Any best practice for error handling for file upload job? On Wed, Oct 2, 2024 at 1:04 PM [email protected] <[email protected]> wrote:
> STORAGE_API_AT_LEAST_ONCE only saves dataflow engine cost, but the storage > api cost alone is too high for us, that's why we want to switch to file > upload > > On Wed, Oct 2, 2024 at 12:08 PM XQ Hu via user <[email protected]> > wrote: > >> Have you checked >> https://cloud.google.com/dataflow/docs/guides/write-to-bigquery? >> >> autosharding is generally recommended. If the cost is the concern, have >> you checked STORAGE_API_AT_LEAST_ONCE? >> >> On Wed, Oct 2, 2024 at 2:16 PM [email protected] <[email protected]> wrote: >> >>> We are trying to process over 150TB data(streaming unbound) per day and >>> save them to BQ and it looks like storage api is not economical enough for >>> us. I tried to use file upload but somehow it doesn't work and there are >>> not many documents for file upload method online. I have a few questions >>> regarding the file_upload method in streaming mode. >>> 1. How do I decide numOfFileShards? can I still reply on autosharding? >>> 2. I noticed the fileloads method requires much more memory, I'm not >>> sure if dataflow runner would keep all the data in memory before writing to >>> file? If so even one minute data is too much to be kept in memory and less >>> than one minute means would exceed the api quota. Is there a way to cap the >>> memory usage like write data to files before trigger file load job? >>> 3. I also noticed that if there is a file upload job failure, I don't >>> get the error message, so what can I do to handle the error, what is the >>> best practice in terms of error handling in file_upload method? >>> >>> Thanks! >>> Regards, >>> Siyuan >>> >>
