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've got a relational json called "client" inside Bill's model. This is my code:
const mongoose = require("mongoose");
const { Schema } = mongoose;
const billSchema = new Schema({
number: Number,
date: { type: Date, default: Date.now() },
type: String,
local: String,
client: { type: mongoose.Schema.Types.ObjectId, ref: "clients", required: true },
detail: [
{
quantity: Number,
product: { code: Number, name: String, price: Number },
undertotal: Number
}
],
total: Number
});
mongoose.model("bills", billSchema);
this is my post route:
app.post("/api/bills", async (req, res) => {
const { number, type, local, client, detail, total } = req.body;
await Client.findById(req.body.client._id).then(client => {
if (!client) {
return res.status(404).json({
message: "client not found"
});
}
});
const bill = new Bill({
number,
date: new Date(),
type,
local,
client,
detail,
total
});
try {
let newBill = await bill.save();
res.status(201).send(newBill);
} catch (err) {
if (err.name === "MongoError") {
res.status(409).send(err.message);
}
res.status(500).send(err);
}
});
//my get route
app.get("/api/bills", function(req, res) {
Bill.find({}, function(err, bills) {
Client.populate(bills, { path: "clients" }, function(err, bills) {
res.status(200).send(bills);
});
});
});
I want something like this:
{
"number": 302,
"type": "c",
"local": "porstmouth",
"client": {
"address": {
"street": "victoria street",
"number": 1001,
"floor": "2",
"flat": 4
},
"_id": "5dab929613fb682b48e4ca6b",
"name": "luke skywalker",
"mail": "l.skywalker#yahoo.com",
"cuil": "39193219",
"phone": 128391,
"__v": 0
},
"detail": [
{
"quantity": 500,
"product": {
"code": 300,
"name": "P2",
"price": 800
},
"undertotal": 5000
}
],
"total": 11000
}
But I see this result:
{
"date": "2019-10-20T12:27:17.162Z",
"_id": "5dac52a577e09b4acc45718d",
"number": 302,
"type": "c",
"local": "porstmouth ",
"client": "5dab929613fb682b48e4ca6b",
"detail": [
{
"_id": "5dac52a577e09b4acc45718e",
"quantity": 500,
"product": {
"code": 300,
"name": "P2",
"price": 800
},
"undertotal": 5000
}
],
"total": 11000,
"__v": 0
}
I don't want to see id client only. I want to see all content from client inside bill.
I tried to do with populate method, but I haven't results.
So, Which is form to post and populate a nested json relational object in this case?
While posting only clientId is enough.
So your post route can be like this (you both used await and then, which is incorrect, so I refactored it to use only await)
app.post('/api/bills', async (req, res) => {
const { number, type, local, client, detail, total } = req.body;
let existingClient = await Client.findById(req.body.client._id)
if (!existingClient) {
return res.status(404).json({
message: "client not found"
});
}
const bill = new Bill({
number,
date: new Date(),
type,
local,
client: req.body.client._id
detail,
total
})
try {
let newBill = await bill.save();
res.status(201).send(newBill);
} catch (err) {
if (err.name === 'MongoError') {
res.status(409).send(err.message);
}
res.status(500).send(err);
}
});
And in the get route to retrieve all the client info you need to populate it like this:
app.get('/api/bills', async (req, res) => {
try {
const bills = await Bill.find({}).populate("clients");
res.status(200).send(bills);
} catch (err) {
console.log(err);
res.status(500).send(err);
}
}
)
I have two models in my ottoman 1.0.5 setup. One holds contact info which includes an emails array of docs and then the email doc. I can insert new contacts fine as well as emails in docs and the corresponding link in the contact doc for the new email.
