Communities
A collaborative platform to connect and grow with like-minded Informaticans across the globe
Product Communities
Connect and collaborate with Informatica experts and champions
Discussions
Have a question? Start a Discussion and get immediate answers you are looking for
User Groups
Customer-organized groups that meet online and in-person. Join today to network, share ideas, and get tips on how to get the most out of Informatica
Get Started
Community Guidelines
Knowledge Center
Troubleshooting documents, product guides, how to videos, best practices, and more
Knowledge Base
One-stop self-service portal for solutions, FAQs, Whitepapers, How Tos, Videos, and more
Support TV
Video channel for step-by-step instructions to use our products, best practices, troubleshooting tips, and much more
Documentation
Information library of the latest product documents
Velocity (Best Practices)
Best practices and use cases from the Implementation team
Learn
Rich resources to help you leverage full capabilities of our products
Trainings
Role-based training programs for the best ROI
Certifications
Get certified on Informatica products. Free, Foundation, or Professional
Product Learning Paths
Free and unlimited modules based on your expertise level and journey
Resources
Library of content to help you leverage the best of Informatica products
Tech Tuesdays Webinars
Most popular webinars on product architecture, best practices, and more
Product Availability Matrix
Product Availability Matrix statements of Informatica products
SupportFlash
Monthly support newsletter
Support Documents
Informatica Support Guide and Statements, Quick Start Guides, and Cloud Product Description Schedule
Product Lifecycle
End of Life statements of Informatica products
Ideas
Events
Change Request Tracking
Marketplace
English
  • Data Engineering Streaming 10.5.1
  • All Products

Table of Contents

Search

  1. Preface
  2. Introduction to Data Engineering Streaming
  3. Data Engineering Streaming Administration
  4. Sources in a Streaming Mapping
  5. Targets in a Streaming Mapping
  6. Streaming Mappings
  7. Window Transformation
  8. Appendix A: Connections
  9. Appendix B: Monitoring REST API Reference
  10. Appendix C: Sample Files

User Guide

User Guide

Back Next

Column Projections Properties

Column Projections Properties

The following table describes the columns projection properties that you configure for Amazon Kinesis Stream sources:
Property
Description
Column Name
The name field that contains data.
This property is read-only.
Type
The native data type of the resource.
This property is read-only.
Enable Column Projection
Indicates that you use a schema to read the data that the source streams.
By default, the data is streamed in binary format. To change the format in which the data is processed, select this option and specify the schema format.
Schema Format
The format in which the source processes data. You can select one of the following formats:
  • XML
  • JSON
  • Avro
  • Flat
Use Schema
Specify the XSD schema for the XML format, the sample JSON for the JSON format.
Specify a .avsc file for the Avro format or a sample file for the Flat format.
Use Intelligent Structure Model
Displays the intelligent structure model associated with the complex file. You can select a different model.
You can associate the data object with an intelligent structure model and directly parse input from CSV, XML, Avro, or JSON input files.
  • If you disable the column projection, the intelligent structure model associated with the data object is removed. If you want to associate an intelligent structure model with the data object again, enable the column projection and click
    Select Model
    .
  • A streaming mapping fails due to schema drift when you use Avro schema with an intelligent structure model.
For more information about intelligent structure models, see the
Data Engineering Integration User Guide
.
Column Mapping
The mapping of source data to the data object. Click
View
 to see the mapping.
Project Column as Complex Data Type
Project columns as complex data type for sources with hierarchical data.
Select this option if the source has hierarchical data.
For more information about hierarchical data, see the
Data Engineering Integration User Guide
.
0 COMMENTS
We’d like to hear from you!