William A. Mazza

dblp:243/2379 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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 · 61% Data models and query languages · 30% Graph data management · 9%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization › recursive query
recursive aggregate SQL
0.412019
RaSQL: Greater Power and Performance for Big Data Analytics with Recursive-aggregate-SQL on Spark · SIGMOD Conference 2019
Query processing and optimization
recursive query
0.412019
RaSQL: Greater Power and Performance for Big Data Analytics with Recursive-aggregate-SQL on Spark · SIGMOD Conference 2019
Data models and query languages › SQL
SQL extension
0.412019
RaSQL: Greater Power and Performance for Big Data Analytics with Recursive-aggregate-SQL on Spark · SIGMOD Conference 2019

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

fixpoint computation · 0.4compiler optimization · 0.4
YearPublicationVenuePosition
2019 RaSQL: Greater Power and Performance for Big Data Analytics with Recursive-aggregate-SQL on Spark
abstract
Thanks to a simple SQL extension, Recursive-aggregate-SQL (RaSQL) can express very powerful queries and declarative algorithms, such as classical graph algorithms and data mining algorithms. A novel compiler implementation allows RaSQL to map declarative queries into one basic fixpoint operator supporting aggregates in recursive queries. A fully optimized implementation of this fixpoint operator leads to superior performance, scalability and portability. Thus, our RaSQL system, which extends Spark SQL with the before-mentioned new constructs and implementation techniques, matches and often surpasses the performance of other systems, including Apache Giraph, GraphX and Myria.
Jiaqi Gu 0001, Yugo H. Watanabe, William A. Mazza, Alexander Shkapsky, Mohan Yang, Ling Ding 0002, Carlo Zaniolo
SIGMOD Conference3