Join 10350+ others. No spamming.
I promise!

Follow us at github.



hadley/multidplyr

260

hadley / multidplyr

R

Partitioned data frames for 'dplyr'


READ ME

multidplyr

Travis-CI Build Status Coverage Status CRAN_Status_Badge

multidplyr is a backend for dplyr that partitions a data frame across multiple cores. You tell multidplyr how to split the data up with partition() and then the data stays on each node until you explicitly retrieve it with collect(). This minimises the amount of time spent moving data around, and maximises parallel performance. This idea is inspired by partools by Norm Matloff and distributedR by the Vertica Analytics team.

Due to the overhead associated with communicating between the nodes, you won't expect to see much performance improvement on basic dplyr verbs with less than ~10 million observations. However, you'll see improvements much faster if you're doing more complex operations with do().

To learn more, read the vignette.

Installation

To install from GitHub:

# install.packages("devtools")
devtools::install_github("hadley/multidplyr")