$sort (aggregation)

Limits

You can sort on a maximum of 32 keys.

Sort Consistency

MongoDB does not store documents in a collection in a particular order. When sorting on a field which contains duplicate values, documents containing those values may be returned in any order.

If consistent sort order is desired, include at least one field in your sort that contains unique values. The easiest way to guarantee this is to include the _id field in your sort query.

Consider the following restaurant collection:

db.restaurants.insertMany( [
   { "_id" : 1, "name" : "Central Park Cafe", "borough" : "Manhattan"},
   { "_id" : 2, "name" : "Rock A Feller Bar and Grill", "borough" : "Queens"},
   { "_id" : 3, "name" : "Empire State Pub", "borough" : "Brooklyn"},
   { "_id" : 4, "name" : "Stan's Pizzaria", "borough" : "Manhattan"},
   { "_id" : 5, "name" : "Jane's Deli", "borough" : "Brooklyn"},
] )

The following command uses the $sort stage to sort on the borough field:

db.restaurants.aggregate(
   [
     { $sort : { borough : 1 } }
   ]
)

In this example, sort order may be inconsistent, since the borough field contains duplicate values for both Manhattan and Brooklyn. Documents are returned in alphabetical order by borough, but the order of those documents with duplicate values for borough might not the be the same across multiple executions of the same sort. For example, here are the results from two different executions of the above command:

{ "_id" : 3, "name" : "Empire State Pub", "borough" : "Brooklyn" }
{ "_id" : 5, "name" : "Jane's Deli", "borough" : "Brooklyn" }
{ "_id" : 1, "name" : "Central Park Cafe", "borough" : "Manhattan" }
{ "_id" : 4, "name" : "Stan's Pizzaria", "borough" : "Manhattan" }
{ "_id" : 2, "name" : "Rock A Feller Bar and Grill", "borough" : "Queens" }
{ "_id" : 5, "name" : "Jane's Deli", "borough" : "Brooklyn" }
{ "_id" : 3, "name" : "Empire State Pub", "borough" : "Brooklyn" }
{ "_id" : 4, "name" : "Stan's Pizzaria", "borough" : "Manhattan" }
{ "_id" : 1, "name" : "Central Park Cafe", "borough" : "Manhattan" }
{ "_id" : 2, "name" : "Rock A Feller Bar and Grill", "borough" : "Queens" }

While the values for borough are still sorted in alphabetical order, the order of the documents containing duplicate values for borough (i.e. Manhattan and Brooklyn) is not the same.

To achieve a consistent sort, add a field which contains exclusively unique values to the sort. The following command uses the $sort stage to sort on both the borough field and the _id field:

db.restaurants.aggregate(
   [
     { $sort : { borough : 1, _id: 1 } }
   ]
)

Since the _id field is always guaranteed to contain exclusively unique values, the returned sort order will always be the same across multiple executions of the same sort.

Ascending/Descending Sort

For the field or fields to sort by, set the sort order to 1 or -1 to specify an ascending or descending sort respectively, as in the following example:

db.users.aggregate(
   [
     { $sort : { age : -1, posts: 1 } }
   ]
)

This operation sorts the documents in the users collection, in descending order according by the age field and then in ascending order according to the value in the posts field.

When comparing values of different BSON types, MongoDB uses the following comparison order, from lowest to highest:

1. MinKey (internal type)

2. Null

3. Numbers (ints, longs, doubles, decimals)

4. Symbol, String

5. Object

6. Array

7. BinData

8. ObjectId

9. Boolean

10. Date

11. Timestamp

12. Regular Expression

13. MaxKey (internal type)

For details on the comparison/sort order for specific types, see Comparison/Sort Order.

Text Score Metadata Sort

For a pipeline that includes a $text search, you can sort by descending relevance score using the { $meta: "textScore" } expression. In the { <sort-key> } document, set the { $meta: "textScore" } expression to an arbitrary field name. The field name is ignored by the query system. For example:

db.users.aggregate(
   [
     { $match: { $text: { $search: "operating" } } },
     { $sort: { score: { $meta: "textScore" }, posts: -1 } }
   ]
)

This operation uses the $text operator to match the documents, and then sorts first by the "textScore" metadata in descending order, and then by the posts field in descending order. The score field name in the sort document is ignored by the query system. In this pipeline, the "textScore" metadata is not included in the projection and is not returned as part of the matching documents. See $meta for more information.

$sort + $limit Memory Optimization

When a $sort precedes a $limit and there are no intervening stages that modify the number of documents, the optimizer can coalesce the $limit into the $sort. This allows the $sort operation to only maintain the top n results as it progresses, where n is the specified limit, and ensures that MongoDB only needs to store n items in memory. This optimization still applies when allowDiskUse is true and the n items exceed the aggregation memory limit.

Optimizations are subject to change between releases.

$sort and Memory Restrictions

$sort is subject to the 100 megabyte memory usage limit, but is able to write temporary files to disk if additional space is required.

Starting in MongoDB 6.0, pipeline stages that require more than 100 megabytes of memory to execute write temporary files to disk by default. In earlier verisons of MongoDB, you must pass { allowDiskUse: true } to individual find and aggregate commands to enable this behavior.

Individual find and aggregate commands may override the allowDiskUseByDefault parameter by either:

• Using { allowDiskUse: true } to allow writing temporary files out to disk when allowDiskUseByDefault is set to false

• Using { allowDiskUse: false } to prohibit writing temporary files out to disk when allowDiskUseByDefault is set to true