Authors:
Hagen Höpfner
1
and
Erik Buchmann
2
Affiliations:
1
School of Information Technology, International University in Germany, Germany
;
2
Institute for Program Structures and Data Organization, Universität Karlsruhe (TH), Germany
Keyword(s):
Databases, Query Indexes, Query Semantics.
Related
Ontology
Subjects/Areas/Topics:
Business Analytics
;
Communication and Software Technologies and Architectures
;
Data Engineering
;
Data Management and Quality
;
Data Semantics
;
Data Warehouses and Data Mining
;
e-Business
;
Engineering Information System
;
Enterprise Information Systems
;
Information Quality
;
Information Systems Analysis and Specification
Abstract:
Application areas like semantic caches or update relevancy checks require query based indexing: They use an algebra representation of the query tree to identify reusable fragments of former query results. This requires compact query representations, where semantically equivalent (sub-)queries are expressed with identical terms. It is challenging to obtain such query representations: Attributes and relations can be renamed, there are numerous ways to formulate equivalent selection predicates, and query languages like SQL allow a wide range of alternatives for joins and nested queries. In this paper we present our first steps towards optimizing SQL-based query trees for indexing. In particular, we use both existing equivalence rules and new transformations to normalize the sub-tree structure of query trees. We optimize selection and join predicates, and we present an approach to obtain generic names for attributes and table aliases. Finally, we discuss the benefits and limitations of o
ur intermediate results and give directions for future research.
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