Row Normaliser

Description

The Row Normaliser transform converts the columns of an input stream into rows.

You can use this transform to normalize repeating groups of columns.

Important: When combining multiple columns with different meta types (e.g., String and Integer) into a new field, no automatic type conversion is performed. Instead the first meta type is set. This lack of conversion may lead to issues with subsequent transformations on the resulting data rows. It is strongly advised to ensure that the data types of values being put into the same field are aligned before normalization.

Supported Engines

Hop Engine

Supported

Spark

Supported

Flink

Supported

Dataflow

Supported

Options

Option	Description
Transform name	Name of the transform this name has to be unique in a single pipeline.
Typefield	The name of the type field (product in the example above).
Fields table	A list of the fields you want to normalize; you must set the following properties for each selected field: Fieldname: Name of the fields to normalize (Product A ? C in the example). Type: Give a string to classify the field (A, B or C in our example). New field: You can give one or more fields where the new value should transferred to (sales in our example).
Get Fields	Click to retrieve a list of all fields coming in on the stream(s).

Option

Description

Transform name

Name of the transform this name has to be unique in a single pipeline.

Typefield

The name of the type field (product in the example above).

Fields table

A list of the fields you want to normalize; you must set the following properties for each selected field:

Fieldname: Name of the fields to normalize (Product A ? C in the example).
Type: Give a string to classify the field (A, B or C in our example).
New field: You can give one or more fields where the new value should transferred to (sales in our example).

Get Fields

Click to retrieve a list of all fields coming in on the stream(s).

Metadata Injection Support

All fields of this transform support metadata injection. You can use this transform with ETL Metadata Injection to pass metadata to your pipeline at runtime.