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Documents in a pipeline can be hierarchical, meaning which means an object can contain other contain other objects or arrays, which themselves can contain objects or arrays.  For exampleFor example, the following JSON document is hierarchical since because the root object contains object contains an object in the "child" field:

  {
    "name": "Acme",
    "child": { "field1": 1, "field2": 2 } }

Mapping simple hierarchical documents that only contain containing other objects objects is straightforward since because you can directly map one field to another. However, mapping  mapping for documents that contain arrays of objects is more  complicated because the objects in the array must be mapped separately from the parent the parent object. The mapping is separate because there is no unambiguous no unambiguous way to describe the array mapping using with the expression language and JSONPathsand JSONPaths. To map arrays, the Mapping Root property is included in the in the Mapper Snap. 

The Mapping Root property is a JSONPath that limits the scope of a mapping to the to the parts of the document that match the given specific path. For example, a the Mapping Root like  $.my_array[*] enables the Mapper to iterate over the objects in the array and transform each object based on the mapping. The other parts of the document that do not match the Mapping Root are passed  pass through untouched in the output. By default, the  The root is set to to $, which is the root of the document. Because array mappings must be done separately, add additional Mapper Snaps the document's root by default. 

To move variables inside $original to the root level, you must map the variables to root variables. For example, you must map $original.salary to $salary and $original.balance to $balance.

Because you must do array mappings separately, add an additional Mapper Snap for each array mapping. Chain additional Mapper additional Mapper Snaps together such that so the top levels of the hierarchy the hierarchy are mapped before descending down they descend to the lower levels. The reason for this ordering is that  This order is because the Mapper UI pares passes down the Input and Target schema views to only show the fields that are in the array's objects of the array.

The outer structures of the document need to must agree between the source the source and target; otherwise. Otherwise, the schema views are not useful. 

As a more complete example, we built The following example shows a pipeline that maps the following source document source document to a target document.:

Source document:

{
    "name": "Acme",
    "employee": [ { "first_name": "Bob", "last_name": "Smith", "age": 32 }, { "first_name": "Joe", "last_name": "Doe", "age": 44 } ] }
 

...

Target document:

  {
    "company_name": "Acme",
    "workers": [ { "name": "Bob Smith", "age": 32 }, { "name": "Joe Doe", "age": 44 } ] }

The source document is hierarchical because it contains an array of objects. You need You need two separate Mapper Snaps: one

1. to map the parent fields

...

2. to map the elements in the "employee" array. 

The first Mapper's configuration is simple is simple because it is just only changes names:  

The second Mapper is connected to the output of the first , mapper so that it works on the lower levels of the document hierarchy. The  You must change the "Mapping Root" for this Snap must be changed, so that the Snap so the mapping transformations impact only the objects in the "workers" array will be impacted by the mapping transformations. After setting the root, the Input schema changes to only show shows the fields in the array objects. If there is a a target schema is available, it is narrowed down to show the "name" and "age" fields.  

Mapping Root: $workers[*]