Here is my model
const ottoman = require("ottoman")
ottoman.bucket = require("../app").bucket
var ContactModel = ottoman.model("Contact",{
timestamp: {
type: "Date",
default: function() {return new Date()}
},
first_name : "string",
last_name : "string",
emails: [
{
ref:"Email"
}
]} )
var EmailModel = ottoman.model("Email",{
timestamp: {
type: "Date",
default: function() {return new Date()}
},
type : "string",
address : "string",
name: "string"
} )
module.exports = {
ContactModel : ContactModel,
EmailModel : EmailModel
}
Now to get an contact and all its emails i use this function
app.get("/contacts/:id", function(req, res){
model.ContactModel.getById(req.params.id,{load: ["emails"]}, function(error, contact){
if(error) {
res.status(400).json({ Success: false , Error: error, Message: ""})
}
res.status(200).json({ Success: true , Error: "", Message: "", Data : contact})
})
})
Which returns me this
{
"Success": true,
"Error": "",
"Message": "",
"Data": {
"timestamp": "2019-01-30T23:59:59.188Z",
"emails": [
{
"$ref": "Email",
"$id": "3ec07ba0-aaec-4fd4-a207-c4272cef8d66"
}
],
"_id": "0112f774-4b5d-4b73-b784-60fa9fa2f9ff",
"first_name": "Test",
"last_name": "User"
}
}
if i go and log the contact to my console i get this
OttomanModel(`Contact`, loaded, key:Contact|0112f774-4b5d-4b73-b784-60fa9fa2f9ff, {
timestamp: 2019-01-30T23:59:59.188Z,
emails: [ OttomanModel(`Email`, loaded, key:Email|3ec07ba0-aaec-4fd4-a207-c4272cef8d66, {
timestamp: 2019-01-31T00:36:01.264Z,
_id: '3ec07ba0-aaec-4fd4-a207-c4272cef8d66',
type: 'work',
address: 'test#outlook.com',
name: 'Test Outlook',
}),
OttomanModel(`Email`, loaded, key:Email|93848b71-7696-4ef5-979d-05c19be9d593, {
timestamp: 2019-01-31T04:12:40.603Z,
_id: '93848b71-7696-4ef5-979d-05c19be9d593',
type: 'work',
address: 'newTest#outlook.com',
name: 'Test2 Outlook',
}) ],
_id: '0112f774-4b5d-4b73-b784-60fa9fa2f9ff',
first_name: 'Test',
last_name: 'User',
})
This shows that emails was resolved but why does it not show up in the returned json. On the other hand if i return contact.emails i get the resolved emails just fine. So i hope someone can shed some light on what i am missing here
I asked a similar question on the couchbase forum, and I also found out the solution:
(a slight difference that the result of my search is an array not an object like in your case)
forum.couchbase.com
app.get("/assets", (req, res) => {
AssetModel.find({}, { load: ["assetModelId", "assetGroupId", "assetTypeId"] }, (err, results) => {
if (err) return res.status(400).send("no asset found");
const assets = [];
results.map(asset => {
assets.push({...asset});
});
res.status(200).send(assets)
});
});
I'm fairly new to MongoDB and I'm trying to merge an embedded array in a MongoDB collection, my schema for my Project collection is as follows:
Projects:
{
_id: ObjectId(),
client_id: String,
description: String,
samples: [
{
location: String, //Unique
name: String,
}
...
]
}
A user can upload a JSON file that is in the form of:
[
{
location: String, //Same location as in above schema
concentration: float
}
...
]
The length of the samples array is the same length as the uploaded data array. I'm trying to figure out how to add the data field into every element of my samples array, but I can't find out how to do it based on MongoDB documentation. I can load my json data in as "data" and I want to merge based on the common "location" field:
db.projects.update({_id: myId}, {$set : {samples.$[].data : data[location]}});
But I can't think of how to get the index on the json array in update query, and I haven't been able to find any examples in the mongodb documentation, or questions like this.
Any help would be much appreciated!
MongoDB 3.6 Positional Filtered Updates
So you're actually in the right "ballpark" with the positional all $[] operator, but the problem is that just simply applies to "every" array element. Since what you want is "matched" entries you actually want the positional filtered $[<identifier>] operator instead.
