Re: [spark streaming] checkpoint location feature for batch processing

Replied inline: On Sun, May 3, 2020 at 6:25 PM Magnus Nilsson wrote: > Thank you, so that would mean spark gets the current latest offset(s) when > the trigger fires and then process all available messages in the topic upto > and including that offset as long as maxOffsetsPerTrigger is the

Re: [spark streaming] checkpoint location feature for batch processing

Thank you, so that would mean spark gets the current latest offset(s) when the trigger fires and then process all available messages in the topic upto and including that offset as long as maxOffsetsPerTrigger is the default of None (or large enought to handle all available messages). I think the

Re: [spark streaming] checkpoint location feature for batch processing

If I understand correctly, Trigger.once executes only one micro-batch and terminates, that's all. Your understanding of structured streaming applies there as well. It's like a hybrid approach as bringing incremental processing from micro-batch but having processing interval as batch. That said,

Re: [spark streaming] checkpoint location feature for batch processing

I've always had a question about Trigger.Once that I never got around to ask or test for myself. If you have a 24/7 stream to a Kafka topic. Will Trigger.Once get the last offset(s) when it starts and then quit once it hits this offset(s) or will the job run until no new messages is added to the

Re: [spark streaming] checkpoint location feature for batch processing

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

Re: [spark streaming] checkpoint location feature for batch processing

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!

[spark streaming] checkpoint location feature for batch processing

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