MongoDB Aggregate - Unwind, group and project - javascript

Using the collection Users, is it possible to retrieve the below unique list of organisations/owners? If this current set up isn't possible, is it possible to get the same results from two ID-linked collections with one query?
Currently, using Mongoose I can only retrieve the group of organisation names:
Current query
userModel.aggregate([
{ $unwind:'$organisations' }
, { $group: { name: '$organisations.name' } }
])
Users
{ "_id" : ObjectId("53f4a94e7c88310000000001"),
"email" : "bob#example.com",
"organisations" : [
{
"name" : "OrgOne",
"isOwner" : true
}
]
},
{ "_id" : ObjectId("53f4a94e7c88310000000002"),
"email" : "ash#something.com",
"organisations" : [
{
"name" : "OrgOne"
}
]
},
{ "_id" : ObjectId("53f4a94e7c88310000000003"),
"email" : "george#hello.com",
"organisations" : [
{
"name" : "OrgTwo",
"isOwner" : true
}
]
}
Results
{ "orgName" : "OrgOne",
"owner" : 53f4a94e7c88310000000001
},
{ "orgName" : "OrgTwo",
"owner" : 53f4a94e7c88310000000003
}
Thanks in advance, Nick


Seems like an odd use of aggregation to me, but possibly there are several "organisations" per user here, so I guess I'll continue:
userModel.aggregate(
[
{ "$match": { "organisations.isOwner": true } },
{ "$unwind": "$organisations" },
{ "$match": { "organisations.isOwner": true } },
{ "$group": {
"_id": "$organisations.name",
"owner": { "$first": "$_id" }
}}
],
function(err,result) {
}
);
If there is more than one owner and you need some precedence then you can implement a $sort before the group. Or otherwise just $project rather than group in order to get everyone.

Related

Mongo return data based on nested date params

I'm scraping and saving a bunch of data into a mongodb collection by pushing it into an array, an example of the saved data looks like this:
{
"_id" : ObjectId("616eafce1e7edf6e9b033938"),
"collectibleId" : "34e05c2c-19dd-4509-a98c-bb11cd275d34",
"__v" : NumberInt(0),
"createdAt" : ISODate("2021-10-19T11:45:16.845+0000"),
"history" : [
{
"storePrice" : 6.99,
"value" : NumberInt(27),
"date" : ISODate("2021-10-19T11:45:16.683+0000"),
"totalListings" : NumberInt(904),
"hourlyChange" : {
"market" : NumberInt(0)
}
},
{
"storePrice" : 6.99,
"value" : 27.5,
"date" : ISODate("2021-10-19T11:59:01.192+0000"),
"totalListings" : NumberInt(902),
"hourlyChange" : {
"market" : NumberInt(0)
}
},
... loads more items ...
],
"updatedAt" : ISODate("2021-10-27T18:59:01.109+0000")
}
I'm trying to now write a query for the data that can return only the recorded data within a specific timeframe. So far I've tried this:
Prices.findOne({
collectibleId: slug,
history: {
date: {
$gte: new Date("2021-10-26T00:00:00.000Z")
}
}
}).exec((err, data) => {
if (err){
return res.status(400).json({
error: errorHandler(err)
})
}
res.json(data)
})
But the result im getting is always null. I'm wondering if it's because date is nested in history and perhaps im writing that wrong ? Any advice appreciated thank you.

$match then $set
db.collection.aggregate([
{
"$match": {
collectibleId: "slug",
"history.date": {
$gte: ISODate("2021-10-26T00:00:00.000Z")
}
}
},
{
"$set": {
"history": {
"$filter": {
"input": "$history",
"as": "h",
"cond": {
$gte: [
"$$h.date",
ISODate("2021-10-26T00:00:00.000Z")
]
}
}
}
}
}
])
mongoplayground

Can i filter one collection that has _id in other collection and have result on in mongodb

