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

### What changes were proposed in this pull request?

Added Java UDF suggestion in the in error message of untyped Scala UDF.

### Why are the changes needed?

To help user migrate their use case from deprecate untyped Scala UDF to other supported UDF.

### Does this PR introduce any user-facing change?

No. It haven't been released.

### How was this patch tested?

Pass Jenkins.

Closes #28070 from Ngone51/spark_31010.

Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>

Author: Ngone51

sql/core/src/main/scala/org/apache/spark/sql/functions.scala

@@ -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)