I have two mongo aggregate pipelines that output results. Now I want combine these two pipelines to have a singular output.
Please find below sample collection.
[
{
_id: "ddfdfdfdggfgfgsg",
rate: "3323",
quantity_packs: "343",
shop_name: "Whole Foods",
sku: "20"
manufacturer_name: "Unilever"
},
{
_id: "ddfdfdfsdsds",
rate: "434",
quantity_packs: "453",
shop_name: "Carrefour",
sku: "200"
manufacturer_name: "Unilever"
},
{
_id: "dfdfdgcvgfgfvvv",
rate: "343",
quantity_packs: "23",
shop_name: "Target",
manufacturer_name: "Beirsdorf"
sku: "34"
}
]
Please find below my queries.
First Query
db.collection.aggregate([
{
$match: {
manufacturer_name: {
$in: [ "unilever" ]
}
}
},
{
$group: {
_id: {
"Shop Name": "$shop_name"
},
"total_sku": {
"$addToSet": "$sku"
},
"annual_cost": {
$sum: {
$cond: [
{
$eq: ["$manufacturer_name", "unilever"]
},
{
"$toDouble": "$rate"
},
0
]
}
},
"annual_qty": {
$sum: {
"$toDouble": "$annual_qty"
}
}
}
},
{
$project: {
"sku count": {
"$size": "$total_sku"
},
"Annual Cost WO GST": {
$multiply: [ "$annual_cost", "$annual_qty" ]
},
}
},
])
Result of First Query
[
{
_id: { 'Hospital Name': '7AM mart' },
'sku count': 29,
'Annual Cost WO GST': 79968887.67999999
},
{
_id: { 'Shop Name': 'Apex' },
'sku count': 20,
'Annual Cost WO GST': 1779192666.96
}
]
Second Query
db.collection.aggregate([
{
$match: {
$expr: {
$ne: ["$manufacturer_name", "unilever"]
}
}
},
{
$group: {
_id: {
"Shop Name": "$shop_name"
},
"annual_cost_wo_gst_wo_manu": {
$sum: {
"$toDouble": "$rate"
}
},
"annual_qty": {
$sum: {
"$toDouble": "$annual_qty"
}
}
}
},
{
$project: {
"Ann Cost For Other Manufacturers": {
$multiply: ["$annual_cost_wo_gst_wo_manu", "$annual_qty"]
},
}
}
])
Result of Second Query
[
{
_id: { 'Hospital Name': 'Apex' },
'Ann Cost For Other Manufacturers': 25246715130525.273
},
{
_id: { 'Hospital Name': '7AM Mart' },
'Ann Cost For Other Manufacturers': 1347701834351.495
}
]
As mentioned above, I somehow want to combine to results by correctly mapping the items.
Intended Result
[
{
_id: { 'Hospital Name': '7AM mart' },
'sku count': 29,
'Annual Cost WO GST': 79968887.67999999
'Ann Cost For Other Manufacturers': 1347701834351.495
},
{
_id: { 'Shop Name': 'Apex' },
'sku count': 20,
'Annual Cost WO GST': 1779192666.96
'Ann Cost For Other Manufacturers': 25246715130525.273
}
]
Your 2 queries do not quite produce your stated outputs. Nevertheless, you could first perform uncorrelated $lookup to perform your second query, storing the result of your secondary query in a field/object. Then you can continue your first query. Finally extract the result of secondary query from the previously stored field/object.
Here is a Mongo playground with some modifications to your original examples for your reference.
Related
I'll explain my problem here and i'll put a tldr at the bottom summarizing the question.
We have a collection called apple_receipt, since we have some apple purchases in our application. That document has some fields that we will be using on this aggregation. Those are: price, currency, startedAt and history. Price, currency and startedAt are self-explanatory. History is a field that is an array of objects containing a price and startedAt. So, what we are trying to accomplish is a query that gets every document between a date of our choice, for example: 06-06-2020 through 10-10-2022 and get the total price combined of all those receipts that have a startedAt between that. We have a document like this:
{
price: 12.9,
currency: 'BRL',
startedAt: 2022-08-10T16:23:42.000+00:00
history: [
{
price: 12.9,
startedAt: 2022-05-10T16:23:42.000+00:00
},
{
price: 12.9,
startedAt: 2022-06-10T16:23:42.000+00:00
},
{
price: 12.9,
startedAt: 2022-07-10T16:23:42.000+00:00
}
]
}
If we query between dates 06-06-2022 to 10-10-2022, we would have a return like this: totalPrice: 38,7.
