revsetbenchmark: add more example for roots usages...
revsetbenchmark: add more example for roots usages
We test the `roots` revset in setting similar to our test for `heads`.
Note that the algorithm used for roots can give result without consuming the
full input set. This provides a significant speedup when testing or accessing
a single value. We can't just replace it with simple, full algorithm like we
did for `heads`. See performance number below:
0) roots((tip~100::) - (tip~100::tip))
1) roots((0::) - (0::tip))
2) roots(tip~100:)
3) roots(:42)
4) roots(not public())
5) roots((0:tip)::)
6) roots(0::tip)
7) 42:68 and roots(42:tip)
8) roots(0:tip)
9) roots((:42) + (tip~42:))
10) roots(all())
11) roots(-10000:-1)
12) (-5000:-1000) and roots(-10000:-1)
13) roots(matching(tip, "author"))
14) roots(matching(tip, "author")) and -10000:-1
15) (-10000:-1) and roots(matching(tip, "author"))
plain min max first last reverse rev..rst rev..ast sort sor..rst sor..ast
00) 0.000789 0.000801 0.000801 0.000819 0.000784 0.000774 0.000793 0.000816 0.000815 0.000831 0.000799
01) 0.097610 0.002717 0.096706 0.002615 0.059189 0.089033 0.059862 0.002644 0.098058 0.002640 0.058992
02) 0.000709 0.000117 0.000382 0.000136 0.000384 0.000724 0.000412 0.000133 0.000733 0.000159 0.000416
03) 0.000075 0.000064 0.000093 0.000080 0.000097 0.000089 0.000123 0.000079 0.000105 0.000102 0.000126
04) 0.000055 0.000071 0.000070 0.000087 0.000075 0.000066 0.000100 0.000085 0.000082 0.000110 0.000102
05) 0.088043 0.001084 0.087816 0.001097 0.048049 0.072454 0.047673 0.001089 0.088491 0.001163 0.047824
06) 0.058761 0.001727 0.059324 0.001850 0.058562 0.059198 0.058998 0.001743 0.058556 0.001874 0.059420
07) 0.000131 0.000121 0.000145 0.000138 0.000150 0.000142 0.000178 0.000135 0.000160 0.000163 0.000179
08) 0.058003 0.000077 0.032327 0.000093 0.031966 0.056812 0.031753 0.000092 0.057113 0.000116 0.031933
09) 0.000503 0.000145 0.000469 0.000161 0.000476 0.000564 0.000502 0.000160 0.000537 0.000187 0.000500
10) 0.056654 0.000058 0.033104 0.000073 0.032157 0.056598 0.031877 0.000071 0.056433 0.000094 0.031819
11) 0.005842 0.000081 0.001907 0.000101 0.001883 0.005868 0.001915 0.000099 0.005836 0.000122 0.001896
12) 0.003237 0.000634 0.001784 0.000655 0.001803 0.003245 0.001837 0.000649 0.003231 0.000680 0.001858
Boris Feld - Mon, 14 Jan 2019 17:19:22