Champagne Supernova

When I started reaching my goal weight, something changed. I didn't have much energy, I couldn't spend time with friends, I stopped enjoying sex, and I lost my period. But then again, it felt okay. Because even if I wasn't socializing in real life, people on the internet kept praising me.

At some point, though, looking at my face through my phone, I realized something: my incisors were looking longer and longer. Weird, right? The thing is, I wasn't transforming into a rabbit - they were falling out. I could move them with my tongue. They were literally hanging from my face. I had to have them removed. I had lost all the bone mass in that area.

My hair, something that I was very proud of growing up, started falling out. My face looked different. I couldn't think. I couldn't study. I had always been extremely good in school, but I had to drop out of college because I didn't have enough stamina to get out of bed in the morning.

I had to go through many surgeries to fix my teeth, but they kept failing because the bone mass simply wasn't there, and my body kept rejecting the bone grafts. My lips started to look different. My face looked different. Everything about me was different.

And people stopped praising me, because I didn't look chic anymore - I looked sick. Nobody wants to watch someone slowly kill themselves. It's not aesthetically pleasing.

It took years to recover from that, and I still haven't recovered completely. I never ended up finishing university, and I feel too embarrassed to go back.

Now I'm trying to practice a sport that I love, and I struggle every day to convince myself that succeeding in my passions feels better than being skinny. And it does.

When you see people online claiming absurdly low weights while also looking muscular and healthy, sometimes they're lying, and sometimes the numbers don't tell the full story. You won't feel better if you reach those weights. You will feel like you're dying. You will probably lose everything.

Your ability to think, to enjoy your body, to study, to have sex and feel good about it, and to do anything that is fulfilling to you is far more important and consequential than thinness.

"Then watch something else," you might say, and you're right, in a way, but I also want to mourn the extremely vulnerable and excruciating coming-of-age story that hypnotized me years ago.

Chapter 1. Trade-offs in Data System Architecture

"There are no solutions; there are only trade-offs. [...] But you try to get the best trade-off you can get, and that's all you can hope for."

Thomas Sowell, interview with Fred Barnes (2005)

Data is central to much application development today. It has become normal to store data from many different users in a shared server-based data infrastructure. As users interact with an application, they both read the data that is stored and generate more data.

As the data volumes or the rate of queries grows, it needs to be distributed across multiple machines, which introduces many challenges.

We call an application data-intensive if data management is one of the primary challenges in developing the application. While in compute-intensive systems the challenge is parallelizing a very large computation, in data-intensive applications we usually worry more about things like storing and processing large data volumes, managing changes to data, ensuring consistency in the face of failures and concurrency, and making sure services are highly available.

Building blocks: 1. Databases: store data so that they, or another application, can find it again later;

2. Caches: remember the result of an expensive operation, to speed up reads;

3. Search indexes: allow users to search data by keyword or filter it in various ways;

4. Stream processing: handle events and data changes as soon as they occur;

5. Batch processing: periodically crunch a large amount of accumulated data;

One of the key challenges with data systems is that different people need to do very different things with data. This chapter compares several contrasting concepts and explores their trade-offs. We will consider the following topics:

The difference between operational and analytical systems

The pros and cons of cloud services and self-hosted systems

When to move from a single-node system to distributed systems