RaSQL: Greater Power and Performance for Big Data Analytics with Recursive-aggregate-SQL on Spark
Summary: RaSQL extends Spark SQL with Recursive-aggregate-SQL for declarative recursive queries with aggregates. A novel fixpoint-based compiler maps RaSQL to a single fixpoint operator; optimized runtime yields superior performance vs Giraph, GraphX, Myria. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiaqi Gu
- 2. Yugo H. Watanabe
- 3. William A. Mazza
- 4. Alexander Shkapsky
- 5. Mohan Yang
- 6. Ling Ding
- 7. Carlo Zaniolo
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 5,259 | On the Optimization of Recursive Relational Queries: Application to Graph Queries | 2020 | SIGMOD | 5.5984356e-05 |
| 66 | Spark SQL: Relational Data Processing in Spark | 2015 | SIGMOD | 0.00061639801 |
| 9,997 | Raqlet: Cross-Paradigm Compilation for Recursive Queries | 2026 | CIDR | 4.1945683e-05 |
| 3,200 | Big Data Analytics with Datalog Queries on Spark | 2016 | SIGMOD | 7.3912411e-05 |
| 11,576 | RASQL: A Powerful Language and its System for Big Data Applications | 2020 | SIGMOD | 4.1945683e-05 |