MapReduce Based Scalable Range Query Architecture for Big Spatial Data

被引：1

作者：

Eken, Suleyman ^{[1
]}

Kizgindere, Umut ^{[1
]}

Sayar, Ahmet ^{[1
]}

机构：

[1] Kocaeli Univ, Dept Comp Engn, Engn Fac, Umuttepe Campus, TR-41380 Izmit, Kocaeli, Turkey

来源：

RISE OF BIG SPATIAL DATA | 2017年

关键词：

Big spatial data; Range query; MapReduce; Scalability; IMAGES;

D O I：

10.1007/978-3-319-45123-7_19

中图分类号：

P9 [自然地理学]; K9 [地理];

学科分类号：

0705 ; 070501 ;

摘要：

Finding all objects that overlap a given range query is very important in terms of extraction useful information from big spatial data. In this study, in order to be able to realize range query on large amounts of spatial data, three datasets are created with different size and a MapReduce computation model is set up to test scalability of range queries. Experimental results show that process times for range query reduce with increase of conventional machines.

引用

页码：263 / 272

页数：10

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