distinct
Definition
distinct
Finds the distinct values for a specified field across a single collection.
distinct
returns a document that contains an array of the distinct values. The return document also contains an embedded document with query statistics and the query plan.Tip
In
mongosh
, this command can also be run through thedb.collection.distinct()
helper method.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.
Compatibility
This command is available in deployments hosted in the following environments:
MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud
Important
This command has limited support in M0, M2, and M5 clusters. For more information, see Unsupported Commands.
MongoDB Enterprise: The subscription-based, self-managed version of MongoDB
MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB
Syntax
The command has the following syntax:
db.runCommand( { distinct: "<collection>", key: "<field>", query: <query>, readConcern: <read concern document>, collation: <collation document>, comment: <any>, hint: <string or document> } )
Command Fields
The command takes the following fields:
Field | Type | Description | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
distinct | string | The name of the collection to query for distinct values. | ||||||||||
key | string | The field for which to return distinct values. | ||||||||||
query | document | Optional. A query that specifies the documents from which to retrieve the
distinct values. | ||||||||||
readConcern | document | Optional. Specifies the read concern. The Possible read concern levels are:
For more formation on the read concern levels, see Read Concern Levels. | ||||||||||
collation | document | Optional. Specifies the collation to use for the operation. Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks. The collation option has the following syntax:
When specifying collation, the If the collation is unspecified but the collection has a
default collation (see If no collation is specified for the collection or for the operations, MongoDB uses the simple binary comparison used in prior versions for string comparisons. You cannot specify multiple collations for an operation. For example, you cannot specify different collations per field, or if performing a find with a sort, you cannot use one collation for the find and another for the sort. | ||||||||||
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). | ||||||||||
hint | string or document | Optional. Specify the index name, either as a string or a document. If specified, the query planner only considers plans using the hinted index. For more details, see Specify an Index. New in version 7.1. |
Note
Results must not be larger than the maximum BSON size. If your results exceed the maximum
BSON size, use the aggregation pipeline to retrieve distinct
values using the $group
operator, as described in
Retrieve Distinct Values with the Aggregation Pipeline.
MongoDB also provides the shell wrapper method
db.collection.distinct()
for the distinct
command. Additionally, many MongoDB drivers
provide a wrapper method. Refer to the specific driver documentation.
Behavior
In a sharded cluster, the distinct
command may return
orphaned documents.
For time series collections, the
distinct
command can't make efficient use of indexes. Instead, use a
$group
aggregation to group documents by distinct values. For
details, see Time Series Limitations.
Array Fields
If the value of the specified field
is an array,
distinct
considers each element of the array
as a separate value.
For instance, if a field has as its value [ 1, [1], 1 ]
, then
distinct
considers 1
, [1]
, and 1
as separate values.
Starting in MongoDB 6.0, the distinct
command returns the
same results for collections and views when
using arrays.
For examples, see:
Index Use
When possible, distinct
operations can use indexes.
Indexes can also cover
distinct
operations. See Covered Query for more information
on queries covered by indexes.
Transactions
To perform a distinct operation within a transaction:
For unsharded collections, you can use the
db.collection.distinct()
method/thedistinct
command as well as the aggregation pipeline with the$group
stage.For sharded collections, you cannot use the
db.collection.distinct()
method or thedistinct
command.To find the distinct values for a sharded collection, use the aggregation pipeline with the
$group
stage instead. See Distinct Operation for details.
Important
In most cases, a distributed transaction incurs a greater performance cost over single document writes, and the availability of distributed transactions should not be a replacement for effective schema design. For many scenarios, the denormalized data model (embedded documents and arrays) will continue to be optimal for your data and use cases. That is, for many scenarios, modeling your data appropriately will minimize the need for distributed transactions.
For additional transactions usage considerations (such as runtime limit and oplog size limit), see also Production Considerations.
Client Disconnection
Starting in MongoDB 4.2, if the client that issued distinct
disconnects before the operation completes, MongoDB marks distinct
for termination using killOp
.
Replica Set Member State Restriction
To run on a replica set member, distinct
operations require the member
to be in PRIMARY
or SECONDARY
state. If the member
is in another state, such as STARTUP2
, the
operation errors.
Index Filters and Collations
Starting in MongoDB 6.0, an index filter uses the collation previously set using the planCacheSetFilter
command.
