I'm trying to return size of 'orders' and sum of 'item' values for each 'order' for each order from documents like the example document:
orders: [
{
order_id: 1,
items: [
{
item_id: 1,
value:100
},
{
item_id: 2,
value:200
}
]
},
{
order_id: 2,
items: [
{
item_id: 3,
value:300
},
{
item_id: 4,
value:400
}
]
}
]
I'm using following aggregation to return them, everything works fine except I can't get size of 'orders' array because after unwind, 'orders' array is turned into an object and I can't call $size on it since it is an object now.
db.users.aggregate([
{
$unwind: "$orders"
},
{
$project: {
_id: 0,
total_values: {
$reduce: {
input: "$orders.items",
initialValue: 0,
in: { $add: ["$$value", "$$this.value"] }
}
},
order_count: {$size: '$orders'}, //I get 'The argument to $size must be an array, but was of type: object' error
}
},
])
the result I expected is:
{order_count:2, total_values:1000} //For example document
{order_count:3, total_values:1500}
{order_count:5, total_values:2500}
I found a way to get the results that I wanted. Here is the code
db.users.aggregate([
{
$project: {
_id: 1, orders: 1, order_count: { $size: '$orders' }
}
},
{ $unwind: '$orders' },
{
$project: {
_id: '$_id', items: '$orders.items', order_count: '$order_count'
}
},
{ $unwind: '$items' },
{
$project: {
_id: '$_id', sum: { $sum: '$items.value' }, order_count: '$order_count'
}
},
{
$group: {
_id: { _id: '$_id', order_count: '$order_count' }, total_values: { $sum: '$sum' }
}
},
])
output:
{ _id: { _id: ObjectId("5dffc33002ef525620ef09f1"), order_count: 2 }, total_values: 1000 }
{ _id: { _id: ObjectId("5dffc33002ef525620ef09f2"), order_count: 3 }, total_values: 1500 }
Related
I have grouped all the users by country, but I would also like to have a row showing the grand total (users are tagged to a single country in our use case).
Data Model / Sample Input
The collection is filled with objects representing a country (name) and each contains a list of user objects in an array under users.
{ _id: ObjectId("..."),
name: 'SG',
type: 'COUNTRY',
increment: 200,
users:
[ ObjectId("..."),
ObjectId("..."),
...
Query
db.collection.aggregate([{$match:{type:"COUNTRY"}},{$unwind:"$users"},{$sortByCount:"$name"}])
Current Results
{ _id: 'SG', count: 76 }
{ _id: 'IN', count: 6 }
{ _id: 'US', count: 4 }
{ _id: 'FR', count: 3 }
{ _id: 'UK', count: 2 }
{ _id: 'RU', count: 1 }
{ _id: 'CO', count: 1 }
{ _id: 'DK', count: 1 }
{ _id: 'ID', count: 1 }
{ _id: 'PH', count: 1 }
Expected Results
{ _id: 'SG', count: 76 }
{ _id: 'IN', count: 6 }
{ _id: 'US', count: 4 }
{ _id: 'FR', count: 3 }
{ _id: 'UK', count: 2 }
{ _id: 'RU', count: 1 }
{ _id: 'CO', count: 1 }
{ _id: 'DK', count: 1 }
{ _id: 'ID', count: 1 }
{ _id: 'PH', count: 1 }
{ _id: null, count: 96 } <<< TOTAL COUNT ADDED
Any tips to achieve this without resorting to complex or dirty tricks?
You can also try using $facet to calculate counts by country name and total count, and then combine them together. Something like this:
db.collection.aggregate([
{
$match: {
type: "COUNTRY"
}
},
{
"$unwind": "$users"
},
{
"$facet": {
"groupCountByCountry": [
{
"$sortByCount": "$name"
}
],
"totalCount": [
{
"$group": {
"_id": null,
"count": {
"$sum": 1
}
}
}
]
}
},
{
"$project": {
array: {
"$concatArrays": [
"$groupCountByCountry",
"$totalCount"
]
}
}
},
{
"$unwind": "$array"
},
{
"$replaceRoot": {
"newRoot": "$$ROOT.array"
}
}
])
Here's the playground link.
