Generate SQL expression for window functions

win_over() makes it easy to generate the window function specification. win_absent(), win_rank(), win_aggregate(), and win_cumulative() provide helpers for constructing common types of window functions. win_current_group() and win_current_order() allow you to access the grouping and order context set up by dplyr::group_by() and dplyr::arrange().

Usage

win_over(
  expr,
  partition = NULL,
  order = NULL,
  frame = NULL,
  con = sql_current_con()
)

win_rank(f, empty_order = FALSE)

win_aggregate(f)

win_aggregate_2(f)

win_cumulative(f)

win_absent(f)

win_current_group()

win_current_order()

win_current_frame()

win_rank_tdata(f)

Arguments

expr

The window expression

partition

Variables to partition over

order

Variables to order by

frame

A numeric vector of length two defining the frame.

f

The name of an sql function as a string

empty_order

A logical value indicating whether to order by NULL if order is not specified

Examples

con <- simulate_dbi()

win_over(sql("avg(x)"), con = con)
#> <SQL> avg(x) OVER ()
win_over(sql("avg(x)"), "y", con = con)
#> <SQL> avg(x) OVER (PARTITION BY `y`)
win_over(sql("avg(x)"), order = "y", con = con)
#> <SQL> avg(x) OVER (ORDER BY `y`)
win_over(sql("avg(x)"), order = c("x", "y"), con = con)
#> <SQL> avg(x) OVER (ORDER BY `x`, `y`)
win_over(sql("avg(x)"), frame = c(-Inf, 0), order = "y", con = con)
#> <SQL> avg(x) OVER (ORDER BY `y` ROWS UNBOUNDED PRECEDING)