概述
欢迎加入ThingsBoard技术交流群
这里可复制Q群号:69998183
关注“云腾五洲”:获取二开ThingsBoard物联网平台演示
交流社区:ThingsKit-ThingsBoard社区
#ThingsBoard源码分析3-启动分析2
以下的分析环境基于内存消息队列和默认配置
1. DefaultTransportService
分析初始化方法:
@PostConstruct
public void init() {
//根据配置判断是否创建限流
if (rateLimitEnabled) {
//Just checking the configuration parameters
new TbRateLimits(perTenantLimitsConf);
new TbRateLimits(perDevicesLimitsConf);
}
this.schedulerExecutor = Executors.newSingleThreadScheduledExecutor(ThingsBoardThreadFactory.forName("transport-scheduler"));
this.transportCallbackExecutor = Executors.newWorkStealingPool(20);
this.schedulerExecutor.scheduleAtFixedRate(this::checkInactivityAndReportActivity, new Random().nextInt((int) sessionReportTimeout), sessionReportTimeout, TimeUnit.MILLISECONDS);
//transportApiRequestTemplate的创建见下分析①,transportApiRequestTemplate中包含了
//一个生产者producerTemplate(requestTemplate) topic:tb_transport.api.responses ②
//和一个消费者consumerTemplate (responseTemplate) topic:tb_transport.api.responses.localHostName ③
transportApiRequestTemplate = queueProvider.createTransportApiRequestTemplate();
//此处的producerProvider bean的创建是按照配置文件的值创建的,TbQueueProducerProvider有三个实现类,使用ConditionalOnExpression注解,读取service.type的值(默认monolith),所以该Bean的实现类是TbCoreQueueProducerProvider,此类的@PostConstruct标记的init()方法初始化的,该类TbCoreQueueProducerProvider初始化了一下变量:
// 1.toTbCore topic:tb_core
// 2.toTransport topic:tb_transport.notifications
// 3.toRuleEngine topic:tb_rule_engine
// 4.toRuleEngineNotifications topic:tb_rule_engine
// 5.toTbCoreNotifications topic:tb_core
ruleEngineMsgProducer = producerProvider.getRuleEngineMsgProducer();
tbCoreMsgProducer = producerProvider.getTbCoreMsgProducer();
transportNotificationsConsumer = queueProvider.createTransportNotificationsConsumer();
//fullTopic = topic:tb_transport.notifications.localHostName
TopicPartitionInfo tpi = partitionService.getNotificationsTopic(ServiceType.TB_TRANSPORT, serviceInfoProvider.getServiceId());
transportNotificationsConsumer.subscribe(Collections.singleton(tpi));
//见④分析
transportApiRequestTemplate.init();
mainConsumerExecutor.execute(() -> {
while (!stopped) {
try {
List<TbProtoQueueMsg<ToTransportMsg>> records = transportNotificationsConsumer.poll(notificationsPollDuration);
if (records.size() == 0) {
continue;
}
records.forEach(record -> {
try {
processToTransportMsg(record.getValue());
} catch (Throwable e) {
log.warn("Failed to process the notification.", e);
}
});
transportNotificationsConsumer.commit();
} catch (Exception e) {
if (!stopped) {
log.warn("Failed to obtain messages from queue.", e);
try {
Thread.sleep(notificationsPollDuration);
} catch (InterruptedException e2) {
log.trace("Failed to wait until the server has capacity to handle new requests", e2);
}
}
}
}
});
}
① createTransportApiRequestTemplate
In InMemoryTbTransportQueueFactory
,因为我们没有启用相应的消息队列中间件,我们分析InMemoryTbTransportQueueFactory
:
public TbQueueRequestTemplate<TbProtoQueueMsg<TransportApiRequestMsg>, TbProtoQueueMsg<TransportApiResponseMsg>> createTransportApiRequestTemplate() {
//根据配置文件值queue.transport_api.requests_topic获取到的topic是tb_transport.api.requests创建了生产者
InMemoryTbQueueProducer<TbProtoQueueMsg<TransportApiRequestMsg>> producerTemplate =
new InMemoryTbQueueProducer<>(transportApiSettings.getRequestsTopic());
//根据配置文件值queue.transport_api.responses_topic获取到的topic是tb_transport.api.responses
//加上serviceId(我们在第二篇分析中提到,本机的HostName作为serviceId,其topic就是tb_transport.api.responses.localHostName
InMemoryTbQueueConsumer<TbProtoQueueMsg<TransportApiResponseMsg>> consumerTemplate =
