simple collection:
[
{
_id: '123',
name: 'product1',
quantity: 10
},{
_id: '456',
name: 'product2',
quantity: 20
},{
_id: '789',
name: 'product1',
quantity: 30
},{
_id: '145',
name: 'product3',
quantity: 30
}
]
what im trying to get:
[
{
_id: 'product1',
quantity: 40
},{
_id:'product2',
quantity: 20
}
]
I want to filter by product1 and product2 and group by the 2 products with the total quantity.
what i tried:
db.CustomerOrders.aggregate([
{
"$match":{
"$or":[{"name":"product1"},{"name": "product2"}
]}},
{
"$group": {_id:"$name", quantity:{$sum:"$quantity"}}
}
}])
Code doesnt seem to work
Use $in in your $match stage.
db.collection.aggregate([
{
"$match": {
name: {
$in: [
"product1",
"product2"
]
}
}
},
{
$group: {
_id: "$name",
quantity: {
$sum: "$quantity"
}
}
}
])
Mongo Playground
Related
Considering the following document structure:
{_id: 1, name: 'joe', snapshot: null, age: 30}
{_id: 2, name: 'joe', snapshot: 'snapshot1', age: 30}
{_id: 3, name: 'joe', snapshot: 'snapshot15', age: 30}
{_id: 4, name: 'joe', snapshot: 'snapshot23', age: 30}
How would I perform a query that groups on the name field and adds an additional field that is a count of the remaining records containing subtree: 'additionalinfo'. It would look like this:
{_id: 1, name: 'joe', snapcount: 3, age: 30}
I've been able to group using aggregations but I can't quite get it like this.
My own solution:
I ultimately restructured my data to look like this instead:
{
_id: 1,
name: 'joe',
snapshots: [
{name: 'snap17', id: 1},
{name: 'snap15', id: 2},
{name: 'snap14', id: 3}
],
age: 30
}
This allows me to just check snapshots.length to solve my original problem. However; the answers in this post where very helpful and answered the original question.
Adding another aggregation query to do it: playground link: try it
db.collection.aggregate([
{
$match: {
"snapshot": {
$exists: true,
$ne: null
}
}
},
{
$group: {
_id: "$name",
snapcount: {
$sum: 1
},
age: {
"$first": "$age"
},
name: {
"$first": "$name"
}
}
},
{
"$unset": "_id"
}
])
Based on the comments, the query worked for OP:
db.collection.aggregate([
{
$match: {
"snapshot": {
$exists: true,
$ne: null
}
}
},
{
$group: {
_id: "$name",
snapcount: {
$sum: 1
},
age: {
"$first": "$age"
},
name: {
"$first": "$name"
},
id: {
"$first": "$_id"
}
}
},
{
"$unset": "_id"
}
])
Here's one way you could do it.
db.collection.aggregate([
{
"$group": {
"_id": "$name",
"name": {"$first": "$name"},
"age": {"$first": "$age"},
"snapcount": {
"$sum": {
"$cond": [
{"$eq": [{"$type": "$snapshot"}, "string"]},
1,
0
]
}
}
}
},
{"$unset": "_id"}
])
Try it on mongoplayground.net.
I have two collections where I'm trying to do an aggregation query with filter options. I have looked online but I couldn't find solution for this.
Col 1
[
{
_id: ObjectId('st_123'),
stud_num: 123,
school: ObjectId('sc_123'),
gender: 'M'
},
{
_id: ObjectId('st_234'),
stud_num: 123,
school: ObjectId('sc_234'),
gender: 'F'
},
{
_id: ObjectId('st_345'),
stud_num: 123,
school: ObjectId('sc_345'),
gender: 'M'
}
]
Col 2
[
{
_id: ObjectId('f_123'),
stud_health_id: ObjectId('st_123'),
schoolYear: ObjectId('sy123')
},
{
_id: ObjectId('f_234'),
stud_health_id: ObjectId('st_234'),
schoolYear: ObjectId('sy234')
},
{
_id: ObjectId('f_345'),
stud_health_id: ObjectId('st_890'),
schoolYear: ObjectId('sy234')
},
{
_id: ObjectId('f_456'),
stud_health_id: ObjectId('st_345'),
schoolYear: ObjectId('sy345')
}
]
I am trying to filter the records from collection 1 which doesn't have entry in collection 2 with extra params.
If I send {schoolYear: ObjectID('sy234)} then it should return the first and third document of collection 1 because for that year those two students doesn't have record.
One option is using $lookup and $match:
db.col1.aggregate([
{$lookup: {
from: "col2",
as: "col2",
let: {schoolYear: "sy234", stud_id: "$_id"},
pipeline: [
{$match: {$expr: {
$and: [
{$eq: ["$schoolYear", "$$schoolYear"]},
{$eq: ["$stud_health_id", "$$stud_id"]}
]
}
}
}
]
}
},
{$match: {"col2.0": {$exists: false}}},
{$unset: "col2"}
])
See how it works on the playground example
How to get the nested object in projection and group in mongodb aggregate query.
[
{
city: "Mumbai",
meta: {
luggage: 2,
scanLuggage: 1,
upiLuggage: 1
},
cash: 10
},
{
city: "Mumbai",
meta: {
luggage: 4,
scanLuggage: 3,
upiLuggage: 1
},
cash: 24
},
]
I want to $match the above on the basis of city, and return the sum of each luggage type.
