Github user mmolimar commented on a diff in the pull request:
https://github.com/apache/spark/pull/18447#discussion_r124545289
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala ---
@@ -209,6 +209,18 @@ class DataFrameFunctionsSuite extends QueryTest with
SharedSQLContext {
Row(2743272264L, 2180413220L))
}
+ test("misc data_type function") {
+ val df = Seq(("a", false)).toDF("a", "b")
+
+ checkAnswer(
+ df.select(data_type($"a"), data_type($"b")),
--- End diff --
The idea would be to know the type based on the value itself, not by the
schema (i.e. the value could be null):
```scala
val df = spark.sparkContext.parallelize(
StringData(null) ::
StringData("a") :: Nil).toDF()
df.select(data_type(col("s"))) //you get null and string in this case
df.schema.map(_.dataType.simpleString) // you just get string
```
On the other hand, it'd be nice to have this SQL function as we do in some
databases.
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