eejbyfeldt opened a new pull request, #43213:
URL: https://github.com/apache/spark/pull/43213
<!--
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
'core/src/main/resources/error/README.md'.
-->
### What changes were proposed in this pull request?
Support for InMememoryTableScanExec in AQE was added in #39624, but this
patch contained a bug when a Dataset is persisted using `StorageLevel.NONE`.
Before that patch a query like:
```
import org.apache.spark.storage.StorageLevel
spark.createDataset(Seq(1, 2)).persist(StorageLevel.NONE).count()
```
would correctly return 2. But after that patch it incorrectly returns 0.
This is because AQE incorrectly determines based on the runtime statistics that
are collected here:
https://github.com/apache/spark/blob/eac5a8c7e6da94bb27e926fc9a681aed6582f7d3/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/InMemoryRelation.scala#L294
that the input is empty. The problem is that the action that should make
sure the statistics are collected here
https://github.com/apache/spark/blob/eac5a8c7e6da94bb27e926fc9a681aed6582f7d3/sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/QueryStageExec.scala#L285-L291
never use the iterator and when we have `StorageLevel.NONE` the persisting
will also not use the iterator and we will not gather the correct statistics.
The proposed fix in the patch just make calling persist with
StorageLevel.NONE a no-op. Changing the action since it always "emptied" the
iterator would also work but seems like that would be unnecessary work in a lot
of normal circumstances.
<!--
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.
-->
### Why are the changes needed?
The current code has a correctness issue.
<!--
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.
-->
### Does this PR introduce _any_ user-facing change?
Yes, fixes the correctness issue.
<!--
Note that it means *any* user-facing change including all aspects such as
the documentation fix.
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 possible, please also clarify if this is a user-facing change compared to
the released Spark versions or within the unreleased branches such as master.
If no, write 'No'.
-->
### How was this patch tested?
New and existing unit tests.
<!--
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.
-->
### Was this patch authored or co-authored using generative AI tooling?
No
<!--
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.
-->
--
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]
