Execution Primitives for Scalable Joins and Aggregations in Map Reduce

Summary: Introduces Rubix primitives for scalable MapReduce joins and aggregations: cost-function-organized calculation units, optimized operators, and skew-resistant load partitioning. Deployed at LinkedIn, it accelerates and lowers the cost of TB-scale analytics. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 10995
Venue: VLDB
Year: 2014
Pagerank: 5.4940737e-05
Overall Rank: 8,069 | 44.64%
DOI: 10.14778/2733004.2733006

Incoming Non-self Citations Over Time

Authors

1. Srinivas Vemuri (LinkedIn)
2. Maneesh Varshney (LinkedIn)
3. Krishna Puttaswamy (LinkedIn)
4. Rui Liu (LinkedIn)

BibTeX Citation

@article{vemuri_vldb14,
        title = {{Execution Primitives for Scalable Joins and Aggregations in Map Reduce}},
        author = {Vemuri, Srinivas and Varshney, Maneesh and Puttaswamy, Krishna and Liu, Rui},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {13},
        pages = {1462--1473},
        doi = {10.14778/2733004.2733006},
        url = {https://doi.org/10.14778/2733004.2733006},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
1,320	From Theory to Practice: Efficient Join Query Evaluation in a Parallel Database System	2015	SIGMOD	0.00011166426
12,036	An Efficient MapReduce Cube Algorithm for Varied Data Distributions	2016	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
872	Tenzing: A SQL Implementation On The MapReduce Framework	2011	VLDB	0.00013486409

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