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
Related
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'
}
}
])
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.
I am looking for a query for a $match stage in my aggregation which do almost the same, as in this question, but..
if field (named rank in my case) doesn't exists in document, add document to results
but if field, exists, apply $operator condition (in my case it's $max) to this field, and add all documents that suits this condition to the results.
MongoPlayground with example collection.
Result should be like this:
[
{
"method": 3,
"item": 1,
"rank": 3 //because it has field named rank, and suits condition {rank: $max}
},
{
"method": 4,
"item": 1 //we need this, because document doesn't have rank field at all
},
{
"method": 5,
"item": 1 //we need this, because document doesn't have rank field at all
}
]
Things, that I have tried already:
{
$match: {
$or: [
{item: id, rank: {$exists: true, $max: "$rank"}}, //id === 1
{item: id, rank: {$exists: false}} //id === 1
]
}
}
UPD: As for now, probably I don't limit with $match stage only, $project is also relevant after default match, so I could request every document during $match stage by id no matter, have the doc rank field or not, and then, during $project stage do a "separation" by rank $exists
Try this one:
db.collection.aggregate([
{
$match: {
item: id
}
},
{
$group: {
_id: "$item", //<- Change here your searching field
max: {
$max: "$rank" //<- Change here your field to apply $max
},
data: {
$push: "$$ROOT"
}
}
},
{
$unwind: "$data"
},
{
$match: {
$expr: {
$or: [
{
$eq: [
{
$type: "$data.rank"
},
"missing"
]
},
{
$eq: [
"$data.rank",
"$max"
]
}
]
}
}
},
{
$replaceWith: "$data"
}
])
MongoPlayground
I have found an answer, separated from #Valijon's method, but it's also based on the logic above. My query is:
db.collection.aggregate([
{
$match: {
item: id
}
},
{
$project: {
method: 1,
item: 1,
rank: {
$ifNull: [
"$rank",
0
]
}
}
},
{
$group: {
_id: "$item",
data: {
$addToSet: "$$ROOT"
},
min_value: {
$min: "$rank"
},
max_value: {
$max: "$rank"
}
}
},
{
$unwind: "$data"
},
{
$match: {
$or: [
{
$expr: {
$eq: [
"$data.rank",
"$max_value"
]
}
},
{
$expr: {
$eq: [
"$data.rank",
"$min_value"
]
}
},
]
}
}
])
My query is based on $project stage which gives the empty field value 0. It also could be -1, or any value that isn't used in collection. And then I separate results.
MongoPlayground
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
}
}
])
I am new to MongoDB and I am stuck in the below scenario.
I have a collection that contains duplicate docs.
I just want to get the sum of the property in each doc excluding the duplicate docs.
My Docs looks like this:
{"_id":"5dd629461fc50b782479ea90",
"referenceId":"5dd581f10859d2737965d23a",
"sellingId":"319723fb80b1a297cf0803abad9bc60787537f14a6a37d6e47",
"account_name":"mrfsahas1234",
"vendor_name":"testaccount2",
"action_type":"purchase",
"product_name":"Bottle",
"product_quantity":10,
"transactionId":"319723fb80b1a297cf0803abad9bc60787537f14a6a37d6e47",
"uid":"2019-11-20T17:39:17.405Z",
"createdAt":"2019-11-21T08:56:56.589+00:00",
"updatedAt":"2019-11-21T08:56:56.589+00:00","__v":0
},
{
"_id":"5dd629461fc50b782479ea90",
"referenceId":"5dd581f10859d2737965d23a",
"sellingId":"320a9a2f814a45e01eb98344c9af708fa2864d81587e5914",
"account_name":"mrfsahas1234",
"vendor_name":"testaccount2",
"action_type":"purchase",
"product_name":"Bottle",
"product_quantity":50,
"transactionId":"320a9a2f814a45e01eb98344c9af708fa2864d81587e5914",
"uid":"2019-11-20T17:39:17.405Z",
},
{
"_id":"5dd629461fc50b782479ea90",
"referenceId":"5dd581f10859d2737965d23a",
"sellingId":"320a9a2f814a45e01eb98344c9af708fa2864d81587e5914",
"account_name":"mrfsahas1234",
"vendor_name":"testaccount2",
"action_type":"purchase",
"product_name":"Bottle",
"product_quantity":50,
"transactionId":"320a9a2f814a45e01eb98344c9af708fa2864d81587e5914",
"uid":"2019-11-20T17:39:17.405Z",
},
Currently, I am doing this:
MaterialsTrack.aggregate([
{
$match: {
$and: [
{product_name: product_name},
{account_name: account_name},
{action_type: 'purchase'},
{uid:uid}
]
}
},
{
$group: {_id: "$sellingId", PurchseQuantity: {$sum: "$product_quantity"}}
},
])
It returns the sum of product_quantity all the matching docs (including the duplicate docs).
Current Output:
{_id: "320a9a2f814a45e01eb98344c9af708fa2864d81587e5914", PurchseQuantity:110}
Expected Output:
{_id: "320a9a2f814a45e01eb98344c9af708fa2864d81587e5914", PurchseQuantity:60}
I want to get the sum of only unique docs. How can I achieve it?
Thanks in advance!
You need to sum inside of the $group _id field, and then use the replaceRoot to achieve the the result you wanted.
MaterialsTrack.aggregate([
{
$match: {
$and: [
{
product_name: "Bottle"
},
{
account_name: "mrfsahas1234"
},
{
action_type: "purchase"
},
{
uid: "2019-11-20T17:39:17.405Z"
}
]
}
},
{
$group: {
_id: {
sellingId: "$sellingId",
PurchaseQuantity: {
$sum: "$product_quantity"
}
}
}
},
{
$replaceRoot: {
newRoot: {
_id: "$_id.sellingId",
PurchaseQuantity: "$_id.PurchaseQuantity"
}
}
}
]);
Sample Output:
[
{
"PurchaseQuantity": 50,
"_id": "320a9a2f814a45e01eb98344c9af708fa2864d81587e5914"
}
]
Playground:
https://mongoplayground.net/p/MOneCRiSlO0
What about adding $addToSet to your aggregations pipeline
MaterialsTrack.aggregate([
{
$match: {
$and: [
{product_name: product_name},
{account_name: account_name},
{action_type: 'purchase'},
{uid:uid}
]
}
},
{
$group: {_id: "$sellingId", PurchseQuantity: {$sum: "$product_quantity"},"list" : {$addToSet : "$list"}}
},
])