So as you all know, find() returns an array of results, with findOne() returning just a simply object.
With Angular, this makes a huge difference. Instead of going {{myresult[0].name}}, I can simply just write {{myresult.name}}.
I have found that the $lookup method in the aggregate pipeline returns an array of results instead of just a single object.
For example, I have two colletions:
users collection:
[{
"firstName": "John",
"lastName": "Smith",
"country": 123
}, {
"firstName": "Luke",
"lastName": "Jones",
"country": 321
}]
countries collection:
[{
"name": "Australia",
"code": "AU",
"_id": 123
}, {
"name": "New Zealand",
"code": "NZ",
"_id": 321
}]
My aggregate $lookup:
db.users.aggregate([{
$project: {
"fullName": {
$concat: ["$firstName", " ", "$lastName"]
},
"country": "$country"
}
}, {
$lookup: {
from: "countries",
localField: "country",
foreignField: "_id",
as: "country"
}
}])
The results from the query:
[{
"fullName": "John Smith",
"country": [{
"name": "Australia",
"code": "AU",
"_id": 123
}]
}, {
"fullName": "Luke Jones",
"country": [{
"name": "New Zealand",
"code": "NZ",
"_id": 321
}]
}]
As you can see by the above results, each country is an array instead of a single object like "country": {....}.
How can I have my $lookup return a single object instead of an array since it will only ever match a single document?
You're almost there, you need to add another $project stage to your pipeline and use the $arrayElemAt to return the single element in the array.
db.users.aggregate(
[
{ "$project": {
"fullName": {
"$concat": [ "$firstName", " ", "$lastName"]
},
"country": "$country"
}},
{ "$lookup": {
"from": "countries",
"localField": "country",
"foreignField": "_id",
"as": "countryInfo"
}},
{ "$project": {
"fullName": 1,
"country": 1,
"countryInfo": { "$arrayElemAt": [ "$countryInfo", 0 ] }
}}
]
)
You can also use "preserveNullAndEmptyArrays"
Like so:
db.users.aggregate(
[
{ "$project": {
"fullName": {
"$concat": [ "$firstName", " ", "$lastName"]
},
"country": "$country"
}},
{ "$lookup": {
"from": "countries",
"localField": "country",
"foreignField": "_id",
"as": "countryInfo"
}},
{"$unwind": {
"path": "$countryInfo",
"preserveNullAndEmptyArrays": true
}
},
]
)
db.users.aggregate([
{
$lookup: {
from: 'countries',
localField: 'country',
foreignField: '_id',
as: 'country'
}
},
{
$unwind: '$country'
}
]).pretty()
You can use this mongo query for getting the country object
When you don't want to repeat all fields in project, just overwrite the field in question with $addFields:
db.users.aggregate([
{ "$project": {
"fullName": {
"$concat": [ "$firstName", " ", "$lastName"]
},
"country": "$country"
}},
{ "$lookup": {
"from": "countries",
"localField": "country",
"foreignField": "_id",
"as": "countryInfo"
}},
{ "$addFields": {
"countryInfo": {
"$arrayElemAt": [ "$countryInfo", 0 ]
}
}}
])
I think the cleanest approach would be to add another step to the pipeline:
...,
{
$addFields : {
$country: { $first: '$country' }
}
}
Related
I am having a collection which contains the data like the following and want to have the desirable output which I have mentioned below.
