Expand JSON array processor

Anthony Pépin Updated by Anthony Pépin

The Expand JSON array processor transposes rows containing a JSON array into several rows with a new column containing each value of the array.

Configuring the processor

The parameter "iJSON rule to array" works exactly as it does in the "Extract from JSON" processor and should contain the array to transpose (represented with the iJSON rule .item).

  • If the field contains the JSON array directly, just put item as an iJSON rule.
  • If the final element is an array, the iJSON rule must end with .item, meaning that the reached object should be treated as an array of items in the iJSON syntax.
  • If you want to keep going into the items inside the array, you can keep adding key names after the .item, but be careful to check that this path is valid for every object in the array.

To set the parameters of the Expand JSON array processor, follow the indications from the table below.

Label

Description

Example

JSON array field

Name of the field that holds the JSON array

data

iJSON rule to array

iJSON rule to iterate in the JSON array above. An iJSON rule is built with the names of all the field from the JSON root to the data to extract, separated with a dot.

block.metaB

Output field

Name of the field that will contain the extracted element

 

Example

iJSON rules to extract from the following JSON array field:

[
{
"metaB" : "value1",
"int": 5,
"boolean": false
},
{
"metaB" : "value2",
"int": 6,
"boolean": true
},
]
  • item will transpose the record into two, one with each object of the array in the "Output field" column
{ "metaA": "Joe",
"bloc" : [
{
"metaB" : "value1",
"int": 5,
"boolean": false,
"sub" : { "sub_sub" : "sub_value"}
},
{
"metaB" : "value2",
"int": 6,
"boolean": true,
"sub" : { "sub_sub" : "other_sub_value"}
},
]
}
  • bloc.item will transpose the record into two, one with each object of the array in the "Output field" column
  • bloc.item.sub will transpose the record into two, one with each object inside the "sub" tag of each object of the array.
If you get an error using this processor, it may be because your source has the incorrect type. Verify that your JSON file has the correct data type. To do this, go to the Sources tab on your dataset:
1. Open the three-dot menu icon on the far right, and click View source
2. In the dropdown menu in the upper-right, make sure "JSON file" is selected

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