Found in 7 comments
chw9e · 2018-07-22 · Original thread
As a self-taught developer, I used to think that some of the theoretical elements were overhyped. I can build iOS apps that work, and I did just that for the last 2-3 years. However, many of the programs that I wrote have not been as easy to maintain as I would like and some difficult to fix bugs have popped up overtime, both of which are due to a lack of deeper understanding of CS fundamentals. Last year I started interviewing and was ridiculed at one company in particular for a lack of CS knowledge. Afterwords I started exploring a lot of the CS concepts listed in this link and I have since found numerous ways to improve my code quality and have a better understanding of how CS best practices came to be. I also used to think that algorithms and data structures were relatively useless for an iOS developer, and I was able to do the job without them, thus proving my point. However, after gaining a better understanding, it quickly becomes clear that things like view hierarchies are simply trees and understanding ways to traverse these hierarchies can lead to much cleaner code. With the open sourcing of Swift, I also became more interested in understanding the language, but a lot of the language design decisions didn't make sense to me until I gained a better understanding of CS fundamentals. I have found the programming languages course on Coursera [1] to be particularly useful, and have also greatly enjoyed the book Designing Data Intensive Applications [2]. There's also a great video from this year's WWDC that really inspires algorithm study and use in everyday applications [3].




dustingetz · 2018-07-14 · Original thread
"CP/AP: a false dichotomy" . Martin Kleppman is the author of "Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems"
Another good resource is Designing Data-Intensive Applications [1]. Chapter 2 does a really good job explaining how different categories of databases relate to different data models, including examples of querying graph-like data models using `WITH RECURSIVE` compared to a query language for graph databases.


throwawaypls · 2018-05-16 · Original thread
I read this book titled "Designing Data Intensive Applications", which covers this and a lot of other stuff about designing applications in general.
jpamata · 2018-05-10 · Original thread
Designing Data-Intensive Applications[0] by Martin Kleppmann. There's a previous HN thread about it[1]. Helped me understand a bit more about databases and systems. The book is also very approachable and has the perfect blend of application and theory at a high level that anyone approaching the industry for the first time stands to gain a lot from reading it.

The Architecture of Open Source Applications[2] series is a good one for leaning how to build production applications and you can read it online. The chapter on Scalable Web Architecture[3] is a must-read.





adamnemecek · 2017-01-17 · Original thread
You should try to understand how databases in general work, it will help you with your query writing.

One thing you have to realize is that once you get a little advanced, you have to get to the details of the single SQL implementations, it's not about SQL but about Postgres.

I've found these books really valuable

# SQL Performance Explained Everything Developers Need to Know about SQL Performance

This book fundamentally talks about how to effectively use and leverage the SQL indices. Talks about all the important implementations (Postgres, MySQL, Oracle, SQL Server).

# Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

This book gets mentioned a bunch around here and for a good reason. There aren't too many concrete resources on making your systems "webscale" and this one is really good.

# PostgreSQL 9.0 High Performance

Discusses all the different settings and tweaks you can do in Postgres. It's crazy how much of a perf gain you can get just by twiddling the parameters of the database, i.e. all the tricks you can do when the single instances are bottle necks.

There's a similar book for MySQL

# PostgreSQL 9 High Availability Cookbook

Discusses how do you go from 1 Postgres instance to 1+ instance. Talks about replication, monitoring, cluster management, avoiding downtime etc i.e. all the tricks you can do to manage multiple instances. Again there's a similar book for MySQL

Last but not least check out the postgres documentation, people consider it a standard of what good documentation looks like

Also last but not least, read up on relational algebra (the foundation of SQL) I've always found SQL to be extremely verbose (the syntax reminds me of idk COBOL or smth) but there's another query language called Datalog, that's for our purposes similar to SQL but the syntax is much more legible.

E.g. check out these snippets from these slides (page 29) (and check out the whole class too)


s(X) <- p(X,Y).

s(X) <- r(Y,X).

t(X,Y,Z) <- p(X,Y), r(Y,Z).

w(X) <- s(X), not q(X).






SELECT a, b, c

FROM p, r

WHERE p.b = r.a,



mindcrash · 2016-02-25 · Original thread
You probably might want to read this (for free):

And pay a little to read this book:

And this one:

Nathan Marz brought Apache Storm to the world, and Martin Kleppmann is pretty well known for his work on Kafka.

Both are very good books on building scalable data processing systems.

View this Book on Amazon