Should I implement auto-incrementing in MongoDB?
I'm making the switch to MongoDB from MySQL. A familiar architecture to me for a very basic users table would have auto-incrementing of the uid. See Mongo's own documentation for this use case.
I'm wondering whether this is the best architectural decision. From a UX standpoint, I like having UIDs as external references, for example in shorter URLs: http://example.com/users/12345
Is there a third way? Someone in IRC Freenode's #mongodb suggested creating a range of IDs and caching them. I'm unsure of how to actually implement that, or whether there's another route I can go. I don't necessarily even need the _id itself to be incremented this way. As long as the users all have a unique numerical uid within the document, I would be happy.
Answer
I strongly disagree with author of selected answer that No auto-increment id in MongoDB and there are good reasons. We don't know reasons why 10gen didn't encourage usage of auto-incremented IDs. It's speculation. I think 10gen made this choice because it's just easier to ensure uniqueness of 12-byte IDs in clustered environment. It's default solution that fits most newcomers therefore increases product adoption which is good for 10gen's business.
Now let me tell everyone about my experience with ObjectIds in commercial environment.
I'm building social network. We have roughly 6M users and each user has roughly 20 friends.
Now imagine we have a collection which stores relationship between users (who follows who). It looks like this
_id : ObjectId
user_id : ObjectId
followee_id : ObjectId
on which we have unique composite index {user_id, followee_id}. We can estimate size of this index to be 12*2*6M*20 = 2GB. Now that's index for fast look-up of people I follow. For fast look-up of people that follow me I need reverse index. That's another 2GB.
And this is just the beginning. I have to carry these IDs everywhere. We have activity cluster where we store your News Feed. That's every event you or your friends do. Imagine how much space it takes.
And finally one of our engineers made an unconscious decision and decided to store references as strings that represent ObjectId which doubles its size.
What happens if an index does not fit into RAM? Nothing good, says 10gen:
When an index is too large to fit into RAM, MongoDB must read the index from disk, which is a much slower operation than reading from RAM. Keep in mind an index fits into RAM when your server has RAM available for the index combined with the rest of the working set.
That means reads are slow. Lock contention goes up. Writes gets slower as well. Seeing lock contention in 80%-nish is no longer shock to me.
Before you know it you ended up with 460GB cluster which you have to split to shards and which is quite hard to manipulate.
Facebook uses 64-bit long as user id :) There is a reason for that. You can generate sequential IDs
- using 10gen's advice.
- using mysql as storage of counters (if you concerned about speed take a look at handlersocket)
- using ID generating service you built or using something like Snowflake by Twitter.
So here is my general advice to everyone. Please please make your data as small as possible. When you grow it will save you lots of sleepless nights.