$match in $lookup result - mongodb

I have next mongo code:
db.users.aggregate([
{
$match: {
$and: [
{ UserName: { $eq: 'administrator' } },
{ 'Company.CompanyName': { $eq: 'test' } }
]
}
},
{
$lookup: {
from: "companies",
localField: "CompanyID",
foreignField: "CompanyID",
as: "Company"
}
},
])
The $lookup part of the code working great. I got next result:
But if I add $match to the code, it brings nothing.
I found that the problem is in the second match: { 'Company.CompanyName': { $eq: 'test' } }, but I can not realize what is wrong with it.
Any ideas?
UPDATE:
I had also tried $unwind on the $lookup result, but no luck:
db.users.aggregate([
{
$match: {
$and: [
{ UserName: { $eq: 'administrator' } },
{ 'Company.CompanyName': { $eq: 'edt5' } }
]
}
},
{ unwind: '$Company' },
{
$lookup: {
from: 'companies',
localField: 'CompanyID',
foreignField: 'CompanyID',
as: 'Company'
}
},
])

With MongoDB 3.4, you can run an aggregation pipeline that uses the $addFields pipeline and a $filter operator to only return the Company array with elements that match the given condition. You can then wrap the $filter expression with the $arrayElemAt operator to return a single document which in essence incorporates the $unwind functionality by flattening the array.
Follow this example to understand the above concept:
db.users.aggregate([
{ "$match": { "UserName": "administrator" } },
{
"$lookup": {
"from": 'companies',
"localField": 'CompanyID',
"foreignField": 'CompanyID',
"as": 'Company'
}
},
{
"$addFields": {
"Company": {
"$arrayElemAt": [
{
"$filter": {
"input": "$Company",
"as": "comp",
"cond": {
"$eq": [ "$$comp.CompanyName", "edt5" ]
}
}
}, 0
]
}
}
}
])

Below answer is for mongoDB 3.6 or later.
Given that:
You have a collection users with a field CompanyID and a collection of companies with a field CompanyID
you want to lookup Companies on Users by matching CompanyID, where additionally:
each User must match condition: User.UserName equals administrator
each Company on User must match condition: CompanyName equals edt5
The following query will work for you:
db.users.aggregate([
{ $match: { UserName: 'administrator' } },
{
$lookup: {
from: 'companies',
as: 'Company',
let: { CompanyID: '$CompanyID' },
pipeline: [
{
$match: {
$expr: {
$and: [
{ $eq: ['$CompanyID', '$$CompanyID'] },
{ $eq: ['$CompanyName', 'edt5'] },
]
}
}
}
]
}
},
])
Explanation:
This is the way to perform left join queries with conditions more complex than simple foreign / local field equality match.
Instead of using localField and foreignField, you use:
let option where you can map local fields to variables,
pipeline option where you can specify aggregation Array.
In pipeline you can use $match filter, with $expr, where you can reuse variables defined earlier in let.
More info on $lookup
Nice tutorial

here is code for fitering array inside lookup.
const userId = req.userData.userId;
const limit = parseInt(req.params.limit);
const page = parseInt(req.params.page);
Collection.aggregate([
{ $match: {} },
{ $sort: { count: -1 } },
{ $skip: limit * page },
{ $limit: limit },
{
$lookup: {
from: Preference.collection.name,
let: { keywordId: "$_id" },
pipeline: [
{
$match: {
$expr: {
$and: [
{ $eq: ["$keyword", "$$keywordId"] },
{
$eq: ["$user", mongoose.Types.ObjectId(userId)],
},
],
},
},
},
],
as: "keywordData",
},
},
{
$project: {
_id: 0,
id: "$_id",
count: 1,
for: 1,
against: 1,
created_at: 1,
updated_at: 1,
keyword: 1,
selected: {
$cond: {
if: {
$eq: [{ $size: "$keywordData" }, 0],
},
then: false,
else: true,
},
},
},
}])

