Snowpark Migration Accelerator: Roadmap¶

The SMA team continuously enhances and updates the tool. You can track these improvements in the Release Notes.

The SMA team continuously improves the tool based on user feedback. This roadmap outlines current and future enhancements, and will be updated regularly.

Coming Soon¶

  • Initial support for converting SparkML code to SnowparkML

  • Initial support for converting Pandas and PySpark Pandas code to Snowpark

  • Better organization of Python import statements

  • Step-by-step conversion guide in the documentation

Planned¶

  • Enhanced assessment metrics beyond the Readiness Score, including:

    • Compatibility indicators for third-party libraries

    • Code parsing accuracy measurement

    • SQL conversion accuracy measurement

  • Command-line interface version of the Workspace Estimator (WE)

  • Comprehensive Airflow analysis and inventory tools

  • Automated conversion of Spark SQL to Snowflake SQL within Python and Scala code and notebooks

  • Automated conversion of HiveQL to Snowflake SQL within Python and Scala code and notebooks

  • Access to Workspace Estimator (WE) scripts through Snowflake Labs Git Repository

  • Integration with Workspace Estimator (WE) calculator

  • EMR and Cloudera analysis capabilities in Workspace Estimator (WE)

  • SMA deployment option within your Snowflake account

  • Interactive Assessment Application for analyzing SMA output

Feature Requests¶

We welcome your suggestions for improving the Snowpark Migration Accelerator (SMA). Here’s how you can share your feedback:

We welcome your feedback on how we can enhance this tool. Please share your suggestions and comments.

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