Related
I'm new in mongoose and I'm trying to find user by code [user.test.test1.code] , any idea ?
Model :
const userSechema = new mongoose.Schema({
name: {
type: String,
required: true
},
test: [{}],
})
Data :
{
"_id": {
"$oid": "600020ab34742c2d34ae45e5"
},
"test": [{
"test1": {
"code": 11111
},
"test2": {
"code": 22222
}
}]
"name": "daniel"
}
query :
let regex = new RegExp(req.query.searchUserKey, 'i')
const users = await User.find({ $or: [{'name': regex },{'test.test1': { code : regex} }]})
-- Solution --
Thanks you guys, both answers is work for me
Is as simple as do "test.test1.code": 418816 into find query like this:
db.collection.find({
"test.test1.code": 418816
})
This query will give you all documents where exists test.test1.code with value 418816.
Note that this query return the whole document, not only the sub-document into the array. But I'm assuming by your post that a user is the document where exists the field name.
Example here
you can use $elemMatch, check the documentation
const users = await User.find(
{ test: { $elemMatch: { "test1.code": 418816 } } }
)
I have the following schemas designed in my Node server
SCHEMAS
const mongoose = require('mongoose');
const Schema = mongoose.Schema;
const dataSchema = new Schema({
time: Date,
value: String
});
const nodeSchema = new Schema({
name: String,
description: String,
number: Number,
status: String,
lastSeen: Date,
data: [dataSchema]
});
const siteSchema = new Schema({
code: String,
name: String,
description: String,
totalNodes: Number,
nodes: [nodeSchema]
});
const Site = mongoose.model('site',siteSchema);
module.exports = Site;
They basically look like this. You can see there are two nodes with some demo data.
EXAMPLE
{
"_id": "5fa169473a394829bc485069",
"code": "xfx3090",
"name": "Name of this site",
"description": "Some description",
"totalNodes": 2,
"__v": 0,
"nodes": [
{
"_id": "5fa1af361e085b516066d7e2",
"name": "device name",
"description": "device description",
"number": 1,
"status": "Offline",
"lastSeen": "2020-11-03T19:27:50.062Z",
"data": [
{
"Date": "2019-01-01T00:00:00.000Z",
"value": "12"
},
{
"Date": "2019-01-01T00:00:00.000Z",
"Value": "146"
}
]
},
{
"_id": "5fa1b10f4f24051520f85a58",
"name": "device name",
"description": "device description",
"number": 2,
"status": "Offline",
"lastSeen": "2020-11-03T19:35:43.409Z",
"data": [
{
"Date": "2019-01-01T00:00:00.000Z",
"Value": "555"
}
]
}
]
}
]
My question is how can I update a specific field of a node, in particular how I can update the last seen or the status. It is important to mention that the client making the request will only have access the the site code and the node number. The Object Id's of sites and nodes will not be known.
So far this is what I have, but it only creates one new Object Id for some reason.
Any advice will be appreciated
updateNode: async (req,res,next) => {
const {siteCode} = req.params;
const { nodeNumber } = req.params;
const status = req.body.status;
const nodeStatus = await Site.findOneAndUpdate({'code': siteCode, 'nodes.number':nodeNumber}, { '$set': {'nodes.$.status': {'status':status}}});
res.status(200).json({message: 'success'});
}
You'll need to do it this way.
I have predefined the ._ids.
You can do this dynamically if you want. If you are using express you could just use queries. Example req.query.documentID. The URL to access it will be localhost:p/?documentID=5fa169473a394829bc485069&nodeID=5fa1af361e085b516066d7e2
p in localhost is for port
await Site
.findOne({
"_id": "5fa169473a394829bc485069",
"nodes._id": "5fa1af361e085b516066d7e2"
})
.update({ "lastSeen": Date })
.then(doc => res.json(doc))
.catch(e => console.log(e))
Basically finding a doc with id of 5fa169473a394829bc485069
Then a node with _id of 5fa1af361e085b516066d7e2
And then update() method and { "lastSeen": Date } parameter to Date.
