I'm trying to learn the advanced mongodb+mongoose function, so this is the result of my orders, and what I'm trying to do here is to compute the total amounts related to the sellerId
So in this one, I have two documents, the document 1 have an amount of 99 and and the other one is 11
so I need to get the sum of two. I've been searching and found the aggregate, but I can't figure out how I can combine the two documents.
[
{
"_id": "6360d1d0bd860240e2589564",
"userId": "6360cf687e186ebe29ab2a29",
"products": [
{
"productId": "6360cdd166480badb8c1e05b",
"quantity": 1,
"sellerId": "6360c6ed05e1e99034b5f7eb",
"_id": "6360d1d0bd860240e2589565"
}
],
"amount": 99,
"location": "asdsad",
"time": "asdsad",
"status": "pending",
"tax": 0.99,
},
{
"_id": "6360d7978044f3048e59bf34",
"userId": "6360d50dbd860240e258c585",
"products": [
{
"productId": "6360d7528044f3048e59bb6c",
"quantity": 1,
"sellerId": "6360d4d5bd860240e258c582",
"_id": "6360d7978044f3048e59bf35"
},
{
"productId": "6360d7868044f3048e59bd8c",
"quantity": 1,
"sellerId": "6360d4d5bd860240e258c582",
"_id": "6360d7978044f3048e59bf36"
}
],
"amount": 11,
"location": "Gym",
"time": "8:00 AM",
"status": "pending",
"tax": 0.11,
}
]
This might helps.
db.collection.aggregate([
{
$group: {
_id: null,
count: {
$sum: "$amount"
}
}
}
])
Related
I have a collection where from the backend user can input multiple same name bikes but with different registration number but in front-End I want them to be grouped by matching the same name but as user updates separately display image changes but I want only one display image as it is 1 vehicle
provided there is a node created I will implement it we can sort it by the latest and take the price and image of it
Activa -2 Count
KTM -1 Count
but there is a catch.
Activa 2 bikes but I want only count 2 and the price as it is the same in an array I want only 1 and the same applies to displayimage here display image file path is different but I want the latest one only Sharing data below
Data:
[
{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62e69ee3edfe4d0f3cb4994a",
"bikename": "KTM",
"bikenumber": "KA05HM2034",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-2020-honda-city-exterior-8-1659281111883.jpg",
"file_path": "https://www.example.com/images/upload/bike-2020-honda-city-exterior-8-1659281111883.jpg",
"idx": 1
}
},
{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62dba8418ef8f51f454ed757",
"bikename": "Activa",
"bikenumber": "KA05HM2033",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-v_activa-i-deluxe-1658562557459.jpg",
"file_path": "https://www.example.com/images/upload/bike-v_activa-i-deluxe-1658562557459.jpg",
"idx": 0
}
},
{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62d7ff7e70b9ab38c6ab0cb1",
"bikename": "Activa",
"bikenumber": "KA05HM2223",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"afterfreekmprice": 22,
"descreption": "Activa",
"displayimage": {
"file": "bike-v_activa-i-deluxe-1658322798414.jpg",
"file_path": "https://www.example.com/images/upload/bike-v_activa-i-deluxe-1658322798414.jpg",
"idx": 0
}
}
]
Expected:
[
{
"_id":{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62dba8418ef8f51f454ed757",
"bikename": "Activa",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-v_activa-i-deluxe-1658562557459.jpg",
