Java JOLT Examples..

1. REAL-WORLD JOLT PATTERNS

These patterns cover 95% of JSON transformation tasks.

---

Pattern 1 — Flattening deep JSON into simple key/value JSON

Input

{
  "user": {
    "profile": {
      "name": "Alice",
      "age": 30
    },
    "address": {
      "city": "Dhaka",
      "zip": "1000"
    }
  }
}

Spec

[
  {
    "operation": "shift",
    "spec": {
      "user": {
        "profile": {
          "name": "name",
          "age": "age"
        },
        "address": {
          "city": "city",
          "zip": "zip"
        }
      }
    }
  }
]

Output

{
  "name": "Alice",
  "age": 30,
  "city": "Dhaka",
  "zip": "1000"
}

---

Pattern 2 — Flatten unknown dynamic keys

Input

{
  "env": {
    "JAVA_HOME": "/opt/java",
    "PATH": "/bin:/usr/bin",
    "USER": "root"
  }
}

Spec

[
  {
    "operation": "shift",
    "spec": {
      "env": {
        "*": "&"       // & means “copy key name"
      }
    }
  }
]

Output

{
  "JAVA_HOME": "/opt/java",
  "PATH": "/bin:/usr/bin",
  "USER": "root"
}

---

Pattern 3 — Flatten Array of Objects → Map by ID

Very common in backend transformations.

Input

{
  "products": [
    { "id": 1, "name": "Pen", "price": 10 },
    { "id": 2, "name": "Notebook", "price": 30 }
  ]
}

Spec

[
  {
    "operation": "shift",
    "spec": {
      "products": {
        "*": {
          "@": "productMap.@(1,id)"
        }
      }
    }
  }
]

Explanation

• * → iterate array
• @ → copy entire object
• @(1,id) → read parent object’s id and use as map key

Output

{
  "productMap": {
    "1": { "id": 1, "name": "Pen", "price": 10 },
    "2": { "id": 2, "name": "Notebook", "price": 30 }
  }
}

---

Pattern 4 — Grouping items by category

Input

{
  "items": [
    { "name": "Fish", "type": "Food" },
    { "name": "Apple", "type": "Food" },
    { "name": "Shirt", "type": "Clothes" }
  ]
}

Spec

[
  {
    "operation": "shift",
    "spec": {
      "items": {
        "*": {
          "@": "grouped.@(1,type)[]"
        }
      }
    }
  }
]

Explanation:

• @(1,type) → read the type dynamically
• [ ] → append to array

Output

{
  "grouped": {
    "Food": [
      { "name": "Fish", "type": "Food" },
      { "name": "Apple", "type": "Food" }
    ],
    "Clothes": [
      { "name": "Shirt", "type": "Clothes" }
    ]
  }
}

---

Pattern 5 — Filter array items based on value

⚠ JOLT cannot do conditional filtering directly (no "if"),
BUT you can simulate filtering by mapping only the matching items.

Example: Keep only items where "active": true.

Input

{
  "users": [
    { "id": 1, "name": "A", "active": true },
    { "id": 2, "name": "B", "active": false },
    { "id": 3, "name": "C", "active": true }
  ]
}

Spec

This keeps only active==true.

[
  {
    "operation": "shift",
    "spec": {
      "users": {
        "*": {
          "active": {
            "true": {
              "@2": "activeUsers[]"
            }
          }
        }
      }
    }
  }
]

Explanation

• @2 = go 2 levels up → the whole user object
• Only items where "active": "true" map successfully

Output

{
  "activeUsers": [
    { "id": 1, "name": "A", "active": true },
    { "id": 3, "name": 3, "active": true }
  ]
}

---

Pattern 6 — Reorder and rename fields

Input

{
  "id": 10,
  "first": "Alice",
  "last": "Wonder"
}

Spec

[
  {
    "operation": "shift",
    "spec": {
      "id": "user.id",
      "first": "user.name.first",
      "last": "user.name.last"
    }
  }
]

Output

{
  "user": {
    "id": 10,
    "name": {
      "first": "Alice",
      "last": "Wonder"
    }
  }
}

---

Pattern 7 — Add default values

Spec

[
  {
    "operation": "default",
    "spec": {
      "status": "ACTIVE",
      "roles": ["USER"]
    }
  }
]

Useful in user creation APIs.

---

Pattern 8 — Selective removal of fields

Spec

[
  {
    "operation": "remove",
    "spec": {
      "internalId": "",
      "debug": ""
    }
  }
]

---

Pattern 9 — Math and string operations

Using modify-overwrite-beta.

Input

{
  "price": 100,
  "tax": 15
}

Spec

[
  {
    "operation": "modify-overwrite-beta",
    "spec": {
      "total": "=intSum(@(1,price), @(1,tax))"
    }
  }
]

Output

{
  "price": 100,
  "tax": 15,
  "total": 115
}

---

Pattern 10 — Transform list of values to objects

Input

{
  "tags": ["red", "blue", "green"]
}

Spec

[
  {
    "operation": "shift",
    "spec": {
      "tags": {
        "*": {
          "@": "list[]",
          "$": "list[].name"
        }
      }
    }
  }
]

Output

{
  "list": [
    { "name": "red" },
    { "name": "blue" },
    { "name": "green" }
  ]
}

---

2. INTERACTIVE EXAMPLES

These help you understand JOLT step-by-step.

---

Interactive Example 1: Dynamic key renaming

Input

{
  "meta": {
    "user_id": 5,
    "user_role": "admin"
  }
}

Goal

Convert keys from snake_case → camelCase.

Spec

[
  {
    "operation": "shift",
    "spec": {
      "meta": {
        "user_*": "user.&(0,1)"
      }
    }
  }
]

Explanation:

• user_* matches → user_id, user_role

• &(0,1) takes the part after the underscore

  • id
  • role

Output

{
  "user": {
    "id": 5,
    "role": "admin"
  }
}

---

Interactive Example 2: Pick fields based on dynamic index

Input

{
  "data": [
    { "name": "A", "score": 80 },
    { "name": "B", "score": 90 }
  ]
}

Want → convert list to key/value

Spec

[
  {
    "operation": "shift",
    "spec": {
      "data": {
        "*": {
          "score": "scores.@(2,name)"
        }
      }
    }
  }
]

Explanation:

@(2,name) goes 2 levels up → reads the "name"

Output

{
  "scores": {
    "A": 80,
    "B": 90
  }
}

---

Interactive Example 3 — Conditional grouping by value

Input

{
  "items": [
    { "name": "Book", "type": "A", "price": 20 },
    { "name": "Pen", "type": "B", "price": 5 },
    { "name": "Bag", "type": "A", "price": 100 }
  ]
}

Spec

[
  {
    "operation": "shift",
    "spec": {
      "items": {
        "*": {
          "@": "group.@(1,type)[]"
        }
      }
    }
  }
]

Output

group:
  A:
    - Book
    - Bag
  B:
    - Pen