Demo Data from EDBT 2026 / reviewers in the wild / expert
Valeri Kim
dblp:65/991
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Query processing and optimization
parallel query processing |
0.2 | 1 | 2015 | On Improving User Response Times in Tableau · SIGMOD Conference 2015 |
Query processing and optimization
query result caching |
0.2 | 1 | 2015 | On Improving User Response Times in Tableau · SIGMOD Conference 2015 |
Visualization and visual analytics
interactive visualization |
0.2 | 1 | 2015 | On Improving User Response Times in Tableau · SIGMOD Conference 2015 |
Methods — techniques the papers use, named apart from their topics
prefetching · 0.4caching · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | On Improving User Response Times in TableauabstractThe rapid increase in data volumes and complexity of applied analytical tasks poses a big challenge for visualization solutions. It is important to keep the experience highly interactive, so that users stay engaged and can perform insightful data exploration. Query processing usually dominates the cost of visualization generation. Therefore, in order to achieve acceptable response times, one needs to utilize backend capabilities to the fullest and apply techniques, such as caching or prefetching. In this paper we discuss key data processing components in Tableau: the query processor, query caches, Tableau Data Engine [1, 2] and Data Server. Furthermore, we cover recent performance improvements related to the number and quality of remote queries, broader reuse of cached data, and application of inter and intra query parallelism. Pawel Terlecki, Marianne Shaw, Valeri Kim, Richard Michael Grantham Wesley |
SIGMOD Conference | 4 |