Research On Spatio-temporal Data Dtorage And Query Oriented To Multidimensional Attributes

As one of the most important types of big data,spatiotemporal data has multi-dimensional characteristics such as spatial attributes,temporal attributes and other attributes.It contains huge information value and plays an important role in various aspects of daily life such as map navigation and smart cities.By collecting and managing the past temporal and spatial trajectory data of vehicles and pedestrians and using big data technology to analyze the operation status of vehicles and the movement rules of people,it can effectively alleviate the problem of urban traffic congestion and improve the efficiency of urban travel.Therefore,how to store and manage massive historical trajectory data has become a hot issue that needs to be solved urgently.At the same time,with the wide application of geolocation technology on the Internet,more and more applications based on location services(such as Dianping,Auto Navi maps,etc.)have begun to be favored by people,and spatial keyword query is one of its main technologies.,has become a popular research object of current spatial database,and its development has very important reference value for route planning,social recommendation,and providing good travel advice for urban traffic.In order to improve the overall operation efficiency of urban travel,this paper decomposes the problem from the perspective of managing past travel data and improving travel advice.Reasonable travel advice to avoid traffic jams.Therefore,this paper studies the distributed storage and query system for trajectory data,and the Top-K space keyword query algorithm based on TKG-tree index.On the one hand,this paper adopts the method of combining distributed storage and multi-dimensional spatiotemporal indexing,proposes a distributed storage and query system for trajectory data,and designs the column family storage mode of HBase to meet the multi-dimensional unstructured requirements of spatiotemporal data.Using the object ID +time as the table row key,preserving the integrity of the trajectory data,and building an NDTR-tree index for space-time query and a B+-tree index for attribute query on the data,and designing the corresponding query algorithm to improve access speed.The experimental results show that the query speed of this scheme is nearly two orders of magnitude faster than the original HBase method,and it can effectively store and query large-scale spatiotemporal data.On the other hand,this paper considers the influence of time factor on the query of nearest neighbor spatial keywords and proposes a Top-K spatial keyword query algorithm based on TKG-tree index.The method uses the shortest transit time and the TF-IDF model as measures of object spatial proximity and text similarity,respectively.Combining the inverted document recording the object text information with the road network index technology,a new index TKG-tree applied to the road network is proposed,and a Top-K space keyword query algorithm is designed on the basis of it.Experimental results show that the query time of the algorithm is 1 to 2 orders of magnitude faster than other methods,and it has good scalability to large-scale datasets.