DW Complex Operators: DataWeave 2.0 Transformations
This article is about writing complex DataWeave codes using (some, every, countBy, sumBy) operators after importing DW core libraries.
Hi Muleys,
This article is about writing complex DataWeave codes using (some, every, countBy, sumBy) operators after importing DW core libraries.
We all know how to write DataWeave coding but to use some complex operators like (some, every, countBy, sumBy, and more), we need to import DW libraries.
Example:
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import * from dw::core::Arrays
Let's begin with operators:
1. some:
It is Boolean, returns either true or false.
Example:
DataWeave Code:
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%dw 2.0
import * from dw::core::Arrays
output application/json
var a = [{name: "Max", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft"},{name: "Mule", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft"}]
---
{
"Name": a.name some($ contains "M"),
"Company": a.company some($ matches "XYZ")
}
Expression Output:
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{
"Name": true,
"Company": false
}
2. every:
It is Boolean, return true only if every element matches the condition else false.
Example:
DataWeave Code:
xxxxxxxxxx
%dw 2.0
import * from dw::core::Arrays
output application/json
var a = [{name: "Max", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft"},{name: "Mule", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft"}]
---
{
"Name": a.name every($ contains "S"),
"Company": a.company every($ contains "M")
}
Expression Output:
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{
"Name": false,
"Company": true
}
3. countBy:
It returns the count of the elements as per the condition is applied.
Example:
DataWeave Code:
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%dw 2.0
import * from dw::core::Arrays
output application/json
var a = [{name: "Max", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft", allowance: 2000},{name: "Mule", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft",allowance: 4000}]
---
{
"Name": a.name countBy($ contains "M"),
"Company": a.company countBy($ contains "F"),
"Count": a.allowance countBy($>1000),
}
Expression Output:
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{
"Name": 2,
"Company": 0,
"Count": 2
}
4. sumBy:
It returns the sum of total elements if the applied condition matches.
Example:
DataWeave Code:
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%dw 2.0
import * from dw::core::Arrays
output application/json
var a = [{name: "Max", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft", allowance: 2000},{name: "Mule", email: "[email protected]", phone: "91 0808907890", company: "MuleSoft",allowance: 4000}]
---
{
"Name": a.name sumBy(if($ contains "M") 1 else 0),
"Company": a.company sumBy(if($ contains "Z") 1 else 0),
"Sum": a.allowance sumBy(if($>1000) $ else 0),
}
Expression Output:
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{
"Name": 2,
"Company": 0,
"Sum": 6000
}
Conclusion
Using the above Operators and DW Libraries in DataWeave/Transform Message component, we can transform our data as per our complex requirements.
Happy Learning!!
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