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createIndexes

On this page

  • Definition
  • Compatibility
  • Syntax
  • Command Fields
  • Considerations
  • Index Names
  • Replica Sets and Sharded Clusters
  • Collation and Index Types
  • Stable API
  • Behavior
  • Concurrency
  • Memory Usage Limit
  • Index Options
  • Wildcard Indexes
  • Transactions
  • Commit Quorum Contrasted with Write Concern
  • Example
  • Create a Wildcard Index
  • Create Index With Commit Quorum
  • Output
createIndexes

Builds one or more indexes on a collection.

Tip

In mongosh, this command can also be run through the db.collection.createIndex() and db.collection.createIndexes() helper methods..

Helper methods are convenient for mongosh users, but they may not return the same level of information as database commands. In cases where the convenience is not needed or the additional return fields are required, use the database command.

This command is available in deployments hosted in the following environments:

  • MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud

Note

This command is supported in all MongoDB Atlas clusters. For information on all commands, see Unsupported Commands.

The createIndexes command takes the following form:

db.runCommand(
{
createIndexes: <collection>,
indexes: [
{
key: {
<key-value_pair>,
<key-value_pair>,
...
},
name: <index_name>,
<option1>,
<option2>,
...
},
{ ... },
{ ... }
],
writeConcern: { <write concern> },
commitQuorum: <int|string>,
comment: <any>
}
)

The createIndexes command takes the following fields:

Field
Type
Description
createIndexes
string
The collection for which to create indexes.
indexes
array
Specifies the indexes to create. Each document in the array specifies a separate index.
writeConcern
document
Optional. A document expressing the write concern. Omit to use the default write concern.
commitQuorum
integer or string

Optional. The minimum number of data-bearing replica set members (i.e. commit quorum), including the primary, that must report a successful index build before the primary marks the indexes as ready.

Starting in MongoDB v5.0, you can resume some interrupted index builds when the commit quorum is set to "votingMembers".

Replica set nodes in a commit quorum must have members[n].buildIndexes set to true. If any voting nodes have members[n].buildIndexes set to false, you can't use the default "votingMembers" commit quorum. Either configure all nodes with members[n].buildIndexes set to true, or select a different commit quorum.

Supports the following values:

  • "votingMembers" - all data-bearing voting replica set members (Default). A "voting" member is any replica set member where members[n].votes is greater than 0.

  • "majority" - a simple majority of data-bearing replica set members.

  • <int> - a specific number of data-bearing replica set members.

  • 0 - Disables quorum-voting behavior. Members start the index build simultaneously but do not vote or wait for quorum before completing the index build. If you start an index build with a commit quorum of 0, you cannot later modify the commit quorum using setIndexCommitQuorum.

  • A replica set tag name.

comment
any

Optional. A user-provided comment to attach to this command. Once set, this comment appears alongside records of this command in the following locations:

A comment can be any valid BSON type (string, integer, object, array, etc).

Each document in the indexes array can take the following fields:

Field
Type
Description
key
document

Specifies the index's fields. For each field, specify a key-value pair in which the key is the name of the field to index and the value is either the index direction or index type. If specifying direction, specify 1 for ascending or -1 for descending.

MongoDB supports several different index types, including:

See index types for more information.

Wildcard indexes support workloads where users query against custom fields or a large variety of fields in a collection:

  • You can create a wildcard index on a specific field and its subpaths or on all of the fields in a document.

    For details see, Wildcard Indexes.

name
string
A name that uniquely identifies the index.
unique
boolean

Optional. Creates a unique index so that the collection will not accept insertion or update of documents where the index key value matches an existing value in the index.

Specify true to create a unique index. The default value is false.

The option is unavailable for hashed indexes.

partialFilterExpression
document

Optional. If specified, the index only references documents that match the filter expression. See Partial Indexes for more information.

A filter expression can include:

If you are using Client-Side Field Level Encryption or Queryable Encryption, a partialFilterExpression cannot reference an encrypted field.

You can specify a partialFilterExpression option for all MongoDB index types.

sparse
boolean

Optional. If true, the index only references documents with the specified field. These indexes use less space but behave differently in some situations (particularly sorts). The default value is false. See Sparse Indexes for more information.