Related

Mongo DB Join on Primary/Foreign Key

I have two collections, viz: clib and mp.
The schema for clib is : {name: String, type: Number} and that for mp is: {clibId: String}.
Sample Document for clib:
{_id: ObjectId("6178008397be0747443a2a92"), name: "c1", type: 1}
{_id: ObjectId("6178008397be0747443a2a91"), name: "c2", type: 0}
Sample Document for mp:
{clibId: "6178008397be0747443a2a92"}
{clibId:"6178008397be0747443a2a91"}
While Querying mp, I want those clibId's that have type = 0 in clib collection.
Any ideas how this can be achieved?
One approach that I can think of was to use $lookUp, but that doesnt seem to be working. Also, I m not sure if this is anti-pattern for mongodb, another approach is to copy the type from clib to mp while saving mp document.
If I've understood correctly you can use a pipeline like this:
This query get the values from clib where its _id is the same as clibId and also has type = 0. Also I've added a $match stage to not output values where there is not any coincidence.
db.mp.aggregate([
{
"$lookup": {
"from": "clib",
"let": {
"id": "$clibId"
},
"pipeline": [
{
"$match": {
"$expr": {
"$and": [
{
"$eq": [
{
"$toObjectId": "$$id"
},
"$_id"
]
},
{
"$eq": [
"$type",
0
]
}
]
}
}
}
],
"as": "result"
}
},
{
"$match": {
"result": {
"$ne": []
}
}
}
])
Example here
db.mp.aggregate([
{
$lookup: {
from: "clib",
let: {
clibId: "$clibId"
},
pipeline: [
{
$match: {
$expr: {
$and: [
{
$eq: [ "$_id", "$$clibId" ],
}
]
}
}
},
{
$project: { type: 1, _id: 0 }
}
],
as: "clib"
}
},
{
"$unwind": "$clib"
},
{
"$match": {
"clib.type": 0
}
}
])
Test Here

MongoDb return records only if $lookup cond is occur

I have a class model which has field ref.
I'm trying to fetch only records that match the condition in lookup.
so what i did:
{
$lookup: {
from: 'fields',
localField: "field",
foreignField: "_id",
as: 'FieldCollege',
},
},
{
$addFields: {
"FieldCollege": {
$arrayElemAt: [
{
$filter: {
input: "$FieldCollege",
as: "field",
cond: {
$eq: ["$$field.level", req.query.level]
}
}
}, 0
]
}
}
},
The above code works fine and returning the FieldCollege if the cond is matched.
but the thing is, i wanted to return the class records only if the FieldCollege is not empty.
I'm totally new to mongodb. so i tried something like this:
{
$match: {
'FieldCollege': { $exists: true, $ne: [] }
}
},
Obv this didn't work.
does mongodb support something like this or am i complicating things?
EDIT:
the result from the above code:
"Classes": [
{
"_id": "613245664c6ea614e001fcef",
"name": "test",
"language": "en",
"year_cost": "3232323",
"FieldCollege":[] // with $unwind
}
],
expected Result:
"Classes": [
// FieldCollege is empty
],
I think the good option is to use lookup with pipeline, and see the final version of your query,
$lookup with fields collection and match your both conditions
$limit to result one document
$match FieldCollege is not empty []
$addElemAt to get first element from result FieldCollege
[
{
$lookup: {
from: "fields",
let: { field: "$field" },
pipeline: [
{
$match: {
$and: [
{ $expr: { $eq: ["$$field", "$_id"] } },
{ level: req.query.level }
]
}
},
{ $limit: 1 }
],
as: "FieldCollege"
}
},
{ $match: { FieldCollege: { $ne: [] } } },
{
$addFields: {
FieldCollege: { $arrayElemAt: ["$FieldCollege", 0] }
}
}
]

how to reduce unnecessary unwind stages from aggregation pipeline

Like if i'm applying many lookup stages in aggregation pipeline and each lookup is followed by an unwind(just to covert into object) first question does it affect query performance? and if yes how to do that in optimised manner
Note: all lookup's will return only one object
For Ex:
xyz.aggregate([
{ $lookup:{ ----}} //first lookup
{$unwind :{----}} //first unwind
{ $lookup:{ ----}} //second lookup
{$unwind :{----}} //second unwind
{ $lookup:{ ----}} //third lookup
{$unwind :{----}} //third unwind
{ $lookup:{ ----}} //fourth lookup
{$unwind :{----}} //fourth unwind
])
In reference to comments, here is advanced $lookup:
$lookup: {
from: 'accounts',
let: { "localAccountField": "$account" },
pipeline: [
{
$match: {
$expr: {
$eq: ["$_id", "$$localAccountField"]
}
}
},
{
$project: {
_id: 1,
user: 1
}
},
{
$lookup: {
from: 'users',
let: { 'localUserField': "$user" },
pipeline: [
{
$match: {
$expr: {
$eq: ["$_id", "$$localUserField"]
}
}
},
{
$project: {
_id: 1,
username: "$uid",
phone:"$phoneNumber",
email: "$email.add",
name: {
$concat: [
"$profile.name.first",
' ',
"$profile.name.last"
]
},
}
}
],
as: "users"
}
},
{
$lookup: {
from: 'documents',
let: { 'localDocumentField': "$user" },
pipeline: [
{
$match: {
$expr: {
$eq: ["$user", "$$localDocumentField"]
},
status:"verified",
"properties.expirydate": { $exists: true, $ne: "" },
name: "idcard"
}
},
{
$project: {
_id: 0,
cnic: "$properties.number"
}
}
],
as: "documents"
}
}
],
as: 'account'
}

