News Feed System Design

Assumptions:
- 500M DAU
- Average user follows 200 people
- Average user creates 2 posts/day
- Average user checks feed 10 times/day

Traffic:
- Writes: 500M × 2 = 1B posts/day ≈ 12K/sec
- Reads: 500M × 10 = 5B feeds/day ≈ 58K/sec
- Read:Write ratio ≈ 5:1

Storage:
- Post: 1 KB average (text, metadata)
- Daily posts: 1B × 1 KB = 1 TB/day
- 5 years: 1.8 PB (without media)

CREATE TABLE posts (
    post_id UUID,
    user_id UUID,
    content TEXT,
    media_urls LIST<TEXT>,
    created_at TIMESTAMP,
    likes_count INT,
    comments_count INT,
    shares_count INT,
    PRIMARY KEY (user_id, created_at, post_id)
) WITH CLUSTERING ORDER BY (created_at DESC);

-- For fetching specific user's posts
CREATE TABLE posts_by_id (
    post_id UUID PRIMARY KEY,
    user_id UUID,
    content TEXT,
    media_urls LIST<TEXT>,
    created_at TIMESTAMP
);

Key: feed:{user_id}
Value: Sorted Set of post_ids with scores (timestamp/rank)

ZADD feed:user123 1705312800 post:abc123
ZADD feed:user123 1705312700 post:def456

ZREVRANGE feed:user123 0 19  # Get top 20 posts

(User A)-[:FOLLOWS]->(User B)
(User A)-[:FOLLOWS]->(User C)
(User B)-[:FOLLOWS]->(User A)

Query followers:
MATCH (u:User {id: 'userB'})<-[:FOLLOWS]-(follower)
RETURN follower.id

Score = Affinity × PostWeight × TimeDecay

Problem: New user with no pre-computed feed

Solution:
1. Check for pre-computed feed → Empty
2. Generate cold-start feed:
   - Popular posts from followed users
   - Trending posts globally
   - Content based on interests
3. Trigger async feed generation

Problem: User follows celebrity with 100M followers

Solution:
1. Don't fan-out to celebrity's followers
2. When user requests feed:
   - Pull celebrity posts on demand
   - Merge with pre-computed feed
3. Cache celebrity posts aggressively (shared by many)