zhengruifeng commented on code in PR #41687:
URL: https://github.com/apache/spark/pull/41687#discussion_r1242871046
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sql/core/src/main/scala/org/apache/spark/sql/functions.scala:
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@@ -7715,9 +7688,30 @@ object functions {
* @since 3.2.0
*/
@scala.annotation.varargs
- def call_udf(udfName: String, cols: Column*): Column = withExpr {
- UnresolvedFunction(udfName, cols.map(_.expr), isDistinct = false)
- }
+ @deprecated("Use call_function")
+ def call_udf(udfName: String, cols: Column*): Column =
+ call_function(udfName, cols: _*)
+
+ /**
+ * Call a builtin or temp function.
+ *
+ * @param funcName function name
+ * @param cols the expression parameters of function
+ * @since 3.5.0
+ */
+ def call_function(funcName: String, cols: Column*): Column =
+ withExpr { UnresolvedFunction(funcName, cols.map(_.expr), false) }
+
+ /**
+ * Call a builtin or temp function.
+ *
+ * @param funcName function name
+ * @param cols the expression parameters of function
+ * @param isDistinct the distinct for aggregate functions
+ * @since 3.5.0
+ */
+ def call_function(funcName: String, isDistinct: Boolean, cols: Column*):
Column =
Review Comment:
qq:
1, dose parameter `isDistinct` works for all the functions?
2, since `call_function` can invoke both built-in functions and udfs, shall
we add a new parameter `isBuiltIn` or `isUDF` to specify the where to look up
the function? so that we can invoke a built-in function even it is overrided by
udfs, e.g.
```
scala> import org.apache.spark.sql.functions._
import org.apache.spark.sql.functions._
scala> val df = Seq(("a", "A"), ("b", "B")).toDF("key", "value")
df: org.apache.spark.sql.DataFrame = [key: string, value: string]
scala> df.selectExpr("upper(key)").show
+----------+
|upper(key)|
+----------+
| A|
| B|
+----------+
scala> val foo = udf{str: String => str.toUpperCase() + "_X"}
foo: org.apache.spark.sql.expressions.UserDefinedFunction =
SparkUserDefinedFunction($Lambda$3089/0x000000080140f040@6ccb2162,StringType,List(Some(class[value[0]:
string])),Some(class[value[0]: string]),None,true,true)
scala> spark.udf.register("upper", foo.asNondeterministic())
23/06/26 15:15:09 WARN SimpleFunctionRegistry: The function upper replaced a
previously registered function.
res1: org.apache.spark.sql.expressions.UserDefinedFunction =
SparkUserDefinedFunction($Lambda$3089/0x000000080140f040@6ccb2162,StringType,List(Some(class[value[0]:
string])),Some(class[value[0]: string]),Some(upper),true,false)
scala> df.selectExpr("upper(key)").show
+----------+
|upper(key)|
+----------+
| A_X|
| B_X|
+----------+
```
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