Что думаешь? Оцени!
Очевидцы и специалисты пояснили: из троих животных агрессию проявила только одна особь, которая и укусила пострадавшую. Две другие собаки не трогали горожанку.
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Documents of products collection are intentionally designed to be more complex and larger than accounts - I want to see what happens, what is the performance penalty mainly, once individual documents are stored on multiple database pages. In Postgres, page size is 8 KB by default - in practice, the goal is to have at least 4 rows stored on a single page, so every record that is larger than 2 KB is put on two or more disk pages. It obviously reduces performance for both writes & reads - more disk pages to read from and write to. In Mongo it works slightly differently in details, but essentially in the same vein - larger documents are stored on more than one page, degrading performance for all operations. In both cases we are about to see - how much exactly.
NFAs are cheaper to construct, but have a O(n*m) matching time, where n is the size of the input and m is the size of the state graph. NFAs are often seen as the reasonable middle ground, but i disagree and will argue that NFAs are worse than the other two. they are theoretically “linear”, but in practice they do not perform as well as DFAs (in the average case they are also much slower than backtracking). they spend the complexity in the wrong place - why would i want matching to be slow?! that’s where most of the time is spent. the problem is that m can be arbitrarily large, and putting a large constant of let’s say 1000 on top of n will make matching 1000x slower. just not acceptable for real workloads, the benchmarks speak for themselves here.