Database Paper Browser

Back to papers

Set Similarity Joins on MapReduce: An Experimental Survey

Summary: Experimental survey of ten distributed MapReduce set similarity join algorithms. Uniform benchmarking across 12 datasets reveals no universal scalability; long sets, frequent elements, or low thresholds degrade performance, with analytic root-cause insights and suggested future directions. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11605
Venue
VLDB
Year
2018
Pagerank
5.9315784e-05
Overall Rank
4,775 | 66.79%
DOI
10.14778/3231751.3231760

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 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