MongoDB is famous for its flexible schema. This feature is invaluable to developer productivity, enabling applications to evolve naturally with changing requirements without the need to revisit the schema designs throughout multiple layers of the stack. However, in any organization, a number of factors ranging from risk mitigation to politics may drive the need to enforce a more rigid schema. The way to address this need is through JSON Schema, which is an industry standard for validating JSON documents. In this talk, I will provide an overview of how to implement JSON Schema in MongoDB. I will also outline how teams can introduce JSON schema validation at just the right time in the lifecycle of their applications, balancing the benefits of developer productivity with requirements for strict schema enforcement.

1. Yulia Genkina - Curriculum Engineer, Circus Enthusiast
Just in Time Validation with JSON Schema
ygenkina

2. Flexible
Schema
Rigid
Schema
Startup
Enterprise
Your App

3. Flexible
Schema
Rigid
Schema
Startup
Enterprise
Your App
risk
scaling
regulation
policy
politics

4. Flexible
Schema
Rigid
Schema
Startup
Enterprise
Your App
regulation
politics
risk
policy
scaling

6. {
_id: 34556,
item: “Bow Tie",
price: NumberDecimal("27.99"),
quantity: NumberInt(1)
color: “green"
}
Simple Schema to Start

7. Use query filters to define schema constraints. E.g.,
db.createCollection("orders", {
validator: {
item: {$type: "string"},
price: {$type: "decimal"},
quantity: {$type: "int"},
color: {$in: ["red", "green", "blue"]}
}
});
Document Validation

8. $jsonSchema

9. • JSON Schema Draft 07
• Is an industry standard
• Widely used; lots of community support
JSON Schema

10. {
_id: 34556,
item: “Bow Tie”,
price: NumberDecimal("27.99"),
quantity: NumberLong(1),
color: "green"
}
Good for Starter Examples
{
_id: 34556,
total: NumberDecimal("100.00"),
VAT: NumberDecimal("0.20"),
totalWithVAT: NumberDecimal("100.20"),
lineitems: [
{ sku: "MDBTS001",
name: "Flannel T-shirt",
quantity: 2,
unit_price: NumberDecimal(”40.00") },
{ sku: "MDBTS002",
quantity: 4,
unit_price: NumberDecimal(”5.00")}]
}
More Realistic

11. {
_id: 34556,
item: “Bow Tie”,
price: NumberDecimal("27.99"),
quantity: NumberLong(1),
color: "green"
}
Good for Starter Examples
{
_id: 34556,
total: NumberDecimal("100.00"),
VAT: NumberDecimal("0.20"),
totalWithVAT: NumberDecimal("100.20"),
lineitems: [
{ sku: "MDBTS001",
name: "Flannel T-shirt",
quantity: 2,
unit_price: NumberDecimal(”40.00") },
{ sku: "MDBTS002",
quantity: 4,
unit_price: NumberDecimal(”5.00")}]
}
More Realistic

12. • Orders must contain a lineitems array of 1 to 10 documents
• Documents embedded in lineitems have fields for:
• sku (required)
• name (optional)
• unit_price (required)
• quantity (required)
• Value of quantity must be an integer
• (Must also contain fields: total, VAT, totalWithVAT, but we'll get to that.)
Our New Orders Schema

13. Let's validate the line item documents (embedded
in an array)

14. The most recent order we looked at actually contains a few errors:
• The total value should be the sum of each line item sub-total
• I.e., (2 * 400) + (4 * 50) = 1000
• The totalWithVAT value should be 1000 * 1.20 = 1200
Can we enforce that totalWithVAT and total are correct using validation?
Now Let's Deal with Totals and VAT

15. • MongoDB 4.2 -- more expressive query syntax
• Can express complex business rules in validations
• E.g, compute and compare multiple values at runtime
Yes we can!

16. Check that totalWithVAT == total * (1+VAT):
$expr: {
$eq: [
"$totalWithVAT",
{$multiply: [
"$total",
{$sum: [1, "$VAT"]}
]}
]
}
Let's add this as a validation rule alongside our JSON Schema validation ()
$expr

17. Now let's make sure the total is the sum of the line
item subtotals

18. $expr: {
$eq: [
"$total",
{$sum: {
$map: {
"input": "$lineitems",
"as": "item",
"in": {
"$multiply": [
"$$item.quantity",
"$$item.unit_price"
] } } }} ] }
Ensure total equals sum of line items

19. All together now

20. Flexible
Schema
Rigid
Schema
Startup
Enterprise
Your App
regulation
politics
risk
policy
scaling

21. Just the right amount of validation

22. When we want it, not before

23. • MongoDB 4.2 -- “Field-Level Encryption” feature
• Using Client-Side Encryption in MongoDB 4.2 by Kevin Albertson
• Tuesday (tomorrow) @ 12:45 pm
Bonus feature!

24. • MongoDB Documentation
• Schema Validation
• Expressive Query Syntax
• Free MongoDB Online Course from MongoDB University
• M320 Data Modeling
• A Complete Methodology to Data Modeling for MongoDB
• Today following this talk at 2 PM
• and other “Schema Design” talks
• http://bit.ly/schema_validation
Learn More

25. Special thanks to
Shannon Bradshaw - VP Education
and
Asya Kamsky - Principal Product Manager