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Sort Atlas Search Results

On this page

  • Overview
  • Usage
  • Behavior
  • Considerations
  • Limitations
  • Compatibility
  • Syntax
  • Examples
  • Index Definition
  • Date Search and Sort
  • Number Search and Sort
  • String Search and Sort
  • Sort by ObjectId
  • Sort by UUID
  • Sort by Null Value
  • Sort by Boolean
  • Compound Search and Sort
  • Facet Search and Sort
  • Sort by Score

Atlas Search allows you to sort the results in ascending or descending order on fields that you define in your Atlas Search index. You can sort by the following field types using the sort option:

  • boolean

  • date

  • number (integer, float, and double values)

  • objectId

  • uuid

  • string (indexed as the token type)

You can also sort by the score of the documents in the results and by null values.

To sort your Atlas Search results, you must do the following:

  1. Create an Atlas Search index on the fields to sort the results by.

    To sort on boolean, date, number, UUID, and objectId fields, use dynamic or static mappings. To sort on string fields, you must use static mappings to index the field as the token type.

  2. Create and run your query with the sort option against the fields you defined in the index for sorting. To learn more, see Syntax.

The sort option takes a document that specifies the fields to sort by and the respective sort order. Atlas Search follows the MongoDB comparison order for the supported data types. It treats UUID values like BinData. To learn more, see non-existent fields.

You can specify the following sort order to sort your results by:

1

Sort in ascending order.

When you sort in ascending order, Atlas Search returns documents with missing values before documents with values.

-1
Sort in descending order.

You can also sort by score in ascending or descending order. The sort option takes a document that specifies the $meta expression, which requires the searchScore value.

Example

Suppose your application allows users to skip to the last page of the search results. The following example sorts the results by score in ascending order so that the document with the lowest score displays at the top of the results:

sort: {score: {$meta: "searchScore", order: 1}}

You can use sort to also ensure that the results have a determined order when multiple documents in the results have identical scores. For example, if you sort the results by a unique field, such as a date field named lastUpdated as shown in the following example, Atlas Search returns results with identical scores in a determined order:

Example

sort: {score: {$meta: "searchScore"}, lastUpdated: 1}

However, if you don't specify a unique field to sort the results by, Atlas Search returns the results sorted by score in descending order. Atlas Search returns results with identical scores or values in an arbitrary order. The following example doesn't sort the results by a unique field.

Example

sort: {score: {$meta: "searchScore"}}

To learn more, see Score the Documents in the Results.

Atlas Search flattens the arrays for sorting.

Example

Consider the following array:

[4, [1, [8,5], 9], 2]

Atlas Search flattens the preceding array similar to the following:

4, 1, 8, 5, 9, 2

For an ascending sort, Atlas Search uses 1 to compare the array to other values. For a descending sort, Atlas Search uses 9 to compare the array to other values.

When comparing with elements inside an array:

  • For an ascending sort, Atlas Search compares the smallest elements of the array or performs a less than (<) comparison.

    Example

    Atlas Search sorts results in the following order if you sort by numbers in ascending order:

    -20
    [-3, 12] // <- -3 comes before 5.
    5
    [6, 18] // <- 6 comes after 5.
    13
    14
  • For a descending sort, Atlas Search compares the largest elements of the array or performs a greater than (>) comparison.

    Example

    Atlas Search sorts results in the following order if you sort by numbers in descending order:

    [6, 18] // <- 18 comes before 14.
    14
    13
    [-3, 12] // <- 12 comes after 13.
    5
    -20

Atlas Search treats null as equivalent to missing fields and therefore, if you sort by fields that contain null values or is missing in some documents, the ordering of the documents in the results is non-deterministic. When comparing values of different BSON types in sort operations, Atlas Search follows the MongoDB comparison and sort order and considers null values lower than all other supported BSON types.

To sort the parent documents by an embedded document field, you must do the following:

  • Index the parents of the embedded document child field as the document type.

  • Index the child field with string values within the embedded document as the token type. For child fields with number and date values, enable dynamic mapping to index those fields automatically.

