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$type

Definition

$type

$type selects documents where the value of the field is an instance of the specified BSON type(s). Querying by data type is useful when dealing with highly unstructured data where data types are not predictable.

A $type expression for a single BSON type has the following syntax:

Changed in version 3.2.

{ field: { $type: <BSON type> } }

You can specify either the number or alias for the BSON type

The $type expression can also accept an array of BSON types and has the following syntax:

{ field: { $type: [ <BSON type1> , <BSON type2>, ... ] } }

The above query will match documents where the field value is any of the listed types. The types specified in the array can be either numeric or string aliases.

See Querying by Multiple Data Type for an example.

Available Types describes the BSON types and their corresponding numeric and string aliases.

See also

Behavior

$type returns documents where the BSON type of the field matches the BSON type passed to $type.

Arrays

For documents where field is an array, $type returns documents in which at least one array element matches a type passed to $type.

Querying for the Array BSON Type

With MongoDB 3.6 and later, querying for $type: "array" returns documents where the field itself is an array. Prior to MongoDB 3.6, $type: "array" returned documents where the field is an array containing at least one element of type array. For example, given the following documents:

{ "data" : [ "values", [ "values" ] ] }
{ "data" : [ "values" ] }

With MongoDB 3.6 and later, the query find( {"data" : { $type : "array" } } ) returns both documents. Prior to MongoDB 3.6, the query returns only the first document.

Available Types

Starting in MongoDB 3.2, $type operator accepts string aliases for the BSON types in addition to the numbers corresponding to the BSON types. Previous versions only accepted the numbers corresponding to the BSON type. [1]

Type Number Alias Notes
Double 1 “double”  
String 2 “string”  
Object 3 “object”  
Array 4 “array”  
Binary data 5 “binData”  
Undefined 6 “undefined” Deprecated.
ObjectId 7 “objectId”  
Boolean 8 “bool”  
Date 9 “date”  
Null 10 “null”  
Regular Expression 11 “regex”  
DBPointer 12 “dbPointer” Deprecated.
JavaScript 13 “javascript”  
Symbol 14 “symbol” Deprecated.
JavaScript code with scope 15 “javascriptWithScope” Deprecated in MongoDB 4.4.
32-bit integer 16 “int”  
Timestamp 17 “timestamp”  
64-bit integer 18 “long”  
Decimal128 19 “decimal” New in version 3.4.
Min key -1 “minKey”  
Max key 127 “maxKey”  

$type supports the number alias, which will match against the following BSON types:

For examples, see Examples.

[1]Starting in MongoDB 4.2, users can no longer use the query filter $type: 0 as a synonym for $exists:false. To query for null or missing fields, see Query for Null or Missing Fields.

See also

$isNumber New in MongoDB 4.4

MinKey and MaxKey

MinKey and MaxKey are used in comparison operations and exist primarily for internal use. For all possible BSON element values, MinKey will always be the smallest value while MaxKey will always be the greatest value.

Querying for minKey or maxKey with $type will only return fields that match the special MinKey or MaxKey values.

Suppose that the data collection has two documents with MinKey and MaxKey:

{ "_id" : 1, x : { "$minKey" : 1 } }
{ "_id" : 2, y : { "$maxKey" : 1 } }

The following query will return the document with _id: 1:

db.data.find( { x: { $type: "minKey" } } )

The following query will return the document with _id: 2:

db.data.find( { y: { $type: "maxKey" } } )

Examples

Querying by Data Type

The addressBook contains addresses and zipcodes, where zipCode has string, int, double, and long values:

db.addressBook.insertMany(
   [
      { "_id" : 1, address : "2030 Martian Way", zipCode : "90698345" },
      { "_id" : 2, address: "156 Lunar Place", zipCode : 43339374 },
      { "_id" : 3, address : "2324 Pluto Place", zipCode: NumberLong(3921412) },
      { "_id" : 4, address : "55 Saturn Ring" , zipCode : NumberInt(88602117) },
      { "_id" : 5, address : "104 Venus Drive", zipCode : ["834847278", "1893289032"]}
   ]
)

The following queries return all documents where zipCode is the BSON type string or is an array containing an element of the specified type:

db.addressBook.find( { "zipCode" : { $type : 2 } } );
db.addressBook.find( { "zipCode" : { $type : "string" } } );

These queries return:

{ "_id" : 1, "address" : "2030 Martian Way", "zipCode" : "90698345" }
{ "_id" : 5, "address" : "104 Venus Drive", "zipCode" : [ "834847278", "1893289032" ] }

The following queries return all documents where zipCode is the BSON type double or is an array containing an element of the specified type:

db.addressBook.find( { "zipCode" : { $type : 1 } } )
db.addressBook.find( { "zipCode" : { $type : "double" } } )

These queries return:

{ "_id" : 2, "address" : "156 Lunar Place", "zipCode" : 43339374 }

The following query uses the number alias to return documents where zipCode is the BSON type double, int, or long or is an array containing an element of the specified types:

db.addressBook.find( { "zipCode" : { $type : "number" } } )

These queries return:

{ "_id" : 2, "address" : "156 Lunar Place", "zipCode" : 43339374 }
{ "_id" : 3, "address" : "2324 Pluto Place", "zipCode" : NumberLong(3921412) }
{ "_id" : 4, "address" : "55 Saturn Ring", "zipCode" : 88602117 }

Querying by Multiple Data Type

The grades collection contains names and averages, where classAverage has string, int, and double values:

db.grades.insertMany(
   [
      { "_id" : 1, name : "Alice King" , classAverage : 87.333333333333333 },
      { "_id" : 2, name : "Bob Jenkins", classAverage : "83.52" },
      { "_id" : 3, name : "Cathy Hart", classAverage: "94.06" },
      { "_id" : 4, name : "Drew Williams" , classAverage : NumberInt("93") }
   ]
)

