Gautam Bhargava

dblp:85/2528 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 1996
—ORCID · none

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

Databases, data management, data science and information retrieval · 4 · 4 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
4 papers
Query processing and optimization · 67% Spatial and temporal data management · 19% Database system architecture and tuning · 15%
Network and information security
1 paper
Systems and software security · 100%

Topics — the 8 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization
query optimization
0.021996
Efficient Processing of Outer Joins and Aggregate Functions · ICDE 1996
Hypergraph Based Reorderings of Outer Join Queries with Complex Predicates · SIGMOD Conference 1995
Query processing and optimization › query optimization
join enumeration
0.011995
Hypergraph Based Reorderings of Outer Join Queries with Complex Predicates · SIGMOD Conference 1995
Query processing and optimization › query optimization › join ordering
outerjoin reordering
0.011995
Hypergraph Based Reorderings of Outer Join Queries with Complex Predicates · SIGMOD Conference 1995
Query processing and optimization › query optimization › transformation-based optimization
query reordering
0.011995
Hypergraph Based Reorderings of Outer Join Queries with Complex Predicates · SIGMOD Conference 1995
Database system architecture and tuning › database security
database auditing
0.011993
Relational Database Systems with Zero Information Loss · IEEE Trans. Knowl. Data Eng. 1993
Spatial and temporal data management
temporal databases
0.011993
Relational Database Systems with Zero Information Loss · IEEE Trans. Knowl. Data Eng. 1993
Spatial and temporal data management › temporal databases
transaction time
0.011993
Relational Database Systems with Zero Information Loss · IEEE Trans. Knowl. Data Eng. 1993
Systems and software security
database security
0.011993
Relational Database Systems with Zero Information Loss · IEEE Trans. Knowl. Data Eng. 1993

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

temporal data modeling · 0.0hypergraph abstraction · 0.0dynamic programming · 0.0
YearPublicationVenuePosition
1996 Efficient Processing of Outer Joins and Aggregate Functions
abstract
Removal of redundant outer joins is essential for the reassociation of outer joins with other binary operations. We present a set of comprehensive algorithms that employ the properties of strong predicates along with the properties of aggregation, intersection, union, and except operations to remove redundant outer joins from a query. For the purpose of query simplification, we generate additional projections by determining the keys. Our algorithm for generating keys is based on a novel concept of weak bindings that is essential for queries containing outer joins. Our algorithm for converting outer joins to joins is based on a novel concept of join-reducibility.
Gautam Bhargava, Piyush Goel, Balakrishna R. Iyer
ICDE1
1995 Hypergraph Based Reorderings of Outer Join Queries with Complex Predicates
abstract
Complex queries containing outer joins are, for the most part, executed by commercial DBMS products in an "as written" manner. Only a very few reorderings of the operations are considered and the benefits of considering comprehensive reordering schemes are not exploited. This is largely due to the fact there are no readily usable results for reordering such operations for relations with duplicates and/or outer join predicates that are other than "simple." Most previous approaches have ignored duplicates and complex predicates; the very few that have considered these aspects have suggested approaches that lead to a possibly exponential number of, and redundant intermediate joins. Since traditional query graph models are inadequate for modeling outer join queries with complex predicates, we present the needed hypergraph abstraction and algorithms for reordering such queries with joins and outer joins. As a result, the query optimizer can explore a significantly larger space of execution plans, and choose one with a low cost. Further, these algorithms are easily incorporated into well known and widely used enumeration methods such as dynamic programming.
Gautam Bhargava, Piyush Goel, Balakrishna R. Iyer
SIGMOD Conference1
1993 Relational Database Systems with Zero Information Loss
abstract
Transaction time is used for time stamping object values to record their database history and formulate a zero information loss model for database transactions. The model consists of three components, a data history store, an update store, and a query store. In such a model, the effect of a past transaction (a query or an update) can be determined at any time. Additionally, the update and query stores make it possible to reconstruct the circumstances of updates and the information divulged in queries. Such a model is suitable for the design of secure, easy-to-audit database systems.>
Gautam Bhargava, Shashi K. Gadia
IEEE Trans. Knowl. Data Eng.1
1989 Achieving Zero Information-Loss in a Classical Database Environment
Gautam Bhargava, Shashi K. Gadia
VLDB1