fix(flink): Support read non-VECTOR columns from table containing VEC…

[cshuo]

…TOR columns

Describe the issue this Pull Request addresses

Flink table reads could fail for Hudi tables created by Spark when the table schema contains VECTOR columns, even when the query only projects non-VECTOR fields. The failure came from Flink-side schema conversion and reader validation not distinguishing between the full table schema and the required/projected read schema.

This PR improves Flink compatibility with Spark-written VECTOR tables by converting VECTOR schema metadata into Flink array element types while still rejecting actual VECTOR column reads until Flink reader support is implemented.

Summary and Changelog

• Adds VECTOR handling to HoodieSchemaConverter, mapping VECTOR element types to Flink arrays:
  • FLOAT -> ARRAY<FLOAT>
  • DOUBLE -> ARRAY<DOUBLE>
  • INT8 -> ARRAY<TINYINT>
• Adds Flink reader validation via DataTypeUtils.validateReaderSupportedDataTypes, rejecting reads only when projected fields include VECTOR columns.
• Updates HoodieTableSource to validate the produced/read data type before building the source pipeline, and caches resolved table schema.

Impact

• Flink can build read pipelines and query non-VECTOR columns from Hudi tables that contain VECTOR columns; direct VECTOR column reads still fail with a clear validation error.

Risk Level

low

Documentation Update

Contributor's checklist

• Read through contributor's guide
• Enough context is provided in the sections above
• Adequate tests were added if applicable

have one concern.

[hudi-bot]

CI report:

• 440de18 Azure: SUCCESS

Bot commands

@hudi-bot supports the following commands:

• @hudi-bot run azure re-run the last Azure build

[codecov-commenter]

Codecov Report

❌ Patch coverage is 60.00000% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 68.09%. Comparing base (f2f6203) to head (440de18).

Files with missing lines	Patch %	Lines
...va/org/apache/hudi/util/HoodieSchemaConverter.java	60.00%	2 Missing and 2 partials ⚠️

Additional details and impacted files

@@            Coverage Diff            @@
##             master   #18712   +/-   ##
=========================================
  Coverage     68.09%   68.09%           
- Complexity    29106    29123   +17     
=========================================
  Files          2528     2528           
  Lines        141467   141477   +10     
  Branches      17544    17541    -3     
=========================================
+ Hits          96330    96339    +9     
+ Misses        37217    37216    -1     
- Partials       7920     7922    +2     

Flag	Coverage Δ
common-and-other-modules	44.41% <60.00%> (-0.01%)	⬇️
hadoop-mr-java-client	45.01% <ø> (+<0.01%)	⬆️
spark-client-hadoop-common	48.35% <ø> (+<0.01%)	⬆️
spark-java-tests	49.01% <ø> (+0.01%)	⬆️
spark-scala-tests	44.90% <ø> (-0.01%)	⬇️
utilities	37.64% <ø> (+0.01%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines	Coverage Δ
...va/org/apache/hudi/util/HoodieSchemaConverter.java	69.04% <60.00%> (-0.38%)	⬇️

... and 8 files with indirect coverage changes

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