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pyflink.table.WindowGroupedTable.aggregate#

WindowGroupedTable.aggregate(func: Union[str, pyflink.table.expression.Expression, pyflink.table.udf.UserDefinedAggregateFunctionWrapper]) → pyflink.table.table.AggregatedTable[source]#

Performs an aggregate operation on a window grouped table. You have to close the aggregate with a select statement.

Example:

>>> agg = udaf(lambda a: (a.mean(), a.max()),
...               result_type=DataTypes.ROW(
...                   [DataTypes.FIELD("a", DataTypes.FLOAT()),
...                    DataTypes.FIELD("b", DataTypes.INT())]),
...               func_type="pandas")
>>> window_grouped_table.group_by(col("w")) \
...     .aggregate(agg(col('b'))) \
...     .alias("c", "d") \
...     .select(col('c'), col('d'))
>>> # take all the columns as inputs
>>> # pd is a Pandas.DataFrame
>>> agg_row = udaf(lambda pd: (pd.a.mean(), pd.b.max()),
...               result_type=DataTypes.ROW(
...                   [DataTypes.FIELD("a", DataTypes.FLOAT()),
...                    DataTypes.FIELD("b", DataTypes.INT())]),
...               func_type="pandas")
>>> window_grouped_table.group_by(col("w"), col("a")).aggregate(agg_row)
Parameters

func – user-defined aggregate function.

Returns

The result table.

New in version 1.13.0.

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