Querying MongoDB (Using Edge Collection - The most efficient way?) - mongodb

Question

I've written Users, Clubs and Followers collections for the sake of an example the below.
I want to find all user documents from the Users collection that are following "A famous club". How can I find those? and Which way is the fastest?
More info about 'what do I want to do - Edge collections'
Users collection
{
"_id": "1",
"fullname": "Jared",
"country": "USA"
}
Clubs collection
{
"_id": "12",
"name": "A famous club"
}
Followers collection
{
"_id": "159",
"user_id": "1",
"club_id": "12"
}
PS: I can get the documents using Mongoose like the below way. However, creating followers array takes about 8 seconds with 150.000 records. And second find query -which is queried using followers array- takes about 40 seconds. Is it normal?
Clubs.find(
{ club_id: "12" },
'-_id user_id', // select only one field to better perf.
function(err, docs){
var followers = [];
docs.forEach(function(item){
followers.push(item.user_id)
})
Users.find(
{ _id:{ $in: followers } },
function(error, users) {
console.log(users) // RESULTS
})
})

Answer 1

There is no an eligible formula to manipulate join many-to-many relation on MongoDB. So I combined collections as embedded documents like the below. But the most important taks in this case creating indexes. For instance if you want to query by followingClubs you should create an index like schema.index({ 'followingClubs._id':1 }) using Mongoose. And if you want to query country and followingClubs you should create another index like schema.index({ 'country':1, 'followingClubs._id':1 })
Pay attention when working with Embedded Documents: http://askasya.com/post/largeembeddedarrays
Then you can get your documents fastly. I've tried to get count of 150.000 records using this way it took only 1 second. It's enough for me...
ps: we musn't forget that in my tests my Users collection has never experienced any data fragmentation. Therefore my queries may demonstrated good performance. Especially, followingClubs array of embedded documents.
Users collection
{
"_id": "1",
"fullname": "Jared",
"country": "USA",
"followingClubs": [ {"_id": "12"} ]
}
Clubs collection
{
"_id": "12",
"name": "A famous club"
}