The Normalizer transformation receives a row that contains multiple-occurring columns and returns a row for each instance of the multiple-occurring data. The transformation processes multiple-occurring columns or multiple-occurring groups of columns in each source row. The Normalizer transformation is an active transformation.
The Normalizer transformation parses multiple-occurring columns from COBOL sources, relational tables, or other sources. It can process multiple record types from a COBOL source that contains a REDEFINES clause.
For example, you might have a relational table that stores four quarters of sales by store. You need to create a row for each sales occurrence. You can configure a Normalizer transformation to return a separate row for each quarter.
The following source rows contain four quarters of sales by store:
Store1 100 300 500 700
Store2 250 450 650 850
The Normalizer returns a row for each store and sales combination. It also returns an index that identifies the quarter number:
Store1 100 1
Store1 300 2
Store1 500 3
Store1 700 4
Store2 250 1
Store2 450 2
Store2 650 3
Store2 850 4
The Normalizer transformation generates a key for each source row. The Integration Service increments the generated key sequence number each time it processes a source row. When the source row contains a multiple-occurring column or a multiple-occurring group of columns, the Normalizer transformation returns a row for each occurrence. Each row contains the same generated key value.
When the Normalizer returns multiple rows from a source row, it returns duplicate data for single-occurring source columns. For example, Store1 and Store2 repeat for each instance of sales.
You can create a VSAM Normalizer transformation or a pipeline Normalizer transformation:
VSAM Normalizer transformation.
A non-reusable transformation that is a Source Qualifier transformation for a COBOL source. The Mapping Designer creates VSAM Normalizer columns from a COBOL source in a mapping. The column attributes are read-only. The VSAM Normalizer receives a multiple-occurring source column through one input port.
Pipeline Normalizer transformation.
A transformation that processes multiple-occurring data from relational tables or flat files. You create the columns manually and edit them in the Transformation Developer or Mapping Designer. The pipeline Normalizer transformation represents multiple-occurring columns with one input port for each source column occurrence.