Uncertainty Modeling of Object-Oriented Biomedical Information in HBase

Abstract

While object-oriented databases (OODBs) are known to be rich in functionality, HBase database, which is a distributed and scalable big data store, as well as uncertain databases have recently gained a lot of attention in the database community. This paper presents a methodology for handling an important step of knowledge integrations and migrations. In particular, a formal approach for reengineering fuzzy object-oriented databases in HBase is firstly developed. The reengineering approach is based on the technique of rule-based schema mapping, which defines a set of transformation rules involved in the process of schema transformations for mapping a fuzzy object-oriented database schema into a fuzzy HBase database schema. In addition, a formal approach to map the fuzzy object-oriented algebra into fuzzy HBase algebra is proposed. On this basis, we complement the work with a comprehensive set of experiments to show the efficiency of our proposed approach in terms of query time and scalability metrics. INDEX TERMS Big data store, fuzzy HBase, fuzzy object-oriented database, mapping.

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