zero323 commented on a change in pull request #27406:
[SPARK-30681][PYSPARK][SQL] Add higher order functions API to PySpark
URL: https://github.com/apache/spark/pull/27406#discussion_r373156864
##########
File path: python/pyspark/sql/functions.py
##########
@@ -2840,6 +2840,359 @@ def from_csv(col, schema, options={}):
return Column(jc)
+def _invoke_higher_order_function(name):
+ """
+ Given name of the expression corresponding to a higher order SQL function,
+ return a function that takes
+
+ - a list of columns
+ - a list of functions (*Column) -> Column
+
+ invokes expression, and wraps result in a Column
+ (first Scala one, then Python).
+ """
+
+ def _(cols, funs):
+ sc = SparkContext._active_spark_context
+ expressions = sc._jvm.org.apache.spark.sql.catalyst.expressions
+ expr = getattr(expressions, name)
+
+ jcols = [_to_java_column(col).expr() for col in cols]
+ jfuns = [_create_lambda(f) for f in funs]
+
+ return Column(sc._jvm.Column(expr(*jcols + jfuns)))
+
+ return _
+
+
+@since(3.0)
+def transform(col, f):
+ """
+ Returns an array of elements after applying a transformation to each
element in the input array.
+
+ :param col: name of column or expression
+ :param f: a function that is applied to each element of the input array.
+ Can take one of the following forms:
+
+ - Unary ``(x: Column) -> Column: ...``
+ - Binary ``(x: Column, i: Column) -> Column...``, where the second
argument is
+ a 0-based index of the element.
+
+ and an use methods of :class:`pyspark.sql.Column`, functions defined in
+ :py:mod:`pyspark.sql.functions` and Scala ``UserDefinedFunctions``.
+ Python ``UserDefinedFunctions`` are not supported
+ (`SPARK-27052 <https://issues.apache.org/jira/browse/SPARK-27052>`__).
Review comment:
If SPARK-27052 is won't fix, we could be more proactive and inspect the
closure here:
```python
import inspect
from itertools import chain
from pyspark.sql.udf import UserDefinedFunction
def _is_udf(f):
return isinstance(f, UserDefinedFunction) or (
hasattr(f, "returnType")
and hasattr(f, "evalType")
and f.__closure__
and isinstance(f.__closure__[0].cell_contents, UserDefinedFunction)
)
def _check_conatins_udf(f):
closurevars = inspect.getclosurevars(f)
for name, f in chain.from_iterable(
[closurevars.nonlocals.items(), closurevars.globals.items()]
):
if _is_udf(f):
raise ValueError(
"Higher order functions cannot use UserDefinedFunctions ",
"Detected following udf {}: {}".format(name, f),
)
```
or throw an exception at the analyzer level
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