Defines an event time watermark for this DataFrame. A watermark tracks a point
in time before which we assume no more late data is going to arrive.
To know when a given time window aggregation can be finalized and thus can be emitted
when using output modes that do not allow updates.
To minimize the amount of state that we need to keep for on-going aggregations.
The current watermark is computed by looking at the MAX(eventTime) seen across
all of the partitions in the query minus a user specified delayThreshold. Due to the cost
of coordinating this value across partitions, the actual watermark used is only guaranteed
to be at least delayThreshold behind the actual event time. In some cases we may still
process records that arrive more than delayThreshold late.
New in version 2.1.0.
the name of the column that contains the event time of the row.
the minimum delay to wait to data to arrive late, relative to the
latest record that has been processed in the form of an interval
(e.g. “1 minute” or “5 hours”).
This API is evolving.
>>> from pyspark.sql.functions import timestamp_seconds
... timestamp_seconds(sdf.time).alias('time')).withWatermark('time', '10 minutes')
DataFrame[name: string, time: timestamp]