Hi @Velankanni ,

I got to say that this is one of the most complex jolt I have ever written. Im starting to question if its even worth doing it because it will make maintaining the the spec very hard. I would urge you to look at this post which has similar request of flattening complex json and there I recommended to use JSTL transformation spec instead as it would simplify things by a lot.

As far as the jolt spec , I was able to do it in 4 transformation:

1- Start form the leaf "labelingCluster" and work your way up to collect common data for each node and assign arrays for the values of metadata & parent identifiers.

2- traverse the metadata array from step 1 to replicate the values from above against each metadata array item.

3- traverse the parent identifier array from step 1 to replicate the values from step2 against each parent identifier array item.

4- Bucket result from step3 into single array

It important to maintain parent\sub array  index position during each transformation to help you group fields correctly.

[
  {
    "operation": "shift",
    "spec": {
      "data": {
        "getItemListing": {
          "edges": {
            "*": {
              "node": {
                "treatmentClusterIds": {
                  "*": {
                    "element": {
                      "labelingClusters": {
                        "*": {
                          "labelingCluster": {
                            "@(3,name)": "[&8].treatmentClusterIds[&5].labelingClusters[&2].Element",
                            "@(6,identifier)": "[&8].treatmentClusterIds[&5].labelingClusters[&2].identifier",
                            "@": "[&8].treatmentClusterIds[&5].labelingClusters[&2].labelingCluster",
                            "@(4,metadata)": {
                              "*": {
                                "treatmentClusterIDs": "[&10].treatmentClusterIds[&7].labelingClusters[&4].metadata[]"
                              }
                            },
                            "@(6,parentItems)": {
                              "*": {
                                "parentIdentifier": "[&10].treatmentClusterIds[&7].labelingClusters[&4].parentId[]"
                              }
                            }
                          }
                        }
                      }
                    }
                  }
                }
              }
            }
          }
        }
      }
    }
  },
  {
    "operation": "shift",
    "spec": {
      "*": {
        "treatmentClusterIds": {
          "*": {
            "labelingClusters": {
              "*": {
                "metadata": {
                  "*": {
                    "@(2,identifier)": "[&7].treatmentClusterIds[&5].labelingClusters[&3][&1].identifier",
                    "@": "[&7].treatmentClusterIds[&5].labelingClusters[&3][&1].TreatmentId",
                    "@(2,Element)": "[&7].treatmentClusterIds[&5].labelingClusters[&3][&1].Element",
                    "@(2,labelingCluster)": "[&7].treatmentClusterIds[&5].labelingClusters[&3][&1].labelingCluster",
                    "@(2,parentId)": "[&7].treatmentClusterIds[&5].labelingClusters[&3][&1].parentId"
                  }
                }
              }
            }
          }
        }
      }
    }
  }
  ,
  {
    "operation": "shift",
    "spec": {
      "*": {
        "treatmentClusterIds": {
          "*": {
            "labelingClusters": {
              "*": {
                "*": {
                  "parentId": {
                    "*": {
                      "@(2,identifier)": "[&8].treatmentClusterIds[&6].labelingClusters[&4][&3][&1].identifier",
                      "@": "[&8].treatmentClusterIds[&6].labelingClusters[&4][&3][&1].parentIdentifier",
                      "@(2,Element)": "[&8].treatmentClusterIds[&6].labelingClusters[&4][&3][&1].Element",
                      "@(2,TreatmentId)": "[&8].treatmentClusterIds[&6].labelingClusters[&4][&3][&1].TreatmentId",
                      "@(2,labelingCluster)": "[&8].treatmentClusterIds[&6].labelingClusters[&4][&3][&1].labelingCluster"
                    }
                  }
                }
              }
            }
          }
        }
      }
    }
  },
  {
    "operation": "shift",
    "spec": {
      "*": {
        "treatmentClusterIds": {
          "*": {
            "labelingClusters": {
              "*": {
                "*": {
                  "*": "[]"
                }
              }
            }
          }
        }
      }
    }
  }

]

Again, look into JSTL spec to simplify, or try to break up the json and store into database where you can easily perform sql queries to flatten the data using join

If this helps please accept the solution

Thanks