Before You Get Started

Before you begin mapping data, make sure you have completed the following actions:

1. Review the Navigating the Mappings Canvas article to learn about all the features of the Mappings page and the Using the Semantic Layer in Mappings to learn how to use the Semantic Layer in Reactor's Mappings interface to transform source data to destination schemas
2. Connect all data sources needed for your mapping exercise (for more details, see: Connect to a Data Source)

3. Standardize data for your connected data sources (for more details, see: Standardize Your Source Data)

4. (Optional) If multiple data sources need to be linked so that you can join data between the sources, configure source links (for more details, see: Source Links)

5. Create Mapping Configurations for your source data (for more details, see: Mapping Data in the Mappings Canvas

How to Create an Output Configuration

To create a new output configuration:

1. Select the ➕ Add icon at the top Mapping Canvas, then select Output.

2. On the first page of the Add Output wizard: 
   • Select the destination to which you want to output data from the "Select a destination" menu (see <<link forthcoming>> for more information on adding destinations).
   • Select the target of the destination to which you want to output data from the "Select a target" menu (see Connect Reactor To Your Data Destination (Target) for more information on adding destination targets).
   • Select Next to continue to the next step
3. On the second page of the Add Output wizard:
   • Select the model that should output to the destination table you selected in the previous step, then select Next
   • Enter an alias, or display name, to use for your output. This alias will be displayed on the output's tile in the mapping canvas.
   • Select Submit to complete the wizard and load your output.

After selecting Submit, the configuration for the Output will appear on the screen, where you can make any changes to the output's configuration, then deploy your changes. Once you have updated your output configuration, select the Deploy button at the top-right of the output configuration window to deploy your output.

For more information on configuring your output, see the selections below: 

1. How to Configure an Output Iterator 
2. How to Configure an Inclusion Filter

How to Edit an Existing Output

To edit any configuration on the graph, click the configuration’s box on the mapping canvas. Alternatively, select the Search box at the top-right of the mapping graph to search for a specific configuration. When you select a result from the search, the Mapping Graph will center on that configuration.

How to Configure an Output Iterator

An output iterator is used to specify when a record consisting of an array of objects should be enumerated, such that one object in the array becomes a single output record. For instance, Shopify Product records contain a product family of variants varying by size and color. Below is a mapping configuration of Shopify product data. Note that in the Results box, two variations are captured in the product array, which is comprised of the same attributes as the product landing table in the pre-configured Reactor Reference Data Model or your data warehouse common data model:

To output one row per variant, it is necessary to define an iterator expression for the product data output. In the example above, the iterator expression would be product. With this iterator defined, Reactor will output each object in the product array to one database row instead of outputting the entire product array to one database row.

Select the Settings ⚙️ icon at the top of the output configuration screen to configure an output iterator. The Output settings window will appear in a pop-up menu. Enter the name of the array in your mapping configuration that should be iterated on to form new records in the Iterator Expression box, then select the Save button at the bottom-right of the popup to apply your changes.

After the pop-up closes, the Output table will refresh with your iterator expression applied. Use the arrow toggles (< and >) above the table to review each output object for your source record.

Once you are done configuring your iterator expression, select the Deploy button at the top-right of the output configuration screen to deploy your changes.

How to Configure an Inclusion Filter

An inclusion filter is an optional setting in output configurations that defines which transformed source records should be output to your data destination. This is useful when a data source contains records not germane to your data use cases.

Select the Settings ⚙️ icon at the top of the output configuration screen to configure an inclusion filter in the output configuration. The Output settings window will appear in a pop-up menu. In the Inclusion Filter Expression box, enter an expression to use as the filter's logic.

Inclusion filter expressions use the same syntax and functions as mapping expressions (ℹ️ See Writing Mapping Expressions for more information on mapping expressions and a glossary of mapping functions). As with mapping expressions, multiple functions can be nested to create complex inclusion filter expressions. The expression should resolve to either true or false when applied to a transformed source data record:

• If the expression resolves to true when applied to a record, the record will be exported to the destination.
• If the expression resolves to false when applied to a record, the record will not be exported to the destination.

Below the inclusion filter editor is a text box where users can enter a source record and validate whether the record will be included or excluded by the filter. Select the source in the dropdown next to the text box, enter the source ID you wish to evaluate, then select the Validate button. Reactor will evaluate the inclusion filter expression against the record and display whether the record will be included or excluded by the filter. The number of record outputs will also be displayed if the output contains an iterator expression.

In the example below, a filter is written to include records with an adspend_date of April 15, 2024, or later. The expression is: adspend_date >= "2024-04-15".

Deploy Your Changes

Select the Deploy button at the top-right of the output configuration window to deploy changes to an output configuration. 

What is Next?

After you have deployed your output, data from the sources connected to that output will begin being transformed according to the mapping configurations in the data pipeline and output to the designated data destination. You can monitor data flow directly in your connected destination.

If you make updates to an output configuration and need to retransform your collected data, you can execute a replay of the data by selecting the 🔃 icon on a data source in the Mapping UI. For more information on retransforming data, see Retransforming Data and Mapper Replay.