Mapper

Overview

You can use this Snap to map input fields to output fields using JavaScript expressions or expressions created using the Expression Builder. It transforms incoming data using the given mappings and produces new output data.

This is a Transform-type Snap.
Works in Ultra Tasks

Snap views


Type	Description	Examples of upstream and downstream Snaps
Input	This Snap supports exactly one document input view.	JSON Parser CSV Parser
Output	This Snap supports exactly one document output view. Outputs the mapped documents as defined by the user-configured expressions.	Type Converter Join
Learn more about Error handling.

Snap settings

Note: Learn about the common controls in the Snap settings dialog.


Field/Field set	Description
Label* `String`	Specify a unique name for the Snap. Modify this to be more appropriate, especially if more than one of the same Snaps is in the pipeline. Default value: Mapper Snap Example: Transform key records
Null-safe access `Checkbox`	Select this checkbox to treat missing source paths as `null` instead of failing the document. For example, if you access `$a` but the `a` key does not exist in the input data, the Snap assumes its value is `null` and continues. Default value: Deselected
Omit mapping if missing `Checkbox`	Appears when you deselect Null-safe access. Select this checkbox to omit the entire mapping from the Mapping table when an expression references a field that is missing from the input data, instead of failing the document. If Pass through is selected, the original target path is preserved. Attention: When you select this checkbox, we recommend you to choose the preview type as JSON instead of Table, because the Table preview will contain the omitted field label which can be misleading. The JSON preview skips the omitted fields as expected. Default value: Deselected
Pass through `Checkbox`	Select this checkbox so the Snap passes all the original input data into the output document with the data transformation results. If you deselect this checkbox, only the data transformation results in the mapping section appear in the output document and the input data is discarded. Note: This setting is impacted by Mapping Root. If Mapping Root is set to `$` and Pass through is deselected, anything not mapped in the table does not pass through. However, if Mapping Root is set to `$customer` and Pass through is deselected, it only applies to the items in the Mapping Root level. That means that anything above the Mapping Root level passes through and items at the Mapping level that are not mapped in the table do not pass through. Remember: Always select Pass through if you plan to leave the Target path field blank. Otherwise, an error displays to indicate that the field you want to delete does not exist. This is the expected behavior. For example, if you have an input file that contains a number of attributes and you need only two of these downstream. To accomplish that: Connect a Mapper Snap to the downstream Snap. List the two attributes you need in the Expression fields. Leave the Target path field blank. Select Pass through. When you execute the pipeline, this Snap evaluates the input document/binary data, extracts the two attributes that you want, and passes the entire document/binary data through to the Target schema. From the list of available attributes in the Target Schema, the Mapper Snap picks up the two attributes you listed in the Expression fields, and passes them as output. However, if you do not select the Pass through checkbox, the Target Schema would be empty, and the Snap displays the `No schema available` error. Default value: Deselected
Transformations*	Use this field set to configure the settings for data transformations.
Mapping Root `String/Suggestion`	Specify the subsection of the input data to map. Learn more: Understand the Mapping Root. Default value: $ Example: $
Input Schema `Dropdown list`	Select the input data (from the upstream Snap) that you want to transform. You can either Select All or Deselect All items from the input schema. Drag the item you want to map and place it under the Mapping table.
Sorted `Checkbox`	Select this checkbox to sort the input schema and the target schema. The sort options are: All: Sorts both mapped and unmapped data. Mapped: Sorts only the mapped data. Unmapped: Sorts only the unmapped data.
Mapping table	Use this field set to specify the mapping expressions and target paths used to map schema structure. The mapping table enables you to: Determine which fields in a schema are mapped or unmapped. Create and manage a large mapping table through drag-and-drop. Search for specific fields. You can also use SnapGPT icon to construct expressions by using natural language. For example, when you specify, "convert the value of `$input.name` to uppercase", SnapGPT generates this expression: `$name → $input.name.toUpperCase()` Learn more about: Mapping Table.
Expression `String/Expression`	Specify the function to use to transform the data. For example, combine, concatenate, or flatten. Expressions that are evaluated replace the source targets at the end of the pipeline runtime. Note: The data from previous undefined Snaps in the Mapping Table pass through the Data Snap to the next Snap. However, when you define output fields in the Target Path, and if the field name is the same as a field name that would otherwise pass through, the field in the mapping table overrides the output. Learn more: Understanding Expressions in SnapLogic and Using Expressions for usage guidelines. Managing Numeric Inputs in Mapper Expressions When you work with upstream numeric data, you might see some unexpected behavior. For example, consider a mapping that reads as follows: Expression: `$num +100` Target path: `$numnew` Now, the value passes from upstream for $num is 20.05. You expect the value of `$numnew` to now be 120.05. However, when you execute the Snap, the value of `$numnew` is shown as 20.05100. This happens because, as of now, the Mapper Snap reads all incoming data as strings, unless they are specifically listed as integers (INT) or decimals (FLOAT). So, to ensure that the upstream numeric data is appropriately interpreted, parse the data as a float to convert the numeric data into a decimal, and all calculations on the upstream data in the Mapper Snap work as expected: Expression: `pareFloat($num1)+100` Target path: `$numnew` The value of `$numnew` shows 120.05. Default value: $ Example: $
Target path `String/Suggestion`	Specify the target JSON path where the value from the evaluated expression is written. For example, after evaluation of the `$person.firstname` expression, the Snap inserts the `firstname` for the `person` object. Remember: The expression in the Target path field works only when Pass through is enabled. The Target Path field in the Mapper Snap supports expression-based values, allowing you to compute paths at runtime based on input data. Refer to the example for better understanding. Note: Target path recommendation: SnapLogic can suggest standardized target paths based on your Environment's historical mappings. It simplifies configuring the Target path property in the Snap with suggestions for the Expression and Target path fields mapping. To populate these suggestions, SnapLogic analyzes Expression and Target path mappings in other pipelines in your Environment and suggests the exact matches for the Expressions in your current pipeline. Click the Suggestions icon on the Target Path field to get intelligent suggestions. For example, if your expression resolves to `$Emp.Emp_Personal.FirstName`, SnapLogic may suggest `$FirstName` as a cleaner, standardized target path. It helps maintain consistent naming conventions across pipelines in your organization. The following gif shows how SnapLogic recommends the Target path in the Mapper Snap:
Snap execution `Dropdown list`	Choose one of the three modes in which the Snap executes. Available options are: `Validate & Execute`: Performs limited execution of the Snap and generates a data preview during pipeline validation. Subsequently, performs full execution of the Snap (unlimited records) during pipeline runtime. `Execute only`: Performs full execution of the Snap during pipeline execution without generating preview data. `Disabled`: Disables the Snap and all Snaps that are downstream from it. Default value: Validate & Execute Example: Execute only