In this guide, I am going to cover the $size operator in MongoDB.
The $size operator in MongoDB helps us match any array that matches the number of elements given by the argument. It works with the find operation.
This guide aims to provide examples so it is easier for you to use the $size operator in MongoDB with your applications. So, let us get this guide started.
The $size Operator Syntax
Let us take a quick look at the syntax of MongoDB’s $size operator.
db.collection.find( { field: { $size: 1 } } )
Here are just a few things to note.
The $size operator does not support value ranges. Create a counter field that you increment when you add elements to a field to select documents based on fields with different numbers of elements.
Queries cannot use indexes for the $size portion of a query, but indexes can be used for the other portions of a query if applicable.
Using the $size Operator in MongoDB
Let us get started by taking a look at some examples to know how to use the $size operator in MongoDB.
To achieve this below is the collection we will use to demonstrate the usage:
> db.drones.find().pretty()
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0c"),
"utility" : [
"Natural Resource Exploration",
"Remote sensing",
"Real estate and construction",
"Recreation",
"Delivery"
],
"onSale" : false,
"name" : "Nimbari Gryphon Medeta 65",
"price" : 77500,
"weight" : "77 kilograms",
"additionalDetails" : {
"material" : "carbon fiber",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Cinematography"
]
}
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0d"),
"utility" : [
"Natural Resource Exploration",
"Remote sensing",
"Real estate and construction",
"Recreation",
"Delivery"
],
"onSale" : false,
"name" : "X-Strimmer Eye",
"price" : 23500,
"weight" : "24 kilograms",
"additionalDetails" : {
"material" : "glass fiber",
"moreUses" : [
"Precision Agriculture",
"Cinematography"
]
}
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0e"),
"utility" : [
"Natural Resource Exploration",
"Remote sensing",
"Real estate and construction",
"Recreation",
"Delivery"
],
"onSale" : false,
"name" : "Khai Balemosh Shefqa TRX",
"price" : 120500,
"weight" : "80 kilograms",
"additionalDetails" : {
"material" : "aluminum",
"moreUses" : [
"Precision Agriculture",
"Land Inspection"
]
}
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0f"),
"utility" : [
"Natural Resource Exploration",
"Recreation",
"Delivery"
],
"onSale" : false,
"name" : "Sifinist Croma AX",
"price" : 99500,
"weight" : "97 kilograms",
"additionalDetails" : {
"material" : "lithium",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
}
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf10"),
"utility" : [
"Remote sensing",
"Real estate and construction",
"Recreation"
],
"onSale" : false,
"name" : "Drovce Finnifield FR-7",
"price" : 87600,
"weight" : "13 kilograms",
"additionalDetails" : {
"material" : "polysterene",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
}
}
Matching Top-Level Arrays with the $size Operator in MongoDB
Let us first see an example that aims to match array fields that is at the top level. We want to match all those documents whose utility array field is of the size 3.
> db.drones.find( { utility: { $size: 3 } } ).pretty()
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0f"),
"utility" : [
"Natural Resource Exploration",
"Recreation",
"Delivery"
],
"onSale" : false,
"name" : "Sifinist Croma AX",
"price" : 99500,
"weight" : "97 kilograms",
"additionalDetails" : {
"material" : "lithium",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
}
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf10"),
"utility" : [
"Remote sensing",
"Real estate and construction",
"Recreation"
],
"onSale" : false,
"name" : "Drovce Finnifield FR-7",
"price" : 87600,
"weight" : "13 kilograms",
"additionalDetails" : {
"material" : "polysterene",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
}
}
Perfect! We found 2 such documents with help of the $size operator.
Matching Embedded Array Fields with the $size Operator in MongoDB
This is an interesting one. Here in this example, we are operating on an array field that is embedded inside a document. We want to look for all those documents that have an array field called moreUses which is embedded inside additionalDetails field, with the size of 2.
> db.drones.find( { "additionalDetails.moreUses": { $size: 2 } } ).pretty()
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0d"),
"utility" : [
"Natural Resource Exploration",
"Remote sensing",
"Real estate and construction",
"Recreation",
"Delivery"
],
"onSale" : false,
"name" : "X-Strimmer Eye",
"price" : 23500,
"weight" : "24 kilograms",
"additionalDetails" : {
"material" : "glass fiber",
"moreUses" : [
"Precision Agriculture",
"Cinematography"
]
}
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0e"),
"utility" : [
"Natural Resource Exploration",
"Remote sensing",
"Real estate and construction",
"Recreation",
"Delivery"
],
"onSale" : false,
"name" : "Khai Balemosh Shefqa TRX",
"price" : 120500,
"weight" : "80 kilograms",
"additionalDetails" : {
"material" : "aluminum",
"moreUses" : [
"Precision Agriculture",
"Land Inspection"
]
}
}
Amazing! The operation went successful!
Conclusion
This guide will help you learn to use the $size operator in MongoDB inside the mongo shell.
References
https://docs.mongodb.com/manual/reference/operator/query/size/
https://linuxhint.com/size-operator-mongodb/
