Brian E. Hart

dblp:38/1663 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1990
—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 system architecture and tuning · 70% Indexing and storage engines · 23% Transaction processing and concurrency control · 7%

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

TopicWeightPapersLastEvidence papers
Indexing and storage engines › partitioning
data declustering
0.011990
Prototyping Bubba, A Highly Parallel Database System · IEEE Trans. Knowl. Data Eng. 1990
Database system architecture and tuning
horizontal partitioning
0.011990
Prototyping Bubba, A Highly Parallel Database System · IEEE Trans. Knowl. Data Eng. 1990
Database system architecture and tuning
parallel database system
0.011990
Prototyping Bubba, A Highly Parallel Database System · IEEE Trans. Knowl. Data Eng. 1990
Database system architecture and tuning › parallel database system
shared-nothing architecture
0.011990
Prototyping Bubba, A Highly Parallel Database System · IEEE Trans. Knowl. Data Eng. 1990
Transaction processing and concurrency control
distributed transaction management
0.011990
Prototyping Bubba, A Highly Parallel Database System · IEEE Trans. Knowl. Data Eng. 1990

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

range partitioning · 0.0hashing · 0.0
YearPublicationVenuePosition
1990 Prototyping Bubba, A Highly Parallel Database System
abstract
Bubba is a highly parallel computer system for data-intensive applications. The basis of the Bubba design is a scalable shared-nothing architecture which can scale up to thousands of nodes. Data are declustered across the nodes (i.e. horizontally partitioned via hashing or range partitioning) and operations are executed at those nodes containing relevant data. In this way, parallelism can be exploited within individual transactions as well as among multiple concurrent transactions to improve throughput and response times for data-intensive applications. The current Bubba prototype runs on a commercial 40-node multicomputer and includes a parallelizing compiler, distributed transaction management, object management, and a customized version of Unix. The current prototype is described and the major design decisions that went into its construction are discussed. The lessons learned from this prototype and its predecessors are presented.>
Haran Boral, William Alexander, Larry Clay, George P. Copeland, Scott Danforth, Michael J. Franklin, Brian E. Hart, Marc G. Smith, Patrick Valduriez
IEEE Trans. Knowl. Data Eng.7