Abstract: The rapid growth of the mobile internet and the internet of things generates a large amount data of spatial text object with relational attributes.Search engines for webpage text data can efficiently store and index textual data,but only support textual keyword queries.However mixed data including geographic location information,textual information,and relational attributes cannot be processed.Existing query-processing techniques for space-oriented keywords do not consider relation attributes as filter conditions.And those techniques are based on stand-alone implementation and cannot meet query performance requirements.In order to solve the above problems,this paper proposed a novel Baseline algorithm named BADKLRQ (Baseline Algorithm of Distributed Keywords and Location-aware with Relational Attributes Query) that maps attributes of relation attributes,space,and keywords into text data.The row text index indexes the converted text data.For query requests with relation attributes,space,and keywords,the query request is also converted into a plurality of text keywords in the mapping space,and the converted text data is queried.And an improved algorithm based on Baseline algorithm MGDKLRQ is proposed to improve the algorithm of converting spatial attributes into text keywords.Experiments show that the BADKLRQ algorithm improves by 10% to 15% and MGDKLRQ algorithm improves by 20% to 30% over the existing algorithm in terms of index time and query time.

Key words: Distributed index, Range query, Relation attributes, Spatial keywords