Table of Contents

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  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

Rules and Guidelines for Window Functions

Rules and Guidelines for Window Functions

Certain guidelines apply when you use window functions on the Spark engine.
Consider the following rules and guidelines when you define window functions in a transformation:
  • Specify a constant integer as the offset argument in a window function.
  • Specify a default argument that is the same data type as the input value.
  • You cannot specify a default argument that contains complex data type or a SYSTIMESTAMP argument.
  • To use the LEAD and LAG window functions, you must configure partition and order keys in the windowing properties.
  • To use an aggregate function as a window function in an Expression transformation, you must configure a frame specification in the windowing properties.


Updated September 28, 2020