Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views
Summary: SVC cleans a sample of stale MV rows to estimate fresh aggregates between maintenance batches. It uses sampling with optional outlier indexing to handle skew, delivering bounded, accurate estimates faster than full MV maintenance for diverse MVs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sanjay Krishnan (University of California Berkeley)
- 2. Jiannan Wang (University of California Berkeley)
- 3. Michael J. Franklin (University of California Berkeley)
- 4. Ken Goldberg (University of California Berkeley)
- 5. Tim Kraska (Brown University)
BibTeX Citation
@article{krishnan_vldb15,
title = {{Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views}},
author = {Krishnan, Sanjay and Wang, Jiannan and Franklin, Michael J. and Goldberg, Ken and Kraska, Tim},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {12},
pages = {1370--1381},
doi = {10.14778/2824032.2824037},
url = {https://doi.org/10.14778/2824032.2824037},
year = {2015}
}
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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