RASQL: A Powerful Language and its System for Big Data Applications
Summary: Recursive-aggregate SQL (RaSQL) extends SQL with aggregates in recursion to express advanced analytics on Spark. Demonstrates formal semantics, diverse examples (graph search, ML), and a user-friendly interface for expressing and monitoring complex declarative algorithms. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Jin Wang (University of California Los Angeles)
- 2. Guorui Xiao (University of California Los Angeles)
- 3. Jiaqi Gu (University of California Los Angeles)
- 4. Jiacheng Wu (Tsinghua University)
- 5. Carlo Zaniolo (University of California Los Angeles)
BibTeX Citation
@inproceedings{wang_sigmod20,
title = {{RASQL: A Powerful Language and its System for Big Data Applications}},
author = {Wang, Jin and Xiao, Guorui and Gu, Jiaqi and Wu, Jiacheng and Zaniolo, Carlo},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3384677},
url = {https://dl.acm.org/doi/10.1145/3318464.3384677},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,858 | Optimizing Parallel Recursive Datalog Evaluation on Multicore Machines | 2022 | SIGMOD | 5.3567857e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 24 | Spark SQL: Relational Data Processing in Spark | 2015 | SIGMOD | 0.00054865648 |
| 2,935 | RaSQL: Greater Power and Performance for Big Data Analytics with Recursive-aggregate-SQL on Spark | 2019 | SIGMOD | 7.9444531e-05 |
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