[SPARK-52651][SQL] Handle User Defined Type in Nested ColumnVector #51349
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| val targetType = sparkReadType.map { | ||
| case udt: UserDefinedType[_] => udt.sqlType | ||
| case otherType => otherType | ||
| _.transformRecursively { case t: UserDefinedType[_] => t.sqlType } |
Member
There was a problem hiding this comment.
Just a question. What about ORC file format?
Member
Author
There was a problem hiding this comment.
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
Member
|
cc @peter-toth |
peter-toth
approved these changes
Jul 2, 2025
Member
Author
|
Merged to master, thank you @dongjoon-hyun @peter-toth |
dongjoon-hyun
pushed a commit
that referenced
this pull request
Sep 24, 2025
…ith null DataType ### What changes were proposed in this pull request? Check whether the parameter DataType is null in ColumnVector constructor before transforming it ### Why are the changes needed? A subclass of ColumnVector, e.g. Iceberg's [ConstantColumnVector](https://github.com/apache/iceberg/blob/main/spark/v4.0/spark/src/main/java/org/apache/iceberg/spark/data/vectorized/ConstantColumnVector.java#L41), could be created with null `DataType`. It throws NPE after #51349, which can be verified by failed tests in [integrating Spark 4.1.0-preview1 in Iceberg](apache/iceberg#14155) ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? UT. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #52423 from manuzhang/SPARK-53678. Authored-by: manuzhang <owenzhang1990@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
huangxiaopingRD
pushed a commit
to huangxiaopingRD/spark
that referenced
this pull request
Nov 25, 2025
…ith null DataType ### What changes were proposed in this pull request? Check whether the parameter DataType is null in ColumnVector constructor before transforming it ### Why are the changes needed? A subclass of ColumnVector, e.g. Iceberg's [ConstantColumnVector](https://github.com/apache/iceberg/blob/main/spark/v4.0/spark/src/main/java/org/apache/iceberg/spark/data/vectorized/ConstantColumnVector.java#L41), could be created with null `DataType`. It throws NPE after apache#51349, which can be verified by failed tests in [integrating Spark 4.1.0-preview1 in Iceberg](apache/iceberg#14155) ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? UT. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#52423 from manuzhang/SPARK-53678. Authored-by: manuzhang <owenzhang1990@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
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