Implementing suggestions for Azure Search

Azure Search provides a suggestions feature that allows users to view a list of potential search terms in response to partial string inputs.

If you wish to use search suggestions on your website, you need to add a suggester construction to your search indexes. The suggester specifies a list of fields that are used as sources for the content of suggestions.

For detailed information, refer to the following articles:

To add a suggester for an Azure Search index managed by Kentico, you need to customize the functionality that Kentico uses to build the indexes:

  1. Open your Kentico solution in Visual Studio.
  2. Create a custom module class.
  3. Override the module’s OnInit method and assign a handler to the SearchServiceManager.CreatingOrUpdatingIndex.Execute event.
  4. Perform the following in the event’s handler method:
    1. Access the Microsoft.Azure.Search.Models.Index object representing the processed index via the Index property of the handler’s CreateOrUpdateIndexEventArgs parameter.

    2. Write conditions to add different suggesters for specific indexes.

    3. Prepare a Microsoft.Azure.Search.Models.Suggester object according to your requirements and add it to the Suggesters list of the processed index.


      The system triggers the CreatingOrUpdatingIndex event both when building new indexes and when updating indexes that already exist under the specified Azure Search service. Depending on the number of indexed pages or objects and the used batch size, the event may occur multiple times when building a single search index (separately for each batch of processed search documents that include a new field not yet contained by the index).

      Your code needs to handle the following scenarios:

      • The index already contains the suggester you are adding.
      • The index does not yet contain all possible fields (for example in cases where the first processed batch of search documents does not include an object with the required fields).

      See the code of the example below.

  5. If you are utilizing the MVC development model, also deploy the custom module class to your separate MVC application (otherwise indexing may not work correctly for changes performed through the live site).
  6. Sign in to the Kentico administration interface.
  7. Open the Smart search application and Rebuild any related Azure Search indexes.

The system creates the customized Azure Search indexes with the specified suggester. You can see the suggester when viewing the details of index fields in the Microsoft Azure portal.

You can now adjust your search functionality or components to retrieve and display the suggestions – you need to call the ISearchIndexClient.Documents.Suggest method when users input search text and process the retrieved DocumentsSuggestResult data.


The following example demonstrates how to create a suggester for an Azure Search index named dg-store. The sample suggester uses the skuname field (containing product names) as the source for suggestions.

Start by preparing a separate project in your Kentico solution for the custom module class:

  1. Open your Kentico solution in Visual Studio.

  2. Create a new Class Library project in the Kentico solution named SearchCustomization.

  3. Add references to the required Kentico libraries (DLLs) for the new project:

    1. Right-click the project and select Add -> Reference.

    2. Switch to the Browse tab, click Browse, and navigate to the Lib folder of your Kentico web project.

    3. Add references to the following libraries:

      • CMS.Base.dll
      • CMS.Core.dll
      • CMS.DataEngine.dll
      • CMS.Search.Azure.dll
  4. Right-click the SearchCustomization project in the Solution Explorer and select Manage NuGet Packages.

  5. Install the Microsoft.Azure.Search package.

  6. Reference the SearchCustomization project from the Kentico web project (CMSApp or CMS).

  7. Edit the SearchCustomization project’s AssemblyInfo.cs file (in the Properties folder).

  8. Add the AssemblyDiscoverable assembly attribute:

     using CMS;

Continue by implementing the custom module class and rebuilding your search index:

  1. Create a new class named CustomAzureSearchModule under the SearchCustomization project, with the following code:

     using System;
     using System.Collections.Generic;
     using System.Linq;
     using CMS;
     using CMS.DataEngine;
     using CMS.Search.Azure;
     using Microsoft.Azure.Search.Models;
     // Registers the custom module into the system
     [assembly: RegisterModule(typeof(CustomAzureSearchModule))]
     public class CustomAzureSearchModule : Module
         // Module class constructor, the system registers the module under the name "CustomAzureSearch"
         public CustomAzureSearchModule()
             : base("CustomAzureSearch")
         // Contains initialization code that is executed when the application starts
         protected override void OnInit()
             // Assigns a handler to the CreatingOrUpdatingIndex event for Azure Search indexes
             SearchServiceManager.CreatingOrUpdatingIndex.Execute += AddSuggester;
         private void AddSuggester(object sender, CreateOrUpdateIndexEventArgs e)
             Microsoft.Azure.Search.Models.Index index = e.Index;
             // Ends the handler method if the index name is not 'dg-store'
             if (!index.Name.Equals("dg-store", StringComparison.InvariantCultureIgnoreCase))
             // Initializes the index's list of suggesters (if it does not exist)
             if (index.Suggesters == null)
                 index.Suggesters = new List<Suggester>();
             // Used to determine whether a new suggester was created and needs to be added to the index
             bool newSuggester = false;
             // Checks whether the index already contains a suggester named 'productnamesuggester'
             Suggester suggester = index.Suggesters.FirstOrDefault(s => s.Name == "productnamesuggester");
             // Creates a new suggester if it does not exist
             if (suggester == null)
                 suggester = new Suggester
                     Name = "productnamesuggester",
                     SourceFields = new List<string>()
                 // A new suggester was created, it needs to be added to the index
                 newSuggester = true;
             // Creates a dictionary containing the index's fields
             Dictionary<string, Field> indexFields = index.Fields.ToDictionary(f => f.Name, StringComparer.InvariantCultureIgnoreCase);
             // Confirms that the index contains the 'skuname' field and that it is not yet added as a suggester source field
             if (indexFields.ContainsKey("skuname") && !suggester.SourceFields.Contains("skuname", StringComparer.InvariantCultureIgnoreCase))
                 // Adds the 'skuname' fields as a source for suggestions
             // If a new suggester was created and is not empty, adds it to the index
             if (newSuggester && suggester.SourceFields.Count > 0)
  2. Save all changes and Build the SearchCustomization project.

  3. Sign in to the Kentico administration interface.

  4. Open the Smart search application and Rebuild the dg-store index.

The dg-store Azure Search index now contains the productnamesuggester suggester, using skuname as the source field for the content of suggestions. To retrieve and display the suggestions, you need to implement the required logic in your search functionality (see Integrating Azure Search into MVC projects or Integrating Azure Search into pages for general information). Call the ISearchIndexClient.Documents.Suggest method and process the retrieved DocumentSuggestResult data.

using System;

using Microsoft.Azure.Search;
using Microsoft.Azure.Search.Models;


if (!String.IsNullOrWhiteSpace(searchString))
    // Retrieves suggestions based on search input using 'productnamesuggester'
    DocumentSuggestResult suggestResult = searchIndexClient.Documents.Suggest(searchString, "productnamesuggester");