Select from multiple tables in sequelize - sql

I'm struggling in how to select from two tables using the Sequelize.
Actually I'm trying to do it:
SELECT * FROM users, clients WHERE user.id = clients.user_id
I have no idea how to user two tables as I described, the only thing I did that got some results were:
const clients = await Client.findAll({
attributes: ["user_id"],
});
const users = [];
for (const client of clients) {
let user = await User.findAll({
where: {
id: {
[Op.eq]: client.user_id
}
}
});
users.push(user);
}
Which return me something:
[
[
{
"id": 1,
"first_name": "Velda",
"middle_name": "Zboncak",
"last_name": "Kris",
"email": "vkris10#hotmail.com",
"created_at": "2020-02-07T20:09:29.484Z",
"updated_at": "2020-02-07T20:09:29.484Z"
}
]
];

Model and Assossiation
First of all, you need to create the correct associations in the model of your table. In this case for the User and the Client, it's supposed to be an Client.belongsTo(...)
Take a look at User model:
const { Model, DataTypes } = require("sequelize");
class User extends Model {
static init(sequelize) {
super.init({
first_name: DataTypes.STRING,
middle_name: DataTypes.STRING,
last_name: DataTypes.STRING,
email: DataTypes.STRING
}, { sequelize });
}
}
module.exports = User;
Take a look at Client model:
const { Model, DataTypes } = require("sequelize");
class Client extends Model {
static init(sequelize) {
super.init({
user_id: DataTypes.INTEGER // The foreign key
}, { sequelize });
}
static associate(models) {
Client.belongsTo(models.User, {
foreignKey: "id", // Column name of associated table
as: "user" // Alias for the table
});
}
}
module.exports = Client;
When associating tables you need to have in mind those values inside the associate method, being the foreignKey: "id" the column name inside the models.ModelName, which will be used to make the joins, and the as: "user" which are used as an alias for the table like SELECT t.column1 FROM table AS t;
Controller
Okay, now you have set your models, you need to set your controller, where the magic happens. As you said you want to fetch results using:
SELECT * FROM users, clients WHERE user.id = clients.user_id
But to achieve the same result you can follow the sql join method to fetch the results from db, so it will be something like this:
SELECT
"user"."first_name", "user"."middle_name", "user"."last_name", "user"."email"
FROM "clients" AS "client"
LEFT JOIN "users" AS "user"
ON "client"."id" = "user"."id";
Knowing that we can talk about including tables in sequelize, which is the same as associations
const Client = require("./path/to/models/Client");
module.exports = {
async fetchAll(req, res) {
const results = await Client.findAll({
limit: 25,
include: [
{
association: "user",
attributes: ["first_name", "middle_name", "last_name", "email"]
}
]
});
return res.json(results);
},
};
Now lets talk about what is going on in the code:
The Model.findAll({}) will fetch all the result inside the specified table, in this case clients table.
The limit: 25 will limit your results in only 25 rows, you are free to remove or edit as you need.
The include: [], it will do the joins through the tables you specify, as you need only the users table, we are going to use only one object, so the assossiation: "user" will make this connection between tables, you must use the same alias you set inside the model. And at least the attributes: ["columns"] is where you set all the fields you want to fetch.
And that's it, you make you request, and the result of this will be exactly the same join as I mentioned. And the results will be:
[
{
"id": 1,
"user_id": 1,
"user": {
"first_name": "John",
"middle_name": "Ironsight",
"last_name": "Doe",
"email": "johndoe#example.com"
}
}, {...}
]

Can use where in include. Find the document at here
let user_id = client.user_id;
users = await User.findAll({
include: [
{
model: Client,
as: 'client',
where: {
user_id: user_id
}
}
]
});

