Comprehensive and Efficient Workload Compression
Summary: Construct a representative workload from an input analytical workload with guarantees on representativity and coverage. A greedy, approximation-guaranteed algorithm solves the NP-hard problem, preserving distributions and outliers, and compares with sampling and clustering. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shaleen Deep (University of Wisconsin)
- 2. Anja Gruenheid (Google)
- 3. Paraschos Koutris (University of Wisconsin)
- 4. Jeffrey Naughton (Google)
- 5. Stratis Viglas (Google)
BibTeX Citation
@article{deep_vldb21,
title = {{Comprehensive and Efficient Workload Compression}},
author = {Deep, Shaleen and Gruenheid, Anja and Koutris, Paraschos and Naughton, Jeffrey and Viglas, Stratis},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {3},
pages = {418--430},
doi = {10.14778/3430915.3430931},
url = {https://doi.org/10.14778/3430915.3430931},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,460 | DIAMetrics: Benchmarking Query Engines at Scale | 2020 | VLDB | 7.3939262e-05 |
| 4,398 | Real-time Workload Pattern Analysis for Large-scale Cloud Databases | 2023 | VLDB | 6.7248611e-05 |
| 5,091 | Budget-aware Index Tuning with Reinforcement Learning | 2022 | SIGMOD | 6.3669569e-05 |
| 5,869 | ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning | 2022 | SIGMOD | 6.0610922e-05 |
| 7,076 | Refactoring Index Tuning Process with Benefit Estimation | 2024 | VLDB | 5.7098893e-05 |
| 7,750 | DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning | 2022 | VLDB | 5.5523652e-05 |
| 9,536 | Database Gyms | 2023 | CIDR | 5.2529727e-05 |
| 9,767 | TracEx: Understanding and Analyzing Database Traces | 2024 | CIDR | 5.2212078e-05 |
| 10,082 | Wred: Workload Reduction for Scalable Index Tuning | 2024 | SIGMOD | 5.1587525e-05 |
| 10,105 | SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression | 2025 | VLDB | 5.1435736e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 154 | Neo: A Learned Query Optimizer | 2019 | VLDB | 0.00028726181 |
| 501 | Database Tuning Advisor for Microsoft SQL Server 2005 | 2004 | VLDB | 0.0001738508 |
| 1,266 | Compressing SQL Workloads | 2002 | SIGMOD | 0.00011412078 |
| 2,889 | F1 Query: Declarative Querying at Scale | 2018 | VLDB | 7.9935046e-05 |
| 3,460 | DIAMetrics: Benchmarking Query Engines at Scale | 2020 | VLDB | 7.3939262e-05 |
| 4,198 | Primitives for Workload Summarization and Implications for SQL | 2003 | VLDB | 6.8397659e-05 |
| 4,926 | Adaptive Sampling for Rapidly Matching Histograms | 2018 | VLDB | 6.4428362e-05 |
| 5,965 | Answering Top-k Representative Queries on Graph Databases | 2014 | SIGMOD | 6.0256454e-05 |
| 8,583 | Query Log Compression for Workload Analytics | 2019 | VLDB | 5.4079618e-05 |
| 8,584 | Efficient Summarization Framework for Multi-Attribute Uncertain Data | 2014 | SIGMOD | 5.4079618e-05 |
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