1. #MongoDBDays
Schema Design
Craig Wilson
Software Engineer, 10gen
@craiggwilson

2. Agenda
• Working with Documents
• Schema Design by Example
• Common Patterns
Single Table En

3. RDBMS MongoDB
Database ➜ Database
Table ➜ Collection
Row ➜ Document
Index ➜ Index
Join ➜ Embedding & Linking
Terminology

4. Example Schema (MongoDB)

5. Embedding
Example Schema (MongoDB)

6. Embedding
Linking
Example Schema (MongoDB)

7. Working with Documents

8. Documents
Provide flexibility and
performance

9. Traditional Schema Design
Focuses on data storage

10. Document Schema Design
Focuses on data use

11. Document Schema Design
• Read Heavy?
• Write Heavy?
– Document Growth
• Analytics
– Map Reduce
– External System

12. Tools for Working with Data
• Dynamic Schemas
• Embedded data structures
• Ad-hoc queries
– Simple Queries
– Aggregation Framework
• Secondary indexes
• Multi-Key indexes

13. Tools for Manipulating Data
• On the way out
– Scalar: $ne, $mod, $exists, $type, $lt, $lte, $gt, $gte, $ne
– Vector: $in, $nin, $all, $size
• On the way in
– Scalar: $inc, $set, $unset
– Vector: $push, $pop, $pull, $pushAll, $pullAll, $addToSet

14. Schema Design by
Example

15. Library Management Application
• Patrons
• Books
• Authors
• Publishers

16. Use Case #1
As a Librarian, when I
swipe a patron’s card, I
need to verify their
address.

17. Modeling Patrons
patron = { patron = {
_id: "joe“, _id: "joe",
name: "Joe Bookreader” name: "Joe Bookreader",
} address: {
street: "123 Fake St. ",
address = { city: "Faketon",
_id = "joe“,
state: "MA",
street: "123 Fake St. ",
city: "Faketon", zip: 12345
state: "MA", }
zip: 12345 }
}

18. One to One Relations
• “Belongs to” relationships are often embedded
• Document model provides a holistic
representation of objects with embedded entities
• Optimized for read performance

19. Use Case #2
As a Librarian, I want to
store multiple addresses
so I have a better chance
of getting my book back.

20. Modeling Patrons
patron = { patron = {
_id: "joe", _id: "joe",
name: "Joe Bookreader", name: "Joe Bookreader",
address: { join_date: ISODate("2011-10-15"),
addresses: [
street: "123 Fake St. ",
{street: "1 Vernon St.", city: "Newton", …},
city: "Faketon", {street: "52 Main St.", city: "Boston", …},
state: "MA", ]
zip: 12345 }
}
}

21. Use Case #3
As a Librarian, I want to
see to the publisher of a
book.

22. Publishers and Books
• Publishers put out many books
• Books have one publisher

23. Book Data
MongoDB: The Definitive Guide,
By Kristina Chodorow and Mike Dirolf
Published: 9/24/2010
Pages: 216
Language: English
Publisher: O’Reilly Media, CA

24. Book Model with Embedded
Publisher
book = {
_id: “123”,
title: "MongoDB: The Definitive Guide",
authors: [ "Kristina Chodorow", "Mike Dirolf" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
publisher: {
name: "O’Reilly Media",
founded: "1980",
location: "CA"
}
}

25. Book Model with Embedded
Publisher
• Optimized for read performance of Books
• Other queries are difficult
– All publishers

26. Use Case #4
As a Librarian, I want to
see all the publishers in
the system.

27. Book Model with a Publisher
Link
publisher = {
_id: “oreilly”,
name: "O’Reilly Media",
founded: "1980",
location: "CA"
}
book = {
_id: “123”,
publisher_id: “oreilly”,
title: "MongoDB: The Definitive Guide",
authors: [ "Kristina Chodorow", "Mike Dirolf" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English"
}

28. Use Case #5
As a Librarian, I want to
see all the books a
publisher has published.

29. Publisher Model with Book
Links
publisher = {
_id: “oreilly”,
name: "O’Reilly Media",
founded: "1980",
location: "CA“,
books: [“123”,…]
}
book = {
_id: “123”,
title: "MongoDB: The Definitive Guide",
authors: [ "Kristina Chodorow", "Mike Dirolf" ]
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English"
}

