Extracting OLAP Cubes From Document-Oriented NoSQL Database Based on Parallel Similarity Algorithms

Today, the relational database is not suitable for data management due to the large variety and volume of data which are mostly untrusted. Therefore, NoSQL has attracted the attention of companies. Despite it being a proper choice for managing a variety of large volume data, there is a big challenge...

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Bibliographic Details
Published in:Canadian journal of electrical and computer engineering 2020-01, Vol.43 (2), p.111-118
Main Authors: Davardoost, Farnaz, Babazadeh Sangar, Amin, Majidzadeh, Kambiz
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Computational modeling
Cubes
Data management
Data models
document-oriented
locality-sensitive hashing (LSH)
MapReduce (MR)
NoSQL
NoSQL databases
Null value
Online analytical processing
online analytical processing (OLAP)
Relational data bases
Relational databases
Similarity
Unified modeling language
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Summary:Today, the relational database is not suitable for data management due to the large variety and volume of data which are mostly untrusted. Therefore, NoSQL has attracted the attention of companies. Despite it being a proper choice for managing a variety of large volume data, there is a big challenge and difficulty in performing online analytical processing (OLAP) on NoSQL since it is schema-less. This article aims to introduce a model to overcome null value in converting document-oriented NoSQL databases into relational databases using parallel similarity techniques. The proposed model includes four phases, shingling, chunck, minhashing, and locality-sensitive hashing MapReduce (LSHMR). Each phase performs a proper process on input NoSQL databases. The main idea of LSHMR is based on the nature of both locality-sensitive hashing (LSH) and MapReduce (MR). In this article, the LSH similarity search technique is used on the MR framework to extract OLAP cubes. LSH is used to decrease the number of comparisons. Furthermore, MR enables efficient distributed and parallel computing. The proposed model is an efficient and suitable approach for extracting OLAP cubes from an NoSQL database.
ISSN:0840-8688
2694-1783
DOI:10.1109/CJECE.2019.2953049