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====================== User Defined Functions

Scalar Function

A user-defined scalar functions maps zero, one, or multiple scalar values to a new scalar value.

.. currentmodule:: pyflink.table.udf

.. autosummary:: :toctree: api/

ScalarFunction
udf

Table Function

A user-defined table function creates zero, one, or multiple rows to a new row value.

.. currentmodule:: pyflink.table.udf

.. autosummary:: :toctree: api/

TableFunction
udtf

Aggregate Function

A user-defined aggregate function maps scalar values of multiple rows to a new scalar value.

.. currentmodule:: pyflink.table.udf

.. autosummary:: :toctree: api/

AggregateFunction
udaf

Table Aggregate Function

A user-defined table aggregate function maps scalar values of multiple rows to zero, one, or multiple rows (or structured types). If an output record consists of only one field, the structured record can be omitted, and a scalar value can be emitted that will be implicitly wrapped into a row by the runtime.

.. currentmodule:: pyflink.table.udf

.. autosummary:: :toctree: api/

TableAggregateFunction
udtaf

DataView

If an accumulator needs to store large amounts of data, pyflink.table.ListView and pyflink.table.MapView could be used instead of list and dict. These two data structures provide the similar functionalities as list and dict, however usually having better performance by leveraging Flink’s state backend to eliminate unnecessary state access. You can use them by declaring DataTypes.LIST_VIEW(...) and DataTypes.MAP_VIEW(...) in the accumulator type.

.. currentmodule:: pyflink.table.data_view

.. autosummary:: :toctree: api/

ListView
MapView