I have the collection "A" like this
{
"_id" : ObjectId("5c4c1f2a5173562961468b30"),
"name" : "first"
},
{
"_id" : ObjectId("57c162f267045ec439ba2485"),
"name" : "second"
}
Like above i have multiple doc in a collection,
Now i have colection "B" like below which has _id of Collections a's doc
{
"_id" : ObjectId("57d14ad36495a197593ab7ab"),
"a_id" : ObjectId("5c4c1f2a5173562961468b30"),
"name" : "ab"
},
{
"_id" : ObjectId("57d941503dd051cc04205e1e"),
"a_id" : ObjectId("5c4c1f2a5173562961468b30"),
"name" : "cd "
}
Now i need a query that will give me result collection "A" based on how many documents are associated with "B"
If "A" has 2 documents in "B" I need those 2 "B" documents

This simple aggregation make your result
db.A.aggregate([
{
"$lookup": {
"from": "B",
"localField": "_id",
"foreignField": "a_id",
"as": "docuentInB"
}
},
{
$match: {
$expr: { $gte: [{ $size: "$docuentInB" }, 2 ] }
}
},
{
$project: {
docuentInB: 0
}
}
])

Simplify forEach statement to update a mongoDB document with nested objects and arrays

I'd like to update the value of the key shouldSendAlert in the following document:
{
"_id" : ObjectId("5c61c4db46d18e1092c5b024"),
"service" : "SRVPVD",
"menu" : [
{
"sub" : [
{
"options" : [
{
"item" : [
{
"name" : "",
"actions" : [
{
"name" : "communicateClient",
"value" : true
},
{
"name" : "shouldSendAlert",
"value" : false
}
]
}
],
"name" : "Technology Support"
},
{
"item" : [
{
"name" : "",
"actions" : [
{
"name" : "communicateClient",
"value" : true
}
]
}
],
"name" : "Company Support"
}
],
"name" : "Support"
},
{
"name" : " FAQ"
}
],
"name" : "Help"
}
]
}
I've managed to do this, querying the document using a multiple $elemMatch query, and using forEach to run through the nested arrays in order to alter the value of shouldSendAlert:
{
let menuItems = db.getCollection('menumodels').find({menu: {$elemMatch: {name: 'Help',sub: {$elemMatch: {name: 'Support',motivos: {$elemMatch: {name: 'Technology Support'}}}}}}});
menuItems.forEach((r) => {
r.menu.forEach(menuItem => {
if (menuItem.name == 'Help') {
menuItem.sub.forEach(sub => {
if (sub.name == 'Support') {
sub.motivos.forEach(motivo => {
if (motivo.name == "Technology Support") {
motivo.item[0].actions.forEach(action => {
if (action.name == 'shouldSendAlert') {
action.value = true;
db.getCollection('menumodels').update({_id: r._id}, {$set: {menu: r.menu}})
}
})
}
})
}
})
}
})
});
}
Is it - regarding performance - necessary, to code this MongoDB query
or update logic into a smarter form? Does the multiple use of $elemMatch affect performance?

Updating array inside two object in mongod

I have a collection of the structure as follows:
collection name : "positions"
Structure
{
"_id" : "vtQ3tFXg8THF3TNBc",
"candidatesActions" : {
"sourced" : [ ],
},
"appFormObject" : {
"name" : "✶ mandatory",
"questions" : [
{
"qusId" : "qs-585494",
"type" : "simple",
"qus" : "Which was your previous company"
},
{
"qusId" : "qs-867766",
"type" : "yesNo",
"qus" : "Are you willing to relocate?",
"disqualify" : "true"
}
]
}
}
I want to update "qus" field of the above collection whose _id is "vtQ3tFXg8THF3TNBc" and "qusId" is "qs-585494".

Try following....
db.positions.update(
{_id: "vtQ3tFXg8THF3TNBc", "appFormObject.questions.qusId":"qs-585494"},
{$set:{"appFormObject.questions.$.qus": "this is updated value"}}
)

Use following query
db.positions.findAndModify({
query: { _id: "vtQ3tFXg8THF3TNBc", "appFormObject.questions.qusId":"qs-585494"} ,
update: { $set: { 'appFormObject.questions.$.qus': 'Brilliant Green' } },
});
Thanks

How do I query referenced objects in MongoDB?

