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LAQy: Efficient and Reusable Query Approximations via Lazy Sampling
Summary: LAQy enables lazy, reusable samples for online AQP that adapt to changing predicates. It merges and expands samples to cross-query reuse, avoiding per-query sampling, with 2.5–19.3x speedups on a code-generation-based in-memory engine under unpredictable workloads.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6678
- Venue
- SIGMOD
- Year
- 2023
- Pagerank
- 4.5287754e-05
- Overall Rank
- 8,370 | 41.83%
- DOI
-
10.1145/3589319
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 23 of 23 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 14 |
Online Aggregation |
1997 |
SIGMOD |
0.0010813443 |
| 59 |
Efficiently Compiling Efficient Query Plans for Modern Hardware |
2011 |
VLDB |
0.0006445664 |
| 113 |
Encapsulation of Parallelism in the Volcano Query Processing System |
1990 |
SIGMOD |
0.0004673401 |
| 204 |
Monitoring Streams – A New Class of Data Management Applications |
2002 |
VLDB |
0.00034696955 |
| 398 |
Mergeable Summaries |
2012 |
PODS |
0.00024383201 |
| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 1,161 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00013579831 |
| 1,320 |
Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters |
2016 |
SIGMOD |
0.00012606067 |
| 1,574 |
Approximate Query Processing: No Silver Bullet |
2017 |
SIGMOD |
0.00011289028 |
| 1,683 |
Cardinality Estimation: An Experimental Survey |
2018 |
VLDB |
0.0001091276 |
| 1,790 |
Effective Use of Block-Level Sampling in Statistics Estimation |
2004 |
SIGMOD |
0.00010529479 |
| 2,005 |
Rapid Sampling for Visualizations with Ordering Guarantees |
2015 |
VLDB |
9.8168893e-05 |
| 2,126 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
9.4814404e-05 |
| 2,494 |
DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models |
2019 |
SIGMOD |
8.6457436e-05 |
| 2,659 |
HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines |
2019 |
VLDB |
8.3615158e-05 |
| 3,425 |
General Incremental Sliding-Window Aggregation |
2015 |
VLDB |
7.1042928e-05 |
| 3,944 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
6.6056349e-05 |
| 4,319 |
Fast Queries Over Heterogeneous Data Through Engine Customization |
2016 |
VLDB |
6.2823814e-05 |
| 5,020 |
Adaptive HTAP through Elastic Resource Scheduling |
2020 |
SIGMOD |
5.7482116e-05 |
| 5,540 |
Permutable Compiled Queries: Dynamically Adapting Compiled Queries without Recompiling |
2021 |
VLDB |
5.450319e-05 |
| 8,235 |
Experiences with Approximating Queries in Microsoft’s Production Big-Data Clusters |
2019 |
VLDB |
4.5481384e-05 |
| 9,631 |
Approximate Query Processing for Interactive Data Science |
2017 |
SIGMOD |
4.3095152e-05 |
| 11,430 |
Accelerating Complex Analytics using Speculation |
2021 |
CIDR |
4.1905499e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 2,424 |
The Analytical Bootstrap: a New Method for Fast Error Estimation in Approximate Query Processing |
2014 |
SIGMOD |
8.8415494e-05 |
| 6,481 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.039683e-05 |
| 1,257 |
Dynamic Sample Selection for Approximate Query Processing |
2003 |
SIGMOD |
0.00013002384 |
| 11,287 |
Approximate Queries over Concurrent Updates |
2023 |
VLDB |
4.1905499e-05 |
| 3,944 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
6.6056349e-05 |
| 1,320 |
Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters |
2016 |
SIGMOD |
0.00012606067 |
| 1,867 |
Knowing When You’re Wrong: Building Fast and Reliable Approximate Query Processing Systems |
2014 |
SIGMOD |
0.00010264932 |
| 2,583 |
Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee |
2016 |
SIGMOD |
8.4973431e-05 |
| 6,724 |
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing |
2021 |
SIGMOD |
4.9449472e-05 |
| 10,349 |
Efficient Approximate Query Processing with Block Sampling |
2025 |
CIDR |
4.1905499e-05 |