-total price of the 3 objects that have matched the date inside that value range-
I have tried this so far:
AppleReceipt.aggregate([
{
$project: {
price: 1,
startedAt: 1,
currency: 1,
history: 1,
}
},
{
$unwind: {
path: "$history",
preserveNullAndEmptyArrays: true,
}
},
{
$match: {
$or: [
{ startedAt: {$gte: new Date(filters.begin), $lt: new Date(filters.end)} },
]
}
},
{
$group: {
_id: "$_id",
data: { $push: '$$ROOT' },
totalAmountHelper: { $sum: '$history.price' }
}
},
{
$unwind: "$data"
},
{
$addFields: {
totalAmount: { $add: ['$totalAmountHelper', '$data.price'] }
}
}
])
It does bring me the total value but I couldn't know how to take into consideration the date to make the match stage to only get the sum of the documents that are between that date.
tl;dr: Want to make a query that gets the total sum of the prices of all documents that have startedAt between the dates we choose. Needs to match the ones inside history field - which is an array of objects, and also the startedAt outside of the history field.
https://mongoplayground.net/p/lOvRbX24QI9
db.collection.aggregate([
{
$set: {
"history_total": {
"$reduce": {
"input": "$history",
"initialValue": 0,
"in": {
$sum: [
{
"$cond": {
"if": {
$and: [
{
$gte: [
new Date("2022-06-06"),
{
$dateFromString: {
dateString: "$$this.startedAt"
}
}
]
},
{
$lt: [
{
$dateFromString: {
dateString: "$$this.startedAt"
}
},
new Date("2022-10-10")
]
},
]
},
"then": "$$this.price",
"else": 0
}
},
"$$value",
]
}
}
}
}
},
{
$set: {
"history_total": {
"$sum": [
"$price",
"$history_total"
]
}
}
}
])
Result:
[
{
"_id": ObjectId("5a934e000102030405000000"),
"currency": "BRL",
"history": [
{
"price": 12.9,
"startedAt": "2022-05-10T16:23:42.000+00:00"
},
{
"price": 12.9,
"startedAt": "2022-06-10T16:23:42.000+00:00"
},
{
"price": 12.9,
"startedAt": "2022-07-10T16:23:42.000+00:00"
}
],
"history_total": 325.79999999999995,
"price": 312.9,
"startedAt": "2022-08-10T16:23:42.000+00:00"
}
]
Kudos goes to #user20042973
I have an array field (contains objects) in multiple documents, I want to merge the arrays into one array and group the array by object key. I have manage to group the array but I dont know how to group the data. See the code I tried below
const test = await salesModel.aggregate([
{ $unwind: "$items" },
{
$group: {
_id: 0,
data: { $addToSet: '$items' }
},
}
])
Result of the query:
{
_id: 0,
data: [
{
_id: 61435b3c0f773abaf77a367e,
price: 3000,
type: 'service',
sellerId: 61307abca667678553be81cb,
},
{
_id: 613115808330be818abaa613,
price: 788,
type: 'product',
sellerId: 61307abca667678553be81cb,
},
{
_id: 61307c1ea667676078be81cc,
price: 1200,
type: 'product',
sellerId: 61307abca667678553be81cb,
}
]
}
Now I want to group the data array by object key data.sellerId and sum price
Desired Output:
{
data: [
{
sumPrice: 788,
sellerId: 613115808330be818abaa613,
},
{
sumPrice: 1200,
sellerId: 61307abca667678553be81cb,
}
]
}
Extend with the current query and result with:
$unwind: Deconstruct the array field to multiple documents.
$group: Group by data.sellerId to sum ($sum) for data.price.
$group: Group by 0 with $addToSet to combine multiple documents into one document with data.
