Normalizer transformation is an active
transformation that transforms one source row into multiple target rows. The
transformation can pass source data from one source row to multiple targets to
reduce target file size and to decrease data redundancy. When you define the
Normalizer transformation, you configure an input row hierarchy that describes
the source data structure.
Generated Column ID
The Normalizer
transformation returns a Generated Column ID output port for each
instance of a multiple-occurring field. For example, if a field occurs four
times in a source record, the Developer tool returns a value of 1, 2, 3, or 4
in the generated column ID port based on which instance of the
multiple-occurring data occurs in the row.
Input Hierarchy Definition
When we create a
Normalizer transformation, we define an input hierarchy that describes records
and fields in the source.The Developer tool creates the transformation input
ports based on our definition.
Occurs column in the Normalizer view identifies
the number of instances of a field or record in a source row.
Level column in the Normalizer view indicates
where a field or record appears in the input hierarchy.
Output Groups and Ports
The output groups
and ports are defined in the Overview view of the Normalizer transformation.
You can create the output ports after you define the transformation input
hierarchy. The Developer tool generates the first level output groups by
default. The Developer tool does not generate an output group for any record.
You must manually configure how you want to return the multiple-occurring
groups of fields.
Advanced properties for normalizer transformation
Automatically generate first-level output groups
Automatically generates the output groups for level 1 fields.
Tracing Level Amount of detail that appears in
the log for this transformation.
Scenario
Normalize
multiple-occurring quarterly sales data
*In case of any
questions, feel free to leave comments on this page and I would get back as
soon as I can.
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