In this Article, we will see how we can optimize and allow Json data to accept and transform duplicate elements. In real-time projects optimizing data really matters when we talk about tuning performance. Either you say in terms of logging data or in terms of processing data every byte matters.
In DataWeave, we have two properties which will hep us to optimize our application data.
- duplicateKeyAsArray: JSON data does not allow duplicate keys within same parent, so we may get exception in real-time project development scenario. With this attribute, if your dataweave finds any duplicate keys, it will create an array with all those values.
Sample XML Input:
<users>
<user>
<personal_information>
<first_name version=”V1″>Manish</first_name>
<first_name version=”V1″>Mak</first_name>
<middle_name>Kumar</middle_name>
<last_name>Sah</last_name>
</personal_information>
</user>
</users>
Dataweave Script:
%dw 2.0
output application/json duplicateKeyAsArray=true
—
payload
Sample Output:
{
“users”: {
“user”: {
“personal_information”: {
“first_name”: [
“Manish”,
“MaK”
],
“middle_name”: “Kumar”,
“last_name”: “Sah”
}
}
}
}
- indent: It indicates whether you want to compress your JSON data into a single line or you need JSON data for better readability.
Sample Input:
<users>
<user>
<personal_information>
<first_name version=”V1″>Manish</first_name>
<first_name version=”V1″>Mak</first_name>
<middle_name>Kumar</middle_name>
<last_name>Sah</last_name>
</personal_information>
</user>
</users>
<users>
<user>
<personal_information>
<first_name version=”V1″>Manish</first_name>
<first_name version=”V1″>Mak</first_name>
<middle_name>Kumar</middle_name>
<last_name>Sah</last_name>
</personal_information>
</user>
</users>
Dataweave Script:
%dw 2.0
output application/json duplicateKeyAsArray=true, indent=false
—
payload
Sample Output:
{“users”: {“user”: {“personal_information”: {“first_name”: [“Manish”,”MaK”],”middle_name”: “Kumar”,”last_name”: “Sah”}}}}
Happy Learning 🙂
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