[SPARK-52433][PYTHON] Unify the string coercion in createDataFrame #51140
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HyukjinKwon
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thanks, merged to master |
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### What changes were proposed in this pull request?
Unify the string coercion in createDataFrame
### Why are the changes needed?
currently there is behavior difference between PySpark Classic and PySpark Connect:
```python
from pyspark.sql.types import StructType, StructField, StringType, IntegerType
items = [{'id': '5558382', 'broker': {'teamId': 3398, 'contactEmail': 'abc.xyz123.ca'}} ]
schema = StructType([
StructField("id", StringType()),
StructField("broker", StringType())
])
df = spark.createDataFrame(items, schema=schema)
df.show(truncate=False)
```
PySpark Classic:
```
+-------+------------------------------------------+
|id |broker |
+-------+------------------------------------------+
|5558382|{contactEmail=abc.xyz123.ca, teamId=3398}|
+-------+------------------------------------------+
```
PySpark Connect:
```
+-------+--------------------------------------------------+
|id |broker |
+-------+--------------------------------------------------+
|5558382|{'teamId': 3398, 'contactEmail': 'abc.xyz123.ca'}|
+-------+--------------------------------------------------+
```
The latter seems more reasonable, the dicts should be converted into strings in the python side.
### Does this PR introduce _any_ user-facing change?
yes, in the PySpark classic
### How was this patch tested?
new UT
### Was this patch authored or co-authored using generative AI tooling?
no
Closes apache#51140 from zhengruifeng/py_create_df.
Authored-by: Ruifeng Zheng <ruifengz@apache.org>
Signed-off-by: Ruifeng Zheng <ruifengz@apache.org>
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What changes were proposed in this pull request?
Unify the string coercion in createDataFrame
Why are the changes needed?
currently there is behavior difference between PySpark Classic and PySpark Connect:
PySpark Classic:
PySpark Connect:
The latter seems more reasonable, the dicts should be converted into strings in the python side.
Does this PR introduce any user-facing change?
yes, in the PySpark classic
How was this patch tested?
new UT
Was this patch authored or co-authored using generative AI tooling?
no