Merge pull request #1224 from taosdata/feature/subscribe

subscribe: update documentation

documentation/webdocs/markdowndocs/advanced features-ch.md

@@ -67,7 +67,7 @@ TDengine内嵌支持轻量级的消息订阅与推送服务。使用系统提供
 
 TDengine的订阅与推送服务的状态是客户端维持，TDengine服务器并不维持。因此如果应用重启，从哪个时间点开始获取最新数据，由应用决定。
 
-订阅相关API请见 [连接器](https://www.taosdata.com/cn/documentation/connector/)。
+订阅相关API文档请见 [C/C++ 数据订阅接口](https://www.taosdata.com/cn/documentation/connector/#C/C++-%E6%95%B0%E6%8D%AE%E8%AE%A2%E9%98%85%E6%8E%A5%E5%8F%A3)，《[TDEngine中订阅的用途和用法](https://www.taosdata.com/blog/2020/02/12/1277.html)》则以一个示例详细介绍了这些ＡＰＩ的用法。
 
 ## 缓存 (Cache)
 TDengine采用时间驱动缓存管理策略（First-In-First-Out，FIFO），又称为写驱动的缓存管理机制。这种策略有别于读驱动的数据缓存模式（Least-Recent-Use，LRU），直接将最近写入的数据保存在系统的缓存中。当缓存达到临界值的时候，将最早的数据批量写入磁盘。一般意义上来说，对于物联网数据的使用，用户最为关心最近产生的数据，即当前状态。TDengine充分利用了这一特性，将最近到达的（当前状态）数据保存在缓存中。

documentation/webdocs/markdowndocs/advanced features.md

@@ -62,7 +62,7 @@ Time series data is a sequence of data points over time. Inside a table, the dat
 
 To reduce the development complexity and improve data consistency, TDengine provides the pub/sub functionality. To publish a message, you simply insert a record into a table. Compared with popular messaging tool Kafka, you subscribe to a table or a SQL query statement, instead of a topic. Once new data points arrive, TDengine will notify the application. The process is just like Kafka.  
 
-The detailed API will be introduced in the [connectors](https://www.taosdata.com/en/documentation/connector/) section. 
+The API documentation is at [C/C++ subscription API](https://www.taosdata.com/en/documentation/connector/#C/C++-subscription-API) section, and you can find more information from blog article (only Chinese version at present) [The usage of subscription](https://www.taosdata.com/blog/2020/02/12/1277.html).
 
 ##Caching
 TDengine allocates a fixed-size buffer in memory, the newly arrived data will be written into the buffer first. Every device or table gets one or more memory blocks. For typical IoT scenarios, the hot data shall always be newly arrived data, they are more important for timely analysis. Based on this observation, TDengine manages the cache blocks in First-In-First-Out strategy. If no enough space in the buffer, the oldest data will be saved into hard disk first, then be overwritten by newly arrived data. TDengine also guarantees every device can keep at least one block of data in the buffer.