SreeramaYeshwanthGowd opened a new pull request, #39442:
URL: https://github.com/apache/beam/pull/39442
### Problem
Java has `Sample.any(n)`, which returns up to n arbitrary elements from a
PCollection without the cost of a uniform random sample. The Python SDK has
no
equivalent. Its only global option is `Sample.FixedSizeGlobally(n)`, which
runs
a uniform reservoir sample and returns a single `list[T]`. This gap was
reported
in #18552.
### Solution
Add `Sample.Any`, the Python equivalent of Java's `Sample.any`. It keeps up
to n
arbitrary elements using a small `CombineFn` and returns them as a
PCollection
of individual elements. It makes no uniformity guarantee and is cheaper than
`FixedSizeGlobally` because it skips the per element random sampling. If the
input has fewer than n elements, all of them are returned. This mirrors
Java's
semantics and its element returning result type.
### Testing
Added unit tests in `combiners_test.py` that run on the DirectRunner and
cover
the normal case, an input smaller than n, a windowed input, an empty input,
and
n equal to zero. Also extended the existing display data test to cover the
new
transform.
Fixes #18552
------------------------
Thank you for your contribution! Follow this checklist to help us
incorporate your contribution quickly and easily:
- [x] Mention the appropriate issue in your description (for example:
`addresses #123`), if applicable. This will automatically add a link to the
pull request in the issue. If you would like the issue to automatically close
on merging the pull request, comment `fixes #<ISSUE NUMBER>` instead.
- [x] Update `CHANGES.md` with noteworthy changes.
- [ ] If this contribution is large, please file an Apache [Individual
Contributor License Agreement](https://www.apache.org/licenses/icla.pdf).
See the [Contributor Guide](https://beam.apache.org/contribute) for more
tips on [how to make review process
smoother](https://github.com/apache/beam/blob/master/CONTRIBUTING.md#make-the-reviewers-job-easier).
--
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]
