类型、必填与枚举约束
您将在 JSON Schema 验证器中定义类型限制、必填字段和允许值枚举。
类型、必填与枚举约束 是 CoddyKit 上的免费 MongoDB Academy 课时。 这是第 2 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 MongoDB Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 MongoDB Academy 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
The Three Core Constraint Types
MongoDB JSON Schema validators support three fundamental constraint categories that cover the majority of real-world validation needs: type constraints that enforce the BSON data type of a field, required constraints that mandate the presence of certain fields, and enum constraints that restrict a field's value to a predefined whitelist. Together they form the backbone of any production schema validator.
BSON Types vs JSON Schema Types
JSON Schema uses standard JSON types like string, number, and object. MongoDB extends this with BSON types declared via the bsonType keyword—values like objectId, date, int, long, double, and decimal. Always use bsonType in MongoDB validators (not type) when you need precision about numeric subtypes or MongoDB-specific types like objectId and date.
// BSON type names to use in validators
// 'string', 'bool', 'int', 'long', 'double', 'decimal',
// 'objectId', 'date', 'array', 'object', 'null', 'binData'
db.createCollection('products', {
validator: {
$jsonSchema: {
bsonType: 'object',
properties: {
_id: { bsonType: 'objectId' },
price: { bsonType: 'decimal' },
stock: { bsonType: 'int' },
isActive: { bsonType: 'bool' },
createdAt: { bsonType: 'date' }
}
}
}
});Declaring Required Fields
The required keyword takes an array of field names that must be present in every document inserted or updated in the collection. If any required field is missing, the write is rejected. Required fields are declared at the schema level, not inside individual property definitions.
db.createCollection('employees', {
validator: {
$jsonSchema: {
bsonType: 'object',
required: ['firstName', 'lastName', 'email', 'hiredAt'],
properties: {
firstName: { bsonType: 'string' },
lastName: { bsonType: 'string' },
email: { bsonType: 'string' },
hiredAt: { bsonType: 'date' },
salary: { bsonType: 'decimal' } // optional
}
}
}
});Enum Constraints: Restricting Allowed Values
The enum keyword restricts a field to a fixed list of permitted values. This is ideal for status fields, category codes, or any field that must come from a controlled vocabulary. Attempting to insert a value outside the enum list causes the write to fail with a validation error.
db.createCollection('tickets', {
validator: {
$jsonSchema: {
bsonType: 'object',
required: ['title', 'status', 'priority'],
properties: {
title: { bsonType: 'string' },
status: { enum: ['open', 'in_progress', 'resolved', 'closed'] },
priority: { enum: ['low', 'medium', 'high', 'critical'] }
}
}
}
});Numeric Range Constraints
For numeric fields, JSON Schema provides minimum, maximum, exclusiveMinimum, and exclusiveMaximum keywords. These work alongside bsonType to enforce valid ranges—for example, ensuring a product price is positive and a rating falls between 1 and 5.
db.createCollection('reviews', {
validator: {
$jsonSchema: {
bsonType: 'object',
required: ['productId', 'rating'],
properties: {
productId: { bsonType: 'objectId' },
rating: {
bsonType: 'int',
minimum: 1,
maximum: 5,
description: 'Rating must be between 1 and 5'
},
price: {
bsonType: 'decimal',
minimum: 0,
exclusiveMinimum: true
}
}
}
}
});String Length Constraints
String fields support minLength and maxLength to enforce character count limits. A username might need to be at least 3 characters and at most 30. A description field might have a 2000-character cap. These constraints prevent accidentally storing empty strings or truncated text that exceeds UI display limits.
db.createCollection('profiles', {
validator: {
$jsonSchema: {
bsonType: 'object',
required: ['username'],
properties: {
username: {
bsonType: 'string',
minLength: 3,
maxLength: 30,
description: 'Username must be 3-30 characters'
},
bio: {
bsonType: 'string',
maxLength: 500
}
}
}
}
});Pattern Constraints for Strings
The pattern keyword accepts a regular expression string and validates that the field value matches it. This is useful for enforcing email format, phone number patterns, UUID format, or slug conventions. Unlike regex queries used for search, pattern constraints run at write time to block non-conforming data from entering the collection.
