Open AccessPROVIDING R-TREE SUPPORT FOR MONGODB
Author(s) -
Longgang Xiang,
Xiaotian Shao,
Dehao Wang
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b4-545-2016
Subject(s) - nosql , computer science , geospatial analysis , oracle , spatial database , tree (set theory) , database , big data , spatial query , index (typography) , relational database , sql , variety (cybernetics) , data mining , relational database management system , spatial analysis , information retrieval , world wide web , sargable , geography , search engine , web search query , cartography , artificial intelligence , remote sensing , mathematical analysis , software engineering , mathematics
Supporting large amounts of spatial data is a significant characteristic of modern databases. However, unlike some mature relational databases, such as Oracle and PostgreSQL, most of current burgeoning NoSQL databases are not well designed for storing geospatial data, which is becoming increasingly important in various fields. In this paper, we propose a novel method to provide R-tree index, as well as corresponding spatial range query and nearest neighbour query functions, for MongoDB, one of the most prevalent NoSQL databases. First, after in-depth analysis of MongoDB’s features, we devise an efficient tabular document structure which flattens R-tree index into MongoDB collections. Further, relevant mechanisms of R-tree operations are issued, and then we discuss in detail how to integrate R-tree into MongoDB. Finally, we present the experimental results which show that our proposed method out-performs the built-in spatial index of MongoDB. Our research will greatly facilitate big data management issues with MongoDB in a variety of geospatial information applications.