Introduction

The contains one of many transform function is used to match string values against a (comma delimited) list that you want to include.

For details, please see: Using contains one of many or does not contain one of many for string filters.

Introduction

The concatenate transform function is used to join the values for two or more source fields (using a given joining character) and then map the output of this transformation to a destination field.

For example, you might have a source system that captures the first name and last name for customer records, and then a destination system that expects this information in a single name field.

Adding a concatenate transform

In the instructions below, we'll step through the scenario mentioned above where our incoming payload includes the first name and last name for customer records, but our destination system expects this information in a single full_name field. The steps required are detailed in two stages:

• Stage 1: Add all required source fields to the mapping row

• Stage 2: Add a concatenate transform function

Stage 1: Add all required source fields to the mapping row

To begin, we need to update/add the required mapping row so that it includes all source fields that need to be joined and then pushed to the specified destination.

Step 1 In your process flow, access settings for your map shape:

Step 2 Find (or add) the mapping row which requires a concatenate 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 add all the fields that need to be joined. 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 join - 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 join.

Step 9 Go to stage 2.

Stage 2: Add a concatenate transform function

With all required source fields defined for our mapping row, we can add a concatenate transform function to join the values for 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 concatenate from the string section in the list of transform functions:

...concatenate options are displayed:

Step 4 In the join character field, enter the character that you want to join each of your source fields - for example, a hyphen or a space:

Step 5 Click the add field button:

Step 6 Click in source fields and select the first source field to be joined:

Step 7 Accept your changes.

Step 8 Click the add field button again:

...and add the next source field to be joined - for example:

Step 9 Accept your changes.

Step 10 Repeat steps 8 and 9 to add any more source fields to be joined. 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:

Step 11 Having added all required source fields to be joined, 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 given source fields for this mapping row will be joined and then that value is pushed to the target. The example below shows an incoming payload before and after the concatenate transformation is applied:

Introduction

The first word transform function is used to extract the first word of an incoming string value, based on a user-defined delimiter. For example, you might have product data in a string:

{"first_fruit":"apples,oranges,pears,grapes"}

...and need to extract just the last item in the string for pushing to the destination system:

{"first_fruit":"apples"}

In this case, items in our source string value are delimited with a comma, so we can use this to determine the first word. The transform checks incoming string values and determines the 'first word' to be the word after the first occurrence of the given delimiter.

Adding a first word transform

Step 1 In your process flow, access settings for your map shape:

Step 2 Select the add transform icon 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 first word from the string category:

Step 5 In the delimiter field, enter the character that delimits elements in the string:

If you use any of the following characters, they should be escaped: . + * ? ^ $ ( ) [ ] { } | \ /

For example, a delimiter of * would be entered as:

\*

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:

Introduction

The cast to float transform function is used to change the data type associated with a source field from string to float.

Adding a cast to float transform

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 float from the string 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:

Introduction

The cast to number transform function is used to change the data type associated with a source field from string to number. For example, you might have an id field in a source system that's stored as number value, but your destination system expects the id to be a string.

Adding a cast to number transform

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 number from the string 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:

Introduction

The custom string transform function is used to map a given string to a target field. This string can be static, or you can reference flow variables and cached data.

Adding a custom string transform

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 string:

Step 5 Move down to the custom string field and enter your required text or variables - 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 string (or associated values from variables) will be mapped to the given target field.

Introduction

The does not contain one of many transform function is used to match string values against a (comma delimited) list of values that you want to exclude.

For details, please see: .

Transforms in this section

Introduction

The last word transform function is used to extract the last word of an incoming string value, based on a user-defined delimiter. For example, you might have product data in a string:

...and need to extract just the last item in the string for pushing to the destination system:

In this case, items in our source string value are delimited with a comma, so we can use this to determine the last word. The transform checks incoming string values and determines the 'last word' to be the word after the last occurrence of the given delimiter.

Adding a last word transform

Step 1 In your process flow, access settings for your map shape:

Step 2 Select the add transform icon 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 last word from the string category:

Step 5 In the delimiter field, enter the character that delimits elements in the string:

If you use any of the following characters, they should be escaped: . + * ? ^ $ ( ) [ ] { } | \ /

For example, a delimiter of * would be entered as:

\*

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:

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:

Introduction

The split string transform function is used to split elements of a string into an array, with a user-defined delimiter. For example, you might have product data in a string:

...and need to convert these items to an array before pushing to the destination system:

In this case, items in our source string value are delimited with a comma, so we can use this to determine where each split occurs. The transform checks incoming string values and determines each array item to be the word after each comma.

Adding a split string transform

Step 1 In your process flow, access settings for your map shape:

Step 2 Select the add transform icon 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 split from the string category:

Step 5 In the delimiter field, enter the character that delimits elements in the string:

If you use any of the following characters, they should be escaped: . + * ? ^ $ ( ) [ ] { } | \ /

For example, a delimiter of * would be entered as:

\*

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:

Introduction

The pad transform function is used to pad an existing string of characters to a given length, using a given character. You can apply padding to the left (i.e. immediately before the existing string), to the right (i.e. immediately after the existing string), or both (immediately before and after, as equally as possible).

Example

The payload item below contains a string that's 8 characters long:

If we apply padding to a length of 20 using a * character to the right, the result would be:

Here, we have an extra 12 * characters to the right, giving a string length of 20. However, if we apply the * character to both, the result would be:

Now the padding is applied with 6 characters to the left of the original string and 6 characters to the right.

Adding a round date transform

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 pad from the string section:

Step 5 Click in the direction field and select where you would like padding to be applied:

You can apply padding to the left (i.e. immediately before the existing string), to the right (i.e. immediately after the existing string), or both (immediately before and after, as equally as possible).

Step 6 In the length field, specify the number of characters that you'd like the final (i.e. transformed) string to be - for example:

Step 7 In the pad character field, specify the character that you'd like to use for padding - for example:

Step 8 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.

Introduction

The JSON encode transform function is encode incoming values as JSON. For example, you might have product data in a string:

{"last_fruit":"apples"}

...and need to encode the values for pushing to the destination system:

{"last_fruit":"\"apples\""}

Adding a last word transform

Step 1 In your process flow, access settings for your map shape:

Step 2 Select the add transform icon 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 JSON encode from the string 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:

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:

Introduction

The replace transform function is used to replace an existing source string value with either:

• An alternative string value

• An empty value

Adding a replace transform

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 replace from the string category:

Step 5 Update search and replace fields with your required values:

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: