
},
requestTimeout,
timeoutExecutor,
callbackExecutor);
.......
- 具体验证逻辑：
@Override
public ListenableFuture<TbProtoQueueMsg<TransportApiResponseMsg>> handle(TbProtoQueueMsg<TransportApiRequestMsg> tbProtoQueueMsg) {
TransportApiRequestMsg transportApiRequestMsg = tbProtoQueueMsg.getValue();
// protobuf构造的类中判定是否包含需要验证的信息块
if (transportApiRequestMsg.hasValidateTokenRequestMsg()) {
ValidateDeviceTokenRequestMsg msg = transportApiRequestMsg.getValidateTokenRequestMsg();
//调用validateCredentials，具体内容就是查询deviceInfo，并将结果交由第二个Function进行进一步处理
return Futures.transform(validateCredentials(msg.getToken(), DeviceCredentialsType.ACCESS_TOKEN), value -> new TbProtoQueueMsg<>(tbProtoQueueMsg.getKey(), value, tbProtoQueueMsg.getHeaders()), MoreExecutors.directExecutor());
}
......
- 当通过设备的acess token找到了deviceInfo,便会通过消息中间件将DeviceInfo发出来，topic是tb_transport.api.responses.localHostName，在第三篇的分析中，
DefaultTransportService的transportApiRequestTemplate即订阅此topic：
List<Response> responses = responseTemplate.poll(pollInterval);
if (responses.size() > 0) {
log.trace("Polling responses completed, consumer records count [{}]", responses.size());
} else {
continue;
}
responses.forEach(response -> {
byte[] requestIdHeader = response.getHeaders().get(REQUEST_ID_HEADER);
UUID requestId;
if (requestIdHeader == null) {
log.error("[{}] Missing requestId in header and body", response);
} else {
requestId = bytesToUuid(requestIdHeader);
log.trace("[{}] Response received: {}", requestId, response);
//参见上②，将验证的future放入到pendingRequests中，现在通过设置的requestId取出来
ResponseMetaData<Response> expectedResponse = pendingRequests.remove(requestId);
if (expectedResponse == null) {
log.trace("[{}] Invalid or stale request", requestId);
} else {
//设置settableFuture的结果
expectedResponse.future.set(response);
}
}
......
DefaultTransportService的process异步请求获得了返回的结果，此时调用onSuccess回调，即调用MqttTransportHandler的onValidateDeviceResponse；
private void onValidateDeviceResponse(ValidateDeviceCredentialsResponseMsg msg, ChannelHandlerContext ctx) {
if (!msg.hasDeviceInfo()) {
ctx.writeAndFlush(createMqttConnAckMsg(CONNECTION_REFUSED_NOT_AUTHORIZED));
ctx.close();
} else {
deviceSessionCtx.setDeviceInfo(msg.getDeviceInfo());
sessionInfo = SessionInfoProto.newBuilder()
.setNodeId(context.getNodeId())
.setSessionIdMSB(sessionId.getMostSignificantBits())
.setSessionIdLSB(sessionId.getLeastSignificantBits())
.setDeviceIdMSB(msg.getDeviceInfo().getDeviceIdMSB())
.setDeviceIdLSB(msg.getDeviceInfo().getDeviceIdLSB())
.setTenantIdMSB(msg.getDeviceInfo().getTenantIdMSB())
.setTenantIdLSB(msg.getDeviceInfo().getTenantIdLSB())
.setDeviceName(msg.getDeviceInfo().getDeviceName())
.setDeviceType(msg.getDeviceInfo().getDeviceType())
.build();
//创建SessionEvent.OPEN的消息，调用sendToDeviceActor方法，包含sessionInfo
transportService.process(sessionInfo, DefaultTransportService.getSessionEventMsg(SessionEvent.OPEN), new TransportServiceCallback<Void>() {
.......
- sendToDeviceActor的实现：
protected void sendToDeviceActor(TransportProtos.SessionInfoProto sessionInfo, TransportToDeviceActorMsg toDeviceActorMsg, TransportServiceCallback<Void> callback) {
//创建tpi，此时会选择一个固定的partition Id,组成的topic是tb_core, fullTopicName是tb_core.(int) 如： tb_core.1
TopicPartitionInfo tpi = partitionService.resolve(ServiceType.TB_CORE, getTenantId(sessionInfo), getDeviceId(sessionInfo));
......
