面向大数据管理的树形数据结构和高效索引技术:综合研究

Dimitrios Samoladas, Christos N. Karras, Aristeidis Karras, Leonidas Theodorakopoulos, S. Sioutas
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引用次数: 1

摘要

在数据来自多元来源的现代时代,人们迫切需要以高效而有效的方式处理这些数据。因此,需要这种功能的应用程序应该使用能够执行快速索引操作的数据结构和索引机制,同时在插入、删除和搜索方面具有较低的复杂性。在这项工作中,我们调查了B+树、四叉树、kD树、R树和其他有效的大数据管理索引技术,以便向读者提供该领域的一般概述。最后,我们根据插入操作和响应时间提供了一些索引实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tree Data Structures and Efficient Indexing Techniques for Big Data Management: A Comprehensive Study
In the modern era where data is produced from multivariate sources, there is an urge to handle such data in an efficient yet effective manner. Therefore, applications that necessitate such capabilities shall make use of data structures and indexing mechanisms that can perform fast index operations along with low complexity as per insertion, deletion, and search. In this work, we survey B+ Tree, QuadTree, kD Tree, R Tree, and others along with efficient indexing techniques for big data management in order to provide a generic overview of the field to readers. Ultimately, we provide some indexing experiments as per insert operations and response times.
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