As you note your "location" is going to be unique and within the array. Using "index positions" is really not reliable for atomic updates, but actually matching the "unique" properties is. Basically you need to get from something like this:
let input = [
{ location: "A", concentration: 3, other: "c" },
{ location: "C", concentration: 4, other: "a" }
];
To this:
{
"$set": {
"samples.$[l0].concentration": 3,
"samples.$[l0].other": "c",
"samples.$[l1].concentration": 4,
"samples.$[l1].other": "a"
},
"arrayFilters": [
{
"l0.location": "A"
},
{
"l1.location": "C"
}
]
}
And that really is just a matter of applying some basic functions to the provided input array:
let arrayFilters = input.map(({ location },i) => ({ [`l${i}.location`]: location }));
let $set = input.reduce((o,{ location, ...e },i) =>
({
...o,
...Object.entries(e).reduce((oe,[k,v]) => ({ ...oe, [`samples.$[l${i}].${k}`]: v }),{})
}),
{}
);
log({ $set, arrayFilters });
The Array.map() simply takes the values of the input and creates a list of identifiers to match the location values within arrayFilters. The construction of the $set statement uses Array.reduce() with two iterations being able to merge keys for each array element processed and for each key present in that array element, after removing the location from consideration since this is not being updated.
Alternately, loop with for..of:
let arrayFilters = [];
let $set = {};
for ( let [i, { location, ...e }] of Object.entries(input) ) {
arrayFilters.push({ [`l${i}.location`]: location });
for ( let [k,v] of Object.entries(e) ) {
$set[`samples.$[l${i}].${k}`] = v;
}
}
Note we use Object.entries() here as well as the "object spread" ... in construction. If you find yourself in a JavaScript environment without this support, then Object.keys() and Object.assign() are basically drop in replacements with little change.
Then those can actually be applied within an update as in:
Project.update({ client_id: 'ClientA' }, { $set }, { arrayFilters });
So the positional filtered $[<identifier>] is actually used here to create "matching pairs" of entries within the $set modifier and within the arrayFilters option of the update(). So for each "location" we create an identifier that matches that value within the arrayFilters and then use that same identifier within the actual $set statement in order to just update the array entry which matches the condition for the identifier.
The only real rule with "identifiers" is that that cannot start with a number, and they "should" be unique but it's not a rule and you simply get the first match anyway. But the updates then only touch those entries which actually match the condition.
Ealier MongoDB fixed Indexes
Failing having support for that, then you are basically falling back to "index positions" and that's really not that reliable. More often than not you will actually need to read each document and determine what is in the array already before even updating. But with at least presumed "parity" where index positions are in place then:
let input = [
{ location: "A", concentration: 3 },
{ location: "B", concentration: 5 },
{ location: "C", concentration: 4 }
];
let $set = input.reduce((o,e,i) =>
({ ...o, [`samples.${i}.concentration`]: e.concentration }),{}
);
log({ $set });
Producing an update statement like:
{
"$set": {
"samples.0.concentration": 3,
"samples.1.concentration": 5,
"samples.2.concentration": 4
}
}
Or without the parity:
let input = [
{ location: "A", concentration: 3, other: "c" },
{ location: "C", concentration: 4, other: "a" }
];
// Need to get the document to compare without parity
let doc = await Project.findOne({ "client_id": "ClientA" });
let $set = input.reduce((o,e,i) =>
({
...o,
...Object.entries(e).filter(([k,v]) => k !== "location")
.reduce((oe,[k,v]) =>
({
...oe,
[`samples.${doc.samples.map(c => c.location).indexOf(e.location)}`
+ `.${k}`]: v
}),
{}
)
}),
{}
);
log({ $set });
await Project.update({ client_id: 'ClientA' },{ $set });
Producing the statement matching on the indexes ( after you actually read the document ):
{
"$set": {
"samples.0.concentration": 3,
"samples.0.other": "c",
"samples.2.concentration": 4,
"samples.2.other": "a"
}
}
Noting of course that for each "update set" you really don't have any other option than to read from the document first to determine which indexes you will update. This generally is not a good idea as aside from the overhead of needing to read each document before a write, there is no absolute guarantee that the array itself remains unchanged by other processes in between the read and the write, so using a "hard index" is making the presumption that everything is still the same, when that may not actually be the case.
