MongoDB/Mongoose : CastError in updateMany $inc - javascript

My MongoDB schema (simplified):
user: ObjectID
calories: Number
meals:[{
calories: Number
name:String
}]
And I have a updateMany query:
await Meals.updateMany(
{ user: user, 'meals.name': extraMealName },
{ $inc: { calories: 'meals.$.calories' } },
{multi : true},
function(error, result) {
console.log(error);
}
);
The query throws me this error:
CastError: Cast to Number failed for value "meals.$.calories" at path "calories"
I have tried changing the query for the last hour, but nothing worked... I also browsed stackoverflow, but found nothing I could work with
Does someone have an idea how to fix this?

Using pipelined update,
$reduce, go through the meals array and add up the calories where name=extraMealName
$subtract from calories, the sum from previous step
mongoplayground
db.Meals.update({
user: "user", "meals.name": "extraMealName"
},
[
{
$set: {
calories: {
$subtract: [
"$calories",
{
$reduce: {
input: "$meals",
initialValue: 0,
in: {
$add: [
"$$value",
{
$cond: [
{$eq: ["$$this.name", "extraMealName"]},
"$$this.calories",
0
]
}
]
}
}
}
]
}
}
}
]);
Updated for multiple fields.
db.collection.update({
user: "user", "meals.name": "extraMealName"
},
[
{
$addFields: {
reducedValues: {
$reduce: {
input: "$meals",
initialValue: {
calories: 0, fat: 0
},
in: {
calories: {
$add: [
"$$value.calories",
{
$cond: [
{$eq: ["$$this.name", "extraMealName"]},
"$$this.calories",
0
]
}
]
},
fat: {
$add: [
"$$value.fat",
{
$cond: [
{$eq: ["$$this.name", "extraMealName"]},
"$$this.fat",
0
]
}
]
}
}
}
}
}
},
{
$set: {
"calories": {
$subtract: ["$calories", "$reducedValues.calories"]
},
"fat": {
$subtract: ["$fat", "$reducedValues.fat"]
},
}
}
]);
Playground

the $inc has a syntax error, $inc expects a number not string so try some like this.
await Meals.updateMany(
{ user: user, 'meals.name': extraMealName },
{ $inc: { calories: { $sum: '$meals.$.calories' } } },
{ multi: true },
function(error, result) {
console.log(error);
}
);

Related

MongoDB - Generating dynamic $or using pipeline variable?

