Note
Access to this page requires authorization. You can try signing in or changing directories.
Access to this page requires authorization. You can try changing directories.
The $minN operator is used to retrieve the bottom N values for a field based on a specified filtering criteria.
Syntax
$minN: {
input: < field or expression > ,
n: < number of values to retrieve >
}
Parameters
| Parameter | Description |
|---|---|
input |
Specifies the field or expression to evaluate for minimum values. |
n |
Specifies the number of minimum values to retrieve. Must be a positive integer. |
Examples
Consider this sample document from the stores collection.
{
"_id": "7954bd5c-9ac2-4c10-bb7a-2b79bd0963c5",
"name": "Lakeshore Retail | DJ Equipment Stop - Port Cecile",
"location": {
"lat": 60.1441,
"lon": -141.5012
},
"staff": {
"totalStaff": {
"fullTime": 2,
"partTime": 0
}
},
"sales": {
"salesByCategory": [
{
"categoryName": "DJ Headphones",
"totalSales": 35921
}
],
"fullSales": 3700
},
"promotionEvents": [
{
"eventName": "Bargain Blitz Days",
"promotionalDates": {
"startDate": {
"Year": 2024,
"Month": 3,
"Day": 11
},
"endDate": {
"Year": 2024,
"Month": 2,
"Day": 18
}
},
"discounts": [
{
"categoryName": "DJ Turntables",
"discountPercentage": 18
},
{
"categoryName": "DJ Mixers",
"discountPercentage": 15
}
]
}
],
"tag": [
"#ShopLocal",
"#SeasonalSale",
"#FreeShipping",
"#MembershipDeals"
],
"company": "Lakeshore Retail",
"city": "Port Cecile",
"lastUpdated": {
"$date": "2024-12-11T10:21:58.274Z"
}
}
Example 1: Retrieve bottom two sales categories
This query retrieves the bottom two sales categories per store with the lowest sales volume. Run a query using the $minN operator on the nested salesCategory field.
db.stores.aggregate([{
$project: {
bottomSalesCategories: {
$minN: {
input: "$sales.salesByCategory",
n: 2
}
}
}
},
{
$limit: 4
}
])
This query returns the following results:
[
{
"_id": "a715ab0f-4c6e-4e9d-a812-f2fab11ce0b6",
"bottomSalesCategories": [
{
"categoryName": "Stockings",
"totalSales": 25731
}
]
},
{
"_id": "923d2228-6a28-4856-ac9d-77c39eaf1800",
"bottomSalesCategories": [
{
"categoryName": "Lamps",
"totalSales": 19880
},
{
"categoryName": "Rugs",
"totalSales": 20055
}
]
},
{
"_id": "7e53ca0f-6e24-4177-966c-fe62a11e9af5",
"bottomSalesCategories": [
{
"categoryName": "Markers",
"totalSales": 3927
}
]
},
{
"_id": "44fdb9b9-df83-4492-8f71-b6ef648aa312",
"bottomSalesCategories": [
{
"categoryName": "Storage Boxes",
"totalSales": 2236
}
]
}
]
Example 2 - Using $minN with $setWindowFields
To get the bottom two lists of sales categories by sales volume across all stores within the "First Up Consultants" company, first run a query to partition the stores by the company. Then, use the $minN operator to determine the two categories with the lowest sales within each partition.
db.stores.aggregate([{
$match: {
company: {
$in: ["First Up Consultants"]
}
}
}, {
$setWindowFields: {
partitionBy: "$company",
sortBy: {
"sales.totalSales": -1
},
output: {
minTwoBySales: {
$minN: {
input: "$sales.totalSales",
n: 2
}
}
}
}
}, {
$project: {
company: 1,
name: 1,
minCategoriesBySales: 1
}
}])
The first result returned by this query is:
[
{
"_id": "a0386810-b6f8-4b05-9d60-e536fb2b0026",
"name": "First Up Consultants | Electronics Stop - South Thelma",
"company": "First Up Consultants",
"minCategoriesBySales": [
[
{
"categoryName": "3D Printers",
"totalSales": 20882
},
{
"categoryName": "Phone Mounts",
"totalSales": 13624
},
{
"categoryName": "Prepaid Phones",
"totalSales": 7182
},
{
"categoryName": "MacBooks",
"totalSales": 10541
},
{
"categoryName": "Chargers",
"totalSales": 37542
},
{
"categoryName": "Student Laptops",
"totalSales": 43977
},
{
"categoryName": "Screen Protectors",
"totalSales": 14648
},
{
"categoryName": "Photo Printers",
"totalSales": 40064
},
{
"categoryName": "Printer Ink",
"totalSales": 30784
},
{
"categoryName": "Smartphone Cases",
"totalSales": 30468
},
{
"categoryName": "Printer Drums",
"totalSales": 34980
},
{
"categoryName": "Desktops",
"totalSales": 3890
}
],
[
{
"categoryName": "4K Camcorders",
"totalSales": 10466
},
{
"categoryName": "Tripods",
"totalSales": 30942
},
{
"categoryName": "Camcorder Accessories",
"totalSales": 25601
}
]
]
}
]
Example 3 - Using $minN operator as array-expression to get lowest two sales values
This query extracts the two lowest sales values for a specific store document.
db.stores.aggregate([
{ $match: {_id: "40d6f4d7-50cd-4929-9a07-0a7a133c2e74"} },
{
$project: {
name: 1,
lowestTwoSales: {
$minN: {
input: "$sales.salesByCategory.totalSales",
n: 2
}
}
}
}
])
This query returns the following result.
[
{
"_id": "40d6f4d7-50cd-4929-9a07-0a7a133c2e74",
"name": "Proseware, Inc. | Home Entertainment Hub - East Linwoodbury",
"lowestTwoSales": [28946, 3000]
}
]
Related content
- Review options for migrating from MongoDB to Azure DocumentDB.
- Read more about feature compatibility with MongoDB.