The following index types are sparse by default and ignore this option:

For a compound index that includes 2dsphere index key(s) along with keys of other types, only the 2dsphere index fields determine whether the index references a document.

MongoDB provides the option to create partial indexes. These offer a superset of the functionality of sparse indexes and are preferred instead.

expireAfterSeconds
integer

Optional. Specifies a value, in seconds, as a time to live (TTL) to control how long MongoDB retains documents in this collection. This option only applies to TTL indexes. See Expire Data from Collections by Setting TTL for more information.

If you use TTL indexes created before MongoDB 5.0, or if you want to sync data created in MongDB 5.0 with a pre-5.0 installation, see Indexes Configured Using NaN to avoid misconfiguration issues.

The TTL index expireAfterSeconds value must be within 0 and 2147483647 inclusive.

boolean

Optional. A flag that determines whether the index is hidden from the query planner. A hidden index is not evaluated as part of query plan selection.

Default is false.

storageEngine
document

Optional. Allows users to configure the storage engine on a per-index basis when creating an index.

The storageEngine option should take the following form:

storageEngine: { <storage-engine-name>: <options> }

Storage engine configuration options specified when creating indexes are validated and logged to the oplog during replication to support replica sets with members that use different storage engines.

weights
document
Optional. For text indexes, a document that contains field and weight pairs. The weight is an integer ranging from 1 to 99,999 and denotes the significance of the field relative to the other indexed fields in terms of the score. You can specify weights for some or all the indexed fields. See Assign Weights to Text Search Results on Self-Managed Deployments to adjust the scores. The default value is 1.
default_language
string

Optional. For text indexes, the language that determines the list of stop words and the rules for the stemmer and tokenizer. See Text Search Languages on Self-Managed Deployments for the available languages and Specify the Default Language for a Text Index on Self-Managed Deployments for more information and examples. The default value is english.

language_override
string
Optional. For text indexes, the name of the field, in the collection's documents, that contains the override language for the document. The default value is language. See Specify the Default Language for a Text Index on Self-Managed Deployments for an example.
textIndexVersion
integer

Optional. The text index version number. Users can use this option to override the default version number.

For available versions, see Text Index Versions on Self-Managed Deployments.

2dsphereIndexVersion
integer

Optional. The 2dsphere index version number. Users can use this option to override the default version number.

For the available versions, see 2dsphere Indexes.

bits
integer

Optional. For 2d indexes, the number of precision of the stored geohash value of the location data.

The bits value ranges from 1 to 32 inclusive. The default value is 26.

min
number
Optional. For 2d indexes, the lower inclusive boundary for the longitude and latitude values. The default value is -180.0.
max
number
Optional. For 2d indexes, the upper inclusive boundary for the longitude and latitude values. The default value is 180.0.
collation
document

Optional. Specifies the collation for the index.

Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.

If you have specified a collation at the collection level, then:

  • If you do not specify a collation when creating the index, MongoDB creates the index with the collection's default collation.

  • If you do specify a collation when creating the index, MongoDB creates the index with the specified collation.

The collation option has the following syntax:

collation: {
locale: <string>,
caseLevel: <boolean>,
caseFirst: <string>,
strength: <int>,
numericOrdering: <boolean>,
alternate: <string>,
maxVariable: <string>,
backwards: <boolean>
}

When specifying collation, the locale field is mandatory; all other collation fields are optional. For descriptions of the fields, see Collation Document.

wildcardProjection
document

Optional.

Allows users to include or exclude specific field paths from a wildcard index using the { "$**" : 1} key pattern. This option is only valid if creating a wildcard index on all document fields. You cannot specify this option if creating a wildcard index on a specific field path and its subfields, e.g. { "path.to.field.$**" : 1 }

The wildcardProjection option takes the following form:

wildcardProjection: {
"path.to.field.a" : <value>,
"path.to.field.b" : <value>
}

The <value> can be either of the following:

  • 1 or true to include the field in the wildcard index.

  • 0 or false to exclude the field from the wildcard index.

