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Emy Tseng

dblp:00/3946 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1993
—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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 77% High-performance computing · 23%
Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 100%

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

TopicWeightPapersLastEvidence papers
Query processing and optimization › query rewriting › query transformation
query decomposition		 0.011993
Parallel Database Processing on the KSR1 Computer · SIGMOD Conference 1993
Parallel and multicore computing › parallel computing › parallel database systems
parallel database processing		 0.011993
Parallel Database Processing on the KSR1 Computer · SIGMOD Conference 1993

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

query decomposition · 0.0data partitioning · 0.0
YearPublicationVenuePosition
1993 Parallel Database Processing on the KSR1 Computer
abstract
The Kendall Square Research high performance computer (KSR1) provides a spectrum of parallel database processing techniques to achieve scalability and performance in a shared memory environment. The techniques include running multiple transactions in parallel, decomposing queries into parallel subqueries, running multiple instances of the DBMS and partitioning data over disks. These techniques enable on-line transactions to be run in parallel at high throughput rates and decision-support queries to be parallelized and executed very rapidly.This paper focuses upon two of the parallel database processing techniques used on the KSR1—the Kendall Square Query Decomposer and the Oracle Parallel Server. The Query Decomposer intercepts costly decision support queries and decomposes them into subqueries which are executed in parallel. Parallel Server enables multiple ORACLE instances to run simultaneously on the same database.
Emy Tseng, David S. Reiner
 SIGMOD Conference1