Atlas Search sorts on parent documents only. It doesn't sort the child fields within an array of documents. For an example, see Sort Example.

Atlas Search indexes are eventually consistent, and values returned in results might be different from values used in sorting.

This feature optimizes queries that use $search with $limit as a subsequent stage. If Atlas Search needs to sort all documents in the collection, the response might be slow.

Atlas Search returns scores for all documents in the results. However, you might see higher scoring documents after lower scoring documents because the order of documents in the results is based on the sort criteria unless you explicitly sort by score.

Atlas supports non-sharded sort queries across all major and minor MongoDB 5.0 and later versions. Sharded sort queries are available on all major releases for 6.0 and on all major and minor releases for 7.0 and later versions. If you use sort on sharded Atlas clusters running MongoDB v5.0 and earlier, Atlas Search returns an error.

sort has the following syntax:

1{
2 "$search": {
3 "index": "<index name>", // optional, defaults to "default"
4 "<operator>": { // such as "text", "compound", or "phrase"
5 <operator-specification>
6 },
7 "sort": {
8 score: {$meta: "searchScore"},
9 "<field-to-sort>": <sort-order>,
10 ...
11 }
12 }
13}

The following examples use the sample_mflix.movies, sample_airbnb.listingsAndReview, or a custom collection named users.

The example queries in this page use either the sample_mflix.movies, the sample_airbnb.listingsAndReview, or a custom collection. If you create the following indexes on these collections, you can run the sample queries against the indexed fields.

The index definition for the movies collection specifies the following:

  • Index awards.wins field as:

    • number type for sorting and querying

    • numberFacet type for running facet queries

  • Index released field as:

    • date type for sorting and querying

    • dateFacet type for running facet queries

  • Index title field as:

    • token type for sorting

    • string type for querying

1{
2 "mappings": {
3 "dynamic": true,
4 "fields": {
5 "awards": {
6 "dynamic": false,
7 "fields": {
8 "wins": [
9 {
10 "type": "number"
11 },
12 {
13 "type": "numberFacet"
14 }
15 ]
16 },
17 "type": "document"
18 },
19 "released": [
20 {
21 "type": "date"
22 },
23 {
24 "type": "dateFacet"
25 }
26 ],
27 "title": [{
28 "type": "token"
29 }, {
30 "type": "string"
31 }]
32 }
33 }
34}

For the preceding index definition, Atlas Search creates an index named default with static mappings on the specified fields.

The example queries against the sample_airbnb.listingsAndReviews collection use the following index. The index definition specifies dynamic mappings on the fields in the collection:

{
"mappings": {
"dynamic": true
}
}

The users collection contains the following documents:

db.users.insertMany([
{
"_id": 0,
"a": UUID("1a324de2-e34b-c87e-f2a1-42ce37ad74ed"),
"b": "hello",
"c": ObjectId("507f1f77bcf86cd799439011")
},
{
"_id": 1,
"a": UUID("3b241101-e2bb-4255-8caf-4136c566a962"),
"b": "hello",
"c": true
},
{
"_id": 2,
"a": UUID("dee11d4e-63c6-4d90-983c-5c9f1e79e96c"),
"b": "hello",
"c": "foo"
},
{
"_id": 3,
"b": "hello",
"c": UUID("3be11d4e-62cb-4e95-9a3c-5c9f1e56c732")
},
{
"_id": 4,
"a": UUID("d3c12e1c-c36e-25ed-7c3e-1e7f1e53c752"),
"b": "hello",
"c": null
}
])

The index definition for the users collection specifies the following:

  • Dynamically index all the fields except fields named c.

  • Statically index field named c as the following types for sorting:

    • token

    • uuid

    • objectId

    • boolean

1{
2 "mappings": {
3 "dynamic": true,
4 "fields": {
5 "c": [
6 { "type": "token" },
7 { "type": "uuid" },
8 { "type": "objectId" },
9 { "type": "boolean" }
10 ]
11 }
12 }
13}

For the preceding collection, Atlas Search creates an index named default with the specified mappings on the specified fields.

