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INPUT file 'A' contains:
1
2
3
4
5
6
7
8
9
10
input file 'B' contains:
6
7
8
9
10
11
12
13
14
15
Output file 'X' contains:
1
2
3
4
5
Output file 'Y' contains:
6
7
8
9
10
Output file 'Z' contains:
11
12
13
14
15
How can we implement this in a single ds job?
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Answer Posted / subbuchamala
1)
We can solve this by using Change capture stage. First,we use source as 'A' and refrerence as 'B' both of them are connected to Change capture stage. From, change capture stage it connected to filter stage and then targets X,Y and Z.
(Change Code '0'--->exist in both, copy record
Change Code '1'--->Exists in SRC 'A', INSERT record
Change Code '2'--->Exists in SRC 'B', DELETE record
Change Code '3'--->Exists in 'A' & 'B' with changes, UPDATE record)
In the filter stage:
Change_code column=1 it goes to 'X' [1,2,3,4,5]
Change_code column=0 it goes to 'Y' [6,7,8,9,10]
Change_code column=2 it goes to 'Z' [11,12,13,14,15]
2)
Add an extra column 'colA' and 'colB' to the files 'A' and 'B' respectively. Let the value for colsA be 'a' for all the rows in file 'A' and the value for colB be 'b' in file 'B'(using the column generator stage).Now join both the files using join stage using 'ID' column. Perform full outer join. Map the ID col, colA and colB to output. Next pass it through a transformer.
Transformer constraint:
1) file X - colA=a and colB<>b ----->[1,2,3,4,5]
2) file Y - colA=a and colB=b------->[6,7,8,9,10]
3) file Z - colA<>a and colB=b------>[11,12,13,14,15]
| Is This Answer Correct ? | 5 Yes | 3 No |
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