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Prompt: Dynamic Data-Partitioning for Distributed Micro-batch Stream Processing Systems

Summary: Prompt introduces dynamic data partitioning for micro-batch streams, with buffering and key-sorting to handle skew. Greedy workload-aware partitioning with load-aware distribution and elastic resources yields 2x throughput with maintained latency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5929
Venue
SIGMOD
Year
2020
Pagerank
4.4844961e-05
Overall Rank
8,594 | 40.28%
DOI
10.1145/3318464.3389713

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
9,041 TreeSensing: Linearly Compressing Sketches with Flexibility 2023 SIGMOD 4.3997447e-05
9,800 Dalton: Learned Partitioning for Distributed Data Streams 2023 VLDB 4.2777144e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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