1,987 research outputs found
Queries with Guarded Negation (full version)
A well-established and fundamental insight in database theory is that
negation (also known as complementation) tends to make queries difficult to
process and difficult to reason about. Many basic problems are decidable and
admit practical algorithms in the case of unions of conjunctive queries, but
become difficult or even undecidable when queries are allowed to contain
negation. Inspired by recent results in finite model theory, we consider a
restricted form of negation, guarded negation. We introduce a fragment of SQL,
called GN-SQL, as well as a fragment of Datalog with stratified negation,
called GN-Datalog, that allow only guarded negation, and we show that these
query languages are computationally well behaved, in terms of testing query
containment, query evaluation, open-world query answering, and boundedness.
GN-SQL and GN-Datalog subsume a number of well known query languages and
constraint languages, such as unions of conjunctive queries, monadic Datalog,
and frontier-guarded tgds. In addition, an analysis of standard benchmark
workloads shows that most usage of negation in SQL in practice is guarded
negation
Query Containment for Highly Expressive Datalog Fragments
The containment problem of Datalog queries is well known to be undecidable.
There are, however, several Datalog fragments for which containment is known to
be decidable, most notably monadic Datalog and several "regular" query
languages on graphs. Monadically Defined Queries (MQs) have been introduced
recently as a joint generalization of these query languages. In this paper, we
study a wide range of Datalog fragments with decidable query containment and
determine exact complexity results for this problem. We generalize MQs to
(Frontier-)Guarded Queries (GQs), and show that the containment problem is
3ExpTime-complete in either case, even if we allow arbitrary Datalog in the
sub-query. If we focus on graph query languages, i.e., fragments of linear
Datalog, then this complexity is reduced to 2ExpSpace. We also consider nested
queries, which gain further expressivity by using predicates that are defined
by inner queries. We show that nesting leads to an exponentially increasing
hierarchy for the complexity of query containment, both in the linear and in
the general case. Our results settle open problems for (nested) MQs, and they
paint a comprehensive picture of the state of the art in Datalog query
containment.Comment: 20 page
A Robust Logical and Computational Characterisation of Peer-to-Peer Database Systems
In this paper we give a robust logical and computational characterisation of peer-to-peer (p2p) database systems. We first define a precise model-theoretic semantics of a p2p system, which allows for local inconsistency handling. We then characterise the general computational properties for the problem of answering queries to such a p2p system. Finally, we devise tight complexity bounds and distributed procedures for the problem of answering queries in few relevant special cases
Four Lessons in Versatility or How Query Languages Adapt to the Web
Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”
Rewritability in Monadic Disjunctive Datalog, MMSNP, and Expressive Description Logics
We study rewritability of monadic disjunctive Datalog programs, (the
complements of) MMSNP sentences, and ontology-mediated queries (OMQs) based on
expressive description logics of the ALC family and on conjunctive queries. We
show that rewritability into FO and into monadic Datalog (MDLog) are decidable,
and that rewritability into Datalog is decidable when the original query
satisfies a certain condition related to equality. We establish
2NExpTime-completeness for all studied problems except rewritability into MDLog
for which there remains a gap between 2NExpTime and 3ExpTime. We also analyze
the shape of rewritings, which in the MMSNP case correspond to obstructions,
and give a new construction of canonical Datalog programs that is more
elementary than existing ones and also applies to formulas with free variables
Datalog Rewritability of Disjunctive Datalog Programs and its Applications to Ontology Reasoning
We study the problem of rewriting a disjunctive datalog program into plain
datalog. We show that a disjunctive program is rewritable if and only if it is
equivalent to a linear disjunctive program, thus providing a novel
characterisation of datalog rewritability. Motivated by this result, we propose
weakly linear disjunctive datalog---a novel rule-based KR language that extends
both datalog and linear disjunctive datalog and for which reasoning is
tractable in data complexity. We then explore applications of weakly linear
programs to ontology reasoning and propose a tractable extension of OWL 2 RL
with disjunctive axioms. Our empirical results suggest that many non-Horn
ontologies can be reduced to weakly linear programs and that query answering
over such ontologies using a datalog engine is feasible in practice.Comment: 14 pages. To appear at AAAI-1
Eliminating Recursion from Monadic Datalog Programs on Trees
We study the problem of eliminating recursion from monadic datalog programs
on trees with an infinite set of labels. We show that the boundedness problem,
i.e., determining whether a datalog program is equivalent to some nonrecursive
one is undecidable but the decidability is regained if the descendant relation
is disallowed. Under similar restrictions we obtain decidability of the problem
of equivalence to a given nonrecursive program. We investigate the connection
between these two problems in more detail
- …