cloud-fan commented on a change in pull request #28645:
URL: https://github.com/apache/spark/pull/28645#discussion_r442631217
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala
##########
@@ -581,4 +581,99 @@ class UDFSuite extends QueryTest with SharedSparkSession {
.toDF("col1", "col2")
checkAnswer(df.select(myUdf(Column("col1"), Column("col2"))), Row(2020) ::
Nil)
}
+
+ test("case class as element type of Seq/Array") {
+ val f1 = (s: Seq[TestData]) => s.map(d => d.key * d.value.toInt).sum
+ val myUdf1 = udf(f1)
+ val df1 = Seq(("data", Seq(TestData(50, "2")))).toDF("col1", "col2")
+ checkAnswer(df1.select(myUdf1(Column("col2"))), Row(100) :: Nil)
+
+ val f2 = (s: Array[TestData]) => s.map(d => d.key * d.value.toInt).sum
+ val myUdf2 = udf(f2)
+ val df2 = Seq(("data", Array(TestData(50, "2")))).toDF("col1", "col2")
+ checkAnswer(df2.select(myUdf2(Column("col2"))), Row(100) :: Nil)
+ }
+
+ test("case class as key/value type of Map") {
+ val f1 = (s: Map[TestData, Int]) => s.keys.head.key *
s.keys.head.value.toInt
+ val myUdf1 = udf(f1)
+ val df1 = Seq(("data", Map(TestData(50, "2") -> 502))).toDF("col1", "col2")
+ checkAnswer(df1.select(myUdf1(Column("col2"))), Row(100) :: Nil)
+
+ val f2 = (s: Map[Int, TestData]) => s.values.head.key *
s.values.head.value.toInt
+ val myUdf2 = udf(f2)
+ val df2 = Seq(("data", Map(502 -> TestData(50, "2")))).toDF("col1", "col2")
+ checkAnswer(df2.select(myUdf2(Column("col2"))), Row(100) :: Nil)
+
+ val f3 = (s: Map[TestData, TestData]) => s.keys.head.key *
s.values.head.value.toInt
+ val myUdf3 = udf(f3)
+ val df3 = Seq(("data", Map(TestData(50, "2") -> TestData(50,
"2")))).toDF("col1", "col2")
+ checkAnswer(df3.select(myUdf3(Column("col2"))), Row(100) :: Nil)
+ }
+
+ test("case class as element of tuple") {
+ val f = (s: (TestData, Int)) => s._1.key * s._2
+ val myUdf = udf(f)
+ val df = Seq(("data", (TestData(50, "2"), 2))).toDF("col1", "col2")
+ checkAnswer(df.select(myUdf(Column("col2"))), Row(100) :: Nil)
+ }
+
+ test("case class as generic type of Option") {
+ val f = (o: Option[TestData]) => o.map(t => t.key * t.value.toInt)
+ val myUdf = udf(f)
+ val df1 = Seq(("data", Some(TestData(50, "2")))).toDF("col1", "col2")
+ checkAnswer(df1.select(myUdf(Column("col2"))), Row(100) :: Nil)
+ val df2 = Seq(("data", None: Option[TestData])).toDF("col1", "col2")
+ checkAnswer(df2.select(myUdf(Column("col2"))), Row(null) :: Nil)
+ }
+
+ test("more input fields than expect for case class") {
+ val f = (t: TestData2) => t.a * t.b
+ val myUdf = udf(f)
+ val df = spark.range(1)
+ .select(lit(50).as("a"), lit(2).as("b"), lit(2).as("c"))
+ .select(struct("a", "b", "c").as("col"))
+ checkAnswer(df.select(myUdf(Column("col"))), Row(100) :: Nil)
+ }
+
+ test("less input fields than expect for case class") {
+ val f = (t: TestData2) => t.a * t.b
+ val myUdf = udf(f)
+ val df = spark.range(1)
+ .select(lit(50).as("a"))
+ .select(struct("a").as("col"))
+ val error = intercept[AnalysisException] (df.select(myUdf(Column("col"))))
+ assert(error.getMessage.contains("cannot resolve '`b`' given input
columns: [a]"))
+ }
+
+ test("wrong order of input fields for case class") {
+ val f = (t: TestData) => t.key * t.value.toInt
+ val myUdf = udf(f)
+ val df = spark.range(1)
+ .select(lit("2").as("value"), lit(50).as("key"))
+ .select(struct("value", "key").as("col"))
+ checkAnswer(df.select(myUdf(Column("col"))), Row(100) :: Nil)
+ }
+
+ test("top level Option primitive type") {
+ val f = (i: Option[Int]) => i.map(_ * 10)
+ val myUdf = udf(f)
+ val df = Seq(Some(10), None).toDF("col")
+ checkAnswer(df.select(myUdf(Column("col"))), Row(100) :: Row(null) :: Nil)
+ }
+
+ test("top level Option case class") {
Review comment:
This is already tested in `case class as generic type of Option`
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