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cursor.sort()

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  • Definition
  • Compatibility
  • Syntax
  • Behavior
  • Examples
  • Return in Natural Order
cursor.sort(sort)

Important

mongosh Method

This page documents a mongosh method. This is not the documentation for a language-specific driver, such as Node.js.

For MongoDB API drivers, refer to the language-specific MongoDB driver documentation.

Specifies the order in which the query returns matching documents. You must apply sort() to the cursor before retrieving any documents from the database.

You can use cursor.sort(sort) for deployments hosted in the following environments:

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

  • MongoDB Enterprise: The subscription-based, self-managed version of MongoDB

  • MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB

The sort() method has the following parameter:

Parameter
Type
Description
sort
document
A document that defines the sort order of the result set.

The sort parameter contains field and value pairs, in the following form:

{ field: value }

The sort document can specify ascending or descending sort on existing fields or sort on text score metadata.

You can sort on a maximum of 32 keys.

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() method to sort on the borough field:

db.restaurants.find().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 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() method to sort on both the borough field and the _id field:

db.restaurants.find().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.

Specify in the sort parameter the field or fields to sort by and a value of 1 or -1 to specify an ascending or descending sort respectively.

The following operation sorts the documents first by the age field in descending order and then by the posts field in ascending order:

db.users.find({ }).sort( { age : -1, posts: 1 } )

When comparing values of different BSON types in sort operations, 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.

Note

$text provides text query capabilities for self-managed (non-Atlas) deployments. For data hosted on MongoDB Atlas, MongoDB offers an improved full-text query solution, Atlas Search.

If you use $text, you can sort by descending relevance score using the { $meta: "textScore" } expression.

The following sample document specifies a descending sort by the "textScore" metadata:

db.users.find(
{ $text: { $search: "operating" } },
{ score: { $meta: "textScore" }}
).sort({ score: { $meta: "textScore" } })

The "textScore" metadata sorts in descending order.

For more information, see $meta for details.

When MongoDB sorts documents by an array-value field, the sort key depends on whether the sort is ascending or descending:

  • In an ascending sort, the sort key is the lowest value in the array.

  • In a descending sort, the sort key is the highest value in the array.

The query filter does not affect sort key selection.

For example, create a shoes collection with these documents:

db.shoes.insertMany( [
{ _id: 'A', sizes: [ 7, 11 ] },
{ _id: 'B', sizes: [ 8, 9, 10 ] }
] )

The following queries sort the documents by the sizes field in ascending and descending order:

// Ascending sort
db.shoes.find().sort( { sizes: 1 } )
// Descending sort
db.shoes.find().sort( { sizes: -1 } )

Both of the preceding queries return the document with _id: 'A' first because sizes 7 and 11 are the lowest and highest in the entries in the sizes array, respectively.

The following query finds shoes with sizes greater than 10 and sorts the results by shoe size in ascending order:

db.shoes.find( { sizes: { $gte: 7 } } ).sort( { sizes: 1 } )

This query returns document with _id: 'A' first even though the filter includes a condition on sizes greater than 7 because the query filter does not affect sort key selection.

MongoDB can obtain the results of a sort operation from an index which includes the sort fields. MongoDB may use multiple indexes to support a sort operation if the sort uses the same indexes as the query predicate.

If MongoDB cannot use an index or indexes to obtain the sort order, MongoDB must perform a blocking sort operation on the data. A blocking sort indicates that MongoDB must consume and process all input documents to the sort before returning results. Blocking sorts do not block concurrent operations on the collection or database.

Sort operations that use an index often have better performance than blocking sorts. For more information on creating indexes to support sort operations, see Use Indexes to Sort Query Results.

If MongoDB requires using more than 100 megabytes of system memory for the blocking sort operation, MongoDB returns an error unless the query specifies cursor.allowDiskUse(). allowDiskUse() allows MongoDB to use temporary files on disk to store data exceeding the 100 megabyte system memory limit while processing a blocking sort operation.

To check if MongoDB must perform a blocking sort, append cursor.explain() to the query and check the explain results. If the query plan contains a SORT stage, then MongoDB must perform a blocking sort operation subject to the 100 megabyte memory limit.

