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Demystifying Teradata AsterR - R in Parallel, R at Scale

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.  All the Aster analytic functions may be executed from R using SQL, but many of the functions such as nPath, cFilter, Minhash, and Random Forest have been "translated" into a pure R look and feel.  In addition, AsterR provides pathways called the "R Runners" to push R code into Aster for execution.

Database Integration

At its most trivial level, AsterR provides R with database integration.  Simple DB integration is something that R users are trying to achieve in a variety of ways because it begins to address some of R's most important weaknesses.  Typically data is passed into and out of R via flat files, ODBC integration is awkward, its file system is not open, and it even struggles with Excel files.  R also suffers from important limitations in the size of the data that it can manage and simple DB integration provides workarounds.

AsterR establishes a connection to Aster that is based on both ODBC for small data exchanges and mule copy for large data exchanges.  Using Aster as a simple database provides enterprise quality security for accessing and subsequently landing data and Aster is a component of the larger Teradata Unified Data Architecture so data can easily be sourced from Hadoop, an EDW, or other enterprise systems.

Example

Create Connection to Aster

AsterR <- ta.connect("aster", uid = "bob",     pwd = "open_seseme", database = "r", dType = "odbc")

Create an AsterR Virtual Data Frame from an Aster Table or a View to Hadoop or Teradata EDW

salaries <- ta.data.frame("salaries", schemaName = "baseball")

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Tags: Analytics, Aster, AsterR, R, Teradata

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