BryanCutler commented on a change in pull request #27466: [SPARK-30722][PYTHON][DOCS] Update documentation for Pandas UDF with Python type hints URL: https://github.com/apache/spark/pull/27466#discussion_r375575696
########## File path: docs/sql-pyspark-pandas-with-arrow.md ########## @@ -65,132 +65,188 @@ Spark will fall back to create the DataFrame without Arrow. ## Pandas UDFs (a.k.a. Vectorized UDFs) -Pandas UDFs are user defined functions that are executed by Spark using Arrow to transfer data and -Pandas to work with the data. A Pandas UDF is defined using the keyword `pandas_udf` as a decorator -or to wrap the function, no additional configuration is required. Currently, there are two types of -Pandas UDF: Scalar and Grouped Map. +Pandas UDFs are user defined functions that are executed by Spark using +Arrow to transfer data and Pandas to work with the data, which allows vectorized operations. A Pandas +UDF is defined using the `pandas_udf` as a decorator or to wrap the function, and no additional +configuration is required. A Pandas UDF behaves as a regular PySpark function API in general. -### Scalar +Before Spark 3.0, Pandas UDFs used to be defined with `PandasUDFType`. From Spark 3.0 +with Python 3.6+, you can also use Python type hints. Using Python type hints are preferred and the +previous way will be deprecated in the future release. Review comment: instead of "previous way" maybe say "using a `PandasUDFType` will be deprecated.." so it's clear what is planned to be deprecated. ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
