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Thomas Jagodis

dblp:01/1415 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1987
—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
Query processing and optimization · 50% Indexing and storage engines · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Indexing and storage engines
storage model
0.011987
A Query Processing Strategy for the Decomposed Storage Model · ICDE 1987
Parallel and multicore computing
parallel query processing
0.011987
A Query Processing Strategy for the Decomposed Storage Model · ICDE 1987
YearPublicationVenuePosition
1987 A Query Processing Strategy for the Decomposed Storage Model
abstract
Handling parallelism in database systems involves the specification of a storage model, a placement strategy, and a query processing strategy. An important goal is to determine the appropriate combination of these three strategies in order to obtain the best performance advantages. In this paper we present a novel and promising query processing strategy for a decomposed storage model. We discuss some of the qualitative advantages of the scheme. We also compare the performance of the proposed “pivot” strategy with conventional query processing for the n-ary storage model. The comparison is performed using the Wisconsin Benchmarks.
Setrag Khoshafian, George P. Copeland, Thomas Jagodis, Haran Boral, Patrick Valduriez
ICDE3