问题
I have always wondered how Facebook designed the friend <-> user relation.
I figure the user table is something like this:
user_email PK
user_id PK
password
I figure the table with user's data (sex, age etc connected via user email I would assume).
How does it connect all the friends to this user?
Something like this?
user_id
friend_id_1
friend_id_2
friend_id_3
friend_id_N
Probably not. Because the number of users is unknown and will expand.
回答1:
Keep a friend table that holds the UserID and then the UserID of the friend (we will call it FriendID). Both columns would be foreign keys back to the Users table.
Somewhat useful example:
Table Name: User
Columns:
UserID PK
EmailAddress
Password
Gender
DOB
Location
TableName: Friends
Columns:
UserID PK FK
FriendID PK FK
(This table features a composite primary key made up of the two foreign
keys, both pointing back to the user table. One ID will point to the
logged in user, the other ID will point to the individual friend
of that user)
Example Usage:
Table User
--------------
UserID EmailAddress Password Gender DOB Location
------------------------------------------------------
1 bob@bob.com bobbie M 1/1/2009 New York City
2 jon@jon.com jonathan M 2/2/2008 Los Angeles
3 joe@joe.com joseph M 1/2/2007 Pittsburgh
Table Friends
---------------
UserID FriendID
----------------
1 2
1 3
2 3
This will show that Bob is friends with both Jon and Joe and that Jon is also friends with Joe. In this example we will assume that friendship is always two ways, so you would not need a row in the table such as (2,1) or (3,2) because they are already represented in the other direction. For examples where friendship or other relations aren't explicitly two way, you would need to also have those rows to indicate the two-way relationship.
回答2:
Have a look at the following database schema, reverse engineered by Anatoly Lubarsky:
回答3:
TL;DR:
They use a stack architecture with cached graphs for everything above the MySQL bottom of their stack.
Long Answer:
I did some research on this myself because I was curious how they handle their huge amount of data and search it in a quick way. I've seen people complaining about custom made social network scripts becoming slow when the user base grows. After I did some benchmarking myself with just 10k users and 2.5 million friend connections - not even trying to bother about group permissions and likes and wall posts - it quickly turned out that this approach is flawed. So I've spent some time searching the web on how to do it better and came across this official Facebook article:
- TAO: Facebook’s Distributed Data Store for the Social Graph
- TAO: The power of the graph.
I really recommend you to watch the presentation of the first link above before continue reading. It's probably the best explanation of how FB works behind the scenes you can find.
The video and article tells you a few things:
- They're using MySQL at the very bottom of their stack
- Above the SQL DB there is the TAO layer which contains at least two levels of caching and is using graphs to describe the connections.
- I could not find anything on what software / DB they actually use for their cached graphs
Let's take a look at this, friend connections are top left:
Well, this is a graph. :) It doesn't tell you how to build it in SQL, there are several ways to do it but this site has a good amount of different approaches. Attention: Consider that a relational DB is what it is: It's thought to store normalised data, not a graph structure. So it won't perform as good as a specialised graph database.
Also consider that you have to do more complex queries than just friends of friends, for example when you want to filter all locations around a given coordinate that you and your friends of friends like. A graph is the perfect solution here.
I can't tell you how to build it so that it will perform well but it clearly requires some trial and error and benchmarking.
Here is my disappointing test for just findings friends of friends:
DB Schema:
CREATE TABLE IF NOT EXISTS `friends` (
`id` int(11) NOT NULL,
`user_id` int(11) NOT NULL,
`friend_id` int(11) NOT NULL
) ENGINE=InnoDB AUTO_INCREMENT=2 DEFAULT CHARSET=utf8;
Friends of Friends Query:
(
select friend_id
from friends
where user_id = 1
) union (
select distinct ff.friend_id
from
friends f
join friends ff on ff.user_id = f.friend_id
where f.user_id = 1
)
I really recommend you to create you some sample data with at least 10k user records and each of them having at least 250 friend connections and then run this query. On my machine (i7 4770k, SSD, 16gb RAM) the result was ~0.18 seconds for that query. Maybe it can be optimized, I'm not a DB genius (suggestions are welcome). However, if this scales linear you're already at 1.8 seconds for just 100k users, 18 seconds for 1 million users.
