QPJVis Demo: Quality-boost Progressive Join Query Processing System
Summary: QPJVis demonstrates progressive join processing that corrects key bias under nonuniform inputs by dynamically estimating the final-result distribution and selectively hiding outputs. It contrasts this input&output strategy with Prism’s input-only control. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Xin Zhang (University of California Riverside)
- 2. Ahmed Eldawy (University of California Riverside)
BibTeX Citation
@article{zhang_vldb24,
title = {{QPJVis Demo: Quality-boost Progressive Join Query Processing System}},
author = {Zhang, Xin and Eldawy, Ahmed},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4345--4348},
doi = {10.14778/3685800.3685871},
url = {https://doi.org/10.14778/3685800.3685871},
year = {2024}
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,880 | Scalable Sweeping-Based Spatial Join | 1998 | VLDB | 9.5562066e-05 |
| 3,288 | I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making | 2017 | VLDB | 7.5578177e-05 |
| 4,630 | Efficient Join Synopsis Maintenance for Data Warehouse | 2020 | SIGMOD | 6.5955933e-05 |
| 5,676 | Scalable Progressive Analytics on Big Data in the Cloud | 2013 | VLDB | 6.1251441e-05 |
| 7,129 | Marviq: Quality-Aware Geospatial Visualization of Range-Selection Queries Using Materialization | 2020 | SIGMOD | 5.694968e-05 |
| 8,024 | Progressive Join Algorithms Considering User Preference | 2021 | CIDR | 5.5052493e-05 |
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