hoping someone can help as I am truly stuck!
I have this query
SwapModel.aggregate([
{
$match: {
organisationId: mongoose.Types.ObjectId(organisationId),
matchId: null,
matchStatus: 0,
offers: {
$elemMatch: {
from: { $lte: new Date(from) },
to: { $gte: new Date(to) },
locations: { $elemMatch: { $eq: location } },
types: { $elemMatch: { $eq: type } },
},
},
//problem is HERE
$or: {
$map: {
input: "$offers",
as: "offer",
in: {
from: { $gte: new Date("$$offer.from") },
to: { $lte: new Date("$$offer.to") },
location: { $in: "$$offer.locations" },
type: { $in: "$$offer.types" },
},
},
},
},
},
{ ...swapUserLookup },
{ $unwind: "$matchedUser" },
{ $sort: { from: 1, to: 1 } },
]);
I'm trying to use the results of the $match document to generate an array for $or. My data looks like this:
[{
_id: ObjectId("id1"),
from: ISODate("2023-01-21T06:30:00.000Z"),
to: ISODate("2023-01-21T18:30:00.000Z"),
matchStatus: 0,
matchId: null,
userId: ObjectId("ddbb8f3c59cf13467cbd6a532"),
organisationId: ObjectId("246afaf417be1cfdcf55792be"),
location: "Chertsey",
type: "DCA",
offers: [{
from: ISODate("2023-01-23T05:00:00.000Z"),
to: ISODate("2023-01-24T07:00:00.000Z"),
locations: ["Chertsey", "Walton"],
types: ["DCA", "SRV"],
}]
}, {
_id: ObjectId("id2"),
from: ISODate("2023-01-23T06:30:00.000Z"),
to: ISODate("2023-01-23T18:30:00.000Z"),
matchStatus: 0,
matchId: null,
userId: ObjectId("d6f10351dd8cf3462e3867f56"),
organisationId: ObjectId("246afaf417be1cfdcf55792be"),
location: "Chertsey",
type: "DCA",
offers: [{
from: ISODate("2023-01-21T05:00:00.000Z"),
to: ISODate("2023-01-21T07:00:00.000Z"),
locations: ["Chertsey", "Walton"],
types: ["DCA", "SRV"],
}]
}]
I want the $or to match all documents that have the corresponding from/to/location/type as the current document - the idea is two shifts that could be swapped
If the offers are known (passed as an array to the function calling aggregate), I can do this with:
$or: offers.map((x) => ({
from: { $gte: new Date(x.from) },
to: { $lte: new Date(x.to) },
location: { $in: x.locations },
type: { $in: x.types },
}))
BUT I want to be able to do this in an aggregation pipeline when the offers will only be known from the current document, $offers
Is this possible? I've tried $in, $map, $lookup, $filter, $getField but can't get it right and can't get anything from Google as it thinks I want $in (which is the opposite of what I need).
I'm pretty new to MongoDB and am probably approaching this completely wrong but I'd really appreciate any help!
Edit: expected output is simply an array of matching documents, so passing document id1 to the function would return an array with id2 in, because each document is compatible with the other
///expected output, from and to are between an offer in id1's from and to, similarly types/locations are compatible
{
_id: ObjectId("id2"),
from: ISODate("2023-01-23T06:30:00.000Z"),
to: ISODate("2023-01-23T18:30:00.000Z"),
matchStatus: 0,
matchId: null,
userId: ObjectId("d6f10351dd8cf3462e3867f56"),
organisationId: ObjectId("246afaf417be1cfdcf55792be"),
location: "Chertsey",
type: "DCA",
offers: [{
from: ISODate("2023-01-21T05:00:00.000Z"),
to: ISODate("2023-01-21T07:00:00.000Z"),
locations: ["Chertsey", "Walton"],
types: ["DCA", "SRV"],
}]
You can perform self-lookup with your criteria set in the sub-pipeline.
db.collection.aggregate([
{
$match: {
organisationId: "organisationId1",
matchId: null,
matchStatus: 0
}
},
{
$unwind: "$offers"
},
{
"$lookup": {
"from": "collection",
"let": {
offersFrom: "$offers.from",
offersTo: "$offers.to",
offersLocation: "$offers.locations",
offersType: "$offers.types"
},
"pipeline": [
{
$match: {
$expr: {
$and: [
{
$gte: [
"$from",
"$$offersFrom"
]
},
{
$lte: [
"$to",
"$$offersTo"
]
},
{
"$in": [
"$location",
"$$offersLocation"
]
},
{
"$in": [
"$type",
"$$offersType"
]
},
]
}
}
}
],
"as": "selfLookup"
}
},
{
"$unwind": "$selfLookup"
},
{
"$replaceRoot": {
"newRoot": "$selfLookup"
}
}
])
Mongo Playground

MongoDB - How to combine findOne (in array) with aggregate

I currently have a Mongo query that looks like this:
const user = await User.findOne({ userId }).lean() || []
const contributions = await Launch.aggregate([
{ $sort: { addedAt: -1 } },
{ $limit: 10 },
{
$match: {
_id: { $in: user.contributions }
}
},
{
$addFields: {
activity: 'contribution',
launchName: '$name',
launchId: '$_id',
date: '$addedAt',
content: '$description'
}
}
])
But instead of having two different Mongo queries (findOne and aggregate), how can I combine them into one query?
I tried this but it just errors out immediately in the lookup part:
const contributions = await Launch.aggregate([
{ $sort: { addedAt: -1 } },
{ $limit: 10 },
{
$lookup: {
from: 'user',
let: { id: $user.contributions },
pipeline: [
{ $match: { $expr: { $in: [$_id, $$user.contributions] } } }
],
localField: '_id',
foreignField: 'userId',
as: 'user'
}
},
{
$addFields: {
activity: 'contribution',
launchName: '$name',
launchId: '$_id',
date: '$addedAt',
content: '$description'
}
}
])
I've never used the pipeline option so a little confused onn how to fix this problem?
Enclose these $user.contributions, $_id with quotes in order to make the query valid.
Since you declare the id variable with the value of user.contributions. You should use the variable with $$id instead of $$user.contributions.
I don't think the localField and foreignField are needed as you are mapping/joining with pipeline.
Your aggregation query should be looked as below:
const contributions = await Launch.aggregate([
{ $sort: { addedAt: -1 } },
{ $limit: 10 },
{
$lookup: {
from: 'user',
let: { id: "$user.contributions" },
pipeline: [
{ $match: { $expr: { $in: ["$_id", "$$id"] } } }
],
as: 'user'
}
},
{
$addFields: {
activity: 'contribution',
launchName: '$name',
launchId: '$_id',
date: '$addedAt',
content: '$description'
}
}
])

