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John Sieg Jr.

dblp:41/5661 · DBLP profile ↗
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2ranked-venue papers
1as 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 · 2 · 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.

Databases, data mining, and information retrieval
2 papers
Data models and query languages · 46% Indexing and storage engines · 30% Query processing and optimization · 23%
Software engineering, system software, and programming languages
1 paper
Compilers and program optimization · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Indexing and storage engines
access methods
0.011990
Extended Relations · ICDE 1990
Data models and query languages › relational algebra
extended relational algebra
0.011990
Extended Relations · ICDE 1990
Query processing and optimization
query optimization
0.011990
A Modular Query Optimizer Generator · ICDE 1990
Data models and query languages
relational algebra
0.011990
Extended Relations · ICDE 1990
Indexing and storage engines
secondary index
0.011990
Extended Relations · ICDE 1990

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

tuple identifier algebra · 0.0
YearPublicationVenuePosition
1990 A Modular Query Optimizer Generator
abstract
An examination is made of existing rule-based optimizers, showing that they have significant limitations. A new approach to optimization based on the idea of modules is presented. An optimizer is divided into several interconnected modules. Each module has its own set of rewrite rules and can be implemented differently according to how the rules are used. This modular approach avoids the limitations of existing systems and supports flexible optimizer prototyping, efficient optimize-time search, and convenient access to metadata. To illustrate these ideas, a decomposition into modules is given for an example relational query optimizer.>
Edward Sciore, John Sieg Jr.
ICDE2
1990 Extended Relations
abstract
A description is given of extended relations, a generalization of ordinary relations in which tuple identifiers (tids) can appear as attribute values. The relational algebra is extended to include new operators that manipulate these tids; the resulting algebra is called the tid-algebra. The theorems of the tid-algebra are shown to provide a formal basis for optimizer transformations that involve high-level access structures. Three particular access structures-secondary indices, join indices, and join extensions-are examined in detail.>
John Sieg Jr., Edward Sciore
ICDE1