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Somebody implements that infra, and in many cases you need to use them to build it, and it's important to understand them.

I'm not asking you implement one from memory, but at least have some knowledge of its properties and the reasoning behind their design.

For example Bloom filters are a probabilistic data structure, even if you don't use one as is, it's a representative algorithm of whole class of techniques that can be used when exact answers are not required. For example, at scale, if you have something that can cheaply shed 90% of the load without falling back to a more expensive precise algorithm is a big win.

Or Splay trees, binary trees, etc. the notion of self balancing structures and the concept of "divide and conquer" as a problem solving strategy.

All these add something to your toolbox and in many cases can make a huge difference on the type of solutions that you can come up with other than "throw more money at it".

Many people miss the point on these, it's like learning math, it's the way you learn to think that matters, not the particular piece of math you learn.




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