Related

Join two collection in mongodb

I'm new in mongodb. Could you please tell me how to perform join operation in this. I've two collection:
Collection 1 ("user")
{
_id: "d04d53dc-fb88-433e-a1c5-dd41a68d7655",
userName: "XYZ User",
age: 12
}
Collection 2 ("square")
{
_id: "ef6f6ac2-a08a-4f68-a63c-0b4a70285427",
userId: "d04d53dc-fb88-433e-a1c5-dd41a68d7655",
side: 4,
area: 16
}
Now I want to retrieve the data from collection 2 is like this.
Expected output:
{
_id: "ef6f6ac2-a08a-4f68-a63c-0b4a70285427",
userId: "d04d53dc-fb88-433e-a1c5-dd41a68d7655",
userName: "XYZ User",
side: 4,
area: 16
}
Thanks in advance :)
Here's one way to do it.
db.square.aggregate([
{
"$lookup": {
"from": "user",
"localField": "userId",
"foreignField": "_id",
"as": "userDoc"
}
},
{
"$set": {
"userName": {
"$first": "$userDoc.userName"
}
}
},
{ "$unset": "userDoc" }
])
Try it on mongoplayground.net.
You can keep the first documentid (_id) in the second document as userId for refrence and after that, you can use the join feature supported by MongoDB 3.2 and later versions. You can use joins by using an aggregate query.
You can do it using the below example :
db.user.aggregate([
// Join with square table
{
$lookup:{
from: "square", // other table name
localField: "_id", // name of user table field
foreignField: "userId", // name of square table field
as: "square" // alias for userinfo table
}
},
{ $unwind:"$user_info" }, // $unwind used for getting data in object or for one record only
// define some conditions here
{
$match:{
$and:[{"userName" : "XYZ User"}]
}
},
// define which fields are you want to fetch
{
$project:{
_id: 1,
userId: "$square.userId",
userName: 1,
side: "$square.side",
area: "$square.area"
}
}
]);
The Result will be
{
_id: "ef6f6ac2-a08a-4f68-a63c-0b4a70285427",
userId: "d04d53dc-fb88-433e-a1c5-dd41a68d7655",
userName: "XYZ User",
side: 4,
area: 16
}
Cheers

Seqeulize query a table with multiple where values for same column?

I have a sequelize query that looks like
const deliveriesToCancel = await Model.ShipperContract.findByPk(organizationId, {
include: [
{
model: Model.Order,
as: organizationId,
include: [
{
model: Model.Delivery,
as: "deliveries",
where: {
state: {
[Op.not]: "DELIVERED" || "CANCELED_BYL" || "CANCELED_BY_SHIPPER"
}
}
},
],
},
],
});
Is it possible to query on Delivery table with 3 possible choices for state column? or in this case, WHERE !== those 3 values?
How can I write taht in seqeulize?
If you want to select the deliveries where "state" isn't any of "DELIVERED", "CANCELED_BYL", or "CANCELED_BY_SHIPPER", you can use:
where: {
state: {
[Op.notIn]: ["DELIVERED", "CANCELED_BYL", "CANCELED_BY_SHIPPER"]
}
}
Note:
WHERE NOT IN can be slow. If your dataset is huge and your query is slow, consider looking into modifying it to an exists. Docs, Docs

How to create or update many-to-many relation in Prisma?

I have the following models, and many-to-many relation between them:
model User {
id String #id #default(cuid())
name String?
email String? #unique
followings Artist[]
}
model Artist {
id String #id #default(cuid())
name String #unique
spotifyId String #unique
followers User[]
}
When a user logs into my app, I retrieve their current followed artists, and need to update my database.
I have managed to select artists data from database (for updating user <-> artist relation), sample data:
const followings = [
{
id: '...',
name: 'MARINA',
spotifyId: '6CwfuxIqcltXDGjfZsMd9A'
},
{
id: '...',
name: 'Dua Lipa',
spotifyId: '6M2wZ9GZgrQXHCFfjv46we'
},
]
Now, this is my user object:
const user = {
id: 'someId',
name: 'someName',
email: 'someEmail'
}
I tried to insert or update user <-> artist relation with this query but I'm getting Bad Request error:
await prisma.user.upsert({
where: {
email: user.email
},
create: {
name: user.name,
email: user.email,
followings: {
connectOrCreate: followings
}
},
update: {
followings: {
connectOrCreate: followings
}
}
})
Please advise what I need to do. Thanks in advance.
P.S. I took the idea of the query from Updating a many-to-many relationship in Prisma post, but it didn't work for me, so please don't mark duplicate.
connectOrCreate should specify where key with id (so Prisma could find this entity) and create key with all required model fields (so Prisma could create it if it not already present), but you just passing an array of models. Change your code to this one:
await prisma.user.upsert({
where: {
email: 'user.email',
},
create: {
name: 'user.name',
email: 'user.email',
followings: {
connectOrCreate: [
{
create: {
name: 'MARINA',
spotifyId: '6CwfuxIqcltXDGjfZsMd9A',
},
where: { id: '...' },
},
],
},
},
update: {
followings: {
connectOrCreate: [
{
create: {
name: 'MARINA',
spotifyId: '6CwfuxIqcltXDGjfZsMd9A',
},
where: { id: '...' },
},
],
},
},
});

