imback82 commented on a change in pull request #26593: [SPARK-29890][SQL]
DataFrameNaFunctions.fill should handle duplicate columns
URL: https://github.com/apache/spark/pull/26593#discussion_r349715065
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
##########
@@ -266,6 +267,32 @@ class DataFrameNaFunctionsSuite extends QueryTest with
SharedSparkSession {
assert(message.contains("Reference 'f2' is ambiguous"))
}
+ test("fill with col(*)") {
+ val df = createDF()
+ // If columns are specified with "*", they are ignored.
+ checkAnswer(df.na.fill("new name", Seq("*")), df.collect())
+ }
+
+ test("fill with nested columns") {
+ val schema = new StructType()
+ .add("c1", new StructType()
+ .add("c1-1", StringType)
+ .add("c1-2", StringType))
+
+ val data = Seq(
+ Row(Row(null, "a2")),
+ Row(Row("b1", "b2")))
+
+ val df = spark.createDataFrame(
+ spark.sparkContext.parallelize(data), schema)
+
+ checkAnswer(df.select("c1.c1-1"),
+ Row(null) :: Row("b1") :: Nil)
+
+ // Nested columns are ignored for fill().
+ checkAnswer(df.na.fill("a1", Seq("c1.c1-1")), data)
Review comment:
This example works fine, and you also need to update the previous line to:
```
checkAnswer(df.select("c1.c1-1"),
Row(null) :: Row("b1") :: Row(null) :: Nil)
```
(This is just to illustrate the nested type, but I can remove it if you
think it's confusing.)
The reason the nested types are ignored is the following check:
```Scala
case (NumericType, dt) => dt.isInstanceOf[NumericType]
case (StringType, dt) => dt == StringType
case (BooleanType, dt) => dt == BooleanType
```
The datatype for the nested column that is resolved to `Attribute` is
`StructType`, so this will not be matched.
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