Prepare Recommendations

Recommendations and Scripts provide rich technical details and tips about the components, usage, and performance of dataflows.

The dataflow must be saved before Recommendations can be accessed. Even if only one entity has been added to the canvas, the dataflow must be saved to access helpful design tips. For example, when JDBC entities are discovered at the same time, relations between fields are identified and retained for Primary Keys (PK) and Foreign Keys (FK). This information is leveraged in the metadata to assist users to build dataflows.

Recommendations: Common Usage tab details how the same entities have been used in other dataflows.

Prepare recommendations common usage

Recommendations: Design Tips provide options and directions for dataflow design. For example, for a JDBC entity that was discovered with other entities, design tips may provide primary and foreign keys that help for designing joins. Suggestions are provided for building dataflows such as join conditions, filter and router options, transform ranges and trimming options.

Prepare recommendations design tips

Recommendations: Performance Tips tab details how users can optimize performance for dataflow executions

Prepare recommendations performance tips

Performance recommendations are generated when the latest execution of a dataflow is in Mapreduce mode. (Mapreduce mode is when Mapreduce is invoked in the back-end to perform a particular operation on the data that exists in the file system). However, if the dataflow is a simple one, no performance recommendations may be generated.

Did this page help you?

If you find any issues with this page or its content – a typo, a missing step, or a technical error – let us know how we can improve!

Leave your feedback here