facet

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Definition

Syntax
Fields
Facet Definition
String Facets
Numeric Facets
Date Facets
Facet Results
SEARCH_META Aggregation Variable
Limitations
Examples

facet is only available on Atlas clusters running one of the following versions:

MongoDB 4.4.11+
MongoDB 5.0.4+
MongoDB 6.0+
MongoDB 7.0+
Note
To run facet queries over sharded collections, your cluster must run MongoDB v6.0 or higher.

You can't run facet queries with Retrieve Query Plan and Execution Statistics.

Definition

facet

The facet collector groups results by values or ranges in the specified faceted fields and returns the count for each of those groups.

You can use facet with both the $search and $searchMeta stages. MongoDB recommends using facet with the $searchMeta stage to retrieve metadata results only for the query. To retrieve metadata results and query results using the $search stage, you must use the $$SEARCH_META aggregation variable. See SEARCH_META Aggregation Variable to learn more.

Syntax

facet has the following syntax:

{
  "$searchMeta"|"$search": {
    "index": <index name>, // optional, defaults to "default"
    "facet": {
      "operator": {
        <operator-specifications>
      },
      "facets": {
        <facet-definitions>
      }
    }
  }
}

Fields

Field	Type	Required?	Description
`facets`	document	yes	Information for bucketing the data for each facet. You must specify at least one Facet Definition.
`operator`	document	no	Operator to use to perform the facet over. If omitted, Atlas Search performs the facet over all documents in the collection.

Facet Definition

The facet definition document contains the facet name and options specific to a type of facet. Atlas Search supports the following types of facets:

String Facets
Numeric Facets
Date Facets

String Facets

String facets allow you to narrow down Atlas Search results based on the most frequent string values in the specified string field. Note that the string field must be indexed as How to Index String Fields For Faceted Search.

Syntax

String facets have the following syntax:

{
  "$searchMeta": {
    "facet":{
      "operator": {
        <operator-specification>
      },
      "facets": {
        "<facet-name>" : {
          "type" : "string",
          "path" : "<field-path>",
          "numBuckets" : <number-of-categories>,
        }
      }
    }
  }
}

Options

Option	Type	Description	Required?
`numBuckets`	int	Maximum number of facet categories to return in the results. Value must be less than or equal to `1000`. If specified, Atlas Search may return fewer categories than requested if the data is grouped into fewer categories than your requested number. If omitted, defaults to `10`, which means that Atlas Search will return only the top `10` facet categories by count.	no
`path`	string	Field path to facet on. You can specify a field that is indexed as a How to Index String Fields For Faceted Search.	yes
`type`	string	Type of facet. Value must be `string`.	yes

Example

The following example uses an index named default on the sample_mflix.movies collection. The genres field in the collection is indexed as type How to Index String Fields For Faceted Search and the year field is indexed as How to Index Numeric Values.

{
  "mappings": {
    "dynamic": false,
    "fields": {
      "genres": {
        "type": "stringFacet"
      },
      "year": {
        "type": "number"
      }
    }
  }
}

The query uses the $searchMeta stage to search the year field in the movies collection for movies from 2000 to 2015 and retrieve a count of the number of movies in each genre.

db.movies.aggregate([
  {
    "$searchMeta": {
      "facet": {
        "operator": {
          "range": {
            "path": "year",
            "gte": 2000,
            "lte": 2015
          }
        },
        "facets": {
          "genresFacet": {
            "type": "string",
            "path": "genres"
          }
        }
      }
    }
  }
])

This query returns the following results:

[
  {
    count: { lowerBound: Long("13718") },
    facet: {
      genresFacet: {
        buckets: [
          { _id: 'Drama', count: Long("7759") },
          { _id: 'Comedy', count: Long("3937") },
          { _id: 'Romance', count: Long("1916") },
          { _id: 'Thriller', count: Long("1705") },
          { _id: 'Documentary', count: Long("1703") },
          { _id: 'Action', count: Long("1558") },
          { _id: 'Crime', count: Long("1475") },
          { _id: 'Adventure', count: Long("1111") },
          { _id: 'Horror', count: Long("1008") },
          { _id: 'Biography', count: Long("877") }
        ]
      }
    }
  }
]

To learn more about these results, see Facet Results.