The following query on the sample_mflix.movies namespace uses the $search stage to do the following:

  • Search for movies released between 01 January, 2010 and 01, January, 2015 using the range operator.

  • Sort the results in descending order of released date using the sort option.

The query uses the $limit stage to limit the output to 5 documents. It also uses the $project stage to omit all fields except title and released in the results.

db.movies.aggregate([
{
"$search": {
"range": {
"path": "released",
"gt": ISODate("2010-01-01T00:00:00.000Z"),
"lt": ISODate("2015-01-01T00:00:00.000Z")
},
"sort": {
"released": -1
}
}
},
{
"$limit": 5
},
{
"$project": {
"_id": 0,
"title": 1,
"released": 1
}
}
])
[
{
title: 'Cold in July',
released: ISODate("2014-12-31T00:00:00.000Z")
},
{
title: 'The Gambler',
released: ISODate("2014-12-31T00:00:00.000Z")
},
{
title: 'Force Majeure',
released: ISODate("2014-12-30T00:00:00.000Z")
},
{
title: 'LFO',
released: ISODate("2014-12-27T00:00:00.000Z")
},
{
title: 'Peace After Marriage',
released: ISODate('2014-12-26T00:00:00.000Z')
}
]

The following query on the sample_mflix.movies namespace uses the $search stage to do the following:

  • Search for movies that have won awards.

  • Sort the results in descending order using sort option.

The query uses the $limit stage to limit the output to 5 documents. It also uses the $project stage to omit all fields except title and awards.wins in the results.

db.movies.aggregate([
{
"$search": {
"range": {
"path": "awards.wins",
"gt": 3
},
"sort": {
"awards.wins": -1
}
}
},
{
"$limit": 5
},
{
"$project": {
"_id": 0,
"title": 1,
"awards.wins": 1
}
}
])
[
{ title: '12 Years a Slave', awards: { wins: 267 } },
{ title: 'Gravity', awards: { wins: 231 } },
{ title: 'Gravity', awards: { wins: 231 } },
{
title: 'Birdman: Or (The Unexpected Virtue of Ignorance)',
awards: { wins: 210 }
},
{ title: 'Boyhood', awards: { wins: 185 } },
]

The following query on the sample_mflix.movies namespace uses the $search stage to do the following:

  • Search for movies that have the term country in the title.

  • Sort the results in ascending order using sort option.

The query uses the $limit stage to limit the output to 5 documents. It also uses the $project stage to do the following:

  • Omit all fields except title in the results.

  • Add a field named score.

db.movies.aggregate([
{
"$search": {
"text": {
"path": "title",
"query": "country"
},
"sort": {
"title": 1
}
}
},
{
"$limit": 5
},
{
"$project": {
"_id": 0,
"title": 1,
"score": { "$meta": "searchScore" }
}
}
])
[
{ title: 'A Country Called Home', score: 2.536633253097534 },
{ title: 'A Month in the Country', score: 2.258953094482422 },
{ title: 'A Quiet Place in the Country', score: 2.0360684394836426 },
{ title: 'A Sunday in the Country', score: 2.258953094482422 },
{ title: 'Another Country', score: 3.3635599613189697 }
]

The following query uses the range operator to search the the released field in the sample_mflix.movies collection for movies released between 2015-01-01 and 2015-12-31. It sorts the results by the _id field, which contains value of type ObjectId, in descending order.

db.movies.aggregate([
{
"$search": {
"range": {
"path": "released",
"gt": ISODate("2015-01-01T00:00:00.000Z"),
"lt": ISODate("2015-12-31T00:00:00.000Z")
},
"sort": {
"_id": -1
}
}
},
{
"$limit": 5
},
{
"$project": {
"_id": 1,
"title": 1,
"released": 1,
"score": { "$meta": "searchScore" }
}
}
])
[
{
_id: ObjectId('573a13fbf29313caabdedf31'),
title: 'No Home Movie',
released: ISODate('2015-08-10T00:00:00.000Z'),
score: 1
},
{
_id: ObjectId('573a13fbf29313caabdedf30'),
title: 'Our Loved Ones',
released: ISODate('2015-08-12T00:00:00.000Z'),
score: 1
},
{
_id: ObjectId('573a13faf29313caabded406'),
title: 'The Red Spider',
released: ISODate('2015-11-20T00:00:00.000Z'),
score: 1
},
{
_id: ObjectId('573a13faf29313caabded1d6'),
title: 'The Laundryman',
released: ISODate('2015-07-11T00:00:00.000Z'),
score: 1
},
{
_id: ObjectId('573a13faf29313caabdecaf3'),
title: 'Right Now, Wrong Then',
released: ISODate('2015-09-01T00:00:00.000Z'),
score: 1
}
]

