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The most successful relational programming language in existence is SQL. The dream of the relational family was to separate the logic of exactly what's happening from the data and the description of what we want. Every programmer feels like they ought to know more Prolog than they do; if you learn it, it's like tricking a search algorithm into doing other things too. SQL queries have a smoothness to the solution space (ignoring nits in big queries). In K, if you need to do a specific thing like parse some fiddly record format, if you solve the exact problem in front of you, there's normally some elegant way to do it. But if you change the problem even slightly, the solution will wildly change to something else. It's nicer if small changes to the constraints/requirements of a problem correspond to a small change to the program that solves it. I would argue small changes to a query require small changes to the SQL code (ignoring SQL-engine dependent issues). It's like a unified algorithmic framework for sorting, filtering, mapping, set operations etc. The idea of a new control structure unifying operations like is exactly what Lil's query language is intended to be: unifying searching, mapping, filtering, grouping etc. into queries.
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Сравнение Москвы с городами Индии от Галустяна (20:51).
MAP_PRIVATE | MAP_ANONYMOUS, -1, 0);
TRIBE v2 clearly exceeds conventional Finite Impulse Response (FIR) models, which have been the benchmark for unit-level encoding.