Table of Contents


  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Flatten Hierarchical Data with Schema Changes

Flatten Hierarchical Data with Schema Changes

You can flatten dynamic arrays, maps, and structs with schema changes into relational data. Use the flatten action in the Normalizer transformation to flatten dynamic arrays and maps. Use the EXTRACT_STRUCT function in dynamic expressions to extract all elements from a dynamic struct port in an Expression transformation.


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