Yeah now it worked. I took 4 min 22 sec. But that's great. In my computer with 20gb ram it took 2 hours and nothing. So I'm glad I can put the load on motherduck. Geospatial is pretty demanding.
Hi guys. I tried to make a query through python - a heavy spatial one on ducklake and got this error: File "<input>", line 231, in <module>
_duckdb.Error: You've encountered an internal MotherDuck error. You can help us diagnose and fix the issue by contacting support via slack or support@motherduck.com and referencing error ID: 5eae79dd. The same query ran to a smaller scale but then failed on a bigger one.
Ok. Thank you. Now our team needs to build something and try. Since the computing power is good for each instance it can probably run most of etl workloads.
Another question: each flight runs a separate instance? In case I run 2 flights in parallel, does MD handle write concurrency if it occurs? I mean, if the tasks refer to the same table/db.
So each flight runs a separate instance? In case I run 2 flights in parallel, does MD handle write concurrency if it occurs? I mean, if the tasks refer to the same table.
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