Patterns for Indexing Large Datasets

Garima Gaur, S. Kalra, Arnab Bhattacharya
{"title":"Patterns for Indexing Large Datasets","authors":"Garima Gaur, S. Kalra, Arnab Bhattacharya","doi":"10.1145/3282308.3282314","DOIUrl":null,"url":null,"abstract":"Searching is one of the fundamental tasks in Computer Science. An intuitive way to search is to do it linearly, that is, start at the beginning of the dataset and continue till the searched-for item is found or nothing is found. However, as the volume of data increases, the response time of linear search is no longer acceptable. Indexes are designed to search through massive datasets quickly. There are a number of different ways of building complex and advanced indexes. Appropriate selection and modification of indexing structures according to dynamic business requirements is crucial for data-intensive applications. In this work, we present a few basic reusable indexing structures. These structures can be used to create advanced and complex indexing structures with lesser effort and time.","PeriodicalId":136534,"journal":{"name":"Proceedings of the 23rd European Conference on Pattern Languages of Programs","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd European Conference on Pattern Languages of Programs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3282308.3282314","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Searching is one of the fundamental tasks in Computer Science. An intuitive way to search is to do it linearly, that is, start at the beginning of the dataset and continue till the searched-for item is found or nothing is found. However, as the volume of data increases, the response time of linear search is no longer acceptable. Indexes are designed to search through massive datasets quickly. There are a number of different ways of building complex and advanced indexes. Appropriate selection and modification of indexing structures according to dynamic business requirements is crucial for data-intensive applications. In this work, we present a few basic reusable indexing structures. These structures can be used to create advanced and complex indexing structures with lesser effort and time.
索引大型数据集的模式
搜索是计算机科学的基本任务之一。一种直观的搜索方法是线性地进行搜索,也就是说,从数据集的开头开始,然后继续搜索,直到找到要搜索的项或什么都没有找到。然而,随着数据量的增加,线性搜索的响应时间不再是可以接受的。索引是用来快速搜索海量数据集的。有许多不同的方法可以构建复杂和高级的索引。根据动态业务需求适当选择和修改索引结构对于数据密集型应用程序至关重要。在这项工作中,我们提出了一些基本的可重用索引结构。这些结构可用于创建高级和复杂的索引结构,花费较少的精力和时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信