I have two schemas:
var ShelfSchema = new Schema({
...
tags: [{
type: Schema.Types.ObjectId,
ref: 'Tag'
}]
});
var TagSchema = new Schema({
name: {
type: String,
unique: true,
required: true
}
});
I would like to search for all Shelves where the tags array has a tag with a specific value.
I have tried using:
modelShelf.find({tags 'tags.name': 'mytag'})...
but it does not work. It always returns an empty array.
Any idea?
Looking at db each Shelf instance links only the objectID of the tags.
I have used references because I need to work also with Tag(s) entities.
In mongoDB you essentially can't do this directly as queries target a single collection at a time. Recently there were added new features which allow some kind of join when using the aggregation framework but for your needs that is not necessary.
From your schemas I see that the tags' names are unique so you can first fetch your desired tag with something like
modelTag.find({name: 'mytag'})
in order to get the tag's ID and then query your shelf collection for this tag ID
modelShelf.find({tags: tagId})
Here is my current Schema
Brand:
var mongoose = require('mongoose');
var Schema = mongoose.Schema;
var BrandSchema = new mongoose.Schema({
name: { type: String, lowercase: true , unique: true, required: true },
photo: { type: String , trim: true},
email: { type: String , lowercase: true},
year: { type: Number},
timestamp: { type : Date, default: Date.now },
description: { type: String},
location: { },
social: {
website: {type: String},
facebook: {type: String },
twitter: {type: String },
instagram: {type: String }
}
});
Style:
var mongoose = require('mongoose');
var Schema = mongoose.Schema;
var StyleSchema = new mongoose.Schema({
name: { type: String, lowercase: true , required: true},
});
Product
var mongoose = require('mongoose');
var Schema = mongoose.Schema;
var ProductSchema = new mongoose.Schema({
name: { type: String, lowercase: true , required: true},
brandId : {type: mongoose.Schema.ObjectId, ref: 'Brand'},
styleId: {type: mongoose.Schema.ObjectId, ref: 'Style'},
year: { type: Number },
avgRating: {type: Number}
});
Post:
var mongoose = require('mongoose');
var Schema = mongoose.Schema;
var PostSchema = new mongoose.Schema({
rating: { type: Number},
upVote: {type: Number},
brandId : {type: mongoose.Schema.ObjectId, ref: 'Brand'},
comment: {type: String},
productId: {type: mongoose.Schema.ObjectId, ref: 'Style'},
styleId: {type: mongoose.Schema.ObjectId, ref: 'Style'},
photo: {type: String}
});
I'm currently making use of the mongoose populate feature:
exports.productsByBrand = function(req, res){
Product.find({product: req.params.id}).populate('style').exec(function(err, products){
res.send({products:products});
});
};
This works, however, being a noob --- i've started reading about performance issues with the mongoose populate, since it's really just adding an additional query.
For my post , especially, it seems that could be taxing. The intent for the post is to be a live twitter / instagram-like feed. It seems that could be a lot of queries, which could greatly slow my app down.
also, I want to be able to search prodcuts / post / brand by fields at some point.
Should i consider nesting / embedding this data (products nested / embedded in brands)?
What's the most efficient schema design or would my setup be alright -- given what i've specified I want to use it for?
User story:
There will be an Admin User.
The admin will be able to add the Brand with the specific fields in the Brand Schema.
Brands will have associated Products, each Product will have a Style / category.
Search:
Users will be able to search Brands by name and location (i'm looking into doing this with angular filtering / tags).
Users will be able to search Products by fields (name, style, etc).
Users will be able to search Post by Brand Product and Style.
Post:
Users will be able to Post into a feed. When making a Post, they will choose a Brand and a Product to associate the Post with. The Post will display the Brand name, Product name, and Style -- along with newly entered Post fields (photo, comment, and rating).
Other users can click on the Brand name to link to the Brand show page. They can click on the Product name to link to a Product show page.
Product show page:
Will show Product fields from the above Schema -- including associated Style name from Style schema. It will also display Post pertaining to the specific Product.
Brand show page:
Will simply show Brand fields and associated products.
My main worry is the Post, which will have to populate / query for the Brand , Product, and Style within a feed.
Again, I'm contemplating if I should embed the Products within the Brand -- then would I be able to associate the Brand Product and Style with the Post for later queries? Or, possibly $lookup or other aggregate features.
Mongodb itself does not support joins. So, mongoose populate is an attempt at external reference resolution. The thing with mongodb is that you need to design your data so that:
most of you queries need not to refer multiple collections.
after getting data from query, you need not to transform it too much.
