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Posted to issues@spark.apache.org by "koert kuipers (Jira)" <ji...@apache.org> on 2021/04/14 21:47:00 UTC
[jira] [Created] (SPARK-35079) Transform with udf gives incorrect
result
koert kuipers created SPARK-35079:
-------------------------------------
Summary: 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
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("11", "22", "33")).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))|
+---------------------------------------------------+
| [1, 2, 3]|
+---------------------------------------------------+
{code}
in spark 3.1.1:
{code:java}
scala> import spark.implicits._
scala> import org.apache.spark.sql.functions._
scala> val x = Seq(Seq("11", "22", "33")).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))|
+---------------------------------------------------+
| [3, 3, 3]|
+---------------------------------------------------+
{code}
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