"file_path": "https://www.example.com/images/upload/bike-v_activa-i-deluxe-1658562557459.jpg",
"idx": 0
}
},
"count": 2
},
{
"_id":{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62e69ee3edfe4d0f3cb4994a",
"bikename": "KTM",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-2020-honda-city-exterior-8-1659281111883.jpg",
"file_path": "https://www.example.com/images/upload/bike-2020-honda-city-exterior-8-1659281111883.jpg",
"idx": 1
}
}
"count": 1
}
]
You can use the aggregation pipeline,
$sort by _id in descending order
$group by bikename and get the first root document that is latest one in root and count total documents in count
$project to show required documents
db.collection.aggregate([
{ $sort: { _id: -1 } },
{
$group: {
_id: "$bikename",
root: { $first: "$$ROOT" },
count: { $sum: 1 }
}
},
{
$project: {
_id: "$root",
count: 1
}
}
])
Playground
You can use $group for this:
db.collection.aggregate([
{$group: {
_id: "$bikename",
count: {$sum: 1},
data: {$first: "$$ROOT"}
}
},
{$set: {"data.count": "$count"}},
{$replaceRoot: {newRoot: "$data"}}
])
See how it works on the playground example
Let's say I have a MongoDB storing transaction prices of a few products like this:
[
{
"_id": 1,
"product": "A",
"price": NumberDecimal("1.00")
},
{
"_id": 2,
"product": "A",
"price": NumberDecimal("20.00")
},
{
"_id": 3,
"product": "A",
"price": NumberDecimal("30.00")
},
{
"_id": 4,
"product": "B",
"price": NumberDecimal("10.00")
},
{
"_id": 5,
"product": "B",
"price": NumberDecimal("200.00")
},
{
"_id": 6,
"product": "B",
"price": NumberDecimal("300.00")
}
]
I want to remove bottom 10% of the extreme transaction prices, I do this:
db.collection.aggregate([
{
$bucketAuto: {
groupBy: "$price",
buckets: 10,
output: {
docs: {
$push: "$$ROOT"
}
}
}
},
{
$skip: 1
},
{
$unwind: "$docs"
},
{
$replaceWith: "$docs"
}
])
The outcome is like this:
[
{
"_id": 4,
"price": NumberDecimal("10.00"),
"product": "B"
},
{
"_id": 2,
"price": NumberDecimal("20.00"),
"product": "A"
},
{
"_id": 3,
"price": NumberDecimal("30.00"),
"product": "A"
},
{
"_id": 5,
"price": NumberDecimal("200.00"),
"product": "B"
},
{
"_id": 6,
"price": NumberDecimal("300.00"),
"product": "B"
}
]
The extreme transaction price 1.00 is removed. But I actually want the extreme 10% prices for each product to be removed, so that price 1.00 of product A is removed, and price 10.00 for product B is also removed. Expected result should be:
[
{
"_id": 2,
"price": NumberDecimal("20.00"),
"product": "A"
},
{
"_id": 3,
"price": NumberDecimal("30.00"),
"product": "A"
},
{
"_id": 5,
"price": NumberDecimal("200.00"),
"product": "B"
},
{
"_id": 6,
"price": NumberDecimal("300.00"),
"product": "B"
}
]
How can I achieve this? I have something very close but it is hard coding the product names in the query, which is very wrong:
https://mongoplayground.net/p/ur3Qmr2VJKb
I have two collections, products and orders.
products collection look like this.
[
{
"_id": "5efb56741c32133bf43ea9aa",
"title": "Xyz",
"image": "172e4eb73415b3cc8540e651.jpg",
"quantity": "1 Ltr",
"price": 1500,
"status": true,
"creationDate": "2020-06-30T15:12:52.570Z",
"__v": 0
},
{
"_id": "5f0079bd27a734424cb3069a",
"title": "abc",
"image": "122e4eb73413b3cc854n42n1.jpg",
"quantity": "500 ml",
"price": 700,
"status": true,
"creationDate": "2020-06-30T15:12:52.570Z",
"__v": 0
}
]
orders collection look like this.
