pyflink.dataframe.dataframe.DataFrame.group_by

DataFrame.group_by(*columns: str | Expression) → GroupedDataFrame

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")
... )