sven-weber-db opened a new pull request, #55768:
URL: https://github.com/apache/spark/pull/55768
<!--
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.
7. If you want to add a new configuration, please read the guideline first
for naming configurations in
'core/src/main/scala/org/apache/spark/internal/config/ConfigEntry.scala'.
8. If you want to add or modify an error type or message, please read the
guideline first in
'common/utils/src/main/resources/error/README.md'.
-->
### What changes were proposed in this pull request?
This PR introduces new logical and physical Catalyst nodes for
language-agnostic User Defined Functions (UDF) as part of [SPIP
SPARK-55278](https://issues.apache.org/jira/browse/SPARK-55278), which proposes
language-agnostic UDFs.
As a first step towards the goal of language-agnostic UDFs, we want to
target mapPartition UDFs like `pyspark.sql.DataFrame.mapInArrow`,
`pyspark.RDD.mapPartitions`, or `pyspark.sql.DataFrame.mapInArrow`. The
overarching goal is to deprecate the current, language-specific Catalyst nodes
(like `mapInArrow`). However, for now, the new nodes will exist in addition to
the old ones until the new framework has reach maturity.
In summary, this PR introduces:
- A new Catalyst Expression, `ExternalUDFExpression`, which captures
language-agnostic UDF properties (payload, name, etc.)
- A new Catalyst logical node, `ExternalUDF`, which serves as a base class
for all language-agnostic UDF nodes
- A new Catalyst logical node, `MapPartitionExternalUDF`, which is the new,
language-agnostic map partition node
- Catalyst physical nodes for both logical nodes
- `WorkerDispatcherManager` - A manager class which manages UDF Dispatchers
based on the target `UDFWorkerSpecification`
None of the changes introduced above are currently consumed in Spark.
### Why are the changes needed?
This is the first step toward language-agnostic UDF execution for Spark.
Existing physical and logical planning nodes need to be replaced eventually to
achieve this goal as they make language-specific assumptions.
### Does this PR introduce _any_ user-facing change?
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.
If benchmark tests were added, please run the benchmarks in GitHub Actions
for the consistent environment, and the instructions could accord to:
https://spark.apache.org/developer-tools.html#github-workflow-benchmarks.
-->
New unit-tests were added.
### Was this patch authored or co-authored using generative AI tooling?
<!--
If generative AI tooling has been used in the process of authoring this
patch, please include the
phrase: 'Generated-by: ' followed by the name of the tool and its version.
If no, write 'No'.
Please refer to the [ASF Generative Tooling
Guidance](https://www.apache.org/legal/generative-tooling.html) for details.
-->
Partially. However, the code was manually reviewed and adjusted.
--
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]