I recommend just doing this in memory as the alternative is "hacky" but in order to achieve this in Mongo you just need to group all documents, add a new documents and unwind again, like so:
db.collection.aggregate([
{
$group: {
_id: null,
roots: {
$push: "$$ROOT"
},
sum: {
$sum: "$count"
}
}
},
{
$addFields: {
roots: {
"$concatArrays": [
"$roots",
[
{
_id: null,
count: "$sum"
}
]
]
}
}
},
{
$unwind: "$roots"
},
{
$replaceRoot: {
newRoot: "$roots"
}
}
])
Mongo Playground
I've created an aggregate query but for some reason it doesn't seem to work for custom fields created in the aggregation pipeline.
return this.repository.mongo().aggregate([
{
$match: { q1_avg: { $regex: baseQuery['value'], $options: 'i' } }, // NOT WORKING
},
{
$group: {
_id: '$product_sku',
id: { $first: "$_id" },
product_name: { $first: '$product_name' },
product_category: { $first: '$product_category' },
product_sku: { $first: '$product_sku' },
q1_cnt: { $sum: 1 },
q1_votes: { $push: "$final_rating" }
},
},
{
$facet: {
pagination: [ { $count: 'total' } ],
data: [
{
$project: {
_id: 1,
id: 1,
product_name: 1,
product_category: 1,
product_sku: 1,
q1_cnt: 1,
q1_votes: {
$filter: {
input: '$q1_votes',
as: 'item',
cond: { $ne: ['$$item', null] }
}
},
},
},
{
$set: {
q1_avg: { $round: [ { $avg: '$q1_votes' }, 2 ] },
}
},
{ $unset: ['q1_votes'] },
{ $skip: skip },
{ $limit: limit },
{ $sort: sortList }
]
}
},
{ $unwind : "$pagination" },
]).next();
q1_avg value is an integer and as far as I know, regex only works with strings. Could that be the reason
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
}
]
}
]
I would like to count the status and group them by country.
Data:
[
{ id: 100, status: 'ordered', country: 'US', items: [] },
{ id: 101, status: 'ordered', country: 'UK', items: [] },
{ id: 102, status: 'shipped', country: 'UK', items: [] },
]
Desired aggregation outcome:
[
{ _id: 'US', status: { ordered: 1} },
{ _id: 'UK', status: { ordered: 1, shipped: 1 } }
]
I can $count and $group, but I am not sure how to put this together. Any hint is appreciated.
Thanks,
bluepuama
$group by country and status, and count total
$group by only country and construct array of status and count in key-value format
$set to update status field to object using $arrayToObject
db.collection.aggregate([
{
$group: {
_id: { country: "$country", status: "$status" },
count: { $sum: 1 }
}
},
{
$group: {
_id: "$_id.country",
status: { $push: { k: "$_id.status", v: "$count" } }
}
},
{ $set: { status: { $arrayToObject: "$status" } } }
])
Playground
You can do it with a single $group stage like so:
db.collection.aggregate([
{
$group: {
_id: "$country",
"shipped": {
$sum: {
$cond: [
{
$eq: [
"$status",
"ordered"
]
},
0,
1
]
}
},
"ordered": {
$sum: {
$cond: [
{
$eq: [
"$status",
"shipped"
]
},
0,
1
]
}
}
}
},
{
$project: {
_id: 1,
status: {
shipped: "$shipped",
ordered: "$ordered"
}
}
}
])
Mongo Playground
I have a collection with documents similar to the following format:
{
departure:{name: "abe"},
arrival:{name: "tom"}
},
{
departure:{name: "bob"},
arrival:{name: "abe"}
}
And to get output like so:
{
name: "abe",
departureCount: 1,
arrivalCount: 1
},
{
name: "bob",
departureCount: 1,
arrivalCount: 0
},
{
name: "tom",
departureCount: 0,
arrivalCount: 1
}
I'm able to get the counts individually by doing a query for the specific data like so:
db.sched.aggregate([
{
"$group":{
_id: "$departure.name",
departureCount: {$sum: 1}
}
}
])
But I haven't figured out how to merge the arrival and departure name into one document along with counts for both. Any suggestions on how to accomplish this?
You should use a $map to split your doc into 2, then $unwind and $group..
[
{
$project: {
dep: '$departure.name',
arr: '$arrival.name'
}
},
{
$project: {
f: {
$map: {
input: {
$literal: ['dep', 'arr']
},
as: 'el',
in : {
type: '$$el',
name: {
$cond: [{
$eq: ['$$el', 'dep']
}, '$dep', '$arr']
}
}
}
}
}
},
{
$unwind: '$f'
}, {
$group: {
_id: {
'name': '$f.name'
},
departureCount: {
$sum: {
$cond: [{
$eq: ['$f.type', 'dep']
}, 1, 0]
}
},
arrivalCount: {
$sum: {
$cond: [{
$eq: ['$f.type', 'arr']
}, 1, 0]
}
}
}
}, {
$project: {
_id: 0,
name: '$_id.name',
departureCount: 1,
arrivalCount: 1
}
}
]