Back to papers
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
- 11252
- Venue
- VLDB
- Year
- 2016
- Pagerank
- 0.00020186115
- Overall Rank
- 557 | 96.14%
- DOI
-
-
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 14 of 64 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 9,442 |
BlockJoin: Efficient Matrix Partitioning Through Joins |
2017 |
VLDB |
4.3384032e-05 |
| 9,608 |
Unified Data Analytics: State-of-the-art and Open Problems |
2022 |
VLDB |
4.3136057e-05 |
| 9,855 |
In-Database Data Imputation |
2024 |
SIGMOD |
4.2652623e-05 |
| 10,177 |
InferF: Declarative Factorization of AI/ML Inferences over Joins |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,303 |
Morphing-based Compression for Data-centric ML Pipelines |
2026 |
VLDB |
4.1905499e-05 |
| 10,393 |
LCP: Enhancing Scientific Data Management with Lossy Compression for Particles |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,508 |
Privacy and Accuracy-Aware AI/ML Model Deduplication |
2025 |
SIGMOD |
4.1905499e-05 |
| 11,157 |
Templating Shuffles |
2023 |
CIDR |
4.1905499e-05 |
| 11,341 |
Redundancy Elimination in Distributed Matrix Computation |
2022 |
SIGMOD |
4.1905499e-05 |
| 11,343 |
Juggler: Autonomous Cost Optimization and Performance Prediction of Big Data Applications |
2022 |
SIGMOD |
4.1905499e-05 |
| 11,475 |
Hybrid Evaluation for Distributed Iterative Matrix Computation |
2021 |
SIGMOD |
4.1905499e-05 |
| 11,480 |
Enforcing Constraints for Machine Learning Systems via Declarative Feature Selection: An Experimental Study |
2021 |
SIGMOD |
4.1905499e-05 |
| 11,515 |
HyMAC: A Hybrid Matrix Computation System |
2021 |
VLDB |
4.1905499e-05 |
| 11,598 |
TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications |
2020 |
SIGMOD |
4.1905499e-05 |
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.
Semantically Similar Papers