Demo Data from EDBT 2026 / reviewers in the wild / expert
Manuel A. Penaloza
dblp:74/4448
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1992
—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.
| Databases, data mining, and information retrieval
1 paper |
Query processing and optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 50% Interconnection networks and networks-on-chip · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Query processing and optimization
join processing |
0.0 | 1 | 1992 | Parallel Algorithms for Executing Joins on Cube-Conneced Multicomputers · ICDE 1992 |
Query processing and optimization › join processing
parallel join |
0.0 | 1 | 1992 | Parallel Algorithms for Executing Joins on Cube-Conneced Multicomputers · ICDE 1992 |
Interconnection networks and networks-on-chip › network topology › hypercubic networks
hypercube |
0.0 | 1 | 1992 | Parallel Algorithms for Executing Joins on Cube-Conneced Multicomputers · ICDE 1992 |
Parallel and multicore computing
parallel algorithms |
0.0 | 1 | 1992 | Parallel Algorithms for Executing Joins on Cube-Conneced Multicomputers · ICDE 1992 |
Methods — techniques the papers use, named apart from their topics
dynamic order-preserving partitioning · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1992 | Parallel Algorithms for Executing Joins on Cube-Conneced MulticomputersabstractThe authors present parallel processing of database joins in a hypercube system based on a dynamic and order-preserving data partitioning storage organization referred to as DYOP. A DYOP file system corresponds to a grid-based file organization. A grid-based file is any file organization where the n-field (attribute) records of a file are represented as points in an n-dimensional space. Such a hyperspace is divided into a set of hyperrectangles, each of which corresponds to a disk block. In DYOP, values along each attribute are stored in an order-preserving fashion. As the file grows, its partitions are split along a dimension (attribute) by preserving the order of values. As the file growth continues, further splits are performed in such a way that each split occurs along a different attribute in a cyclic fashion. There have been two previous studies in implementing a database join operation on hypercubes. A performance comparison of these studies is presented.> Manuel A. Penaloza, Esen A. Ozkarahan |
ICDE | 1 |