xinrong-meng opened a new pull request, #40539:
URL: https://github.com/apache/spark/pull/40539
### What changes were proposed in this pull request?
Implement CoGrouped Map API: `applyInPandas`.
### Why are the changes needed?
Parity with vanilla PySpark.
### Does this PR introduce _any_ user-facing change?
Yes. CoGrouped Map API is supported as shown below.
```sh
>>> import pandas as pd
>>> df1 = spark.createDataFrame(
... [(20000101, 1, 1.0), (20000101, 2, 2.0), (20000102, 1, 3.0),
(20000102, 2, 4.0)], ("time", "id", "v1"))
>>>
>>> df2 = spark.createDataFrame(
... [(20000101, 1, "x"), (20000101, 2, "y")], ("time", "id", "v2"))
>>>
>>> def asof_join(l, r):
... return pd.merge_asof(l, r, on="time", by="id")
...
>>> df1.groupby("id").cogroup(df2.groupby("id")).applyInPandas(
... asof_join, schema="time int, id int, v1 double, v2 string"
... ).show()
+--------+---+---+---+
| time| id| v1| v2|
+--------+---+---+---+
|20000101| 1|1.0| x|
|20000102| 1|3.0| x|
|20000101| 2|2.0| y|
|20000102| 2|4.0| y|
+--------+---+---+---+
```
### How was this patch tested?
Parity unit tests.
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