scholarly journals Query Lifting

Author(s):  
Wilmer Ricciotti ◽  
James Cheney

AbstractLanguage-integrated query based on comprehension syntax is a powerful technique for safe database programming, and provides a basis for advanced techniques such as query shredding or query flattening that allow efficient programming with complex nested collections. However, the foundations of these techniques are lacking: although SQL, the most widely-used database query language, supports heterogeneous queries that mix set and multiset semantics, these important capabilities are not supported by known correctness results or implementations that assume homogeneous collections. In this paper we study language-integrated query for a heterogeneous query language $$\mathcal {NRC}_{\lambda }( Set,Bag )$$ NRC λ ( S e t , B a g ) that combines set and multiset constructs. We show how to normalize and translate queries to SQL, and develop a novel approach to querying heterogeneous nested collections, based on the insight that “local” query subexpressions that calculate nested subcollections can be “lifted” to the top level analogously to lambda-lifting for local function definitions.

Author(s):  
Z. Abdul-Mehdi

This article will highlight the framework opted by the authors in developing a database query system for usage on mobile phones. As the development work is still in progress, the authors will share some of the approaches taken in developing a prototype for a relationally complete database query language. This work concentrates on developing an application-independent, relationally complete database query language. The remainder of this article is organized as follows. The next section presents some of the existing work related to the study. We then introduce and describe the framework undertaken in order to develop a database query system for mobile phones, and discuss the prototype of the database query language used by the system. We end with our conclusion.


Author(s):  
Magdalena Ortiz

The development of tools and techniques for flexible and reliable data management is a long-standing challenge, ever more pressing in today’s data-rich world. We advocate using domain knowledge expressed in ontologies to tackle it, and summarize some research efforts to this aim that follow two directions. First, we consider the problem of ontology-mediated query answering (OMQA), where queries in a standard database query language are enriched with an ontology expressing background knowledge about the domain of interest, used to retrieve more complete answers when querying incomplete data. We discuss some of our contributions to OMQA, focusing on (i) expressive languages for OMQA, with emphasis on combining the open- and closed-world assumptions to reason about partially complete data; and (ii) OMQA algorithms based on rewriting techniques. The second direction we discuss proposes to use ontologies to manage evolving data. In particular, we use ontologies to model and reason about constraints on datasets, effects of operations that modify data, and the integrity of the data as it evolves.


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