A Multilevel Indexing Method for Approximate Geospatial Aggregation Analysis

Luo CHEN  Ye WU  Wei XIONG  Ning JING  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.12   pp.3242-3245
Publication Date: 2018/12/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8120
Type of Manuscript: LETTER
Category: Data Engineering, Web Information Systems
aggregation computation,  approximate query,  spatial index,  online analysis,  

Full Text: PDF(409.4KB)
>>Buy this Article

In terms of spatial online aggregation, traditional stand-alone serial methods gradually become limited. Although parallel computing is widely studied nowadays, there scarcely has research conducted on the index-based parallel online aggregation methods, specifically for spatial data. In this letter, a parallel multilevel indexing method is proposed to accelerate spatial online aggregation analyses, which contains two steps. In the first step, a parallel aR tree index is built to accelerate aggregate query locally. In the second step, a multilevel sampling data pyramid structure is built based on the parallel aR tree index, which contribute to the concurrent returned query results with certain confidence degree. Experimental and analytical results verify that the methods are capable of handling billion-scale data.