new InMemoryTbQueueConsumer<>(transportApiSettings.getResponsesTopic() + "." + serviceInfoProvider.getServiceId());
//使用建造者模式返回了TbQueueRequestTemplate实例,其中包含了一个消费者和一个生产者
DefaultTbQueueRequestTemplate.DefaultTbQueueRequestTemplateBuilder
<TbProtoQueueMsg<TransportApiRequestMsg>, TbProtoQueueMsg<TransportApiResponseMsg>> templateBuilder = DefaultTbQueueRequestTemplate.builder();
templateBuilder.queueAdmin(new TbQueueAdmin() {
@Override
public void createTopicIfNotExists(String topic) {}
@Override
public void destroy() {}
});
templateBuilder.requestTemplate(producerTemplate);
templateBuilder.responseTemplate(consumerTemplate);
templateBuilder.maxPendingRequests(transportApiSettings.getMaxPendingRequests());
templateBuilder.maxRequestTimeout(transportApiSettings.getMaxRequestsTimeout());
templateBuilder.pollInterval(transportApiSettings.getResponsePollInterval());
return templateBuilder.build();
}
④init()
in DefaultTbQueueRequestTemplate
:
public void init() {
queueAdmin.createTopicIfNotExists(responseTemplate.getTopic());
//按照是使用的中间件,实现不同的初始化方法,Inmemory该方法体为空
this.requestTemplate.init();
tickTs = System.currentTimeMillis();
//见③,订阅主题为 tb_transport.api.responses.localHostName
responseTemplate.subscribe();
executor.submit(() -> {
long nextCleanupMs = 0L;
while (!stopped) {
try {
//从消息队列里面获取消息
List<Response> responses = responseTemplate.poll(pollInterval);
...........
2.TbCoreTransportApiService
-
PostConstruct
注解方法:
@PostConstruct
public void init() {
this.transportCallbackExecutor = Executors.newWorkStealingPool(maxCallbackThreads);
//topic是配置文件queue.transport_api.responses_topic的值默认为:tb_transport.api.responses ⑤
TbQueueProducer<TbProtoQueueMsg> producer = tbCoreQueueFactory.createTransportApiResponseProducer();
//topic是配置文件queue.transport_api.requests_topic的值,默认为:tb_transport.api.requests ⑥
TbQueueConsumer<TbProtoQueueMsg> consumer = tbCoreQueueFactory.createTransportApiRequestConsumer();
DefaultTbQueueResponseTemplate.DefaultTbQueueResponseTemplateBuilder
<TbProtoQueueMsg<TransportApiRequestMsg>, TbProtoQueueMsg<TransportApiResponseMsg>> builder = DefaultTbQueueResponseTemplate.builder();
builder.requestTemplate(consumer);
builder.responseTemplate(producer);
builder.maxPendingRequests(maxPendingRequests);
builder.requestTimeout(requestTimeout);
builder.pollInterval(responsePollDuration);
builder.executor(transportCallbackExecutor);
builder.handler(transportApiService);
transportApiTemplate = builder.build();
- `@EventListener(ApplicationReadyEvent.class)`注解方法,调用了`transportApiTemplate.init(transportApiService);``transportApiTemplate`即上一步创建的`DefaultTbQueueResponseTemplate`对象`init()`方法为:
```java
@Override
public void init(TbQueueHandler<Request, Response> handler) {
//按照是使用的中间件,实现不同的初始化方法,Inmemory该方法体为空
this.responseTemplate.init();
//见⑥,订阅主题为tb_transport.api.requests
requestTemplate.subscribe();
loopExecutor.submit(() -> {
while (!stopped) {
try {
while (pendingRequestCount.get() >= maxPendingRequests) {
try {
Thread.sleep(pollInterval);
} catch (InterruptedException e) {
log.trace("Failed to wait until the server has capacity to handle new requests", e);
}
}
List<Request> requests = requestTemplate.poll(pollInterval);
...........
总结
DefaultTransportService
和TbCoreTransportApiService
方法的启动并不是很复杂,我们需要将主要的关注点放在两个Bean初始化消费者和生产者的topic上面,thingsboard将使用中间件将消息解耦,如果按照传统的调试方法很容易找不到消息的流向,此时我们将topic作为关键的切入点,方便后面整个数据流的分析。
最后
以上就是忧虑大碗为你收集整理的ThingsBoard 二次开发之源码分析 3-启动分析 2的全部内容,希望文章能够帮你解决ThingsBoard 二次开发之源码分析 3-启动分析 2所遇到的程序开发问题。
如果觉得靠谱客网站的内容还不错,欢迎将靠谱客网站推荐给程序员好友。
发表评论 取消回复