useBackend: Sets the active backend driver. Functions exported by the...

In ddR: Distributed Data Structures in R

Description

The default driver uses R's 'parallel' as the backend.

Usage

useBackend(driver, ...)

Arguments

driver	driver object for the backend that will be used. This object should extend class 'ddRDriver', and the S4 methods for do_dmapply, do_collect, and get_parts should be defined in the class of the driver object.
...	additional parameters to pass to the initialization function of the driver.

Details

After successfully registering a new backend with useBackend(), all subsequent dmapply, collect, and parts operations will dispatch on that driver object's class. Note that distributed objects created with a different backend prior to switching will be incompatible with these backend-specific functions of the new driver.

References

Prasad, S., Fard, A., Gupta, V., Martinez, J., LeFevre, J., Xu, V., Hsu, M., Roy, I. Large scale predictive analytics in Vertica: Fast data transfer, distributed model creation and in-database prediction. _Sigmod 2015_, 1657-1668.

Venkataraman, S., Bodzsar, E., Roy, I., AuYoung, A., and Schreiber, R. (2013) Presto: Distributed Machine Learning and Graph Processing with Sparse Matrices. _EuroSys 2013_, 197-210.

Homepage: https://github.com/vertica/ddR

Examples

## Not run: 
useBackend(parallel,executors=2)
library(distributedR.ddR); useBackend(distributedR)

## End(Not run)

ddR documentation built on May 29, 2017, 6:52 p.m.