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 10.4.1
  • All Products

Table of Contents

Search

  1. Preface
  2. Part 1: Version 10.4.1
  3. Part 2: Version 10.4.0
  4. Part 3: Version 10.2.2
  5. Part 4: Version 10.2.1
  6. Part 5: Version 10.2
  7. Part 6: Version 10.1.1
  8. Part 7: Version 10.1

Release Guide

Release Guide

Back Next

Date/Time Format on Databricks

Date/Time Format on Databricks

Effective in version 10.4.0, when the Databricks Spark engine reads and writes date/time values, it uses the format YYYY-MM-DD HH24:MM:SS.US.
Previously, you set the format in the mapping properties for the run-time preferences of the Developer tool.
You might need to perform additional tasks to continue using date/time data on the Databricks engine. For more information, see the "Databricks Integration" chapter in the
Data Engineering 10.4.0 Integration Guide
.
0 COMMENTS
We’d like to hear from you!