Using JSON schema validation

Using the $jsonSchema evaluation query operator, you can validate documents being inserted into your collections.

Creating and using JSON schema validation

Creating a collection with schema validation

You can create a collection with createCollection operation and validation rules. These validation rules are applied during inserts or updates of Amazon DocumentDB documents. The following code example shows validation rules for a collection of employees:

db.createCollection("employees", {
   "validator": {
      "$jsonSchema": {
         "bsonType": "object",
         "title": "employee validation",
         "required": [ "name", "employeeId"],
         "properties": {
            "name": {
                  "bsonType": "object",
                  "properties": {
                     "firstName": {
                        "bsonType": ["string"]
                     },
                     "lastName": {
                        "bsonType": ["string"]
                     }
                  },
                  "additionalProperties" : false 
            },
            "employeeId": {
               "bsonType": "string",
               "description": "Unique Identifier for employee"
            },
             "salary": {
               "bsonType": "double"
            },
            "age": {
               "bsonType": "number"
            }
         },
         "additionalProperties" : true 
      }
   },
   "validationLevel": "strict", "validationAction": "error"
} )

Inserting a valid document

The following example inserts documents that comply with the above schema validation rules:

db.employees.insert({"name" : { "firstName" : "Carol" , "lastName" : "Smith"}, "employeeId": "c720a" , "salary": 1000.0 })
db.employees.insert({ "name" : { "firstName" : "William", "lastName" : "Taylor" }, "employeeId" : "c721a", "age" : 24})

Inserting an invalid document

The following example inserts documents that do not comply with the above schema validation rules. In this example, the employeeId value is not a string:

db.employees.insert({
    "name" : { "firstName" : "Carol" , "lastName" : "Smith"}, 
    "employeeId": 720 , 
    "salary": 1000.0 
})

This example shows incorrect syntax within the document.

Modifying a collection

The collMod command is used to add or modify validation rules of existing collection. The following example adds a salary field to the required field list:

db.runCommand({"collMod" : "employees", 
   "validator": {
      "$jsonSchema": {
         "bsonType": "object",
         "title": "employee validation",
         "required": [ "name", "employeeId", "salary"],
         "properties": {
            "name": {
                  "bsonType": "object",
                  "properties": {
                     "firstName": {
                        "bsonType": ["string"]
                     },
                     "lastName": {
                        "bsonType": ["string"]
                     }
                  },
                  "additionalProperties" : false 
            },
            "employeeId": {
               "bsonType": "string",
               "description": "Unique Identifier for employee"
            },
             "salary": {
               "bsonType": "double"
            },
            "age": {
               "bsonType": "number"
            }
         },
         "additionalProperties" : true 
      }
   }
} )

Addressing documents added before the validation rules were changed

To address documents that were added to you collection before the validation rules were changed, use the following validationLevel modifiers:

In the following example, after updating the validation rules on the collection named “employees”, the salary field is required. Updating following document will fail:

db.runCommand({ 
    update: "employees", 
    updates: [{ 
        q: { "employeeId": "c721a" }, 
        u: { age: 25 , salary : 1000}, 
        upsert: true }] 
})

Amazon DocumentDB returns the following output:

{
"n" : 0,
    "nModified" : 0,
    "writeErrors" : [
        {
"index" : 0,
            "code" : 121,
            "errmsg" : "Document failed validation"
        }
    ],
    "ok" : 1,
    "operationTime" : Timestamp(1234567890, 1)
}

Updating the validation level to moderate will allow the above document to be updated successfully:

db.runCommand({
    "collMod" : "employees", 
    validationLevel : "moderate"
})

db.runCommand({ 
    update: "employees", 
    updates: [{ 
        q: { "employeeId": "c721a" }, 
        u: { age: 25 , salary : 1000}, 
        upsert: true }]
})

Amazon DocumentDB returns the following output:

{
"n" : 1,
    "nModified" : 1,
    "ok" : 1,
    "operationTime" : Timestamp(1234567890, 1)
}

Retrieving documents with the $jsonSchema

The $jsonSchema operator can be used as a filter to query documents that match the JSON schema. This is a top-level operator which can be present in filter documents as a top level field or used with query operators such as $and, $or, and $nor. The following examples show the use of $jsonSchema as an individual filter and with other filter operators:

Document inserted into an "employee" collection:

{ "name" : { "firstName" : "Carol", "lastName" : "Smith" }, "employeeId" : "c720a", "salary" : 1000 }
{ "name" : { "firstName" : "Emily", "lastName" : "Brown" }, "employeeId" : "c720b", "age" : 25, "salary" : 1050.2 }
{ "name" : { "firstName" : "William", "lastName" : "Taylor" }, "employeeId" : "c721a", "age" : 24, "salary" : 1400.5 }
{ "name" : { "firstName" : "Jane", "lastName" : "Doe" }, "employeeId" : "c721a", "salary" : 1300 }

Collection filtered with the $jsonSchema operator only:

db.employees.find({ 
       $jsonSchema: { required: ["age"] } })

