pyflink.table.GroupedTable.aggregate

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

Performs a aggregate operation with an aggregate function. 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")
>>> tab.group_by(col('a')).aggregate(agg(col('b')).alias("c", "d")).select(
...     col('a'), 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")
>>> tab.group_by(col('a')).aggregate(agg.alias("a", "b")).select(col('a'), col('b'))

Parameters

func – user-defined aggregate function.

Returns

The result table.

New in version 1.13.0.