longvu-db opened a new pull request, #44988:
URL: https://github.com/apache/spark/pull/44988

   <!--
   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?
   <!--
   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 extends `DynamicPruningSubquery` to support broadcasting of multiple 
filtering keys (instead of one as before). The majority of the PR is to simply 
generalise singularity to plurality.
   
   **Note:** We actually do not use the multiple filtering keys 
`DynamicPruningSubquery` in this PR, we are doing this to make supporting DPP 
Null Safe Equality or multiple Equality predicates easier in the future.
   
   In Null Safe Equality JOIN, the JOIN condition `a <=> b` is transformed to 
`Coalesce(key1, Literal(key1.dataType)) = Coalesce(key2, 
Literal(key2.dataType)) AND IsNull(key1) = IsNull(key2)`. In order to have the 
highest pruning efficiency, we broadcast the 2 keys `Coalesce(key, 
Literal(key.dataType))` and `IsNull(key)` and use them to prune the other side 
at the same time. 
   
   Before, the `DynamicPruningSubquery` only has one broadcasting key and we 
only supports DPP for one `EqualTo` JOIN predicate, now we are extending the 
subquery to multiple broadcasting keys. Please note that DPP has not been 
supported for multiple JOIN predicates. 
   
   Put it in another way, at the moment, we don't insert a DPP Filter for 
multiple JOIN predicates at the same time, only potentially insert a DPP Filter 
for a given Equality JOIN predicate.
   
   
   ### 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.
   -->
   To make supporting DPP Null Safe Equality or DPP multiple Equality 
predicates easier in the future.
   
   ### Does this PR introduce _any_ user-facing change?
   <!--
   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'.
   -->
   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.
   -->
   Added unit tests.
   
   ### 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.
   -->
   No.


-- 
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]

Reply via email to