Github user zero323 commented on a diff in the pull request:
https://github.com/apache/spark/pull/16536#discussion_r97951062
--- Diff: python/pyspark/sql/functions.py ---
@@ -1826,19 +1826,27 @@ class UserDefinedFunction(object):
def __init__(self, func, returnType, name=None):
self.func = func
self.returnType = returnType
- self._judf = self._create_judf(name)
-
- def _create_judf(self, name):
+ self._judf_placeholder = None
+ self._name = name or (
+ func.__name__ if hasattr(func, '__name__')
+ else func.__class__.__name__)
+
+ @property
+ def _judf(self):
+ if self._judf_placeholder is None:
--- End diff --
Could you elaborate a bit? I am not sure if I understand the issue.
Assignment is atomic (so we don't have to worry about corruption), for any
practical purpose operation is idempotent (we can return expressions using
different Java objects but as far as I am concerned this is just a detail of
implementation), access to Py4J is thread safe and as far as I remember
function registries are synchronized. I there any issue i missed here?
Thanks for looking into this.
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