Earlier MongoDB positional matches
Where data permits it's generally better to cycle standard positional matched $ updates instead. Here location is indeed unique so it's a good candidate, and most importantly you do not need read the existing documents to compare arrays for indexes:
let input = [
{ location: "A", concentration: 3, other: "c" },
{ location: "C", concentration: 4, other: "a" }
];
let batch = input.map(({ location, ...e }) =>
({
updateOne: {
filter: { client_id: "ClientA", 'samples.location': location },
update: {
$set: Object.entries(e)
.reduce((oe,[k,v]) => ({ ...oe, [`samples.$.${k}`]: v }), {})
}
}
})
);
log({ batch });
await Project.bulkWrite(batch);
A bulkWrite() sends multiple update operations, but it does so with a single request and response just like any other update operation. Indeed if you are processing a "list of changes" then returning the document for comparison of each and then constructing one big bulkWrite() is the direction to go in instead of individual writes, and that actually even applies to all previous examples as well.
The big difference is "one update instruction per array element" in the change set. This is the safe way to do things in releases without "positional filtered" support, even if it means more write operations.
Demonstration
A full listing in demonstration follows. Note I'm using "mongoose" here for simplicity, but there is nothing really "mongoose specific" about the actual updates themselves. The same applies to any implementation, and particular in this case the JavaScript examples of using Array.map() and Array.reduce() to process the list for construction.
const { Schema } = mongoose = require('mongoose');
const uri = 'mongodb://localhost/test';
mongoose.Promise = global.Promise;
mongoose.set('debug',true);
const sampleSchema = new Schema({
location: String,
name: String,
concentration: Number,
other: String
});
const projectSchema = new Schema({
client_id: String,
description: String,
samples: [sampleSchema]
});
const Project = mongoose.model('Project', projectSchema);
const log = data => console.log(JSON.stringify(data, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri);
await Promise.all(Object.entries(conn.models).map(([k,m]) => m.remove()));
await Project.create({
client_id: "ClientA",
description: "A Client",
samples: [
{ location: "A", name: "Location A" },
{ location: "B", name: "Location B" },
{ location: "C", name: "Location C" }
]
});
let input = [
{ location: "A", concentration: 3, other: "c" },
{ location: "C", concentration: 4, other: "a" }
];
let arrayFilters = input.map(({ location },i) => ({ [`l${i}.location`]: location }));
let $set = input.reduce((o,{ location, ...e },i) =>
({
...o,
...Object.entries(e).reduce((oe,[k,v]) => ({ ...oe, [`samples.$[l${i}].${k}`]: v }),{})
}),
{}
);
log({ $set, arrayFilters });
await Project.update(
{ client_id: 'ClientA' },
{ $set },
{ arrayFilters }
);
let project = await Project.findOne();
log(project);
mongoose.disconnect();
} catch(e) {
console.error(e)
} finally {
process.exit()
}
})()
And the output for those who cannot be bothered to run, shows the matching array elements updated:
Mongoose: projects.remove({}, {})
Mongoose: projects.insertOne({ _id: ObjectId("5b1778605c59470ecaf10fac"), client_id: 'ClientA', description: 'A Client', samples: [ { _id: ObjectId("5b1778605c59470ecaf10faf"), location: 'A', name: 'Location A' }, { _id: ObjectId("5b1778605c59470ecaf10fae"), location: 'B', name: 'Location B' }, { _id: ObjectId("5b1778605c59470ecaf10fad"), location: 'C', name: 'Location C' } ], __v: 0 })
