The Backend Engineering Show with Hussein Nasser Hussein Nasser

Get my backend course https://backend.win



Google submitted a patch to Linux Kernel 6.8 to improve TCP performance by 40%, this is done via rearranging the tcp structures for better cpu cache lines, I explore this here.

0:00 Intro
0:30 Google improves Linux Kernel TCP by 40%
1:40 How CPU Cache Line Works
6:45 Reviewing the Google Patch

https://www.phoronix.com/news/Linux-6.8-Networking
https://lore.kernel.org/netdev/20231129072756.3684495-1-lixiaoyan@google.com/


Discovering Backend Bottlenecks: Unlocking Peak Performance
https://performance.husseinnasser.com

0:00 Intro

2:00 File System Block vs Database Pages

4:00 Torn pages or partial page

7:40 How Oracle Solves torn pages

8:40 MySQL InnoDB Doublewrite buffer

10:45 Postgres Full page writes

Get my backend course https://backend.win



Cloudflare has announced they are opening sources Pingora as a networking framework! Big news, let us discuss 



0:00 Intro

0:30 Reasons why Cloudflare built Pingora?

3:00 It is a framework! 

7:30 What in Pingora?

11:50 Security in Pingora

13:45 Multi-threading in Pingora

21:00 Customization vs Configuration

25:00 Summary







⁠https://blog.cloudflare.com/pingora-open-source/?utm_campaign=cf_blog&utm_content=20240228&utm_medium=organic_social&utm_source=twitter⁠

https://backend.win

https://databases.win



I’m a big believer that database systems share similar core fundamentals at their storage layer and understanding them allows one to compare different DBMS objectively. For example, How documents are stored in MongoDB is no different from how MySQL or PostgreSQL store rows. 

Everything goes to pages of fixed size and those pages are flushed to disk. 



Each database define page size differently based on their workload, for example MongoDB default page size is 32KB, MySQL InnoDB is 16KB and PostgreSQL is 8KB.



The trick is to fetch what you need from disk efficiently with as fewer I/Os as possible, the rest is API.  



In this video I discuss the evolution of MongoDB internal architecture on how documents are stored and retrieved focusing on the index storage representation. I assume the reader is well versed with fundamentals of database engineering such as indexes, B+Trees, data files, WAL etc, you may pick up my database course to learn the skills.

Let us get started.

In this video I explore the type of languages, compiled, garbage collected, interpreted, JIT and more. 

I talk about default values and how PostgreSQL 14 got slower when a default parameter has changed.

Mike's blog
https://smalldatum.blogspot.com/2024/02/it-wasnt-performance-regression-in.html