Flat file To JSON Conversion using Copybook Schema

1. Mule ESB – DataWeave - CopyBook
Flat file To JSON Conversion using Copybook Schema

2. Steps :
1) First configure the ‘HTTP’ connector as a source in Anypoint Studio Mule.
2) Drag & Drop the ‘Transform Message’ from the Mule palette window for
conversion.
3) In the Transform Message as input metadata provide copybook schema at the
same time as output metadata provide JSON Data. Because of Flatfile – JSON
conversion using copybook schema.
4) Drag & Drop ‘Byte Array to String’ Transformer from Mule Palette window for
converting result into string.

3. 5) Finally use the Logger for logging the result message.
Note:
Find the Sample Copybook & JSON Data in the next slides.

4. Sample Copybook :
000000 01 HospitalsCopyBook.
000100 02 Hospitals.
000200 03 Basic-Info.
000300 05 Name PIC X(4).
000400 05 Address PIC XXXX.
000500 05 Phone-Number PIC 9(10).
000600 05 Admin PIC XXXX.
000700* Ward Information
000800 02 Wards.
000900 03 Basic-Info.
001000 05 Name PIC XXXX.
001100 05 Address PIC X(4).
001200 05 Number PIC 9999999999.
001300 05 Admin PIC X(4).
001400* Patient Information
001500 02 Patients.
001600 03 Basic-Info.
001700 05 Name PIC XXXX.
001800 05 Address PIC X(4).
001900 05 Phone-Number PIC 9(10).
002000 05 Blood-Group PIC SX(3).

5. 002100* Symptom Information
002200 02 Symptoms.
002300 03 Basic-Info.
002400 05 Name PIC X(4).
002500 05 Address PIC XXXX.
002600 05 Phone-Number PIC 9(10).
002700 05 Admin PIC XXXX.
002800* Treatment Details
002900 02 Treatments.
003000 03 Basic-Info.
003100 05 Name PIC X(4).
003200 05 Type PIC XXXX.
003300 05 Code PIC 9(10).
003400 05 Amount PIC 999V9.
003500* Doctor Availabilty Info
003600 02 Doctors.
003700 03 Basic-Info.
003800 05 Name PIC X(4).
003900 05 Address PIC XXXX.
004000 05 Phone-Number PIC 9(10).
004100 05 Admin PIC XXXX.

6. 004200* Facilities Availabilty
004300 02 Facilities.
004400 03 Basic-Info.
004500 05 Name PIC X(4).
004600 05 Address PIC XXXX.
004700 05 Phone-Number PIC 9(10).
004800 05 Admin PIC X(4).

7. Sample JSON :
[
{
"HospitalsCopyBook": {
"Hospitals": {
"Basic-Info" :
{
"Name" : "AA",
"Address" : "HYD",
"Phone-Number" : 1111111111,
"Admin" : "ABCD"
}
},
"Wards": {
"Basic-Info":
{
"Name" : "BB",
"Address" : "BNG",
"Number" : 2222222222,
"Admin" : "XYZA"
}
},

8. "Patients": {
"Basic-Info":
{
"Name" : "CC",
"Address" : "TPT",
"Phone-Number" : 3333333333,
"Blood-Group" : "+ve"
}
},
"Symptoms": {
"Basic-Info":
{
"Name" : "DD",
"Address" : "KDP",
"Phone-Number" : 4444444444,
"Admin" : "PQRS"
}
},
"Treatments": {
"Basic-Info":
{
"Name" : "EE",
"Type" : "NML",
"Code" : 55555,
"Amount" : 123.4
}
},

9. "Doctors": {
"Basic-Info":
{
"Name" : "FF",
"Address" : "RJPT",
"Phone-Number" : 6666666666,
"Admin" : "MNOP"
}
},
"Facilities": {
"Basic-Info":
{
"Name" : "GG",
"Address" : "PNGL",
"Phone-Number" : 7777777777,
"Admin" : "KLMN"
}
}
}
}
]
Note: Map field by field in dataweave

10. Mule Flow :

11. Sample Flatfile Data :
AAAABNGL1234567890AAAABBBBHYDB1234567890BBBBCCCCRJPT1234567890+veD
DDDTPTT1234567890DDDDEEEENMLR123456789012304FFFFPNG1234567890FFFFG
GGGKLMN1234567890GGGG

12. Thank Q