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https://issues.apache.org/jira/browse/SPARK-35079?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Takeshi Yamamuro resolved SPARK-35079.
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Fix Version/s: 3.2.0
3.1.2
Resolution: Fixed
> Transform with udf gives incorrect result
> -----------------------------------------
>
> Key: SPARK-35079
> URL: https://issues.apache.org/jira/browse/SPARK-35079
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.1
> Reporter: koert kuipers
> Priority: Minor
> Fix For: 3.1.2, 3.2.0
>
>
> i think this is a correctness bug in spark 3.1.1
> the behavior is correct in spark 3.0.1
> in spark 3.0.1:
> {code:java}
> scala> import spark.implicits._
> scala> import org.apache.spark.sql.functions._
> scala> val x = Seq(Seq("aa", "bb", "cc")).toDF
> x: org.apache.spark.sql.DataFrame = [value: array<string>]
> scala> x.select(transform(col("value"), col => udf((_:
> String).drop(1)).apply(col))).show
> +---------------------------------------------------+
> |transform(value, lambdafunction(UDF(lambda 'x), x))|
> +---------------------------------------------------+
> | [a, b, c]|
> +---------------------------------------------------+
> {code}
> in spark 3.1.1:
> {code:java}
> scala> import spark.implicits._
> scala> import org.apache.spark.sql.functions._
> scala> val x = Seq(Seq("aa", "bb", "cc")).toDF
> x: org.apache.spark.sql.DataFrame = [value: array<string>]
> scala> x.select(transform(col("value"), col => udf((_:
> String).drop(1)).apply(col))).show
> +---------------------------------------------------+
> |transform(value, lambdafunction(UDF(lambda 'x), x))|
> +---------------------------------------------------+
> | [c, c, c]|
> +---------------------------------------------------+
> {code}
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