Mongoose add to array of nested array if exists create otherwise

i'm trying to accomplish the following in mongoose:
Say i have the following collection
{
"_id": {
"$oid": "111"
},
"email": "xxx#mail.com",
"givenName": "xxx",
"familyName": "xxx",
"favoriteProducts": [{
"soldTo": "33040404",
"skus": ["W0541", "W2402"]
}, {
"soldTo": "1223",
"skus": ["12334"]
}]
}
i want to be able to add a sku to the favorite products array based on soldTo and _id.
When doing this there are two possible scenarios.
a. There is already an object in favoriteProducts with the given soldTo in which case the sku is simply added to the array.(for example add sku '12300' to soldTo '1223' for id '111')
b. There is no object with the given soldTo yet in which case this object need to be created with the given sku and soldTo. (for example add sku '123' to soldTo '321' for id '111')
so far i've done this but i feel like there is a way to do it in one query instead.
private async test() {
const soldTo = '1223';
const sku = '12300';
const id = '111';
const hasFavoriteForSoldTo = await userModel.exists({
_id: id,
'favoriteProducts.soldTo': soldTo,
});
if (!hasFavoriteForSoldTo) {
await userModel
.updateOne(
{
_id: id,
},
{ $addToSet: { favoriteProducts: { skus: [sku], soldTo } } },
)
.exec();
} else {
await userModel
.updateOne(
{
_id: id,
'favoriteProducts.soldTo': soldTo,
},
{ $addToSet: { 'favoriteProducts.$.skus': sku } }
)
.exec();
}
}
Use update-documents-with-aggregation-pipeline
Check out mongo play ground below. Not sure you want Output 1 or Output 2.
Output 1
db.collection.update({
_id: { "$oid": "111222333444555666777888" }
},
[
{
$set: {
favoriteProducts: {
$cond: {
if: { $in: [ "1223", "$favoriteProducts.soldTo" ] },
then: {
$map: {
input: "$favoriteProducts",
as: "f",
in: {
$cond: {
if: { $eq: [ "1223", "$$f.soldTo" ] },
then: { $mergeObjects: [ "$$f", { skus: [ "12300" ] } ] },
else: "$$f"
}
}
}
},
else: {
$concatArrays: [ "$favoriteProducts", [ { skus: [ "12300" ], soldTo: "1223" } ] ]
}
}
}
}
}
],
{
multi: true
})
mongoplayground
Output 2
db.collection.update({
_id: { "$oid": "111222333444555666777888" }
},
[
{
$set: {
favoriteProducts: {
$cond: {
if: { $in: [ "1223", "$favoriteProducts.soldTo" ] },
then: {
$map: {
input: "$favoriteProducts",
as: "f",
in: {
$cond: {
if: { $eq: [ "1223", "$$f.soldTo" ] },
then: {
$mergeObjects: [
"$$f",
{ skus: { $concatArrays: [ [ "12300" ], "$$f.skus" ] } }
]
},
else: "$$f"
}
}
}
},
else: {
$concatArrays: [ "$favoriteProducts", [ { skus: [ "12300" ], soldTo: "1223" } ] ]
}
}
}
}
}
],
{
multi: true
})
mongoplayground

