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:
Post your question in the Spark Migration forum in the Snowflake Community.
Report an issue or request a new feature in the SMA.
Send an email to sma-support@snowflake.com.
We welcome your feedback on how we can enhance this tool. Please share your suggestions and comments.