Lachesis: Automatic Partitioning for UDF-Centric Analytics
Summary: Lachesis automates partitioning for UDF-centric analytics, where reusable computation and functional dependencies are scarce. It models workloads as analyzable workflow sub-computations and uses deep reinforcement learning to select partitioning features, optimizing shared storage across applications. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jia Zou (Arizona State University)
- 2. Amitabh Das (Arizona State University)
- 3. Pratik Barhate (Arizona State University)
- 4. Arun Iyengar (IBM)
- 5. Binhang Yuan (Rice University)
- 6. Dimitrije Jankov (Rice University)
- 7. Chris Jermaine (Rice University)
BibTeX Citation
@article{zou_vldb21,
title = {{Lachesis: Automatic Partitioning for UDF-Centric Analytics}},
author = {Zou, Jia and Das, Amitabh and Barhate, Pratik and Iyengar, Arun and Yuan, Binhang and Jankov, Dimitrije and Jermaine, Chris},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {8},
pages = {1262--1275},
doi = {10.14778/3457390.3457392},
url = {https://doi.org/10.14778/3457390.3457392},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,642 | User-Defined Operators: Efficiently Integrating Custom Algorithms into Modern Databases | 2022 | VLDB | 7.1416697e-05 |
| 6,726 | A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning | 2023 | SIGMOD | 5.6948731e-05 |
| 6,844 | Serving Deep Learning Models with Deduplication from Relational Databases | 2022 | VLDB | 5.6664512e-05 |
| 7,977 | The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions | 2024 | VLDB | 5.4142519e-05 |
| 10,653 | InferF: Declarative Factorization of AI/ML Inferences over Joins | 2026 | SIGMOD | 4.9793485e-05 |
| 11,714 | QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark | 2023 | SIGMOD | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 32 of 32 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 1 | 2,663 | A Layered Aggregate Engine for Analytics Workloads | 2019 | SIGMOD |
| 2 | 281 | Accelerating Machine Learning Inference with Probabilistic Predicates | 2018 | SIGMOD |
| 3 | 9,200 | Dalton: Learned Partitioning for Distributed Data Streams | 2023 | VLDB |
| 4 | 9,772 | Lachesis: Robust Database Storage Management Based on Device-specific Performance Characteristics | 2003 | VLDB |
| 5 | 5,041 | LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems | 2022 | SIGMOD |
| 6 | 5,834 | Opportunistic Physical Design for Big Data Analytics | 2014 | SIGMOD |
| 7 | 1,444 | An Architecture for Compiling UDF-centric Workflows | 2015 | VLDB |
| 8 | 4,008 | Automating Distributed Tiered Storage Management in Cluster Computing | 2020 | VLDB |
| 9 | 3,239 | Locality-aware Partitioning in Parallel Database Systems | 2015 | SIGMOD |
| 10 | 2,478 | Learning a Partitioning Advisor for Cloud Databases | 2020 | SIGMOD |