Mark van der Broek
Mark van der Broek
+1 as discussed here: https://prefect-community.slack.com/archives/C048ZHT5U3U/p1728058604714769. This workflow is really useful for machine learning pipelines to be able to schedule a flow for different models.
+1 for this issue. This is a very common use-case in machine learning. E.g., running a train job with different parameters.
Another way of enabling access to more historical data (even going beyond the previous day runs data that is done per day instead of per run) would be to split...
Thanks for the _swift_ response! That repo looks really interesting; I will have a look at it. Correct me if I'm wrong but the parsing of the data into the...
> I was talking more about serving the raw data before being loaded into the DB, which of course has much lower latency than using anything else like Python. I...
Noticed the same on Prefect 3.0.3. ``` Version: 3.0.3 API version: 0.8.4 Python version: 3.10.11 Git commit: d9c51bc3 Built: Fri, Sep 20, 2024 8:52 AM OS/Arch: linux/x86_64 Profile: local Server...
To give some more context, there are no error logs for the Prefect server and I use Postgres as the database.
@0leg-st I'm not 100% sure, since I didn't experiment with it, but I suspect the issue is caused when the new deployment somehow is no longer connected to the old...