{
"$set": {
"samples.$[l0].concentration": 3,
"samples.$[l0].other": "c",
"samples.$[l1].concentration": 4,
"samples.$[l1].other": "a"
},
"arrayFilters": [
{
"l0.location": "A"
},
{
"l1.location": "C"
}
]
}
Mongoose: projects.update({ client_id: 'ClientA' }, { '$set': { 'samples.$[l0].concentration': 3, 'samples.$[l0].other': 'c', 'samples.$[l1].concentration': 4, 'samples.$[l1].other': 'a' } }, { arrayFilters: [ { 'l0.location': 'A' }, { 'l1.location': 'C' } ] })
Mongoose: projects.findOne({}, { fields: {} })
{
"_id": "5b1778605c59470ecaf10fac",
"client_id": "ClientA",
"description": "A Client",
"samples": [
{
"_id": "5b1778605c59470ecaf10faf",
"location": "A",
"name": "Location A",
"concentration": 3,
"other": "c"
},
{
"_id": "5b1778605c59470ecaf10fae",
"location": "B",
"name": "Location B"
},
{
"_id": "5b1778605c59470ecaf10fad",
"location": "C",
"name": "Location C",
"concentration": 4,
"other": "a"
}
],
"__v": 0
}
Or by hard index:
const { Schema } = mongoose = require('mongoose');
const uri = 'mongodb://localhost/test';
mongoose.Promise = global.Promise;
mongoose.set('debug',true);
const sampleSchema = new Schema({
location: String,
name: String,
concentration: Number,
other: String
});
const projectSchema = new Schema({
client_id: String,
description: String,
samples: [sampleSchema]
});
const Project = mongoose.model('Project', projectSchema);
const log = data => console.log(JSON.stringify(data, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri);
await Promise.all(Object.entries(conn.models).map(([k,m]) => m.remove()));
await Project.create({
client_id: "ClientA",
description: "A Client",
samples: [
{ location: "A", name: "Location A" },
{ location: "B", name: "Location B" },
{ location: "C", name: "Location C" }
]
});
let input = [
{ location: "A", concentration: 3, other: "c" },
{ location: "C", concentration: 4, other: "a" }
];
// Need to get the document to compare without parity
let doc = await Project.findOne({ "client_id": "ClientA" });
let $set = input.reduce((o,e,i) =>
({
...o,
...Object.entries(e).filter(([k,v]) => k !== "location")
.reduce((oe,[k,v]) =>
({
...oe,
[`samples.${doc.samples.map(c => c.location).indexOf(e.location)}`
+ `.${k}`]: v
}),
{}
)
}),
{}
);
log({ $set });
await Project.update(
{ client_id: 'ClientA' },
{ $set },
);
let project = await Project.findOne();
log(project);
mongoose.disconnect();
} catch(e) {
console.error(e)
} finally {
process.exit()
}
})()
And the output:
Mongoose: projects.remove({}, {})
Mongoose: projects.insertOne({ _id: ObjectId("5b1778e0f7be250f2b7c3fc8"), client_id: 'ClientA', description: 'A Client', samples: [ { _id: ObjectId("5b1778e0f7be250f2b7c3fcb"), location: 'A', name: 'Location A' }, { _id: ObjectId("5b1778e0f7be250f2b7c3fca"), location: 'B', name: 'Location B' }, { _id: ObjectId("5b1778e0f7be250f2b7c3fc9"), location: 'C', name: 'Location C' } ], __v: 0 })
Mongoose: projects.findOne({ client_id: 'ClientA' }, { fields: {} })
{
"$set": {
"samples.0.concentration": 3,
"samples.0.other": "c",
"samples.2.concentration": 4,
"samples.2.other": "a"
}
}
Mongoose: projects.update({ client_id: 'ClientA' }, { '$set': { 'samples.0.concentration': 3, 'samples.0.other': 'c', 'samples.2.concentration': 4, 'samples.2.other': 'a' } }, {})
Mongoose: projects.findOne({}, { fields: {} })
