HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries

Summary: HADAD is an extensible approach optimizing hybrid RA-LA analytics via a unified relational model. It plugs into LA or RA-LA systems without internal changes, leveraging materialized results to unify optimization and boost LA workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6263
Venue: SIGMOD
Year: 2021
Pagerank: 5.3354529e-05
Overall Rank: 8,999 | 38.26%
DOI: 10.1145/3448016.3457311

Incoming Non-self Citations Over Time

Authors

1. Rana Alotaibi (University of California San Diego)
2. Bogdan Cautis (University of Paris)
3. Alin Deutsch (University of California San Diego)
4. Ioana Manolescu (INRIA; Institut Polytechnique de Paris)

BibTeX Citation

@inproceedings{alotaibi_sigmod21,
        title = {{HADAD: A Lightweight Approach for Optimizing Hybrid Complex Analytics Queries}},
        author = {Alotaibi, Rana and Cautis, Bogdan and Deutsch, Alin and Manolescu, Ioana},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457311},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457311},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,414	Optimizing Tensor Programs on Flexible Storage	2023	SIGMOD	6.2258658e-05
7,915	Krypton: Real-time Serving and Analytical SQL Engine at ByteDance	2023	VLDB	5.5181056e-05

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 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
415	SystemML: Declarative Machine Learning on Spark	2016	VLDB	0.0001888524
1,235	Towards Linear Algebra over Normalized Data	2017	VLDB	0.00011548457
1,250	Data Management in Machine Learning: Challenges, Techniques, and Systems	2017	SIGMOD	0.00011485301
2,239	An Intermediate Representation for Optimizing Machine Learning Pipelines	2019	VLDB	8.8875753e-05
2,293	Extending Relational Query Processing with ML Inference	2020	CIDR	8.7949378e-05
3,205	On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML	2018	VLDB	7.6386536e-05
3,392	Complete Yet Practical Search for Minimal Query Reformulations Under Constraints	2014	SIGMOD	7.4515019e-05
3,459	A Comparative Evaluation of Systems for Scalable Linear Algebra-based Analytics	2018	VLDB	7.3953716e-05
4,409	MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions	2019	SIGMOD	6.7178579e-05
4,968	Towards Scalable Hybrid Stores: Constraint-Based Rewriting to the Rescue	2019	SIGMOD	6.4206525e-05
4,976	SPORES: Sum-Product Optimization via Relational Equality Saturation for Large Scale Linear Algebra	2020	VLDB	6.4168322e-05
5,182	Probabilistic Demand Forecasting at Scale	2017	VLDB	6.3287692e-05
6,215	ESTOCADA: Towards Scalable Polystore Systems	2020	VLDB	5.9425753e-05

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