Optimizing big data processing through lazy computations: a systematic review of techniques and applications

Authors

  • M.V. Talakh Yuriy Fedkovich Chernivtsi National University
  • Yu.O. Ushenko Yuriy Fedkovich Chernivtsi National University
  • E.V. Vatamanitsa Yuriy Fedkovich Chernivtsi National University
  • Yu.O. Halin Yuriy Fedkovich Chernivtsi National University

DOI:

https://doi.org/10.31649/1681-7893-2024-48-2-24-33

Keywords:

lazy operations, Big Data, data processing, optimization, data streams, computing strategies, programming languages.

Abstract

The article examines the concept of lazy operations and its application for efficient processing of large volumes of data. The main principles of lazy computations, their implementation in various programming languages, and strategies for effective use in Big Data processing are analyzed. The advantages and limitations of the lazy approach are investigated, particularly regarding memory savings, performance improvement, and the ability to work with infinite data streams. A concept for selecting computation strategies based on data size and computational complexity is proposed.

Author Biographies

M.V. Talakh, Yuriy Fedkovich Chernivtsi National University

Ph.D., assistant professor of Computer Science Department

Yu.O. Ushenko, Yuriy Fedkovich Chernivtsi National University

D.Sc.,Professor of Computer Science Department

E.V. Vatamanitsa, Yuriy Fedkovich Chernivtsi National University

assistant  professor  of  Computer  Science  Department

Yu.O. Halin, Yuriy Fedkovich Chernivtsi National University

postgraduate student of Computer Science Department

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Published

2024-11-19

How to Cite

[1]
M. . Talakh, Y. . Ushenko, E. . Vatamanitsa, and Y. Halin, “Optimizing big data processing through lazy computations: a systematic review of techniques and applications”, Опт-ел. інф-енерг. техн., vol. 48, no. 2, pp. 24–33, Nov. 2024.

Issue

Vol. 48 No. 2 (2024)

Section

OptoElectronic/Digital Methods and Systems for Image/Signal Processing

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