吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

MapReduce模型下基于R树索引的Skyline查询算法

李建伟, 王康平, 黄岚, 王贵参   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2015-12-29 出版日期:2016-07-26 发布日期:2016-07-20
  • 通讯作者: 黄岚 E-mail:huanglan@jlu.edu.cn

Skyline Query Algorithm Based on RTree Index in MapReduce Model

LI Jianwei, WANG Kangping, HUANG Lan, WANG Guishen   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2015-12-29 Online:2016-07-26 Published:2016-07-20
  • Contact: HUANG Lan E-mail:huanglan@jlu.edu.cn

摘要:

提出一种MapReduce并行计算模型下基于R树索引的Skyline查询算法, 解决了海量空间数据集下执行Skyline查询效率低的问题. 通过建立R树索引实现空间数据不同粒度的范围剪枝, 有效降低了分布式Skyline查询需扫描的数据规模, 提高了在MapReduce模型下Skyline查询的执行效率. 在不同数据分布下进行对比实验的结果表明, 该方法比已有算法在执行效率上更具优势.

关键词: MapReduce模型, R树索引, Skyline查询, 空间数据

Abstract:

We proposed a Skyline query algorithm based on Rtree index in MapReduce parallel computing model, which solved the low execution efficiency problems of Skyline query in the massive spatial data sets. Through the establishment of Rtree index to realize spatial data of different size range pruning, the algorithm effectively reduced the size of the data required to scan the distributed Skyline query, and improved the execution efficiency of Skyline query in MapReduce model. Comparative tests in different data distribution shows the proposed method has more advantages on efficiency than the existing algorithms.

Key words: MapReduce model, Rtree index, Skyline query, spatial data

中图分类号: 

  • TP391