Let me fix my mistake :) What I suggested in that earlier thread does not work. The streaming query that joins a streaming dataset with a batch view, does not correctly pick up when the view is updated. It works only when you restart the query. That is, - stop the query - recreate the dataframes, - start the query on the new dataframe using the same checkpoint location as the previous query
Note that you dont need to restart the whole process/cluster/application, just restart the query in the same process/cluster/application. This should be very fast (within a few seconds). So, unless you have latency SLAs of 1 second, you can periodically restart the query without restarting the process. Apologies for my misdirections in that earlier thread. Hope this helps. TD On Wed, Feb 14, 2018 at 2:57 AM, Appu K <kut...@gmail.com> wrote: > More specifically, > > Quoting TD from the previous thread > "Any streaming query that joins a streaming dataframe with the view will > automatically start using the most updated data as soon as the view is > updated” > > Wondering if I’m doing something wrong in https://gist.github.com/ > anonymous/90dac8efadca3a69571e619943ddb2f6 > > My streaming dataframe is not using the updated data, even though the view > is updated! > > Thank you > > > On 14 February 2018 at 2:54:48 PM, Appu K (kut...@gmail.com) wrote: > > Hi, > > I had followed the instructions from the thread https://mail-archives. > apache.org/mod_mbox/spark-user/201704.mbox/%3CD1315D33- > 41cd-4ba3-8b77-0879f3669...@qvantel.com%3E while trying to reload a > static data frame periodically that gets joined to a structured streaming > query. > > However, the streaming query results does not reflect the data from the > refreshed static data frame. > > Code is here https://gist.github.com/anonymous/ > 90dac8efadca3a69571e619943ddb2f6 > > I’m using spark 2.2.1 . Any pointers would be highly helpful > > Thanks a lot > > Appu > >