Research On Data Warehouse Of Logistics Supply Chain Based On Hive Architecture And Optimization Of Transport Capacity Matching Model

Along with the rapid development of the Internet and the Internet of things, logistics capacity supply chain data scale is gradually increasing. In order to make full use of logistics capacity data and provide decision support for logistics enterprises, and also in order to protect the logistics capacity of the industry security. To build a powerful distributed data warehouse platform and research of massive logistics capacity of the supply chain data storage and decision-making application has important significance.Due to shortage of traditional database in the logistics industry capacity to store huge amounts of data, and also can provide decision support, this paper presents based on Hive architecture of logistics capacity of the supply chain data warehouse construction method. Through joint research topic of an enterprise(hereinafter referred to as enterprises) in many application systems of shipping supply chain data analysis, integration, realize system capacity data sharing. In view of the mass transport power supplies chain data analysis and decision-making needs, design and optimization of the capacity matching the original model, through the Hive data warehouse for enterprise capacity matching to provide decision support.The specific research work of this paper is as follows:Firstly, the method of constructing a data warehouse based on Hive architecture is proposed. Using this method, a fully distributed Hive data warehouse is set up in a number of Ali cloud servers.Secondly, for the enterprise application systems of heterogeneous capacity data source by based on integration of the Hive data warehouse integration of multiple capacity data source, will be integrated capacity data into data warehouse, realize the sharing of data between multiple system capacities.Thirdly, for enterprises in a capacity scheduling subsystem, design and optimization of the capacity matching model, combined with the Hive data warehouse can match between multiple systems of the vehicle information, and enterprise capacity to match the offer assistance in the decision-making.Fourthly, with enterprises to provide the data source and the construction of the Hive data warehouse. By comparison of the data analysis of Oracle, My SQL, impala and Hive query efficiency and achieve multi-source heterogeneous capacity data sharing and optimization of the capacity matching model.