Wildcard indexes omit the _id field by default. To include the _id field in the wildcard index, you must explicitly include it in the wildcardProjection document:

{
"wildcardProjection" : {
"_id" : 1,
"<field>" : 0|1
}
}

All of the statements in the wildcardProjection document must be either inclusion or exclusion statements. You can also include the _id field with exclusion statements. This is the only exception to the rule.

mongosh provides the methods db.collection.createIndex() and db.collection.createIndexes() as wrappers for the createIndexes command.

MongoDB disallows the creation of version 0 indexes.

The createIndexes command and mongosh helpers db.collection.createIndex() and db.collection.createIndexes() report an error if you create an index with one name, and then try to create the same index again but with another name.

{
"ok" : 0,
"errmsg" : "Index with name: x_1 already exists with a different name",
"code" : 85,
"codeName" : "IndexOptionsConflict"
}

In previous versions, MongoDB did not create the index again, but would return a response object with ok value of 1 and a note that implied that the index was not recreated. For example:

{
"numIndexesBefore" : 2,
"numIndexesAfter" : 2,
"note" : "all indexes already exist",
"ok" : 1
}

Note

Requires featureCompatibilityVersion 4.4+

Each mongod in the replica set or sharded cluster must have featureCompatibilityVersion set to at least 4.4 to start index builds simultaneously across replica set members.

Index builds on a replica set or sharded cluster build simultaneously across all data-bearing replica set members. For sharded clusters, the index build occurs only on shards containing data for the collection being indexed. The primary requires a minimum number of data-bearing voting members (i.e commit quorum), including itself, that must complete the build before marking the index as ready for use. See Index Builds in Replicated Environments for more information.

To start an index build with a non-default commit quorum, specify the commitQuorum.

Use the setIndexCommitQuorum command to modify the commit quorum of an in-progress index build.

To minimize the impact of building an index on replica sets and sharded clusters, use a rolling index build procedure as described on Rolling Index Builds on Replica Sets.

The following indexes only support simple binary comparison and do not support collation:

Tip

To create a text or 2d index on a collection that has a non-simple collation, you must explicitly specify {collation: {locale: "simple"} } when creating the index.

When using Stable API V1:

  • You cannot specify any of the following fields in the indexes array:

    • background

    • bucketSize

    • sparse

    • storageEngine

  • You cannot create geoHaystack or text indexes.

  • The above unsupported index types are ignored by the query planner in strict mode. For example, attempting to use a sparse index with cursor.hint() will result in the following BadValue error:

    planner returned error :: caused by :: hint provided does not
    correspond to an existing index

For featureCompatibilityVersion "4.2", createIndexes uses an optimized build process that obtains and holds an exclusive lock on the specified collection at the start and end of the index build. All subsequent operations on the collection must wait until createIndexes releases the exclusive lock. createIndexes allows interleaving read and write operations during the majority of the index build.

For featureCompatibilityVersion "4.0", createIndexes uses the pre-4.2 index build process which by default obtains an exclusive lock on the parent database for the entire duration of the build process. The pre-4.2 build process blocks all operations on the database and all its collections until the operation completed. background indexes do not take an exclusive lock.

For more information on the locking behavior of createIndexes, see Index Builds on Populated Collections.

Important

If a data-bearing voting node becomes unreachable and the commitQuorum is set to the default votingMembers, index builds can hang until that node comes back online.

createIndexes supports building one or more indexes on a collection. createIndexes uses a combination of memory and temporary files on disk to complete index builds. The default limit on memory usage for createIndexes is 200 megabytes, shared between all indexes built using a single createIndexes command. Once the memory limit is reached, createIndexes uses temporary disk files in a subdirectory named _tmp within the --dbpath directory to complete the build.

You can override the memory limit by setting the maxIndexBuildMemoryUsageMegabytes server parameter. Setting a higher memory limit may result in faster completion of index builds. However, setting this limit too high relative to the unused RAM on your system can result in memory exhaustion and server shutdown.

The hidden option can be changed without dropping and recreating the index. See Hidden Option.

Collation options on an existing index can be updated. To change other index options, drop the existing index with db.collection.dropIndex() then run createIndexes with the new options.

You can create multiple indexes on the same key(s) with different collations. To create indexes with the same key pattern but different collations, you must supply unique index names.

