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

Map Data Type

Map Data Type

A map data type represents an unordered collection of key-value pair elements. A map element is a key and value pair that maps one thing to another. To pass, generate, or process map data, assign map data type to ports.
The key must be of a primitive data type. The value can be of a primitive or complex data type. A map data type with values of a complex data type is a nested map. A nested map can contain up to three levels of nesting of map data type.
The Spark engine allows duplicate keys in the map data.
The transformation language includes subscript operator to access map elements. It also includes functions to generate and process map data.


map <primitive_type -> data_type>
The following table describes the arguments for this data type:
Name of the map column or port.
Data type of the key in a map element.
The key must be of a primitive data type.
Data type of the value in a map element.
The value can be of a primitive or complex data type.

Map Example

The following map column represents map data with an integer key and a string value to map customer ids with customer names:
custid_name <integer -> string>
The following example shows data values for the custid_name column:
<26745 -> 'John Baer'>
<56743 -> 'Bobbi Apperley'>
<32879 -> 'Linda Bender'>


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