[SPARK-59273][SQL][FOLLOWUP] Skip non-string columns in fill - #58647
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zhangxinyao88 wants to merge 1 commit into
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@zhangxinyao88 Is this fix still relevant? If so, please resolve conflicts.
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Seems like this was superseded by #58646 (already merged). Shall we close the current PR @zhangxinyao88? |
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Thanks, #58646 covers the same regression and is now in master. Closing this PR. |
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What changes were proposed in this pull request?
Restore
DataFrameNaFunctions.fillValuebehavior for string replacements: non-string columns are skipped rather than falling through to an exception.The existing SPARK-59273 CHAR/VARCHAR test now also includes an integer column, ensuring
na.fill("x")fills the string-family columns while leaving the integer column unchanged.Why are the changes needed?
SPARK-59273 changed the string match from exact
StringTypeequality to aStringTypesubtype match so CHAR and VARCHAR columns are included. Without a fallback for other column types, a normal mixed string/integer DataFrame throwsStringType is not matched at fillValue. This regressesna.fill("x")in Scala, PySpark, SparkR, and Connect tests.Does this PR introduce any user-facing change?
Yes. It restores the existing behavior of
DataFrame.na.fill("...")on DataFrames that contain both string-family and non-string columns.How was this patch tested?
./build/sbt -Phadoop-3 -Dsbt.supershell=false 'sql/testOnly org.apache.spark.sql.DataFrameNaFunctionsSuite -- -z "fill"'\n\n### Was this patch authored or co-authored using generative AI tooling?\n\nGenerated-by: Codex (GPT-5)