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
  • Informatica Data Quality 10.4.0
  • All Products

Table of Contents

Search

  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Back Next

Lookup Transformation in a Streaming Mapping

Lookup Transformation in a Streaming Mapping

Streaming mappings have additional processing rules that do not apply to batch mappings.

Mapping Validation

Mapping validation fails in the following situations:
  • The lookup is a data object.
  • An Aggregator transformation is in the same streaming pipeline as a passive Lookup transformation configured with an inequality lookup condition.
  • A Rank transformation is in the same streaming pipeline as a passive Lookup transformation configured with an inequality lookup condition.
  • A pipeline contains more than one passive Lookup transformation configured with an inequality condition.
The mapping fails in the following situations:
  • The transformation is unconnected.

General Guidelines

Consider the following general guidelines:
  • Using a float data type to look up data can return unexpected results.
  • Use a Lookup transformation to look up data in a flat file, HDFS, Hive, relational, and HBase data.
  • To avoid cross join of DataFrames, configure the Lookup transformation to ignore null values that match.

HBase Lookups

To use a Lookup transformation on uncached HBase tables, perform the following steps:
  1. Create an HBase data object. When you add an HBase table as the resource for a HBase data object, include the ROW ID column.
  2. Create a HBase read data operation and import it into the streaming mapping.
  3. When you import the data operation to the mapping, select the
    Lookup
     option.
  4. On the Lookup tab, configure the following options:
    • Lookup column. Specify an equality condition on ROW ID
    • Operator. Specify =
  5. Verify that format for any date value in the HBase tables is of a valid Java date format. Specify this format in the
    Date Time Format
     property of the
    Advanced Properties
     tab of the data object read operation.
If an HBase lookup does not result in a match, it generates a row with null values for all columns. You can add a Filter transformation after the Lookup transformation to filter out null rows.
Mapping validation fails in the following situations:
  • The condition does not contain a ROW ID.
  • The transformation contains an inequality condition.
  • The transformation contains multiple conditions.
  • An input column is of a date type.
0 COMMENTS
We’d like to hear from you!