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SystemML: Declarative Machine Learning on Spark

Summary: Declarative ML via SystemML's DSL for linear algebra lets data scientists express custom algorithms while Spark uses cost-based plans. End-to-end Spark integration yields in-memory and scalable plans; open-source with optimizer/runtime insights for research. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11439
Venue
VLDB
Year
2016
Pagerank
0.0001888524
Overall Rank
415 | 97.16%
DOI
10.14778/3007263.3007273

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{boehm_vldb16,
        title = {{SystemML: Declarative Machine Learning on Spark}},
        author = {Boehm, Matthias and Dusenberry, Michael W. and Eriksson, Deron and Evfimievski, Alexandre V. and Manshadi, Faraz Makari and Pansare, Niketan and Reinwald, Berthold and Reiss, Frederick R. and Sen, Prithviraj and Surve, Arvind C. and Tatikonda, Shirish},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {13},
        pages = {1425--1436},
        doi = {10.14778/3007263.3007273},
        url = {https://doi.org/10.14778/3007263.3007273},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 14 of 64 citing papers.

Rank Citing Paper Year Venue Pagerank
9,572 PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development 2018 SIGMOD 5.2528121e-05
9,675 BlockJoin: Efficient Matrix Partitioning Through Joins 2017 VLDB 5.2380072e-05
9,742 Unified Data Analytics: State-of-the-art and Open Problems 2022 VLDB 5.227679e-05
9,993 In-Database Data Imputation 2024 SIGMOD 5.1815618e-05
10,466 InferF: Declarative Factorization of AI/ML Inferences over Joins 2026 SIGMOD 5.093636e-05
10,589 Morphing-based Compression for Data-centric ML Pipelines 2026 VLDB 5.093636e-05
10,669 LCP: Enhancing Scientific Data Management with Lossy Compression for Particles 2025 SIGMOD 5.093636e-05
11,360 Templating Shuffles 2023 CIDR 5.093636e-05
11,537 Redundancy Elimination in Distributed Matrix Computation 2022 SIGMOD 5.093636e-05
11,539 Juggler: Autonomous Cost Optimization and Performance Prediction of Big Data Applications 2022 SIGMOD 5.093636e-05
11,669 Hybrid Evaluation for Distributed Iterative Matrix Computation 2021 SIGMOD 5.093636e-05
11,674 Enforcing Constraints for Machine Learning Systems via Declarative Feature Selection: An Experimental Study 2021 SIGMOD 5.093636e-05
11,709 HyMAC: A Hybrid Matrix Computation System 2021 VLDB 5.093636e-05
11,789 TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications 2020 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
20 Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud 2012 VLDB 0.00056944564
106 The MADlib Analytics Library or MAD Skills, the SQL 2012 VLDB 0.00033539462
532 MLbase: A Distributed Machine-learning System 2013 CIDR 0.00017072641
640 Materialization Optimizations for Feature Selection Workloads 2014 SIGMOD 0.00015409494
993 Simulation of Database-Valued Markov Chains Using SimSQL 2013 SIGMOD 0.00012789598
1,079 Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML 2014 VLDB 0.00012258469
1,442 An Architecture for Compiling UDF-centric Workflows 2015 VLDB 0.00010778486
2,217 Cumulon: Optimizing Statistical Data Analysis in the Cloud 2013 SIGMOD 8.9332438e-05
2,681 Exploiting Matrix Dependency for Efficient Distributed Matrix Computation 2015 SIGMOD 8.2632778e-05
2,717 Implicit Parallelism through Deep Language Embedding 2015 SIGMOD 8.2102313e-05
4,049 Resource Elasticity for Large-Scale Machine Learning 2015 SIGMOD 6.9369379e-05
6,430 REEF: Retainable Evaluator Execution Framework 2015 SIGMOD 5.880521e-05
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