Database Paper Browser

Back to papers

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
13307
Venue
VLDB
Year
2023
Pagerank
4.2777144e-05
Overall Rank
9,800 | 31.89%
DOI
10.14778/3570690.3570699

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,844 Learned Cost Models for Query Optimization: From Batch to Streaming Systems 2025 VLDB 4.1905499e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 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