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Hitachi Vantara Lumada and Pentaho Documentation

Row Denormaliser

Parent article

The Row denormaliser step can be used to try to improve performance either by adding redundant copies of data values or by grouping data. You can also use this step to convert data types.

NoteThe data must be normalized before you can denormalize it.

For example, consider the following set of normalized data:

Produce CategoryDelivery TimeProduce Type
fruit2018/01/05 08:00:00apples
fruit2018/01/05 08:10:00oranges
fruit2018/01/05 08:20:00apples
fruit2018/01/05 08:30:00oranges

The data can be denormalized by grouping on the type of fruit, as shown in the following table:

Produce CategoryApplesOranges
fruit2018/01/05 08:00:002018/01/05 08:10:00
fruit2018/01/05 08:20:002018/01/05 08:30:00


Enter the following information in the transformation step fields.

Step nameSpecify the unique name of the transformation step on the canvas. The step name is set to Row denormaliser by default.
Key fieldDefine the key of the output row. The available fields are from the incoming PDI data stream. Another step with output data must be connected to the Row denormaliser step via hop for options to appear in this field.

Group field table

Group field table in Row               denormaliser

Use The fields that make up the grouping table to specify what fields from the incoming PDI data stream define the grouping for the denormalization process. You can click Get Fields to automatically fill the table with all the fields from the incoming PDI data stream.

Target fields table

Target fields table in Row               denormaliser

Use the Target fields table to select the fields to denormalize by specifying the String value for the Key field. Options are provided to convert data types. Strings are most common as key-value pairs so you must often convert to Integer, Number or Date. If you get key-value pair collisions (key is not unique for the group specified), specify the aggregation method to use. You can click Get lookup fields to retrieve fields from the PDI data stream.


The data-integration/samples/transformations directory contains the following example KTRs that show how to use this step:

Example KTR FileDescription
Denormaliser – Simple Example.ktrConverts a ‘month’ row in a record to a multiple ‘month’ columns.
Denormaliser – Data Conversion and Aggregation.ktrConverts data values by ‘month’.
Denormaliser – 2 Series of Key-Value Pairs.ktrConverts ‘name’ and ‘ID’ rows to multiple ‘name’ and ‘ID’ columns.
Denormaliser – Capturing Last State Timestamp.ktrAggregates data values by ‘state’.

Metadata injection support

All fields of this step support metadata injection. You can use this step with ETL metadata injection to pass metadata to your transformation at runtime.