Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Connections
  4. Mappings in the Hadoop Environment
  5. Mapping Objects in the Hadoop Environment
  6. Processing Hierarchical Data on the Spark Engine
  7. Stateful Computing on the Spark Engine
  8. Monitoring Mappings in the Hadoop Environment
  9. Mappings in the Native Environment
  10. Profiles
  11. Native Environment Optimization
  12. Data Type Reference
  13. Complex File Data Object Properties
  14. Function Reference
  15. 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 December 13, 2018