Removing join table data in sequelize returned value

I am currently trying to remove a joint table data added when retrieving an association data.
The query is done by sequelize using a method added to the model through specifying model relationships(sequelize magic methods), for some reason, I'm not able to do that.
I have currently tried passing in attributes: {exclude: ['...']} to the method but the field still persists.
Current association
// Class sequelize model
Class.belongsToMany(models.Subject, {
through: 'ClassSubject',
foreignKey: 'class_id',
otherKey: 'subject_id',
as: 'subjects'
})
// Subject sequelize model
Subject.belongsToMany(models.Class, {
through: 'ClassSubject',
foreignKey: 'subject_id',
otherKey: 'class_id',
as: 'classes'
});
Query and Response
const subjects = await dbClass.getSubjects(); // dbClass is a Class model instance
// Response
[
{
"id": "1b89d44c-2caa-452d-a1f8-7faa11970917",
"name": "Mathematics",
"code": "MATHS",
"summary": "Mathematics for class 1",
"ClassSubject": {
"class_id": "637afc7b-40f6-478e-b35e-859ca462e2e7",
"subject_id": "1b89d44c-2caa-452d-a1f8-7faa11970917"
}
}
]
Desired output
// Response
[
{
"id": "1b89d44c-2caa-452d-a1f8-7faa11970917",
"name": "Mathematics",
"code": "MATHS",
"summary": "Mathematics for class 1"
}
]
I have tried passing options to the method as specified below but to no avail
const subjects = await dbClass.getSubjects({
attributes: { exclude: ['ClassSubject'] }
});
But it still doesn't work.
Try using the joinTableAttributes option and pass empty array to exclude everything in joint table.
const subjects = await dbClass.getSubjects({ joinTableAttributes: [] });

How to configure Typegoose with GraphQL to reference subdocument to part of another document? [duplicate]

