MaxGekk commented on code in PR #36064:
URL: https://github.com/apache/spark/pull/36064#discussion_r846764249
##########
sql/core/src/test/scala/org/apache/spark/sql/errors/QueryCompilationErrorsSuite.scala:
##########
@@ -171,4 +174,113 @@ class QueryCompilationErrorsSuite extends QueryTest with
SharedSparkSession {
"The feature is not supported: " +
"Pandas UDF aggregate expressions don't support pivot.")
}
+
+ test("NO_HANDLER_FOR_UDAF: No handler for UDAF error") {
+ val functionName = "myCast"
+ withUserDefinedFunction(functionName -> true) {
+ sql(
+ s"""
+ |CREATE TEMPORARY FUNCTION $functionName
+ |AS 'org.apache.spark.sql.errors.MyCastToString'
+ |""".stripMargin)
+
+ val e = intercept[AnalysisException] (
+ sql(s"SELECT $functionName(123) as value")
+ )
+
+ assert(e.errorClass === Some("NO_HANDLER_FOR_UDAF"))
+ assert(e.message ===
+ "No handler for UDAF 'org.apache.spark.sql.errors.MyCastToString'. " +
+ "Use sparkSession.udf.register(...) instead.")
+ }
+ }
+
+ test("UNTYPED_SCALA_UDF: use untyped Scala UDF should fail by default") {
+ val e = intercept[AnalysisException](udf((x: Int) => x, IntegerType))
+
+ assert(e.errorClass === Some("UNTYPED_SCALA_UDF"))
+ assert(e.message ===
+ "You're using untyped Scala UDF, which does not have the input type " +
+ "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. " +
+ "To get rid of this error, you could:\n" +
+ "1. use typed Scala UDF APIs(without return type parameter), 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")
+ }
+
+ test("NO_UDF_INTERFACE_ERROR: java udf class does not implement any udf
interface") {
+ val className = "org.apache.spark.sql.errors.MyCastToString"
+ val e = intercept[AnalysisException](
+ spark.udf.registerJava(
+ "myCast",
+ className,
+ StringType)
+ )
+
+ assert(e.errorClass === Some("NO_UDF_INTERFACE_ERROR"))
+ assert(e.message ===
+ s"UDF class $className doesn't implement any UDF interface")
+ }
+
+ test("MULTI_UDF_INTERFACE_ERROR: java udf implement multi UDF interface") {
+ val className = "org.apache.spark.sql.errors.MySum"
+ val e = intercept[AnalysisException](
+ spark.udf.registerJava(
+ "mySum",
+ className,
+ StringType)
+ )
+
+ assert(e.errorClass === Some("MULTI_UDF_INTERFACE_ERROR"))
+ assert(e.message ===
+ s"Not allowed to implement multiple UDF interfaces, UDF class
$className")
+ }
+
+ test("UDF_WITH_TOO_MANY_TYPE_ARGUMENT_ERROR: java udf with too many type
arguments") {
Review Comment:
```suggestion
test("UNSUPPORTED_FEATURE: java udf with too many type arguments") {
```
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