[WIP] Zipfian distribution in pgbench

Hello!

PostgreSQL shows very bad results in YCSB Workload A (50% SELECT and 50% UPDATE of random row by PK) on benchmarking with big number of clients using Zipfian distribution. MySQL also has decline but it is not significant as it is in PostgreSQL. MongoDB does not have decline at all. And if pgbench would have Zipfian distribution random number generator, everyone will be able to make research on this topic without using YCSB. 
 
This is the reason why I am currently working on random_zipfian function.

The bottleneck of algorithm that I use is that it calculates zeta function (it has linear complexity - https://en.wikipedia.org/wiki/Riemann_zeta_function). It my cause problems on generating huge amount of big numbers. 

That’s why I added caching for zeta value. And it works good for cases when random_zipfian called with same parameters in script. For example:

… 
\set a random_zipfian(1, 100, 1.2)
\set b random_zipfian(1, 100, 1.2)
…

In other case, second call will override cache of first and caching does not make any sense:
…
\set a random_zipfian(1, 100, 1.2)
\set b random_zipfian(1, 200, 1.4)
… 

That’s why I have a question: should I implement support of caching zeta values for calls with different parameters, or not? 

P.S. I attaching patch and script - analogue of YCSB Workload A.
Run benchmark with command:
$ pgbench -f  ycsb_read_zipf.sql -f  ycsb_update_zipf.sql

On scale = 10(1 million rows) it gives following results on machine with 144 cores(with synchronous_commit=off):
	nclients	tps
	1		8842.401870
	2		18358.140869
	4		45999.378785
	8		88713.743199
	16		170166.998212
	32		290069.221493
	64		178128.030553
	128		88712.825602
	256		38364.937573
	512		13512.765878
	1000 	6188.136736