I've got two collections in my Mongo database, and the Foos contain references to one or more Bars:
Foo: {
prop1: true,
prop2: true,
bars: [
{
"$ref": "Bar",
"$id": ObjectId("blahblahblah")
}
]
}
Bar: {
testprop: true
}
What I want is to find all of the Foos that have at least one Bar that has its testprop set to true. I've tried this command, but it doesn't return any results:
db.Foo.find({ "bars.testprop" : { "$in": [ true ] } })
Any ideas?

You can now do it in Mongo 3.2 using $lookup
$lookup takes four arguments
from: Specifies the collection in the same database to perform the join with. The from collection cannot be sharded.
localField: Specifies the field from the documents input to the $lookup stage. $lookup performs an equality match on the localField to the foreignField from the documents of the from collection.
foreignField: Specifies the field from the documents in the from collection.
as: Specifies the name of the new array field to add to the input documents. The new array field contains the matching documents from the from collection.
db.Foo.aggregate(
{$unwind: "$bars"},
{$lookup: {
from:"bar",
localField: "bars",
foreignField: "_id",
as: "bar"
}},
{$match: {
"bar.testprop": true
}}
)

You can't. See http://www.mongodb.org/display/DOCS/Database+References
You have to do it in the client.

We have had a similar issue as we use MongoDB (3.4.4, actually 3.5.5 for testing) in combination with Morphia where we use #Referenece on a couple of entities. We are though not that happy with this solution and are considering removing these declarations and instead do the reference lookups manually.
I.e. we have a company collection and a user collection. The user entity in Morphia contains a #Refrence declaration on a company entity. The respective company collections contains entries like:
/* 1 */
{
"_id" : ObjectId("59a92501df01110fbb6a5dee"),
"name" : "Test",
"gln" : "1234567890123",
"uuid" : "f1f86961-e8d5-40bb-9d3f-fdbcf549066e",
"creationDate" : ISODate("2017-09-01T09:14:41.551Z"),
"lastChange" : ISODate("2017-09-01T09:14:41.551Z"),
"version" : NumberLong(1),
"disabled" : false
}
/* 2 */
{
"_id" : ObjectId("59a92501df01110fbb6a5def"),
"name" : "Sample",
"gln" : "3210987654321",
"uuid" : "fee69ee4-b29c-483b-b40d-e702b50b0451",
"creationDate" : ISODate("2017-09-01T09:14:41.562Z"),
"lastChange" : ISODate("2017-09-01T09:14:41.562Z"),
"version" : NumberLong(1),
"disabled" : false
}
while the user collections contains the following entries:
/* 1 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df0"),
"userId" : "admin",
"userKeyEncrypted" : {
"salt" : "78e0528db239fd86",
"encryptedAttribute" : "e4543ddac7cca9757721379e4e70567bb13956694f473b73f7723ac2e2fc5245"
},
"passwordHash" : "$2a$10$STRNORu9rcbq4qYUMld4G.HJk8QQQQBmAswSNC/4PBn2bih0BvjM6",
"roles" : [
"ADMIN"
],
"company" : {
"$ref" : "company",
"$id" : ObjectId("59a92501df01110fbb6a5dee")
},
"uuid" : "b8aafdcf-d5c4-4040-a96d-8ab1a8608af8",
"creationDate" : ISODate("2017-09-01T09:14:41.673Z"),
"lastChange" : ISODate("2017-09-01T09:14:41.765Z"),
"version" : NumberLong(1),
"disabled" : false
}
/* 2 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df1"),
"userId" : "sample",
"userKeyEncrypted" : {
"salt" : "e3ac48695dea5f51",
