💡Use a unique comment ID generated from a combination of machine ID and a monotonic counter to guarantee uniqueness.
🔑Consider using a thread ID that keeps track of thread-specific comments.
⚙️Explore approaches for partitioning the comment database to handle high volumes of read and write operations.
🚀Optimize read queries by pre-rendering HTML files for archived threads and considering caching mechanisms.
📈Design for high-volume scenarios with read and write rates exceeding 100,000 TPS.
How can comment uniqueness be guaranteed in a distributed comment system?
—Generate a unique comment ID by combining a machine ID and a monotonic counter.
Should the comment system use an auto-incrementing ID or a custom ID for comments?
—Due to distributed nature and clock synchronization issues, it is advisable to use a custom ID generation mechanism.
How can the nested comment structure be efficiently stored in a database?
—Consider using a graph database or implementing a nested structure using attributes like parent comment IDs.
What optimizations can be applied for read-heavy scenarios?
—Pre-render HTML files for archived threads and consider implementing caching mechanisms.
What are the performance requirements for this comment system?
—Design for high volumes of read and write operations, targeting rates exceeding 100,000 TPS.
01:09The video discusses the design of a high-volume comment system.
20:20The video mentions using Lamport timestamps to guarantee uniqueness in comment IDs.
23:27The video explores the use of counter IDs for comments and discusses the challenges of distributed databases.
25:57The video mentions the use of graph databases for efficiently storing nested comment structures.
26:12The video highlights the need to optimize read queries for high-volume scenarios.
