Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/17848#discussion_r128444945
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -3185,170 +3185,207 @@ object functions {
val inputTypes = (1 to x).foldRight("Nil")((i, s) =>
{s"ScalaReflection.schemaFor(typeTag[A$i]).dataType :: $s"})
println(s"""
/**
- * Defines a user-defined function of ${x} arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of ${x} arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[$typeTags](f: Function$x[$types]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try($inputTypes).toOption
- UserDefinedFunction(f, dataType,
inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}""")
}
*/
/**
- * Defines a user-defined function of 0 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 0 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag](f: Function0[RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 1 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 1 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag](f: Function1[A1, RT]):
UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 2 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 2 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag](f: Function2[A1, A2,
RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 3 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 3 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag](f:
Function3[A1, A2, A3, RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 4 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 4 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4:
TypeTag](f: Function4[A1, A2, A3, A4, RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType ::
ScalaReflection.schemaFor(typeTag[A4]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 5 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 5 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag,
A5: TypeTag](f: Function5[A1, A2, A3, A4, A5, RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType ::
ScalaReflection.schemaFor(typeTag[A4]).dataType ::
ScalaReflection.schemaFor(typeTag[A5]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 6 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 6 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag,
A5: TypeTag, A6: TypeTag](f: Function6[A1, A2, A3, A4, A5, A6, RT]):
UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType ::
ScalaReflection.schemaFor(typeTag[A4]).dataType ::
ScalaReflection.schemaFor(typeTag[A5]).dataType ::
ScalaReflection.schemaFor(typeTag[A6]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 7 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 7 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag,
A5: TypeTag, A6: TypeTag, A7: TypeTag](f: Function7[A1, A2, A3, A4, A5, A6, A7,
RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType ::
ScalaReflection.schemaFor(typeTag[A4]).dataType ::
ScalaReflection.schemaFor(typeTag[A5]).dataType ::
ScalaReflection.schemaFor(typeTag[A6]).dataType ::
ScalaReflection.schemaFor(typeTag[A7]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 8 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 8 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag,
A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag](f: Function8[A1, A2, A3,
A4, A5, A6, A7, A8, RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType ::
ScalaReflection.schemaFor(typeTag[A4]).dataType ::
ScalaReflection.schemaFor(typeTag[A5]).dataType ::
ScalaReflection.schemaFor(typeTag[A6]).dataType ::
ScalaReflection.schemaFor(typeTag[A7]).dataType ::
ScalaReflection.schemaFor(typeTag[A8]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 9 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 9 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag,
A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag](f:
Function9[A1, A2, A3, A4, A5, A6, A7, A8, A9, RT]): UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType ::
ScalaReflection.schemaFor(typeTag[A4]).dataType ::
ScalaReflection.schemaFor(typeTag[A5]).dataType ::
ScalaReflection.schemaFor(typeTag[A6]).dataType ::
ScalaReflection.schemaFor(typeTag[A7]).dataType ::
ScalaReflection.schemaFor(typeTag[A8]).dataType ::
ScalaReflection.schemaFor(typeTag[A9]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
/**
- * Defines a user-defined function of 10 arguments as user-defined
function (UDF).
- * The data types are automatically inferred based on the function's
signature.
+ * Defines a deterministic user-defined function of 10 arguments as
user-defined
+ * function (UDF). The data types are automatically inferred based on
the function's
+ * signature. To change a UDF to nondeterministic, call the API
+ * `UserDefinedFunction.asNondeterministic()`.
*
* @group udf_funcs
* @since 1.3.0
*/
def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag,
A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10:
TypeTag](f: Function10[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, RT]):
UserDefinedFunction = {
val ScalaReflection.Schema(dataType, nullable) =
ScalaReflection.schemaFor[RT]
val inputTypes = Try(ScalaReflection.schemaFor(typeTag[A1]).dataType
:: ScalaReflection.schemaFor(typeTag[A2]).dataType ::
ScalaReflection.schemaFor(typeTag[A3]).dataType ::
ScalaReflection.schemaFor(typeTag[A4]).dataType ::
ScalaReflection.schemaFor(typeTag[A5]).dataType ::
ScalaReflection.schemaFor(typeTag[A6]).dataType ::
ScalaReflection.schemaFor(typeTag[A7]).dataType ::
ScalaReflection.schemaFor(typeTag[A8]).dataType ::
ScalaReflection.schemaFor(typeTag[A9]).dataType ::
ScalaReflection.schemaFor(typeTag[A10]).dataType :: Nil).toOption
- UserDefinedFunction(f, dataType, inputTypes).withNullability(nullable)
+ val udf = UserDefinedFunction(f, dataType, inputTypes)
+ if (nullable) udf else udf.asNonNullabe()
}
// scalastyle:on parameter.number
// scalastyle:on line.size.limit
/**
- * Defines a user-defined function (UDF) using a Scala closure. For this
variant, the caller must
- * specify the output data type, and there is no automatic input type
coercion.
+ * Defines a deterministic user-defined function (UDF) using a Scala
closure. For this variant,
--- End diff --
not only scala closure, I think java UDF class is also supported here.
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