Big Data Warehouse

Author:

Dehdouh Khaled1,Boussaid Omar2,Bentayeb Fadila3

Affiliation:

1. Computer Engineering Department of Cherchell Military Academy, TIPAZA Algeria

2. ERIC Laboratory/ University of Lyon 2, Bron, France

3. ERIC Laboratory/ University of Lyon, Lyon 2, Bron, France

Abstract

In the Big Data warehouse context, a column-oriented NoSQL database system is considered as the storage model which is highly adapted to data warehouses and online analysis. Indeed, the use of NoSQL models allows data scalability easily and the columnar store is suitable for storing and managing massive data, especially for decisional queries. However, the column-oriented NoSQL DBMS do not offer online analysis operators (OLAP). To build OLAP cubes corresponding to the analysis contexts, the most common way is to integrate other software such as HIVE or Kylin which has a CUBE operator to build data cubes. By using that, the cube is built according to the row-oriented approach and does not allow to fully obtain the benefits of a column-oriented approach. In this article, the focus is to define a cube operator called MC-CUBE (MapReduce Columnar CUBE), which allows building columnar NoSQL cubes according to the columnar approach by taking into account the non-relational and distributed aspects when data warehouses are stored.

Publisher

IGI Global

Subject

Modeling and Simulation,General Computer Science

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