Table of Contents


  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Overview of Data Preview

Overview of Data Preview

You can preview data within a mapping in the Developer tool. You can choose sources and transformations in a mapping as preview points. Previewing data helps to design and debug mappings.
Data preview jobs run on either the Data Integration Service or the Spark engine. The Spark engine runs the job in the following cases:
  • The preview point or any upstream transformation contains hierarchical data.
  • The preview point or any upstream transformation is a Python transformation.
  • The preview point or any upstream transformation is an Expression transformation configured for windowing.
  • The mapping contains a combination of transformations that must run on the Spark engine.
When you view the results of data preview on hierarchical data, you can view the complex data types, the schema, and values. You can also navigate through the structure with breadcrumbs. You can export the results to a JSON file.
Before you preview data, verify that Spark is configured as the mapping run-time environment. If you are previewing hierarchical data in a complex file object, add the complex file object to a mapping to preview the data. You cannot preview data in mappings configured for the Databricks Spark engine.
Monitor ad hoc data preview jobs in the Monitor tab of the Administrator tool. From the Monitor tab, you can view job status, view job logs, and cancel jobs.


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