基于MapReduce的时空数据模型设计方法

Design Method of GIS Spatio-Temporal Data Model Based on MapReduce

针对时空数据存储与查询问题,传统方法存在硬件成本高,存储效率低等缺点。通过对MapReduce模型和Hadoop框架等云计算核心技术的分析和研究,提出了一种基于Hadoop的时空数据存储模型,并在此模型的基础上,设计了基于MapReduce的时空数据查询并行化框架。该框架通过对时空数据的并行操作,使其适用于海量时空数据的存储与管理。

Using traditional methods to solve the storage and query of the spaio-temporal data exists several disadvantages such as the high cost of hardware and low storage efficiency.After analyzing and researching the MapReduce model,Hadoop framework and other cloud computing core technology,this paper presents a spaio-temporal data storage model based on Hadoop and designs the spaio temporal data query parallelization framework based on MapReduce.The framework based on the parallel operation of spatio-temporal data is applicable for massive spatio-temporal data storage and management.