AsterR: Memorializing Some Great Content on AsterR

Learn Data Science
Teradata Employee

I want to take a moment and thank Roger Fried for all the work he has done with the Aster Community.  I also want to highlight some really good work around AsterR.  Please take a look at the following blog posts:

LINK:  How AsterR is used in the “Data Discovery Process?

AsterR is a Teradata produced package installed within the R client application.  This package is distinct from, but complements, the installation of R within Aster.  Together the AsterR package and the R installation into Aster create a rich environment that provides the R user with the normal look and feel of R while maintaining the power and speed of Aster.  There is a great deal of new functionality in AsterR that duplicates standard R functions while carrying out the operations and data storage within Aster.

LINK:  R-in-Aster: Loading Helper Files into R During Stream Process

The primary path for loading data into R while it is running in-database within Aster is through the STDIN in a data frame format.  The STDIN is definitely the path for processing large volumes of data at high speeds.  On the other hand, there will be many instances where helper files are needed.  A randomForest type algorithm, for instance, will use a model file, a text analysis algorithm may use a dictionary file, etc.

LINK:  R-in-Aster: Basic Prototyping and Script Conversion

The process of converting an existing R script or creating a script from scratch is pretty easy.  The main requirement is an awareness of R Input / Output (I/O) techniques including database connection databases.  Or, if like me you skipped over the chapter on R I/O you can just copy the boilerplate R I/O code structures and paste them into your code.  This demo will focus on pasting in the boilerplate structures and tweaking a few parameters to get you up and running with a minimum of focus on the I/O structures themselves.