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Templating Shuffles

Summary: TeShu: a unified, extensible shuffle service that represents optimization choices as parameterized shuffle templates capturing application, workload, and data‑center variability. Templates are instantiated via efficient sampling to quickly find near‑optimal shuffles. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
500
Venue
CIDR
Year
2023
Pagerank
4.1945683e-05
Overall Rank
11,154 | 22.41%
DOI
-

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Showing 18 of 18 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
4 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0019005923
66 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00061639801
288 Storm @Twitter 2014 SIGMOD 0.00028939871
396 One Trillion Edges: Graph Processing at Facebook-Scale 2015 VLDB 0.00024424102
557 SystemML: Declarative Machine Learning on Spark 2016 VLDB 0.00020197988
1,326 Starling: A Scalable Query Engine on Cloud Functions 2020 SIGMOD 0.00012576952
1,543 NUMA-aware algorithms: the case of data shuffling 2013 CIDR 0.0001145318
2,424 Lambada: Interactive Data Analytics on Cold Data Using Serverless Cloud Infrastructure 2020 SIGMOD 8.8380822e-05
2,840 Understanding the Effect of Data Center Resource Disaggregation on Production DBMSs 2020 VLDB 8.0349523e-05
3,200 Big Data Analytics with Datalog Queries on Spark 2016 SIGMOD 7.3912411e-05
4,247 Rethinking Data Management Systems for Disaggregated Data Centers 2020 CIDR 6.325596e-05
4,483 DFI: The Data Flow Interface for High-Speed Networks 2021 SIGMOD 6.148188e-05
4,800 Boxer: Data Analytics on Network-enabled Serverless Platforms 2021 CIDR 5.9117077e-05
5,118 AdaptDB: Adaptive Partitioning for Distributed Joins 2017 VLDB 5.6820984e-05
6,282 Cheetah: Accelerating Database Queries with Switch Pruning 2020 SIGMOD 5.128797e-05
8,396 Optimizing Declarative Graph Queries at Large Scale 2019 SIGMOD 4.5276541e-05
8,462 Topology-aware Parallel Data Processing: Models, Algorithms and Systems at Scale 2020 CIDR 4.5056381e-05
9,504 Supporting Scalable Analytics with Latency Constraints 2015 VLDB 4.3341665e-05
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