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Robert S. Epstein

dblp:38/2827 · also Bob Epstein · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 1995
—ORCID · none

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

Databases, data management, data science and information retrieval · 3 · 3 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
2 papers
Distributed and cloud data management · 77% Query processing and optimization · 23%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed and cloud data management › distributed query processing
communication cost optimization		 0.011978
Distributed Query Processing in a Relational Data Base System · SIGMOD Conference 1978
Query processing and optimization › query optimization
distributed query optimization		 0.011978
Distributed Query Processing in a Relational Data Base System · SIGMOD Conference 1978
Distributed and cloud data management
distributed query processing		 0.011978
Distributed Query Processing in a Relational Data Base System · SIGMOD Conference 1978

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

heuristic query decomposition · 0.0
YearPublicationVenuePosition
1995 Keynote Address
abstract
No abstract available.
Robert S. Epstein
 SIGMOD Conference1
1980 Analysis of Distributed Data Base Processing Strategies
Robert S. Epstein, Michael Stonebraker
 VLDB1
1978 Distributed Query Processing in a Relational Data Base System
abstract
In this paper we present a new algorithm for retrieving and updating data from a distributed relational data base. Within such a data base, any number of relations can be distributed over any number of sites. Moreover, a user supplied distribution criteria can optionally be used to specify what site a tuple belongs to.The algorithm is an efficient way to process any query by "breaking" the qualification into separate "pieces" using a few simple heuristics. The cost criteria considered are minimum response time and minimum communications traffic. In addition, the algorithm can optimize separately for two models of a communication network representing respectively ARPANET and ETHERNET like networks. This algorithm is being implemented as part of the INGRES data base system.
Robert S. Epstein, Michael Stonebraker, Eugene Wong 0001
 SIGMOD Conference1