> I increasingly just directly equate 'logs' with 'property hypergraphs' and skip the relational step. Funny enough, a lot of our enterprise+gov work is undoing the weird tabular optimizations of SQL engines to get 360 views of data back to users. It's cool someone has 10,000 tables, but..... :)
The more I program, the more I realize that all these data-structures are conceptually the same if you squint enough.
Graphs are matrices (Edge == 1. Non-edge == 0). Matrices are graphs (see sparse matricies, like COO and its really obvious). Computer Code is graphs, Databases are Hypergraphs. Circuits are hypergraphs. Etc. etc. Everything seems to convert into each other.
The study of NP-completeness is the study of graph (or hypergraph) complexity. Chordal graphs and Bipartite Graphs seem to have significantly more algorithms in P-complexity rather than NP-complexity. (Assuming P =/= NP)
--------
There are questions about which forms are easier to think about... both for the human and the computer. At least, for the equivalent forms (Relational Databases vs Hypergraph representations seem to be equivalent, though I'm not 100% sure)
When one form is "less powerful" than another form, you often get significant improvements in speed. Lists are less powerful than trees, but almost all list algorithms operate way faster.
The more I program, the more I realize that all these data-structures are conceptually the same if you squint enough.
Graphs are matrices (Edge == 1. Non-edge == 0). Matrices are graphs (see sparse matricies, like COO and its really obvious). Computer Code is graphs, Databases are Hypergraphs. Circuits are hypergraphs. Etc. etc. Everything seems to convert into each other.
The study of NP-completeness is the study of graph (or hypergraph) complexity. Chordal graphs and Bipartite Graphs seem to have significantly more algorithms in P-complexity rather than NP-complexity. (Assuming P =/= NP)
--------
There are questions about which forms are easier to think about... both for the human and the computer. At least, for the equivalent forms (Relational Databases vs Hypergraph representations seem to be equivalent, though I'm not 100% sure)
When one form is "less powerful" than another form, you often get significant improvements in speed. Lists are less powerful than trees, but almost all list algorithms operate way faster.