Specify Validation for Polymorphic Collections

Create a JSON schema definition for each type of document

To distinguish between different types of documents, you can use multiple JSON schemas. To define what attributes need to be in a document and what data types they accept, create two schemas: one for a customer document, and one for an account document. Each schema includes a docType attribute to identify which type of entity it represents.

const customerSchema = {
 required: ["docType", "customerId", "name", "customerSince"],
 properties: {
 docType: { enum: ["customer"] },
 customerId: { bsonType: "string"},
 name: {
 bsonType: "object",
 required: ["first", "last"],
 properties: {
 title: { enum: ["Mr", "Mrs", "Ms", "Dr"]},
 first: { bsonType: "string" },
 middle: { bsonType: "string" },
 last: { bsonType: "string" }
 }
 },
 address: {
 bsonType: "object",
 required: ["street1", "city", "postCode", "country"],
 properties: {
 street1: { bsonType: "string" },
 street2: { bsonType: "string" },
 postCode: { bsonType: "string" },
 country: { bsonType: "string" }
 }
 },
 customerSince: {
 bsonType: "date"
 }
 }
};
const accountSchema = {
 required: ["docType", "accountNumber", "accountType", "customerId", "dateOpened", "balance"],
 properties: {
 docType: { enum: ["account"] },
 accountNumber: { bsonType: "string" },
 accountType: { enum: ["checking", "savings", "mortgage", "loan"] },
 customerId: { bsonType: "array" },
 dateOpened: { bsonType: "date" },
 balance: { bsonType: "decimal" }
 }
};

Configure the collection to only accept the appropriate documents

To allow documents that match either the customerSchema or the accountSchema, use the oneOf JSON schema operator. Then, use the collMod command to update the accounts collection to use to your schema validation.

db.runCommand({
 collMod: "accounts",
 validator: { $jsonSchema: { oneOf: [ customerSchema, accountSchema ] } }
})

Add extra semantic validations

You can optionally add extra semantic validations. For example, you can add the following constraints to your collection’s documents:

• For customer documents, the customerSince value can't be any earlier than the current time.

• For account documents, the dateOpened value can't be any earlier than the current time.

• For savings accounts, the balance can't fall below zero.

You can implement the extra validations by identifying invalid customer and account documents and implementing those constraints into your schema validation.

const invalidCustomer = {
 "$expr": { "$gt": ["$customerSince", "$$NOW"] }
};
const invalidAccount = {
 $or: [
 {
 accountType: "savings",
 balance: { $lt: 0}
 },
 {
 "$expr": { "$gt": ["$dateOpened", "$$NOW"]}
 }
 ]
};

const schemaValidation = {
 "$and": [
 { $jsonSchema: { oneOf: [ customerSchema, accountSchema ] }},
 { $nor: [
 invalidCustomer,
 invalidAccount
 ]
 }
 ]
};
db.runCommand({
 collMod: "accounts",
 validator: schemaValidation
})

Verify the documents in your collection

To verify that all the documents already in your collection adhere to your new schema validation, use the db.collection.validate() command.

db.accounts.validate()

{
 ns: '66cf8508e64dbb03ce45b30e_test.accounts',
 uuid: UUID('1aedf62a-f202-4e7c-b434-879057bb6d6b'),
 nInvalidDocuments: 0,
 nNonCompliantDocuments: 0,
 nrecords: 10,
 nIndexes: 1,
 keysPerIndex: { _id_: 10 },
 indexDetails: { _id_: { valid: true } },
 valid: true,
 repaired: false,
 readTimestamp: Timestamp({ t: 1749235730, i: 26 }),
 warnings: [],
 errors: [],
 extraIndexEntries: [],
 missingIndexEntries: [],
 corruptRecords: [],
 ok: 1,
 '$clusterTime': {
 clusterTime: Timestamp({ t: 1749235753, i: 31 }),
 signature: {
 hash: Binary.createFromBase64('3h7qyhLsgU21Pnzf/KVLl8suu2I=', 0),
 keyId: Long('7449048397505364002')
 }
 },
 operationTime: Timestamp({ t: 1749235753, i: 31 })
}

nNonCompliantDocuments: 0 in the output indicates that all the documents in the accounts collection comply with the collection schemas.

Test your schema validation

To verify your schema validation, you can try to insert an invalid document into the accounts collection. For example, try inserting a customer document missing the required last field, for last name:

db.accounts.insertOne(
 {
 "docType": "customer",
 "customerId": "12345",
 "name": {
 "first": "John",
 },
 "customerSince": "2025-01-01T00:00:00Z"
 }
)

MongoServerError: Document failed validation