fix: calling with_column twice and using a window function for the 2nd call returns an error
#12428
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My mental model for `with_column` is sugar for `df.select([wildcard(), expr.alias(name)])`. The bug test-case passes with this implementation, but a few other test cases fail. Those test cases resolve around ambiguity in column names, which I *think* I can solve by using `WildcardOptions`.
Michael-J-Ward
changed the title
with_column twice and using a window function for the 2nd call returns an error
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Alternative approach: #12431 |
The sugared version uses a wildcard to express the previous columns
The ambiguous projection now does not occur until the `physical` stage. I assume there's a way to expand the wildcard and catch it during the `logical` stage, but I haven't found it yet.
…ing wildcardoptions There's still a TODO because I'm not sure **how** to construct the WildcardOptions, but this captures the semantic behavior.
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is this PR similar to #12431 ? |
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@comphead yes. I started this draft late last night but hit a block, then Tim put up his working implementation this morning. Purely for the benefit of my own understanding, could you take a look at my proposed impl and let me know if that captures the intended semantic behavior of the function? I'm still building my understanding of the |
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DRAFT
My first attempt was to convert
with_columnto a sugar API fordf.select(vec![wildcard(), expr.alias(name)]), which mostly matches my mental model of what the function should do.There are currently failing test cases surrounding ambiguous and/or "over-write an existing column" use cases. I suspect proper use of
WildcardOptionswill let me resolve those.Which issue does this PR close?
Closes #12425.
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What changes are included in this PR?
Are these changes tested?
Are there any user-facing changes?