Sample: Retrieve records from an intersect table
This sample shows how to retrieve records from an intersect table.
How to run this sample
- Download or clone the Samples repo so that you have a local copy.
- (Optional) Edit the dataverse/App.config file to define a connection string specifying the Microsoft Dataverse instance you want to connect to.
- Open the sample solution in Visual Studio and press F5 to run the sample. After you specify a connection string in dataverse/App.config, any sample you run will use that connection information.
If you do not specify a connection string in dataverse/App.config file, a dialog will open each time you run the sample and you will need to enter information about which Dataverse instance you want to connect to and which credentials you want to use. This dialog will cache previous connections so that you can choose a previously used connection.
Those samples in this repo that require a connection to a Dataverse instance to run will include a linked reference to the dataverse/App.config file.
What this sample does
The QueryExpression
message is intended to be used in a scenario that contains queries in a hierarchy of expressions.
How this sample works
In order to simulate the scenario described in What this sample does, the sample will do the following:
Setup
- Checks for the current version of the org.
- The
CreateRequireRecords
method creates table records that are used by the sample. - The
QueryExpression
message is used to retrieve the default business unit needed to create the team. - The
WhoAmIRequest
gets the GUID of the current user. - The
Role
message instantiate a role table record and set its property values. - The
AssociateRequest
assigns the user to the Managers role.
Demonstrate
- The
QueryExpression
retrieves the records from an intersect table. - The
RetrieveMultipleRequest
builds the fetch request and obtains the results.
Clean up
Display an option to delete the records created in the Setup. The deletion is optional in case you want to examine the tables and data created by the sample. You can manually delete the records to achieve the same result.