That's it!
EDIT
You'll have to create a VALID MongoDB object by doing this
app.get("/new", async (req, res) => {
let Site = new model({
code: "String",
name: "String",
description: "String",
totalNodes: 2,
nodes: [
{
_id: new mongoose.Types.ObjectId,
name: "String",
description: "String",
number: 1,
status: "offline",
lastSeen: Date.now(),
data: [{ "someData": "someData" }]
},
{
_id: new mongoose.Types.ObjectId,
name: "String",
description: "String",
number: 2,
status: "offline",
lastSeen: Date.now(),
data: [{ "someData": "someData" }]
}
]
});
await Site
.save()
.then(doc => {
console.log(doc);
res.json(doc);
})
.catch(e => console.error(e));
});
Everything is loaded with dummy data. Then you update the data like this.
app.get("/", async (req, res) => {
await model
.findOne({ "code": "String" })
.update({
"nodes.0.status": "online"
})
.then(doc => {
console.log(doc);
res.json(doc);
})
.catch(e => console.error(e));
})
Basically you access the object at the index position 0 ( that means the first post ) like this nodes.0 and then the status of that object will be respectively nodes.0.status. Then you just save the object and that's it!
I am creating a schema for an Order model that will track the items ordered along with the quantity purchased. I want to keep the itemId references and the quantity tied together as an array in one parameter.
I have created an Array that includes a reference to the ObjectId plus an additional Number type. I am currently unable to populate the product information using a .populate() query.
Order Schema
const mongoose = require("mongoose");
const { Schema } = mongoose;
const orderSchema = new Schema({
orderNumber: String,
_itemsOrdered: [
{
itemId: {
type: mongoose.Schema.Types.ObjectId,
ref: "menuItems"
},
quantity: Number
}
]
});
mongoose.model("orders", orderSchema);
MenuItem Schema
const mongoose = require("mongoose");
const { Schema } = mongoose;
const MenuItemSchema = new Schema({
imageURL: String,
name_en: String,
name_es: String,
type_en: String,
type_es: String,
description_en: String,
description_es: String,
dietaryCallouts: [String],
price: Number
});
mongoose.model("menuItems", MenuItemSchema);
module.export = MenuItemSchema;
I am able to save the record but cannot populate the MenuItem information with the following query:
Order Controller
async show(req, res, next) {
try {
const orderId = req.params.id;
let order = await Order.findById({ _id: orderId }).populate(
"_itemsOrdered.itemId"
);
res.send(order);
} catch (err) {
res.status(402).send(err);
}
}
Here it the order object that is being saved to the DB.
Order Object
{
"_id": "5dc93b9c0085b8045e0c8aa3",
"orderNumber": "Order 3",
"_itemsOrdered": [
{
"_id": "5dc93b9c0085b8045e0c8aa5",
"itemId": "5dc7f814a2679b47319a79a4",
"quantity": 1
},
{
"_id": "5dc93b9c0085b8045e0c8aa4",
"itemId": "5dc7e5c7de590744c46f93da",
"quantity": 2
}
],
"__v": 0
}
Your order schema must be like this:
const orderSchema = new Schema({
orderNumber: String,
_itemsOrdered: [
{
itemId: { type: mongoose.Schema.Types.ObjectId, ref: "menuItems" },
quantity: Number
}
]
});
And you can use the following route to create an order document.