The following query searches for the term hello in field b in the users collection. The query sorts the results by field a, which contains polymorphic data (to demonstrate the sort order), in ascending order.

db.users.aggregate([
{
"$search": {
"text": {
"path": "b",
"query": "hello"
},
"sort": {
"a": 1
}
}
},
{
"$project": {
"_id": 1,
"a": 1,
"score": { "$meta": "searchScore" }
}
}
])
[
{ _id: 3, score: 0.039550621062517166 },
{
_id: 0,
a: UUID('1a324de2-e34b-c87e-f2a1-42ce37ad74ed'),
score: 0.039550621062517166
},
{
_id: 1,
a: UUID('3b241101-e2bb-4255-8caf-4136c566a962'),
score: 0.039550621062517166
},
{
_id: 4,
a: UUID('d3c12e1c-c36e-25ed-7c3e-1e7f1e53c752'),
score: 0.039550621062517166
},
{
_id: 2,
a: UUID('dee11d4e-63c6-4d90-983c-5c9f1e79e96c'),
score: 0.039550621062517166
}
]

The following query searches field b for the string hello in the users collection using the text operator. The query sorts the results by field a in ascending order.

db.users.aggregate([
{
"$search": {
"text": {
"path": "b",
"query": "hello"
},
"sort": {
"c": 1
}
}
},
{
"$project": {
"_id": 1,
"c": 1,
"score": { "$meta": "searchScore" }
}
}
])
[
{ _id: 4, c: null, score: 0.039550621062517166 },
{ _id: 2, c: 'foo', score: 0.039550621062517166 },
{
_id: 3,
c: UUID('3be11d4e-62cb-4e95-9a3c-5c9f1e56c732'),
score: 0.039550621062517166
},
{
_id: 0,
c: ObjectId('507f1f77bcf86cd799439011'),
score: 0.039550621062517166
},
{ _id: 1, c: true, score: 0.039550621062517166 }
]

Atlas Search returns all the documents, but the ordering of documents with "_id": 2 and "_id": 4 is random because Atlas Search treats missing and nulls equally when sorting. For more details, see the MongoDB sort order for sorting data of different BSON types.

The following query searches the sample_airbnb.listingsAndReviews collection for properties in Portugal and sorts the results in descending order by the boolean field is_location_exact.

The query uses the $limit stage to limit the output to 5 documents. It also uses the $project stage to omit all fields except name, property_type, address.country, and address.location.is_location_exact in the results.

1db.listingsAndReviews.aggregate([
2 {
3 "$search": {
4 "text": {
5 "path": "address.country",
6 "query": "Portugal"
7 },
8 "sort": {
9 "address.location.is_location_exact": -1,
10 }
11 }
12 },
13 {
14 "$limit": 5
15 },
16 {
17 "$project": {
18 "_id": 0,
19 "name": 1,
20 "property_type": 1,
21 "address.country": 1,
22 "address.location.is_location_exact": 1
23 }
24 }
25])
1[
2 {
3 name: 'BBC OPORTO 4X2',
4 property_type: 'Apartment',
5 address: { country: 'Portugal', location: { is_location_exact: true } }
6 },
7 {
8 name: 'Heroísmo IV',
9 property_type: 'Apartment',
10 address: { country: 'Portugal', location: { is_location_exact: true } }
11 },
12 {
13 name: 'Spacious and well located apartment',
14 property_type: 'Apartment',
15 address: { country: 'Portugal', location: { is_location_exact: true } }
16 },
17 {
18 name: 'Renovated Classic Design Studio with Sun Room',
19 property_type: 'Apartment',
20 address: { country: 'Portugal', location: { is_location_exact: true } }
21 },
22 {
23 name: "O'Porto Studio | Historic Center",
24 property_type: 'Loft',
25 address: { country: 'Portugal', location: { is_location_exact: true } }
26 }
27]