//使用tbCoreMsgProducer发送到消息队列，设置了toDeviceActorMsg
tbCoreMsgProducer.send(tpi,
new TbProtoQueueMsg<>(getRoutingKey(sessionInfo),
ToCoreMsg.newBuilder().setToDeviceActorMsg(toDeviceActorMsg).build()), callback != null ?
new TransportTbQueueCallback(callback) : null);
}
- 此时第二篇基于
DefaultTbCoreConsumerService可以知道DefaultTbCoreConsumerService的消费者订阅该主题的消息：
try {
ToCoreMsg toCoreMsg = msg.getValue();
if (toCoreMsg.hasToSubscriptionMgrMsg()) {
log.trace("[{}] Forwarding message to subscription manager service {}", id, toCoreMsg.getToSubscriptionMgrMsg());
forwardToSubMgrService(toCoreMsg.getToSubscriptionMgrMsg(), callback);
} else if (toCoreMsg.hasToDeviceActorMsg()) {
log.trace("[{}] Forwarding message to device actor {}", id, toCoreMsg.getToDeviceActorMsg());
//交由此方法进行处理
forwardToDeviceActor(toCoreMsg.getToDeviceActorMsg(), callback);
}
-
forwardToDeviceActor对消息的处理private void forwardToDeviceActor(TransportToDeviceActorMsg toDeviceActorMsg, TbCallback callback) { if (statsEnabled) { stats.log(toDeviceActorMsg); } //创建type为TRANSPORT_TO_DEVICE_ACTOR_MSG的消息，并交给AppActor处理 actorContext.tell(new TransportToDeviceActorMsgWrapper(toDeviceActorMsg, callback)); } -
通过第四篇的总结3，我们可以直接去看
AppActor的doProcess方法对此类型消息的处理,跟踪发现AppActor将消息转给了TenantActor,TenantActor创建了DeviceActor,并将消息转给了DeviceActor; -
DeviceActor拿到此类型的消息，进行了如下的处理：
protected boolean doProcess(TbActorMsg msg) { switch (msg.getMsgType()) { case TRANSPORT_TO_DEVICE_ACTOR_MSG: //包装成TransportToDeviceActorMsgWrapper交由processor处理，并继续调用processSessionStateMsgs processor.process(ctx, (TransportToDeviceActorMsgWrapper) msg); break; case DEVICE_ATTRIBUTES_UPDATE_TO_DEVICE_ACTOR_MSG: -
processSessionStateMsgs的处理：private void processSessionStateMsgs(SessionInfoProto sessionInfo, SessionEventMsg msg) { UUID sessionId = getSessionId(sessionInfo); if (msg.getEvent() == SessionEvent.OPEN) { ..... sessions.put(sessionId, new SessionInfoMetaData(new SessionInfo(SessionType.ASYNC, sessionInfo.getNodeId()))); if (sessions.size() == 1) { // 将调用pushRuleEngineMessage(stateData, CONNECT_EVENT); reportSessionOpen(); } //将调用pushRuleEngineMessage(stateData, ACTIVITY_EVENT); systemContext.getDeviceStateService().onDeviceActivity(deviceId, System.currentTimeMillis()); dumpSessions(); } .... -
由于
CONNECT_EVENT和ACTIVITY_EVENT仅仅类型不同，以下暂时只分析CONNECT_EVENTpublic void pushMsgToRuleEngine(TenantId tenantId, EntityId entityId, TbMsg tbMsg, TbQueueCallback callback) { if (tenantId.isNullUid()) { if (entityId.getEntityType().equals(EntityType.TENANT)) { tenantId = new TenantId(entityId.getId()); } else { log.warn("[{}][{}] Received invalid message: {}", tenantId, entityId, tbMsg); return; } } //和第7点类似，创建的tpi的fullTopicName的例子 tb_rule_engine.main.1 TopicPartitionInfo tpi = partitionService.resolve(ServiceType.TB_RULE_ENGINE, tenantId, entityId); log.trace("PUSHING msg: {} to:{}", tbMsg, tpi); ToRuleEngineMsg msg = ToRuleEngineMsg.newBuilder() .setTenantIdMSB(tenantId.getId().getMostSignificantBits()) .setTenantIdLSB(tenantId.getId().getLeastSignificantBits()) .setTbMsg(TbMsg.toByteString(tbMsg)).build(); producerProvider.getRuleEngineMsgProducer().send(tpi, new TbProtoQueueMsg<>(tbMsg.getId(), msg), callback); toRuleEngineMsgs.incrementAndGet(); } -
通过第二篇的分析
DefaultTbRuleEngineConsumerService订阅了此topic: tb_rule_engine.main.1的消息，收到消息以后，调用forwardToRuleEngineActor方法，包裹成QUEUE_TO_RULE_ENGINE_MSG类型的消息，交由AppActor进行分发处理； -