router.post("/order", async (req, res, next) => {
try {
const { orderNumber, _itemsOrdered } = req.body;
let order = new Order({ orderNumber, _itemsOrdered });
order = await order.save();
res.status(201).send(order);
} catch (err) {
console.log(err);
res.status(500).send(err);
}
});
Sample body: (you need to change ids according to yours)
{
"orderNumber": "Order 1",
"_itemsOrdered": [
{"itemId": "5dc90346222b892434e4675a", "quantity" : 1 },
{"itemId": "5dc90359222b892434e4675b", "quantity" : 2 }
]
}
To get the order and its items you can use populate like this:
router.get("/orders/:id", async (req, res) => {
try {
const orderAndItems = await Order.findById(req.params.id).populate(
"_itemsOrdered.itemId"
);
res.send(orderAndItems);
} catch (err) {
console.log(err);
res.status(500).send(err);
}
});
This will give you a result like this:
{
"_id": "5dc904db8407a217b4dfe6f4",
"orderNumber": "Order 1",
"_itemsOrdered": [
{
"_id": "5dc904db8407a217b4dfe6f6",
"itemId": {
"_id": "5dc90346222b892434e4675a",
"name_en": "item 1",
"price": 1,
"__v": 0
},
"quantity": 1
},
{
"_id": "5dc904db8407a217b4dfe6f5",
"itemId": {
"_id": "5dc90359222b892434e4675b",
"name_en": "item 2",
"price": 2,
"__v": 0
},
"quantity": 2
}
],
"__v": 0
}
So i have two schemas, Article and Event
Both have an image field.
For Article,
featured_image: {
type: String,
default: '',
}
For Event,
featured_image: {
type: Schema.ObjectId,
ref: 'Medium'
}
I have another schema, Card, like this
type: {
type: String,
enum: ['Article', 'Event']
},
data: {
type: Schema.ObjectId,
refPath: 'type'
}
I am trying to populate the cards, like this
Card
.find(query)
.populate({
path: 'data',
populate: [{
path: 'featured_image',
model: 'Medium',
select: 'source type'
}]
};)
However, it keeps giving me a cast error, because when card is of type Event, it populates fine, but when it's of type 'Article', featured_image field is of string type and hence cannot be populated.
How do i populate featured_image field only if card is of type Event or it's a reference id, instead of string.
Instead of what you are attempting to do you should be using "discriminators", which is in fact the correct way to handle a relationship where the object types vary in the reference given.
You use discriminators by the different way in which you define the model, which instead constructs from a "base model" and schema as in:
const contentSchema = new Schema({
name: String
});
const articleSchema = new Schema({
image: String,
});
const eventSchema = new Schema({
image: { type: Schema.Types.ObjectId, ref: 'Medium' }
});
const cardSchema = new Schema({
name: String,
data: { type: Schema.Types.ObjectId, ref: 'Content' }
});
const Medium = mongoose.model('Medium', mediumSchema);
const Card = mongoose.model('Card', cardSchema )
const Content = mongoose.model('Content', contentSchema);
const Article = Content.discriminator('Article', articleSchema);
const Event = Content.discriminator('Event', eventSchema);
So instead you define a "base model" such as Content here which you actually point the references to within Event.
The next part is that the differing schema are actually registered to this model via the .discriminator() method from the base model, as opposed to the .model() method. This registers the schema with the general Content model in such a way that when you refer to any model instance defined with .discriminator() that a special __t field is implied to exist in that data, using the registered model name.
Aside from enabling mongoose to .populate() on different types, this also has the advantage of being a "full schema" attached to the different types of items. So you have have different validation and other methods as well if you like. It is indeed "polymorphism" at work in a database context, with helpful schema objects attached.
Therefore we can demonstrate both the varied "joins" that are done, as well as that you can now both use the individual models for Article and Event which would deal with only those items in all queries and operations. And not only can you use "individually", but since the mechanism for this actually stores the data in the same collection, there is also a Content model which gives access to both these types. Which is in essence how the main relation works in the definition to the Event schema.