In the preceding results, the value of is_location_exact is true for the documents because in a descending sort, Atlas Search ranks true values above false values. If you do an ascending sort by changing the value on line 9 of the preceding query to 1, Atlas Search ranks the documents with false values higher than true values and returns the following documents:

[
{
name: 'Ribeira Charming Duplex',
property_type: 'House',
address: { country: 'Portugal', location: { is_location_exact: false } }
},
{
name: 'Be Happy in Porto',
property_type: 'Loft',
address: { country: 'Portugal', location: { is_location_exact: false } }
},
{
name: 'Downtown Oporto Inn (room cleaning)',
property_type: 'Hostel',
address: { country: 'Portugal', location: { is_location_exact: false } }
},
{
name: 'A Casa Alegre é um apartamento T1.',
property_type: 'Apartment',
address: { country: 'Portugal', location: { is_location_exact: false } }
},
{
name: 'FloresRooms 3T',
property_type: 'Apartment',
address: { country: 'Portugal', location: { is_location_exact: false } }
}
]

The following query uses the $search stage to do the following:

  • Search for movies that have the term dance in the title, with a preference for movies that have won 2 or more awards and were released after 01 January, 1990.

  • Sort the results by the number of awards in descending order, then by the movie title in ascending order, and then by the release date in descending order.

The query uses the $limit stage to limit the output to 10 documents. It also uses the $project stage to do the following:

  • Omit all fields except title, released, and awards.wins in the results.

  • Add a field named score.

db.movies.aggregate([
{
"$search": {
"compound": {
"must": [{
"text": {
"path": "title",
"query": "dance"
}
}],
"should": [{
"range": {
"path": "awards.wins",
"gte": 2
}
}, {
"range": {
"path": "released",
"gte": ISODate("1990-01-01T00:00:00.000Z")
}
}]
},
"sort": {
"awards.wins": -1,
"title": 1,
"released": -1
}
}
},
{
"$limit": 10
},
{
"$project": {
"_id": 0,
"title": 1,
"released": 1,
"awards.wins": 1,
"score": { "$meta": "searchScore" }
}
}
])
[
{
title: 'Shall We Dance?',
released: ISODate("1997-07-11T00:00:00.000Z"),
awards: { wins: 57 },
score: 4.9811458587646484
},
{
title: 'Shall We Dance?',
released: ISODate("1997-07-11T00:00:00.000Z"),
awards: { wins: 57 },
score: 4.9811458587646484
},
{
title: 'War Dance',
released: ISODate("2008-11-01T00:00:00.000Z"),
awards: { wins: 11 },
score: 5.466421127319336
},
{
title: 'Dance with the Devil',
released: ISODate("1997-10-31T00:00:00.000Z"),
awards: { wins: 6 },
score: 4.615056037902832
},
{
title: 'Save the Last Dance',
released: ISODate("2001-01-12T00:00:00.000Z"),
awards: { wins: 6 },
score: 4.615056037902832
},
{
title: 'Dance with a Stranger',
released: ISODate("1985-08-09T00:00:00.000Z"),
awards: { wins: 4 },
score: 3.615056037902832
},
{
title: 'The Baby Dance',
released: ISODate("1998-08-23T00:00:00.000Z"),
awards: { wins: 4 },
score: 4.981145858764648
},
{
title: 'Three-Step Dance',
released: ISODate("2004-02-19T00:00:00.000Z"),
awards: { wins: 4 },
score: 4.981145858764648
},
{
title: "Cats Don't Dance",
released: ISODate("1997-03-26T00:00:00.000Z"),
awards: { wins: 3 },
score: 4.981145858764648
},
{
title: 'Dance Me Outside',
released: ISODate("1995-03-10T00:00:00.000Z"),
awards: { wins: 3 },
score: 4.981145858764648
}
]

The following query uses the $search stage to do the following:

  • Search for movies released between 01 January, 2010 and 01, January, 2015 using the range operator.

