Jolt grouping together

Question

I have this input in JSON, I am having difficulty grouping things together:

[   
    {
        \"PK\": \"123\",
        \"SURNAME\": \"CHEN\",
        \"SEX\": \         


        

Answer 1

This is pretty much as close as OOTB Jolt can get. Note Jolt is for changing the structure of your data, not doing custom data mappings of things like "PHONE_TYPE": "04" means "Fax".

Transformed Output

{
  "Customers" : [ {
    "MatchingProfile" : {
      "DBKey" : "123",
      "Gender" : "F",
      "LastName" : "CHEN",
      "Birthdate" : "1962-08-29 00:00:00.0",
      "Contacts" : [ {
        "ContactType" : "05",
        "Phone_Number" : "12312312",
        "Status" : "INSERT"
      }, {
        "ContactType" : "04",
        "Phone_Number" : "78787878",
        "Status" : "UPDATE"
      } ]
    }
  }, {
    "MatchingProfile" : {
      "DBKey" : "456",
      "Gender" : "M",
      "LastName" : "DEV",
      "Birthdate" : "1953-06-06 00:00:00.0",
      "Contacts" : [ {
        "ContactType" : "05",
        "Phone_Number" : "34343434",
        "Status" : "INSERT"
      }, {
        "ContactType" : "02",
        "Phone_Number" : "56565656",
        "Status" : "DELETE"
      } ]
    }
  } ]
}

Jolt Spec

[
  // first pivot by the value of SURNAME
  {
    "operation": "shift",
    "spec": {
      "*": { // for each item in the array
        "SURNAME": { // match SURNAME
          "*": { // match any value of SURNAME
            "@2": "&[]" // copy the whole record from 2 levels up to the SURNAME as an array, so we know that in the next step it is always an array
          }
        }
      }
    }
  },
  {
    "operation": "shift",
    "spec": {
      "*": { // match CHEN or DEV
        "0": {
          // only pull pk, sex, dob from the first entry of the SURNAME array so as to not duplicate output
          "PK": "Customers[#3].MatchingProfile.DBKey",
          "SEX": "Customers[#3].MatchingProfile.Gender",
          "SURNAME": "Customers[#3].MatchingProfile.LastName",
          "DATE_OF_BIRTH": "Customers[#3].MatchingProfile.Birthdate",

          // this does mean that the PHONE_TYPE has to be dealt with twice
          // once for the zeroth item, and then once again for the rest
          "PHONE_TYPE": "Customers[#3].MatchingProfile.Contacts[0].ContactType",
          "PHONE_NO": "Customers[#3].MatchingProfile.Contacts[0].Phone_Number",
          "OPERATION": "Customers[#3].MatchingProfile.Contacts[0].Status"
        },
        "*": {
          // handle PHONE_TYPE and friends for the other records
          "PHONE_TYPE": "Customers[#3].MatchingProfile.Contacts[&1].ContactType",
          "PHONE_NO": "Customers[#3].MatchingProfile.Contacts[&1].Phone_Number",
          "OPERATION": "Customers[#3].MatchingProfile.Contacts[&1].Status"
        }
      }
    }
  }
]

If if you find Jolt valuable for the pivot and the structure change, then your best bet is to "fixup" your input data array, aka map "PHONE_TYPE": "04" to "Fax", trim the 00:00:00 from the birthday, and then use Jolt to make the nested "Customers[].MatchingProfile.Contacts[]" structure.