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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:

期数:

2025年05期

页码:

166-172

栏目:

新型计算应用系统

出版日期:

2025-05-10

文章信息/Info

Title:

Design and Application of Spatio-temporal Databases for Non-ferrous Metals Industry

文章编号:

1673-629X(2025)05-0166-07

作者:

钱志超1; 王建国2; 赵德锋3; 冯勇1; 李英娜1; 张大骋1

1. 云南省计算机技术应用计算机重点实验室,云南 昆明 650500;

2. 中国铜业有限公司,云南 昆明 650051;

3. 云南省无线电有限公司,云南 昆明 650033

Author(s):

QIAN Zhi-chao1; WANG Jian-guo2; ZHAO De-feng3; FENG Yong1; LI Ying-na1; ZHANG Da-cheng1

1. Yunnan Province Key Laboratory of Computer Technology Application,Kunming 650500,China;

2. China Copper Corporation Limited,Kunming 650051,China;

3. Yunnan Radio Co. ,Ltd. ,Kunming 650033,China

关键词:

典型流程工业; 数据库; 时空索引; Hilbert曲线; Hbase

Keywords:

typical process industry; database; spatio-temporal index; Hilbert curve; Hbase

分类号:

TP311

DOI:

10.20165/j.cnki.ISSN1673-629X.2024.0403

摘要:

有色金属工业产生的海量数据具有高度局部性和异质性等特点,提高此类数据的存储与索引效率成为亟待解决的问题。 传统的关系型数据库因其扩展能力和性能存在局限性,难以满足当前需求,而非关系型数据库在实现高效检索方面仍存在一定的局限性。 为此,该文设计并实现了一种基于 HBase 的时空数据管理框架。 首先,构建了一种携带分片键的 RowKey 结构用于存储数据,并集成时空索引工具构建了 GeoMesa-HBase 数据存储模型;其次,将 Hilbert 曲线和 S2编码技术结合构建时空索引,提高了有色金属工业所产生数据的存储与检索效率;最后,为了验证该方法的可用性和有效性,基于所提出的存储框架搭建了应用服务平台并进行了系列性能测试。 实验结果表明,与主流的数据库(HBase、MySQL和 PostGIS)以及 GeoHash 编码相比,该方法在数据存储和查询性能上表现出了明显优势,为有色金属工业的数据管理领域所面临的多项挑战提供了重要的理论支撑和技术参考。

Abstract:

The non-ferrous metals industry generates a massive amount of data characterized by high locality and heterogeneity,making the improvement of storage and indexing efficiency for such data an urgent issue. Traditional relational databases have limitations in scalability and performance,making it difficult to meet current demands,while NoSQL databases still have certain limitations in achieving efficient retrieval. To address this,we design and implement a spatiotemporal data management framework based on HBase. Firstly,a RowKey structure with a sharding key is constructed for storing data,and a GeoMesa-HBase data storage model is built by integrating spatiotemporal indexing tools. Secondly, the Hilbert curves and S2 encoding techniques are combined to construct a spatiotemporal index,thereby improving the storage and retrieval efficiency of the data generated by the non-ferrous metals industry. Finally,to verify the feasibility and effectiveness of the proposed method, an application service platform was set up based on the proposed storage framework,and a series of performance tests were conducted. The experimental results show that compared to mainstream databases (HBase,MySQL,and PostGIS) and GeoHash encoding,the proposed method demonstrates significant advantages in terms of data storage and query performance,providing important theoretical support and technical references for addressing multiple challenges in the data management field of the non-ferrous metals industry.

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更新日期/Last Update: 2025-05-10