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Sashi Parthasarathy

dblp:49/1937 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1999
—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 · 44% Indexing and storage engines · 44% Transaction processing and concurrency control · 13%

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

TopicWeightPapersLastEvidence papers
Indexing and storage engines › query indexing
boolean expression indexing
0.011999
Scalable Trigger Processing · ICDE 1999
Database system architecture and tuning › active database
trigger processing
0.011999
Scalable Trigger Processing · ICDE 1999
Transaction processing and concurrency control
concurrency control
0.011999
Scalable Trigger Processing · ICDE 1999

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

trigger caching · 0.0expression signatures · 0.0
YearPublicationVenuePosition
1999 Scalable Trigger Processing
abstract
Current database trigger systems have extremely limited scalability. This paper proposes a way to develop a truly scalable trigger system. Scalability to large numbers of triggers is achieved with a trigger cache to use the main memory effectively, and a memory-conserving selection predicate index based on the use of unique expression formats called expression signatures. A key observation is that if a very large number of triggers are created, many will have the same structure, except for the appearance of different constant values. When a trigger is created, tuples are added to special relations created for expression signatures to hold the trigger's constants. These tables can be augmented with a database index or main-memory index structure to serve as a predicate index. The design presented also uses a number of types of concurrency to achieve scalability, including token (tuple)-level, condition-level, rule action-level and data-level concurrency.
Eric N. Hanson, Chris Carnes, Mohan Konyala, Lloyd Noronha, Sashi Parthasarathy, J. B. Park, Albert Vernon
ICDE6