As a full listing
const async = require('async'),
mongoose = require('mongoose'),
Schema = mongoose.Schema;
mongoose.set('debug',true);
mongoose.Promise = global.Promise;
mongoose.connect('mongodb://localhost/cards');
const mediumSchema = new Schema({
title: String
});
const contentSchema = new Schema({
name: String
});
const articleSchema = new Schema({
image: String,
});
const eventSchema = new Schema({
image: { type: Schema.Types.ObjectId, ref: 'Medium' }
});
const cardSchema = new Schema({
name: String,
data: { type: Schema.Types.ObjectId, ref: 'Content' }
});
const Medium = mongoose.model('Medium', mediumSchema);
const Card = mongoose.model('Card', cardSchema )
const Content = mongoose.model('Content', contentSchema);
const Article = Content.discriminator('Article', articleSchema);
const Event = Content.discriminator('Event', eventSchema);
function log(data) {
console.log(JSON.stringify(data, undefined, 2))
}
async.series(
[
// Clean data
(callback) =>
async.each(mongoose.models,(model,callback) =>
model.remove({},callback),callback),
// Insert some data
(callback) =>
async.waterfall(
[
(callback) =>
Medium.create({ title: 'An Image' },callback),
(medium,callback) =>
Content.create(
[
{ name: "An Event", image: medium, __t: 'Event' },
{ name: "An Article", image: "A String", __t: 'Article' }
],
callback
),
(content,callback) =>
Card.create(
[
{ name: 'Card 1', data: content[0] },
{ name: 'Card 2', data: content[1] }
],
callback
)
],
callback
),
// Query and populate
(callback) =>
Card.find()
.populate({
path: 'data',
populate: [{
path: 'image'
}]
})
.exec((err,cards) => {
if (err) callback(err);
log(cards);
callback();
}),
// Query on the model for the discriminator
(callback) =>
Article.findOne({},(err,article) => {
if (err) callback(err);
log(article);
callback();
}),
// Query on the general Content model
(callback) =>
Content.find({},(err,contents) => {
if (err) callback(err);
log(contents);
callback();
}),
],
(err) => {
if (err) throw err;
mongoose.disconnect();
}
);
And the sample output for different queries
Mongoose: cards.find({}, { fields: {} })
Mongoose: contents.find({ _id: { '$in': [ ObjectId("595ef117175f6850dcf657d7"), ObjectId("595ef117175f6850dcf657d6") ] } }, { fields: {} })
Mongoose: media.find({ _id: { '$in': [ ObjectId("595ef117175f6850dcf657d5") ] } }, { fields: {} })
[
{
"_id": "595ef117175f6850dcf657d9",
"name": "Card 2",
"data": {
"_id": "595ef117175f6850dcf657d7",
"name": "An Article",
"image": "A String",
"__v": 0,
"__t": "Article"
},
"__v": 0
},
{
"_id": "595ef117175f6850dcf657d8",
"name": "Card 1",
"data": {
"_id": "595ef117175f6850dcf657d6",
"name": "An Event",
"image": {
"_id": "595ef117175f6850dcf657d5",
"title": "An Image",
"__v": 0
},
"__v": 0,
"__t": "Event"
},
"__v": 0
}
]
Mongoose: contents.findOne({ __t: 'Article' }, { fields: {} })
{
"_id": "595ef117175f6850dcf657d7",
"name": "An Article",
"image": "A String",
"__v": 0,
"__t": "Article"
}
Mongoose: contents.find({}, { fields: {} })
[
{
"_id": "595ef117175f6850dcf657d6",
"name": "An Event",
"image": "595ef117175f6850dcf657d5",
"__v": 0,
"__t": "Event"
},
{
"_id": "595ef117175f6850dcf657d7",
"name": "An Article",
"image": "A String",
"__v": 0,
"__t": "Article"
}
]
I'm having trouble 'upserting' to my array. The code below creates duplicates in my answers array which I definitely do not want and by now it's apparent $push will not work. I have tried using the different methodologies I see on SO for a while now but none are working for me. With this web app, users are allows to view a question on the website and respond with a 'yes' or 'no' response and they are allowed to change(upsert) their response at any one time meaning a sort of upsert takes place on the db at different times. How do get around this?