If you have specified a collation at the collection level, then:

  • If you do not specify a collation when creating the index, MongoDB creates the index with the collection's default collation.

  • If you do specify a collation when creating the index, MongoDB creates the index with the specified collation.

Tip

By specifying a collation strength of 1 or 2, you can create a case-insensitive index. Index with a collation strength of 1 is both diacritic- and case-insensitive.

To use an index for string comparisons, an operation must also specify the same collation. That is, an index with a collation cannot support an operation that performs string comparisons on the indexed fields if the operation specifies a different collation.

Warning

Because indexes that are configured with collation use ICU collation keys to achieve sort order, collation-aware index keys may be larger than index keys for indexes without collation.

For example, the collection myColl has an index on a string field category with the collation locale "fr".

db.myColl.createIndex( { category: 1 }, { collation: { locale: "fr" } } )

The following query operation, which specifies the same collation as the index, can use the index:

db.myColl.find( { category: "cafe" } ).collation( { locale: "fr" } )

However, the following query operation, which by default uses the "simple" binary collator, cannot use the index:

db.myColl.find( { category: "cafe" } )

For a compound index where the index prefix keys are not strings, arrays, and embedded documents, an operation that specifies a different collation can still use the index to support comparisons on the index prefix keys.

For example, the collection myColl has a compound index on the numeric fields score and price and the string field category; the index is created with the collation locale "fr" for string comparisons:

db.myColl.createIndex(
{ score: 1, price: 1, category: 1 },
{ collation: { locale: "fr" } } )

The following operations, which use "simple" binary collation for string comparisons, can use the index:

db.myColl.find( { score: 5 } ).sort( { price: 1 } )
db.myColl.find( { score: 5, price: { $gt: NumberDecimal( "10" ) } } ).sort( { price: 1 } )

The following operation, which uses "simple" binary collation for string comparisons on the indexed category field, can use the index to fulfill only the score: 5 portion of the query:

db.myColl.find( { score: 5, category: "cafe" } )

Important

Matches against document keys, including embedded document keys, use simple binary comparison. This means that a query for a key like "foo.bár" will not match the key "foo.bar", regardless of the value you set for the strength parameter.

To change the hidden option for existing indexes, you can use the following mongosh methods:

For example,

  • To change the hidden option for an index to true, use the db.collection.hideIndex() method:

    db.restaurants.hideIndex( { borough: 1, ratings: 1 } );
  • To change the hidden option for an index to false, use the db.collection.unhideIndex() method:

    db.restaurants.unhideIndex( { borough: 1, city: 1 } );

Tip

See also:

  • Wildcard indexes omit the _id field by default. To include the _id field in the wildcard index, you must explicitly include it in the wildcardProjection document:

    {
    "wildcardProjection" : {
    "_id" : 1,
    "<field>" : 0|1
    }
    }

    All of the statements in the wildcardProjection document must be either inclusion or exclusion statements. You can also include the _id field with exclusion statements. This is the only exception to the rule.

  • Wildcard indexes do not support:

    Wildcard indexes are sparse indexes. They do not support queries when an indexed field does not exist. A wildcard index will index the document if the wildcard field has a null value.

    Starting in MongoDB 7.0, wildcard indexes support ascending (1) and descending (-1) sort order. Earlier versions only supported ascending order.

To learn more, see:

You can create collections and indexes inside a distributed transaction if the transaction is not a cross-shard write transaction.

To use createIndexes in a transaction, the transaction must use read concern "local". If you specify a read concern level other than "local", the transaction fails.

There are important differences between commit quorums and write concerns:

  • Index builds use commit quorums.

  • Write operations use write concerns.

Each data-bearing node in a cluster is a voting member.

The commit quorum specifies how many data-bearing voting members, or which voting members, including the primary, must be prepared to commit a simultaneous index build before the primary will execute the commit.

The write concern is the level of acknowledgment that the write has propagated to the specified number of instances.

The commit quorum specifies how many nodes must be ready to finish the index build before the primary commits the index build. In contrast, when the primary has committed the index build, the write concern specifies how many nodes must finish the index build before the command returns.