db={
collectionA: [
{
"id": ObjectId("63b7c24c06ebe7a8fd11777b"),
"uniqueRefId": "UUID-2023-0001",
"products": [
{
"productIndex": 1,
"productCategory": ObjectId("63b7c24c06ebe7a8fd11777b"),
"productOwners": [
ObjectId("63b7c2fd06ebe7a8fd117781")
]
},
{
"productIndex": 2,
"productCategory": ObjectId("63b7c24c06ebe7a8fd11777b"),
"productOwners": [
ObjectId("63b7c2fd06ebe7a8fd117781"),
ObjectId("63b7c12706ebe7a8fd117778")
]
},
{
"productIndex": 3,
"productCategory": "",
"productOwners": ""
}
]
}
],
collectionB: [
{
"_id": ObjectId("63b7c2fd06ebe7a8fd117781"),
"fullname": "Jim Corbett",
"email": "jim.corbett#pp.com"
},
{
"_id": ObjectId("63b7c12706ebe7a8fd117778"),
"fullname": "Carry Minatti",
"email": "carry.minatty#pp.com"
},
]
}
Desirable Output = [
{
"id": ObjectId("507f1f77bcf86cd799439011"),
"uniqueRefId": "UUID-2023-0001",
"products": [
{
"productIndex": 1,
"productCategory": ObjectId('614g2f77bff86cd755439021'),
"productOwners": [
{
"_id": ObjectId("63ac1e59c0afb8b6f2d41acd"),
"fullname": "Jim Corbett",
"email": "jim.corbett#pp.com"
}
]
},
{
"productIndex": 2,
"productCategory": ObjectId('614g2f77bff86cd755439021'),
"productOwners": [
{
"_id": ObjectId("63ac1e59c0afb8b6f2d41acd"),
"fullname": "Jim Corbett",
"email": "jim.corbett#pp.com"
},
{
"_id": ObjectId("63ac1e59c0afb8b6f2d41ace"),
"fullname": "Carry Minatti",
"email": "carry.minatty#pp.com"
}
]
},
{
"productIndex": 3,
"productCategory": "",
"productOwners": ""
}
]
}
]
In the collectionA we are having other documents as well, its not just one document.
Similarly for collectionB we are having other documents too.
How we can get this desirable output?
I am expecting the mongodb query for getting this solution.
I have implemented the lookup like the following
db.collectionA.aggregate([
{
"$lookup": {
"from": "collectionB",
"localField": "products.productOwners",
"foreignField": "_id",
"as": "inventory_docs"
}
}
])
You can try this:
db.collectionA.aggregate([
{
"$unwind": "$products"
},
{
"$lookup": {
"from": "collectionB",
"localField": "products.productOwners",
"foreignField": "_id",
"as": "products.productOwners"
}
},
{
"$group": {
"_id": {
id: "$id",
uniqueRefId: "$uniqueRefId"
},
"products": {
"$push": "$products"
}
}
},
{
"$project": {
id: "$_id.id",
uniqueRefId: "$_id.uniqueRefId",
products: 1,
_id: 0
}
}
])
Playground link.
In this query, we do the following:
First we unwind the products array, using $unwind.
Then we calculate productOwners, using $lookup.
Then we group the unwinded elements, using $group.
Finally we, project the desired output using $project.
I need to join the faults array
{
"_id": "99812930-37CE-456F-A9D9-837E9E3F712A",
"faultsChanged": [
{
"_id": "7C628A46-7E80-4615-8B08-10C5E9A6B1D7",
"faults": [
"BF221A71-0217-42E7-B853-53112EDA9694",
"E4A54172-7E93-49C4-840B-8E6116116979"
],
"isDeleted": false,
"partition": "indego",
"sessionUuid": "A83CE9A1-7539-493F-8BA4-6FBE25B18B57",
"source": "1",
"timestamp": {
"$date": {
"$numberLong": "1630603342700"
}
},
"unmigratedNote": null,
"uuid": "7C628A46-7E80-4615-8B08-10C5E9A6B1D7"
}
]
}
So that it gets replaced by a document from another collection OOFaultEntry.
New to the aggregation pipeline, I have tried
{$lookup:{
from: "OOFaultEntry",
localField: 'faultsChanged.faults',
foreignField: "_id",
let:{faults:"$faultsChanged.faults"},
pipeline:[],
as:"faults"
}}
but this just created a key on the result and was not embedded inside of each respective faultChanged object
expected result
OOFaultEntry would be JOINED on _id . So ,it should look something like
{
"_id": "99812930-37CE-456F-A9D9-837E9E3F712A",
"faultsChanged": [
{
"_id": "7C628A46-7E80-4615-8B08-10C5E9A6B1D7",
"faults": [
{
"_id": "BF221A71-0217-42E7-B853-53112EDA9694",
"some_key": "value"
},
{
"_id": "E4A54172-7E93-49C4-840B-8E6116116979",
"some_key": "value"
}
],
"isDeleted": false,
"partition": "indego",
"sessionUuid": "A83CE9A1-7539-493F-8BA4-6FBE25B18B57",
"source": "1",
"timestamp": {
"$date": {
"$numberLong": "1630603342700"
}
},
"unmigratedNote": null,
"uuid": "7C628A46-7E80-4615-8B08-10C5E9A6B1D7"
}
]
}
One way would be $unwind the faultsChanged array first. Perform the $lookup and regroup the results.
db.Faults.aggregate([
{
"$unwind": "$faultsChanged"
},
{
"$lookup": {
"from": "00FaultEntry",
"localField": "faultsChanged.faults",
"foreignField": "_id",
"as": "faultsChanged.faults"
}
},
{
"$group": {
"_id": "$_id",
"faultsChanged": {
$push: "$faultsChanged"
}
}
}
])
Mongo Playground
I have a problem with how to lookup nested array, for example i have 4 collections.