The following queries return all documents where classAverage is the BSON type string or double or is an array containing an element of the specified types. The first query uses numeric aliases while the second query uses string aliases.

db.grades.find( { "classAverage" : { $type : [ 2 , 1 ] } } );
db.grades.find( { "classAverage" : { $type : [ "string" , "double" ] } } );

These queries return the following documents:

{ "_id" : 1, "name" : "Alice King", "classAverage" : 87.33333333333333 }
{ "_id" : 2, "name" : "Bob Jenkins", "classAverage" : "83.52" }
{ "_id" : 3, "name" : "Cathy Hart", "classAverage" : "94.06" }

Querying by MinKey and MaxKey

The restaurants collection uses minKey for any grade that is a failing grade:

{
   "_id": 1,
   "address": {
      "building": "230",
      "coord": [ -73.996089, 40.675018 ],
      "street": "Huntington St",
      "zipcode": "11231"
   },
   "borough": "Brooklyn",
   "cuisine": "Bakery",
   "grades": [
      { "date": new Date(1393804800000), "grade": "C", "score": 15 },
      { "date": new Date(1378857600000), "grade": "C", "score": 16 },
      { "date": new Date(1358985600000), "grade": MinKey(), "score": 30 },
      { "date": new Date(1322006400000), "grade": "C", "score": 15 }
   ],
   "name": "Dirty Dan's Donuts",
   "restaurant_id": "30075445"
}

And maxKey for any grade that is the highest passing grade:

{
   "_id": 2,
   "address": {
      "building": "1166",
      "coord": [ -73.955184, 40.738589 ],
      "street": "Manhattan Ave",
      "zipcode": "11222"
   },
   "borough": "Brooklyn",
   "cuisine": "Bakery",
   "grades": [
      { "date": new Date(1393804800000), "grade": MaxKey(), "score": 2 },
      { "date": new Date(1378857600000), "grade": "B", "score": 6 },
      { "date": new Date(1358985600000), "grade": MaxKey(), "score": 3 },
      { "date": new Date(1322006400000), "grade": "B", "score": 5 }
   ],
   "name": "Dainty Daisey's Donuts",
   "restaurant_id": "30075449"
}

The following query returns any restaurant whose grades.grade field contains minKey or is an array containing an element of the specified type:

db.restaurants.find(
   { "grades.grade" : { $type : "minKey" } }
)

This returns

{
   "_id" : 1,
   "address" : {
      "building" : "230",
      "coord" : [ -73.996089, 40.675018 ],
      "street" : "Huntington St",
      "zipcode" : "11231"
   },
   "borough" : "Brooklyn",
   "cuisine" : "Bakery",
   "grades" : [
      { "date" : ISODate("2014-03-03T00:00:00Z"), "grade" : "C", "score" : 15 },
      { "date" : ISODate("2013-09-11T00:00:00Z"), "grade" : "C", "score" : 16 },
      { "date" : ISODate("2013-01-24T00:00:00Z"), "grade" : { "$minKey" : 1 }, "score" : 30 },
      { "date" : ISODate("2011-11-23T00:00:00Z"), "grade" : "C", "score" : 15 }
   ],
   "name" : "Dirty Dan's Donuts",
   "restaurant_id" : "30075445"
}

The following query returns any restaurant whose grades.grade field contains maxKey or is an array containing an element of the specified type:

db.restaurants.find(
   { "grades.grade" : { $type : "maxKey" } }
)

This returns

{
   "_id" : 2,
   "address" : {
      "building" : "1166",
      "coord" : [ -73.955184, 40.738589 ],
      "street" : "Manhattan Ave",
      "zipcode" : "11222"
   },
   "borough" : "Brooklyn",
   "cuisine" : "Bakery",
   "grades" : [
      { "date" : ISODate("2014-03-03T00:00:00Z"), "grade" : { "$maxKey" : 1 }, "score" : 2 },
      { "date" : ISODate("2013-09-11T00:00:00Z"), "grade" : "B", "score" : 6 },
      { "date" : ISODate("2013-01-24T00:00:00Z"), "grade" : { "$maxKey" : 1 }, "score" : 3 },
      { "date" : ISODate("2011-11-23T00:00:00Z"), "grade" : "B", "score" : 5 }
   ],
   "name" : "Dainty Daisey's Donuts",
   "restaurant_id" : "30075449"
}

Querying by Array Type

A collection named SensorReading contains the following documents:

{
   "_id": 1,
   "readings": [
      25,
      23,
      [ "Warn: High Temp!", 55 ],
      [ "ERROR: SYSTEM SHUTDOWN!", 66 ]
   ]
},
{
   "_id": 2,
   "readings": [
      25,
      25,
      24,
      23
   ]
},
{
   "_id": 3,
   "readings": [
      22,
      24,
      []
   ]
},
{
   "_id": 4,
   "readings": []
},
{
   "_id": 5,
   "readings": 24
}

The following query returns any document in which the readings field is an array, empty or non-empty.

db.SensorReading.find( { "readings" : { $type: "array" } } )

The above query returns the following documents:

{
   "_id": 1,
   "readings": [
      25,
      23,
      [ "Warn: High Temp!", 55 ],
      [ "ERROR: SYSTEM SHUTDOWN!", 66 ]
   ]
},
{
   "_id": 2,
   "readings": [
      25,
      25,
      24,
      23
   ]
},
{
   "_id": 3,
   "readings": [
      22,
      24,
      []
   ]
},
{
   "_id": 4,
   "readings": []
}

In the documents with _id : 1, _id : 2, _id : 3, and _id : 4, the readings field is an array.