Use an indexer to build an index
In order to index the documents in Azure Storage, they need to be exported from their original file type to JSON. In order to export data in any format to JSON, and load it into an index, we use an indexer.
To create search documents, you can either generate JSON documents with application code or you can use Azure's indexer to export incoming documents into JSON.
Azure AI Search lets you create and load JSON documents into an index with two approaches:
Push method: JSON data is pushed into a search index via either the REST API or the .NET SDK. Pushing data has the most flexibility as it has no restrictions on the data source type, location, or frequency of execution.
Pull method: Search service indexers can pull data from popular Azure data sources, and if necessary, export that data into JSON if it isn't already in that format.
Use the pull method to load data with an indexer
Azure AI Search's indexer is a crawler that extracts searchable text and metadata from an external Azure data source and populates a search index using field-to-field mappings between source data and your index. Using the indexer is sometimes referred to as a 'pull model' approach because the service pulls data in without you having to write any code that adds data to an index. An indexer maps source fields to their matching fields in the index.
Data import monitoring and verification
The search services overview page has a dashboard that lets you quickly see the health of the search service. On the dashboard, you can see how many documents are in the search service, how many indexes have been used, and how much storage is in use.
When loading new documents into an index, the progress can be monitored by clicking on the index's associated indexer. The document count will grow as documents are loaded into the index. In some instances, the portal page can take a few minutes to display up-to-date document counts. Once the index is ready for querying, you can then use Search explorer to verify the results. An index is ready when the first document is successfully loaded.
Indexers only import new or updated documents, so it is normal to see zero documents indexed.
The Search explorer can perform quick searches to check the contents of an index, and ensure that you are getting expected search results. Having this tool available in the portal enables you to easily check the index by reviewing the results that are returned as JSON documents.
Making changes to an index
You have to drop and recreate indexes if you need to make changes to field definitions. Adding new fields is supported, with all existing documents having null values. You'll find it faster using a code-based approach to iterate your designs, as working in the portal requires the index to be deleted, recreated, and the schema details to be manually filled out.
An approach to updating an index without affecting your users is to create a new index under a different name. You can use the same indexer and data source. After importing data, you can switch your app to use the new index.