MongoDB aggregation query
db.collection.aggregate([
{
$unwind: "$data"
},
{
$group: {
_id: {
sellerId: "$data.sellerId"
},
"sumPrice": {
$sum: "$data.price"
}
}
},
{
"$group": {
"_id": 0,
"data": {
$addToSet: {
"sellerId": "$_id.sellerId",
"sumPrice": "$sumPrice"
}
}
}
}
])
Sample Mongo Playground
Output
[
{
"_id": 0,
"data": [
{
"sellerId": ObjectId("61307abca667678553be81cb"),
"sumPrice": 4988
}
]
}
]
If you want to re-write the query, here are the query with sample input.
Input
[
{
items: [
{
_id: ObjectId("61435b3c0f773abaf77a367e"),
price: 3000,
type: "service",
sellerId: ObjectId("61307abca667678553be81cb"),
},
{
_id: ObjectId("613115808330be818abaa613"),
price: 788,
type: "product",
sellerId: ObjectId("61307abca667678553be81cb"),
},
{
_id: ObjectId("61307c1ea667676078be81cc"),
price: 1200,
type: "product",
sellerId: ObjectId("61307abca667678553be81cb"),
}
]
}
]
Mongo aggregation query
db.collection.aggregate([
{
$unwind: "$items"
},
{
$group: {
_id: {
sellerId: "$items.sellerId"
},
"sumPrice": {
$sum: "$items.price"
}
}
},
{
"$group": {
"_id": 0,
"data": {
$addToSet: {
"sellerId": "$_id.sellerId",
"sumPrice": "$sumPrice"
}
}
}
}
])
Sample 2 on Mongo Playground
Output
[
{
"_id": 0,
"data": [
{
"sellerId": ObjectId("61307abca667678553be81cb"),
"sumPrice": 4988
}
]
}
]
My company has inserted numerical values for certain keys in string format. They can't be converted to integer format for some business reason.
Now coming to the query...
I am writing a mongo aggregate query which calculates annual cost for a particular manufacturer like Unilever across shops. It seems I cannot convert a string to integer inside the $cond and $eq blocks using $toInt method.
Please find below the sample collection.
[
{
_id: "ddfdfdfdggfgfgsg",
rate: "3323",
quantity_packs: "343",
shop_name: "Whole Foods",
manufacturer_name: "Unilever"
},
{
_id: "ddfdfdfsdsds",
rate: "434",
quantity_packs: "453",
shop_name: "Carrefour",
manufacturer_name: "Unilever"
},
{
_id: "dfdfdgcvgfgfvvv",
rate: "343",
quantity_packs: "23",
shop_name: "Target",
manufacturer_name: "Beirsdorf"
}
]
The query is
db.collection.aggregate([
{
$match: {
manufacturer_name: {
$in: [ "Unilever" ]
}
}
},
{
$group: {
_id: {
"Shop Name": "$shop_name"
},
"annual_cost": {
$sum: {
$cond: [
{
$eq: ["manufacturer_name", "Unilever"]
},
{ "$toInt": "$rate"},
0
]
}
},
"other_annual_cost": {
$sum: {
$cond: [
{
$ne: [$manufacturer_name, "Unilever"]
}, {"$toInt" : "$rate"},
0
]
}
},
"annual_qty": {
$sum: {
"$toInt": "$quantity_packs"
}
},
}
},
{
$project: {
"Purchase_Cost": {
$multiply: [ "$annual_cost", "$annual_qty" ]
},
"Other Manu Pur Cost": {
$multiply: ["$other_annual_cost", "$annual_qty"]
}
}
}
])
Current Output
[
{
_id: { 'Shop Name': 'Whole Foods' },
Purchase_Cost: 0
}
]
As $rate is of string type, the multiplication has yielded 0 as shown over here. Ideally the result should show some integer value for purchase cost as shown below.
Intended Output
[
{
_id: { 'Shop Name': 'Whole Foods' },
Purchase_Cost: 234
}
]
Any suggestion would be of great help. I want to make this query work somehow.
I have updated the question based on Rajdeep's Answer.