I'm pretty new to Mongoose and MongoDB in general so I'm having a difficult time figuring out if something like this is possible:
Item = new Schema({
id: Schema.ObjectId,
dateCreated: { type: Date, default: Date.now },
title: { type: String, default: 'No Title' },
description: { type: String, default: 'No Description' },
tags: [ { type: Schema.ObjectId, ref: 'ItemTag' }]
});
ItemTag = new Schema({
id: Schema.ObjectId,
tagId: { type: Schema.ObjectId, ref: 'Tag' },
tagName: { type: String }
});
var query = Models.Item.find({});
query
.desc('dateCreated')
.populate('tags')
.where('tags.tagName').in(['funny', 'politics'])
.run(function(err, docs){
// docs is always empty
});
Is there a better way do this?
Edit
Apologies for any confusion. What I'm trying to do is get all Items that contain either the funny tag or politics tag.
Edit
Document without where clause:
[{
_id: 4fe90264e5caa33f04000012,
dislikes: 0,
likes: 0,
source: '/uploads/loldog.jpg',
comments: [],
tags: [{
itemId: 4fe90264e5caa33f04000012,
tagName: 'movies',
tagId: 4fe64219007e20e644000007,
_id: 4fe90270e5caa33f04000015,
dateCreated: Tue, 26 Jun 2012 00:29:36 GMT,
rating: 0,
dislikes: 0,
likes: 0
},
{
itemId: 4fe90264e5caa33f04000012,
tagName: 'funny',
tagId: 4fe64219007e20e644000002,
_id: 4fe90270e5caa33f04000017,
dateCreated: Tue, 26 Jun 2012 00:29:36 GMT,
rating: 0,
dislikes: 0,
likes: 0
}],
viewCount: 0,
rating: 0,
type: 'image',
description: null,
title: 'dogggg',
dateCreated: Tue, 26 Jun 2012 00:29:24 GMT
}, ... ]
With the where clause, I get an empty array.
With a modern MongoDB greater than 3.2 you can use $lookup as an alternate to .populate() in most cases. This also has the advantage of actually doing the join "on the server" as opposed to what .populate() does which is actually "multiple queries" to "emulate" a join.
So .populate() is not really a "join" in the sense of how a relational database does it. The $lookup operator on the other hand, actually does the work on the server, and is more or less analogous to a "LEFT JOIN":
Item.aggregate(
[
{ "$lookup": {
"from": ItemTags.collection.name,
"localField": "tags",
"foreignField": "_id",
"as": "tags"
}},
{ "$unwind": "$tags" },
{ "$match": { "tags.tagName": { "$in": [ "funny", "politics" ] } } },
{ "$group": {
"_id": "$_id",
"dateCreated": { "$first": "$dateCreated" },
"title": { "$first": "$title" },
"description": { "$first": "$description" },
"tags": { "$push": "$tags" }
}}
],
function(err, result) {
// "tags" is now filtered by condition and "joined"
}
)
N.B. The .collection.name here actually evaluates to the "string" that is the actual name of the MongoDB collection as assigned to the model. Since mongoose "pluralizes" collection names by default and $lookup needs the actual MongoDB collection name as an argument ( since it's a server operation ), then this is a handy trick to use in mongoose code, as opposed to "hard coding" the collection name directly.
Whilst we could also use $filter on arrays to remove the unwanted items, this is actually the most efficient form due to Aggregation Pipeline Optimization for the special condition of as $lookup followed by both an $unwind and a $match condition.
This actually results in the three pipeline stages being rolled into one:
{ "$lookup" : {
"from" : "itemtags",
"as" : "tags",
"localField" : "tags",
"foreignField" : "_id",
"unwinding" : {
"preserveNullAndEmptyArrays" : false
},
"matching" : {
"tagName" : {
"$in" : [
"funny",
"politics"
]
}
}
}}
This is highly optimal as the actual operation "filters the collection to join first", then it returns the results and "unwinds" the array. Both methods are employed so the results do not break the BSON limit of 16MB, which is a constraint that the client does not have.
The only problem is that it seems "counter-intuitive" in some ways, particularly when you want the results in an array, but that is what the $group is for here, as it reconstructs to the original document form.
It's also unfortunate that we simply cannot at this time actually write $lookup in the same eventual syntax the server uses. IMHO, this is an oversight to be corrected. But for now, simply using the sequence will work and is the most viable option with the best performance and scalability.
Addendum - MongoDB 3.6 and upwards
Though the pattern shown here is fairly optimized due to how the other stages get rolled into the $lookup, it does have one failing in that the "LEFT JOIN" which is normally inherent to both $lookup and the actions of populate() is negated by the "optimal" usage of $unwind here which does not preserve empty arrays. You can add the preserveNullAndEmptyArrays option, but this negates the "optimized" sequence described above and essentially leaves all three stages intact which would normally be combined in the optimization.
