JENNER: Just-in-time Enrichment in Query Processing
Summary: JENNER defers costly ML enrichment from ingestion to query time, exploiting cost–quality tradeoffs to progressively refine answers for SPJ and aggregation queries. On IoT and Twitter data, it outperforms naive progressive-computation strategies. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dhrubajyoti Ghosh (University of California Irvine)
- 2. Peeyush Gupta (University of California Irvine)
- 3. Sharad Mehrotra (University of California Irvine)
- 4. Roberto Yus (University of Maryland)
- 5. Yasser Altowim (Saudi Data and Artificial Intelligence Authority)
BibTeX Citation
@article{ghosh_vldb22,
title = {{JENNER: Just-in-time Enrichment in Query Processing}},
author = {Ghosh, Dhrubajyoti and Gupta, Peeyush and Mehrotra, Sharad and Yus, Roberto and Altowim, Yasser},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {11},
pages = {2666--2678},
doi = {10.14778/3551793.3551822},
url = {https://doi.org/10.14778/3551793.3551822},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,285 | ZIP: Lazy Imputation during Query Processing | 2024 | VLDB | 5.292293e-05 |
| 10,657 | A Rank-Based Approach to Recommender System’s Top-K Queries with Uncertain Scores | 2025 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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