// Continuous trigger with one-second checkpointing intervaldf.writeStream
.format("console")
.trigger(Trigger.Continuous("1 second"))
.start()
On Tue, 14 May 2019 at 22:10, suket arora wrote:
> Hey Austin,
>
> If you truly want to process as a stream
df = inputStream.withWatermark("eventtime", "20
seconds").groupBy("sharedId", window("20 seconds", "10 seconds")
// ProcessingTime trigger with two-seconds micro-batch interval
df.writeStream
.format("console")
.trigger(Trigger.ProcessingTime("2 seconds"))
.start()
On Tue, 14 May 201
Hi Joe,
As per the spark structured streaming documentation and I quote
"withWatermark must be called on the same column as the timestamp column
used in the aggregate. For example, df.withWatermark("time", "1
min").groupBy("time2").count() is invalid in Append output mode, as
watermark is defined o
