63c5bf13ce
## What changes were proposed in this pull request?
In Python 2, when `pandas_udf` tries to return string type value created in the udf with `".."`, the execution fails. E.g.,
```python
from pyspark.sql.functions import pandas_udf, col
import pandas as pd
df = spark.range(10)
str_f = pandas_udf(lambda x: pd.Series(["%s" % i for i in x]), "string")
df.select(str_f(col('id'))).show()
```
raises the following exception:
```
...
java.lang.AssertionError: assertion failed: Invalid schema from pandas_udf: expected StringType, got BinaryType
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.sql.execution.python.ArrowEvalPythonExec$$anon$2.<init>(ArrowEvalPythonExec.scala:93)
...
```
Seems like pyarrow ignores `type` parameter for `pa.Array.from_pandas()` and consider it as binary type when the type is string type and the string values are `str` instead of `unicode` in Python 2.
This pr adds a workaround for the case.
## How was this patch tested?
Added a test and existing tests.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes #20507 from ueshin/issues/SPARK-23334.
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|---|---|---|
| .. | ||
| __init__.py | ||
| catalog.py | ||
| column.py | ||
| conf.py | ||
| context.py | ||
| dataframe.py | ||
| functions.py | ||
| group.py | ||
| readwriter.py | ||
| session.py | ||
| streaming.py | ||
| tests.py | ||
| types.py | ||
| udf.py | ||
| utils.py | ||
| window.py | ||