  • Get a count of the number of movies that won 1, 5, 10, and 15 awards.

  • Get a count of the number of movies released on 2010-01-01, 2011-01-01, 2012-01-01, 2013-01-01, 2014-01-01, and 2015-01-01.

  • Sort the results in descending order of released date using the sort option.

The query uses the $limit stage to do the following:

  • Limit the output to 5 documents in the docs output field.

  • Limit the output to 1 document in the meta output field.

It uses the $project stage to omit all fields except the awards.wins, released, and title fields.

It also uses the $replaceWith stage to include the metadata results stored in the $$SEARCH_META variable in the meta output field and the $set stage to add the meta field to the results.

db.movies.aggregate([
{
"$search": {
"facet": {
"operator": {
"range": {
"path": "released",
"gt": ISODate("2010-01-01T00:00:00.000Z"),
"lt": ISODate("2015-01-01T00:00:00.000Z")
}
},
"facets": {
"awardsFacet": {
"type": "number",
"path": "awards.wins",
"boundaries" : [1,5,10,15]
},
"releasedFacet" : {
"type" : "date",
"path" : "released",
"boundaries" : [ISODate("2010-01-01T00:00:00.000Z"), ISODate("2011-01-01T00:00:00.000Z"), ISODate("2012-01-01T00:00:00.000Z"), ISODate("2013-01-01T00:00:00.000Z"), ISODate("2014-01-01T00:00:00.000Z"), ISODate("2015-01-01T00:00:00.000Z")]
}
}
},
"sort": {
"released": -1
}
}
},
{
"$facet": {
"docs": [
{ "$limit": 5 },
{ "$project":
{
"_id": 0,
"title": 1,
"released": 1,
"awards.wins": 1
}
}
],
"meta": [
{"$replaceWith": "$$SEARCH_META"},
{"$limit": 1}
]
}
},
{
"$set": {
"meta": {
"$arrayElemAt": ["$meta", 0]
}
}
}
])
[
{
docs: [
{
title: 'Cold in July',
released: ISODate("2014-12-31T00:00:00.000Z"),
awards: { wins: 1 }
},
{
title: 'The Gambler',
released: ISODate("2014-12-31T00:00:00.000Z"),
awards: { wins: 7 }
},
{
title: 'Force Majeure',
released: ISODate("2014-12-30T00:00:00.000Z"),
awards: { wins: 31 }
},
{
title: 'LFO',
released: ISODate("2014-12-27T00:00:00.000Z"),
awards: { wins: 3 }
},
{
title: 'Peace After Marriage',
released: ISODate('2014-12-26T00:00:00.000Z'),
awards: { wins: 5 }
}
],
meta: {
count: { lowerBound: Long("4821") },
facet: {
releasedFacet: {
buckets: [
{
_id: ISODate("2010-01-01T00:00:00.000Z"),
count: Long("857")
},
{
_id: ISODate("2011-01-01T00:00:00.000Z"),
count: Long("909")
},
{
_id: ISODate("2012-01-01T00:00:00.000Z"),
count: Long("903")
},
{
_id: ISODate("2013-01-01T00:00:00.000Z"),
count: Long("1063")
},
{
_id: ISODate("2014-01-01T00:00:00.000Z"),
count: Long("1089")
}
]
},
awardsFacet: {
buckets: [
{ _id: 1, count: Long("2330") },
{ _id: 5, count: Long("604") },
{ _id: 10, count: Long("233") }
]
}
}
}
}
}
]

The following examples demonstrate how to sort the results by the score of the documents in the results. The examples demonstrate how to perform the following actions:

  • Retrieve the lowest scoring documents first by sorting the results in ascending order.

  • Sort the results by score in descending order and for results with identical scores, sort arbitrarily.