30. Use Case #6
As a Librarian, I want to
find the author(s) of
book “Foo”.

31. Books and Authors
book = {
_id: “123”,
title: "MongoDB: The Definitive Guide",
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English"
}
author = {
_id: “kchodorow”,
name: "Kristina Chodorow",
hometown: "New York"
}
author = {
_id: “mdirolf”,
name: “Mike Dirolf",
hometown: “Albany"
}

32. Relation stored on book end
book = {
title: "MongoDB: The Definitive Guide",
authors = ["kchodorow", "mdirolf“],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English"
}
author = {
_id: "kchodorow",
name: "Kristina Chodorow",
hometown: "New York"
}
author = {
_id: “mdirolf”,
name: “Mike Dirolf",
hometown: “Albany"
}

33. Relation stored on book end
book = {
title: "MongoDB: The Definitive Guide",
authors = [
{ id: "kchodorow", name: "Kristina Chodorow” },
{ id: "mdirolf", name: "Mike Dirolf” }
]
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English"
}
author = {
_id: "kchodorow",
name: "Kristina Chodorow",
hometown: "New York"
}
author = {
_id: “mdirolf”,
name: “Mike Dirolf",
hometown: “Albany"
}

34. Use Case #7
As a Librarian, I want to
find other books written
by the same author.

35. Relation stored on author end
book = {
_id: “123”,
title: "MongoDB: The Definitive Guide",
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English"
}
author = {
_id: "kchodorow",
name: "Kristina Chodorow",
hometown: "Cincinnati",
books: [ {id: “123”, title : "MongoDB: The Definitive Guide“ } ]
}

36. Relation stored on both sides
book = {
_id: “123”,
title: "MongoDB: The Definitive Guide",
authors = [
{ id: "kchodorow", name: "Kristina Chodorow” },
{ id: "mdirolf", name: "Mike Dirolf” }
]
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English"
}
author = {
_id: "kchodorow",
name: "Kristina Chodorow",
hometown: "Cincinnati",
books: [ {id: “123”, title : "MongoDB: The Definitive Guide“ } ]
}

37. Linking vs. Embedding
• Embedding
– Great for read performance
• One seek to load entire object
• One roundtrip to database
– Writes can be slow
– Maintaining data integrity
• Linking
– More flexibility
– Data integrity is maintained
– Work is done during reads

38. Common Patterns

39. An Example
Trees

40. Parent Links
book = {
title: "MongoDB: The Definitive Guide",
authors: [ "Kristina Chodorow", "Mike Dirolf" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
category: "MongoDB"
}
category = { _id: ”MongoDB”, parent: “Databases” }
category = { _id: ”Databases”, parent: “Programming” }

41. Array of Ancestors
book = {
title: "MongoDB: The Definitive Guide",
authors: [ "Kristina Chodorow", "Mike Dirolf" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
parent: "MongoDB",
categories: ["MongoDB", "Databases", "Programming" ]
}
book = {
title: "MySQL: The Definitive Guide",
authors: [ ”Michael Kofler" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
parent: "MySQL",
categories : ["MySQL", "Databases", "Programming" ]
}

42. Ancestors as path
book = {
title: "MongoDB: The Definitive Guide",
authors: [ "Kristina Chodorow", "Mike Dirolf" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
category: "MongoDB/Databases/Programming"
}
book = {
title: "MySQL: The Definitive Guide",
authors: [ ”Michael Kofler" ],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
parent: "MySQL",
category: "MySQL/Databases/Programming"
}

43. An Example
Inheritance

44. Single Table Inheritance
id type area radius length width
1 circle 3.14 1
2 square 4 2
3 rect 10 5 2
• Sparse data
• Is missing value not required or an error?

45. Single collection (table)
inheritance - MongoDB
> db.shapes.find()
{ _id : 1, type: "circle", area : 3.14, radius : 1 }
{ _id : 2, type: "square", area : 4, length : 2 }
{ _id : 3, type: "rect", area : 10, length : 5, width : 2 }

46. Summary
• Schema design is different in MongoDB
• Basic data design principals stay the same
• Focus on how application accesses/manipulates
data
• Rapidly evolve schema to meet your
requirements

47. #MongoDBDays
Thank You
Craig Wilson
Software Engineer, 10gen
@craiggwilson