Demo Data from EDBT 2026 / reviewers in the wild / expert
K. Bernhard Schiefer
dblp:95/5216
· DBLP profile ↗
7ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 7 · 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
4 papers |
Query processing and optimization · 51% Data integration and cleaning · 26% Database system architecture and tuning · 15% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Storage systems · 79% Memory systems · 21% |
Topics — the 7 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data integration and cleaning
integrity constraint discovery |
0.0 | 1 | 2001 | Discovery and Application of Check Constraints in DB2 · ICDE 2001 |
Query processing and optimization › semantic query processing
semantic query optimization |
0.0 | 1 | 1999 | Implementation of Two Semantic Query Optimization Techniques in DB2 Universal Database · VLDB 1999 |
Query processing and optimization › query execution › scan processing
index scan |
0.0 | 1 | 1995 | Estimating Page Fetches for Index Scans with Finite LRU Buffers · VLDB J. 1995 |
Storage systems
buffer management |
0.0 | 1 | 1995 | Estimating Page Fetches for Index Scans with Finite LRU Buffers · VLDB J. 1995 |
Indexing and storage engines
b+-tree |
0.0 | 1 | 1994 | Estimating Page Fetches for Index Scans with Finite LRU Buffers · SIGMOD Conference 1994 |
Query processing and optimization
cardinality estimation |
0.0 | 1 | 1994 | Estimating Page Fetches for Index Scans with Finite LRU Buffers · SIGMOD Conference 1994 |
Memory systems
cache management |
0.0 | 1 | 1994 | Estimating Page Fetches for Index Scans with Finite LRU Buffers · SIGMOD Conference 1994 |
Methods — techniques the papers use, named apart from their topics
semantic rewriting · 0.0empirical modeling · 0.0constraint propagation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Discovery and Application of Check Constraints in DB2abstractThe traditional role of integrity constraints is to protect the integrity of data, but integrity constraints can and do play other roles in databases; for example, they can be used for query optimization. In this role, they do not need to model the domain; it is sufficient that they describe regularities that are true about the data currently stored in a database. In this paper, we describe two algorithms for finding such regularities (in the syntactic form of check constraints) and discuss some of their applications in DB2. In particular, we show their use in query optimization. Jarek Gryz, K. Bernhard Schiefer, Calisto Zuzarte |
ICDE | 2 |
| 2000 | Performance of DB2 Enterprise-Extended Edition on NT with Virtual Interface Architecture
Sivakumar Harinath, Robert L. Grossman, K. Bernhard Schiefer, Xun Xue, Sadique Syed |
EDBT | 3 |
| 1999 | Implementation of Two Semantic Query Optimization Techniques in DB2 Universal Database
Jarek Gryz, Fred Koo, T. Y. Cliff Leung, Linqi Liu, K. Bernhard Schiefer |
VLDB | 7 |
| 1998 | IBM's DB2 Universal Database demonstrations at VLDB'98
K. Bernhard Schiefer, Jim Kleewein, Karen Brannon, Guy M. Lohman, Gene Fuh |
VLDB | 1 |
| 1995 | Estimating Page Fetches for Index Scans with Finite LRU Buffers
Arun N. Swami, K. Bernhard Schiefer |
VLDB J. | 2 |
| 1994 | On the Estimation of Join Result Sizes
Arun N. Swami, K. Bernhard Schiefer |
EDBT | 2 |
| 1994 | Estimating Page Fetches for Index Scans with Finite LRU BuffersabstractWe describe an algorithm for estimating the number of page fetches for a partial or complete scan of a B-tree index. The algorithm obtains estimates for the number of page fetches for an index scan when given the number of tuples selected and the number of LRU buffers currently available. The algorithm has an initial phase that is performed exactly once before any estimates are calculated. This initial phase, involving LRU buffer modeling, requires a scan of all the index entries and calculates the number of page fetches for different buffer sizes. An approximate empirical model is obtained from this data. Subsequently, an inexpensive estimation procedure is called by the query optimizer whenever it needs an estimate of the page fetches for the index scan. This procedure utilizes the empirical model obtained in the initial phase. Arun N. Swami, K. Bernhard Schiefer |
SIGMOD Conference | 2 |