The custom number transform function is used to map a given number to a target field.
If you've added/updated a map shape before, you'll be used to selecting a source field and a target field. However, when a custom number transformation is used we don't select a source field - the custom number transformation is our data source.
Step 1 In your process flow, access settings for your map shape:
Step 2 Select the add transform button for the required mapping rule - for example:
Step 3 Click the add transform button:
Step 4 Click in the name field to access a list of all available transform functions, then select custom number:
Step 5 Move down to the custom number field and enter your required number - for example:
Step 6 Accept your changes:
...then save the transformation:
Step 7 Now you can select a target field in the usual way - for example:
...then:
...then:
Step 8 Once your mapping is complete, the row should be displayed without a source field - for example:
From here you can save changes or add more mapping rules as needed. Next time the process flow runs, the custom number will be mapped to the given target field.
The round number transform function is used to change the number of decimal places for a number value. For example:
...might be changed to:
With the round number transform you can specify the number of decimal places that should be applied to incoming numeric values.
Step 1 In your process flow, access settings for your map shape:
Step 2 Select the add transform button for the required mapping rule - for example:
Step 3 Click the add transform button:
Step 4 Click in the name field to access a list of all available transform functions, then select round number from the number category:
Step 5 Move to the decimal places field and enter the required number of decimal places required for transformed values - for example:
Step 6 Click the add field button:
Step 7 Click in source fields and select the source field to be used for this transform:
Step 8 Accept your changes (twice).
Step 9 Save the transform. You'll notice that the transform icon is updated to indicate that a transform function is present for the mapping row - for example:
The math transform function is used to perform a mathematical operation for selected fields. For example, your incoming payload might include customer records, each with a series of numeric value
fields that need to be added together so the total can be pushed to a total
field in the target system.
The following mathematical operations are available:
Add
Subtract
Multiply
Divide
In the instructions below, we'll step through the scenario mentioned above where our incoming payload includes customer records, each with three value fields (value1
, value2
, value3
) that must be added together and pushed to a total
field in the target system.
The steps required are detailed in two stages:
To begin, we need to update/add the required mapping row so that it includes all source fields that need to be added together and then pushed to the target.
Step 1 In your process flow, access settings for your map shape:
Step 2
Find (or add) the mapping row which requires a math transformation. In the example below, we have a row that's currently set to map the source first name
field into the destination full name
field:
Step 3 On the source side of the mapping row, we need to include all the fields to be used in our mathematical operation. To do this, click the 'pencil' icon associated with the existing source field:
Step 4 Details for the selected field are shown - click the add source field button:
Step 5 Click the 'pencil' icon associated with the new source field:
Step 6 Move down and update the display name and payload fields for the second source field that you want to use - for example:
Step 7 Accept these changes to exit back to your mapping rows - notice that there are now two source fields associated with the row you updated:
Step 8 Repeat steps 3 to 7 to add any more source fields that you need to include in the mathematical operation.
With all required source fields defined for our mapping row, we can add a math transform function to define the required calculation based on these fields.
Step 1 Select the add transform button for the required mapping rule - for example:
Step 2 Click the add transform button:
Step 3 Click in the name field and select math from the number section in the list of transform functions:
...math options are displayed:
Step 4 Click in the operator field and select the type of calculation to be performed - you can choose from add, subtract, multiply and divide:
Step 5 Click the add field button:
Step 6 Click in source fields and select the first source field to be used in the calculation:
Step 7 Accept your changes.
Step 8 Click the add field button again:
...and add the next source field to be used - for example:
Step 9 Accept your changes.
Step 10 Repeat steps 8 and 9 to include any more source fields to be used in the calculation. Each time you accept a new source field you'll see the sequence that they will be processed when this transform function runs - for example:
Fields are processed in the sequence that they are added here.
Step 11 Having added all required source fields to be calculated, accept changes:
...then save the function:
Step 12 Ensure that the target field for this mapping row is set as required, then save the map shape. Next time the process flow runs, the mathematical operation will be performed for the given source fields and the total value is pushed to the defined target field. The example below shows an incoming payload before and after the math transformation is applied:
The cast to string transform function is used to change the data type associated with a source field from number
to string
. For example, you might have an id
field in a source system that's stored as string
value, but your destination system expects the id
to be a number
.
Step 1 In your process flow, access settings for your map shape:
Step 2 Select the add transform button for the required mapping rule - for example:
Step 3 Click the add transform button:
Step 4 Click in the name field to access a list of all available transform functions, then select cast to string from the number category:
Step 5 Click the add field button:
Step 6 Click in source fields and select the source field to be used for this transform:
Step 7 Accept your changes (twice).
Step 8 Save the transform. You'll notice that the transform icon is updated to indicate that a transform function is present for the mapping row - for example:
In our example, our source data is coming in via a manual payload so are defining the payload field manually - if you're using a to receive data, you'll be able to select the required field from the associated schema for your connection.
Step 9 Go to .
All source fields that were added for this mapping in will be available for selection here.