geom_ribbon() > geom_area() speed difference about ggplot2 HOT 3 CLOSED

library(ggplot2)

dat <- data.frame(
  x = 1:1e4,
  y = rnorm(1e4) + 5
)

area   <- ggplot(dat) + geom_area(aes(x, y))
ribbon <- ggplot(dat) + geom_ribbon(aes(x, ymin = 0, ymax = y))

ragg::agg_png(tempfile(fileext = ".png"))

res <- bench::mark(
  area   = print(area),
  ribbon = print(ribbon),
  check  = FALSE,
  min_iterations = 5
)
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
print(res)
#> # A tibble: 2 × 13
#>   expression      min median `itr/sec` mem_alloc `gc/sec` n_itr  n_gc total_time
#>   <bch:expr> <bch:tm> <bch:>     <dbl> <bch:byt>    <dbl> <int> <dbl>   <bch:tm>
#> 1 area          2.02s   2.1s     0.469     129MB    16.7      5   178      10.7s
#> 2 ribbon      72.24ms 72.6ms     9.04     24.2MB     3.62     5     2    552.8ms
#> # ℹ 4 more variables: result <list>, memory <list>, time <list>, gc <list>

area <- ggplot(dat) + 
  geom_area(aes(x, y), stat = "identity", position = "identity")
ribbon <- ggplot(dat) +
  geom_ribbon(aes(x, ymin = 0, ymax = y), stat = "identity", position = "identity")

res <- bench::mark(
  area   = print(area),
  ribbon = print(ribbon),
  check  = FALSE,
  min_iterations = 5
)
print(res)
#> # A tibble: 2 × 13
#>   expression      min median `itr/sec` mem_alloc `gc/sec` n_itr  n_gc total_time
#>   <bch:expr> <bch:tm> <bch:>     <dbl> <bch:byt>    <dbl> <int> <dbl>   <bch:tm>
#> 1 area         70.6ms 72.1ms      13.8    20.1MB     2.30     6     1      435ms
#> 2 ribbon       70.2ms 71.4ms      14.0    19.5MB     5.61     5     2      356ms
#> # ℹ 4 more variables: result <list>, memory <list>, time <list>, gc <list>

dat |>
  ggplot() +
  geom_area(aes(x = x, y = y), position = "identity")