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 Ports

Rules and Guidelines for Complex Ports

Consider the following rules and guidelines when you work with complex ports:
  • Aggregator transformation. You cannot define a group by value as a complex port.
  • Filter transformation. You cannot use the operators >, < , >=, and <= in a filter condition to compare data in complex ports.
  • Joiner transformation. You cannot use the operators >, < , >=, and <= in a join condition to compare data in complex ports.
  • Lookup transformation. You cannot use a complex port in a lookup condition.
  • Rank transformation. You cannot define a group by or rank value as a complex port.
  • Router transformation. You cannot use the operators >, < , >=, and <= in a group filter condition to compare data in complex ports.
  • Sorter transformation. You cannot define a sort key value as a complex port.
  • You can use complex operators to specify an element of a complex port that is of a primitive data type.
    For example, an array port "emp_names" contains string elements. You can define a group by value as emp_names[0], which is of type string.


Updated October 23, 2019