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室内定位系统是一种利用WIFI网络来实现标签的定位,可以在已有的WIFI网络或无线局域网上实现定位引擎,在智能家居,人力资源管理等方面开始得到广泛的应用。由于室内定位系统的场景中原始定位数据非常庞大,采用传统的关系型数据库架构无法支撑其性能需求。因此采用分布式架构的思想,设计并实现了一个数据处理中间件,承担中间件消息调度,数据库交互处理等任务。并在数据持久层提供读写分离,单库分表等工作模式,将数据按照一定规则分散到不同的集群、分区、分表中,极大降低了数据库的访问压力,一定程度上克服传统关系型数据库在处理大规模数据时的性能瓶颈。同时,为了降低第三方应用开发的复杂度,提高系统响应速度,提供基于Map Reduce的大数据分析模块。
Indoor positioning system is a WIFI network to achieve the label positioning, you can already WIFI network or wireless local area network to achieve positioning engine, in the smart home, human resources management and other aspects of the beginning to be widely used. Due to the huge original positioning data in the scene of the indoor positioning system, the traditional relational database architecture can not support its performance requirements. Therefore, using the idea of distributed architecture, a data processing middleware is designed and implemented to undertake the tasks of middleware message scheduling and database interaction processing. And provide data persistence layer read and write separation, single library table mode, the data in accordance with certain rules scattered to different clusters, partitions, sub-tables, greatly reducing the pressure on the database access to a certain extent, to overcome the traditional relationship Performance bottlenecks when dealing with large-scale data. At the same time, in order to reduce the complexity of third-party application development and improve system response speed, big data analysis module based on Map Reduce is provided.