Configure Dependencies between Datasets
This article describes how to establish dependencies between Datasets by using references in SQL statements and how these dependencies affect Data Collection Trigger (DCT) processing of the Datasets.
- For details on building Datasets, see Create a Dataset from any Data Source
1. Create a New or Access an Existing Dataset
On the Data tab:
- Enter an SQL command. You can reference any available Datasets
- View all the Available Datasets that can be referenced from the current Dataset
2. Check the Dataset Grids
2.1. View the Dependent Dataset
- The Datasets, whose data is used in the current Dataset, are displayed in the Datasets referenced in SQL statement grid
- Datasets that utilize a trigger different from the current Dataset's trigger are displayed in gray color
- Access the referenced Dataset
Referenced Datasets that use different trigger are not considered in the "ready for execution" dependency check during DCT processing.
- See Dataset Dependencies in Data Collection Trigger for more details
2.2. View the Referenced Dataset
- The dependent Datasets, that use this Dataset's data, are displayed in the Datasets fetching data from this Dataset grid
- Access current Dataset's Data Collection Trigger Editor by clicking on the gear icon
If fetch command for the current Dataset fails, DCT processing for all the dependent Datasets will also fail.
Note: Any error except the "0 rows fetched" condition is considered in this evaluation.
3. Check Dataset Dependencies in Data Collection Trigger
On the Recent Runs tab:
- Click [Details] to view the last Trigger run's log
- Note that the data for referenced Dataset is collected prior to the dependent Dataset's data
Only the "ready for execution" Datasets are picked at each stage of DCT processing.
- A Dataset is considered to be "ready for execution" if all the referenced Datasets that utilize the current Dataset's trigger have successfully been updated during DCT processing