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seband_fredes
Contributor II
Contributor II

How I create a pipeline?

Hi everyone, I need your helpyou in this case. I need to create a pipeline with the contract services that actually I've. I've a dataset with this:

ID_ContractCstmrCodeCstmrNameClusterCreateDateEndDate$$$
200891A101-09-201731-08-2020$352.000
211222B201-09-201701-09-2020$166.666
235373C419-04-201831-03-2021$352.000

 

In the first row, I've a contract service, it's started in 1/9/2017 (dd/mm/yyyy) and finish at 31-08-2020. All the contracts are monthly invoiced.

 

I need create a table with this characteristics:

IDCstmrCodeCstmrNameClusterCreateDateEndDateFlowDate$$$
200891A101-09-201731-08-202001-09-2017$352.000
200891A101-09-201731-08-202001-10-2017$352.000
200891A101-09-201731-08-202001-11-2017$352.000
200891A101-09-201731-08-202001-07-2020$352.000
200891A101-09-201731-08-202001-08-2020$352.000

 

Thanks for all.

Blessings.

1 Solution

Accepted Solutions
Kushal_Chawda

try below

Data:
LOAD ID_Contract, 
     CstmrCode, 
     CstmrName, 
     Cluster, 
     CreateDate, 
     monthstart(CreateDate,IterNo()-1) as Flow_Date,
     EndDate, 
     $$$
FROM Table
while monthstart(CreateDate,IterNo()-1)<= EndDate;

View solution in original post

2 Replies
Kushal_Chawda

try below

Data:
LOAD ID_Contract, 
     CstmrCode, 
     CstmrName, 
     Cluster, 
     CreateDate, 
     monthstart(CreateDate,IterNo()-1) as Flow_Date,
     EndDate, 
     $$$
FROM Table
while monthstart(CreateDate,IterNo()-1)<= EndDate;
seband_fredes
Contributor II
Contributor II
Author

Thaks so much, it was very usefull your solution. How would it be done so that the flow-date is quarterly or semi-annual?

 

Quarterly example:

-This is the exam contract=

D_ContractCstmrCodeCstmrNameClusterCreateDateEndDate$$$
200891A101-08-202031-07-2021$352.000

 

-This is my goal's example=

IDCstmrCodeCstmrNameClusterCreateDateEndDateFlowDate$$$
200891A101-08-202031-07-202101-08-2020$352.000
200891A101-08-202031-07-202101-12-2020$352.000
200891A101-08-202031-07-202101-04-2021$352.000