This might still sound OKish for ~100k users but consider that you just fetched friends of friends and didn't do any more complex query like "display me only posts from friends of friends + do the permission check if I'm allowed or NOT allowed to see some of them + do a sub query to check if I liked any of them". You want to let the DB do the check on if you liked a post already or not or you'll have to do in code. Also consider that this is not the only query you run and that your have more than active user at the same time on a more or less popular site.
I think my answer answers the question how Facebook designed their friends relationship very well but I'm sorry that I can't tell you how to implement it in a way it will work fast. Implementing a social network is easy but making sure it performs well is clearly not - IMHO.
I've started experimenting with OrientDB to do the graph-queries and mapping my edges to the underlying SQL DB. If I ever get it done I'll write an article about it.
回答4:
My best bet is that they created a graph structure. The nodes are users and "friendships" are edges.
Keep one table of users, keep another table of edges. Then you can keep data about the edges, like "day they became friends" and "approved status," etc.
回答5:
It's most likely a many to many relationship:
FriendList (table)
user_id -> users.user_id
friend_id -> users.user_id
friendVisibilityLevel
EDIT
The user table probably doesn't have user_email as a PK, possibly as a unique key though.
users (table)
user_id PK
user_email
password
回答6:
Take a look at these articles describing how LinkedIn and Digg are built:
- http://hurvitz.org/blog/2008/06/linkedin-architecture
- http://highscalability.com/scaling-digg-and-other-web-applications
There's also "Big Data: Viewpoints from the Facebook Data Team" that might be helpful:
http://developer.yahoo.net/blogs/theater/archives/2008/01/nextyahoonet_big_data_viewpoints_from_the_fac.html
Also, there's this article that talks about non-relational databases and how they're used by some companies:
http://www.readwriteweb.com/archives/is_the_relational_database_doomed.php
You'll see that these companies are dealing with data warehouses, partitioned databases, data caching and other higher level concepts than most of us never deal with on a daily basis. Or at least, maybe we don't know that we do.
There are a lot of links on the first two articles that should give you some more insight.
UPDATE 10/20/2014
Murat Demirbas wrote a summary on
- TAO: Facebook's distributed data store for the social graph (ATC'13)
- F4: Facebook's warm BLOB storage system (OSDI'14)
http://muratbuffalo.blogspot.com/2014/10/facebooks-software-architecture.html
HTH
回答7:
It's not possible to retrieve data from RDBMS for user friends data for data which cross more than half a billion at a constant time so Facebook implemented this using a hash database (no SQL) and they opensourced the database called Cassandra.
So every user has its own key and the friends details in a queue; to know how cassandra works look at this:
http://prasath.posterous.com/cassandra-55
回答8:
This recent June 2013 post goes into some detail into explaining the transition from relationship databases to objects with associations for some data types.
https://www.facebook.com/notes/facebook-engineering/tao-the-power-of-the-graph/10151525983993920
There's a longer paper available at https://www.usenix.org/conference/atc13/tao-facebook’s-distributed-data-store-social-graph
回答9:
You're looking for foreign keys. Basically you can't have an array in a database unless it has it's own table.
Example schema:
Users Table
userID PK
other data
Friends Table
userID -- FK to users's table representing the user that has a friend.
friendID -- FK to Users' table representing the user id of the friend
回答10:
Its a type of graph database: http://components.neo4j.org/neo4j-examples/1.2-SNAPSHOT/social-network.html
Its not related to Relational databases.
Google for graph databases.
回答11:
Keep in mind that database tables are designed to grow vertically (more rows), not horizontally (more columns)
回答12:
Regarding the performance of a many-to-many table, if you have 2 32-bit ints linking user IDs, your basic data storage for 200,000,000 users averaging 200 friends apiece is just under 300GB.
Obviously, you would need some partitioning and indexing and you're not going to keep that in memory for all users.
回答13:
Probably there is a table, which stores the friend <-> user relation, say "frnd_list", having fields 'user_id','frnd_id'.
Whenever a user adds another user as a friend, two new rows are created.
For instance, suppose my id is 'deep9c' and I add a user having id 'akash3b' as my friend, then two new rows are created in table "frnd_list" with values ('deep9c','akash3b') and ('akash3b','deep9c').
Now when showing the friends-list to a particular user, a simple sql would do that: "select frnd_id from frnd_list where user_id=" where is the id of the logged-in user (stored as a session-attribute).
来源：https://stackoverflow.com/questions/1009025/facebook-database-design