Consider the entities involved, and their relations:
Brand is brand. Doesn't depend on anything else.
Every Product belongs to a Brand.
Every Product is associated with a Style.
Every Post is associated with a Product.
Indirectly, every Post is associated to a Brand and Style, via product.
Now about the use cases:
Refer: If you are looking up one entity by id, then fetching 1-2 related entities is not really a big overhead.
List: It is when you have to return a large set of objects and each object needs an additional query to get associated objects. This is a performance issue. This is usually reduced by processing "pages" of result set at a time, say 20 records per request. Lets suppose you query 20 products (using skip and limit). For 20 products you extract two id arrays, one of referred styles, and other of referred brands. You do 2 additional queries using $in:[ids], get brands and styles object and place them in result set. That's 3 queries per page. Users can request next page as they scroll down, and so on.
Search: You want to search for products, but also want to specify brand name and style name. Sadly, product model only holds ids for style and brand. Same issue with searching Posts with brand and product. Popular solution is to maintain a separate "search index", a sort of table, that stores data exactly the way it will be searched for, with all searchable fields (like brand name, style name) at one place. Maintaining such search collections in mongodb manually can be a pain. This is where ElasticSearch comes in. Since you are already using mongoose, you can simply add mongoosastic to your models. ElasticSearch's search capabilities are far greater than a DB Storage engine will offer you.
Extra Speed: There is still some room for speeding things up: Caching. Attach mongoose-redis-cache and have frequent repeated queries served, in-memory from Redis, reducing load on mongodb.
Twitter like Feeds: Now if all Posts are public then listing them up for users in chronological order is a trivial query. However things change when you introduce "social networking" features. Then you need to list "activity feeds" of friends and followers. There's some wisdom about social inboxes and Fan-out lists in mongodb blog.
Moral of the story is that not all use cases have only "db schema query" solutions. Scalability is one of such cases. That's why other tools exist.
I would like to sort my Group-Model by the name of the departure_country with mongoose-paginate and NodeJS.
My Group-Schema:
var GroupSchema = new Schema({
name: String,
flight_date: Date,
....
departure_country: {type: Schema.ObjectId, ref: 'Country'},
....
});
The Country-Schema:
var CountrySchema = new Schema({
name: String,
code: String,
});
Using the sortBy-option of mongoose-paginate sorts by the country's _ids and I don't know how to tell it to sort by the name.
how about making the country code the _id of Country-Schema?
then departure_country: {type: String, ref: 'Country'}
That might actually be a better design. Country-Schemas _id would be small, and country codes shouldn't have collisions. Also in GroupSchema you'd use less space to store the "foreign key" departure_country.
then you'd be able to sort by departure_country and there's a chance the sort would also be valid for country name.
Is there a way for checking if a reference document id exists in the array field of its "parent" model?
Imagine you know the objectId you want to check if exists because you don't want duplicates and also want to avoid that an error was thrown when trying to insert it.
I would like to know if there is an elegant and simple way as the method mongoose provides when working with subdocuments: var doc = car._components.id(theComponentIdIWantToCheck)
In this case it is a reference document:
Example:
// Car.js
var CarSchema = new Schema({
name: String,
description: String,
_components: [ { type: Schema.Types.ObjectId, ref: 'Component'},]
});
I have a model "Category". Collection categories contains several objects.
I also a have model "Post". Collection posts may contain a lot of objects with users' posts. "Post" object may relate to 1+ categories. How to link "Post" object to 1+ "Category"-objects without placing "Post"-object inside "Category"-object as subdocument? Certainly, I need to have an option to find all posts related to certain category.
One of the ways I can imagine is to store in "Post"-object obj_id of all categories which it's related to. Smth like this:
var postSchema = mongoose.Schema({
title: String,
description: String,
category: [ObjectId],
created_time: Number,
})
and add category later...
post.category.push(obj_id);
but is it really a mongoose-way? Which way is correct? Thanks.
P.S. I've also read about population methods in mongoose docs, may it be useful in my case? Still not completely clear for me what is this.
Populate is a better tool for this since you are creating a many to many relationship between posts and categories. Subdocuments are appropriate when they belong exclusively to the parent object. You will need to change your postSchema to use a reference:
var postSchema = mongoose.Schema({
title: String,
description: String,
category: [{ type: Schema.Types.ObjectId, ref: 'Category' }],
created_time: Number,
});
You can add categories by pushing documents onto the array:
post.category.push(category1);
post.save(callback);
Then rehydrate them during query using populate:
Post.findOne({ title: 'Test' })
.populate('category')
.exec(function (err, post) {
if (err) return handleError(err);
console.log(post.category);
});