In this tutorial, we will discuss the MongoDB select, count, and group by aggregate stages.
The aggregate count and group stage together return the number of documents in a group. We will see an example for this topic in this guide so you can get a better idea of how to select count and group by.
Table of Contents
The MongoDB Count & Group Syntax
Let us take a look at the count and group aggregate stages syntax in MongoDB:
db.drones.aggregate([
{"$group":{fieldName, countFieldName:{$sum:1}}}])
Using the Aggregate Count & Group Stages in MongoDB
Let us start with the examples to cover in this guide for count and group aggregate stages. Below is the collection I will be using:
> db.drones.find().pretty()
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0c"),
"onSale" : false,
"name" : "Nimbari Gryphon Medeta 65",
"price" : 77500,
"weight" : "77 kilograms",
"additionalDetails" : {
"material" : "carbon fiber",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Cinematography"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0d"),
"onSale" : false,
"name" : "X-Strimmer Eye",
"price" : 23500,
"weight" : "24 kilograms",
"additionalDetails" : {
"material" : "glass fiber",
"moreUses" : [
"Precision Agriculture",
"Cinematography"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0e"),
"onSale" : false,
"name" : "Khai Balemosh Shefqa TRX",
"price" : 120500,
"weight" : "80 kilograms",
"additionalDetails" : {
"material" : "aluminum",
"moreUses" : [
"Precision Agriculture",
"Land Inspection"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf0f"),
"onSale" : false,
"name" : "Sifinist Croma AX",
"price" : 99500,
"weight" : "97 kilograms",
"additionalDetails" : {
"material" : "lithium",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("61673f46b34f185eb7b2bf10"),
"onSale" : false,
"name" : "Drovce Finnifield FR-7",
"price" : 87600,
"weight" : "13 kilograms",
"additionalDetails" : {
"material" : "polysterene",
"moreUses" : [
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("6195514a50f8bacf51bdb6ac"),
"onSale" : true,
"name" : "PlayGarra 2078-56",
"price" : 15000,
"weight" : "5 kilograms",
"additionalDetails" : {
"material" : "polysterene",
"moreUses" : [
"Cinematography",
"Wildlife Watching"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("6195514a50f8bacf51bdb6ad"),
"onSale" : true,
"name" : "Frinty Gemini 3X70",
"price" : 55000,
"weight" : "22 kilograms",
"additionalDetails" : {
"material" : "aluminum",
"moreUses" : [
"Cinematography",
"Wildlife Watching",
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("6195514a50f8bacf51bdb6ae"),
"onSale" : true,
"name" : "Rilche Gabbana Flier RG950",
"price" : 110000,
"weight" : "100 kilograms",
"additionalDetails" : {
"material" : "lithium",
"moreUses" : [
"Cinematography",
"Wildlife Watching",
"Precision Agriculture",
"Land Inspection",
"Water Inspection",
"Videography"
]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("619924ef4b1ff00cfd5eb3ae"),
"onSale" : true,
"name" : "Caminara Frucha FCZ-89",
"price" : 67800,
"weight" : "35 kilograms",
"additionalDetails" : {
"material" : "glass fibre",
"moreUses" : [ ]
},
"utility" : [
"Recreation",
"Photography",
"Videography",
"Delivery",
"Natural Resource Exploration"
]
}
{
"_id" : ObjectId("619924ef4b1ff00cfd5eb3af"),
"onSale" : true,
"name" : "Azehsra Chelske AZC-HYU56",
"price" : 45600,
"weight" : "32 kilograms",
"additionalDetails" : {
"material" : "carbon fibre",
"moreUses" : [
"Cinematography",
"Wildlife Watching",
"Precision Agriculture"
]
},
"utility" : null
}
{
"_id" : ObjectId("619924ef4b1ff00cfd5eb3b0"),
"onSale" : true,
"name" : "Hazela Gunce QY999",
"price" : 33900,
"weight" : "20 kilograms",
"additionalDetails" : {
"material" : "carbon fibre",
"moreUses" : [
"Videography",
"Wildlife Watching",
"Photography"
]
},
"utility" : [
undefined
]
}
Counting Documents Using $group by Querying on Top-Level Field
In this example, I will provide 3 different examples of counting documents of a collection and grouping them based on some criteria provided to the $group pipeline stage.
Example 1:
Counting documents by grouping them based on their prices.
> db.drones.aggregate([
... {"$group":{_id:"$price",counter:{$sum:1}}}])
{ "_id" : 33900, "counter" : 1 }
{ "_id" : 99500, "counter" : 1 }
{ "_id" : 120500, "counter" : 1 }
{ "_id" : 15000, "counter" : 1 }
{ "_id" : 55000, "counter" : 1 }
{ "_id" : 77500, "counter" : 1 }
{ "_id" : 23500, "counter" : 1 }
{ "_id" : 67800, "counter" : 1 }
{ "_id" : 110000, "counter" : 1 }
{ "_id" : 45600, "counter" : 1 }
{ "_id" : 87600, "counter" : 1 }
Example 2:
Counting documents by grouping them based on their names.
> db.drones.aggregate([
... {"$group":{_id:"$name",counter:{$sum:1}}}]);
{ "_id" : "PlayGarra 2078-56", "counter" : 1 }
{ "_id" : "Sifinist Croma AX", "counter" : 1 }
{ "_id" : "Drovce Finnifield FR-7", "counter" : 1 }
{ "_id" : "Azehsra Chelske AZC-HYU56", "counter" : 1 }
{ "_id" : "Frinty Gemini 3X70", "counter" : 1 }
{ "_id" : "Rilche Gabbana Flier RG950", "counter" : 1 }
{ "_id" : "Caminara Frucha FCZ-89", "counter" : 1 }
{ "_id" : "X-Strimmer Eye", "counter" : 1 }
{ "_id" : "Nimbari Gryphon Medeta 65", "counter" : 1 }
{ "_id" : "Khai Balemosh Shefqa TRX", "counter" : 1 }
{ "_id" : "Hazela Gunce QY999", "counter" : 1 }
Example 2:
Counting documents by grouping them based on the onSale field to see how many are false and how many are true.
> db.drones.aggregate([
... {"$group":{_id:"$onSale",counter:{$sum:1}}}])
{ "_id" : false, "counter" : 5 }
{ "_id" : true, "counter" : 6 }
Counting Documents Using $group by Querying on Nested Field
In this example, I will give you an example of counting documents and grouping them by operating on a nested field. I will be using dot notation to access the nested document or field.
Example 1:
Counting documents and grouping them based on the material nested field.
> db.drones.aggregate([
... {"$group":{_id:"$additionalDetails.material",counter:{$sum:1}}}])
{ "_id" : "glass fiber", "counter" : 1 }
{ "_id" : "lithium", "counter" : 2 }
{ "_id" : "polysterene", "counter" : 2 }
{ "_id" : "carbon fibre", "counter" : 2 }
{ "_id" : "carbon fiber", "counter" : 1 }
{ "_id" : "aluminum", "counter" : 2 }
{ "_id" : "glass fibre", "counter" : 1 }
Great! With this, we have learned to use the aggregate $group stage to count and group documents.
Conclusion
Learn to select documents by grouping and them and counting them in MongoDB with this easy guide.
References
https://docs.mongodb.com/manual/reference/operator/aggregation/group/#mongodb-pipeline-pipe.-group
https://stackoverflow.com/questions/23116330/mongodb-select-count-group-by