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0 pointsP5fRxh5kUvp2th3y ago0 comments

On point 3 it should be noted that it's almost always a mistake to optimize for scale at the start of a projects lifetime. There will be exceptions, but in general this is true.

You can always migrate that data to a more useful format if you find it starts hurting you at scale, if you start with the assumption you need the scale you're hurting yourself in the here and now for theoretical future benefit.

> The real reason people use joins is because they want to pack a lot of details onto the user's screen when they are looking at a list view

This is completely, emphatically wrong. I'm somewhat miffed at the air of authority you're using here. People use joins for the normalization of data.

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jongjong3y ago

This perspective only makes sense of you assume that designing a scalable system requires MORE work. My experience is that designing a scalable system requires LESS work if you and your team have the right skillset.

In most cases, I can build a scalable system faster than I can build a non-scalable one with the same feature set.

It would make no sense for me to implement the lesser alternative if it requires the same or more work.

P5fRxh5kUvp2thOP3y ago

I'm always leery of people who claim to be senior and have never spent 3-5 years on the same system, and this attitude is why.

It takes at least that long to really start surfacing the design errors that were made that kills productivity long-term in a system. As a result I very often will claim the difference between a skilled and unskilled developer is the ability for a system they built to be reasonable after 5+ years without everyone involved wanting to rebuild the entire thing from scratch.

IOW, this is a fundamental difference in perspective. I was speaking to creating systems that are maintainable over the long haul by actively trying to control complexity. You're speaking speed of initial development.

Rich Hickey went on a small rant in one of his videos (I think the one describing datomic, but could be wrong) in which he pointed out many things that are fast initially will hurt long-term. I agree with that sentiment wholeheartedly.

The fact that you called the less complex alternative the "lesser" alternative speaks volumes. It honestly feels like the whole "mongodb is webscale" devbro culture rearing its ugly head.

jongjong3y ago

I tend to prefer combining data at the last moment on the client side rather than having it pre-combined on the server side (I prefer REST philosophy over GraphQL). It's probably because I'm web-application focused and so scalability and concurrency is far more important to me than raw execution time. Maybe if I was a data scientist or embedded systems developer, I would care more about execution time. I've met people like that. But IMO performant scripts tend to be the result of more optimizations which makes them harder to maintain as the underlying engines or hardware changes.

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0 pointsP5fRxh5kUvp2th3y ago0 comments

On point 3 it should be noted that it's almost always a mistake to optimize for scale at the start of a projects lifetime. There will be exceptions, but in general this is true.

> The real reason people use joins is because they want to pack a lot of details onto the user's screen when they are looking at a list view

This is completely, emphatically wrong. I'm somewhat miffed at the air of authority you're using here. People use joins for the normalization of data.

0 comments

jongjong3y ago

In most cases, I can build a scalable system faster than I can build a non-scalable one with the same feature set.

It would make no sense for me to implement the lesser alternative if it requires the same or more work.

P5fRxh5kUvp2thOP3y ago

I'm always leery of people who claim to be senior and have never spent 3-5 years on the same system, and this attitude is why.

The fact that you called the less complex alternative the "lesser" alternative speaks volumes. It honestly feels like the whole "mongodb is webscale" devbro culture rearing its ugly head.

jongjong3y ago

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j / k navigate · click thread line to collapse