Hi, My sincere apologies for adding my question to this chain. For some reason, I am unable to see the messages which I write to the group ever appear back in it and I think that this might be related in a way that shows a few differences between traditional operations and Spark Streaming operations.
Can I please ask why does lines.count() throws the exception: org.apache.spark.sql.AnalysisException: Queries with streaming sources must be executed with writeStream.start();; Whereas if I do lines.createOrReplaceTempView("test") and then run the sql "select count(*) ccount from test" it runs absolutely fine. I can figure out from the exceptions that there is a check which is getting executed to find out whether isStreaming is true for lines or not, but a bit of explanation might help. Regards, Gourav Sengupta On Fri, Apr 13, 2018 at 3:53 AM, Tathagata Das <tathagata.das1...@gmail.com> wrote: > The traditional SQL windows with `over` is not supported in streaming. > Only time-based windows, that is, `window("timestamp", "10 minutes")` is > supported in streaming. > > On Thu, Apr 12, 2018 at 7:34 PM, kant kodali <kanth...@gmail.com> wrote: > >> Hi All, >> >> Does partition by and order by works only in stateful case? >> >> For example: >> >> select row_number() over (partition by id order by timestamp) from table >> >> gives me >> >> *SEVERE: Exception occured while submitting the query: >> java.lang.RuntimeException: org.apache.spark.sql.AnalysisException: >> Non-time-based windows are not supported on streaming DataFrames/Datasets;;* >> >> I wonder what time based window means? is it not the window from over() >> clause or does it mean group by(window('timestamp'), '10 minutes') like the >> stateful case? >> >> Thanks >> > >