Amazon DocumentDB returns the following output:

{ "_id" : ObjectId("64e5f91c6218c620cf0e8f8b"), "name" : { "firstName" : "Emily", "lastName" : "Brown" }, "employeeId" : "c720b", "age" : 25, "salary" : 1050.2 }
{ "_id" : ObjectId("64e5f94e6218c620cf0e8f8c"), "name" : { "firstName" : "William", "lastName" : "Taylor" }, "employeeId" : "c721a", "age" : 24, "salary" : 1400.5 }

Collection filtered with the $jsonSchema operator and another operator:

db.employees.find({ 
       $or: [{ $jsonSchema: { required: ["age", "name"]}}, 
            { salary: { $lte:1000}}]});

Amazon DocumentDB returns the following output:

{ "_id" : ObjectId("64e5f8886218c620cf0e8f8a"), "name" : { "firstName" : "Carol", "lastName" : "Smith" }, "employeeId" : "c720a", "salary" : 1000 }
{ "_id" : ObjectId("64e5f91c6218c620cf0e8f8b"), "name" : { "firstName" : "Emily", "lastName" : "Brown" }, "employeeId" : "c720b", "age" : 25, "salary" : 1050.2 }
{ "_id" : ObjectId("64e5f94e6218c620cf0e8f8c"), "name" : { "firstName" : "William", "lastName" : "Taylor" }, "employeeId" : "c721a", "age" : 24, "salary" : 1400.5 }

Collection filtered with the $jsonSchema operator and with $match in the aggregate filter:

db.employees.aggregate(
    [{ $match: { 
        $jsonSchema: { 
            required: ["name", "employeeId"],  
            properties: {"salary" :{"bsonType": "double"}}
        }
       }
    }]
)

Amazon DocumentDB returns the following output:

{ 
"_id" : ObjectId("64e5f8886218c620cf0e8f8a"),
 "name" : { "firstName" : "Carol", "lastName" : "Smith" },
"employeeId" : "c720a",
"salary" : 1000 
}
{
"_id" : ObjectId("64e5f91c6218c620cf0e8f8b"),
"name" : { "firstName" : "Emily", "lastName" : "Brown" },
"employeeId" : "c720b",
"age" : 25,
"salary" : 1050.2
}
{
"_id" : ObjectId("64e5f94e6218c620cf0e8f8c"),
"name" : { "firstName" : "William", "lastName" : "Taylor" },
"employeeId" : "c721a",
"age" : 24,
"salary" : 1400.5
}
{
"_id" : ObjectId("64e5f9786218c620cf0e8f8d"),
"name" : { "firstName" : "Jane", "lastName" : "Doe" },
"employeeId" : "c721a",
"salary" : 1300
}

Viewing existing validation rules

To see the existing validation rules on a collection, use:

db.runCommand({
    listCollections: 1, 
    filter: { name: 'employees' }
})

Amazon DocumentDB returns the following output:

{
    "waitedMS" : NumberLong(0),
    "cursor" : {
        "firstBatch" : [
            {
                "name" : "employees",
                "type" : "collection",
                "options" : {
                    "autoIndexId" : true,
                    "capped" : false,
                    "validator" : {
                        "$jsonSchema" : {
                            "bsonType" : "object",
                            "title" : "employee validation",
                            "required" : [
                                "name",
                                "employeeId",
                                "salary"
                            ],
                            "properties" : {
                                "name" : {
                                    "bsonType" : "object",
                                    "properties" : {
                                        "firstName" : {
                                            "bsonType" : [
                                                "string"
                                            ]
                                        },
                                        "lastName" : {
                                            "bsonType" : [
                                                "string"
                                            ]
                                        }
                                    },
                                    "additionalProperties" : false
                                },
                                "employeeId" : {
                                    "bsonType" : "string",
                                    "description" : "Unique Identifier for employee"
                                },
                                "salary" : {
                                    "bsonType" : "double"
                                },
                                "age" : {
                                    "bsonType" : "number"
                                }
                            },
                            "additionalProperties" : true
                        }
                    },
                    "validationLevel" : "moderate",
                    "validationAction" : "error"
                },
                "info" : {
                    "readOnly" : false
                },
                "idIndex" : {
                    "v" : 2,
                    "key" : {
                        "_id" : 1
                    },
                    "name" : "_id_",
                    "ns" : "test.employees"
                }
            }
        ],
        "id" : NumberLong(0),
        "ns" : "test.$cmd.listCollections"
    },
    "ok" : 1,
    "operationTime" : Timestamp(1692788937, 1)
}

Amazon DocumentDB also retains validation rules in the $out aggregation stage.

Supported keywords

The following fields are supported in the create and collMod commands:

The $jsonSchema operator supports the following keywords:

bypassDocumentValidation

Amazon DocumentDB supports bypassDocumentValidation for the following commands and methods:

Amazon DocumentDB does not support the following commands for bypassDocumentValidation:

Limitations

The following limitations apply to $jsonSchema validation: