Design and Implementation of a ROLAP Cube in Scalable Distributed Data Structure

Authors

  • Amel Mechri LEPCI Laboratory, Ferhat Abbas Setif 1 University, Algeria
  • Bilal Bouaita Salah Boubnider Constantine 3 University, Algeria | LEPCI Laboratory, Setif 1 University, Algeria
  • Djamel Eddine Zegour LCSI Laboratory, High School of Computer Science (ESI), Algiers, Algeria
  • Walid Khaled Hidouci LCSI Laboratory, High School of Computer Science (ESI), Algiers, Algeria
Volume: 15 | Issue: 1 | Pages: 20279-20284 | February 2025 | https://doi.org/10.48084/etasr.9648

Abstract

The Scalable Distributed Data Structure (SDDS) is a data model specifically designed for distributed environments. An SDDS file comprises records that are dynamically distributed across servers using an SDDS algorithm. A notable feature of SDDS is the removal of a centralized addressing component, simplifying client-server communication and reducing both the message count and data access time in distributed systems. This work also explores a Data Warehouse (DW) within a decision support system, where multidimensional data are represented as a cube and managed through Relational Online Analytical Processing (ROLAP). Although extensive research has been conducted in both the data warehousing and SDDS fields, no prior studies have combined these two areas. This paper introduces a novel approach to implementing a ROLAP cube within an SDDS using the Linear Hashing algorithm (LH*), which eliminates centralized addressing, enabling direct client-server communication and improving performance by reducing inter-site message exchanges. This work demonstrates the feasibility of this method and its positive impact on data processing efficiency in distributed systems.

Keywords:

SDDS, dynamic linear hashing, linear hashing algorithm LH*, data warehouse, ROLAP cube

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How to Cite

[1]
Mechri, A., Bouaita, B., Zegour, D.E. and Hidouci, W.K. 2025. Design and Implementation of a ROLAP Cube in Scalable Distributed Data Structure. Engineering, Technology & Applied Science Research. 15, 1 (Feb. 2025), 20279–20284. DOI:https://doi.org/10.48084/etasr.9648.

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