Table of Contents

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  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

Sampling Options

Sampling Options

Sampling options determine the number of rows on which the Analyst tool or Developer tool runs a profile. You can configure sampling options when you define a profile or run a profile.
The following table describes the sampling options for a profile:
Sampling Option
Description
All rows
Runs a profile on all the rows in the data object.
Supported on Native, Blaze, and Spark run-time environment.
Sample first <number> rows
Runs a profile on the sample rows from the beginning of the rows in the data object. You can choose a maximum of 2,147,483,647 rows.
Supported on Native and Blaze run-time environment.
Random sample <number> rows
Runs a profile on a randomly picked number of the rows in the data object. You can choose a maximum of 2,147,483,647 rows.
Supported on Native and Blaze run-time environment.
Random sample (auto)
Runs a profile on the sample rows computed on the basis of the number of rows in the data object.
Supported on Native and Blaze run-time environment.
Limit n <number> rows
Runs a profile based on the number of rows in the data object. When you choose to run a profile in the Hadoop validation environment, Spark engine collects samples from multiple partitions of the data object and pushes the samples to a single node to compute sample size. The Limit n sampling option supports Oracle, SQL Server, and DB2 databases. You cannot apply the Advanced filter with the Limit n sampling option.
Supported on Spark run-time environment.
Random percentage
Runs a profile on a percentage of rows in the data object.
Supported on Spark run-time environment.
Exclude approved data types and data domains from the data type and data domain inference in the subsequent profile run
Excludes the approved data type or data domain from data type and data domain inference from the next profile run.


Updated September 28, 2020