What is a flow run?
Flow runs represent an instance of dataflow execution. For example, if a dataflow is scheduled to run hourly at 9:00 AM, 10:00 AM, and 11:00 AM, then you would have three instances of a flow run. Flow runs are specific to your particular organization.
Getting started
NOTEThis document requires a working understanding of the following components of Experience Platform:
- Sources: Experience Platform allows data to be ingested from various sources while providing you with the ability to structure, label, and enhance incoming data using Experience Platform services.
- Dataflows: A dataflow is a representation of data jobs that move data across Experience Platform. Dataflows are configured across different services, helping move data from source connectors to target datasets, to Identity Service and Real-Time Customer Profile, and to Destinations.
- Sandboxes: Experience Platform provides virtual sandboxes that partition a single Experience Platform instance into separate virtual environments to help develop and evolve digital experience applications.
Create a dataflow on demand
Navigate to the Dataflows tab of the sources workspace. From here, find the dataflow that you want to run on demand, and then select the ellipses (...) beside your dataflow name.
Next, select Run on-demand from the dropdown menu that appears.
Configure the schedule of your on-demand ingestion. Select the Ingestion start time, the Date range start time, and the Date range end time.
| Scheduling configuration | Description |
|---|---|
| Ingestion start time | The scheduled time of when the on-demand flow run will begin. |
| Date range start time | The earliest date and time that data will be retrieved from. |
| Date range end time | The date and time that data will be retrieved up to. |
Select Schedule and allow a few moments for your on-demand dataflow to trigger.
Select your dataflow name to view your dataflow activity. Here you will see a list of your dataflow runs that have been processed. You can re-run individual iterations of your dataflow runs regardless of whether they have failed or succeeded. For run iterations that have failed, you can use Retry to initiate the run again after diagnosing and addressing any errors that may have been encountered during the creation process.
Select Scheduled to see a list of dataflow runs that are scheduled for future ingestion.
Next steps
By reading this document, you have learned how to create flow runs on demand for existing sources dataflows. For more information on sources, read the sources overview