  • Sort the results by score and for results with identical scores, sort using a unique field.

The following query uses the $search stage to perform the following actions:

  • Search for movies that have the term story in the title.

  • Sort the results by score in ascending order.

The query uses the $limit stage to limit the output to 5 documents. It also uses the $project stage to perform the following actions:

  • Omit all fields except title in the results.

  • Add a field named score.

db.movies.aggregate([
{
"$search": {
"text": {
"path": "title",
"query": "story"
},
"sort": {score: {$meta: "searchScore", order: 1}}
}
},
{
"$limit": 5
},
{
"$project": {
"_id": 0,
"title": 1,
"score": {$meta: "searchScore"}
}
}
])
[
{
title: 'Do You Believe in Miracles? The Story of the 1980 U.S. Hockey Team',
score: 0.8674521446228027
},
{
title: 'Once in a Lifetime: The Extraordinary Story of the New York Cosmos',
score: 0.9212141036987305
},
{
title: 'The Source: The Story of the Beats and the Beat Generation',
score: 0.9820802211761475
},
{
title: 'If These Knishes Could Talk: The Story of the NY Accent',
score: 0.9820802211761475
},
{
title: 'Dream Deceivers: The Story Behind James Vance vs. Judas Priest',
score: 1.051558256149292
}
]

The following query uses the $search stage to perform the following actions:

  • Search for movies that have the term summer in the title.

  • Sort the results by score in descending order and for results with identical scores, sort arbitrarily.

The query uses the $limit stage to limit the output to 5 documents. It also uses the $project stage to perform the following actions:

  • Omit all fields except _id and title in the results.

  • Add a field named score.

db.movies.aggregate([
{
"$search": {
"text": {
"path": "title",
"query": "summer"
},
"sort": {score: {$meta: "searchScore"}}
}
},
{
"$limit": 5
},
{
"$project": {
"_id": 1,
"title": 1,
"score": {$meta: "searchScore"}
}
}
])
[
{
_id: ObjectId("573a1398f29313caabcea21e"),
title: 'Summer',
score: 3.5844719409942627
},
{
_id: ObjectId("573a13a6f29313caabd18eca"),
title: 'Summer Things',
score: 3.000213623046875
},
{
_id: ObjectId("573a13b8f29313caabd4c1d0"),
title: 'Summer Palace',
score: 3.000213623046875
},
{
_id: ObjectId("573a1394f29313caabcde8e8"),
title: 'Summer Stock',
score: 3.000213623046875
},
{
_id: ObjectId("573a13acf29313caabd284fa"),
title: 'Wolf Summer',
score: 3.000213623046875
}
]

The following query uses the $search stage to perform the following actions:

  • Search for movies that have the term prince in the title.

  • Sort the results first by score and then by the value of the released field in ascending order for results with identical scores.

The query uses the $limit stage to limit the output to 5 documents. It also uses the $project stage to perform the following actions:

  • Omit all fields except title and released in the results.

  • Add a field named score.

db.movies.aggregate([
{
"$search": {
"text": {
"path": "title",
"query": "prince"
},
"sort": {score: {$meta: "searchScore"}, "released": 1}
}
},
{
"$limit": 5
},
{
"$project": {
"_id": 0,
"title": 1,
"released": 1,
"score": {$meta: "searchScore"}
}
}
])
[
{
title: 'Prince',
released: ISODate("2015-08-14T00:00:00.000Z"),
score: 4.168826103210449
},
{
title: 'Prince Avalanche',
released: ISODate("2013-09-19T00:00:00.000Z"),
score: 3.4893198013305664
},
{
title: 'The Prince',
released: ISODate("2014-08-22T00:00:00.000Z"),
score: 3.4893198013305664
},
{
title: 'Prince of Foxes',
released: ISODate("1949-12-23T00:00:00.000Z"),
score: 3.0002830028533936
},
{
title: 'The Oil Prince',
released: ISODate("1966-01-01T00:00:00.000Z"),
score: 3.0002830028533936
}
]

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5. Define Additional Search Options