zero323 opened a new pull request #27406: [SPARK-30681][PYSPARK][SQL] Add higher order functions API to PySpark URL: https://github.com/apache/spark/pull/27406 <!-- Thanks for sending a pull request! Here are some tips for you: 1. If this is your first time, please read our contributor guidelines: https://spark.apache.org/contributing.html 2. Ensure you have added or run the appropriate tests for your PR: https://spark.apache.org/developer-tools.html 3. If the PR is unfinished, add '[WIP]' in your PR title, e.g., '[WIP][SPARK-XXXX] Your PR title ...'. 4. Be sure to keep the PR description updated to reflect all changes. 5. Please write your PR title to summarize what this PR proposes. 6. If possible, provide a concise example to reproduce the issue for a faster review. --> ### What changes were proposed in this pull request? <!-- Please clarify what changes you are proposing. The purpose of this section is to outline the changes and how this PR fixes the issue. If possible, please consider writing useful notes for better and faster reviews in your PR. See the examples below. 1. If you refactor some codes with changing classes, showing the class hierarchy will help reviewers. 2. If you fix some SQL features, you can provide some references of other DBMSes. 3. If there is design documentation, please add the link. 4. If there is a discussion in the mailing list, please add the link. --> This PR add Python API for invoking following higher functions: - `transform` - `exists` - `forall` - `filter` - `aggregate` - `zip_with` - `transform_keys` - `transform_values` - `map_filter` - `map_zip_with` to `pyspark.sql`. Each of these accepts plain Python functions of one of the following types - `(Column) -> Column: ...` - `(Column, Column) -> Column: ...` - `(Column, Column, Column) -> Column: ...` Internally this proposal piggbacks on top of objects supporting Scala implementation ([SPARK-27297](https://issues.apache.org/jira/browse/SPARK-27297)) by: 1. Creating required `UnresolvedNamedLambdaVariables` exposing these as PySpark `Columns` 2. Invoking Python function with these columns as arguments. 3. Using the result, and underlying JVM objects from 1., to create `expressions.LambdaFunction` which is passed to desired expression, and repacked as Python `Column`. ### Why are the changes needed? <!-- Please clarify why the changes are needed. For instance, 1. If you propose a new API, clarify the use case for a new API. 2. If you fix a bug, you can clarify why it is a bug. --> Currently higher order functions are available only using SQL and Scala API and can use only SQL expressions ```python df.selectExpr("transform(values, x -> x + 1)") ``` This works reasonably well for simple functions, but can get really ugly with complex functions (complex functions, casts), resulting objects are somewhat verbose and we don't get any IDE support. Additionally DSL used, though very simple, is not documented. ### Does this PR introduce any user-facing change? <!-- If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible. If no, write 'No'. --> No. ### How was this patch tested? <!-- If tests were added, say they were added here. Please make sure to add some test cases that check the changes thoroughly including negative and positive cases if possible. If it was tested in a way different from regular unit tests, please clarify how you tested step by step, ideally copy and paste-able, so that other reviewers can test and check, and descendants can verify in the future. If tests were not added, please describe why they were not added and/or why it was difficult to add. --> - For positive cases this PR adds doctest strings covering possible usage patterns. - For negative cases (unsupported function types) this PR adds unit tests.
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