[SPARK-52651][SQL] Handle User Defined Type in Nested ColumnVector #51349
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| @@ -196,8 +196,7 @@ class ParquetToSparkSchemaConverter( | |||
| field: ColumnIO, | |||
| sparkReadType: Option[DataType] = None): ParquetColumn = { | |||
| val targetType = sparkReadType.map { | |||
| case udt: UserDefinedType[_] => udt.sqlType | |||
| case otherType => otherType | |||
| _.transformRecursively { case t: UserDefinedType[_] => t.sqlType } | |||
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Just a question. What about ORC file format?
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Hi @dongjoon-hyun, good question. I have an umbrella ticket for udt improvements. Let me check other formats or readers with followups if necessary
dongjoon-hyun
approved these changes
Jul 2, 2025
|
cc @peter-toth |
peter-toth
approved these changes
Jul 2, 2025
|
Merged to master, thank you @dongjoon-hyun @peter-toth |
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What changes were proposed in this pull request?
When I read a map column with a UDT nested, I encountered:
This PR adds a recursive loop to omit the UDT
Why are the changes needed?
Add UDT missing features
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