Upsortable: Programming Top-K Queries Over Data Streams
Summary: Upsortable enables safe, efficient Top-k queries over non-append-only streams by making standard Java sorted collections support evolving data. Its annotation-driven AST/bytecode transformation preserves full Java Collections compatibility without bespoke data structures. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Julien Subercaze (Jean Monnet University; University of Lyon)
- 2. Christophe Gravier (Jean Monnet University; University of Lyon)
- 3. Syed Gillani (Jean Monnet University; University of Lyon)
- 4. Abderrahmen Kammoun (Jean Monnet University; University of Lyon)
- 5. Frederique Laforest (Jean Monnet University; University of Lyon)
BibTeX Citation
@article{subercaze_vldb17,
title = {{Upsortable: Programming Top-K Queries Over Data Streams}},
author = {Subercaze, Julien and Gravier, Christophe and Gillani, Syed and Kammoun, Abderrahmen and Laforest, Frederique},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {12},
pages = {1873--1876},
doi = {10.14778/3137765.3137797},
url = {https://doi.org/10.14778/3137765.3137797},
year = {2017}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,787 | Continuous Query for Top-K Maximal Sum Intervals over Streaming Data | 2026 | VLDB | 4.9793485e-05 |
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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 |
|---|---|---|---|---|
| 510 | TelegraphCQ: Continuous Dataflow Processing | 2003 | SIGMOD | 0.00017065714 |
| 606 | Twitter Heron: Stream Processing at Scale | 2015 | SIGMOD | 0.00015635133 |
| 1,303 | Realtime Data Processing at Facebook | 2016 | SIGMOD | 0.0001110427 |
| 1,439 | Continuous Monitoring of Top-k Queries over Sliding Windows | 2006 | SIGMOD | 0.00010642846 |
| 1,938 | S-Store: Streaming Meets Transaction Processing | 2015 | VLDB | 9.3342542e-05 |
| 8,581 | Changing Engines in Midstream: A Java Stream Computational Model for Big Data Processing | 2014 | VLDB | 5.3100083e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 12,454 | A Dynamic I/O-Efficient Structure for One-Dimensional Top-k Range Reporting | 2014 | PODS |
| 2 | 9,346 | External Merge Sort for Top-K Queries: Eager input filtering guided by histograms | 2020 | SIGMOD |
| 3 | 10,787 | Continuous Query for Top-K Maximal Sum Intervals over Streaming Data | 2026 | VLDB |
| 4 | 7,394 | Efficient and Generic Evaluation of Ranked Queries | 2011 | SIGMOD |
| 5 | 2,485 | Processing a Large Number of Continuous Preference Top-k Queries | 2012 | SIGMOD |
| 6 | 8,581 | Changing Engines in Midstream: A Java Stream Computational Model for Big Data Processing | 2014 | VLDB |
| 7 | 1,439 | Continuous Monitoring of Top-k Queries over Sliding Windows | 2006 | SIGMOD |
| 8 | 7,615 | Processing Top-k Join Queries | 2010 | VLDB |
| 9 | 3,326 | Sliding-Window Top-k Queries on Uncertain Streams | 2008 | VLDB |
| 10 | 3,379 | Ad-hoc Top-k Query Answering for Data Streams | 2007 | VLDB |