zhengruifeng opened a new pull request, #39254:
URL: https://github.com/apache/spark/pull/39254
### What changes were proposed in this pull request?
Implement `GroupedData.{min, max, avg, sum}`
### Why are the changes needed?
TLDR, `df.groupby().min` != `df.groupby().agg(min)`
1, if no columns are provided, `GroupedData.min` will check the schema and
choose the columns with matched datatypes;
2, if a column with unacceptable datatype is given, than `GroupedData.min`
will throw exception like
`"department" is not a numeric column. Aggregation function can only be
applied on a numeric column.`
### Does this PR introduce _any_ user-facing change?
yes, make `GroupedData.{min, max, avg, sum}` consistent with PySpark
### How was this patch tested?
added UT
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