Normalizer
transformation normalizes records from COBOL & relational sources allowing
you to organize the data according to your needs.A normalizer transformation
can appear anywhere in a data flow when you normalize a relational source.
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.
For example, a relational table contains quarterly sales totals 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:quarters of sales by store:
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.
For example, a relational table contains quarterly sales totals 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: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
|
