pyflink.table.table.AggregatedTable.select#

AggregatedTable.select(*fields: Union[str, pyflink.table.expression.Expression]) → pyflink.table.table.Table[source]#

Performs a selection operation after an aggregate operation. The field expressions cannot contain table functions and aggregations.

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.aggregate(agg(col('a')).alias("a", "b")).select(col('a'), col('b'))
>>> # 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: fields – Expression string.
Returns: The result table.