My code is as follows but $project is not working -
City.aggregate([
{
$match: { city: 'Mumbai' }
},
{
$project: {
city: 1,
mata.luggage: 1,
meta.scanLuggage: 1,
meta.upiLuggage: 1
}
},
{
$group: {
id: city,
luggage: {$sum: '$meta.luggage'},
scanLuggage: {$sum: '$meta.scanLuggage'},
upiLuggage: {$sum: '$meta.upiLuggage'}
}
}
])
But the $project is throwing error. I want my output to look like -
{
city: 'Mumbai',
luggage: 6,
scanLuggage: 4,
upiLuggage: 2
}
You should specify nested fields in quotes when using in $project, and also for grouping key should be _id.
db.collection.aggregate([
{
$match: {
city: "Mumbai"
}
},
{
$project: {
city: 1,
"meta.luggage": 1,
"meta.scanLuggage": 1,
"meta.upiLuggage": 1
}
},
{
$group: {
_id: "$city",
luggage: {
$sum: "$meta.luggage"
},
scanLuggage: {
$sum: "$meta.scanLuggage"
},
upiLuggage: {
$sum: "$meta.upiLuggage"
}
}
}
])
This is the playground link.
Trying to figure out something simple in this aggregation. The field "totalArrests" under metadata is coming back 0. It's not able to sum this field from the previous stage for some reason. Please advise.
const agg = await KID.aggregate([
{
$group: {
_id: "$source", // group by this
title: { "$last": "$title"},
comments: { "$last": "$comments"},
body: { "$last": "$body"},
date: { "$last": "$date"},
media: { "$last": "$media"},
source: { "$last": "$source"},
count: { "$sum": 1},
arrestCount: { "$sum": "$arrested"},
rescuedCount: { "$sum": "$rescued"},
}
},
// sorting
{
$sort: {date: sort}
},
// facets for paging
{
$facet: {
metadata: [
{ $count: "total" }, // Returns a count of the number of documents at this stage
{ $addFields: {
page: page,
limit: 30,
totalArrests: {$sum: "$arrestCount"}
}},
],
kids: [ { $skip: (page-1)*30 }, { $limit: 30 } ]
}
},
]);
Here is a sample document in the collection.
[
{
_id: 5e8b922aaf5ccf5ac588398c,
counter: 4,
date: 2017-01-01T17:00:00.000Z,
name: 'Steven Tucker',
arrested: 1,
rescued: 0,
country: 'US',
state: 'NH',
comments: 'Sex trafficking of a minor',
source: 'https://www.justice.gov/opa/pr/new-hampshire-man-indicted-sex-trafficking-minor-connection-interstate-prostitution',
title: 'New ....',
body: 'Steven Tucker, 31, ....',
__v: 0,
media: {
title: 'New Hampshire Man Indicted for Sex ...',
open_graph: [Object],
twitter_card: [Object],
favicon: 'https://www.justice.gov/sites/default/files/favicon.png'
},
id: 5e8b922aaf5ccf5ac588398c,
text: 'New Hampshire Man Indicted',
utcDate: '2017-01-01T12:00'
}
]
$count will only provide you the count for number of documents and escapes all the other things.
So, You have to use one more pipeline in $facet in order to get the documents.
{ $facet: {
metadata: [
{ $group: {
_id: null,
total: { $sum: 1 },
totalArrested: { $sum: "$arrestCount" }
}},
{ $project: {
total: 1,
totalArrested: 1,
page: page,
limit: 30,
hasMore: { $gt: [{ $ceil: { $divide: ["$total", 30] }}, page] }
}}
],
kids: [{ $skip: (page-1) * 30 }, { $limit: 30 }]
}}
I have the following documents in my candidate collection.
candidates = [
{
name: "amit",
age: 21,
city: 'pune'
}
{
name: "rahul",
age: 23,
city: 'pune'
},
{
name: "arjun",
age: 21,
city: 'pune'
},
{
name: "rakesh",
age: 23,
city: 'pune'
},
{
name: "amit",
age: 22,
city: 'nashik'
}
]
I want to group by age and city fields and count the documents based on its sum independent of each other
I tried following query
candidate.aggregate([
{$group: {_id: {age: '$age', city: '$city'}, count: {$sum: -1}}}
{$sort: {count: -1}},
{$limit: 10}
])
which gives me count of combine results of age and city.
what I want instead
{
ages: [
{
age: 21,
count: 2
},
{
age: 23,
count: 2
},
{
age: 21,
count: 1
}
],
cities: [
{
city: 'pune',
count: 4
},
{
city: 'nashik',
count: 1
}
]
}
thanks for any help.
You need to use $facet stage, with a $group stage per age, and another per city.
Here's the query :
db.collection.aggregate([
{
$facet: {
byCity: [
{
$group: {
_id: {
city: "$city"
},
count: {
$sum: 1
}
}
},
{
$sort: {
count: -1
}
},
{
$limit: 10
}
],
byAge: [
{
$group: {
_id: {
age: "$age",
},
count: {
$sum: 1
}
}
},
{
$sort: {
count: -1
}
},
{
$limit: 10
}
]
}
},
])
Mongo playground