[
{
"_id": "5efca937def27b74fc9f6aa6",
"products": [
{
"Date": "2020-07-01T15:14:36.630Z",
"_id": "5efca937def27b74fc9f6aa8",
"productId": "5efb56741c32133bf43ea9aa",
"productQuantity": 2
},
{
"Date": "2020-07-01T15:14:36.630Z",
"_id": "5efca937def27b74fc9f6aa7",
"productId": "5f0079bd27a734424cb3069a",
"productQuantity": 1
}
],
"totalQuantity": 3,
"totalPrice": 3700,
"creationDate": "2020-07-01T15:18:15.756Z",
"__v": 0
},
{
"_id": "5efca897def27b74fc9f6aa2",
"products": [
{
"Date": "2020-07-01T15:14:36.630Z",
"_id": "5efca897def27b74fc9f6aa3",
"productId": "5f0079bd27a734424cb3069a",
"productQuantity": 1
}
],
"totalQuantity": 1,
"totalPrice": 700,
"creationDate": "2020-07-01T15:15:35.422Z",
"__v": 0
}
]
using this two collections how can I get result like this:
[
{
"_id": "5efca937def27b74fc9f6aa6",
"products": [
{
"Date": "2020-07-01T15:14:36.630Z",
"_id": "5efca937def27b74fc9f6aa8",
"productId": "5efb56741c32133bf43ea9aa",
"productQuantity": 2,
"title": "Xyz",
"image": "172e4eb73415b3cc8540e651.jpg",
"quantity": "1 Ltr",
"price": 1500
},
{
"Date": "2020-07-01T15:14:36.630Z",
"_id": "5efca937def27b74fc9f6aa7",
"productId": "5f0079bd27a734424cb3069a",
"productQuantity": 1,
"title": "abc",
"image": "122e4eb73413b3cc854n42n1.jpg",
"quantity": "500 ml",
"price": 700
}
],
"totalQuantity": 3,
"totalPrice": 3700,
"creationDate": "2020-07-01T15:18:15.756Z",
"__v": 0
},
{
"_id": "5efca897def27b74fc9f6aa2",
"products": [
{
"Date": "2020-07-01T15:14:36.630Z",
"_id": "5efca897def27b74fc9f6aa3",
"productId": "5f0079bd27a734424cb3069a",
"productQuantity": 1,
"title": "abc",
"image": "122e4eb73413b3cc854n42n1.jpg",
"quantity": "500 ml",
"price": 700
}
],
"totalQuantity": 1,
"totalPrice": 700,
"creationDate": "2020-07-01T15:15:35.422Z",
"__v": 0
}
]
I got the result using this query.
order.aggregate([
{ "$unwind": "$products" },
{
$lookup: {
from: 'products',
localField: "products.productId",
foreignField: "_id",
as: "product"
}
},
{
"$addFields": {
"products": { $mergeObjects: [{ $arrayElemAt: ["$product", 0] }, "$$ROOT.products"] }
}
},
{
"$group": {
"_id": "$_id",
"products": { "$push": "$products" },
"totalQuantity": { $first: '$totalQuantity' },
"totalPrice": { $first: '$totalPrice' },
"creationDate": { $first: '$creationDate' }
}
}
])
I have my json object like this
{
"_id": "5c2e811154855c0012308f00",
"__pclass": "QXRzXFByb2plY3RcTW9kZWxcUHJvamVjdA==",
"id": 44328,
"name": "Test project via postman2//2",
"address": "some random address",
"area": null,
"bidDate": null,
"building": {
"name": "Health Care Facilities",
"type": "Dental Clinic"
},
"collaborators": [],
"createdBy": {
"user": {
"id": 7662036,
"name": "Someone Here"
},
"firm": {
"id": 2520967,
"type": "ATS"
}
},
"createdDate": "2019-01-03T21:39:29Z",
"customers": [],
"doneBy": null,
"file": null,
"firm": {
"id": 1,
"name": "MyFirm"
},
"leadSource": {
"name": "dontknow",
"number": "93794497"
},
"location": {
"id": null,
"city": {
"id": 567,
"name": "Bahamas"
},
"country": {
"id": 38,
"name": "Canada"
},
"province": {
"id": 7,
"name": "British Columbia"
}
},
"modifiedBy": null,
"modifiedDate": null,
"projectPhase": {
"id": 1,
"name": "pre-design"
},
"quotes": [{
"id": 19,
"opportunityValues": {
"Key1": 100,
"Key2 Key2": 100,
"Key3 Key3 Key3": 200,
}
}],
"specForecast": [],
"specIds": [],
"tags": [],
"valuation": "something"
}
I am trying to aggregate using this query in MongoDB. My aggregation key is 4 level deep and also contains spaces. On all online examples shows me the aggregation at the first level. Looking to the online codes, I tried to re-iterate the same with my 4th level deep key.
