cloud-fan commented on a change in pull request #28070: [SPARK-31010][SQL] Add
Java UDF suggestion in error message of untyped Scala UDF
URL: https://github.com/apache/spark/pull/28070#discussion_r400082499
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/functions.scala
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@@ -4864,9 +4864,10 @@ 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 ${SQLConf.LEGACY_ALLOW_UNTYPED_SCALA_UDF.key} to true and use
this API with " +
- s"caution."
+ "You could use typed Scala UDF APIs (e.g. `udf((x: Int) => x)`) or
Java UDF (e.g. " +
+ "`udf(new UDF1[String, Int] { override def call(s: String): Int =
s.length() }, " +
+ "IntegerType)`) if input types are all non primitive to avoid this
problem or set " +
+ "${SQLConf.LEGACY_ALLOW_UNTYPED_SCALA_UDF.key} to true and use this
API with caution."
Review comment:
now there are 3 workarounds, can we list them nicely?
```
"To get rid of this error, you could:\n" +
"1. use typed Scala UDF, e.g. ...\n" +
"2. use Java UDF, e.g. ..., if input types... \n" +
"3. set .... "
```
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