User Collection
"user": [
{
"_id": "1234",
"name": "Tony",
"language": [
{
"_id": "111",
"language_id": "919",
"level": "Expert"
},
{
"_id": "111",
"language_id": "920",
"level": "Basic"
}
]
}
]
Language Collection
"language": [
{
"_id": "919",
"name": "English"
},
{
"_id": "920",
"name": "Chinese"
}
]
Job
"job": [
{
"_id": "10",
"title": "Programmer",
"location": "New York"
}
],
CvSubmit Collection
"cvsubmit": [
{
"_id": "11",
"id_user": "1234",
"id_job": "11"
}
]
And my query aggregation is:
db.cvsubmit.aggregate([
{
$lookup: {
from: "user",
localField: "id_user",
foreignField: "_id",
as: "id_user"
}
},
{
$lookup: {
from: "language",
localField: "id_user.language.language_id",
foreignField: "_id",
as: "id_user.language.language_id"
}
},
])
But the result is:
[
{
"_id": "11",
"id_job": "11",
"id_user": {
"language": {
"language_id": [
{
"_id": "919",
"name": "English"
},
{
"_id": "920",
"name": "Chinese"
}
]
}
}
}
]
I want the result like this, also showing all user data detail like name:
[
{
"_id": "11",
"id_job": "11",
"id_user": {
"_id": "1234",
"name": "Tony"
"language": [
{
"_id": "919",
"name": "English",
"Level": "Expert"
},
{
"_id": "920",
"name": "Chinese",
"level": "Basic"
}
]
}
}
]
Mongo Playground link https://mongoplayground.net/p/i0yCucjruey
Thanks before.
$lookup with user collection
$unwind deconstruct id_user array
$lookup with language collection and return in languages field
$map to iterate look of id_user.language array
$reduce to iterate loop of languages array returned from collection, check condition if language_id match then return name
db.cvsubmit.aggregate([
{
$lookup: {
from: "user",
localField: "id_user",
foreignField: "_id",
as: "id_user"
}
},
{ $unwind: "$id_user" },
{
$lookup: {
from: "language",
localField: "id_user.language.language_id",
foreignField: "_id",
as: "languages"
}
},
{
$addFields: {
languages: "$$REMOVE",
"id_user.language": {
$map: {
input: "$id_user.language",
as: "l",
in: {
_id: "$$l._id",
level: "$$l.level",
name: {
$reduce: {
input: "$languages",
initialValue: "",
in: {
$cond: [
{ $eq: ["$$this._id", "$$l.language_id"] },
"$$this.name",
"$$value"
]
}
}
}
}
}
}
}
}
])
Playground
You database structure is not accurate as per NoSQL, there should be max 2 collections, loot of join using $lookup and $unwind will cause performance issues.
I'm using Python with pymongo to query from the database.
I have 3 different collections:
1st:
# Projects collection
{
"_id": "A",
},
{
"_id": "B",
},
{
"_id": "C"
},
..
2nd:
# Episodes collection
{
"_id": "A/Episode01",
"project": "A",
"name": "Episode01"
},
{
"_id": "A/Episode02",
"project": "A",
"name": "Episode02"
},
{
"_id": "B/Episode01",
"project": "B",
"name": "Episode01"
},
..
3rd:
# Sequences collection
{
"_id": "A/Episode01/Sequence01",
"project": "A",
"episode": "Episode01",
"name": "Sequence01"
},
{
"_id": "A/Episode02/Sequence02",
"project": "A",
"episode": "Episode02",
"name": "Sequence02"
},
{
"_id": "B/Episode01/Sequence01",
"project": "B",
"episode": "Episode01",
"name": "Sequence01"
},
..