The following command builds two indexes on the inventory collection of the products database:

db.getSiblingDB("products").runCommand(
{
createIndexes: "inventory",
indexes: [
{
key: {
item: 1,
manufacturer: 1,
model: 1
},
name: "item_manufacturer_model",
unique: true
},
{
key: {
item: 1,
supplier: 1,
model: 1
},
name: "item_supplier_model",
unique: true
}
],
writeConcern: { w: "majority" }
}
)

When the indexes successfully finish building, MongoDB returns a results document that includes a status of "ok" : 1.

Note

For complete documentation on Wildcard Indexes, see Wildcard Indexes.

The following lists examples of wildcard index creation:

Consider a collection products_catalog where documents may contain a product_attributes field. The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:

db.products_catalog.insertMany( [
{
_id : ObjectId("5c1d358bf383fbee028aea0b"),
product_name: "Blaster Gauntlet",
product_attributes: {
price: {
cost: 299.99,
currency: "USD"
}
}
},
{
_id: ObjectId("5c1d358bf383fbee028aea0c"),
product_name: "Super Suit",
product_attributes: {
superFlight: true,
resistance: [ "Bludgeoning", "Piercing", "Slashing" ]
}
}
] )

The following operation creates a wildcard index on the product_attributes field:

use inventory
db.runCommand(
{
createIndexes: "products_catalog",
indexes: [
{
key: { "product_attributes.$**" : 1 },
name: "wildcardIndex"
}
]
}
)

With this wildcard index, MongoDB indexes all scalar values of product_attributes. If the field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.

The wildcard index can support arbitrary single-field queries on product_attributes or one of its nested fields:

db.products_catalog.find( { "product_attributes.superFlight" : true } )
db.products_catalog.find( { "product_attributes.maxSpeed" : { $gt : 20 } } )
db.products_catalog.find( { "product_attributes.elements" : { $eq: "water" } } )

Note

The path-specific wildcard index syntax is incompatible with the wildcardProjection option. See the parameter documentation for more information.

Consider a collection products_catalog where documents may contain a product_attributes field. The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:

db.products_catalog.insertMany( [
{
_id : ObjectId("5c1d358bf383fbee028aea0b"),
product_name: "Blaster Gauntlet",
product_attributes: {
price: {
cost: 299.99,
currency: "USD"
}
}
},
{
_id: ObjectId("5c1d358bf383fbee028aea0c"),
product_name: "Super Suit",
product_attributes: {
superFlight: true,
resistance: [ "Bludgeoning", "Piercing", "Slashing" ]
}
}
] )

The following operation creates a wildcard index on all scalar fields (excluding the _id field):

use inventory
db.runCommand(
{
createIndexes: "products_catalog",
indexes: [
{
key: { "$**" : 1 },
name: "wildcardIndex"
}
]
}
)

With this wildcard index, MongoDB indexes all scalar fields for each document in the collection. If a given field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.

The created index can support queries on any arbitrary field within documents in the collection:

db.products_catalog.find( { "product_price" : { $lt : 25 } } )
db.products_catalog.find( { "product_attributes.elements" : { $eq: "water" } } )

Note

Wildcard indexes omit the _id field by default. To include the _id field in the wildcard index, you must explicitly include it in the wildcardProjection document. See parameter documentation for more information.

Consider a collection products_catalog where documents may contain a product_attributes field. The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:

db.products_catalog.insertMany( [
{
_id : ObjectId("5c1d358bf383fbee028aea0b"),
product_name: "Blaster Gauntlet",
product_attributes: {
price: {
cost: 299.99,
currency: "USD"
}
}
},
{
_id: ObjectId("5c1d358bf383fbee028aea0c"),
product_name: "Super Suit",
product_attributes: {
superFlight: true,
resistance: [ "Bludgeoning", "Piercing", "Slashing" ]
}
}
] )

The following operation creates a wildcard index and uses the wildcardProjection option to include only scalar values of the product_attributes.elements and product_attributes.resistance fields in the index.

use inventory
db.runCommand(
{
createIndexes: "products_catalog",
indexes: [
{
key: { "$**" : 1 },
"wildcardProjection" : {
"product_attributes.elements" : 1,
"product_attributes.resistance" : 1
},
name: "wildcardIndex"
}
]
}
)

While the key pattern "$**" covers all fields in the document, the wildcardProjection field limits the index to only the included fields and their nested fields.

