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Showing content from https://www.mongodb.com/docs/v6.0/core/schema-validation/specify-query-expression-rules/ below:

Specify Validation With Query Operators - Database Manual v6.0

You can specify validation using query operators such as $eq and $gt to compare fields.

A common use case for schema validation with query operators is when you want to create dynamic validation rules that compare multiple field values at runtime. For example, if you have a field that depends on the value of another field and need to ensure that those values are correctly proportional to each other.

• You can't specify the following query operators in a validator object:

  • $expr with $function expressions

  • $near

  • $nearSphere

  • $text

  • $where

• You can't specify schema validation for:

  • Collections in the admin, local, and config databases

  • System collections

Consider an application that tracks customer orders. The orders have a base price and a VAT. The orders collection contains these fields to track total price:

• price

• VAT

• totalWithVAT

The following procedure creates a schema validation with query operators to ensure that totalWithVAT matches the expected combination of price and VAT.

Create an orders collection with schema validation:

db.createCollection( "orders",   {      validator: {         $expr:            {               $eq: [                  "$totalWithVAT",                  { $multiply: [ "$total", { $sum:[ 1, "$VAT" ] } ] }               ]            }      }   })

With this validation, you can only insert documents if the totalWithVAT field equals total * (1 + VAT).

The following operation fails because the totalWithVAT field does not equal the correct value:

db.orders.insertOne( {   total: Decimal128("141"),   VAT: Decimal128("0.20"),   totalWithVAT: Decimal128("169")} )

141 * (1 + 0.20) equals 169.2, so the value of the totalWithVAT field must be 169.2.

The operation returns this error:

MongoServerError: Document failed validationAdditional information: {  failingDocumentId: ObjectId("62bcc9b073c105dde9231293"),  details: {    operatorName: '$expr',    specifiedAs: {      '$expr': {        '$eq': [          '$totalWithVAT',          {            '$multiply': [ '$total', { '$sum': [ 1, '$VAT' ] } ]          }        ]      }    },    reason: 'expression did not match',    expressionResult: false  }}

After updating the document to have the correct totalWithVAT value, the operation succeeds:

db.orders.insertOne( {   total: Decimal128("141"),   VAT: Decimal128("0.20"),   totalWithVAT: Decimal128("169.2")} )

MongoDB returns the following output, indicating that the insert was successful:

{  acknowledged: true,  insertedId: ObjectId("6304f4651e52f124b84479ba")}

You can combine query operator validation with JSON Schema validation.

For example, consider a sales collection with this schema validation:

 db.createCollection("sales", {   validator: {     "$and": [              {         "$expr": {           "$lt": ["$lineItems.discountedPrice", "$lineItems.price"]         }       },              {         "$jsonSchema": {           "properties": {             "items": { "bsonType": "array" }           }          }        }      ]    }  })

The preceding validation enforces these rules for documents in the sales collection:

• lineItems.discountedPrice must be less than lineItems.price. This rule is specified using the $lt operator.

• The items field must be an array. This rule is specified using $jsonSchema.

• To see all query operators available in MongoDB, see Query Selectors.

• To learn more about the $expr operator, which allows the use of aggregation expressions within the query language, see $expr.

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