I just corrected this, please take a look
Playground
"annual_cost": {
$sum: {
$cond: [
{
$eq: [
"$manufacturer_name", //added $
"Unilever"
]
},
{
$toInt: "$rate" //added $toInt
},
0
]
I have following 2 collection schema
images:{
imageId:"string", avgRating:{ rating1:decimal,rating2:decimal}, ratingCount:int}
}
ratings:{
imageId:"string", rating1:decimal, rating2:decimal
}
//here rating1 nd rating2 are ratings for different features(just according to my requirements)
so I am calculating avg as follows
db.images.aggregate([
{
$match: {
imageId: "someid",
},
},
{
$lookup:
{
from: "ratings",
let: {id: '$imageId'},
pipeline: [
{
$match: {
{
$eq: ['$imageId','$$id']
},
},
},{
$group:
{
_id: 0,
aggRating1: {$avg: "$rating1"},
aggRating2: {$avg: '$rating2'},
count: {$sum: 1}
}
},
{$project: {_id: 0,count:1,aggRating1:1,aggRating2:1}},
],
as: "rating"
}
},
{
$set: {
ratingCount: '$count',
'avgRating.rating1':'$review.aggRating1'
'avgRating.rating2':'$review.aggRating2'
}
},
]);
I am getting results like this
"data":[
{
"_id": "somedocId",
"imageId":"someid",
"ratingCount": 10,
"avgRating": {
"aggRating1": [
"rating1":{
"$numberDecimal": "3.25"
}],
"aggRating2": [
"rating2":{
"$numberDecimal": "3.25"
}]
},
"rating":[
{
"aggRating1": {
"$numberDecimal": "3.25"
},
"aggRating2": {
"$numberDecimal": "3.25"
},
"count": 10
}
],
}
]
So if u see when I set the aggRating1 and aggRating2 from rating lookup I got, it converts to array. But in rating it is an object. Idk why is that happening.
So how do i get just the decimal value of the avg results? and not like above? :/
I have a collection that looks like below:
[
{
"orderNum": "100",
"createdTime": ISODate("2020-12-01T21:00:00.000Z"),
"amount": 100,
"memo": "100memo",
"list": [
1
]
},
{
"orderNum": "200",
"createdTime": ISODate("2020-12-01T21:01:00.000Z"),
"amount": 200,
"memo": "200memo",
"list": [
1,
2
]
},
{
"orderNum": "300",
"createdTime": ISODate("2020-12-01T21:02:00.000Z"),
"amount": 300,
"memo": "300memo"
},
{
"orderNum": "400",
"createdTime": ISODate("2020-12-01T21:03:00.000Z"),
"amount": 400,
"memo": "400memo"
},
]
and I'm trying to get the total amount of orders that were created before order# 300 (so order#100 and #200, total amount is 300).
Does anyone know how to get it via Mongoose?
You can use this one:
db.collection.aggregate([
{ $sort: { orderNum: 1 } }, // by default the order of documents in a collection is undetermined
{ $group: { _id: null, data: { $push: "$$ROOT" } } }, // put all documents into one document
{ $set: { data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] } } }, // cut desired elementes from array
{ $unwind: "$data" }, // transform back to documents
{ $replaceRoot: { newRoot: "$data" } },
{ $group: { _id: null, total_amount: { $sum: "$amount" } } } // make summary
])
Actually it is not needed to $unwind and $group, so the shortcut would be this:
db.collection.aggregate([
{ $sort: { orderNum: 1 } },
{ $group: { _id: null, data: { $push: "$$ROOT" } } },
{ $set: { data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] } } },
{ $project: { total_amount: { $sum: "$data.amount" } } }
])
But the answer from #turivishal is even better.
Update for additional field
{
$set: {
data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] },
memo: { $arrayElemAt: [ "$data.memo", { $indexOfArray: ["$data.orderNum", "300"] } ] }
}
}
or
{ $set: { data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] } } },
{ $set: { memo: { $last: { "$data.memo" } } },
$match orderNum less than 300
$group by null and get totalAmount using $sum of amount
YourSchemaModel.aggregate([
{ $match: { orderNum: { $lt: "300" } } },
{
$group: {
_id: null,
totalAmount: { $sum: "$amount" }
}
}
])
Playground