db.mydata.aggregate([
{$match: {"id": 44328 } } ,
{$group: { _id: "$quotes.id",
totalKey2:{ $sum: "$quotes.opportunityValues.Key2 Key2"},
totalKey3:{ $sum: "$quotes.opportunityValues.Key3 Key3 Key3"}
}
}
]);
This should return
_id totalKey2 totalKey3
0 19 100 300
But it is returning
_id totalKey2 totalKey3
0 19 0 0
What am I doing Wrong?
Although it's not recommended to use space in field names in Mongo, it works as expected.
The problem with your query is that "quotes" is an array and you should first unwind it before grouping it.
This works as expected:
db.mydata.aggregate([
{ $match: { "id": 44328 } } ,
{ $unwind: "$quotes" },
{ $group: { _id: "$quotes.id",
totalKey2:{ $sum: "$quotes.opportunityValues.Key2 Key2" },
totalKey3:{ $sum: "$quotes.opportunityValues.Key3 Key3 Key3" } }
}
]);
I have this documents of movie showing time and date:
`{
"_id": ObjectId("5628668c3e82c49245b7acdc"),
"ticketID": ObjectId("5606d36b5fbd7d76028b4b08"),
"uid": "50000",
"day": "Friday",
"date": "2015-10-23 21:05:00",
"adult": NumberLong(550),
"student": NumberLong(550),
"children": NumberLong(250),
"limit": NumberLong(20),
"sold": NumberLong(0)
},{
"_id": ObjectId("562866013e82c49045b7acdc"),
"ticketID": ObjectId("5606d36b5fbd7d76028b4b08"),
"uid": "50000",
"day": "Friday",
"date": "2015-10-23 19:30:00",
"adult": NumberLong(1050),
"student": NumberLong(800),
"children": NumberLong(550),
"limit": NumberLong(20),
"sold": NumberLong(0)
},{
"_id": ObjectId("562865013e82c49845b7acda"),
"ticketID": ObjectId("5606d36b5fbd7d76028b4b08"),
"uid": "50000",
"day": "Friday",
"date": "2015-10-23 18:45:00",
"adult": NumberLong(1500),
"student": NumberLong(750),
"children": NumberLong(750),
"limit": NumberLong(20),
"sold": NumberLong(0)
}
`
I want to group the final result by "day" where "ticketID" matches, "date" as an object and adding "adult","student","children","limit" to an array
-- UPDATE --
I would like the returned structure to follow:
{
"_id": "ticketID",
"day": "Friday",
"items": [
{
"date": date,
"time": time"adult": price,
"children": price,
"student": price,
"limit": value
},
{
"date": date,
"time": time"adult": price,
"children": price,
"student": price,
"limit": value
},
{
"date": date,
"time": time"adult": price,
"children": price,
"student": price,
"limit": value
}
]
}
Run the following aggregation pipeline which uses the $group operator to group your documents by the specified fields, add the items array by using the accumulator operator $push that returns an array of expression values for each group. The $project pipeline operator then reshapes the documents by amending the fields to get the final desired structure:
var pipeline = [
{
"$group": {
"_id": {
"ticketID": "$ticketID",
"day": "$day"
},
"items": {
"$push": {
"date": "$date",
"time": "$time",
"adult": "$adult",
"children": "$children",
"student": "$student",
"limit": "$limit"
}
}
}
},
{
"$project": {
"_id": "$_id.ticketID",
"day": "$_id.day",
"items": 1
}
}
];
db.collection.aggregate(pipeline);