MongoDB 3.6 expands with a "more expressive" form of $lookup allowing a "sub-pipeline" expression. Which not only meets the goal of retaining the "LEFT JOIN" but still allows an optimal query to reduce results returned and with a much simplified syntax:
Item.aggregate([
{ "$lookup": {
"from": ItemTags.collection.name,
"let": { "tags": "$tags" },
"pipeline": [
{ "$match": {
"tags": { "$in": [ "politics", "funny" ] },
"$expr": { "$in": [ "$_id", "$$tags" ] }
}}
]
}}
])
The $expr used in order to match the declared "local" value with the "foreign" value is actually what MongoDB does "internally" now with the original $lookup syntax. By expressing in this form we can tailor the initial $match expression within the "sub-pipeline" ourselves.
In fact, as a true "aggregation pipeline" you can do just about anything you can do with an aggregation pipeline within this "sub-pipeline" expression, including "nesting" the levels of $lookup to other related collections.
Further usage is a bit beyond the scope of what the question here asks, but in relation to even "nested population" then the new usage pattern of $lookup allows this to be much the same, and a "lot" more powerful in it's full usage.
Working Example
The following gives an example using a static method on the model. Once that static method is implemented the call simply becomes:
Item.lookup(
{
path: 'tags',
query: { 'tags.tagName' : { '$in': [ 'funny', 'politics' ] } }
},
callback
)
Or enhancing to be a bit more modern even becomes:
let results = await Item.lookup({
path: 'tags',
query: { 'tagName' : { '$in': [ 'funny', 'politics' ] } }
})
Making it very similar to .populate() in structure, but it's actually doing the join on the server instead. For completeness, the usage here casts the returned data back to mongoose document instances at according to both the parent and child cases.
It's fairly trivial and easy to adapt or just use as is for most common cases.
N.B The use of async here is just for brevity of running the enclosed example. The actual implementation is free of this dependency.
const async = require('async'),
mongoose = require('mongoose'),
Schema = mongoose.Schema;
mongoose.Promise = global.Promise;
mongoose.set('debug', true);
mongoose.connect('mongodb://localhost/looktest');
const itemTagSchema = new Schema({
tagName: String
});
const itemSchema = new Schema({
dateCreated: { type: Date, default: Date.now },
title: String,
description: String,
tags: [{ type: Schema.Types.ObjectId, ref: 'ItemTag' }]
});
itemSchema.statics.lookup = function(opt,callback) {
let rel =
mongoose.model(this.schema.path(opt.path).caster.options.ref);
let group = { "$group": { } };
this.schema.eachPath(p =>
group.$group[p] = (p === "_id") ? "$_id" :
(p === opt.path) ? { "$push": `$${p}` } : { "$first": `$${p}` });
let pipeline = [
{ "$lookup": {
"from": rel.collection.name,
"as": opt.path,
"localField": opt.path,
"foreignField": "_id"
}},
{ "$unwind": `$${opt.path}` },
{ "$match": opt.query },
group
];
this.aggregate(pipeline,(err,result) => {
if (err) callback(err);
result = result.map(m => {
m[opt.path] = m[opt.path].map(r => rel(r));
return this(m);
});
callback(err,result);
});
}
const Item = mongoose.model('Item', itemSchema);
const ItemTag = mongoose.model('ItemTag', itemTagSchema);
function log(body) {
console.log(JSON.stringify(body, undefined, 2))
}
async.series(
[
// Clean data
(callback) => async.each(mongoose.models,(model,callback) =>
model.remove({},callback),callback),
// Create tags and items
(callback) =>
async.waterfall(
[
(callback) =>
ItemTag.create([{ "tagName": "movies" }, { "tagName": "funny" }],
callback),
(tags, callback) =>
Item.create({ "title": "Something","description": "An item",
"tags": tags },callback)
],
callback
),
// Query with our static
(callback) =>
Item.lookup(
{
path: 'tags',
query: { 'tags.tagName' : { '$in': [ 'funny', 'politics' ] } }
},
callback
)
],
(err,results) => {
if (err) throw err;
let result = results.pop();
log(result);
mongoose.disconnect();
}
)
Or a little more modern for Node 8.x and above with async/await and no additional dependencies:
const { Schema } = mongoose = require('mongoose');
const uri = 'mongodb://localhost/looktest';
mongoose.Promise = global.Promise;
mongoose.set('debug', true);
const itemTagSchema = new Schema({
tagName: String
});
const itemSchema = new Schema({
dateCreated: { type: Date, default: Date.now },
title: String,
description: String,
tags: [{ type: Schema.Types.ObjectId, ref: 'ItemTag' }]
});
itemSchema.statics.lookup = function(opt) {
let rel =
mongoose.model(this.schema.path(opt.path).caster.options.ref);
let group = { "$group": { } };
this.schema.eachPath(p =>
group.$group[p] = (p === "_id") ? "$_id" :
(p === opt.path) ? { "$push": `$${p}` } : { "$first": `$${p}` });
let pipeline = [
{ "$lookup": {
"from": rel.collection.name,
"as": opt.path,
"localField": opt.path,
"foreignField": "_id"
}},
{ "$unwind": `$${opt.path}` },
{ "$match": opt.query },
group
];
