Enhanced Graph Transforming V2 Algorithm for Non-Simple Graph in Big Data Pre-Processing

Sutedi, Sutedi and Setiawan, Noor Akhmad and Adji, Teguh Bharata (2020) Enhanced Graph Transforming V2 Algorithm for Non-Simple Graph in Big Data Pre-Processing. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 32 (1). pp. 67-77. ISSN 1041-4347

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Abstract

Incapability of relational database in handling large-scale data triggers the development of NoSQL database that becomes part of a big data ecosystem. NoSQL database has different characteristics compared to the relational database. However, NoSQL database requires data from the relational database as one of the structured data sources. Therefore, data pre-processing is required to ensure proper data migration from a relational database to NoSQL database. This data pre-processing is normally called data transformation. One of the simple and understandable transformation algorithms is graph transforming algorithm. However, the algorithm has a problem in solving a non-simple graph (multigraph). This research proposes an algorithm to overcome several multigraph problems. The experimental work confirms that the algorithm proposed in this research is able to transform data from a relational database to NoSQL schema that has a minimum number of redundant attributes while the data completeness is still maintained.

Item Type: Article
Uncontrolled Keywords: SQL to NoSQL, multiple edges, loop, multigraph, graph
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Electrical and Information Technology Department
Depositing User: Sri JUNANDI
Date Deposited: 02 Jun 2025 04:32
Last Modified: 02 Jun 2025 04:33
URI: https://ir.lib.ugm.ac.id/id/eprint/17201

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