HyukjinKwon commented on a change in pull request #24232: [SPARK-27297] [SQL]
Add higher order functions to scala API
URL: https://github.com/apache/spark/pull/24232#discussion_r315993792
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
##########
@@ -1917,19 +1921,33 @@ class DataFrameFunctionsSuite extends QueryTest with
SharedSparkSession {
null
).toDF("i")
+ // transform(i, x -> x + 1)
+ val resA = Seq(
+ Row(Seq(2, 10, 9, 8)),
+ Row(Seq(6, 9, 10, 8, 3)),
+ Row(Seq.empty),
+ Row(null))
+
+ // transform(i, (x, i) -> x + i)
+ val resB = Seq(
+ Row(Seq(1, 10, 10, 10)),
+ Row(Seq(5, 9, 11, 10, 6)),
+ Row(Seq.empty),
+ Row(null))
+
def testArrayOfPrimitiveTypeNotContainsNull(): Unit = {
- checkAnswer(df.selectExpr("transform(i, x -> x + 1)"),
- Seq(
- Row(Seq(2, 10, 9, 8)),
- Row(Seq(6, 9, 10, 8, 3)),
- Row(Seq.empty),
- Row(null)))
- checkAnswer(df.selectExpr("transform(i, (x, i) -> x + i)"),
- Seq(
- Row(Seq(1, 10, 10, 10)),
- Row(Seq(5, 9, 11, 10, 6)),
- Row(Seq.empty),
- Row(null)))
+ checkAnswer(df.selectExpr("transform(i, x -> x + 1)"), resA)
+ checkAnswer(df.selectExpr("transform(i, (x, i) -> x + i)"), resB)
+
+ checkAnswer(df.select(transform(col("i"), x => x + 1)), resA)
+ checkAnswer(df.select(transform(col("i"), (x, i) => x + i)), resB)
+
+ checkAnswer(df.select(transform(col("i"), new JFunc {
+ def call(x: Column) = x + 1
+ })), resA)
+ checkAnswer(df.select(transform(col("i"), new JFunc2 {
+ def call(x: Column, i: Column) = x + i
+ })), resB)
Review comment:
> As for these, the arguments are scala.Function1 and
org.apache.spark.api.java.function.Function, Java compiler recognizes both as
SAM (Single Abstract Method) type when resolving x -> x, and they are ambiguous.
Sounds like a valid concern to me. Does such `x -> x` syntax work in Java
too?
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