Preface
Introduction to Informatica Big Data Management
Mappings in the Hadoop Environment
Mapping Sources in the Hadoop Environment
Mapping Targets in the Hadoop Environment
Mapping Transformations in the Hadoop Environment
Processing Hierarchical Data on the Spark Engine
Configuring Transformations to Process Hierarchical Data
Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
Stateful Computing on the Spark Engine
Monitoring Mappings in the Hadoop Environment
Mappings in the Native Environment
Profiles
Native Environment Optimization
Cluster Workflows
Connections
Data Type Reference
Function Reference
- Function Support in the Hadoop Environment
- Function and Data Type Processing
  - Rules and Guidelines for Spark Engine Processing
  - Rules and Guidelines for Hive Engine Processing
Parameter Reference
- Parameters Overview
- Parameter Usage

Big Data Management User Guide

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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.

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Table of Contents

Big Data Management User Guide

Big Data Management User Guide

Rules and Guidelines for Complex Data Types

Rules and Guidelines for Complex Data Types