[GitHub] [arrow] jonkeane commented on a diff in pull request #12707: ARROW-14810 [R] Implement bindings for lubridate's `date_decimal()` and `decimal_date()`

[GitBox <gi...@apache.org>]

jonkeane commented on code in PR #12707:
URL: https://github.com/apache/arrow/pull/12707#discussion_r847609979


##########
r/R/dplyr-funcs-datetime.R:
##########
@@ -300,6 +314,34 @@ register_bindings_duration <- function() {
 
     build_expr("cast", x, options = cast_options(to_type = duration(unit = "s")))
   })
+  register_binding("decimal_date", function(date) {
+    y <- build_expr("year", date)
+    start <- call_binding("make_datetime", year = y, tz = "UTC")
+    sofar <- call_binding("difftime", date, start, units = "secs")
+    total <- call_binding(
+      "if_else",
+      build_expr("is_leap_year", date),
+      call_binding("as.integer64", 31622400L),  # number of seconds in a leap year (366 days)
+      call_binding("as.integer64", 31536000L)   # number of seconds in a regular year (365 days)

Review Comment:
   I don't have any reason to believe this would be different at larger scales, but for benchmarks like these we probably should use larger sets of data than a handful of rows. It depends on what we're looking at, but 10k-100k rows is more reasonable for something like this



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