@schrepfler.bsky.social

The second edition of Designing Data-Intensive Applications, by myself and @chris.blue, is finished and sent off to the printers! Ebooks should be available in the next week, and print books in 3–4 weeks. Sigh of relief. 😅 (BTW, this is a good opportunity to support your favourite local bookshop!)

Book cover of "Designing Data-Intensive Applications, 2nd edition". It has a similar wild boar on the cover as the first edition, but it uses O'Reilly's new cover design, and the boar is now slightly colourised.

Today we're launching DuckLake, an integrated data lake and catalog format powered by SQL. DuckLake unlocks next-generation data warehousing where compute is local, consistency central, and storage scales till infinity. ⁠ducklake is an open standard and we implemented it in the "ducklake" extension.

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Looking for a new opportunity as a VP Engineering/CTO. 14 years in iGaming, built up the engineering department and architecture for an odds making startup (Huddle Tech) spent many years building bespoke backend dealing low latency and a lot of data. #OpenToWork

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I'd like to build some libraries that are usable across #Java, #Scala & #Kotlin, but I also want to be free to pick my implementation language & libraries (Project Loom, Cats-Effect, Kotlin coroutines). This helps me expose nice APIs to all devs. Work in progress: github.com/funfix/tasks

GitHub - funfix/tasks: Task datatype, meant for cross-language interop (Java, Kotlin, Scala)

Task datatype, meant for cross-language interop (Java, Kotlin, Scala) - funfix/tasks

github.com

I submitted a PR that cuts average ClickBench latency by 15% for DataFusion! But reviewing it wasn't straightforward due to the nature of complex performance tuning dynamics, so I made a blog post to explain why it works -- check it out: blog.xiangpeng.systems/posts/parque...

Efficient Filter Pushdown in Parquet – Xiangpeng’s blog

How to implement efficient filter pushdown in Parquet readers and why it’s challenging in practice.

blog.xiangpeng.systems