"encryptedAttribute" : "e804758b0fd13c219c3fc383eaa9267b70f7b8a1ed74f05575add713ce11804a"
},
"passwordHash" : "$2a$10$Gt2dq1vy4J9MeqDnXjokAOtvFcvbhe/g9wAENXFPaPxLAw1L4EULG",
"roles" : [
"USER"
],
"company" : {
"$ref" : "company",
"$id" : ObjectId("59a92501df01110fbb6a5def")
},
"uuid" : "55b62d4c-e5ee-408d-80c0-b79e02085b02",
"creationDate" : ISODate("2017-09-01T09:14:41.873Z"),
"lastChange" : ISODate("2017-09-01T09:14:41.878Z"),
"version" : NumberLong(1),
"disabled" : false
}
/* 3 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df2"),
"userId" : "user",
"userKeyEncrypted" : {
"salt" : "ab9df671340a7d8b",
"encryptedAttribute" : "7d8ad4ca6ad88686d810c70498407032f1df830596f72d931880483874d9cce3"
},
"passwordHash" : "$2a$10$0FLFw3ixW79JIBrD82Ly6ebOwnEDliS.e7GmrNkFp2nkWDA9OE/RC",
"uuid" : "d02aef94-fc3c-4539-a22e-e43b8cd78aaf",
"creationDate" : ISODate("2017-09-01T09:14:41.991Z"),
"lastChange" : ISODate("2017-09-01T09:14:41.995Z"),
"version" : NumberLong(1),
"disabled" : false
}
In order to create a special company user view we also wanted to dereference the company in the user and only include selected fields. Based on a comment within a bug report we learned that MongoDB provides a $objectToArray: "$$ROOT.element" operation which basically splits fields of the given elements into key and value pairs. Note that $objectToArray operation was added in MongoDB version 3.4.4!
An aggregation on the company element contained in the user collection using the $objectToArray operation may look like below:
dp.user.aggregate([{
$project: {
"userId": 1,
"userKeyEncrypted": 1,
"uuid":1,
"roles": 1,
"passwordHash": 1,
"disabled": 1,
company: { $objectToArray: "$$ROOT.company" }
}
}])
The result of above aggregation looks like this:
/* 1 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df0"),
"userId" : "admin",
"userKeyEncrypted" : {
"salt" : "78e0528db239fd86",
"encryptedAttribute" : "e4543ddac7cca9757721379e4e70567bb13956694f473b73f7723ac2e2fc5245"
},
"passwordHash" : "$2a$10$STRNORu9rcbq4qYUMld4G.HJk8QQQQBmAswSNC/4PBn2bih0BvjM6",
"roles" : [
"ADMIN"
],
"uuid" : "b8aafdcf-d5c4-4040-a96d-8ab1a8608af8",
"disabled" : false,
"company" : [
{
"k" : "$ref",
"v" : "company"
},
{
"k" : "$id",
"v" : ObjectId("59a92501df01110fbb6a5dee")
}
]
}
/* 2 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df1"),
"userId" : "sample",
"userKeyEncrypted" : {
"salt" : "e3ac48695dea5f51",
"encryptedAttribute" : "e804758b0fd13c219c3fc383eaa9267b70f7b8a1ed74f05575add713ce11804a"
},
"passwordHash" : "$2a$10$Gt2dq1vy4J9MeqDnXjokAOtvFcvbhe/g9wAENXFPaPxLAw1L4EULG",
"roles" : [
"USER"
],
"uuid" : "55b62d4c-e5ee-408d-80c0-b79e02085b02",
"disabled" : false,
"company" : [
{
"k" : "$ref",
"v" : "company"
},
{
"k" : "$id",
"v" : ObjectId("59a92501df01110fbb6a5def")
}
]
}
/* 3 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df2"),
"userId" : "user",
"userKeyEncrypted" : {
"salt" : "ab9df671340a7d8b",
"encryptedAttribute" : "7d8ad4ca6ad88686d810c70498407032f1df830596f72d931880483874d9cce3"
},
"passwordHash" : "$2a$10$0FLFw3ixW79JIBrD82Ly6ebOwnEDliS.e7GmrNkFp2nkWDA9OE/RC",
"uuid" : "d02aef94-fc3c-4539-a22e-e43b8cd78aaf",
"disabled" : false,
"company" : null
}
