1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/translate-sql-window.R, R/backend-teradata.R
\name{win_over}
\alias{win_over}
\alias{win_rank}
\alias{win_aggregate}
\alias{win_aggregate_2}
\alias{win_recycled}
\alias{win_cumulative}
\alias{win_absent}
\alias{win_current_group}
\alias{win_current_order}
\alias{win_current_frame}
\alias{win_rank_tdata}
\title{Generate SQL expression for window functions}
\usage{
win_over(
expr,
partition = NULL,
order = NULL,
frame = NULL,
con = sql_current_con()
)
win_rank(f)
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{
\item{expr}{The window expression}
\item{order}{Variables to order by}
\item{frame}{A numeric vector of length two defining the frame.}
\item{f}{The name of an sql function as a string}
\item{parition}{Variables to partition over}
}
\description{
\code{win_over()} makes it easy to generate the window function specification.
\code{win_absent()}, \code{win_rank()}, \code{win_aggregate()}, and \code{win_cumulative()}
provide helpers for constructing common types of window functions.
\code{win_current_group()} and \code{win_current_order()} allow you to access
the grouping and order context set up by \code{\link[=group_by]{group_by()}} and \code{\link[=arrange]{arrange()}}.
}
\examples{
con <- simulate_dbi()
win_over(sql("avg(x)"), con = con)
win_over(sql("avg(x)"), "y", con = con)
win_over(sql("avg(x)"), order = "y", con = con)
win_over(sql("avg(x)"), order = c("x", "y"), con = con)
win_over(sql("avg(x)"), frame = c(-Inf, 0), order = "y", con = con)
}
\keyword{internal}
|