Update to PySpark 3.5.3, limit numpy dependency to < 2

[codesorcery]

PySpark will only become compatible with NumPy 2 starting with PySpark 4. Thus, the NumPy dependency has been limited accordingly for PySpark 3.5 in https://github.com/apache/spark/pull/47175 The same should be done here, so that the builds will succeed again.

Checklist

• [x] Used a personal fork of the feedstock to propose changes
• [ ] Bumped the build number (if the version is unchanged)
• [ ] Reset the build number to 0 (if the version changed)
• [ ] Re-rendered with the latest conda-smithy (Use the phrase code>@<space/conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
• [ ] Ensured the license file is being packaged.

[conda-forge-admin]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipe/meta.yaml) and found it was in an excellent condition.

[codesorcery]

Build now fails, since only latest version (i.e. 3.5.3) is available at https://dist.apache.org/repos/dist/release/spark/ Thus, also directly updating PySpark to 3.5.3 here.

[h-vetinari]

Hey @codesorcery, thanks for the PR! It seems that @conda-forge/pyspark is not that active anymore, would you like to add yourself as a maintainer here?

[codesorcery]

Hi @h-vetinari, I'm not that deep into the build-setup for Conda packages and only use Conda for some side-projects. But if there's no one else maintaining this repository, I could try to do my best to maintain it.

[h-vetinari]

Cool! I'll join as well, so you can ask me if you have questions.

[github-actions[bot]]

Hi! This is the friendly conda-forge automerge bot!

I considered the following status checks when analyzing this PR:

• linter: passed
• azure: passed

Thus the PR was passing and merged! Have a great day!