SquirrelJoin: Network-Aware Distributed Join Processing with Lazy Partitioning
Summary: SquirrelJoin mitigates transient network skew in distributed joins via in-memory lazy partitions, dynamically assigned using throughput-based completion-time estimates. A Flink implementation cuts join latency up to 2.9× under contention with small fixed overhead. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lukas Rupprecht (Imperial College London)
- 2. William Culhane (Imperial College London)
- 3. Peter Pietzuch (Imperial College London)
BibTeX Citation
@article{rupprecht_vldb17,
title = {{SquirrelJoin: Network-Aware Distributed Join Processing with Lazy Partitioning}},
author = {Rupprecht, Lukas and Culhane, William and Pietzuch, Peter},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {11},
pages = {1250--1261},
doi = {10.14778/3137628.3137650},
url = {https://doi.org/10.14778/3137628.3137650},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,227 | MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures | 2021 | SIGMOD | 7.6217889e-05 |
| 3,306 | Frontier: Resilient Edge Processing for the Internet of Things | 2018 | VLDB | 7.5387095e-05 |
| 6,957 | Design and Analysis of a Processing-in-DIMM Join Algorithm: A Case Study with UPMEM DIMMs | 2023 | SIGMOD | 5.7303405e-05 |
| 8,721 | Accelerate Distributed Joins with Predicate Transfer | 2025 | SIGMOD | 5.3772617e-05 |
| 9,628 | INEv: In-Network Evaluation for Event Stream Processing | 2023 | SIGMOD | 5.2434488e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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