数据密集型应用系统设计
了解 Martin Kleppmann 的《数据密集型应用系统设计》(Designing Data-Intensive Applications):2007-02-22–2026-11-01 的 Hacker News 数据中有 846 次提及、659 位讨论者。阅读原文摘录、比较不同观点,将它加入你的书单。
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在 Hacker News 阅读原文Great book recommendations (I have read parts of the Google SRE book and Designing Data Intensive Applications)! I will also add a couple gems that I don't see often-cited: Simple Object-Oriented Design by Mauricio Aniche and Secure by Design by Dan Bergh Johnsson, Daniel Deogun, and Daniel Sawano. Both have a lot to offer in terms of software design and maintaining complexity. I also liked Refactoring to Patterns by Joshua Kerievsky.
在 Hacker News 阅读原文This is not a complete solution, but two books you should buy immediately: Designing Data-Intensive Applications by Martin Kleppmann AI Engineering by Chip Huyen
在 Hacker News 阅读原文…elopers-as-AI-agents-and-sometimes-humans into alignment. I also recommend System Design Interview 1 and 2 books by Xu for logical system design refurbishment, Designing Data Intensive Applications for most company programs, and Hexagonal Architecture Explained by Cockburn for finally getting something as small as a class or module to something as large as an entire Information System to have clear modular boundaries, without needing to do fuzzy pattern matching around half-remembered SOLID principles and GoF design patterns or trying to blindly apply 12 factor app design principles. Quality used to take a back seat because there was so much legwork to do. AI has reduced the cost to be excel…
在 Hacker News 阅读原文…ana. I've been really exercising my non-fiction reading muscles of late. I'm trying weaponise it as an antidote to AI slop and doom-scrolling. My last read was Designing Data-Intensive Applications by Martin Klepmann (the newly released second edition), it was a wonderful read!
在 Hacker News 阅读原文…ot of experience related to this so I’m just noting some things. Some people in this thread don’t seem to think it’s that hard or overcomplicated. When reading Designing Data-Intensive Applications my main takeaway was that event sourcing can make it easier to solve a lot of issues like performance, scaling, consistency, auditability, etc. It would be interesting to look into what a low overhead way of implementing CRUD with event sourcing in Postgres would look like, then decide if it’s too complex.
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