dmapply: A functional primitive to express distributed machine learning algorithms in R

Summary: ddR provides a unified distributed data framework for R, introducing dmapply to run functions on distributed data with function/data broadcast and pair-wise communication across backends. SNOW, Spark, HPE Distributed R, and single-node runtimes enable portable ML with near-native performance, expressing statistical-query and MapReduce algorithms and pushing toward standardized distributed R. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 11238
Venue: VLDB
Year: 2016
Pagerank: 4.1945683e-05
Overall Rank: 11,859 | 17.50%
DOI: -

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Rank	Citing Paper	Year	Venue	Pagerank

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Showing 10 of 10 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
3	Pig Latin: A Not-So-Foreign Language for Data Processing	2008	SIGMOD	0.0024183614
4	Pregel: A System for Large-Scale Graph Processing	2010	SIGMOD	0.0019005923
37	Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud	2012	VLDB	0.0007522744
70	Hive - A Warehousing Solution Over a Map-Reduce Framework	2009	VLDB	0.00059533166
140	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00042270404
288	Storm @Twitter	2014	SIGMOD	0.00028939871
1,402	Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML	2014	VLDB	0.00012180605
1,495	Ricardo: Integrating R and Hadoop	2010	SIGMOD	0.00011691049
5,395	Large-scale Predictive Analytics in Vertica: Fast Data Transfer, Distributed Model Creation, and In-database Prediction	2015	SIGMOD	5.5318806e-05
5,964	Bridging Two Worlds with RICE: Integrating R into the SAP In-Memory Computing Engine	2011	VLDB	5.2520617e-05

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