Machine Learning for Big Data

Summary: Survey of using DB systems to scale ML, highlighting architectures, relational-algebra workflows, recursion, and streaming support. Outlines systems, applications, gaps, and questions at the DB-ML interface to guide cross-domain research. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4806
Venue: SIGMOD
Year: 2013
Pagerank: 6.4750538e-05
Overall Rank: 4,859 | 66.67%
DOI: 10.1145/2463676.2465338

Incoming Non-self Citations Over Time

Authors

1. Tyson Condie (Microsoft)
2. Paul Mineiro (Microsoft)
3. Neoklis Polyzotis (University of California Santa Cruz)
4. Markus Weimer (Microsoft)

BibTeX Citation

@inproceedings{condie_sigmod13,
        title = {{Machine Learning for Big Data}},
        author = {Condie, Tyson and Mineiro, Paul and Polyzotis, Neoklis and Weimer, Markus},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2465338},
        url = {https://dl.acm.org/doi/10.1145/2463676.2465338},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
536	Learning Linear Regression Models over Factorized Joins	2016	SIGMOD	0.0001693369
1,250	Data Management in Machine Learning: Challenges, Techniques, and Systems	2017	SIGMOD	0.00011485301
4,049	Resource Elasticity for Large-Scale Machine Learning	2015	SIGMOD	6.9369379e-05
9,214	ParaX: Boosting Deep Learning for Big Data Analytics on Many-Core CPUs	2021	VLDB	5.3058522e-05

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
3	Pregel: A System for Large-Scale Graph Processing	2010	SIGMOD	0.0012250108
20	Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud	2012	VLDB	0.00056944564

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