pyflink.dataframe.DataFrame.group_by#

DataFrame.group_by(*columns: Union[str, pyflink.table.expression.Expression]) → pyflink.dataframe.dataframe.GroupedDataFrame[source]#

Group the DataFrame by columns.

Parameters: *columns – Columns to group by.
Returns: A GroupedDataFrame for aggregation operations.

Example::

>>> import pyflink.dataframe as pf
>>> df = pf.from_records(
...     [("A", 1), ("A", 2), ("B", 3)],
...     schema=["category", "value"],
... )
>>> result = df.group_by("category").agg(
...     pf.col("category"),
...     pf.col("value").sum.alias("total")
... )