Big Data Analytics with Datalog Queries on Spark
Summary: BigDatalog enables concise declarative Datalog queries for large-scale analytics on Spark. It uses compilation and optimization to efficiently support recursion on Spark, with empirical comparisons against top Datalog systems showing Spark-based analytics viable. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Alexander Shkapsky (University of California Los Angeles)
- 2. Mohan Yang (University of California Los Angeles)
- 3. Matteo Interlandi (University of California Los Angeles)
- 4. Hsuan Chiu (University of California Los Angeles)
- 5. Tyson Condie (University of California Los Angeles)
- 6. Carlo Zaniolo (University of California Los Angeles)
BibTeX Citation
@inproceedings{shkapsky_sigmod16,
title = {{Big Data Analytics with Datalog Queries on Spark}},
author = {Shkapsky, Alexander and Yang, Mohan and Interlandi, Matteo and Chiu, Hsuan and Condie, Tyson and Zaniolo, Carlo},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2915229},
url = {https://dl.acm.org/doi/10.1145/2882903.2915229},
year = {2016}
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