Grouping of Source Data based on Common Values

[former_member192105]

Hello,

I have a File to File scenario and have a mapping requirement between below shown Source and Target structures:

The Employee IDs in the source structure should be grouped together as per their Departments in the Target structure.

Any idea on how this can be achieved in message mapping?

Thank you!

[manoj_khavatkopp · Accepted solution]

Try the below :

Mapping:

Output:

UDF -AddArray: ( All values of a context)

String out= String.join(",", var1); 
result.addValue(out);

Br,

Manoj

[former_member192105 · Accepted solution]

Dear Manoj,

The mapping logic is working perfectly as expected.

Thank you!

[hasan_celebi]

Hi Abhishek;

You can use this mapping.

Item

Emp_ID

Department

concatContextValues UDF

if (delimiterString == null || delimiterString.length == 0) {

throw new IllegalStateException("concatContextValues: "

+ "there is no delimiterString");

}

if (contextValues != null && contextValues.length > 0) {

String delimiter = delimiterString[0];

StringBuffer sb = new StringBuffer(contextValues[0]);

for (int i = 1; i < contextValues.length; i++) {

sb.append(delimiter).append(contextValues[i]);

}

result.addValue(sb.toString());

}

Test Result

Regards
Hasan

[former_member192105]

Dear Hasan,

Thank you for your response!

[apu_das2]

Use multiple mapping.

1) In the first MM - use format by example so that you can get data like below -

<Item>

<Emp_ID> 1111 </Emp_ID>

<Emp_ID> 2222 </Emp_ID>

<Department> Sales </Department>

</Item>

<Item>

<Emp_ID> 4444 </Emp_ID>

<Emp_ID> 6666</Emp_ID>

<Emp_ID> 9999</Emp_ID>

<Department> Accounting</Department>

</Item>

2) In the second MM, Write a simple UDF to concat EMP_ID values separated by coma and put into the final structure.

Thanks,

Apu

[former_member192105]

Dear Apu,

Thank you for your response!