A.4 Verifying the Oracle Machine Learning for R Installation
To verify that the basic functionality of OML4R is working, establish a connection to an OML4R server and execute several basic functions.
Note:
To start and use OML4R, your database user must have the privileges required for OML4R installation. See User Requirements for details.
Example A-2 Connecting to an OML4R Server
To connect the an OML4R client to an OML4R server:
-
Select R x64 3.3.0 from the Windows Start menu.
The R Console is displayed.
-
Type this command to start OML4R:
$ ORE R> library(ORE)
-
Type this command to connect to the OML4R server. The following example connects user
OML_USER
to the databaseorcl
on the server hostserv1
using port 1521:> ore.connect(user="OML_USER", sid="orcl", host="serv1", password="OML_USERpsw", port=1521, all=TRUE) Loading required package: ROracle Loading required package: DBI
-
Execute
ore.is.connected
to validate the connection. If the connection is successful, the function returnsTRUE
:> ore.is.connected() [1] TRUE
Example A-3 Listing the Database Tables Accessible in a Schema
The ore.ls
function
lists the ore.frame
proxy objects
that correspond to database tables in the
environment for a schema. In the following
example, TABLE1
and
TABLE2
exist in the current
schema:
> ore.ls() [1] "TABLE1" "TABLE2"
Example A-4 Pushing an R Data Frame to the Database
The ore.push
function
pushes a local R object into an OML4R object of the appropriate data type in
the database. The following example creates an R
data.frame
and pushes it an
ore.frame
object in the
database.
df <- data.frame(a="abc",
b=1.456,
c=TRUE,
d=as.integer(1))
of <- ore.push(df)
Example A-5 Executing an Embedded R Function
The ore.doEval
function
executes the specified function in an R engine on
the database server and returns the results. This
example declares a function in the
ore.doEval
invocation.
> ore.doEval(function() { 123 }) [1] 123
Parent topic: A Sample Installation of Oracle Machine Learning for R