Physical Data Independence, Constraints and Optimization with Universal Plans

We present an optimization method and al gorithm designed for three objectives: physi cal data independence, semantic optimization, and generalized tableau minimization. The method relies on generalized forms of chase and backchase with constraints (dependen cies). By using dictionaries (finite functions) in physical schemas we can capture with con straints useful access structures such as indexes, materialized views, source capabilities, access support relations, gmaps, etc. The search space for query plans is defined and enumerated in a novel manner: the chase phase rewrites the original query into a universal plan that integrates all the access structures and alternative pathways that are allowed by appli cable constraints. Then, the backchase phase produces optimal plans by eliminating various combinations of redundancies, again according to constraints. This method is applicable (sound) to a large class of queries, physical access structures, and semantic constraints. We prove that it is in fact complete for path-conjunctive queries and views with complex objects, classes and dictio naries, going beyond previous theoretical work on processing queries using materialized views

Query reformulation with constraints

Let Σ1, Σ2 be two schemas, which may overlap, C be a set of constraints on the joint schema Σ1 ∪ Σ2, and q1 be a Σ1-query. An (equivalent) reformulation of q1 in the presence of C is a Σ2-query, q2, such that q2 gives the same answers as q1 on any Σ1 ∪ Σ2-database instance that satisfies C. In general, there may exist multiple such reformulations and choosing among them may require, for example, a cost model

Optimization Properties for Classes of Conjunctive Regular Path Queries

We are interested in the theoretical foundations of the optimization of conjunctive regular path queries (CRPQs). The basic problem here is deciding query containment both in the absence and presence of constraints. Containment without constraints for CRPQs is EXPSPACE-complete, as opposed to only NP-complete for relational conjunctive queries. Our past experience with implementing similar algorithms suggests that staying in PSPACE might still be useful. Therefore we investigate the complexity of containment for a hierarchy of fragments of the CRPQ language. The classifying principle of the fragments is the expressivity of the regular path expressions allowed in the query atoms. For most of these fragments, we give matching lower and upper bounds for containment in the absence of constraints. We also introduce for every fragment a naturally corresponding class of constraints in whose presence we show both decidability and undecidability results for containment in various fragments. Finally, we apply our results to give a complete algorithm for rewriting with views in the presence of constraints for a fragment that contains Kleene-star and disjunction

Querying XML With Mixed and Redundant Storage

This paper examines some of the issues that arise in the process of XML publishing of mixed-storage proprietary data. We argue that such data will reside typically in RDBMS\u27s and/or LDAP, etc, augmented with a set of native XML documents. An additional challenge is to take advantage of redundancy in the storage schema, such as mixed materialized views that are stored for the purpose of enhancing performance. We argue that such systems need to take into consideration mappings in both directions between the proprietary schema and the published schema. Thus, reformulating queries on the (published) XML schema into executable queries on the stored data will require the effect of both composition-with-views (as in SilkRoute and XPERANTO) and rewriting-with-views (as in the Information Manifold and Agora). Using any of the simple encodings of relational data as XML, the mappings between schemas and the materialized views can be expressed in XQery, just like the queries on the published schema. For query reformulation we give an algorithm that uses logical assertions to capture formally the semantics of a large part of XQuery. We also give a completeness theorem for our reformulation algorithm. The algorithm was implemented in an XML query rewriting system and we present a suite of experiments that validate this technique

Integrating XML Data Sources using RDF/S Schemas: The ICS-FORTH Semantic Web Integration Middleware (SWIM)

Semantic Web (SW) technology aims to facilitate the integration of legacy data sources spread worldwide. Despite the plethora of SW languages e.g., RDF/S, OWL recently proposed for supporting large scale information interoperation, the vast majority of legacy sources still rely on relational databases RDB published on the Web or corporate intranets as virtual XML. In this paper, we advocate a Datalog framework for mediating high level queries to relational and or XML sources using community ontologies expressed in a SW language such as RDF/S. We describe the architecture and the reasoning services of our SW integration middleware, called SWIM, and we present the main design choices and techniques for supporting powerful mappings between different data models, as well as reformulation and optimization of queries expressed against mediation schemas and views

Chase & Backchase: A Method for Query Optimization With Materialized Views and Integrity Constraints

We have previously proposed chase and backchase as a novel method for using materialized views and integrity constraints in query optimization. In this paper, we show that the method is usable in realistic optimizers by extending it to bag and mixed (i.e. bag-set) semantics as well as to grouping views and by showing how to integrate it with standard cost-based optimization. We understand materialized views broadly, including user-defined views, cached queries and physical access structures (such as join indexes, access support relations, and gmaps). Moreover, our internal query representation supports object features hence the method applies to OQL and (extended) SQL: 1999 queries. Chase and backchase supports a very general class of integrity constraints, thus being able to find execution plans using views that do not fall in the scope of other methods. In fact, we prove completeness theorems that show that our method will find the best plan in the presence of common and practically important classes of constraints and views, even when bag and set semantics are mixed. We report on a series of experiments that demonstrate the practicality of our new ideas