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mean.piar_index()
Aggregating an index over subperiods seems slow given that it should be a simple operation. The constraint appears to be the loop.
bench::press( levels = c(1e2, 1e3, 1e4), periods = c(3, 12, 120), { index <- as_index(matrix(runif(levels * periods), levels)) bench::mark(mean(index), min_iterations = 10) } ) expression levels periods min median `itr/sec` mem_alloc `gc/sec` n_itr n_gc total_time <bch:expr> <dbl> <dbl> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl> <int> <dbl> <bch:tm> 1 mean(inde… 100 3 1.05ms 1.18ms 727. 8.81KB 7.35 297 3 408.44ms 2 mean(inde… 1000 3 7.69ms 8.87ms 113. 79.06KB 7.90 43 3 379.68ms 3 mean(inde… 10000 3 74.34ms 75.09ms 13.3 881.56KB 31.1 3 7 225.18ms 4 mean(inde… 100 12 3.48ms 3.96ms 252. 25.83KB 10.8 93 4 369.46ms 5 mean(inde… 1000 12 30.57ms 31.63ms 31.2 233.09KB 9.35 10 3 320.98ms 6 mean(inde… 10000 12 338.2ms 398.73ms 2.42 2.5MB 7.74 10 32 4.14s 7 mean(inde… 100 120 35.56ms 39.78ms 25.0 233.06KB 10.7 7 3 279.66ms 8 mean(inde… 1000 120 389.5ms 415.32ms 2.44 2.04MB 6.34 10 26 4.1s 9 mean(inde… 10000 120 4.19s 8.93s 0.116 22.12MB 3.82 10 329 1.44m
The text was updated successfully, but these errors were encountered:
These timings have improved a bit over the last year.
levels periods min median mem_alloc n_itr <dbl> <dbl> <bch:tm> <bch:tm> <bch:byt> <int> 1 100 3 473.32µs 504.85µs 11.44KB 921 2 1000 3 2.68ms 2.96ms 102.78KB 154 3 10000 3 25.28ms 26.86ms 1.09MB 14 4 100 12 685.86µs 746.54µs 19.31KB 623 5 1000 12 4.87ms 5.22ms 173.94KB 84 6 10000 12 47.56ms 49.9ms 1.78MB 6 7 100 120 3.35ms 3.63ms 218.22KB 123 8 1000 120 31.68ms 32.99ms 1.97MB 10 9 10000 120 339.1ms 356.81ms 19.65MB 10
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Aggregating an index over subperiods seems slow given that it should be a simple operation. The constraint appears to be the loop.
The text was updated successfully, but these errors were encountered: