Monitoring data flows
Use the Call instruction with several activities to track the status of data flows that were run in batch mode with the Call Data-Decision-DDF-RunOptions.pxRunDDFWithProgressPage method or submitted on the Data Flows landing page. You can track the number of processed records, and the elapsed or the remaining time of the data flow run.
Create an instance of the Activity rule in the Dev Studio navigation panel by clicking.
In the activity steps, provide the pyWorkObjectID property in order to identify which data flow run you want to monitor.
In the activity steps, enter one of the following methods to monitor a data flow:
- Call Data-Decision-DDF-RunOptions.pxInitializeProgressPage - Creates the progress page that consists of a top level page named Progress of the Data-Decision-DDF-Progress data type.
- Call Data-Decision-DDF-Progress.pxLoadProgress - Updates the current status.
Apart from the API methods for data flows, you can use a default section and harness to display and control execution progress of data flow runs:
- The Data-Decision-DDF-Progress.pyProgress section displays recent information. This section, which is also used on the Data Flows landing page, refreshes periodically to update the progress information.
- The Data-Decision-DDF-RunOptions.pxDDFProgress harness, which is also used in the run dialog box of the Data Flow rule, displays the complete harness for the data flow run. It provides the progress section and the action buttons that you use to start, stop, and restart the data flow run.
- Types of data flows
Data flows are scalable data pipelines that you can build to sequence and combine data based on various data sources. Each data flow consists of components that transform data and enrich data processing with business rules.
- Data Flows landing page
This landing page provides facilities for managing data flows in your application. Data flows allow you to sequence and combine data based on various sources, and write the results to a destination. Data flow runs that are initiated through this landing page run in the access group context. They always use the checked-in instance of the Data Flow rule and the referenced rules.
- Calling another activity
A keystore is a file that contains keys and certificates that you use for encryption, authentication, and serving content over HTTPS. In Pega Platform, you create a keystore data instance that points to a keystore file.
- Decision Management methods