Efficient query reformulation in peer data management systems

Abstract

Peer data management systems (PDMS) offer a flexible architecture for decentralized data sharing. In a PDMS, every peer is associated with a schema that represents the peer's domain of interest, and semantic relationships between peers are provided locally between pairs (or small sets) of peers. By traversing semantic paths of mappings, a query over one peer can obtain relevant data from any reachable peer in the network. Semantic paths are traversed by reformulating queries at a peer into queries on its neighbors.Naively following semantic paths is highly inefficient in practice. We describe several techniques for optimizing the reformulation process in a PDMS and validate their effectiveness using real-life data sets. In particular, we develop techniques for pruning paths in the reformulation process and for minimizing the reformulated queries as they are created. In addition, we consider the effect of the strategy we use to search through the space of reformulations. Finally, we show that pre-computing semantic paths in a PDMS can greatly improve the efficiency of the reformulation process. Together, all of these techniques form a basis for scalable query reformulation in PDMS.To enable our optimizations, we developed practical algorithms, of independent interest, for checking containment and minimization of XML queries, and for composing XML mappings.

Approximate Rewriting of Queries Using Views

“…Of special interest in this context are maximally contained rewritings (MCRs), which can be used to obtain a maximal subset of the query answers that can be obtained using the given views (see, e.g., [10,4,11,12,13]). In addition, in applications such as querying the World-Wide Web, mass marketing, searching for clues related to terrorism suspects, or peer data-management systems (see, e.g., [14,15]), users prefer to get a superset of the query answers, rather than getting no answers at all (when no equivalent or contained rewritings exist). In such scenarios, users might be interested in containing rewritings, which return a superset of the set of the query answers.…”

Inconsistency Tolerance in P2P Data Integration: An Epistemic Logic Approach

“…Recent papers focused on providing techniques for evolving from basic P2P networks supporting only file exchanges to more complex systems like schema-based P2P networks, capable of supporting the exchange of structured contents. From papers like [19,4,18,10,16,27] the idea of peer data management emerges: every peer is characterized by a schema that represents the domain of interest from the peer perspective, and is equipped with mappings to other peers [25], each mapping providing a semantic relationship between pairs of peers. Data integration in such systems is typically virtual: data stored in one peer is not replicated in other peers, and when a query is posed to a peer, query processing is done by both looking at local data, and collecting relevant data from other peers according to the mappings.…”

Information Integration

“…In LRM, the interaction between peer databases is defined with coordination rules and translation rules. [15], [26] propose a peer data management system (PDMS) to manage structured data in a decentralized manner. It describes a formalism, named P P L (PeerProgramming Language), for defining mappings between peer schemas.…”

“…It describes a formalism, named P P L (PeerProgramming Language), for defining mappings between peer schemas. [26] provides the query reformulation algorithm that reformulates a query Q over a peer schema to a query Q over the actual data sources in the peers.…”