Index operations (Azure Search Service REST API)

You can create and manage indexes in Azure Search service via simple HTTP requests (POST, GET, PUT, DELETE) against a given index resource. To create an index, you first POST a JSON document that describes the index schema. The schema defines the fields of the index, their data types, and how they can be used (for example, in full-text searches, filters, sorting, or faceting). It also defines scoring profiles, suggesters, analyzers, and other attributes to configure the behavior of the index.

The following example illustrates an index schema that includes fields, a suggester, a custom analyzer, and a language analyzer. Fields, suggesters, custom analyzers, and scoring profiles (not shown) are sections in the index. A language analyzer is predefined and simply referenced on the field definition.

Within the field definition, attributes control how the field is used. For example, "key": true marks the field that is used to uniquely identify a document (hotelId in the example below). Other attributes like searchable, filterable, sortable, and facetable can be specified to change default behaviors. For example, they are used on the description field to turn off filtering, sorting and faceting. These features aren't needed for verbose text like a description, and turning them off saves space in the index.

Language-specific fields are also illustrated in this index. Description fields exist for English (default) and for French translations, with the French translation using the fr.lucene analyzer for lexical analysis.

 "name": "hotels",  
 "fields": [
  {"name": "hotelId", "type": "Edm.String", "key": true, "searchable": false},
  {"name": "baseRate", "type": "Edm.Double"},
  {"name": "description", "type": "Edm.String", "filterable": false, "sortable": false, "facetable": false},
  {"name": "description_fr", "type": "Edm.String", "filterable": false, "sortable": false, "facetable": false, "analyzer": "fr.lucene"},
  {"name": "hotelName", "type": "Edm.String"},
  {"name": "category", "type": "Edm.String"},
  {"name": "tags", "type": "Collection(Edm.String)", "analyzer": "tagsAnalyzer"},
  {"name": "parkingIncluded", "type": "Edm.Boolean"},
  {"name": "smokingAllowed", "type": "Edm.Boolean"},
  {"name": "lastRenovationDate", "type": "Edm.DateTimeOffset"},
  {"name": "rating", "type": "Edm.Int32"},
  {"name": "location", "type": "Edm.GeographyPoint"}
 "suggesters": [
   "name": "sg",
   "searchMode": "analyzingInfixMatching",
   "sourceFields": ["hotelName"]
 "analyzers": [
   "name": "tagsAnalyzer",
   "type": "#Microsoft.Azure.Search.CustomAnalyzer",
   "charFilters": [ "html_strip" ],
   "tokenizer": "standard"

After the index is created, you'll upload documents that populate the index. See Add, Update or Delete Documents (Azure Search Service REST API) for this next step.

For a code sample that shows how to create and build an index using the REST API, see Get Started with Azure Search using REST.

For a video introduction to indexing, see the Channel 9 Cloud Cover episode 152 on Azure Search.

Operations on indexes

See Also

Azure Search Service REST
Service limits in Azure Search
Azure Search .NET library