in

For the complete MongoDB documentation index, see www.mongodb.com/docs/llms.txt

<!-- Tab options on this page. Append to the .md URL to filter: ?tabs=<id,...> select specific tabs (e.g. ?tabs=nodejs,shell) ?allTabs=true include every tab (no param) default: one tab per tabset

Available tabs: other tabs: single, multiple, compound -->

in Operator

Definition

The in operator in MongoDB Search performs a search for an array of BSON (Binary Javascript Object Notation) number, date, boolean, objectId, uuid, or string values at the given path and returns documents where the value of the field equals any value in the specified array. If the field holds an array, then the in operator selects the documents whose field holds an array that contains at least one element that matches any value in the specified array.

Syntax

The in operator has the following syntax:

{
  $search: {
    "index": <index name>, // optional, defaults to "default"
    "in": {
      "path": "<field-to-search>",
      "score": <options>,
      "value": <single-or-array-of-values-to-search>,
      "doesNotAffect": "<facet-to-exclude>" | [<array-of-facets>]
    }
  }
}

Fields

Examples

The following examples use the in operator to query collections in the [sample_analytics.customers](https://www.mongodb.com/docs/manual/sample-data/sample-analytics.md#std-label-sample-analytics collection. If you load the sample data on your cluster and [create](https://www.mongodb.com/docs/search/indexes/manage-indexes.md#std-label-ref-create-index a MongoDB Search index named default that uses [static mappings](https://www.mongodb.com/docs/search/indexes/define-field-mappings.md#std-label-static-dynamic-mappings on the collection, you can run the following queries against the collections.

Sample Index

The sample index definition specifies the following actions to support in operator queries against the indexed fields in the collection:

• Automatically index all the dynamically indexable fields in the collection.

• Statically index the name field as the [token](https://www.mongodb.com/docs/search/indexes/field-types/token-type.md#std-label-bson-data-types-token type and converts the text in the field to lowercase.

{
  "mappings": {
    "index": "default",
    "dynamic": true,
    "fields": {
      "name": {
        "normalizer": "lowercase",
        "type": "token"
      }
    }
  }
}

To learn how to create a MongoDB Search index, see [Manage MongoDB Search Indexes.](https://www.mongodb.com/docs/search/indexes/manage-indexes.md#std-label-ref-create-index

Sample Queries

Single Value Field Match

The following query uses the in operator to search the birthdate field, which contains a single value, for customers who were born on given dates. The query uses the [$project](https://www.mongodb.com/docs/manual/reference/operator/aggregation/project.md#mongodb-pipeline-pipe.-project stage to:

• Omit the _id field in the results.

• Include only the name and birthdate fields in the results.

db.customers.aggregate([
  {
    "$search": {
      "in": {
        "path": "birthdate",
        "value": [ISODate("1977-03-02T02:20:31.000+00:00"), ISODate("1977-03-01T00:00:00.000+00:00"), ISODate("1977-05-06T21:57:35.000+00:00")]
      }
    }
  },
  {
    "$project": {
      "_id": 0,
      "name": 1,
      "birthdate": 1
    }
  }
])

Output:

[
  {
    name: 'Elizabeth Ray',
    birthdate: ISODate("1977-03-02T02:20:31.000Z")
  },
  {
    name: 'Brad Cardenas',
    birthdate: ISODate("1977-05-06T21:57:35.000Z")
  }
]

MongoDB Search returns two documents that it matches with the dates specified in the query.

Facet Query

The following query uses the in operator to search the active field, which contains a boolean value, for customers who are active. The query returns the number of active customers whose birthdate falls in the following buckets:

• 1970-01-01, inclusive lower bound for this bucket

• 1980-01-01, exclusive upper bound for the 1970-01-01 bucket and inclusive lower bound for this bucket

• 1990-01-01, exclusive upper bound for the 1980-01-01 bucket and inclusive lower bound for this bucket

• 2000-01-01, exclusive upper bound for the 1990-01-01 bucket

db.customers.aggregate([
  {
    "$searchMeta": {
      "facet": {
        "operator": {
          "in": {
            "path": "active",
            "value": null
          }
        },
        "facets": {
          "birthdateFacet": {
            "type": "date",
            "path": "birthdate",
            "boundaries": [ISODate("1970-01-01"), ISODate("1980-01-01"), ISODate("1990-01-01"), ISODate("2000-01-01")],
            "default": "other"
          }
        }
      }
    }
  }
])

Output:

[
  {
    count: { lowerBound: Long('1') },
    facet: {
      birthdateFacet: {
        buckets: [
          {
            _id: ISODate('1970-01-01T00:00:00.000Z'),
            count: Long('1')
          },
          {
            _id: ISODate('1980-01-01T00:00:00.000Z'),
            count: Long('0')
          },
          {
            _id: ISODate('1990-01-01T00:00:00.000Z'),
            count: Long('0')
          }
        ]
      }
    }
  }
]