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 Quality 10.2.1
  • All Products

Table of Contents

Search

  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. Parameter Reference

Big Data Management User Guide

Big Data Management User Guide

Back Next

Update Strategy Transformation Support on the Blaze Engine

Update Strategy Transformation Support on the Blaze Engine

You can use the Update Strategy transformation on the Hadoop distributions that support Hive ACID.
Some processing rules for the Blaze engine differ from the processing rules for the Data Integration Service.

General Restrictions

If the Update Strategy transformation receives multiple update rows for the same primary key value, the transformation selects one random row to update the target.
If multiple Update Strategy transformations write to different instances of the same target, the target data might be unpredictable.
The Blaze engine executes operations in the following order: deletes, updates, inserts. It does not process rows in the same order as the Update Strategy transformation receives them.
Hive targets always perform Update as Update operations. Hive targets do not support Update Else Insert or Update as Insert.

Mapping Validation and Compile Validation

Mapping validation fails in the following situations:
  • The Update Strategy transformation is connected to more than one target.
  • The Update Strategy transformation is not located immediately before the target.
  • The Update Strategy target is not a Hive target.
  • The Update Strategy transformation target is an external ACID table.
  • The target does not contain a primary key.
  • The Hive target property to truncate the target table at run time is enabled.
  • The Hive target property to create or replace the target table at run time is enabled.
The mapping fails in the following situation:
  • The target is not ORC bucketed.
  • The Hive target is modified to have fewer rows than the actual table.
Compile validation errors occur and the mapping execution stops in the following situations:
  • The Hive version is earlier than 0.14.
  • The target table is not enabled for transactions.

Using Hive Target Tables

To use a Hive target table with an Update Strategy transformation, you must create the Hive target table with the following clause in the Hive Data Definition Language:
TBLPROPERTIES ("transactional"="true")
.
To use an Update Strategy transformation with a Hive target, verify that the following properties are configured in the hive-site.xml configuration set associated with the Hadoop connection: 
hive.support.concurrency         true
hive.enforce.bucketing           true
hive.exec.dynamic.partition.mode nonstrict
hive.txn.manager         org.apache.hadoop.hive.ql.lockmgr.DbTxnManager
hive.compactor.initiator.on      true
hive.compactor.worker.threads    1
0 COMMENTS
We’d like to hear from you!