=Paper=
{{Paper
|id=Vol-2994/keynote3
|storemode=property
|title=Scalable Algorithms and Big-Data Applications by Recursive SQL Queries with Aggregates: a Datalog-enabled approach
|pdfUrl=https://ceur-ws.org/Vol-2994/keynote3.pdf
|volume=Vol-2994
|authors=Carlo Zaniolo
|dblpUrl=https://dblp.org/rec/conf/sebd/Zaniolo21
}}
==Scalable Algorithms and Big-Data Applications by Recursive SQL Queries with Aggregates: a Datalog-enabled approach==
Keynote Speech: Scalable Algorithms and Big-Data
Applications by Recursive SQL Queries with
Aggregates: a Datalog-enabled approach – Abstract
Carlo Zaniolo1
1
University of California, Los Angeles, CA 90095, USA
Abstract
The use of basic SQL aggregates in recursive queries enables programmers to employ query languages
to develop complete big-data applications, including graph, machine learning and data mining appli-
cations. To achieve this goal, programmers must make sure that their SQL queries can be converted
into equivalent Datalog programs that combine rigorous declarative semantics with very efficient and
highly scalable fixpoint based semantics. Thus, our approach provides methods and tools to verify that
(i) queries with recursive aggregate have Stable Model Semantics (SMS) and (ii) such SMS can be repre-
sented via a fixpoint-based computation that is conducive to bulk-synchronous and stale-synchronous
parallelism. We also provide techniques to restructure queries that satisfy (i) but not (ii) into queries
that satisfy both.
Keywords
Datalog programs, Recursive SQL queries, Stable Model Semantics (SMS)
SEBD 2021: The 29th Italian Symposium on Advanced Database Systems, September 5-9, 2021, Pizzo Calabro (VV),
Italy
" zaniolo@cs.ucla.edu (C. Zaniolo)
© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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