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[SPARK-31010][SQL][FOLLOW-UP] Add Java UDF suggestion in error message of untyped Scala UDF #28070

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[SPARK-31010][SQL][FOLLOW-UP] Add Java UDF suggestion in error message of untyped Scala UDF #28070

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42e18a3
java udf
Ngone51 Mar 30, 2020
bef033c
address comment
Ngone51 Mar 30, 2020
50e329f
use Integer
Ngone51 Mar 31, 2020
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10 changes: 7 additions & 3 deletions sql/core/src/main/scala/org/apache/spark/sql/functions.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -4864,9 +4864,13 @@ object functions {
"information. Spark may blindly pass null to the Scala closure with primitive-type " +
"argument, and the closure will see the default value of the Java type for the null " +
"argument, e.g. `udf((x: Int) => x, IntegerType)`, the result is 0 for null input. " +
"You could use typed Scala UDF APIs (e.g. `udf((x: Int) => x)`) to avoid this problem, " +
s"or set ${SQLConf.LEGACY_ALLOW_UNTYPED_SCALA_UDF.key} to true and use this API with " +
s"caution."
"To get rid of this error, you could:\n" +
"1. use typed Scala UDF APIs, e.g. `udf((x: Int) => x)`\n" +
"2. use Java UDF APIs, e.g. `udf(new UDF1[String, Integer] { " +
"override def call(s: String): Integer = s.length() }, IntegerType)`, " +
"if input types are all non primitive\n" +
s"3. set ${SQLConf.LEGACY_ALLOW_UNTYPED_SCALA_UDF.key} to true and " +
s"use this API with caution"
throw new AnalysisException(errorMsg)
}
SparkUserDefinedFunction(f, dataType, inputEncoders = Nil)
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