gustavodemorais opened a new pull request, #27603:
URL: https://github.com/apache/flink/pull/27603
<!--
*Thank you very much for contributing to Apache Flink - we are happy that
you want to help us improve Flink. To help the community review your
contribution in the best possible way, please go through the checklist below,
which will get the contribution into a shape in which it can be best reviewed.*
*Please understand that we do not do this to make contributions to Flink a
hassle. In order to uphold a high standard of quality for code contributions,
while at the same time managing a large number of contributions, we need
contributors to prepare the contributions well, and give reviewers enough
contextual information for the review. Please also understand that
contributions that do not follow this guide will take longer to review and thus
typically be picked up with lower priority by the community.*
## Contribution Checklist
- Make sure that the pull request corresponds to a [JIRA
issue](https://issues.apache.org/jira/projects/FLINK/issues). Exceptions are
made for typos in JavaDoc or documentation files, which need no JIRA issue.
- Name the pull request in the form "[FLINK-XXXX] [component] Title of the
pull request", where *FLINK-XXXX* should be replaced by the actual issue
number. Skip *component* if you are unsure about which is the best component.
Typo fixes that have no associated JIRA issue should be named following
this pattern: `[hotfix] [docs] Fix typo in event time introduction` or
`[hotfix] [javadocs] Expand JavaDoc for PuncuatedWatermarkGenerator`.
- Fill out the template below to describe the changes contributed by the
pull request. That will give reviewers the context they need to do the review.
- Make sure that the change passes the automated tests, i.e., `mvn clean
verify` passes. You can set up Azure Pipelines CI to do that following [this
guide](https://cwiki.apache.org/confluence/display/FLINK/Azure+Pipelines#AzurePipelines-Tutorial:SettingupAzurePipelinesforaforkoftheFlinkrepository).
- Each pull request should address only one issue, not mix up code from
multiple issues.
- Each commit in the pull request has a meaningful commit message
(including the JIRA id)
- Once all items of the checklist are addressed, remove the above text and
this checklist, leaving only the filled out template below.
**(The sections below can be removed for hotfixes of typos)**
-->
## What is the purpose of the change
Currently, when a CAST operation is applied to a primary key or upsert key
column in a streaming query, Flink's optimizer loses track of the key even when
the cast is provably injective (one-to-one mapping). This causes the planner to
insert a SinkUpsertMaterializer operator unnecessarily, adding state overhead
and reducing performance.
For example:
```
CREATE TABLE source (
id INT PRIMARY KEY NOT ENFORCED,
name STRING
);
CREATE TABLE sink (
id STRING PRIMARY KEY NOT ENFORCED,
name STRING
);
INSERT INTO sink SELECT CAST(id AS STRING), name FROM source;
```
In this case, CAST(INT AS STRING) is injective - every distinct integer maps
to a distinct string representation. The upsert key should be preserved through
this cast. However, the current implementation treats any cast as potentially
key-destroying, requiring a SinkUpsertMaterializer to re-establish the key
before writing to the sink.
**Solution:**
Extend the key-tracking logic in FlinkRelMdUniqueKeys to recognize injective
casts as key-preserving operations. An explicit cast is considered injective
when every distinct input value maps to a distinct output value.
The following explicit casts to VARCHAR/CHAR are recognized as injective:
- Integer types: TINYINT, SMALLINT, INTEGER, BIGINT (biggest win)
The following were also added but are up to discussion since they're more
rarely used as unique keys
- Floating point types: FLOAT, DOUBLE
- BOOLEAN
- DATE
- Timestamp types: TIMESTAMP, TIMESTAMP_LTZ, TIMESTAMP_TZ
**Notes**
1. Implicit casts (fidelity casts / safe widenings like INT → BIGINT) were
already treated as key-preserving. This change extends that to cover explicit
injective casts.
2. Non-injective casts (e.g., STRING → INT, BIGINT → INT, TIMESTAMP → DATE)
remain non-key-preserving, as multiple distinct inputs can map to the same
output.
3. I left bytes -> string conversion out of this PR on purpose since it's a
more sensitive change since for this case it's not always 100% injective (in
the case the bytes are not UTF-8). I plan to open another PR only for this
change.
## Brief change log
- Add supportsInjectiveCast and isKeyPreservingCast
- Use new utils in unique key logic (which is used for upsert key)
- Add multiple tests
## Verifying this change
- Added unit tests
- Added unique key tests
- Added upsert key tests
- Added simple plan tests
## Does this pull request potentially affect one of the following parts:
- Dependencies (does it add or upgrade a dependency): (no)
- The public API, i.e., is any changed class annotated with
`@Public(Evolving)`: (no)
- The serializers: (no)
- The runtime per-record code paths (performance sensitive): (no)
- Anything that affects deployment or recovery: JobManager (and its
components), Checkpointing, Kubernetes/Yarn, ZooKeeper: (no)
- The S3 file system connector: (no)
## Documentation
- Does this pull request introduce a new feature? (no)
- If yes, how is the feature documented? (not applicable)
--
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]
