Distributed Evaluation of Top-k Temporal Joins
Summary: RTJ defines top-k ranked temporal joins with interval predicates and scoring. TKIJ uses offline time-granule endpoint statistics and online score bounds to balance reducers, minimize replication, and prune results in Map-Reduce, yielding strong n-ary RTJ performance. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Julien Pilourdault (CNRS; Université Grenoble Alpes)
- 2. Vincent Leroy (CNRS; Université Grenoble Alpes)
- 3. Sihem Amer-Yahia (CNRS; Université Grenoble Alpes)
BibTeX Citation
@inproceedings{pilourdault_sigmod16,
title = {{Distributed Evaluation of Top-k Temporal Joins}},
author = {Pilourdault, Julien and Leroy, Vincent and Amer-Yahia, Sihem},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2882912},
url = {https://dl.acm.org/doi/10.1145/2882903.2882912},
year = {2016}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,776 | Relevance Queries for Interval Data | 2025 | SIGMOD | 5.093636e-05 |
| 11,850 | Top-k Queries over Digital Traces | 2019 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 8,281 | Efficient Top-K Processing Over Query-Dependent Functions | 2008 | VLDB |
| 2 | 2,567 | ClusterJoin: A Similarity Joins Framework using Map-Reduce | 2014 | VLDB |
| 3 | 12,090 | Let's Rethink Join Optimization in Distributed Systems | 2015 | CIDR |
| 4 | 12,001 | Runtime Optimization of Join Location in Parallel Data Management Systems | 2017 | VLDB |
| 5 | 7,550 | Processing Top-k Join Queries | 2010 | VLDB |
| 6 | 7,286 | Efficient Computation of Quantiles over Joins | 2023 | PODS |
| 7 | 2,926 | Distributed Join Algorithms on Thousands of Cores | 2017 | VLDB |
| 8 | 7,934 | Ranking Large Temporal Data | 2012 | VLDB |
| 9 | 9,497 | Rank Join Queries in NoSQL Databases | 2014 | VLDB |
| 10 | 8,235 | Computing Complex Temporal Join Queries Efficiently | 2022 | SIGMOD |