AWS Clean Rooms supports error message configurations for PySpark analyses

AWS Clean Rooms now supports error message configurations for PySpark, enabling companies and their partners to develop and test sophisticated analytics faster in a Clean Rooms collaboration. With this launch, you and your partners can specify how much information appears in error messages for analyses that use PySpark, the Python API for Apache Spark. Code authors can configure a PySpark analysis to return detailed error messages when a PySpark analysis fails, provided that each collaboration member approves the analysis to run on their data. For example, when a code author is testing their code for a marketing attribution model in a clean rooms collaboration, they can enable detailed error messages for faster troubleshooting, reducing time-to-insights from weeks to hours or days.

AWS Clean Rooms helps companies and their partners easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.

Categories: marketing:marchitecture/analytics,general:products/aws-clean-rooms

Source: Amazon Web Services

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