Demo Data from VLDB 2026 / reviewers in the wild / expert
Pratap Khedkar
dblp:28/1103
· DBLP profile ↗
1ranked-venue papers
0as 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
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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 77% Performance modeling and evaluation · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems
database recovery |
0.0 | 1 | 1992 | Analysis of Recovery in a Database System Using a Write-Ahead Log Protocol · SIGMOD Conference 1992 |
Performance modeling and evaluation
analytical modeling |
0.0 | 1 | 1992 | Analysis of Recovery in a Database System Using a Write-Ahead Log Protocol · SIGMOD Conference 1992 |
Methods — techniques the papers use, named apart from their topics
queueing model · 0.0LRU buffer replacement · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1992 | Analysis of Recovery in a Database System Using a Write-Ahead Log ProtocolabstractIn this paper we examine the recovery time in a database system using a Write-Ahead Log protocol, such as ARIES [9], under the assumption that the buffer replacement policy is strict LRU. In particular, analytical equations for log read time, data I/O, log application, and undo processing time are presented. Our initial model assumes a read/write ratio of one, and a uniform access pattern. This is later generalized to include different read/write ratios, as well as a “hot set” model (i.e. x% of the accesses go to y% of the data). We show that in the uniform access model, recovery is dominated by data I/O costs, but under extreme hot-set conditions, this may no longer be true. Furthermore, since we derive anaytical equations, recovery can be analyzed for any set of parameter conditions not discussed here. Anant Jhingran, Pratap Khedkar |
SIGMOD Conference | 2 |