I want to use aggregate to query project A and get all of its corresponding episodes and sequences like this:
{
"_id": "A",
"episodes":
[
{
"_id": "A/Episode01",
"project": "A",
"name": "Episode01",
"sequences":
[
{
"_id": "A/Episode01/Sequence01",
"project": "A",
"episode": "Episode01",
"name": "Sequence01"
},
]
},
{
"_id": "A/Episode02",
"project": "A",
"name": "Episode02",
"sequences":
[
{
"_id": "A/Episode02/Sequence02",
"project": "A",
"episode": "Episode02",
"name": "Sequence02"
},
]
},
]
}
I can get as far as getting the proper episodes, but I'm not sure how to add an embed field for any matching sequences. Is it possible to do this all in a single pipeline query?
Right now my query is looking like this:
[
{"$match": {
"_id": "A"}
},
{"$lookup": {
"from": "episodes",
"localField": "_id",
"foreignField": "project",
"as": "episodes"}
},
{"$group": {
"_id": {
"_id": "$_id",
"episodes": "$episodes"}
}}
]
You can do like following
use $match to match the document
use uncorrelated queries to join two collection. But normal joining also possible as you have written. This is easier when we get some complex situations.
Mongo script is given below
[
{
"$match": {
"_id": "A"
}
},
{
$lookup: {
from: "Episodes",
let: {
id: "$_id"
},
pipeline: [
{
$match: {
$expr: {
$eq: [
"$project",
"$$id"
]
}
}
},
{
$lookup: {
from: "Sequences",
let: {
epi: "$name"
},
pipeline: [
{
$match: {
$expr: {
$eq: [
"$episode",
"$$epi"
]
}
}
}
],
as: "sequences"
}
}
],
as: "episodes"
}
}
]
Working Mongo playground
Update 01
Using standard lookup
[
{
"$match": {
"_id": "A"
}
},
{
"$lookup": {
"from": "Episodes",
"localField": "_id",
"foreignField": "project",
"as": "episodes"
}
},
{
$unwind: "$episodes"
},
{
"$lookup": {
"from": "Sequences",
"localField": "episodes.name",
"foreignField": "episode",
"as": "episodes.sequences"
}
},
{
$group: {
_id: "$episodes._id",
episodes: {
$addToSet: "$episodes"
}
}
}
]
Working Mongo playground
I am using aggregate to group and populate the result like below:
{
"$group": {
"_id": "$userId",
"projectId": { "$push": "$projectId" }
}
},
{
"$lookup": {
"from": "users",
"localField": "_id",
"foreignField": "_id",
"as": "user"
}
},
{ $unwind:"$user" },
{
"$lookup": {
"from": "projects",
"localField": "projectId",
"foreignField": "_id",
"as": "projects"
}
}
But i want to populate specific fields from that result For this I tried
$project, But it combining projectId into one array and projectName into another array.Below is my result json:
[
{
"_id": "5c0a29e597e71a0d28b910aa",
"projectId": [
"5c0a2a8897e71a0d28b910ac",
"5c0a4083753a321c6c4ee024"
],
"user": {
"_id": "5c0a29e597e71a0d28b910aa",
"firstName": "Amit"
"lastName": "kumar",
"type": "developer",
"status": "active"
},
"projects": [
{
"_id": "5c0a2a8897e71a0d28b910ac",
"skypeId": "",
"projectName": "LN-PM",
"status": "ongoing",
"assignId": "5c0a2a0a97e71a0d28b910ab"
},
{
"_id": "5c0a4083753a321c6c4ee024",
"skypeId": "",
"status": "pending",
"assignId": "5c0a2a0a97e71a0d28b910ab"
}
]
}
]
Now i want to get the only "firstName and _id" field from user field and "projectName and _id" field from the projects field
You can use below aggregation with mongodb 3.6 and above
With the newer $lookup syntax you can use $projection inside the $lookup pipeline
db.collection.aggregate([
{ "$group": {
"_id": "$userId",
"projectId": { "$push": "$projectId" }
}},
{ "$lookup": {
"from": "users",
"let": { "userId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$_id", "$$userId" ] }}},
{ "$project": { "firstName": 1 }}
],
"as": "user"
}},
{ "$unwind": "$user" },
{ "$lookup": {
"from": "projects",
"let": { "projectId": "$projectId" },
"pipeline": [
{ "$match": { "$expr": { "$in": [ "$_id", "$$projectId" ] }}},
{ "$project": { "projectName": 1 }}
],
"as": "projects"
}}
])