ilicmarkodb opened a new pull request, #54284:
URL: https://github.com/apache/spark/pull/54284
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### What changes were proposed in this pull request?
Call `CollationTypeCasts` immediately to avoid cycle between
`ApplyDefaultCollation`, `ExtractWindowExpressions` and `CollationTypeCasts`.
Example:
```sql
CREATE TABLE t (c1 STRING, c2 STRING); -- c1 is UTF8_BINARY
CREATE TABLE t2 DEFAULT COLLATION UTF8_LCASE AS
SELECT c1 = 'HELLO', ROW_NUMBER() OVER (PARTITION BY c1 ORDER BY c2)
FROM t;
```
Analyzer runs rules in batches sequentially, and the rule order is:
`ApplyDefaultCollation` -> `ExtractWindowExpressions` ->
`CollationTypeCasts`.
Iteration 1:
- `ApplyDefaultCollation` applies `UTF8_LCASE` collation to the literal
`'HELLO'`. Expression `EqualTo` (`c1 = 'HELLO'`) is not resolved after this
because c1 and the literal have different types.
- `ExtractWindowExpressions` tries to extract the window expressions, but
it can't because it expects the whole projectList to be resolved (both
`EqualTo` and `ROW_NUMBER()`). `EqualTo` is not resolved, so it can't apply the
rule.
- `CollationTypeCasts` applies coercion rules, changing the type of the
literal to the default `StringType` again (because that's the type of the
column). Now `EqualTo` is resolved.
Iteration 2:
- `ApplyDefaultCollation` again applies `UTF8_LCASE` collation to the
literal, because its type is default `StringType` again.
- `ExtractWindowExpressions` again can't extract the window expressions
for the same reason as before.
- `CollationTypeCasts` applies the same coercion rules again, changing the
type of the literal back to the default `StringType`.
This cycle continues, and the plan never gets resolved. By calling
`CollationTypeCasts` right after this rule, we ensure that other rules like
`ExtractWindowExpressions` that expect resolved expressions can be applied.
### Why are the changes needed?
Bug fix.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
New tests.
### Was this patch authored or co-authored using generative AI tooling?
No.
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