Numeric Facets

Numeric facets allow you to determine the frequency of numeric values in your search results by breaking the results into separate ranges of numbers.

Syntax

Numeric facets have the following syntax:

{
  "$searchMeta": {
    "facet":{
      "operator": {
        <operator-specification>
      },
      "facets": {
        "<facet-name>" : {
          "type" : "number",
          "path" : "<field-path>",
          "boundaries" : <array-of-numbers>,
          "default": "<bucket-name>"
        }
      }
    }
  }
}

Options

Option	Type	Description	Required?
`boundaries`	array of numbers	List of numeric values, in ascending order, that specify the boundaries for each bucket. You must specify at least two boundaries. Each adjacent pair of values acts as the inclusive lower bound and the exclusive upper bound for the bucket. You can specify any combination of values of the following BSON types: 32-bit integer (`int32`) 64-bit integer (`int64`) 64-bit binary floating point (`double`)	yes
`default`	string	Name of an additional bucket that counts documents returned from the operator that do not fall within the specified boundaries. If omitted, Atlas Search includes the results of the facet operator that do not fall under a specified bucket also, but doesn't include it in any bucket counts.	no
`path`	string	Field path to facet on. You can specify a field that is indexed as a How to Index Numeric Values.	yes
`type`	string	Type of facet. Value must be `number`.	yes

Example

The following example uses an index named default on the sample_mflix.movies collection. The year field in the collection is indexed as type How to Index Numeric Values.

{
  "mappings": {
    "dynamic": false,
    "fields": {
      "year": [
        {
          "type": "numberFacet"
        }
      ]
    }
  }
}

The query uses the $searchMeta stage to search the year field in the movies collection for movies between the years 1980 to 2000 and retrieve metadata results for the query. The query specifies three buckets:

1980, inclusive lower bound for this bucket
1990, exclusive upper bound for the 1980 bucket and inclusive lower bound for this bucket
2000, exclusive upper bound for the 1990 bucket

The query also specifies a default bucket named other to retrieve results of the query that don't fall under any of the specified boundaries.

db.movies.aggregate([
  {
    "$searchMeta": {
      "facet": {
        "operator": {
          "range": {
            "path": "year",
            "gte": 1980,
            "lte": 2000
          }
        },
        "facets": {
          "yearFacet": {
            "type": "number",
            "path": "year",
            "boundaries": [1980,1990,2000],
            "default": "other"
          }
        }
      }
    }
  }
])

This query returns the following results:

[
  {
    "count" : {
      "lowerBound" : NumberLong(6472)
    },
    "facet" : {
      "yearFacet" : {
        "buckets" : [
          { "_id" : 1980, "count" : NumberLong(2081) },
          { "_id" : 1990, "count" : NumberLong(3773) },
          { "_id" : "other", "count" : NumberLong(618) }
        ]
      }
    }
  }
]

To learn more about these results, see Facet Results.

Date Facets

Date facets allow you to narrow down search results based on a date.

Syntax

Date facets have the following syntax:

{
  "$searchMeta": {
    "facet":{
      "operator": {
        <operator-specification>
      },
      "facets": {
        "<facet-name>" : {
          "type" : "date",
          "path" : "<field-path>",
          "boundaries" : <array-of-dates>,
          "default": "<bucket-name>"
        }
      }
    }
  }
}

Options

Option	Type	Description	Required?
`boundaries`	array of numbers	List of date values that specify the boundaries for each bucket. You must specify: At least two boundaries Values in ascending order, with the earliest date first Each adjacent pair of values acts as the inclusive lower bound and the exclusive upper bound for the bucket.	yes
`default`	string	Name of an additional bucket that counts documents returned from the operator that do not fall within the specified boundaries. If omitted, Atlas Search includes the results of the facet operator that do not fall under a specified bucket also, but Atlas Search doesn't include these results in any bucket counts.	no
`path`	string	Field path to facet on. You can specify a field that is indexed as a How to Index Date Fields.	yes
`type`	string	Type of facet. Value must be `date`.	yes

Example

The following example uses an index named default on the sample_mflix.movies collection. The released field in the collection is indexed as type How to Index Date Fields.