var QuestionSchema = Schema ({
title :String,
admin :{type: String, ref: 'User'},
answers :[{type: Schema.Types.Mixed, ref: 'Answer'}]
});
var AnswerSchema = Schema ({
_question :{type: ObjectId, ref: 'Question'},
employee :{type: String, ref: 'User'},
response :String,
isAdmin :{type: Boolean, ref: 'User'}
})
var UserSchema = Schema({
username : String,
isAdmin : {type: Boolean, default: false}
});
module.exports = mongoose.model('Question', QuestionSchema);
module.exports = mongoose.model('Answer', AnswerSchema);
module.exports = mongoose.model('User', UserSchema);
Question.update(
{_id: req.body.id},
{$push: {answers: {_question: req.body.id,
employee: req.body.employee,
response: req.body.response, //this variable changes (yes/no/null)
isAdmin: req.body.isAdmin}}},
{safe: true, upsert: true},
function(err, model) {
}
);
As I see it you seem a little confused and it's reflected in your schema. You don't seem to fully grasp the differences between "embedded" and "referenced" since your schema is actually an invalid "mash" of the two techniques.
Probably best to walk you through both of them.
Embedded Model
So instead of the schema you have defined, you should in fact have something more like this:
var QuestionSchema = Schema ({
title :String,
admin :{type: String, ref: 'User'},
answers :[AnswerSchema]
});
var AnswerSchema = Schema ({
employee :{type: String, ref: 'User'},
response :String,
isAdmin :{type: Boolean, ref: 'User'}
})
mongoose.model('Question', questionSchema);
NOTE: Question is the only actual model here. The AnswerSchema is completely "embedded".
Note the clear definition of the "schema" where the "answers" property in Question is defined as an "array" of AnswerSchema. This is how you do embedding and keep control of the types within the object inside the array.
As for the update, there is a clear logic pattern but you are simply not enforcing it. All you need to do is "tell" the update that you do not want to "push" a new item if something for that "unique" "employee" in the array already exists.
Also. This is NOT and "upsert". Upsert implies "creating a new one", which is different to what you want. You want to "push" to the array of an "existing" Question. If you leave "upsert" on there, then something not found creates a new Question. Which is of course wrong here.
Question.update(
{
"_id": req.body.id,
"answers.employee": { "$ne": req.body.employee },
}
},
{ "$push": {
"answers": {
"employee": req.body.employee,
"response": req.body.response,
"isAdmin": req.body.isAdmin
}
}},
function(err, numAffected) {
});
That will look to check that the "unique" "employee" in the array members already and will only $push where it is not already there.
As a bonus, if you intend to allow the user to "change their answer" then we do this incantation with .bulkWrite():
Question.collection.bulkWrite(
[
{ "updateOne": {
"filter": {
"_id": req.body.id,
"answers.employee": req.body.employee,
},
"update": {
"$set": {
"answers.$.response": req.body.response,
}
}
}},
{ "updateOne": {
"filter": {
"_id": req.body.id,
"answers.employee": { "$ne": req.body.employee },
},
"update": {
"$push": {
"answers": {
"employee": req.body.employee,
"response": req.body.response,
"isAdmin": req.body.isAdmin
}
}
}
}}
],
function(err, writeResult) {
}
);
This effectively puts two updates in one. The first to attempt to alter an existing answer and $set the response at the matched position, and the second to attempt to add a new answer where one was not found on the question.
Referenced Model
With a "referenced" model you actually have the real members of the Answer within their own collection. So instead the schema is defined like this:
var QuestionSchema = Schema ({
title :String,
admin :{type: String, ref: 'User'},
answers :[{ type: Schema.Types.ObjectId, ref: 'Answer' }]
});
var AnswerSchema = Schema ({
_question :{type: ObjectId, ref: 'Question'},
employee :{type: String, ref: 'User'},
response :String,
isAdmin :{type: Boolean, ref: 'User'}
})
mongoose.model('Answer', answerSchema);
mongoose.model('Question', questionSchema);
N.B The other ref's here to User such as :
employee :{type: String, ref: 'User'},
isAdmin :{type: Boolean, ref: 'User'}
These are also really incorrect, and also should be of Schema.Type.ObjectId as they will "reference" the actual _id field of User. But this is actually outside of the scope of this question as asked, so if you still don't grasp that after this read, then Ask a New Question so someone can explain. On with the rest of the answer.
