Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. Parameter Reference

Rules and Guidelines for Complex Data Types

Rules and Guidelines for Complex Data Types

Consider the following rules and guidelines when you work with complex data types:
  • A nested data type can contain up to 10 levels of nesting.
  • A nested map can contain up to three levels of nesting of map data types.
  • An array data type cannot directly contain an element of type array. Use multidimensional arrays to create a nested array. For example, an array with two dimensions is an array of arrays.
  • A multidimensional array can contain up to five levels of nesting. The array dimension determines the levels of nesting.
  • Each array in a multidimensional array must have elements of the same data type.


Updated October 23, 2019