How Grouping Works in Decision Tables

Here are some considerations for grouping decision table rows.

• You can group a table’s rows by up to two input fields that use the Equals operator.
• You can group a decision table’s rows when the input condition uses the All, Any, or Custom logic.

  If you use the Any or Custom logic, grouping fields aren’t part of the input condition logic. However, the grouping fields are appended to the logic by default.

  For example, a decision table has four input fields (3). The table’s rows are grouped by the Name and Id fields (2). The table is configured with the Any condition logic, which uses the OR operator. Here, the grouping fields are excluded from the condition logic (1).

  

• When you group a table’s rows by two input fields, you must pass lookup values for both the fields.
• You can group a decision table’s rows when the number of input fields used for grouping is less than the total number of input fields in the table.

  For example, if your table has three input fields, you can use up to two fields for grouping. If your table has two input fields, you can use one of the fields for grouping. If your table has only one input field, you can’t group the table’s rows.

• If the field that you used for grouping has empty cells, the rows with the empty cells are consolidated into a separate group. When you provide an input value, the group that corresponds to the input value is looked up. When you don’t provide an input value for the grouping field, only the group with the rows where the grouping field cells are empty is looked up.

  This lookup behavior is different from the lookup behavior for tables without row grouping, where rows with both the input value and any empty cells in the grouping field are looked up.

Example A decision table with these columns and rows is grouped by a single input field:

INPUT			OUTPUT
Serial Number	Product Name	Status	Product CODE
1	P1	Active	P101
2	P2	Inactive	P202
3	P2	Active	P200
4	P1	Inactive	P108
5	P1	Active	P105
8	P1	Active	P202
9	P2	Inactive	P101
11		Active	P303
12		Inactive	P300

The table is grouped by the Product Name field and the rows are split into these smaller groups.

This group corresponds to the value P1 for the Product Name field.

INPUT			OUTPUT
Serial Number	Product Name	Status	Product CODE
1	P1	Active	P101
4	P1	Inactive	P108
5	P1	Active	P101
8	P1	Active	P101

This group corresponds to the value P2 for the Product Name field.

INPUT			OUTPUT
Serial Number	Product Name	Status	Product CODE
2	P2	Active	P202
3	P2	Inactive	P200
9	P2	Inactive	P101

This group is specific to the cells in the Product Name field being empty.

INPUT			OUTPUT
Serial Number	Product Name	Status	Product CODE
11		Active	P303
12		Inactive	P300

When P1 is passed as the input value to the table, the rows in the table that’s grouped by Product Name field value P1 are looked up.

Example A decision table with these columns and rows is grouped by two input fields:

INPUT			OUTPUT
Serial Number	Product	Fabric	Product CODE
1	Shirt	Cotton	P101
2	Dress	Silk	P202
3	Dress	Cotton	P200
4	Shirt	Linen	P108
5	Shirt	Cotton	P105
8	Shirt	Cotton	P202
9	Dress	Silk	P101
11	Jacket		P303
12	Jacket		P300

The table is grouped by the Product and Fabric fields. The rows are split into these smaller groups based on these unique combinations of values in the Product and Fabric fields:

• Shirt, Cotton
• Shirt, Linen
• Dress, Silk
• Dress, Cotton
• Jacket, <no value>

This group corresponds to the values Shirt and Cotton for the Product and Fabric fields.

INPUT			OUTPUT
Serial Number	Product	Fabric	Product CODE
1	Shirt	Cotton	P101
5	Shirt	Cotton	P105
8	Shirt	Cotton	P202

This group corresponds to the values Shirt and Linen for the Product and Fabric fields respectively.

INPUT			OUTPUT
Serial Number	Product	Fabric	Product CODE
4	Shirt	Linen	P108

This group corresponds to the values Dress and Silk for the Product and Fabric fields respectively.

INPUT			OUTPUT
Serial Number	Product	Fabric	Product CODE
2	Dress	Silk	P202
9	Dress	Silk	P101

This group corresponds to the values Dress and Cotton for the Product and Fabric fields respectively.

INPUT			OUTPUT
Serial Number	Product	Fabric	Product CODE
3	Dress	Cotton	P200

This group corresponds to the value Jacket and empty cells for the Product and Fabric fields respectively.

INPUT			OUTPUT
Serial Number	Product	Fabric	Product CODE
11	Jacket		P303
12	Jacket		P300

When the values Shirt and Cotton are provided as input for the lookup table, only the group where the Product and Fabric field values are Shirt and Cotton is looked up.