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As I understand, mydataset.mylen function is applied to each row separately and gets the partitioned group as an argument. That's why the function doesn't have to return a similarly sized array - it's called for each row, not for a group of rows.
– Oleg Lokshyn
Commented Nov 26, 2020 at 22:26
1

This is wonderful! Using this approach I can now transfer my pandas code to BigQuery. The main difference I see is that there is no vectorization: I will be computing the aggregate over the partitioned group for each row. Guess that's a minor thing that BigQuery's optimizer will be able to solve.
– Oleg Lokshyn
Commented Nov 26, 2020 at 22:32
Not sure what is your expected output, if you only need a group of value, you should use GROUP BY category instead of a window function with category. But the UDF is the same in both case.
– Yun Zhang
Commented Nov 27, 2020 at 4:08

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