I am trying to aggregate on my User collection and $project out the fields I need. Then I want to set let variables in $lookup to be able to use the variable to find matching documents.
I want to do it this way, because I will have many $lookups by the variables.
However I am not able to get this working correctly. What am I doing wrong with the variables?
$project: {
_id: 1,
name: 1,
goal: 1
}
},
{
$lookup: {
from: "goals",
let: { user: "$_id" },
pipeline: [
{
$match: {
"user": "$$user"
}
},
{ $project: { _id: 0, leads: 0 } },
],
as: "goal"
}
},
{
$project: {
_id: 1,
name: 1,
goal: 1
}
},
You need to use $expr to use variable name inside the $match stage.
{ $match: { $expr: { $eq: ['$user', '$$user'] }}}
Related
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 have a schema like below:
[
{
"_id": 1,
"showResult": true,
"subject": "History",
},
{
"_id": 2,
"showResult": false,
"subject": "Math",
}
]
and an object in JS like below:
result = {
"History": 22,
"Math": 18
}
I am using aggregate to process query, in between i need to find score based on subject field in the document if showResult field is true i.e to access result variable inside query as map result[$subject]
My query:
db.collection.aggregate([
{
"$project": {
_id: 1,
"score":{$cond: { if: { $eq: [ "$showResult", true ] }, then: subjectObj[$subject], else: null }}
}
}
])
can this be done in MongoDB, i want result like below:
{
_id: 1,
score: 22
}
I think query is little costly than JS code, but i am adding the query if it will help you as per your question,
$match showResult is true
$project to show required fields, $reduce to iterate loop of result after converting from object to array using $objectToArray, check condition if subject match then return matching score
let result = {
"History": 22,
"Math": 18
};
db.collection.aggregate([
{ $match: { showResult: true } },
{
$project: {
_id: 1,
score: {
$reduce: {
input: { $objectToArray: result },
initialValue: 0,
in: {
$cond: [{ $eq: ["$$this.k", "$subject"] }, "$$this.v", "$$value"]
}
}
}
}
}
])
Playground
I have the following collections in MongoDB (mongoplayground) [characters,guilds]
I want to make a $lookup, that will add rank field to the resulting document, like that:
"members_t": [
{
"_id": ObjectId("5a934e000102030405000000"),
"level": 20,
"name": "test1",
"rank": 1
},
{
"_id": ObjectId("5a934e000102030405000001"),
"level": 40,
"name": "test2",
"rank": 2
}
]
old $lookup syntax can't help me with that, but the following query with the new syntax returns me an empty array in tested field (even without $addFields stage):
{
$lookup: {
from: "characters",
let: {
members_name: "$members.name",
rank: "$members.rank"
},
pipeline: [
{
$match: {
name: "$$members_name"
}
}
],
as: "tested"
}
}
So, is there any option to add an additional field after $lookup stage or not?
(Mongo -v 4.2.3, so the problem is not related with new syntax support)
You were almost close to solving it. Since the members are an array, you need to pass it through $lookup and then conditionally join it per each character with $reduce (You can do this with $filter as well, but then we need aditional stages).
Note: Explanation why we need to use $expr inside $lookup pipeline.
Try this one:
db.guilds.aggregate([
{
$lookup: {
from: "characters",
let: {
members: "$members"
},
pipeline: [
{
$match: {
$expr: {
$in: [
"$name",
"$$members.name"
]
}
}
},
{
$addFields: {
rank: {
$reduce: {
input: "$$members",
initialValue: null,
in: {
$cond: [
{
$eq: [
"$$this.name",
"$name"
]
},
"$$this.rank",
"$$value"
]
}
}
}
}
}
],
as: "members_t"
}
}
])
MongoPlayground
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
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"}}
},
])