db.collection.createSearchIndex()
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Definition
New in version 7.0: (Also available starting in 6.0.7)
Creates an Atlas Search index or Vector Search index on a specified collection.
Important
This command can only be run on a deployment hosted on MongoDB Atlas, and is not supported in serverless instances.
Important
mongosh Method
This page documents a mongosh
method. This is not
the documentation for database commands or language-specific drivers,
such as Node.js.
For the database command, see the createSearchIndexes
command.
For MongoDB API drivers, refer to the language-specific MongoDB driver documentation.
Syntax
Command syntax:
db.<collection>.createSearchIndex( <name>, <type>, { <definition> } )
Command Fields
createSearchIndex()
takes these fields:
Field | Type | Necessity | Description |
---|---|---|---|
name | string | Optional | Name of the search index to create. You cannot create multiple indexes with the same name on a single collection. If you do not specify a |
type | string | Optional | Type of search index to create. You can specify either:
If you omit the |
definition | document | Required | Document describing the index to create. The |
Search Index Definition Syntax
The search index definition takes the following fields:
{ analyzer: "<analyzer-for-index>", searchAnalyzer: "<analyzer-for-query>", mappings: { dynamic: <boolean>, fields: { <field-definition> } }, analyzers: [ <custom-analyzer> ], storedSource: <boolean> | { <stored-source-definition> }, synonyms: [ { name: "<synonym-mapping-name>", source: { collection: "<source-collection-name>" }, analyzer: "<synonym-mapping-analyzer>" } ] }
Field | Type | Necessity | Description |
---|---|---|---|
analyzer | string | Optional | Specifies the analyzer to apply to string fields when indexing. If you omit this field, the index uses the standard analyzer. |
searchAnalyzer | string | Optional | Specifies the analyzer to apply to query text before the text is searched. If you omit this field, the index uses the same analyzer specified
in the If you omit both the |
mappings | object | Optional | Specifies how to index fields on different paths for this index. |
mappings.dynamic | boolean | Optional | Enables or disables dynamic field mapping for this index. If set to If set to If omitted, defaults to |
mappings.fields | document | Conditional | Required only if dynamic mapping is disabled. Specifies the fields to index. To learn more, see Define Field Mappings. |
analyzers | array | Optional | Specifies the Custom Analyzers to use in this index. |
storedSource | boolean or Stored Source Definition | Optional | Specifies document fields to store for queries performed using the returnedStoredSource option. You can store fields of all Data Types on Atlas Search.
The
If omitted, defaults to To learn more, see Define Stored Source Fields in Your Atlas Search Index. |
synonyms | array of Synonym Mapping Definitions | Optional | Specifies synonym mappings to use in your index. Configuring synonyms allows you to index and search for words that have the same or a similar meaning. To learn more, see Define Synonym Mappings in Your Atlas Search Index. |
Vector Search Index Definition Syntax
The vector search index definition takes the following fields:
{ "fields": [ { "type": "vector" | "filter", "path": "<field-to-index>", "numDimensions": <number-of-dimensions>, "similarity": "euclidean" | "cosine" | "dotProduct" } ] }
For explanations of vector search index definition fields, see How to Index Fields for Vector Search.
Behavior
createSearchIndex()
triggers an index build. There may be a delay
between when you receive a response from the command and when the index
is ready.
To see the status of your search indexes, use the
$listSearchIndexes
aggregation stage.
Access Control
If your deployment enforces access control, the user running
createSearchIndex()
must have the createSearchIndexes
privilege
action on the database or collection:
{ resource: { db : <database>, collection: <collection> }, actions: [ "createSearchIndexes" ] }
The built-in readWrite
role provides the
createSearchIndexes
privilege. The following example grants
accountUser01
the readWrite
role on the products
database:
db.grantRolesToUser( "accountUser01", [ { role: "readWrite", db: "products" } ] )
Examples
Create a Search Index on All Fields
The following example creates a search index named searchIndex01
on
the movies
collection:
db.movies.createSearchIndex( "searchIndex01", { mappings: { dynamic: true } } )
The index definition specifies mappings: { dynamic: true }
, which
means that the index contains all fields in the collection that have
supported data types.
Create a Search Index with a Language Analyzer
A language analyzer introduces stop-words, which are words that are not significant enough to be indexed.
The following example creates a search index named frenchIndex01
on
the cars
collection, and specifies the lucene.french
analyzer on
the fr
field:
db.cars.createSearchIndex( "frenchIndex01", { mappings: { fields: { subject: { fields: { fr: { analyzer: "lucene.french", type: "string" } }, type: "document" } } } } )
To learn more about language analyzers, see Language Analyzers.
Create a Search Index with the Default Name
The following createSearchIndex()
method only specifies the index
definition and omits the index name. The command creates a search index
with the name default
on the food
collection:
db.food.createSearchIndex( { mappings: { fields: { title: { type: "string" } } } } )
Create a Vector Search Index
The following example creates a vector search index named
vectorSearchIndex01
on the movies
collection:
db.movies.createSearchIndex( "vectorSearchIndex01", "vectorSearch", { fields: [ { type: "vector", numDimensions: 1, path: "genre", similarity: "cosine" } ] } )
The vector search index contains one dimension and indexes the genre
field.
Learn More
$vectorSearch
aggregation stage