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David Brekardin

dblp:300/4595 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021

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
Distributed and cloud data management · 100%
Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed and cloud data management
distributed query processing
0.512021
Compliant Geo-distributed Data Processing in Action · Proc. VLDB Endow. 2021
Distributed and cloud data management › distributed analytics
geo-distributed analytics
0.512021
Compliant Geo-distributed Data Processing in Action · Proc. VLDB Endow. 2021
Privacy and data protection › privacy policy
dataflow policy
0.112021
Compliant Geo-distributed Data Processing in Action · Proc. VLDB Endow. 2021

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

distributed SQL · 1.0declarative constraint specification · 1.0
YearPublicationVenuePosition
2021 Compliant Geo-distributed Data Processing in Action
abstract
In this paper we present our work on compliant geo-distributed data processing. Our work focuses on the new dimension of dataflow constraints that regulate the movement of data across geographical or institutional borders. For example, European directives may regulate transferring only certain information fields (such as non personal information) or aggregated data. Thus, it is crucial for distributed data processing frameworks to consider compliance with respect to dataflow constraints derived from these regulations. We have developed a compliance-based data processing framework, which (i) allows for the declarative specification of dataflow constraints, (ii) determines if a query can be translated into a compliant distributed query execution plan, and (iii) executes the compliant plan over distributed SQL databases. We demonstrate our framework using a geo-distributed adaptation of the TPC-H benchmark data. Our framework provides an interactive dashboard, which allows users to specify dataflow constraints, and analyze and execute compliant distributed query execution plans.
Kaustubh Beedkar, David Brekardin, Jorge-Arnulfo Quiané-Ruiz, Volker Markl
Proc. VLDB Endow.2