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A Physical Design Strategy on a NoSQL DBMS
Published in Qurban A. Memon, Shakeel Ahmed Khoja, Data Science, 2019
Marcos Jota, Marlene Goncalves, Ritces Parra
The third limitation is the amount of NoSQL DBMS. The guidelines described herein do not necessarily apply to other DBMSs. For example, the path materialization no longer makes sense for other types of DBMSs. Also, there is no standard for the query language as with relational DBMSs. The physical design guidelines associated with the query rewriting is tied to the Cypher language of Neo4j. When the DBMS changes, the query language becomes different, and therefore, query rewriting guidelines must be rethought.
Selecting accepted assertions in partially ordered inconsistent DL-Lite knowledge bases
Published in Journal of Applied Non-Classical Logics, 2023
Sihem Belabbes, Salem Benferhat
Formal ontologies are often specified in lightweight description logic languages of the DL-Lite family (Calvanese et al., 2007) which offer a good trade-off between expressive power and computational complexity. In particular, query answering can be reduced to standard database query evaluation via query rewriting (Kontchakov et al., 2010). We recall the basics of the DL-Lite dialect which underlies the OWL 2 QL profile devoted to query answering. The DL-Lite language is built upon three countably infinite and mutually disjoint sets. These are: a set of concept names, a set of role names and a set of individual names. The syntax is recursively defined as follows: is a basic role, with and its inverse is . denotes a complex role., with , stands for a basic concept. represents a complex concept.
Interactive Visual Exploration of Big Relational Datasets
Published in International Journal of Human–Computer Interaction, 2023
Katerina Vitsaxaki, Stavroula Ntoa, George Margetis, Nicolas Spyratos
Two prominent characteristics offered by HIFUN language and that we exploit in this work are the following: (a) the clear separation between the conceptual level where analytic queries are expressed in the abstract and the physical level where queries are actually evaluated; (b) algorithms for translating abstract analytic queries to either SQL Group-by queries or to MapReduce jobs; and (c) powerful query rewriting rules that accelerate query evaluation.