Demo Data from EDBT 2026 / reviewers in the wild / expert
Ila Miller
dblp:17/949
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1987
—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 |
Query processing and optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 77% Performance modeling and evaluation · 23% |
Topics — the 3 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 | 1987 | Tree Structured Multiple Processor Join Methods · ICDE 1987 |
Query processing and optimization › join processing
parallel join |
0.0 | 1 | 1987 | Tree Structured Multiple Processor Join Methods · ICDE 1987 |
Parallel and multicore computing
parallel query processing |
0.0 | 1 | 1987 | Tree Structured Multiple Processor Join Methods · ICDE 1987 |
Methods — techniques the papers use, named apart from their topics
hashing · 0.0cost analysis · 0.0semijoin · 0.0semi-join · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1987 | Tree Structured Multiple Processor Join MethodsabstractThis paper summarizes the execution cost of join operations performed by parallel executing processors. Four different parallel join algorithms are proposed for execution on multiple processing nodes interconnected on a tree structured communication network. Secondary storage is accessed in parallel by leaf nodes. An average execution cost analysis is presented for the multiple processor join methods. For a reasonable ratio of result to operand cardinality, joins which use hashing for semi-join of operands at the leaf node secondary storage interface are predicted to perform better than nested-loop and sort-merge joins. Both node memory capacity and join result cardinality have a large influence on the relative performance of the join methods. This analysis method forms a basis for selecting among alternative processing methods for statically linked, multiple processor computer architectures. Roger K. Shultz, Ila Miller |
ICDE | 2 |