Module 12: Content Systems

Welcome to Content Systems. In this module, we explore the architectures behind the internet’s most data-heavy applications. These systems handle exabytes of data, require massive throughput, and demand innovative storage and retrieval strategies.

We move beyond simple CRUD apps to tackle Unstructured Data (Files, Video, HTML) and Specialized Data Structures (Tries, Bloom Filters).

🏗️ The Systems We Build

1. Design Dropbox / Google Drive

The Challenge: How do you sync files across millions of devices instantly without using all the user’s bandwidth?

  • Key Concepts: Block-Level Deduplication, Delta Sync, Namespace Flattening, ACID Metadata.
  • The “Aha!” Moment: Splitting a file into hashed chunks allows us to upload only the parts that changed.

2. Design YouTube / Netflix

The Challenge: How do you stream 4K video to a user on a shaky 4G connection?

  • Key Concepts: Adaptive Bitrate Streaming (ABR), CDN Request Redirection (Anycast/Geo-DNS), Video Encoding (HLS/DASH).
  • The “Aha!” Moment: The client player decides the video quality in real-time based on buffer health.

3. Design a Web Crawler (Googlebot)

The Challenge: How do you download the entire internet (billions of pages) without crashing servers or getting banned?

  • Key Concepts: URL Frontier, Politeness Enforcers, Bloom Filters, DNS Caching.
  • The “Aha!” Moment: Using probabilistic data structures (Bloom Filters) to check for duplicates saves petabytes of RAM.

4. Design Typeahead (Autocomplete)

The Challenge: How do you predict what a user is typing in less than 100 milliseconds?

  • Key Concepts: Trie (Prefix Tree), Top-K Ranking, Data Collection Pipeline, Browser Caching.
  • The “Aha!” Moment: Caching the “Top 5” results at every node of the tree turns an O(N) search into an O(1) lookup.

🧠 Key Takeaways for Interviews

  1. Read vs Write Heavy:
    • Typeahead is extremely Read-Heavy (20:1). We optimize for fast reads using Tries and Caching.
    • Crawler is Write-Heavy (Downloading pages). We optimize for throughput and storage.
  2. Storage Costs:
    • In Dropbox and YouTube, storage is the biggest cost. Deduplication and Cold Storage (Glacier) are mandatory.
  3. Latency:
    • YouTube uses CDNs to bring data close to the user.
    • Typeahead uses In-Memory Tries to respond in < 100ms.

🛠️ Design Tools Introduced

Tool Purpose Used In
Bloom Filter Probabilistic “Have I seen this?” check. Web Crawler
Trie Fast prefix-based string lookup. Typeahead
Consistent Hashing Distributing data across servers. Dropbox, Crawler
CDN (Anycast) Routing users to the nearest edge server. YouTube

[!TIP] Pro Tip: In a system design interview, always ask about the Data Types. Designing for Text (Typeahead) is fundamentally different from designing for Video (YouTube) or Files (Dropbox).

Start with Chapter 1: Dropbox & Google Drive ->

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