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Jürgen Seib

dblp:41/5014 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1991
—ORCID · none

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

Databases, data management, data science and information retrieval · 1 · 1 first-author

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 · 33% Query processing and optimization · 33% Data models and query languages · 33%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data models and query languages
datalog
0.011991
Parallelizing Datalog Programs by Generalized Pivoting · PODS 1991
Database theory
datalog evaluation
0.011991
Parallelizing Datalog Programs by Generalized Pivoting · PODS 1991
Query processing and optimization
parallel query processing
0.011991
Parallelizing Datalog Programs by Generalized Pivoting · PODS 1991
Parallel and multicore computing
parallel programming models
0.011991
Parallelizing Datalog Programs by Generalized Pivoting · PODS 1991

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

generalized pivoting · 0.0bottom-up evaluation · 0.0
YearPublicationVenuePosition
1991 Parallelizing Datalog Programs by Generalized Pivoting
abstract
A Datalog program consists of function-free Horn clause rules.The main problem in evaluating Datalog programs is to achieve an acceptable performance.The reason is, that Datalog programs usually are evaluated bottom-up to compute in an iterative way the fixpoint of the program.Given a large amount of base facts, program evaluation can be a very lengthy process.In the paper parallel processing of decomposable Datalog programs is considered to overcome this problem.A decomposable program can be evaluated in parallel such that neither a communication nor a synchronization of the processors haa to be established [WS88].The concept of generalized pivoting is proposed, which is a sufficient condition for decomposability of arbitrary Datalog programs.Moreover, the clam of completely decomposable programs is introduced and it is shown, that generalized pivoting is also a necessary condition for complete decomposability.
Jürgen Seib, Georg Lausen
PODS1