To prevent blocking sorts from consuming too much memory:

Tip

See also:

You can use sort() in conjunction with limit() to return the first (in terms of the sort order) k documents, where k is the specified limit.

If MongoDB cannot obtain the sort order via an index scan, then MongoDB uses a top-k sort algorithm. This algorithm buffers the first k results (or last, depending on the sort order) seen so far by the underlying index or collection access. If at any point the memory footprint of these k results exceeds 100 megabytes, the query will fail unless the query specifies cursor.allowDiskUse().

When a set of results are both sorted and projected, the MongoDB query engine will always apply the sorting first.

A collection orders contain the following documents:

{ _id: 1, item: { category: "cake", type: "chiffon" }, amount: 10 }
{ _id: 2, item: { category: "cookies", type: "chocolate chip" }, amount: 50 }
{ _id: 3, item: { category: "cookies", type: "chocolate chip" }, amount: 15 }
{ _id: 4, item: { category: "cake", type: "lemon" }, amount: 30 }
{ _id: 5, item: { category: "cake", type: "carrot" }, amount: 20 }
{ _id: 6, item: { category: "brownies", type: "blondie" }, amount: 10 }

The following query, which returns all documents from the orders collection, does not specify a sort order:

db.orders.find()

The query returns the documents in indeterminate order:

{ "_id" : 1, "item" : { "category" : "cake", "type" : "chiffon" }, "amount" : 10 }
{ "_id" : 2, "item" : { "category" : "cookies", "type" : "chocolate chip" }, "amount" : 50 }
{ "_id" : 3, "item" : { "category" : "cookies", "type" : "chocolate chip" }, "amount" : 15 }
{ "_id" : 4, "item" : { "category" : "cake", "type" : "lemon" }, "amount" : 30 }
{ "_id" : 5, "item" : { "category" : "cake", "type" : "carrot" }, "amount" : 20 }
{ "_id" : 6, "item" : { "category" : "brownies", "type" : "blondie" }, "amount" : 10 }

The following query specifies a sort on the amount field in descending order.

db.orders.find().sort( { amount: -1 } )

The query returns the following documents, in descending order of amount:

{ "_id" : 2, "item" : { "category" : "cookies", "type" : "chocolate chip" }, "amount" : 50 }
{ "_id" : 4, "item" : { "category" : "cake", "type" : "lemon" }, "amount" : 30 }
{ "_id" : 5, "item" : { "category" : "cake", "type" : "carrot" }, "amount" : 20 }
{ "_id" : 3, "item" : { "category" : "cookies", "type" : "chocolate chip" }, "amount" : 15 }
{ "_id" : 1, "item" : { "category" : "cake", "type" : "chiffon" }, "amount" : 10 }
{ "_id" : 6, "item" : { "category" : "brownies", "type" : "blondie" }, "amount" : 10 }

The following query specifies the sort order using the fields from an embedded document item. The query sorts first by the category field in ascending order, and then within each category, by the type field in ascending order.

db.orders.find().sort( { "item.category": 1, "item.type": 1 } )

The query returns the following documents, ordered first by the category field, and within each category, by the type field:

{ "_id" : 6, "item" : { "category" : "brownies", "type" : "blondie" }, "amount" : 10 }
{ "_id" : 5, "item" : { "category" : "cake", "type" : "carrot" }, "amount" : 20 }
{ "_id" : 1, "item" : { "category" : "cake", "type" : "chiffon" }, "amount" : 10 }
{ "_id" : 4, "item" : { "category" : "cake", "type" : "lemon" }, "amount" : 30 }
{ "_id" : 2, "item" : { "category" : "cookies", "type" : "chocolate chip" }, "amount" : 50 }
{ "_id" : 3, "item" : { "category" : "cookies", "type" : "chocolate chip" }, "amount" : 15 }

The $natural parameter returns items according to their natural order within the database. This ordering is an internal implementation feature, and you should not rely on any particular ordering of the documents.

Queries that include a sort by $natural order do not use indexes to fulfill the query predicate with the following exception: If the query predicate is an equality condition on the _id field { _id: <value> }, then the query with the sort by $natural order can use the _id index.

Tip

See also:

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