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draft: Spark33rebase #2075

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What changes are proposed in this pull request?

Briefly describe the changes included in this Pull Request.

How is this patch tested?

  • I have written tests (not required for typo or doc fix) and confirmed the proposed feature/bug-fix/change works.

Does this PR change any dependencies?

  • No. You can skip this section.
  • Yes. Make sure the dependencies are resolved correctly, and list changes here.

Does this PR add a new feature? If so, have you added samples on website?

  • No. You can skip this section.
  • Yes. Make sure you have added samples following below steps.
  1. Find the corresponding markdown file for your new feature in website/docs/documentation folder.
    Make sure you choose the correct class estimators/transformers and namespace.
  2. Follow the pattern in markdown file and add another section for your new API, including pyspark, scala (and .NET potentially) samples.
  3. Make sure the DocTable points to correct API link.
  4. Navigate to website folder, and run yarn run start to make sure the website renders correctly.
  5. Don't forget to add <!--pytest-codeblocks:cont--> before each python code blocks to enable auto-tests for python samples.
  6. Make sure the WebsiteSamplesTests job pass in the pipeline.

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Hey @JessicaXYWang 👋!
Thank you so much for contributing to our repository 🙌.
Someone from SynapseML Team will be reviewing this pull request soon.

We use semantic commit messages to streamline the release process.
Before your pull request can be merged, you should make sure your first commit and PR title start with a semantic prefix.
This helps us to create release messages and credit you for your hard work!

Examples of commit messages with semantic prefixes:

  • fix: Fix LightGBM crashes with empty partitions
  • feat: Make HTTP on Spark back-offs configurable
  • docs: Update Spark Serving usage
  • build: Add codecov support
  • perf: improve LightGBM memory usage
  • refactor: make python code generation rely on classes
  • style: Remove nulls from CNTKModel
  • test: Add test coverage for CNTKModel

To test your commit locally, please follow our guild on building from source.
Check out the developer guide for additional guidance on testing your change.

@JessicaXYWang JessicaXYWang changed the base branch from spark3.3 to master September 18, 2023 04:14
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codecov-commenter commented Sep 18, 2023

Codecov Report

Merging #2075 (4713d6e) into master (6ac187d) will decrease coverage by 43.89%.
The diff coverage is n/a.

@@             Coverage Diff             @@
##           master    #2075       +/-   ##
===========================================
- Coverage   87.06%   43.18%   -43.89%     
===========================================
  Files         306      306               
  Lines       16162    16162               
  Branches      824      824               
===========================================
- Hits        14072     6980     -7092     
- Misses       2090     9182     +7092     
Files Coverage Δ
...microsoft/azure/synapse/ml/codegen/PyCodegen.scala 0.00% <ø> (-93.62%) ⬇️

... and 216 files with indirect coverage changes

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Summary by GPT-4

This commit updates the versions of several dependencies in the SynapseML project. The Spark version is updated from 3.2.3 to 3.3.2, and the Horovod version is updated from 0.25.0 to 0.27.0.

In addition, the versions of Torch and Torchvision are updated, and the Transformers library is updated from version 4.15.0 to 4.32.1.

The commit also updates some test files to reflect these changes, and modifies some environment setup scripts and Dockerfiles accordingly.

Overall, this commit aims to keep the project up-to-date with its dependencies, which can bring performance improvements, bug fixes, and new features from these libraries into SynapseML.

Suggestions

The changes in this PR are generally good, but there are a few areas that could be improved:

  1. In the build.sbt file, the spark version is updated from "3.2.3" to "3.3.2". It would be helpful to include a comment explaining why this change was made.

  2. In the core/src/main/scala/com/microsoft/azure/synapse/ml/codegen/PyCodegen.scala file, several package versions are updated. Again, it would be helpful to include comments explaining why these changes were made.

  3. In the core/src/test/scala/com/microsoft/azure/synapse/ml/nbtest/DatabricksUtilities.scala file, several package versions are updated in the GPULibraries string. It would be helpful to include comments explaining why these changes were made.

  4. In the deep-learning/src/main/python/horovod_installation.sh file, several commands are changed and some are removed entirely. It would be helpful to include comments explaining why these changes were made.

  5. In the docs/Explore Algorithms/Hyperparameter Tuning/HyperOpt.ipynb file, the mlflow version is downgraded from 2.6.0 to 2.5.0 without explanation.

  6. In multiple files (e.g., DeepTextClassifier.py, DeepVisionClassifier.py, etc.), checks for specific versions of packages (e.g., transformers and horovod) are updated without explanation.

  7. The Dockerfiles in tools/docker/demo/Dockerfile and tools/docker/minimal/Dockerfile have their Spark and Hadoop versions updated without explanation.

  8. The script in tools/dotnet/dotnetSetup.sh has its Spark version updated without explanation.

In general, it's important to explain why version updates are being made so that other developers can understand the rationale behind these changes.

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

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