column_datetime_diff_functions {SparkR} | R Documentation |
Date time arithmetic functions defined for Column
.
add_months(y, x) datediff(y, x) date_add(y, x) date_format(y, x) date_sub(y, x) from_utc_timestamp(y, x) months_between(y, x) next_day(y, x) to_utc_timestamp(y, x) ## S4 method for signature 'Column' datediff(y, x) ## S4 method for signature 'Column' months_between(y, x) ## S4 method for signature 'Column,character' date_format(y, x) ## S4 method for signature 'Column,character' from_utc_timestamp(y, x) ## S4 method for signature 'Column,character' next_day(y, x) ## S4 method for signature 'Column,character' to_utc_timestamp(y, x) ## S4 method for signature 'Column,numeric' add_months(y, x) ## S4 method for signature 'Column,numeric' date_add(y, x) ## S4 method for signature 'Column,numeric' date_sub(y, x)
y |
Column to compute on. |
x |
For class
|
datediff
: Returns the number of days from y
to x
.
months_between
: Returns number of months between dates y
and x
.
date_format
: Converts a date/timestamp/string to a value of string in the format
specified by the date format given by the second argument. A pattern could be for instance
dd.MM.yyyy
and could return a string like '18.03.1993'. All
pattern letters of java.text.SimpleDateFormat
can be used.
Note: Use when ever possible specialized functions like year
. These benefit from a
specialized implementation.
from_utc_timestamp
: Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a
time in UTC, and renders that time as a timestamp in the given time zone. For example, 'GMT+1'
would yield '2017-07-14 03:40:00.0'.
next_day
: Given a date column, returns the first date which is later than the value of
the date column that is on the specified day of the week. For example,
next_day("2015-07-27", "Sunday")
returns 2015-08-02 because that is the first Sunday
after 2015-07-27. Day of the week parameter is case insensitive, and accepts first three or
two characters: "Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun".
to_utc_timestamp
: Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a
time in the given time zone, and renders that time as a timestamp in UTC. For example, 'GMT+1'
would yield '2017-07-14 01:40:00.0'.
add_months
: Returns the date that is numMonths (x
) after startDate (y
).
date_add
: Returns the date that is x
days after.
date_sub
: Returns the date that is x
days before.
datediff since 1.5.0
months_between since 1.5.0
date_format since 1.5.0
from_utc_timestamp since 1.5.0
next_day since 1.5.0
to_utc_timestamp since 1.5.0
add_months since 1.5.0
date_add since 1.5.0
date_sub since 1.5.0
Other data time functions: column_datetime_functions
## Not run:
##D dts <- c("2005-01-02 18:47:22",
##D "2005-12-24 16:30:58",
##D "2005-10-28 07:30:05",
##D "2005-12-28 07:01:05",
##D "2006-01-24 00:01:10")
##D y <- c(2.0, 2.2, 3.4, 2.5, 1.8)
##D df <- createDataFrame(data.frame(time = as.POSIXct(dts), y = y))
## End(Not run)
## Not run:
##D tmp <- createDataFrame(data.frame(time_string1 = as.POSIXct(dts),
##D time_string2 = as.POSIXct(dts[order(runif(length(dts)))])))
##D tmp2 <- mutate(tmp, datediff = datediff(tmp$time_string1, tmp$time_string2),
##D monthdiff = months_between(tmp$time_string1, tmp$time_string2))
##D head(tmp2)
## End(Not run)
## Not run:
##D tmp <- mutate(df, from_utc = from_utc_timestamp(df$time, "PST"),
##D to_utc = to_utc_timestamp(df$time, "PST"))
##D head(tmp)
## End(Not run)
## Not run:
##D tmp <- mutate(df, t1 = add_months(df$time, 1),
##D t2 = date_add(df$time, 2),
##D t3 = date_sub(df$time, 3),
##D t4 = next_day(df$time, "Sun"))
##D head(tmp)
## End(Not run)