Monitoring data flows

Use the Call instruction with several activities to track the execution status of data flows that were executed 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 recorded, and the elapsed or the remaining time of the data flow execution.

1. Create an instance of the Activity rule by selecting Activity from the Technical category.

2. In the activity steps, provide the pyWorkObjectID property in order to identify which data flow run you want to monitor.

3. In the activity steps, use one of the following methods to monitor a data flow:

   • Call Data-Decision-DDF-RunOptions.pxInitializeProgressPage - It 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 - It updates the current status.

4. Click Save.

Additionally, you can use a default section and harness to display and control execution progress:

• 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 of Data Flow rule, displays the complete harness for the data flow run. It provides the progress section and the action buttons that allow you to start, stop, and restart the data flow run.

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