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Laura Yu Chen

dblp:199/6314 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

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
Database theory · 50% Query processing and optimization · 50%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization
SQL query processing
0.312017
BEAS: Bounded Evaluation of SQL Queries · SIGMOD Conference 2017

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

cardinality constraints · 0.3access schema · 0.3
YearPublicationVenuePosition
2017 BEAS: Bounded Evaluation of SQL Queries
abstract
We demonstrate BEAS, a prototype system for querying relations with bounded resources. BEAS advocates an unconventional query evaluation paradigm under an access schema A, which is a combination of cardinality constraints and associated indices. Given an SQL query Q and a dataset D, BEAS computes Q(D) by accessing a bounded fraction DQ of D, such that Q(DQ) = Q(D) and DQ is determined by A and Q only, no matter how big D grows. It identifies DQ by reasoning about the cardinality constraints of A, and fetches DQ using the indices of A. We demonstrate the feasibility of bounded evaluation by walking through each functional component of BEAS. As a proof of concept, we demonstrate how BEAS conducts CDR analyses in telecommunication industry, compared with commercial database systems.
Yang Cao 0012, Wenfei Fan, Yanghao Wang, Tengfei Yuan, Laura Yu Chen
SIGMOD Conference6