HackerNews Readings
40,000 HackerNews book recommendations identified using NLP and deep learning

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Web Scalability for Startup Engineers

Artur Ejsmont

4.8 on Amazon

6 HN comments

Building Secure and Reliable Systems: Best Practices for Designing, Implementing, and Maintaining Systems

Heather Adkins, Betsy Beyer , et al.

4.7 on Amazon

6 HN comments

Show Me the Numbers: Designing Tables and Graphs to Enlighten

Stephen Few

4.5 on Amazon

6 HN comments

Database Internals: A Deep Dive into How Distributed Data Systems Work

Alex Petrov

4.7 on Amazon

6 HN comments

Whatever It Takes: Master the Habits to Transform Your Business, Relationships, and Life

Brandon Bornancin

4.8 on Amazon

6 HN comments

Kubernetes: Up and Running: Dive into the Future of Infrastructure

Brendan Burns , Joe Beda, et al.

4.6 on Amazon

6 HN comments

Python for Kids: A Playful Introduction to Programming

Jason R. Briggs

4.6 on Amazon

6 HN comments

The Phoenix Project (A Novel About IT, DevOps, and Helping Your Business Win)

Gene Kim

4.7 on Amazon

6 HN comments

Terraform: Up & Running: Writing Infrastructure as Code

Yevgeniy Brikman

4.6 on Amazon

6 HN comments

A World Without Email: Reimagining Work in an Age of Communication Overload

Cal Newport, Kevin R. Free, et al.

4.5 on Amazon

5 HN comments

Discovering Statistics Using R

Andy Field, Jeremy Miles , et al.

4.5 on Amazon

5 HN comments

C++ Crash Course: A Fast-Paced Introduction

Josh Lospinoso

4.7 on Amazon

5 HN comments

Irresistible: The Rise of Addictive Technology and the Business of Keeping Us Hooked

Adam Alter and Penguin Audio

4.6 on Amazon

5 HN comments

Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale

Neha Narkhede , Gwen Shapira, et al.

4.4 on Amazon

5 HN comments

The Great Reset: How Big Tech Elites and the World's People Can Be Enslaved by China CCP or A.I.

Cyrus Parsa and The AI Organization

4.5 on Amazon

5 HN comments

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Sorted by relevance

burlesonaonDec 15, 2019

If you wanted to build your own database (to learn how), is Database Internals the better book, or DDIA?

silentsea90onJuly 5, 2021

The book referenced on the blog post seems interesting:

Database Internals: A Deep Dive into How Distributed Data Systems Work
https://www.amazon.com/_/dp/1492040347

decebalus1onApr 14, 2021

Database Internals: A Deep Dive into How Distributed Data Systems Work by Alex Petrov

LameRubberDuckyonOct 28, 2019

What I saw on the first two pages of Customers who bought.... list was:

Database Internals,
Snowden book,
Algorithms book,
BPF Performance tools,
Your Linux Toolbox,
The Go Programming Language,
The Pragmatic Programmer,
Quantum Computing,
A Programmer's Introduction to Mathematics,
An Elegant Puzzle

I had to go up to page 14 of the items list to find all of the items you listed and to find the wire-type soldering iron tip cleaner.

Edit: Took out unneeded snark. It seems I fell prey to Amazon algorithms.

hugofirthonFeb 1, 2021

I couldn't agree more about curiosity mode (I'm going to use that phrase liberally). Despite reading papers for many years, I rarely go in cold. I browse blog posts and twitter, ask myself a series of questions, then try to find/read papers to answer them. Of course this only leads to more questions, and so the journey continues.

I also agree with the recommendations for "Designing Data-Intensive Applications" and "Database Internals". Though, having read the latter for a book club at $employer, I felt it served better as a sort of "index for the space" for people who already had some DB experience, rather a true introduction.

libraryofbabelonDec 8, 2020

Good list, but is it still being actively updated? Not having Kleppmann’s seminal Designing Data-Intensive Applications (2017) on it would indicate no.

Alex Petrov’s Database Internals: A Deep Dive Into How Distributed Data Systems Work (2019) is another essential recent reference that should be here. Not as broad as Kleppmann but dives a lot deeper into certain topics.

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