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EDBT 2026 Demo / reviewers in the wild / expert

Radu-Alexandru Todor

dblp:215/4907 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—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
Graph data management · 61% Database system architecture and tuning · 30% Query processing and optimization · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph data management › graph algorithms
connected components		 0.412020
In-database connected component analysis · ICDE 2020
Graph data management
graph analytics		 0.412020
In-database connected component analysis · ICDE 2020
Database system architecture and tuning › parallel database system
massively parallel processing database		 0.412020
In-database connected component analysis · ICDE 2020
Query processing and optimization
SQL query processing		 0.112020
In-database connected component analysis · ICDE 2020

Methods — techniques the papers use, named apart from their topics

randomized algorithm · 0.4SQL · 0.4
YearPublicationVenuePosition
2020 In-database connected component analysis
abstract
We describe a Big Data-practical, SQL-implementable algorithm for efficiently determining connected components for graph data stored in a Massively Parallel Processing (MPP) relational database. The algorithm described is a linear-space, randomised algorithm, always terminating with the correct answer but subject to a stochastic running time, such that for any ε > 0 and any input graph G = 〈V,E〉 the algorithm terminates after O(log|V |) SQL queries with probability of at least 1 - ε, which we show empirically to translate to a quasi-linear runtime in practice.
Harald Bögeholz, Michael Brand, Radu-Alexandru Todor
 ICDE3