ueshin commented on code in PR #50084:
URL: https://github.com/apache/spark/pull/50084#discussion_r1970931466
##########
python/pyspark/worker.py:
##########
@@ -160,6 +160,10 @@ def wrap_arrow_batch_udf(f, args_offsets, kwargs_offsets,
return_type, runner_co
import pandas as pd
func, args_kwargs_offsets = wrap_kwargs_support(f, args_offsets,
kwargs_offsets)
+ zero_arg_exec = False
+ if len(args_kwargs_offsets) == 0:
+ args_kwargs_offsets = (0,) # Series([pyspark._NoValue, ...]) is used
for 0-arg execution.
Review Comment:
This comment may not be always true, e.g., when there are 0-arg and 1+arg
UDFs are mixed. I guess it still works, though.
##########
python/pyspark/worker.py:
##########
@@ -160,6 +160,10 @@ def wrap_arrow_batch_udf(f, args_offsets, kwargs_offsets,
return_type, runner_co
import pandas as pd
func, args_kwargs_offsets = wrap_kwargs_support(f, args_offsets,
kwargs_offsets)
+ zero_arg_exec = False
+ if len(args_kwargs_offsets) == 0:
+ args_kwargs_offsets = (0,) # Series([pyspark._NoValue, ...]) is used
for 0-arg execution.
Review Comment:
We need to add such tests if not exists.
- 0-arg only
- 0-arg, 1+arg
- 1+arg, 0-arg
##########
python/pyspark/worker.py:
##########
@@ -176,6 +180,16 @@ def wrap_arrow_batch_udf(f, args_offsets, kwargs_offsets,
return_type, runner_co
elif type(return_type) == BinaryType:
result_func = lambda r: bytes(r) if r is not None else r # noqa: E731
+ if zero_arg_exec:
+
+ def get_args(*args: pd.Series):
+ return [() for _ in range(len(args[0]))]
Review Comment:
Can we directly use `args[0]`?
```suggestion
return [() for _ in range(len(args[0]))]
return [() for _ in args[0]]
```
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