That's the "general" shape of the schema though, with the important thing being the "ref" to the 'Anwser' "model", which is by the registered name. You can optionally just use your "_question" field in modern mongoose versions with a "virtual", but I'm skipping over "Adavanced Usage" for now and keeping it simple with an array of "references" still in the Question model.
In this case, since the Answer model is actually in it's own "collection", then the operations actually become "upserts". Where we only want to "create" when there is no "employee" response to the given "_question" id.
Also demonstrating with a Promise chain instead:
Answer.update(
{ "_question": req.body.id, "employee": req.body.employee },
{
"$set": {
"response": req.body.reponse
},
"$setOnInsert": {
"isAdmin": req.body.isAdmin
}
},
{ "upsert": true }
).then(resp => {
if ( resp.hasOwnProperty("upserted") ) {
return Question.update(
{ "_id": req.body.id, "answers": { "$ne": resp.upserted[0]._id },
{ "$push": { "answers": resp.upserted[0]._id } }
).exec()
}
return;
}).then(resp => {
// either undefined where it was not an upsert or
// the update result from Question where it was
}).catch(err => {
// something
})
This is actually a simple statement since "when matched" we want to change the "response" data with the payload of the request, and really only when "upserting" or "creating/inserting" is when we actually change other data such as the "employee" ( which is always implied for create as part of the query expression ) and the "isAdmin" which clearly should not change with each update request we then explicitly use $setOnInsert so it only writes those two fields on an actual "create".
In the "Promise Chain" we actually look to see if the update request to Answer actually resulted in an "upsert", and when it does we want to append to the array of Question where it does not already exist. In much the same way as the "embedded" example, it's best to look to see if the array actually has the item before modifying with the "update". Alternately you could $addToSet here and just let the query match the Question by _id. To me though, that's a wasted write.
Summary
Those are your different approaches to how you handle this. Each has their own use cases for which you can see a general summary some other answers of mine in:
Mongoose populate vs object nesting which is an overview of the different approaches and reasons behind them
How to Model a “likes” voting system with MongoDB which gives a bit more detail on the "unique array upserts" technique for "embedded" models.
Not "required" reading, but it may help expand your insight into which approach is best for your particular case.
Working Example
Copy these and put them in a directory and do an npm install to install local dependencies. The code will run and create the collections in the database making the alterations.
Logging is turned on with mongoose.set(debug,true) so you should look at the console output and see what it does, along with the resulting collections where answers will be recorded to the related questions, and overwritten instead of "duplicating" where that was also the intent.
Change the connection string if you have to. But that is all you should change in this listing for it's purpose. Both approaches described in the answer are demonstrated.
package.json
{
"name": "colex",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1"
},
"keywords": [],
"author": "",
"license": "ISC",
"dependencies": {
"async": "^2.4.1",
"mongodb": "^2.2.29",
"mongoose": "^4.10.7"
}
}
index.js
const async = require('async'),
mongoose = require('mongoose'),
Schema = mongoose.Schema,
ObjectId = require('mongodb').ObjectID
mongoose.Promise = global.Promise;
mongoose.set('debug',true);
mongoose.connect('mongodb://localhost/coltest');
const userSchema = new Schema({
username: String,
isAdmin: { type: Boolean, default: false }
});
const answerSchemaA = new Schema({