If a field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.

The created index can support queries on any scalar field included in the wildcardProjection:

db.products_catalog.find( { "product_attributes.elements" : { $eq: "Water" } } )
db.products_catalog.find( { "product_attributes.resistance" : "Bludgeoning" } )

Note

Wildcard indexes do not support mixing inclusion and exclusion statements in the wildcardProjection document except when explicitly including the _id field. For more information on wildcardProjection, see the parameter documentation.

Consider a collection products_catalog where documents may contain a product_attributes field. The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:

db.products_catalog.insertMany( [
{
_id : ObjectId("5c1d358bf383fbee028aea0b"),
product_name: "Blaster Gauntlet",
product_attributes: {
price: {
cost: 299.99,
currency: "USD"
}
}
},
{
_id: ObjectId("5c1d358bf383fbee028aea0c"),
product_name: "Super Suit",
product_attributes: {
superFlight: true,
resistance: [ "Bludgeoning", "Piercing", "Slashing" ]
}
}
] )

The following operation creates a wildcard index and uses the wildcardProjection document to index all scalar fields for each document in the collection, excluding the product_attributes.elements and product_attributes.resistance fields:

use inventory
db.runCommand(
{
createIndexes: "products_catalog",
indexes: [
{
key: { "$**" : 1 },
"wildcardProjection" : {
"product_attributes.elements" : 0,
"product_attributes.resistance" : 0
},
name: "wildcardIndex"
}
]
}
)

While the key pattern "$**" covers all fields in the document, the wildcardProjection field excludes the specified fields from the index.

If a field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.

The created index can support queries on any scalar field except those excluded by wildcardProjection:

db.products_catalog.find( { "product_attributes.maxSpeed" : { $gt: 25 } } )
db.products_catalog.find( { "product_attributes.superStrength" : true } )

Note

Wildcard indexes do not support mixing inclusion and exclusion statements in the wildcardProjection document except when explicitly including the _id field. For more information on wildcardProjection, see the parameter documentation.

Note

Requires featureCompatibilityVersion 4.4+

Each mongod in the replica set or sharded cluster must have featureCompatibilityVersion set to at least 4.4 to start index builds simultaneously across replica set members.

Index builds on a replica set or sharded cluster build simultaneously across all data-bearing replica set members. For sharded clusters, the index build occurs only on shards containing data for the collection being indexed. The primary requires a minimum number of data-bearing voting members (i.e commit quorum), including itself, that must complete the build before marking the index as ready for use. See Index Builds in Replicated Environments for more information.

To set the commit quorum, use createIndexes to specify the commitQuorum value.

commitQuorum specifies how many data-bearing voting members, or which voting members, including the primary, must be prepared to commit the index build before the primary will execute the commit. The default commit quorum is votingMembers, which means all data-bearing members.

The following operation creates an index with a commit quorum of "majority", or a simple majority of data-bearing members:

db.getSiblingDB("examples").runCommand(
{
createIndexes: "invoices",
indexes: [
{
key: { "invoices" : 1 },
"name" : "invoiceIndex"
}
],
"commitQuorum" : "majority"
}
)

The primary marks index build as ready only after a simple majority of data-bearing voting members "vote" to commit the index build. For more information on index builds and the voting process, see Index Builds in Replicated Environments.

The createIndexes command returns a document that indicates the success of the operation. The document contains some but not all of the following fields, depending on outcome:

createIndexes.createdCollectionAutomatically

If true, then the collection didn't exist and was created in the process of creating the index.

createIndexes.numIndexesBefore

The number of indexes at the start of the command.

createIndexes.numIndexesAfter

The number of indexes at the end of the command.

createIndexes.ok

A value of 1 indicates the indexes are in place. A value of 0 indicates an error.

createIndexes.note

This note is returned if an existing index or indexes already exist. This indicates that the index was not created or changed.

createIndexes.errmsg

Returns information about any errors.

createIndexes.code

The error code representing the type of error.

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