ueshin opened a new pull request, #36167:
URL: https://github.com/apache/spark/pull/36167
### What changes were proposed in this pull request?
Fixes usage logger attachment to handle static methods properly.
### Why are the changes needed?
The usage logger attachment logic has an issue when handling static methods.
For example,
```
$ PYSPARK_PANDAS_USAGE_LOGGER=pyspark.pandas.usage_logging.usage_logger
./bin/pyspark
```
```py
>>> import pyspark.pandas as ps
>>> psdf = ps.DataFrame({"a": [1,2,3], "b": [4,5,6]})
>>> psdf.from_records([(1, 2), (3, 4)])
A function `DataFrame.from_records(data, index, exclude, columns,
coerce_float, nrows)` was failed after 2007.430 ms: 0
Traceback (most recent call last):
...
```
without usage logger:
```py
>>> import pyspark.pandas as ps
>>> psdf = ps.DataFrame({"a": [1,2,3], "b": [4,5,6]})
>>> psdf.from_records([(1, 2), (3, 4)])
0 1
0 1 2
1 3 4
```
### Does this PR introduce _any_ user-facing change?
Yes, for a user attaches the usage logger, static methods will work as
static methods.
### How was this patch tested?
Manually tested.
```py
>>> import pyspark.pandas as ps
>>> import logging
>>> import sys
>>> root = logging.getLogger()
>>> root.setLevel(logging.INFO)
>>> handler = logging.StreamHandler(sys.stdout)
>>> handler.setLevel(logging.INFO)
>>>
>>> formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s -
%(message)s')
>>> handler.setFormatter(formatter)
>>> root.addHandler(handler)
>>> psdf = ps.DataFrame({"a": [1,2,3], "b": [4,5,6]})
2022-04-12 14:43:52,254 - pyspark.pandas.usage_logger - INFO - A function
`DataFrame.__init__(self, data, index, columns, dtype, copy)` was successfully
finished after 2714.896 ms.
>>> psdf.from_records([(1, 2), (3, 4)])
2022-04-12 14:43:59,765 - pyspark.pandas.usage_logger - INFO - A function
`DataFrame.from_records(data, index, exclude, columns, coerce_float, nrows)`
was successfully finished after 51.105 ms.
2022-04-12 14:44:01,371 - pyspark.pandas.usage_logger - INFO - A function
`DataFrame.__repr__(self)` was successfully finished after 1605.759 ms.
0 1
0 1 2
1 3 4
>>> ps.DataFrame.from_records([(1, 2), (3, 4)])
2022-04-12 14:44:25,301 - pyspark.pandas.usage_logger - INFO - A function
`DataFrame.from_records(data, index, exclude, columns, coerce_float, nrows)`
was successfully finished after 43.446 ms.
2022-04-12 14:44:25,493 - pyspark.pandas.usage_logger - INFO - A function
`DataFrame.__repr__(self)` was successfully finished after 192.053 ms.
0 1
0 1 2
1 3 4
```
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