Getting subdocuments using $lookup

I want to get the subdocuments from another collection using $lookup but it doesn't work. Currently brain dead...
I have a collection for Transactions
example transaction
{
type: 'PURCHASE', // but it can be something else also eg ORDER
reference: '11', // String
amount: 50,
date: 2018-07-18T10:00:00.000Z
}
I have a collection for Purchases
{
code: 11 // Integer
name: 'Product X',
amount: 50
}
My aggregation is the following
Purchase.aggregate([
{
$lookup:
{
from: "transactions",
let: { code: '$code' },
pipeline: [
{
},
{
$match: { $expr:
{ $and:
[
{ $eq: [ "$reference", "$$code" ] },
{ $eq: [ "$type", "PURCHASE" ] }
]
}
}
}
],
as: "transactions",
}
}
]);
The result is an empty tarnsactions array...
You can try below aggregation in mongodb 3.6. Just change code type from integer to string using $toLower aggregation or can use $toString in mongodb 4.0
Purchase.aggregate([
{ "$lookup": {
"from": "transactions",
"let": { "code": { "$toLower": "$code" } },
"pipeline": [
{ "$match": {
"$expr": { "$eq": [ "$reference", "$$code" ] },
"type": "PURCHASE"
}}
],
"as": "transactions"
}}
])

$lookup when foreignField is in nested array

I have two collections :
Student
{
_id: ObjectId("657..."),
name:'abc'
},
{
_id: ObjectId("593..."),
name:'xyz'
}
Library
{
_id: ObjectId("987..."),
book_name:'book1',
issued_to: [
{
student: ObjectId("657...")
},
{
student: ObjectId("658...")
}
]
},
{
_id: ObjectId("898..."),
book_name:'book2',
issued_to: [
{
student: ObjectId("593...")
},
{
student: ObjectId("594...")
}
]
}
I want to make a Join to Student collection that exists in issued_to array of object field in Library collection.
I would like to make a query to student collection to get the student data as well as in library collection, that will check in issued_to array if the student exists or not if exists then get the library document otherwise not.
I have tried $lookup of mongo 3.6 but I didn`t succeed.
db.student.aggregate([{$match:{_id: ObjectId("593...")}}, $lookup: {from: 'library', let: {stu_id:'$_id'}, pipeline:[$match:{$expr: {$and:[{"$hotlist.clientEngagement": "$$stu_id"]}}]}])
But it thorws error please help me in regard of this. I also looked at other questions asked at stackoverflow like. question on stackoverflow,
question2 on stackoverflow but these are comapring simple fields not array of objects. please help me
I am not sure I understand your question entirely but this should help you:
db.student.aggregate([{
$match: { _id: ObjectId("657...") }
}, {
$lookup: {
from: 'library',
localField: '_id' ,
foreignField: 'issued_to.student',
as: 'result'
}
}])
If you want to only get the all book_names for each student you can do this:
db.student.aggregate([{
$match: { _id: ObjectId("657657657657657657657657") }
}, {
$lookup: {
from: 'library',
let: { 'stu_id': '$_id' },
pipeline: [{
$unwind: '$issued_to' // $expr cannot digest arrays so we need to unwind which hurts performance...
}, {
$match: { $expr: { $eq: [ '$issued_to.student', '$$stu_id' ] } }
}, {
$project: { _id: 0, "book_name": 1 } // only include the book_name field
}],
as: 'result'
}
}])
This might not be a very good answer, but if you can change your schema of Library to:
{
_id: ObjectId("987..."),
book_name:'book1'
issued_to: [
ObjectId("657..."),
ObjectId("658...")
]
},
{
_id: "ObjectId("898...")",
book_name:'book2'
issued_to: [
ObjectId("593...")
ObjectId("594...")
]
}
Then when you do:
{
$lookup: {
from: 'student',
localField: 'issued_to',
foreignField: '_id',
as: 'issued_to_students', // this creates a new field without overwriting your original 'issued_to'
}
},
You should get, based on your example above:
{
_id: ObjectId("987..."),
book_name:'book1'
issued_to_students: [
{ _id: ObjectId("657..."), name: 'abc', ... },
{ _id: ObjectId("658..."), name: <name of this _id>, ... }
]
},
{
_id: "ObjectId("898...")",
book_name:'book2'
issued_to: [
{ _id: ObjectId("593..."), name: 'xyz', ... },
{ _id: ObjectId("594..."), name: <name of this _id>, ... }
]
}
You need to $unwind the issued_to from library collection to match the issued_to.student with _id
db.student.aggregate([
{ "$match": { "_id": mongoose.Types.ObjectId(id) } },
{ "$lookup": {
"from": Library.collection.name,
"let": { "studentId": "$_id" },
"pipeline": [
{ "$unwind": "$issued_to" },
{ "$match": { "$expr": { "$eq": [ "$issued_to.student", "$$studentId" ] } } }
],
"as": "issued_to"
}}
])