{
  "mappings": {
    "dynamic": false,
    "fields": {
      "released": [
        {
          "type": "dateFacet"
        }
      ]
    }
  }
}

The query uses the $searchMeta stage to search the released field in the movies collection for movies between the years 2000 to 2015 and retrieve metadata results for the query string. The query specifies four buckets:

2000-01-01, inclusive lower bound for this bucket
2005-01-01, exclusive upper bound for the 2000-01-01 bucket and inclusive lower bound for this bucket
2010-01-01, exclusive upper bound for the 2005-01-01 bucket and inclusive lower bound for this bucket
2015-01-01, exclusive upper bound for the 2010-01-01 bucket

The query also specifies a default bucket named other to retrieve results of the query that don't fall under any of the specified boundaries.

db.movies.aggregate([
  {
    "$searchMeta": {
      "facet": {
        "operator": {
          "range": {
            "path": "released",
            "gte": ISODate("2000-01-01T00:00:00.000Z"),
            "lte": ISODate("2015-01-31T00:00:00.000Z")
          }
        },
        "facets": {
          "yearFacet": {
            "type": "date",
            "path": "released",
            "boundaries": [ISODate("2000-01-01"), ISODate("2005-01-01"), ISODate("2010-01-01"), ISODate("2015-01-01")],
            "default": "other"
          }
        }
      }
    }
  }
])

This query returns the following results:

[
  {
    "count" : {
      "lowerBound" : NumberLong(13064)
    },
    "facet" : {
      "releaseFacet" : {
        "buckets" : [
          {
            "_id" : ISODate("2000-01-01T00:00:00Z"),
            "count" : NumberLong(3242)
          },
          {
            "_id" : ISODate("2005-01-01T00:00:00Z"),
            "count" : NumberLong(4266)
          },
          {
            "_id" : ISODate("2010-01-01T00:00:00Z"),
            "count" : NumberLong(5445)
          },
          {
            "_id" : "other",
            "count" : NumberLong(111)
          }
        ]
      }
    }
  }
]

To learn more about these results, see Facet Results.

Facet Results

For a facet query, Atlas Search returns a mapping of the defined facet names to an array of buckets for that facet in the results. The facet result document contains the buckets option, which is an array of resulting buckets for the facet. Each facet bucket document in the array has the following fields:

Option	Type	Description
`_id`	object	Unique identifier that identifies this facet bucket. This value matches the type of data that is being faceted on.
`count`	int	Count of documents in this facet bucket. To learn more about the `count` field, see Count Atlas Search Results.

`SEARCH_META` Aggregation Variable

When you run your query using the $search stage, Atlas Search stores the metadata results in the $$SEARCH_META variable and returns only the search results. You can use the $$SEARCH_META variable in all the supported aggregation pipeline stages to view the metadata results for your $search query.

MongoDB recommends using the $$SEARCH_META variable only if you need both the search results and the metadata results. Otherwise, use the:

$search stage for just the search results.
$searchMeta stage for just the metadata results.

Limitations

The following limitations apply:

You can run facet queries on a single field only. You can't run facet queries on groups of fields.
You can run facet queries over sharded collections on clusters running MongoDB v6.0 only.

Examples

The following examples use the sample_mflix.movies collection. The metadata results example demonstrates how to run a $searchMeta query with facet to retrieve only the metadata in the results. The metadata and search results example demonstrates how to run a $search query with facet and the $SEARCH_META aggregation variable to retrieve both the search and metadata results.

To learn more about these results, see Facet Results.

← exists geoShape →

facet.css-134mg1q{-webkit-align-self:center;-ms-flex-item-align:center;align-self:center;padding:0 10px;visibility:hidden;}.css-6vrlzm{border-radius:0!important;display:initial!important;margin:initial!important;}.css-1l4s55v{margin-top:-175px;position:absolute;padding-bottom:2px;}

Note

Definition

Syntax

Fields

Facet Definition

String Facets

Syntax

Options

Example

Example

Numeric Facets

Syntax

Options

Example

Example

Date Facets

Syntax

Options

Example

Example

Facet Results

SEARCH_META Aggregation Variable

Limitations

Examples

facet

`SEARCH_META` Aggregation Variable