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Sample: Use FetchXML with a paging cookie

  • Άρθρο

This sample shows how to use the paging cookie in a FetchXML query to retrieve successive pages of query results. It uses the IOrganizationService.RetrieveMultiple.

SDK for .NET: Use FetchXML with a paging cookie sample code

How to run this sample

  1. Download or clone the Samples repo so that you have a local copy.
  2. (Optional) Edit the dataverse/App.config file to define a connection string specifying the Microsoft Dataverse instance you want to connect to.
  3. 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 IOrganizationService.Retrieve method is intended to be used in a scenario where it contains data that retrieves all the records.

How this sample works

In order to simulate the scenario described in What this sample does, the sample will do the following:

Setup

  1. Checks for the current version of the org.
  2. The Account method creates an parent account record and also 10 child account records.

Demonstrate

The fetchXml creates the FetchXML string for retrieving all child accounts to a parent account. This fetch query is using 1 placeholder to specify the parent account id for filtering out required accounts.

Clean up

Displays an option to delete all the data created in the sample. The deletion is optional in case you want to examine the data created by the sample. You can manually delete the data to achieve same results.