Thanks Burak! Appreciate it. This makes sense. How do you suggest we make sure resulting data doesn't produce tiny files? If we are not on databricks yet and can not leverage delta lake features? Also checkpointing feature, do you have active blog/article I can take a look at to try out an example?
On Fri, May 1, 2020 at 7:22 PM Burak Yavuz <brk...@gmail.com> wrote: > Hi Rishi, > > That is exactly why Trigger.Once was created for Structured Streaming. The > way we look at streaming is that it doesn't have to be always real time, or > 24-7 always on. We see streaming as a workflow that you have to repeat > indefinitely. See this blog post for more details! > > https://databricks.com/blog/2017/05/22/running-streaming-jobs-day-10x-cost-savings.html > > Best, > Burak > > On Fri, May 1, 2020 at 2:55 PM Rishi Shah <rishishah.s...@gmail.com> > wrote: > >> Hi All, >> >> I recently started playing with spark streaming, and checkpoint location >> feature looks very promising. I wonder if anyone has an opinion about using >> spark streaming with checkpoint location option as a slow batch processing >> solution. What would be the pros and cons of utilizing streaming with >> checkpoint location feature to achieve fault tolerance in batch processing >> application? >> >> -- >> Regards, >> >> Rishi Shah >> > -- Regards, Rishi Shah
