Scalable and Adaptive Online Joins
Summary: Adaptive online dataflow join for shared-nothing systems; arbitrary predicates. Routing and repartitioning handle skew with amortized constant per-tuple cost, offering strong black-box consistency and a 3.75 ratio, outperforming static partitioning. (summarized by gpt-5-nano on Feb 09 2026)
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,717 | Approximate Join Processing Over Data Streams | 2003 | SIGMOD | 0.00010793312 |
| 6,619 | Near-Optimal Distributed Band-Joins through Recursive Partitioning | 2020 | SIGMOD | 4.9910152e-05 |
| 5,045 | Massive Scale-out of Expensive Continuous Queries | 2011 | VLDB | 5.740793e-05 |
| 1,429 | A Scalable, Predictable Join Operator for Highly Concurrent Data Warehouses | 2009 | VLDB | 0.00012033518 |
| 1,939 | From Theory to Practice: Efficient Join Query Evaluation in a Parallel Database System | 2015 | SIGMOD | 0.00010025655 |
| 11,890 | Let's Rethink Join Optimization in Distributed Systems | 2015 | CIDR | 4.1945683e-05 |
| 6,629 | A Holistic View of Stream Partitioning Costs | 2017 | VLDB | 4.9880986e-05 |
| 11,797 | Runtime Optimization of Join Location in Parallel Data Management Systems | 2017 | VLDB | 4.1945683e-05 |
| 10,967 | Low-Latency Adaptive Distributed Stream Join System Based on a Flexible Join Model | 2024 | SIGMOD | 4.1945683e-05 |
| 4,167 | Scalable Distributed Stream Join Processing | 2015 | SIGMOD | 6.3919506e-05 |