A Holistic View of Stream Partitioning Costs
Summary: Holistic partitioning for pSPEs that accounts for tuple imbalance and aggregation costs in stateful streams. The proposed algorithms beat current approaches by up to an order of magnitude, highlighting cost-aware partitioning for real-time analytics. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,596 | Prompt: Dynamic Data-Partitioning for Distributed Micro-batch Stream Processing Systems | 2020 | SIGMOD | 4.4887993e-05 |
| 9,733 | ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems | 2023 | VLDB | 4.2942813e-05 |
| 9,797 | Dalton: Learned Partitioning for Distributed Data Streams | 2023 | VLDB | 4.2818172e-05 |
| 11,468 | Klink: Progress-Aware Scheduling for Streaming Data Systems | 2021 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 5,045 | Massive Scale-out of Expensive Continuous Queries | 2011 | VLDB | 5.740793e-05 |