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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

Big Data Management User Guide

Big Data Management User Guide

Hive Complex Data Types

Hive Complex Data Types

Hive complex data types such as arrays, maps, and structs are a composite of primitive or complex data types. Informatica Developer represents complex data types with the string data type and uses delimiters to separate the elements of the complex data type.
Hive complex data types in a Hive source or Hive target are not supported when you run mappings on a Hadoop cluster.
The following table describes the transformation types and delimiters that are used to represent the complex data types:
Complex Data Type
Description
Array
The elements in the array are of string data type. The elements in the array are delimited by commas. For example, an array of
fruits
is represented as
[apple,banana,orange]
.
Map
Maps contain key-value pairs and are represented as pairs of strings and integers delimited by the
=
character. String and integer pairs are delimited by commas. For example, a map of
fruits
is represented as
[1=apple,2=banana,3=orange]
.
Struct
Structs are represented as pairs of strings and integers delimited by the
:
character. String and integer pairs are delimited by commas. For example, a struct of
fruits
is represented as
[1,apple]
.

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