On the Expressive Power of the Relational Algebra on Finite Sets of Relation Pairs

Fletcher, George H. L.; Gyssens, Marc; Paredaens, Jan; Gucht, Dirk Van

doi:10.1109/tkde.2008.221

Cited by 19 publications

(12 citation statements)

References 11 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [12], the goal is to heuristically derive a syntactic expression whose semantics coincide with a (possibly infinite) set of data examples. The papers [13,21] are closer to our work, but both consider unirelational schemas only. The problem studied in [13] takes as input a finite set of pairs consisting of a single source relation and a single target relation, and asks whether or not there is a relational algebra expression that produces each of the target relations when evaluated on the corresponding source relation.…”

Section: Related Workmentioning

confidence: 67%

“…The papers [13,21] are closer to our work, but both consider unirelational schemas only. The problem studied in [13] takes as input a finite set of pairs consisting of a single source relation and a single target relation, and asks whether or not there is a relational algebra expression that produces each of the target relations when evaluated on the corresponding source relation. In [21], a problem similar to the preceding one is studied, except that only a rather restricted class of relational algebra expressions (essentially unions of selections) is considered.…”

Section: Related Workmentioning

confidence: 67%

“…Finally, there is a body of work on deriving a relational query or a schema mapping from one or more data examples [12,13,14,21]. In [14], a schema mapping is derived from a single data example using a particular cost model that takes into account, among other parameters, the size of the syntactic description of the schema mapping.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Designing and refining schema mappings via data examples

Alexe

Cate

Kolaitis

et al. 2011

Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data

View full text Add to dashboard Cite

A schema mapping is a specification of the relationship between a source schema and a target schema. Schema mappings are fundamental building blocks in data integration and data exchange and, as such, obtaining the right schema mapping constitutes a major step towards the integration or exchange of data. Up to now, schema mappings have typically been specified manually or have been derived using mapping-design systems that automatically generate a schema mapping from a visual specification of the relationship between two schemas.We present a novel paradigm and develop a system for the interactive design of schema mappings via data examples. Each data example represents a partial specification of the semantics of the desired schema mapping. At the core of our system lies a sound and complete algorithm that, given a finite set of data examples, decides whether or not there exists a GLAV schema mapping (i.e., a schema mapping specified by Global-and-Local-As-View constraints) that "fits" these data examples. If such a fitting GLAV schema mapping exists, then our system constructs the "most general" one.We give a rigorous computational complexity analysis of the underlying decision problem concerning the existence of a fitting GLAV schema mapping, given a set of data examples. Specifically, we prove that this problem is complete for the second level of the polynomial hierarchy, hence, in a precise sense, harder than NP-complete. This worst-case complexity analysis notwithstanding, we conduct an experimental evaluation of our prototype implementation that demonstrates the feasibility of interactively designing schema mappings using data examples. In particular, our experiments show that our system achieves very good performance in real-life scenarios.

show abstract

Section: Related Workmentioning

confidence: 67%

Section: Related Workmentioning

confidence: 67%

See 1 more Smart Citation

Designing and refining schema mappings via data examples

Alexe

Cate

Kolaitis

et al. 2011

Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data

View full text Add to dashboard Cite

show abstract

“…. , (Dn, Sn)} is co-graph-isomorphism hard [16]. Definability as defined above has been studied for the conjunctive queries (CQs) as well and has been shown to be conexptime-complete by Willard [31].…”

Section: Introductionmentioning

confidence: 99%

Definability problems for graph query languages

Antonopoulos

Neven

Servais

2013

Proceedings of the 16th International Conference on Database Theory

View full text Add to dashboard Cite

Given a graph, a relation on its nodes, and a query language Q of interest, we study the Q-definability problem which amounts to deciding whether there exists a query in Q defining precisely the given relation over the given graph. Previous research has identified the complexity of FO-and CQ-definability. In this paper, we consider the definability problem for regular paths and conjunctive regular path queries (CRPQs) over labelled graphs.

show abstract

“…If mappings are to be specified by a human expert, then this will indeed be the case. Recently, a theoretical analysis has been undertaken for this important scenario [18].…”

Section: Example 2 Consider Data Modelsmentioning

confidence: 99%

Towards a General Framework for Effective Solutions to the Data Mapping Problem

Fletcher

Wyss

2009

Journal on Data Semantics XIV

View full text Add to dashboard Cite

Abstract. Automating the discovery of mappings between structured data sources is a long standing and important problem in data management. We discuss the rich history of the problem and the variety of technical solutions advanced in the database community over the previous four decades. Based on this discussion, we develop a basic statement of the data mapping problem and a general framework for reasoning about the design space of system solutions to the problem. We then concretely illustrate the framework with the Tupelo system for data mapping discovery, focusing on the important common case of relational data sources. Treating mapping discovery as example-driven search in a space of transformations, Tupelo generates queries encompassing the full range of structural and semantic heterogeneities encountered in relational data mapping. Hence, Tupelo is applicable in a wide range of data mapping scenarios. Finally, we present the results of extensive empirical validation, both on synthetic and real world datasets, indicating that the system is both viable and effective.

show abstract

On the Expressive Power of the Relational Algebra on Finite Sets of Relation Pairs

Cited by 19 publications

References 11 publications

Designing and refining schema mappings via data examples

Designing and refining schema mappings via data examples

Definability problems for graph query languages

Towards a General Framework for Effective Solutions to the Data Mapping Problem

Contact Info

Product

Resources

About