dstrodtman-db commented on code in PR #42272: URL: https://github.com/apache/spark/pull/42272#discussion_r1287312350
########## python/docs/source/user_guide/sql/python_udtf.rst: ########## @@ -0,0 +1,203 @@ +.. Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + regarding copyright ownership. The ASF licenses this file + to you under the Apache License, Version 2.0 (the + "License"); you may not use this file except in compliance + with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, + software distributed under the License is distributed on an + "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + KIND, either express or implied. See the License for the + specific language governing permissions and limitations + under the License. + +=========================================== +Python User-defined Table Functions (UDTFs) +=========================================== + +Spark 3.5 introduces Python user-defined table functions (UDTFs), a new type of user-defined function. +Unlike scalar functions that return a single result value, a UDTF is invoked in the FROM clause and returns +an entire relation as output. Each UDTF call can accept zero or more arguments. +These arguments can be scalar constant expressions or separate input relations. + +Implementing a Python UDTF +-------------------------- + +.. currentmodule:: pyspark.sql.functions + +To implement a Python UDTF, you can define a class implementing the methods: + +.. code-block:: python + + class PythonUDTF: + + def __init__(self) -> None: + """ + Initialize the user-defined table function (UDTF). + + This method serves as the default constructor and is called once when the + UDTF is instantiated on the executor side. Although its implementation is + optional, it can be for any necessary initialization, such as setting up + resources or state for the UDTF. + + Any class fields assigned in this method will be available for subsequent + calls to the `eval` and `terminate` methods. + + Notes + ----- + - This method does not accept any extra arguments. + - You cannot reference the Spark session within the UDTF. Any attempt to + do so will result in a serialization error. + """ + ... + + def eval(self, *args: Any) -> Iterator[Any]: + """ + Evaluate the function using the given input arguments. + + This method is required and must be implemented. + + The arguments provided to the UDTF call are mapped to the values in the + `*args` list sequentially. Each provided scalar expression maps to exactly + one value in this `*args` list. Each provided TABLE argument of N columns + maps to exactly N values in this `*args` list, in the order of the columns + as they appear in the table. + + This method is called on every input row, and can produce zero or more + output rows. Each element in the tuple will correspond to one column + specified in the return type of the UDTF. + + Parameters + ---------- + *args : Any + Arbitrary positional arguments representing the input to the UDTF. + + Yields + ------ + tuple + A tuple representing a single row in the UDTF result relation. + Yield as many times as needed to produce multiple rows. + + Notes + ----- + - The result of the function must be a tuple representing a single row + in the UDTF result relation. + - UDTFs do not ccept keyword arguments during the function call. Review Comment: ```suggestion - UDTFs do not accept keyword arguments during the function call. ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
