Table of Contents

Search

  1. Preface
  2. Part 1: Version 10.5.2
  3. Part 2: Version 10.5.1 - 10.5.1.1
  4. Part 3: Versions 10.5 - 10.5.0.1
  5. Part 4: Versions 10.4.1 - 10.4.1.3
  6. Part 5: Versions 10.4 - 10.4.0.2
  7. Part 6: Versions 10.2.2 - 10.2.2 HotFix 1
  8. Part 7: Version 10.2.1
  9. Part 8: Version 10.2 - 10.2 HotFix 2

What's New and Changed (10.5.2)

What's New and Changed (10.5.2)

Transformation Support on the Blaze Engine

Transformation Support on the Blaze Engine

This section describes new transformation features on the Blaze engine in version 10.2.1.

Aggregator Transformation

Effective in version 10.2.1, the data cache for the Aggregator transformation uses variable length to store binary and string data types on the Blaze engine. Variable length reduces the amount of data that the data cache stores when the Aggregator transformation runs.
When data that passes through the Aggregator transformation is stored in the data cache using variable length, the Aggregator transformation is optimized to use sorted input and a Sorter transformation is inserted before the Aggregator transformation in the run-time mapping.
For more information, see the "Mapping Transformations in the Hadoop Environment" chapter in the
Informatica Big Data Management 10.2.1 User Guide
.

Match Transformation

Effective in version 10.2.1, you can run a mapping that contains a Match transformation that you configure for identity analysis on the Blaze engine.
Configure the Match transformation to write the identity index data to cache files. The mapping fails validation if you configure the Match transformation to write the index data to database tables.
For more information on transformation support, see the "Mapping Transformations in the Hadoop Environment" chapter in the
Informatica Big Data Management 10.2.1 User Guide
.

Rank Transformation

Effective in version 10.2.1, the data cache for the Rank transformation uses variable length to store binary and string data types on the Blaze engine. Variable length reduces the amount of data that the data cache stores when the Rank transformation runs.
When data that passes through the Rank transformation is stored in the data cache using variable length, the Rank transformation is optimized to use sorted input and a Sorter transformation is inserted before the Rank transformation in the run-time mapping.
For more information, see the "Mapping Transformations in the Hadoop Environment" chapter in the
Informatica Big Data Management 10.2.1 User Guide
.
For more information about transformation operations, see the
Informatica 10.2.1 Developer Transformation Guide
.

0 COMMENTS

We’d like to hear from you!