| window {SparkR} | R Documentation |
Bucketize rows into one or more time windows given a timestamp specifying column. Window starts are inclusive but the window ends are exclusive, e.g. 12:05 will be in the window [12:05,12:10) but not in [12:00,12:05). Windows can support microsecond precision. Windows in the order of months are not supported.
window(x, ...) ## S4 method for signature 'Column' window(x, windowDuration, slideDuration = NULL, startTime = NULL)
The time column must be of TimestampType.
Durations are provided as strings, e.g. '1 second', '1 day 12 hours', '2 minutes'. Valid interval strings are 'week', 'day', 'hour', 'minute', 'second', 'millisecond', 'microsecond'. If the 'slideDuration' is not provided, the windows will be tumbling windows.
The startTime is the offset with respect to 1970-01-01 00:00:00 UTC with which to start window intervals. For example, in order to have hourly tumbling windows that start 15 minutes past the hour, e.g. 12:15-13:15, 13:15-14:15... provide 'startTime' as '15 minutes'.
The output column will be a struct called 'window' by default with the nested columns 'start' and 'end'.
Other datetime_funcs: add_months,
date_add, date_format,
date_sub, datediff,
dayofmonth, dayofyear,
from_unixtime,
from_utc_timestamp, hour,
last_day, minute,
months_between, month,
next_day, quarter,
second, to_date,
to_utc_timestamp,
unix_timestamp, weekofyear,
year
## Not run:
##D # One minute windows every 15 seconds 10 seconds after the minute, e.g. 09:00:10-09:01:10,
##D # 09:00:25-09:01:25, 09:00:40-09:01:40, ...
##D window(df$time, "1 minute", "15 seconds", "10 seconds")
##D
##D # One minute tumbling windows 15 seconds after the minute, e.g. 09:00:15-09:01:15,
##D # 09:01:15-09:02:15...
##D window(df$time, "1 minute", startTime = "15 seconds")
##D
##D # Thirty second windows every 10 seconds, e.g. 09:00:00-09:00:30, 09:00:10-09:00:40, ...
##D window(df$time, "30 seconds", "10 seconds")
## End(Not run)