ỨNG DỤNG CÁC KĨ THUẬT CỦA HÌNH HỌC TÍNH TOÁN ĐỂ XÂY DỰNG CÂY PHẠM VI HỖ TRỢ BÀI TOÁN TRUY VẤN CƠ SỞ DỮ LIỆU=Applying computational geometry techniques to build data structure for range trees to assist the query for database

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Tác giả: Minh Tuyến Phạm, Thuấn Lê Thị

Ngôn ngữ: vie

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Khoa học Đại học Khánh Hòa, 2024

Mô tả vật lý: tr.57

Bộ sưu tập: Metadata

ID: 482666

Thêm vào giỏ

Cuộc cách mạng công nghiệp 4.0 đã mở ra một thời đại cho công nghệ số, vì vậy hệ thống dữ liệu được lưu trữ trên các hệ quản trị cơ dữ liệu càng lớn và phức tạp. Mối tương quan giữa tính chất hình học và cơ sở dữ liệu là phương pháp chuyển đổi các bản ghi trong một cơ sở dữ liệu thành các điểm trong không gian đa chiều và chuyển đổi các truy vấn về các bản ghi thành các truy vấn lên tập các điểm này. Trong bài báo này, chúng tôi tập trung đề xuất xây dựng cấu trúc cây phạm vi bằng các kỹ thuật của hình học tính toán để thực hiện truy vấn trên phạm vi trực giao, đồng thời cũng đề xuất giải pháp cải tiến thuật toán cây phạm vi bằng phương pháp tập điểm chung. Để chứng minh cho cơ sở lý đã đề xuất, chúng tôi tiến hành xây dựng chương trình thử nghiệm tính hiệu quả của thuật toán trên các tập dữ liệu khác nhau. Kết quả thực nghiệm được so sánh với cây KD trên cùng một bộ dữ liệu nhằm minh chứng phương pháp đề xuất mới của chúng tôi được tối ưu hóa hơn về thời gian tìm kiếmThe Fourth Industrial Revolution is the trend towards digital technologies to lead large databases and complicated database storages on Database Management System. At ﬁrst sight it seems that databases have little to do with geometry. Nevertheless, queries about data in a database can be interpreted geometrically. To this end we transform records in a database into points in a multi-dimensional space, and we transform the queries about the records into queries on this set of points. This paper proposed an approach based on computational geometry techniques for building range trees, two-dimensional range search algorithm (search range trees algorithm) and general sets of points to improve the algorithm. To prove for proposed theorem, we had experimental research of Range-Tree structure on the different datasets. The experimental results of an orthogonal range query evaluated with the recently published method of KD-Tree on the same dataset. This proof shows that our proposed method is more time-efficient in queries

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