Hello Peter,
I think that it would also be nice if there was an option to make functions like random_zipfian() actually return a value that has undergone perfect hashing. When this option is used, any given value that the function returns would actually be taken from a random mapping to some other value in the same range. So, you can potentially get a Zipfian distribution without the locality.
I definitely agree. This is a standard problem with all non uniform random generators in pgbench, namely random_{gaussian,exponential}.
However hashing is not a good solution on a finite domain because of the significant collision rate, so that typically 1/3 of values are empty and collisions cause spikes. Also, collisions would break PKs.
The solution is to provide a (good) pseudo-random parametric permutation, which is non trivial especially for non powers of two, so ISTM that it should be a patch on its own.
The good news is that it is on my todo list and I have some ideas on how to do it.
The bad news is that given the rate at which I succeed in getting things committed in pgbench, it might take some years:-( For instance, simplistic functions and operators to extend the current set have been in the pipe for 15 months and missed pg10.
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