AppActor交给TenantActor处理，TenantActor交给RootRuleChain处理，RuleChainActor交给firstRuleNode处理，也就是某一个RuleNodeActor; -
打开前端RULE CHAINS的界面，会发现，MESSAGE TYPE SWITCH是接收input的第一个节点，其实数据库的配置中，rule_chain表中配置的first_rule_node_id就是
TbMsgTypeSwitchNode； -
进入
TbMsgTypeSwitchNode的onMsg方法(实际上所有的ruleNode处理消息的方法都是onMsg),发现根据messageType（此时是CONNECT_EVENT）定义了relationtype并调用ctx.tellNext(msg, relationType); -
此时
DefaultTbContext创建一个RuleNodeToRuleChainTellNextMsg，类型是RULE_TO_RULE_CHAIN_TELL_NEXT_MSG，交给RuleChainActor处理； -
接下来将会进入到
RuleChainActorMessageProcessor的onTellNext方法：private void onTellNext(TbMsg msg, RuleNodeId originatorNodeId, Set<String> relationTypes, String failureMessage) { try { checkActive(msg); //消息来源 EntityId entityId = msg.getOriginator(); //创建一个tpi，可能会使用 TopicPartitionInfo tpi = systemContext.resolve(ServiceType.TB_RULE_ENGINE, msg.getQueueName(), tenantId, entityId); //查询有关系的RuleNode,其实就是从relation表中查询，该消息来源的id，relation_type和在TbMsgTypeSwitchNode定义的relationType一直的节点id,如上Connect Event就没有找到相应的relation的RuleNodeId List<RuleNodeRelation> relations = nodeRoutes.get(originatorNodeId).stream() .filter(r -> contains(relationTypes, r.getType())) .collect(Collectors.toList()); int relationsCount = relations.size(); //Connect Event就没有找到相应的relation的RuleNodeId,消息通过规则引擎，已经处理完成 if (relationsCount == 0) { log.trace("[{}][{}][{}] No outbound relations to process", tenantId, entityId, msg.getId()); if (relationTypes.contains(TbRelationTypes.FAILURE)) { RuleNodeCtx ruleNodeCtx = nodeActors.get(originatorNodeId); if (ruleNodeCtx != null) { msg.getCallback().onFailure(new RuleNodeException(failureMessage, ruleChainName, ruleNodeCtx.getSelf())); } else { log.debug("[{}] Failure during message processing by Rule Node [{}]. Enable and see debug events for more info", entityId, originatorNodeId.getId()); msg.getCallback().onFailure(new RuleEngineException("Failure during message processing by Rule Node [" + originatorNodeId.getId().toString() + "]")); } } else { msg.getCallback().onSuccess(); } //举例:Post telemetry的type可以找到相应的ruleNode,实现类是：TbMsgTimeseriesNode，那么此消息将会交给TbMsgTimeseriesNode处理 } else if (relationsCount == 1) { for (RuleNodeRelation relation : relations) { log.trace("[{}][{}][{}] Pushing message to single target: [{}]", tenantId, entityId, msg.getId(), relation.getOut()); pushToTarget(tpi, msg, relation.getOut(), relation.getType()); } } else { MultipleTbQueueTbMsgCallbackWrapper callbackWrapper = new MultipleTbQueueTbMsgCallbackWrapper(relationsCount, msg.getCallback()); log.trace("[{}][{}][{}] Pushing message to multiple targets: [{}]", tenantId, entityId, msg.getId(), relations); for (RuleNodeRelation relation : relations) { EntityId target = relation.getOut(); putToQueue(tpi, msg, callbackWrapper, target); } } } catch (RuleNodeException rne) { msg.getCallback().onFailure(rne); } catch (Exception e) { msg.getCallback().onFailure(new RuleEngineException("onTellNext - " + e.getMessage())); } }What’s more:
如上面的举例，比如是遥测数据Post telemetry，将会使用
TbMsgTimeseriesNode的onMsg做进一步的处理，比如存储数据，再通过webSocket进行数据的更新如果有webSocket的session的话，或者其他通知消息，就不详细展开了。
总结：
-
处理MQTT的连接其实就是走完了整个规则引擎的逻辑，其他类型的消息，比如遥测数据，属性更新，RPC请求发送与接收，大体流程大同小异；
-
在处理消息流向的时候，我们一定要清楚其订阅或者发布的主题是什么，这样我们才不会丢失方向；
-
Actor的模型就是根据消息的类型，使用AppActor进行一步步的分发，最终交由合适的RuleNode进行处理；
-
Protobuf类型的消息容易序列化传输与解析，所以在thingsboard中大量使用，但是生成的类可读性不是很高，可以选择直接读queue.proto文件，对类有感性的认知。
由于作者水平有限，只是梳理了大致的流程，文章难免出现纰漏，望谅解并指正。