Use this URL to cite or link to this record in EThOS:
Title: Evaluation of relational algebra queries on probabilistic databases : tractability and approximation
Author: Fink, Robert D.
ISNI:       0000 0004 5355 3282
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
Query processing is a core task in probabilistic databases: Given a query and a database that encodes uncertainty in data by means of probability distributions, the problem is to compute possible query answers together with their respective probabilities of being correct. This thesis advances the state of the art in two aspects of query processing in probabilistic databases: complexity analysis and query evaluation techniques. A dichotomy is established for non-repeating, con- junctive relational algebra queries with negation that separates #P-hard queries from those with PTIME data complexity. A framework for computing proba- bilities of relational algebra queries is presented; the probability computation algorithm is based on decomposition methods and provides exact answers in the case of exhaustive decompositions, or anytime approximate answers with absolute or relative error guarantees in the case of partial decompositions. The framework is extended to queries with aggregation operators. An experimental evaluation of the proposed algorithms’ implementations within the SPROUT query engine complements the theoretical results. The SPROUT2 system uses this query engine to compute answers to queries on uncertain, tabular Web data.
Supervisor: Olteanu, Dan Sponsor: European Research Council (ERC)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computer science (mathematics) ; Discrete mathematics (statistics) ; Probability ; Applications and algorithms ; Scalable systems ; Probabilistic database ; uncertain database ; database ; database system ; computational complexity