The content discusses the concept of erasure coding, which involves splitting data into chunks for better storage efficiency and fault tolerance. The trade-off between storage space used and requests issued to read data is highlighted. Different erasure code configurations, such as (k+m), are explained, with examples like Backblaze B2 using (17+3) for fault tolerance. Unique examples include applying erasure coding to distributed systems like caching or quorum systems. The use of erasure coding in systems like HRaft is also explored, with details on adapting the coding based on available replicas. Overall, erasure coding offers significant improvements in storage efficiency and durability.
https://transactional.blog/blog/2024-erasure-coding