Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.618496
Title: Factorisation in relational databases
Author: Zavodny, Jakub
ISNI:       0000 0004 5354 2209
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
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Abstract:
We study representation systems for relational data based on relational algebra expressions with unions, products, and singleton relations. Algebraic factorisation using the distributivity of product over union allows succinct representation of many-to-many relationships; further succinctness is brought by sharing repeated subexpressions. We show that these techniques are especially applicable to results of conjunctive queries. In the first part of the dissertation we derive tight asymptotic size bounds for two flavours of factorised representations of results of conjunctive queries. Any conjunctive query is characterised by rational parameters that govern the factorisability of its results independently of the database instance. We relate these parameters to fractional edge covers and fractional hypertree decompositions. Factorisation naturally extends from relational data to its provenance. We characterise conjunctive queries by tight bounds on their readability, which captures how many times each input tuple is used to contribute to an output tuple, and we define syntactically the class of queries with bounded readability. In the second part of the dissertation we describe FDB, a relational database engine that uses factorised representations at the physical layer to reduce data redundancy and boost query performance. We develop algorithms for optimisation and evaluation of queries with selection, projection, join, aggregation and order-by clauses on factorised representations. By introducing novel operators for factorisation restructuring and a new optimisation objective to maintain intermediate and final results succinctly factorised, we allow query evaluation with lower time complexity than on flat relations. Experiments show that for data sets with many-to-many relationships, FDB can outperform relational engines by orders of magnitude.
Supervisor: Olteanu, Dan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.618496  DOI: Not available
Keywords: Applications and algorithms ; Relational Databases ; Factorisation ; Query Processing ; Algorithms
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