MongoDB lookup and unwind

I'm trying to perform a look up which works fine and in the correct document as 'metrics'. The lookup document has an array inside of its object called 'history'. I'm trying to unwind that history and perform a facet on it, an aggregation query that I have directly on the lookup collection that works fine.
However when using it here it's not returning anything. Am I unwinding this incorrectly? should it be $metrics.history ?
{
from: 'historicprices',
localField: 'collectibleId',
foreignField: 'collectibleId',
pipeline: [
{$set: {"target-date": "$$NOW"}},
{$unwind: {path: "$history"}},
{$facet: {
"one_day": [
{ $match: { $expr: { $lte: [{$subtract: ["$target-date", "$history.date" ]}, {$multiply: [24,60,60,1000] }] } } },
{ $group: { _id: null, "first": { $first: "$history.value" }, "last": { $last: "$history.value" }, "min-price": {"$min": "$history.value"}, "max-price": {"$max": "$history.value"} } },
{ $unset: ["_id"]}
]
"one_week": [
{ $match: { $expr: { $lte: [{$subtract: ["$target-date", "$history.date" ]}, {$multiply: [7, 24, 60, 60, 1000] }] } } },
{ $group: { _id: null, "min-price": {"$min": "$history.value"}, "first": { $first: "$history.value" }, "last": { $last: "$history.value" }, "max-price": {"$max": "$history.value"} } },
{ $unset: ["_id"]}
]
}}
],
as: 'metrics',
}
Thanks
Maybe you need to add preserveNullAndEmptyArrays: true to your unwind stage. Otherwise no data will be received if one of the docs doesn't return this field.

Mongodb Group and get other fields from documents

update so Mohammad Faisal has the best solution.However it breaks when a new document is added lol! so i learned a lot from his code and modified it and it Works! =) the code is all the way in the bottom.
But here's what i said..
So i have this document
{"_id":"5ddea2e44eb407059828d740",
"projectname":"wdym",
"username":"easy",
"likes":0,
"link":["ssss"]
}
{"_id":"5ddea2e44eb407059822d740",
"projectname":"thechosenone",
"username":"easy",
"likes":30,
"link":["ssss"]
}
{"_id":"5ddea2e44eb407059828d740",
"projectname":"thanos",
"username":"wiley",
"likes":10,
"link":["ssss"]
}
and basically what i want is the document that contains the highest
likes with it's associated project name
For example the output would be
"projectname":"thechosenone",
"username":"easy",
"likes":30
}
,
{
"projectname":"thanos",
"username":"wiley",
"likes":10,
}
the code i have for this is the following
db
.collection("projects")
.aggregate([
{
$group: {
_id: { username: "$username" },
likes: { $max: "$likes" }
}
},
{
$project:{projectname:1}
}
])
$project gives me a strange output. However,
the output was correct without the $project.
But i wanted to project the projectname, the user and the highest likes. Thanks for hearing me out :)
heres the solution =)
db
.collection("projects")
.aggregate([
{
$sort: {
likes: -1
}
},
{
$group: {
_id: {
username: "$username"
},
likes: {
$max: "$likes"
},
projectname: {
$push: "$projectname"
},
link: {
$push: "$link"
}
}
},
{
$project: {
username: "$_id.username",
projectname: {
$arrayElemAt: ["$projectname", 0]
},
link: {
$arrayElemAt: ["$link", 0]
}
}
}
])
.toArray()
If you don't have to use $group this will solve your problem:
db.projects.aggregate([
{$sort:{likes:-1}},
{$limit:1}
]).pretty()
the result would be
{
"_id" : ObjectId("5ddee7f63cee7cdf247059db"),
"projectname" : "thechosenone",
"username" : "easy",
"likes" : 30,
"links" : ["ssss"]
}
Try this:-
db.collection("projects").aggregate([
{
$group: {
_id: { username: "$username" },
likes: { $max: "$likes" },
projectname: { $push : { $cond: [ { $max: "$likes" }, "$projectname", "" ]}}
}
}
,
{
$project:{
username:"$_id.username",
projectname:{"$reduce": {
"input": "$projectname",
"initialValue": { "$arrayElemAt": ["$projectname", 0] },
"in": { "$cond": [{ "$ne": ["$$this", ""] }, "$$this", "$$value"] }
}},
likes:1
}
}
])

Categories