return this.aggregate(pipeline).exec().then(r => r.map(m =>
this({ ...m, [opt.path]: m[opt.path].map(r => rel(r)) })
));
}
const Item = mongoose.model('Item', itemSchema);
const ItemTag = mongoose.model('ItemTag', itemTagSchema);
const log = body => console.log(JSON.stringify(body, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri);
// Clean data
await Promise.all(Object.entries(conn.models).map(([k,m]) => m.remove()));
// Create tags and items
const tags = await ItemTag.create(
["movies", "funny"].map(tagName =>({ tagName }))
);
const item = await Item.create({
"title": "Something",
"description": "An item",
tags
});
// Query with our static
const result = (await Item.lookup({
path: 'tags',
query: { 'tags.tagName' : { '$in': [ 'funny', 'politics' ] } }
})).pop();
log(result);
mongoose.disconnect();
} catch (e) {
console.error(e);
} finally {
process.exit()
}
})()
And from MongoDB 3.6 and upward, even without the $unwind and $group building:
const { Schema, Types: { ObjectId } } = mongoose = require('mongoose');
const uri = 'mongodb://localhost/looktest';
mongoose.Promise = global.Promise;
mongoose.set('debug', true);
const itemTagSchema = new Schema({
tagName: String
});
const itemSchema = new Schema({
title: String,
description: String,
tags: [{ type: Schema.Types.ObjectId, ref: 'ItemTag' }]
},{ timestamps: true });
itemSchema.statics.lookup = function({ path, query }) {
let rel =
mongoose.model(this.schema.path(path).caster.options.ref);
// MongoDB 3.6 and up $lookup with sub-pipeline
let pipeline = [
{ "$lookup": {
"from": rel.collection.name,
"as": path,
"let": { [path]: `$${path}` },
"pipeline": [
{ "$match": {
...query,
"$expr": { "$in": [ "$_id", `$$${path}` ] }
}}
]
}}
];
return this.aggregate(pipeline).exec().then(r => r.map(m =>
this({ ...m, [path]: m[path].map(r => rel(r)) })
));
};
const Item = mongoose.model('Item', itemSchema);
const ItemTag = mongoose.model('ItemTag', itemTagSchema);
const log = body => console.log(JSON.stringify(body, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri);
// Clean data
await Promise.all(Object.entries(conn.models).map(([k,m]) => m.remove()));
// Create tags and items
const tags = await ItemTag.insertMany(
["movies", "funny"].map(tagName => ({ tagName }))
);
const item = await Item.create({
"title": "Something",
"description": "An item",
tags
});
// Query with our static
let result = (await Item.lookup({
path: 'tags',
query: { 'tagName': { '$in': [ 'funny', 'politics' ] } }
})).pop();
log(result);
await mongoose.disconnect();
} catch(e) {
console.error(e)
} finally {
process.exit()
}
})()
what you are asking for isn't directly supported but can be achieved by adding another filter step after the query returns.
first, .populate( 'tags', null, { tagName: { $in: ['funny', 'politics'] } } ) is definitely what you need to do to filter the tags documents. then, after the query returns you'll need to manually filter out documents that don't have any tags docs that matched the populate criteria. something like:
query....
.exec(function(err, docs){
docs = docs.filter(function(doc){
return doc.tags.length;
})
// do stuff with docs
});
Try replacing
.populate('tags').where('tags.tagName').in(['funny', 'politics'])
by
.populate( 'tags', null, { tagName: { $in: ['funny', 'politics'] } } )
Update: Please take a look at the comments - this answer does not correctly match to the question, but maybe it answers other questions of users which came across (I think that because of the upvotes) so I will not delete this "answer":
First: I know this question is really outdated, but I searched for exactly this problem and this SO post was the Google entry #1. So I implemented the docs.filter version (accepted answer) but as I read in the mongoose v4.6.0 docs we can now simply use:
Item.find({}).populate({
path: 'tags',
match: { tagName: { $in: ['funny', 'politics'] }}
}).exec((err, items) => {
console.log(items.tags)
// contains only tags where tagName is 'funny' or 'politics'
})
Hope this helps future search machine users.
After having the same problem myself recently, I've come up with the following solution:
First, find all ItemTags where tagName is either 'funny' or 'politics' and return an array of ItemTag _ids.
Then, find Items which contain all ItemTag _ids in the tags array
ItemTag
.find({ tagName : { $in : ['funny','politics'] } })
.lean()
.distinct('_id')
.exec((err, itemTagIds) => {
if (err) { console.error(err); }
Item.find({ tag: { $all: itemTagIds} }, (err, items) => {
console.log(items); // Items filtered by tagName
});
});
#aaronheckmann 's answer worked for me but I had to replace return doc.tags.length; to return doc.tags != null; because that field contain null if it doesn't match with the conditions written inside populate.
So the final code:
query....
.exec(function(err, docs){
docs = docs.filter(function(doc){
return doc.tags != null;
})
// do stuff with docs
});