cloud-fan opened a new pull request, #37758:
URL: https://github.com/apache/spark/pull/37758
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### What changes were proposed in this pull request?
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This PR fixes a regression caused by
https://github.com/apache/spark/pull/32017 .
In https://github.com/apache/spark/pull/32017 , we tried to be more
conservative and decided to not propagate metadata columns in certain
operators, including `Project`. However, the decision was made only considering
SQL API, not DataFrame API. In fact, it's very common to chain `Project`
operators in DataFrame, e.g. `df.withColumn(...).withColumn(...)...`, and it's
very inconvenient if metadata columns are not propagated through `Project`.
This PR makes 2 changes:
1. Project should propagate metadata columns
2. SubqueryAlias should only propagate metadata columns if the child is a
leaf node or also a SubqueryAlias
The second change is needed to still forbid weird queries like `SELECT m
from (SELECT a from t)`, which is the main motivation of
https://github.com/apache/spark/pull/32017 .
### Why are the changes needed?
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fix a regression
### Does this PR introduce _any_ user-facing change?
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For SQL API, there is no change, as a `SubqueryAlias` always comes with a
`Project` or `Aggregate`, so we still don't propagate metadata columns through
a SELECT group.
For DataFrame API, the behavior becomes more lenient. The only breaking case
is an operator that can propagate metadata columns then follows a
`SubqueryAlias`, e.g. `df.filter(...).as("t").select("t.metadata_col")`. But
this is a weird use case and I don't think we should support it at the first
place.
### How was this patch tested?
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new tests
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