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Parallelism-Optimizing Data Placement for Faster Data-Parallel Computations

Summary: Shows that minimizing tail latency for data-parallel queries requires placing items so each query's accesses are spread across many machines to maximize per-query parallelism. Proposes a linear computable parallelism metric and a scalable partitioning-based placement optimizer; 7–64% p99 improvements on Solr/MongoDB. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13328
Venue
VLDB
Year
2023
Pagerank
4.5746638e-05
Overall Rank
8,150 | 43.31%
DOI
10.14778/3574245.3574260

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
8,854 Optimizing the cloud? Don't train models. Build oracles! 2024 CIDR 4.4349047e-05
9,601 SkyPIE: A Fast & Accurate Oracle for Object Placement 2024 SIGMOD 4.3177432e-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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