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Dalton: Learned Partitioning for Distributed Data Streams

Summary: Dalton: an RL-based, lightweight partitioner for distributed streams that memoizes recent state to minimize per-tuple overhead and rapidly adapt to unknown, changing hot-key skews. Scales via cooperative learning across instances (no centralized bottleneck), achieving 1.3–6.7× higher throughput. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13306
Venue
VLDB
Year
2023
Pagerank
4.2818172e-05
Overall Rank
9,797 | 31.85%
DOI
10.14778/3570690.3570699

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Rank Citing Paper Year Venue Pagerank
10,840 Learned Cost Models for Query Optimization: From Batch to Streaming Systems 2025 VLDB 4.1945683e-05
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