Index operations (Azure Cognitive Search REST API)
You can create and manage indexes in Azure Cognitive Search service via simple HTTP requests (POST, GET, PUT, DELETE) against a given index resource. An index specifies the structure of a search document via the fields collection of the index. Field names, data types, and attributes determine how individual fields are configured, analyzed, and used at query time. For example, attributes on the field determine whether a field is searchable, filterable, sortable, and so forth.
An index also defines other constructs, such as scoring profiles for relevance tuning, suggesters, and custom analyzers.
Connections to a search service can be authenticated using API keys or Azure roles.
Example
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 referenced on the field definition.
Within the fields collection, one field must service as the search document identifier. This field is attributed with "key": true (see the HotelId in the example below).
{
"name": "hotels",
"fields": [
{ "name": "HotelId", "type": "Edm.String", "key": true, "filterable": true },
{ "name": "HotelName", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": true, "facetable": false },
{ "name": "Description", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "en.microsoft" },
{ "name": "Description_fr", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "fr.microsoft" },
{ "name": "Category", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "Tags", "type": "Collection(Edm.String)", "searchable": true, "filterable": true, "sortable": false, "facetable": true, "analyzer": "tagsAnalyzer" },
{ "name": "ParkingIncluded", "type": "Edm.Boolean", "filterable": true, "sortable": true, "facetable": true },
{ "name": "LastRenovationDate", "type": "Edm.DateTimeOffset", "filterable": true, "sortable": true, "facetable": true },
{ "name": "Rating", "type": "Edm.Double", "filterable": true, "sortable": true, "facetable": true },
{ "name": "Address", "type": "Edm.ComplexType",
"fields": [
{ "name": "StreetAddress", "type": "Edm.String", "filterable": false, "sortable": false, "facetable": false, "searchable": true },
{ "name": "City", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "StateProvince", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "PostalCode", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "Country", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true }
]
},
{ "name": "Location", "type": "Edm.GeographyPoint", "filterable": true, "sortable": true },
{ "name": "Rooms", "type": "Collection(Edm.ComplexType)",
"fields": [
{ "name": "Description", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "en.lucene" },
{ "name": "Description_fr", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "fr.lucene" },
{ "name": "Type", "type": "Edm.String", "searchable": true },
{ "name": "BaseRate", "type": "Edm.Double", "filterable": true, "facetable": true },
{ "name": "BedOptions", "type": "Edm.String", "searchable": true },
{ "name": "SleepsCount", "type": "Edm.Int32", "filterable": true, "facetable": true },
{ "name": "SmokingAllowed", "type": "Edm.Boolean", "filterable": true, "facetable": true },
{ "name": "Tags", "type": "Collection(Edm.String)", "searchable": true, "filterable": true, "facetable": true, "analyzer": "tagsAnalyzer" }
]
}
],
"suggesters": [
{ "name": "sg", "searchMode": "analyzingInfixMatching", "sourceFields": ["HotelName"] }
],
"analyzers": [
{
"@odata.type": "#Microsoft.Azure.Search.CustomAnalyzer",
"name": "tagsAnalyzer",
"charFilters": [ "html_strip" ],
"tokenizer": "standard_v2"
}
]
}
After the index is created, you'll upload documents that populate the index. See Add, Update, or Delete Documents for this next step.