Big Tech Digest #8

2023-12-09: Incremental data loading at Netflix, Working with unstructured data at Airbnb, Reducing mobile app size at Spotify, Dive deep into B-Trees at Allegro and more!

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// 📫 Engineering blogs digest

Selectively picked recent blog posts from tech companies’ engineering blogs.

• [Meta] Writing and linting Python at scale discusses all things Python at Meta by Pascal Hartig and Amethyst Reese

• [Netflix] Incremental Processing using Netflix Maestro and Apache Iceberg by Jun He, Yingyi Zhang, and Pawan Dixit

• [Airbnb] Wisdom of Unstructured Data: Building Airbnb’s Listing Knowledge from Big Text Data by Hongwei Harvey Li

• [Spotify] The What, Why, and How of Mastering App Size by Viktor Petrovski, Dmitry Povolotskyi, and Bruno Rocha

• [Allegro] How does B-tree make your queries fast? explores how B-tree data structure organises the data and how to performs search queries against it by Mateusz Kuźmik

• [Twilio] A Practical Guide to Creating Microservices With Go-Micro by Elijah Asaolu

• [DoorDash] How DoorDash Manages Mobile Releases by Manolo Sañudo

• [Canva] Summarizing Post Incident Reviews with GPT-4 by Wuji Zhu

• [Hashnode] Hashnode's Feed Architecture is a story of how Hashnode calculates feeds on scale and serverless by Florian Fuchs

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Delivered bi-weekly to your inbox, Big Tech Digest brings you a collection of links to the latest engineering blog posts from +100 Big Tech companies and startups like Airbnb, Uber, Netflix or Meta. Aimed at all Software Engineers and AI/ML folks at any level, Big Tech Digest is focused on engineering problems and their proposed solutions at tech companies that I find particularly interesting. No marketing or non-tech stuff.

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