employee: { type: Schema.Types.ObjectId, ref: 'User' },
response: String,
});
const answerSchemaB = new Schema({
question: { type: Schema.Types.ObjectId, ref: 'QuestionB' },
employee: { type: Schema.Types.ObjectId, ref: 'User' },
response: String,
});
const questionSchemaA = new Schema({
title: String,
admin: { type: Schema.Types.ObjectId, ref: 'User' },
answers: [answerSchemaA]
});
const questionSchemaB = new Schema({
title: String,
admin: { type: Schema.Types.ObjectId, ref: 'User' },
answers: [{ type: Schema.Types.ObjectId, ref: 'AnswerB' }]
});
const User = mongoose.model('User', userSchema);
const AnswerB = mongoose.model('AnswerB', answerSchemaB);
const QuestionA = mongoose.model('QuestionA', questionSchemaA);
const QuestionB = mongoose.model('QuestionB', questionSchemaB);
async.series(
[
// Clear data
(callback) => async.each(mongoose.models,(model,callback) =>
model.remove({},callback),callback),
// Create some data
(callback) =>
async.each([
{
"model": "User",
"object": {
"_id": "594a322619ddbd437193c759",
"name": "Admin",
"isAdmin": true
}
},
{
"model": "User",
"object": {
"_id": "594a323919ddbd437193c75a",
"name": "Bill"
}
},
{
"model": "User",
"object": {
"_id": "594a327b19ddbd437193c75b",
"name": "Ted"
}
},
{
"model": "QuestionA",
"object": {
"_id": "594a32f719ddbd437193c75c",
"admin": "594a322619ddbd437193c759",
"title": "Question A Model"
}
},
{
"model": "QuestionB",
"object": {
"_id": "594a32f719ddbd437193c75c",
"admin": "594a322619ddbd437193c759",
"title": "Question B Model"
}
}
],(data,callback) => mongoose.model(data.model)
.create(data.object,callback),
callback
),
// Submit Answers for Users - Question A
(callback) =>
async.eachSeries(
[
{
"_id": "594a32f719ddbd437193c75c",
"employee": "594a323919ddbd437193c75a",
"response": "Bills Answer"
},
{
"_id": "594a32f719ddbd437193c75c",
"employee": "594a327b19ddbd437193c75b",
"response": "Teds Answer"
},
{
"_id": "594a32f719ddbd437193c75c",
"employee": "594a323919ddbd437193c75a",
"response": "Bills Changed Answer"
}
].map(d => ([
{ "updateOne": {
"filter": {
"_id": ObjectId(d._id),
"answers.employee": ObjectId(d.employee)
},
"update": {
"$set": { "answers.$.response": d.response }
}
}},
{ "updateOne": {
"filter": {
"_id": ObjectId(d._id),
"answers.employee": { "$ne": ObjectId(d.employee) }
},
"update": {
"$push": {
"answers": {
"employee": ObjectId(d.employee),
"response": d.response
}
}
}
}}
])),
(data,callback) => QuestionA.collection.bulkWrite(data,callback),
callback
),
// Submit Answers for Users - Question A
(callback) =>
async.eachSeries(
[
{
"_id": "594a32f719ddbd437193c75c",
"employee": "594a323919ddbd437193c75a",
"response": "Bills Answer"
},
{
"_id": "594a32f719ddbd437193c75c",
"employee": "594a327b19ddbd437193c75b",
"response": "Teds Anwser"
},
{
"_id": "594a32f719ddbd437193c75c",
"employee": "594a327b19ddbd437193c75b",
"response": "Ted Changed it"
}
],
(data,callback) => {
AnswerB.update(
{ "question": data._id, "employee": data.employee },
{ "$set": { "response": data.response } },
{ "upsert": true }
).then(resp => {
console.log(resp);
if (resp.hasOwnProperty("upserted")) {
return QuestionB.update(
{ "_id": data._id, "employee": { "$ne": data.employee } },
{ "$push": { "answers": resp.upserted[0]._id } }
).exec()
}
return;
}).then(() => callback(null))
.catch(err => callback(err))
},
callback
)
],
(err) => {
if (err) throw err;
mongoose.disconnect();
}
)
Here was my quick work around before Neill updated his answer (I used a $pull & $push). Works just as his but I'll mark his correct as I believe it's more efficient.
Question.update(
{_id: req.body.id},
{$pull: {answers: { employee: req.body.employee}}},
{safe: true, multi:true, upsert: true},
function(err, model) {
}
);
Question.update(
{_id: req.body.id},
{$push: {answers: {_question: req.body.id,
employee: req.body.employee,
response: req.body.response,
isAdmin: req.body.isAdmin}}},
{safe: true, upsert: true},
function(err, model) {
}
);