Now it's simply a matter of filtering unwanted stuff (i.e. users that have no company assigned and selecting the right array entries) in order to feed the $lookup operation #sidgate has already explained and copy the value of the dereferenced company into the user response.
I.e. an aggregation like the one below will perform an join and add the data of the company to users that have a company assigned as the as value defined in the lookup:
db.user.aggregate([
{ $project: { "userId": 1, "userKeyEncrypted": 1, "uuid":1, "roles": 1, "passwordHash": 1, "disabled": 1, company: { $objectToArray: "$$ROOT.company" }} },
{ $unwind: "$company" },
{ $match: { "company.k": "$id"} },
{ $lookup: { from: "company", localField: "company.v", foreignField: "_id", as: "company_data" } }
])
The result to the above aggregation can be seen below:
/* 1 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df0"),
"userId" : "admin",
"userKeyEncrypted" : {
"salt" : "78e0528db239fd86",
"encryptedAttribute" : "e4543ddac7cca9757721379e4e70567bb13956694f473b73f7723ac2e2fc5245"
},
"passwordHash" : "$2a$10$STRNORu9rcbq4qYUMld4G.HJk8QQQQBmAswSNC/4PBn2bih0BvjM6",
"roles" : [
"ADMIN"
],
"uuid" : "b8aafdcf-d5c4-4040-a96d-8ab1a8608af8",
"disabled" : false,
"company" : {
"k" : "$id",
"v" : ObjectId("59a92501df01110fbb6a5dee")
},
"company_data" : [
{
"_id" : ObjectId("59a92501df01110fbb6a5dee"),
"name" : "Test",
"gln" : "1234567890123",
"uuid" : "f1f86961-e8d5-40bb-9d3f-fdbcf549066e",
"creationDate" : ISODate("2017-09-01T09:14:41.551Z"),
"lastChange" : ISODate("2017-09-01T09:14:41.551Z"),
"version" : NumberLong(1),
"disabled" : false
}
]
}
/* 2 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df1"),
"userId" : "sample",
"userKeyEncrypted" : {
"salt" : "e3ac48695dea5f51",
"encryptedAttribute" : "e804758b0fd13c219c3fc383eaa9267b70f7b8a1ed74f05575add713ce11804a"
},
"passwordHash" : "$2a$10$Gt2dq1vy4J9MeqDnXjokAOtvFcvbhe/g9wAENXFPaPxLAw1L4EULG",
"roles" : [
"USER"
],
"uuid" : "55b62d4c-e5ee-408d-80c0-b79e02085b02",
"disabled" : false,
"company" : {
"k" : "$id",
"v" : ObjectId("59a92501df01110fbb6a5def")
},
"company_data" : [
{
"_id" : ObjectId("59a92501df01110fbb6a5def"),
"name" : "Sample",
"gln" : "3210987654321",
"uuid" : "fee69ee4-b29c-483b-b40d-e702b50b0451",
"creationDate" : ISODate("2017-09-01T09:14:41.562Z"),
"lastChange" : ISODate("2017-09-01T09:14:41.562Z"),
"version" : NumberLong(1),
"disabled" : false
}
]
}
As can hopefully be seen we only have the two users that contained a company reference and the two users now have also the complete company data in the response. Now additional filtering can be applied to get rid of the key/value helper and also to hide unwanted data.
The final query we came up with looks like this:
db.user.aggregate([
{ $project: { "userId": 1, "userKeyEncrypted": 1, "uuid":1, "roles": 1, "passwordHash": 1, "disabled": 1, company: { $objectToArray: "$$ROOT.company" }} },
{ $unwind: "$company" },
{ $match: { "company.k": "$id"} },
{ $lookup: { from: "company", localField: "company.v", foreignField: "_id", as: "company_data" } },
{ $project: { "userId": 1, "userKeyEncrypted": 1, "uuid":1, "roles": 1, "passwordHash": 1, "disabled": 1, "companyUuid": { $arrayElemAt: [ "$company_data.uuid", 0 ] } } }
])
Which finally returns our desired representation:
/* 1 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df0"),
