PeopleTools 8.62: Data Distribution Framework
PeopleTools 8.62: Data Distribution Framework
April 2025
PeopleTools 8.62: Data Distribution Framework
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PeopleTools Data Distribution Framework is built using the technology from PeopleSoft Search
Framework, such as mappings used to create search index definitions, search instance for defining search
server, and DirectTransfer technology used to index data from PeopleSoft to the search engine. The data is
made available in search engine in JSON format.
The search indexes built for search can be re-used for machine learning or other activities. The data
available from this framework can be used by Oracle Cloud Infrastructure (OCI) Data Science service
to create models that are used for prediction. The OCI Data Science platform is an Oracle Cloud
Infrastructure service. You can use an on-premise PeopleSoft instance or a PeopleSoft instance on OCI.
For more information on OCI Data Science service, see the Data Science documentation on the Oracle
Cloud Infrastructure Documentation website.
• Data Source Definition - This is the data layer, which uses existing PeopleSoft data sources and
contains the definitions required to send data to the search engine from PeopleSoft.
• Search Instance - Data is sent to this search instance. Search instance is defined in PeopleSoft Search
Framework.
• Machine Learning Server configuration - This is the server, which uses the data in Data Distribution
framework and creates models.
Search engine stores the deployed search definitions, builds indexes, and maintains indexes. The OCI
Data Science platform pulls the data from search indexes and trains and builds a model.
The server topology includes the essential elements of a PeopleSoft system, and includes a search server
and an OCI Data Science service.
The following diagram describes the interaction of the PeopleSoft system elements, search server, and the
OCI Data Science service.
The web server and application server (the PeopleSoft Internet Architecture) provide the interface for the
design, administration, and end user access. The PeopleSoft database stores the PeopleSoft queries that
define the search definition metadata.
2. OCI Data Science service pulls data from the search engine.
3. The data is used to train the machine learning model in the Jupyter notebook on the OCI Data Science
service.
4. When the model is created, it can be saved in the OCI object storage.
5. The saved model can be deployed as a REST service using OCI Functions and OCI API Gateway.
The following diagram illustrates the process flow among PeopleSoft, search server, and OCI Data
Science service.
This documentation covers the tasks that are performed in PeopleSoft. For tasks that should be performed
on the OCI Data Science service, such as creating a model, deploying model as REST service and so on,
refer to the OCI Data Science documentation on Oracle Cloud Infrastructure Documentation website.
PeopleSoft provides a navigation collection – Data Distribution Setup – that enables you to perform the
following tasks:
• Register a model.
For information on creating a search definition, see “Creating Search Definitions” (Search Technology).
Access the Data Source Definition page by navigating to PeopleTools > Machine Learning > Data
Distribution Framework > Data Distribution Setup and select Data Source (under the Definition
folder in the left panel). Alternatively, you can navigate to PeopleTools > Machine Learning > Data
Distribution Framework > Define Data Sources.
This example illustrates the fields and controls on the Data Source Definition page. You can find
definitions for the fields and controls later on this page.
The Data Source Definition page displays a list of data sources that you have set up. Use the Source drop-
down list to identify the data source that you require.
To add a new data source, select the Add Data Source button. Use the Data Source Details page to enter
details of a new data source.
Data Source Name Select a search definition. The drop-down list displays all the
search definitions created in Search Framework.
Access the Server Definition page by navigating to PeopleTools > Machine Learning > Data
Distribution Framework > Data Distribution Setup, and select Machine Learning Server (under
the Definition folder in the left panel). Alternatively, you can navigate to PeopleTools > Machine
Learning > Data Distribution Framework > Machine Learning Server.
This example illustrates the fields and controls on the Server Definition page. You can find definitions for
the fields and controls later on this page.
The Server Definition page displays a list of servers that you have set up. Use the Instance Name drop-
down to identify the server that you require. You may set up as many servers as you require.
To add a new instance of a server, select the Add button. Use the Machine Learning Server Configuration
page to specify the details of the new server.
Note: The search instance with the priority set at the lowest
number has the highest priority, and it will be set as the default
server instance.
Host Name Enter the server name of the host where the OCI Data Science
platform server is running, including the domain. The host
name value can be a DNS name or an IP address.
Port Enter the port on which the server listens for requests.
Admin User Name Enter the user name to connect to the server.
Admin Password Enter the password associated with the user name.
Ping Select to make sure your host name and port are correct and
that the server is available. A positive result displays a success
message.
Building an Index
After you have defined a data source, you should create an index in the search engine. The OCI Data
Science service pulls data from the search index to build and train the machine learning model.
You use the Index Manager page to create an index for a data source and to update an index.
Access the Index Manager page by navigating to PeopleTools > Data Distribution
Framework > Data Distribution Setup, and select Manage Data Source Indexes (from the Indexing
folder in the left panel). Alternatively, you can navigate to PeopleTools > Data Distribution
Framework > Manage Data Source Indexes.