Examples
The examples use the inventory
collection that contains the
following documents:
{ "_id": 1, "dept": "A", "item": { "sku": "111", "color": "red" }, "sizes": [ "S", "M" ] } { "_id": 2, "dept": "A", "item": { "sku": "111", "color": "blue" }, "sizes": [ "M", "L" ] } { "_id": 3, "dept": "B", "item": { "sku": "222", "color": "blue" }, "sizes": "S" } { "_id": 4, "dept": "A", "item": { "sku": "333", "color": "black" }, "sizes": [ "S" ] }
Return Distinct Values for a Field
The following example returns the distinct values for the field
dept
from all documents in the inventory
collection:
db.runCommand ( { distinct: "inventory", key: "dept" } )
The command returns a document with a field named values
that
contains the distinct dept
values:
{ "values" : [ "A", "B" ], "ok" : 1 }
Return Distinct Values for an Embedded Field
The following example returns the distinct values for the field
sku
, embedded in the item
field, from all documents in the
inventory
collection:
db.runCommand ( { distinct: "inventory", key: "item.sku" } )
The command returns a document with a field named values
that
contains the distinct sku
values:
{ "values" : [ "111", "222", "333" ], "ok" : 1 }
Return Distinct Values for an Array Field
The following example returns the distinct values for the field
sizes
from all documents in the inventory
collection:
db.runCommand ( { distinct: "inventory", key: "sizes" } )
The command returns a document with a field named values
that
contains the distinct sizes
values:
{ "values" : [ "M", "S", "L" ], "ok" : 1 }
For information on distinct
and array fields, see the
Behavior section.
Arrays in Collections and Views
Starting in MongoDB 6.0, the distinct
command returns the
same results for collections and views when
using arrays.
The following example creates a collection named sensor
with
an array of temperature values for each document:
db.sensor.insertMany( [ { _id: 0, temperatures: [ { value: 1 }, { value: 4 } ] }, { _id: 1, temperatures: [ { value: 2 }, { value: 8 } ] }, { _id: 2, temperatures: [ { value: 3 }, { value: 12 } ] }, { _id: 3, temperatures: [ { value: 1 }, { value: 4 } ] } ] )
The following example creates a view named sensorView
from the
sensor
collection:
db.createView( "sensorView", "sensor", [] )
The following example uses distinct
to return the unique
values from the temperatures
array in the sensor
collection:
db.sensor.distinct( "temperatures.1.value" )
The 1
in temperatures.1.value
specifies the temperatures
array index.
Example output:
[ 4, 8, 12 ]
Example for sensorView
:
db.sensorView.distinct( "temperatures.1.value" )
Example output:
[ 4, 8, 12 ]
starting in MongoDB 6.0 (identical to result returned from thesensor
collection).[]
in MongoDB versions earlier than 6.0.
Specify Query with distinct
The following example returns the distinct values for the field
sku
, embedded in the item
field, from the documents whose
dept
is equal to "A"
:
db.runCommand ( { distinct: "inventory", key: "item.sku", query: { dept: "A"} } )
The command returns a document with a field named values
that
contains the distinct sku
values:
{ "values" : [ "111", "333" ], "ok" : 1 }
Specify a Collation
Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.
A collection myColl
has the following documents:
{ _id: 1, category: "café", status: "A" } { _id: 2, category: "cafe", status: "a" } { _id: 3, category: "cafE", status: "a" }
The following aggregation operation includes the Collation option:
db.runCommand( { distinct: "myColl", key: "category", collation: { locale: "fr", strength: 1 } } )
For descriptions on the collation fields, see Collation Document.
Override Default Read Concern
To override the default read concern level of "local"
,
use the readConcern
option.
The following operation on a replica set specifies a
Read Concern of "majority"
to read the
most recent copy of the data confirmed as having been written to a
majority of the nodes.
Note
Regardless of the read concern level, the most recent data on a node may not reflect the most recent version of the data in the system.
db.runCommand( { distinct: "restaurants", key: "rating", query: { cuisine: "italian" }, readConcern: { level: "majority" } } )
To ensure that a single thread can read its own writes, use
"majority"
read concern and "majority"
write concern against the primary of the replica set.
Specify an Index
You can specify an index name or pattern using the hint option.
To specify a hint based on an index name:
db.runCommand ( { distinct: "inventory", key: "dept", hint: "sizes" } )
To specify a hint based on an index pattern:
db.runCommand ( { distinct: "inventory", key: "dept", hint: { sizes: 1 } } )