{
"_id": "5b1778e0f7be250f2b7c3fc8",
"client_id": "ClientA",
"description": "A Client",
"samples": [
{
"_id": "5b1778e0f7be250f2b7c3fcb",
"location": "A",
"name": "Location A",
"concentration": 3,
"other": "c"
},
{
"_id": "5b1778e0f7be250f2b7c3fca",
"location": "B",
"name": "Location B"
},
{
"_id": "5b1778e0f7be250f2b7c3fc9",
"location": "C",
"name": "Location C",
"concentration": 4,
"other": "a"
}
],
"__v": 0
}
And of course with standard "positional" $ syntax and updates:
const { Schema } = mongoose = require('mongoose');
const uri = 'mongodb://localhost/test';
mongoose.Promise = global.Promise;
mongoose.set('debug',true);
const sampleSchema = new Schema({
location: String,
name: String,
concentration: Number,
other: String
});
const projectSchema = new Schema({
client_id: String,
description: String,
samples: [sampleSchema]
});
const Project = mongoose.model('Project', projectSchema);
const log = data => console.log(JSON.stringify(data, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri);
await Promise.all(Object.entries(conn.models).map(([k,m]) => m.remove()));
await Project.create({
client_id: "ClientA",
description: "A Client",
samples: [
{ location: "A", name: "Location A" },
{ location: "B", name: "Location B" },
{ location: "C", name: "Location C" }
]
});
let input = [
{ location: "A", concentration: 3, other: "c" },
{ location: "C", concentration: 4, other: "a" }
];
let batch = input.map(({ location, ...e }) =>
({
updateOne: {
filter: { client_id: "ClientA", 'samples.location': location },
update: {
$set: Object.entries(e)
.reduce((oe,[k,v]) => ({ ...oe, [`samples.$.${k}`]: v }), {})
}
}
})
);
log({ batch });
await Project.bulkWrite(batch);
let project = await Project.findOne();
log(project);
mongoose.disconnect();
} catch(e) {
console.error(e)
} finally {
process.exit()
}
})()
And output:
Mongoose: projects.remove({}, {})
Mongoose: projects.insertOne({ _id: ObjectId("5b179142662616160853ba4a"), client_id: 'ClientA', description: 'A Client', samples: [ { _id: ObjectId("5b179142662616160853ba4d"), location: 'A', name: 'Location A' }, { _id: ObjectId("5b179142662616160853ba4c"), location: 'B', name: 'Location B' }, { _id: ObjectId("5b179142662616160853ba4b"), location: 'C', name: 'Location C' } ], __v: 0 })
{
"batch": [
{
"updateOne": {
"filter": {
"client_id": "ClientA",
"samples.location": "A"
},
"update": {
"$set": {
"samples.$.concentration": 3,
"samples.$.other": "c"
}
}
}
},
{
"updateOne": {
"filter": {
"client_id": "ClientA",
"samples.location": "C"
},
"update": {
"$set": {
"samples.$.concentration": 4,
"samples.$.other": "a"
}
}
}
}
]
}
Mongoose: projects.bulkWrite([ { updateOne: { filter: { client_id: 'ClientA', 'samples.location': 'A' }, update: { '$set': { 'samples.$.concentration': 3, 'samples.$.other': 'c' } } } }, { updateOne: { filter: { client_id: 'ClientA', 'samples.location': 'C' }, update: { '$set': { 'samples.$.concentration': 4, 'samples.$.other': 'a' } } } } ], {})
Mongoose: projects.findOne({}, { fields: {} })
{
"_id": "5b179142662616160853ba4a",
"client_id": "ClientA",
"description": "A Client",
"samples": [
{
"_id": "5b179142662616160853ba4d",
"location": "A",
"name": "Location A",
"concentration": 3,
"other": "c"
},
{
"_id": "5b179142662616160853ba4c",
"location": "B",
"name": "Location B"
},
{
"_id": "5b179142662616160853ba4b",
"location": "C",
"name": "Location C",
"concentration": 4,
"other": "a"
}
],
"__v": 0
}