System Design: How to design Twitter? Interview question at Facebook, Google, Microsoft

Success in Tech
24 Sept 201726:35

Summary

TLDRThis video script discusses a system design approach to creating a platform like Twitter. It emphasizes the importance of clarifying the problem statement and focusing on core features such as tweeting, timelines, and following. The speaker explains the limitations of a naive relational database solution and introduces Twitter's use of in-memory databases like Redis for fast read access and eventual consistency. The script explores the architecture's trade-offs, including the high memory usage for performance and the challenges of handling tweets from users with millions of followers. It concludes with potential follow-up topics such as search functionality, push notifications, and advertising integration.

Takeaways

  • πŸ€” When designing a system like Twitter, clarify the problem statement and focus on 2-3 core features for detailed design rather than attempting to cover everything.
  • πŸ“ Core features of Twitter include tweeting, timelines (user timeline and home timeline), and the following mechanism.
  • 🚫 A naive approach using relational databases like MySQL for tweets and users can lead to performance issues due to large SELECT statements required for home timeline generation.
  • πŸ’‘ Twitter uses an in-memory database like Redis to store pre-computed timelines for fast read access, prioritizing availability over strict consistency (eventual consistency).
  • πŸ”„ The 'fan-out' mechanism is employed by Twitter to distribute a new tweet to all followers' timelines, updating them in real-time in the Redis cluster.
  • πŸ”’ Redis replication is used to ensure that each user's timeline is stored on multiple machines to enhance availability and fault tolerance.
  • πŸ‘₯ The architecture must handle the computational load of updating millions of timelines when a tweet is made by a celebrity with a large following.
  • πŸ“± For user access, a load balancer directs requests to the fastest available Redis machine that has the user's pre-computed timeline in memory.
  • πŸ”‘ A hash lookup is used to quickly determine which Redis machines store a particular user's timeline.
  • πŸ” Additional system features to consider include search functionality, push notifications, and advertisement placements based on user analytics.
  • πŸ”— The video provides a link to a talk by Twitter's VP of Engineering for further insights into Twitter's architecture and solutions to scaling challenges.

Q & A

  • What is the primary focus of the video script?

    -The primary focus of the video script is to discuss the system design of Twitter, specifically focusing on core features such as tweeting, timelines, and the following mechanism.

  • Why is it important to clarify the problem statement when designing a system like Twitter?

    -Clarifying the problem statement is important because it helps to identify the core features that the design will cover and prevents the designer from running in one direction without a clear focus, which is crucial given the broad nature of the question.

  • What are the two types of timelines mentioned in the script?

    -The two types of timelines mentioned are the 'user timeline', which contains a user's own tweets and retweets, and the 'home timeline', which contains tweets from people the user follows.

  • Why is a relational database like MySQL considered a naive solution for Twitter's system design?

    -A relational database like MySQL is considered naive because it would require performing large SELECT statements to fetch and merge tweets from users a person follows, which is inefficient and not scalable as the database grows.

  • What is the concept of 'fan-out' as mentioned in the script?

    -'Fan-out' is a concept where Twitter takes a user's tweet and pre-computes it into the timelines of all the users following the original tweeter, storing these in an in-memory database for quick access.

  • Why does Twitter use Redis as an in-memory database for storing timelines?

    -Twitter uses Redis because it is a fast, in-memory data structure store, which allows for quick read access to the timelines, meeting the requirement for fast reads and high availability.

  • How does Twitter handle the issue of updating millions of followers' timelines when a celebrity tweets?

    -Twitter handles this by incorporating an SQL approach for very famous users with millions of followers, where their tweets are not pre-computed but merged during load time to avoid massive computational loads.

  • What is the significance of eventual consistency in the context of Twitter's system design?

    -Eventual consistency is significant because it prioritizes availability over strict consistency, meaning it's acceptable for some users to see a tweet slightly later than others, as long as the system remains accessible.

  • How does the architecture ensure that Bob's home timeline is quickly accessible when he accesses Twitter?

    -The architecture ensures quick access by pre-computing and storing Bob's home timeline in multiple Redis machines in memory, with replication for availability, and using a load balancer to direct the request to the fastest responding Redis machine.

  • What are some additional features or considerations that could be discussed in the context of Twitter's system design?

    -Additional features or considerations include search functionality, push notifications, and advertisement placement, which are all important aspects of the Twitter platform that would require their own system design considerations.

Outlines

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Mindmap

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Keywords

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Highlights

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Transcripts

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Related Tags
System DesignTwitter ArchitectureSocial MediaLoad BalancerRedis ClusterFan-OutIn-Memory DatabaseEventual ConsistencyHigh AvailabilityScalabilityInterview Prep