Submit an Article
Become a reviewer
Vol 208
Pages:
249
Download volume:

The choice of data relations storing in informational systems

Authors:
M. V. Kopeikin1
V. V. Spiridonov2
E. O. Shumova3
About authors
  • 1 — National Mineral Resources University (Mining University)
  • 2 — National Mineral Resources University (Mining University)
  • 3 — National Mineral Resources University (Mining University)
Date submitted:
2013-08-27
Date accepted:
2013-10-07
Date published:
2014-02-01

Abstract

Storing and processing data of mineral resources usually imply large amounts of data. So increasing data search operation speed is the subject of a notable interest.  User of any relational data base, as a rule, imagines it as a set of normalized relations (tables). These tables, at the physical level, can be represented in the different ways.  The paper is dedicated to the analysis and comparison of cortege (traditional) and domain (transposed) ways of storing data relations.

Go to volume 208

References

  1. Алгоритмы: Построение и анализ: Пер. с англ. / Томас Х.Кормен, Чарльз И.Лейзерсон, Рональд Л.Ривест, Клиффорд Штайн. М., 2007.
  2. Кнут Д. Искусство программирования для ЭВМ. Сортировка и поиск. М., 2000. Т.3.
  3. Конноли Т. Базы данных: проектирование, реализация и сопровождение. Теория и практика / Т.Конноли, К.Бегг, A.Страчан. М., 2000.

Similar articles

Role of the state in innovative development of oil and gas complex (on the example of Russia and Norway)
2014 E. G. Katysheva
Branch approach to training of specialists in the field of the public and municipal administration for resource-extraction
2014 M. M. Khaikin
Method of identifying models of electronic equipment failure of automation control of dynamic systems
2014 A. A. Klavdiev, O. V. Afanaseva
Model of formation market value vertically integrated oil company
2014 I. V. Burenina, A. K. Barieva, S. V. Ermish
Representation and processing of knowledge in information automated systems of intelligent field
2014 E. B. Mazakov
Classification of the finite algebra concepts for the description of neural network elements
2014 I. V. Ivanova