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Anna Wagner

dblp:148/2221 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 67% Data models and query languages · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization
query rewriting
0.212014
Complex SQL Predicates as Quantifiers · IEEE Trans. Knowl. Data Eng. 2014
Query processing and optimization › query execution
relational operators
0.212014
Complex SQL Predicates as Quantifiers · IEEE Trans. Knowl. Data Eng. 2014
Data models and query languages
SQL
0.212014
Complex SQL Predicates as Quantifiers · IEEE Trans. Knowl. Data Eng. 2014

Methods — techniques the papers use, named apart from their topics

dynamic programming · 0.2
YearPublicationVenuePosition
2014 Complex SQL Predicates as Quantifiers
abstract
We propose a logical framework to analyze complex predicates (those involving a subquery) in SQL. We propose a new operator in the relational algebra for handling such predicates, and study its properties and how it combines with traditional relational operator. We focus on predicates of the form att θ MOD S, where att is an attribute, θ a comparison operator, MOD is one of SOME or ALL, and S is a (correlated or non-correlated) subquery. We provide a formal characterization of these predicate, as well as an implementation and optimization strategies for it. We show that our approach is extendible, so we can support the expression and optimization of other, similar predicates. Finally, we describe experimental evidence that the proposed approach is more efficient than the traditional approach across a variety of conditions.
Antonio Badia, Anna Wagner
IEEE Trans. Knowl. Data Eng.2