createSearchIndexes
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Definition
Creates one or more Atlas Search indexes on a specified collection.
The mongosh method db.collection.createSearchIndex() provides a wrapper around the createSearchIndexes database command.
This command can only be run on a deployment hosted on MongoDB Atlas, and requires an Atlas cluster tier of at least M10.
Syntax
Command syntax:
db.runCommand(
{
createSearchIndexes: "<collection name>",
indexes: [
{
name: "<index name>",
definition: {
/* search index definition fields */
}
},
...
]
}
)
Command Fields
The createSearchIndexes command takes the following fields:
| Field | Type | Necessity | Description |
|---|---|---|---|
createSearchIndexes | string | Required | Name of the collection on which to create the search index. |
indexes | array | Required | Array of documents describing the indexes to create. |
indexes.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 name, the index is named default.
|
indexes.definition | document | Required | Document describing the index to create. For details on definition syntax, see Search Index Definition Syntax. |
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 analyzer field.If you omit both the searchAnalyzer and the analyzer fields, the index uses the standard analyzer.
|
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 true, the index contains all fields containing supported data types.If set to false, you must specify individual fields to index using mappings.fields.If omitted, defaults to false.
|
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 storedSource value can be one of these:
false.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 you 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. |
Behavior
The createSearchIndexes command 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 the createSearchIndexes command 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" } ]
)
Output
The createSearchIndexes command output resembles the following:
{
ok: 1,
indexesCreated: [
{
id: "<index Id>",
name: "<index name>"
}
]
}
The response field ok: 1 indicates that the command was successful. However, there may be a delay between when you receive the response and when the created indexes are ready for use.
To see the status of your search indexes, use the $listSearchIndexes aggregation stage.
Examples
Create a Search Index on All Fields
The following example creates a search index named searchIndex01 on the contacts collection:
db.runCommand( {
createSearchIndexes: "contacts",
indexes: [
{
name: "searchIndex01",
definition: { 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.runCommand( {
createSearchIndexes: "cars",
indexes: [
{
name: "frenchIndex01",
definition: {
mappings: {
fields: {
subject: {
fields: {
fr: {
analyzer: "lucene.french",
type: "string"
}
},
type: "document"
}
}
}
}
}
]
} )
To learn more about language analyzers, see Language Analyzers.
Create Multiple Search Indexes
The following command creates two search indexes on the products collection, searchIndex02 and searchIndex03:
db.runCommand( {
createSearchIndexes: "products",
indexes: [
{
name: "searchIndex02",
definition: {
mappings: {
fields: {
title: {
type: "string",
analyzer: "lucene.simple"
}
}
}
}
},
{
name: "searchIndex03",
definition:
{
mappings: { dynamic: true }
}
}
]
} )
searchIndex02 uses a simple analyzer on the title field. The simple analyzer divides text into searchable terms based on non-letter characters, such as whitespace, punctuation, or digits.
searchIndex03 uses a dynamic field mapping, meaning the index contains all fields in the collection that have supported data types.