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MongoDB vCore
The $objectToArray
operator is used to convert a document (that is, an object) into an array of key-value pairs. This operator can be useful when you need to manipulate or analyze the structure of a document in a more flexible array format.
The syntax for the $objectToArray
operator is as follows:
{
$objectToArray: <object>
}
Description | |
---|---|
<object> |
The document (or object) that you want to convert into an array of key-value pairs. |
Let's understand the usage with the following sample json.
{
"_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"
]
}
Here are some examples of how to use the $objectToArray
operator with the provided sample JSON.
The following aggregation pipeline converts the location
field of the store
document into an array of key-value pairs.
db.stores.aggregate([
{
$project: {
locationArray: { $objectToArray: "$location" }
}
},
// Limit the result to the first 3 documents
{ $limit: 3 }
])
This query would return the following document.
[
{
"_id": "649626c9-eda1-46c0-a27f-dcee19d97f41",
"locationArray": [ { "k": "lat", "v": -85.0867 }, { "k": "lon", "v": -165.3524 } ]
},
{
"_id": "8345de34-73ec-4a99-9cb6-a81f7b145c34",
"locationArray": [ { "k": "lat", "v": -22.5751 }, { "k": "lon", "v": -12.4458 } ]
},
{
"_id": "57cc4095-77d9-4345-af20-f8ead9ef0197",
"locationArray": [ { "k": "lat", "v": -41.287 }, { "k": "lon", "v": -76.0176 } ]
}
]
This example converts the totalStaff
field of the staff
document into an array of key-value pairs.
db.stores.aggregate([
{
$project: {
staffArray: { $objectToArray: "$staff.totalStaff" }
}
},
// Limit the result to the first 3 documents
{ $limit: 3 }
])
This query would return the following document.
[
{
"_id": "649626c9-eda1-46c0-a27f-dcee19d97f41",
"staffArray": [ { "k": "fullTime", "v": 15 }, { "k": "partTime", "v": 9 } ]
},
{
"_id": "8345de34-73ec-4a99-9cb6-a81f7b145c34",
"staffArray": [ { "k": "fullTime", "v": 12 }, { "k": "partTime", "v": 14 } ]
},
{
"_id": "57cc4095-77d9-4345-af20-f8ead9ef0197",
"staffArray": [ { "k": "fullTime", "v": 4 }, { "k": "partTime", "v": 8 } ]
}
]
This pipeline converts the promotionalDates
field for each promotion event into an array of key-value pairs.
db.stores.aggregate([
{
$project: {
promotionEvents: {
$map: {
input: "$promotionEvents",
as: "event",
in: {
eventName: "$$event.eventName",
promotionalDatesArray: { $objectToArray: "$$event.promotionalDates" }
}
}
}
}
},
// Limit the result to the first document
{ $limit: 1 }
])
This query would return the following document.
[
{
"_id": "649626c9-eda1-46c0-a27f-dcee19d97f41",
"promotionEvents": [
{
"eventName": "Markdown Mayhem",
"promotionalDatesArray": [
{ "k": "startDate", "v": { "Year": 2024, "Month": 3, "Day": 24 } },
{ "k": "endDate", "v": { "Year": 2024, "Month": 4, "Day": 3 } }
]
},
{
"eventName": "Spectacular Savings Showcase",
"promotionalDatesArray": [
{ "k": "startDate", "v": { "Year": 2024, "Month": 6, "Day": 22 } },
{ "k": "endDate", "v": { "Year": 2024, "Month": 7, "Day": 1 } }
]
}
]
}
]
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