[SPARK-49230][Connect][SQL] Do not return UnboundRowEncoder when not needed #49339
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xupefei
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hvanhovell
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Dec 31, 2024
sql/api/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala
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hvanhovell
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Jan 6, 2025
| @@ -956,7 +956,7 @@ class Dataset[T] private[sql] ( | |||
| val generator = SparkUserDefinedFunction( | |||
| UDFAdaptors.iterableOnceToSeq(f), | |||
| UnboundRowEncoder :: Nil, | |||
| ScalaReflection.encoderFor[Seq[A]]) | |||
| ScalaReflection.encoderForWithRowEncoderSupport[Seq[A]]) | |||
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Please keep in mind that for encoders that are used to convert data from the external representation to the internal representation we need an encoder with a valid schema. An UnboundRowEncoder does not have a valid/meaningful schema. It should not be used in these cases.
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Thanks for the comment. I evaluated all call sites, it turns out none of them need to be with Row Encoder support. I only left a change in [[ExpressionEncoder]].
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What changes were proposed in this pull request?
This PR corrects the
isRowEncoderSupportedlogic ofencoderFormethod. Now when the flag is off,encoderFormethod will not return anUnboundRowEncoderbut instead throws an exception. To get back to the old behaviour, used one of the following two method instead:encoderFor(..., isRowEncoderSupported = true)encoderForWithRowEncoderSupport(...)To avoid breaking existing use cases, this PR changes some calls of
encoderFortoencoderForWithRowEncoderSupportwhen the input type involves genericT, sinceTcan be aRow.Why are the changes needed?
Code cleanup.
Does this PR introduce any user-facing change?
No. This method is used internally.
How was this patch tested?
Existing tests.
Was this patch authored or co-authored using generative AI tooling?
No.