文章基本信息

标题：A COMPREHENSIVE APPROACH FOR CONVERTING RELATIONAL TO GRAPH DATABASE USING SPARK
本地全文：下载
作者：WAEL MOHAMED ; MANAL A ; ABDEL-FATTAH 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：12
语种：English
出版社：Journal of Theoretical and Applied
摘要：Nowadays, data processing requirements is growing exponentially, and relational database is not always the best solution for all situations in big data such as increasing growth of data. Thus, NoSQL databases emerged to overcome the limitations of relational database and work with big data. NoSQL databases have four types of models, namely, key-value model, document database, column database, and graph database. Many approaches have been proposed to convert relational database to NoSQL models. However, most of them map relational database to key-value or column or document. Converting relational to graph database is slightly disregarded by the researchers.This paper proposes a comprehensive approach, based on Spark framework, for transformation and migration of relational database to graph database without semantic loss. The approach also supports conversions from Sql commands to cypher commands .It is categorized into two parts. The first part is concerned with �transformation and migration using Spark�, which encompasses three phases: Meta data analyzer, transformation algorithm, and migration algorithm. The second part focuses on �SQL to cypher�, which divides into two phases: SQL parser and Translator. The suggested approach has been applied, results and validation for the proposed approach.
关键词：Big Data;NOSQL;Graph Database;Spark;Neo