Demo Data from EDBT 2026 / reviewers in the wild / expert
Ainur Smagulova
dblp:289/1423
· DBLP profile ↗
1ranked-venue papers
1as 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 first-author · 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 |
Query processing and optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Query processing and optimization
join processing |
0.5 | 1 | 2021 | Vertex-centric Parallel Computation of SQL Queries · SIGMOD Conference 2021 |
Query processing and optimization › join processing
parallel join |
0.5 | 1 | 2021 | Vertex-centric Parallel Computation of SQL Queries · SIGMOD Conference 2021 |
Query processing and optimization
parallel query processing |
0.5 | 1 | 2021 | Vertex-centric Parallel Computation of SQL Queries · SIGMOD Conference 2021 |
Methods — techniques the papers use, named apart from their topics
vertex-centric programming · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Vertex-centric Parallel Computation of SQL QueriesabstractWe present a scheme for parallel execution of SQL queries on top of any vertex-centric BSP graph processing engine. The scheme comprises a graph encoding of relational instances and a vertex program specification of our algorithm called TAG-join, which matches the theoretical communication and computation complexity of state-of-the-art join algorithms. When run on top of the vertex-centric TigerGraph database engine on a single multi-core server, TAG-join exploits thread parallelism and is competitive with (and often outperforms) reference RDBMSs on the TPC benchmarks they are traditionally tuned for. In a distributed cluster, TAG-join outperforms the popular Spark SQL engine. Ainur Smagulova, Alin Deutsch |
SIGMOD Conference | 1 |