"userId" : "admin",
"userKeyEncrypted" : {
"salt" : "78e0528db239fd86",
"encryptedAttribute" : "e4543ddac7cca9757721379e4e70567bb13956694f473b73f7723ac2e2fc5245"
},
"passwordHash" : "$2a$10$STRNORu9rcbq4qYUMld4G.HJk8QQQQBmAswSNC/4PBn2bih0BvjM6",
"roles" : [
"ADMIN"
],
"uuid" : "b8aafdcf-d5c4-4040-a96d-8ab1a8608af8",
"disabled" : false,
"companyUuid" : "f1f86961-e8d5-40bb-9d3f-fdbcf549066e"
}
/* 2 */
{
"_id" : ObjectId("59a92501df01110fbb6a5df1"),
"userId" : "sample",
"userKeyEncrypted" : {
"salt" : "e3ac48695dea5f51",
"encryptedAttribute" : "e804758b0fd13c219c3fc383eaa9267b70f7b8a1ed74f05575add713ce11804a"
},
"passwordHash" : "$2a$10$Gt2dq1vy4J9MeqDnXjokAOtvFcvbhe/g9wAENXFPaPxLAw1L4EULG",
"roles" : [
"USER"
],
"uuid" : "55b62d4c-e5ee-408d-80c0-b79e02085b02",
"disabled" : false,
"companyUuid" : "fee69ee4-b29c-483b-b40d-e702b50b0451"
}
Some final note to this approach: This aggregation isn't very fast, sadly, but at least it gets the job done. I haven't tested it with an array of references as originally asked though this may require some additional unwindings probably.
Update: A further way of aggregating the data, which is more in line with the comments in the above mentioned bug report, can be seen below:
db.user.aggregate([
{ $project: { "userId": 1, "userKeyEncrypted": 1, "uuid":1, "roles": 1, "passwordHash": 1, "disabled": 1, companyRefs: { $let: { vars: { refParts: { $objectToArray: "$$ROOT.company" }}, in: "$$refParts.v" } } } },
{ $match: { "companyRefs": { $exists: true } } },
{ $project: { "userId": 1, "userKeyEncrypted": 1, "uuid":1, "roles": 1, "passwordHash": 1, "disabled": 1, "companyRef": { $arrayElemAt: [ "$companyRefs", 1 ] } } },
{ $lookup: { from: "company", localField: "companyRef", foreignField: "_id", as: "company_data" } },
{ $project: { "userId": 1, "userKeyEncrypted": 1, "uuid":1, "roles": 1, "passwordHash": 1, "disabled": 1, "companyUuid": { $arrayElemAt: [ "$company_data.uuid", 0 ] } } }
])
Here the $let: { vars: ..., in: ... } operation copies the key and value of the reference into an own object and thus allows later on to lookup the reference via the corresponding operation.
Which of these aggregations performs better has yet to be profiled.

Well.. you could query the Bar Model for the _id of all documents with testprop: true, then do a find $in and populate bars on the Foo Model with an array of those _id's you got from the first query.. :P
Maybe that counts as "In the Client" :P just a thought.

It wasn't possible before, but improvements from Mongo v3.4 we can get very close to it.
You can do it with mongo-join-query. Your code would look like this:
const mongoose = require("mongoose");
const joinQuery = require("mongo-join-query");
joinQuery(
mongoose.models.Foo,
{
find: { "bars.testprop": { $in: [true] } },
populate: ["bars"]
},
(err, res) => (err ? console.log("Error:", err) : console.log("Success:", res.results))
);
How does it work?
Behind the scenes mongo-join-query will use your Mongoose schema to determine which models to join and will create an aggregation pipeline that will perform the join and the query.
Disclosure: I wrote this library to tackle precisely this use case.

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