xinrong-meng opened a new pull request, #40486:
URL: https://github.com/apache/spark/pull/40486
### What changes were proposed in this pull request?
Implement Grouped Map API:`GroupedData.applyInPandas` and
`GroupedData.apply`.
### Why are the changes needed?
Parity with vanilla PySpark.
### Does this PR introduce _any_ user-facing change?
Yes. `GroupedData.applyInPandas` and `GroupedData.apply` are supported now,
as shown below.
```sh
>>> df = spark.createDataFrame([(1, 1.0), (1, 2.0), (2, 3.0), (2, 5.0), (2,
10.0)],("id", "v"))
>>> def normalize(pdf):
... v = pdf.v
... return pdf.assign(v=(v - v.mean()) / v.std())
...
>>> df.groupby("id").applyInPandas(normalize, schema="id long, v
double").show()
+---+-------------------+
| id| v|
+---+-------------------+
| 1|-0.7071067811865475|
| 1| 0.7071067811865475|
| 2|-0.8320502943378437|
| 2|-0.2773500981126146|
| 2| 1.1094003924504583|
+---+-------------------+
```
```sh
>>> @pandas_udf("id long, v double", PandasUDFType.GROUPED_MAP)
... def normalize(pdf):
... v = pdf.v
... return pdf.assign(v=(v - v.mean()) / v.std())
...
>>> df.groupby("id").apply(normalize).show()
/Users/xinrong.meng/spark/python/pyspark/sql/connect/group.py:228:
UserWarning: It is preferred to use 'applyInPandas' over this API. This API
will be deprecated in the future releases. See SPARK-28264 for more details.
warnings.warn(
+---+-------------------+
| id| v|
+---+-------------------+
| 1|-0.7071067811865475|
| 1| 0.7071067811865475|
| 2|-0.8320502943378437|
| 2|-0.2773500981126146|
| 2| 1.1094003924504583|
+---+-------------------+
```
### How was this patch tested?
(Parity) Unit tests.
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