Contents
TIBCO StreamBase operator for TERR and the TIBCO StreamBase operator for TERR Predict were designed to make it easy to use TERR within a StreamBase application and support many options for dealing with TERR. These samples illustrate the minimum needed to use TERR. Their purpose is not to teach TERR; for that, see the extensive TERR documentation.
The TERR operators require an installation of TERR 4.0 or later on the same machine on which Streaming is installed, as described in the Authoring Guide pages for each operator.
Note
Streaming bundles a Developer Edition of TERR in STREAMBASE_HOME/terr
on Linux and WIndows only. You can use the
bundled edition of TERR for experimentation and development, but not for deployment
as described in License
Considerations.
In StreamBase Studio, import this sample with the following steps:
-
From the top-level menu, click
> . -
Enter
terr
to narrow the list of options. -
Select the TERR and TERR Predict Operators from the Other TIBCO Product Connectivity category.
-
Click
.
StreamBase Studio creates a single project to contain the sample's files.
The TERR Predict sample shows how the TERR Predict operator works. It is set up to
use the included myModel.RDS
file, which contains the
following R data as follows:
lm(y~x, data.frame(x=1:100,y=log(1:100)))
The steps to run this sample in Studio are as follows:
-
In the Project Explorer view, open the sample you just loaded.
If you see red marks on a project folder, wait a moment for the project to load its features.
If the red marks do not resolve themselves after a minute, select the project, right-click, and select
> from the context menu. -
Open the
src/main/eventflow/
folder.packageName
-
Open the
file and click the Run button. This opens the SB Test/Debug perspective and starts the module. Notes are also provided on the EventFlow Editor canvas.predict.sbapp
-
In the Manual Input view of the SB Test/Debug perspective, you can either leave the input null for defaults to be used, or you can enter values for an input tuple.
Each input tuple results in an R execution and a result is returned in the terrData output tuple. The status stream displays any messages if the execution had any errors.
The TERR General sample shows how the TERR General operator works. It is set up to
use the included myModel.r
, myModel.RDS
, and myModel.RData
files,
which all contain the same R data as follows:
lm(y~x, data.frame(x=1:100,y=log(1:100)))
The steps to run this sample in Studio are as follows:
-
Continuing with the same sample, open the
file and click the Run button. This opens the SB Test/Debug perspective and starts the module. Notes are provided on the EventFlow Editor canvas.general.sbapp
-
In the Manual Input view of the SB Test/Debug perspective, you can either leave the input null for defaults to be used, or you can enter values for an input tuple.
Each input tuple results in an R execution and a result is returned in the terrData output tuple. The status stream displays any messages if the execution had any errors.
The TERR Init Via File Load sample shows how the TERR General operator can load R
data objects during runtime. It is set up to use the included myModel.r
, myModel.RDS
, and
myModel.RData
files, which all contain the same R data
as follows:
lm(y~x, data.frame(x=1:100,y=log(1:100)))
The steps to run this sample in Studio are as follows:
-
Continuing with the same sample, open the
file and click the Run button. This opens the SB Test/Debug perspective and starts the module. Notes are also provided on the EventFlow Editor canvas.init_via_fileload.sbapp
-
In the Manual Input view of the SB Test/Debug perspective, you can either leave the input null for defaults to be used, or you can enter values for an input tuple.
Each input tuple results in an R execution and a result is returned in the terrData output tuple. The status stream displays any messages if the execution had any errors.
The TERR Advanced sample shows how you could change from using the TERR Predict
Operator over to use the TERR General operator without having to change event flow.
If you have a use case that changes and you require the more advanced feature set of
the TERR General operator you can set it up to mirror how the TERR Predict operator
works fairly easily. The file advanced_demo.R
in the
project explorer shows what R information is stored in the RDS files used in this
example.
The steps to run this sample in Studio are as follows:
-
Continuing with the same sample, open the
file and click the Run button. This opens the SB Test/Debug perspective and starts the module. Notes are also provided on the EventFlow Editor canvas.advanced.sbapp
-
In the Manual Input view of the SB Test/Debug perspective press the send tuple button to send a tuple into the event flow.
Each input tuple results in an R execution and notice that the result of the
TERRGeneralOut
andTERRPredictOut
streams match each other.
The artifact management sample demonstrates how you can use a TIBCO Artifact Management Server to load new versions of R artifacts at runtime.
The TIBCO Artifact Management Server is a separately installed product. This sample assumes that you have a running Artifact Management Server (AMS) that is accessible by StreamBase. Refer to the product documentation for more information regarding AMS.
This sample also requires that you do the following:
-
Create a project folder in the Artifact Management Server called
sample
. -
Navigate to
sample/terr/src/main/resources
from your StreamBase installation directory and upload theadvanced_demo_data.rds
andadvanced_demo_model.rds
files to the AMSsample
project folder. Note that thesample/terr
directory in StreamBase is a different directory from the AMSsample
project folder.
Run this sample in Studio as follows:
-
Continuing with the same sample, open the
file and click the Run button. This opens the SB Test/Debug perspective and starts the module. Notes are also provided on the EventFlow Editor canvas.artifactmanagement.sbapp
-
The application will try to pull the artifacts from AMS. Note that the
Required On Startup
option is selected for all operators, which means all the artifacts must be loaded from the AMS system before the application will run. If all artifacts cannot be loaded within a specific period of time, the system will fail with anartifact timeout
exception. -
In the Manual Input view of the SB Test/Debug perspective press the send tuple button to send a tuple into the event flow.
Each input tuple results in an R execution. Notice that the result of the
Data
streams match each other. -
From AMS, deploy the model again to the running
artifactmanagement.sbapp
application using the following properties:-
Target Type:
-
StreamBase Service Name
The node name that appears in the studio cluster view for this application
-
-
In the Output Streams view, notice the
Status
output tuple showing a new model was loaded.
When you load the sample into StreamBase Studio, Studio copies the sample project's files to your Studio workspace, which is normally part of your home directory, with full access rights.
Important
Load this sample in StreamBase Studio, and thereafter use the Studio workspace copy of the sample to run and test it, even when running from the command prompt.
Using the workspace copy of the sample avoids permission problems. The default workspace location for this sample is:
studio-workspace
/sample_terr
See Default Installation
Directories for the default location of studio-workspace
on your system.