Demo Data from EDBT 2026 / reviewers in the wild / expert
Pradeep Kumar Gunda
dblp:93/4467
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 3 · 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.
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Parallel and multicore computing · 43% Cloud and datacenter computing · 28% Distributed systems · 28% | |
| Databases, data mining, and information retrieval
1 paper |
Distributed and cloud data management · 77% Query processing and optimization · 23% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing
cluster resource management and scheduling |
0.1 | 1 | 2010 | Nectar: Automatic Management of Data and Computation in Datacenters · OSDI 2010 |
Distributed systems
distributed coordination |
0.1 | 1 | 2010 | Nectar: Automatic Management of Data and Computation in Datacenters · OSDI 2010 |
Distributed and cloud data management › distributed query processing
distributed aggregation |
0.1 | 1 | 2009 | Distributed aggregation for data-parallel computing: interfaces and implementations · SOSP 2009 |
Parallel and multicore computing
data-parallel programming |
0.1 | 1 | 2008 | DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language · OSDI 2008 |
Parallel and multicore computing › data-parallel programming
distributed data-parallel execution |
0.1 | 1 | 2008 | DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language · OSDI 2008 |
Query processing and optimization › aggregation
user-defined aggregate |
0.0 | 1 | 2009 | Distributed aggregation for data-parallel computing: interfaces and implementations · SOSP 2009 |
Methods — techniques the papers use, named apart from their topics
caching · 0.1automatic management · 0.1high-level language · 0.1distributed data-parallel computing · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Nectar: Automatic Management of Data and Computation in Datacenters
Pradeep Kumar Gunda, Lenin Ravindranath, Chandramohan A. Thekkath, Li Zhuang |
OSDI | 1 |
| 2009 | Distributed aggregation for data-parallel computing: interfaces and implementationsabstractData-intensive applications are increasingly designed to execute on large computing clusters. Grouped aggregation is a core primitive of many distributed programming models, and it is often the most efficient available mechanism for computations such as matrix multiplication and graph traversal. Such algorithms typically require non-standard aggregations that are more sophisticated than traditional built-in database functions such as Sum and Max. As a result, the ease of programming user-defined aggregations, and the efficiency of their implementation, is of great current interest. Pradeep Kumar Gunda, Michael Isard |
SOSP | 2 |
| 2008 | DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language
Michael Isard, Dennis Fetterly, Mihai Budiu, Úlfar Erlingsson, Pradeep Kumar Gunda, Jon Currey |
OSDI | 6 |