db.runCommand({
collMod: 'users',
validator: {
$jsonSchema: {
bsonType: 'object',
required: ['email'],
properties: {
email: {
bsonType: 'string',
pattern: '^[a-zA-Z0-9._%+\\-]+@[a-zA-Z0-9.\\-]+\\.[a-zA-Z]{2,}$',
description: 'Must be a valid email address'
},
slug: {
bsonType: 'string',
pattern: '^[a-z0-9]+(?:-[a-z0-9]+)*$'
}
}
}
}
});Combining Type and Enum
Type and enum can be combined. Providing both bsonType and enum ensures the value is both of the correct type and within the allowed set. Without bsonType, an enum will accept any type that matches—including a number equal to the string value if JavaScript coercion were involved. Explicit types make validation intent clear.
properties: {
role: {
bsonType: 'string',
enum: ['admin', 'editor', 'viewer'],
description: 'Must be a string and one of the allowed roles'
}
}additionalProperties to Disallow Unknown Fields
By default, MongoDB validators allow any extra fields not mentioned in properties. Setting additionalProperties: false prevents documents from containing fields not declared in the schema. This is a strict mode that can catch typos in field names during development, though it can be too rigid for schemas that evolve frequently.
db.createCollection('strictUsers', {
validator: {
$jsonSchema: {
bsonType: 'object',
required: ['name', 'email'],
additionalProperties: false, // reject any undeclared fields
properties: {
_id: { bsonType: 'objectId' },
name: { bsonType: 'string' },
email: { bsonType: 'string' }
}
}
}
});Providing Helpful Error Descriptions
The description keyword inside each property definition is included in the validation error message returned to the client. Writing clear, human-readable descriptions like 'Email must be a valid address' or 'Rating must be between 1 and 5' makes it much easier for developers and API consumers to understand and fix validation failures without reading the schema.
Testing Your Validator
After adding a validator, always test it with both valid and invalid documents to confirm it behaves as expected. Try inserting a document missing a required field, a field with the wrong type, and a field with a value outside the enum. Also insert a perfectly valid document to confirm it is accepted. This two-sided testing prevents overly strict validators that block legitimate writes.
// Should FAIL — missing required 'email'
try { db.users.insertOne({ name: 'Bob' }); } catch(e) { console.log('Correctly rejected:', e.code); }
// Should FAIL — wrong type for 'age'
try { db.users.insertOne({ name: 'Bob', email: 'b@b.com', age: 'thirty' }); } catch(e) { console.log('Correctly rejected'); }
// Should PASS
db.users.insertOne({ name: 'Bob', email: 'b@b.com', age: 30 });
console.log('Valid document accepted');Quick Check
Test your understanding of MongoDB & NoSQL Databases concepts from this lesson.
Lesson Recap
In this lesson you learned: bsonType enforces BSON-specific data types including objectId and date, required declares mandatory fields at the schema level, and enum restricts a field to a fixed list of allowed values. Next up we explore validation levels and actions to control how strictly MongoDB enforces these rules.
常见问题解答
「类型、必填与枚举约束」课时是免费的吗？
是的 — 「类型、必填与枚举约束」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 MongoDB Academy 课程的其余内容，请升级到 CoddyKit PRO。 MongoDB Academy 课程共包含 4 节课。
「类型、必填与枚举约束」这节课中我会学到什么？
您将在 JSON Schema 验证器中定义类型限制、必填字段和允许值枚举。 你通过在浏览器中直接运行的动手代码来练习 MongoDB Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 MongoDB Academy 需要有经验吗？
无需任何先前经验。CoddyKit 上的 MongoDB Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 2 节课，共 4 节。
「类型、必填与枚举约束」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 MongoDB Academy 课中编写并运行代码吗？
能。每节 MongoDB Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。