This example illustrates the fields and controls on the Index Manager page. You can find definitions for
the fields and controls later on this page.
Index Name The system appends an index with the database to differentiate
it from indexes with the same name in other databases.
Registering a Model
The machine learning model can be deployed as a REST endpoint after it has been trained and built. Use
the Model page to register the REST endpoint. PeopleSoft applications and users use the REST endpoint
using the delivered IB_Generic service in Integration Broker.
Access the Model Definition page by navigating to PeopleTools > Data Distribution
Framework > Data Distribution Setup, and select Model (under the Inference folder in the left panel).
Alternatively, you can navigate to PeopleTools > Data Distribution Framework > Machine Learning
Models.
This example illustrates the fields and controls on the Model Definition page. You can find definitions for
the fields and controls later on this page.
The Model Definition page displays a list of existing model definitions. The Model Name drop-down
enables you to identify the model that you require.
To add a new model, select the Add Model button. Use the Model Definition page to specify details of a
new model.
Source Select a data source from the list. The data sources are listed
here.
Note: The system appends the value entered here to the server
host to create a fully qualified REST endpoint.
2. OCI Data Science service pulls data from the search engine.
3. The data is used to train the machine learning model using the Python file artifact on the OCI Data
Science service.
4. When the model is created, it can be saved in the OCI object storage.
5. The saved model can be deployed using PeopleSoft Data Science Setup.
6. OCI Data Science service pulls credentials and job information from PeopleSoft to automatically run
jobs.
7. OCI Data Science runs prediction endpoint using the model name and data set.
The following diagram illustrates the process flow among PeopleSoft, search server, and OCI Data
Science service.
PeopleSoft provides a navigation collection – Data Science Setup – that enables you to perform the
following tasks:
• Register a model.
Access the Common Configuration page by navigating to PeopleTools > Machine Learning > Data
Science Setup.
Note: The fields on this page must be filled using the information collected from the OCI data science
system.
This example illustrates the fields and controls on the Common Configuration page. You can find
definitions for the fields and controls later on this page.
Field Description
Tenancy OCID Enter the OCID of your tenancy. To get the value, see
Required Keys and OCIDS.
Example: ocid1.tenancy.oc1.
aaaaaaaaba3xxxxxxxxxxxxxxxxxxxxxx
User OCID Enter OCID of the user calling the endpoint. To get the value,
see Required Keys and OCIDS.
Example: ocid1.user.oc1.
aaaaaaaa3xxxxxxxxxxxxxxxxxxxxxxxxx
Fingerprint Enter the fingerprint for the key pair being used. To get the
value, see Required Keys and OCIDS.
Example:
20:3b:97:13:55:1c:5b:0d:d3:37:d8:50:4e:c5
:3a:34
Field Description
Note: You must place the private key file in either application
server or Process Scheduler, based on the location from where
you execute the job.
PrivatekeyPassphrase Enter the encrypted pass phrase for the signer's private key.
The values of Display Name, Model Deployment VM Shape, Model Deployment Number of Instance and
Model Deployment Load Balancer Bandwidth defined on this page will override the corresponding values
in the OCI system, if those values were provided during OCI artifact creation or job creation.
Access the Data Science Configuration page by navigating to PeopleTools > Machine Learning
> Data Science Setup > Data Science Configuration.
This example illustrates the fields and controls on the Data Science Configuration page. You can find
definitions for the fields and controls later on this page.
Field Description
Field Description
Create Model Click to create a new model from Model Definition page in
Data Distribution Framework, if you do not want to use the
existing models.
Job ID Mandatory parameter to run the data science job. Enter the
OCID of the user-defined job.
Model Deployment VM Shape Enter the VM shape associated with the model deployment.
Model Deployment Number of Instance Enter the number of instance associated with the model
deployment.
Model Deployment Load Balancer Band Width Enter the load balancer bandwidth associated with the model
deployment.
Compartment ID Mandatory parameter to run the data science job. Enter the
OCID of the PeopleSoft data science compartment used for job
creation.
Data Science Project ID Mandatory parameter to run the data science job. Enter the
OCID of the PeopleSoft data science project used for job
creation.
Provide the server name and recurrence corresponding to the Machine Learning model that is already
deployed in Data Distribution Server to automatically execute the Python jobs in data science service.
Access the Data Science Configuration page by navigating to PeopleTools > Machine Learning
> Data Science Setup > Schedule Data Science Jobs.
This example illustrates the fields and controls on the Schedule Data Science Jobs page. You can find
definitions for the fields and controls later on this page.
Field Description
Server Name Select the Process Scheduler server where you run the job.
Schedule Job Click to schedule a job with the selected model, server, and
recurrence.
The Schedule Data Science Jobs page displays a process list with details about the jobs that are run. Select
the Go to Process Monitor link provided on the page to view more details of the scheduled jobs.