CODEWITHSUNDEEP
mysqlsocial-networking
TwilightSun
TwilightSun

Reputation: 2335

How did Facebook or Twitter implement their subscribe system

I'm working on a SNS like mobile app project, where users upload their contents and can see updates of their subscribed topic or friends on their homepage.

I store user contents in mysql, and query the user specific homepage data by simply querying out first who and what the user subscribed and then query the content table filtering out using the 'where userid IN (....) or topic IN (....)' clause.

I suspect this would become quite slow when the content table piles up or when a user subscribe tons of users or topics. Our newly released app is already starting to have thousands of new users each week, and getting more over time. Scalability must be a concern for us right now.

So I wonder how Facebook or Twitter handle this subscribing problem with their amazing number of users. Do they handle a list for each user? I tried to search, but all I got is how to interact with Facebook or Twitter rather than how they actually implement this feature.

I noticed that you see only updates rather than history in your feed when using Facebook. Which means that subscribing a new user won't dump lots out dated content into your feed as how it would be by using my current method.

How do Facebook design their database and how did they dispatch new contents to subscribed users?

My backend is currently PHP+MySQL, and I don't mind introducing other backend technologies such as Redis or JMS and stuff if that's the way it should be done.

Upvotes: 1

Views: 146

Answers (1)

Jack
Jack

Reputation: 417

Sounds like you guys are still in a pretty early stage. There are N-number of ways to solve this, all depending on which stage of DAUs you think you'll hit in the near term, how much money you have to spend on hardware, time in your hands to build it, etc.

You can try an interim table that queues up the newly introduced items, its meta-data on what it entails (which topic, friend user_id list, etc.). Then use a queue-consumer system like RabbitMQ/GearMan to manage the consumption of this growing list, and figure out who should process this. Build the queue-consumer program in Scala or a J2EE system like Maven/Tomcat, something that can persist. If you really wanna stick with PHP, build a PHP REST API that can live in php5-fpm's memory, and managed by the FastCGI process manager, and called via a proxy like nginx, initiated by curl calls at an appropriate interval from a cron executed script.

[EDIT] - It's probably better to not use a DB for a queueing system, use a cache server like Redis, it outperforms a DB in many ways and it can persist to disk (lookup RDB and AOF). It's not very fault tolerant in case the job fails all of a sudden, you might lose a job record. Most likely you won't care on these crash edge cases. Also lookup php-resque!

To prep for the SNS to go out efficiently, I'm assuming you're already de-normalizing the tables. I'd imagine a "user_topic" table with the topic mapped to users who subscribed to them. Create another table "notification_metadata" describing where users prefer receiving notifications (SMS/push/email/in-app notification), and the meta-data needed to push to those channels (mobile client approval keys for APNS/GCM, email addresses, user auth-tokens). Use JSON blobs for the two fields in notification_metadata, so each user will have a single row. This saves I/O hits on the DB.

Use user_id as your primary key for "notification_meta" and user_id + topic_id as PK for "user_topic". DO NOT add an auto-increment "id" field for either, it's pretty useless in this use case (takes up space, CPU, index memory, etc). If both fields are in the PK, queries on user_topic will be all from memory, and the only disk hit is on "notification_meta" during the JOIN.

So if a user subscribes to 2 topics, there'll be two entries in "user_topic", and each user will always have a single row in "notification_meta"

There are more ways to scale, like dynamically creating a new table for each new topic, sharding to different MySQL instances based on user_id, partitioning, etc. There's N-ways to scale, especially in MySQL. Good luck!

Upvotes: 2

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