The document discusses MongoDB's schema design and storage engines, primarily focusing on the differences between mmapv1 and WiredTiger. It outlines schema design best practices, document structures, data lifecycle considerations, and operational best practices for optimizing database performance. Additionally, it highlights the importance of choosing the right storage engine for specific workloads and provides various examples and use cases.

1. RSVP: mongodb.com/events
What’s coming in 3.4?
San Francisco | 11/1

3. Schema Patterns and
Your Storage Engine

4. Agenda
Schema Design 101
MMAPv1
Wired Tiger
Examples
Update Process

5. https://farm3.staticflickr.com/2001/2087134188_98125a9702_z.jpg

6. Why do we have so some many
options?
MMAP V1WT 3rd
Party
Available 3.2 Your
own?
In-memoryEncrypted

7. Example of Document Definition
• App1
- Realtime dashboard
- Ad hoc queries
- User profiles
• App2
- Heavy writes batch process
- Analytics workload
- Multi-tenant application

8. Schema Design 101

9. Why is Schema Design Important ?

10. Why is Schema Design Important ?
• Defines our applications interactions
• How we defined data
• Can considerably impact performance
• Impact DBA’s sleep!
{
first_name: ‘Paul’,
surname: ‘Miller’,
cell: 447557505611,
city: ‘London’,
location: [45.123,47.232],
Profession: [banking, finance, trader],
cars: [
{ model: ‘Bentley’,
year: 1973,
value: 100000, … },
{ model: ‘Rolls Royce’,
year: 1965,
value: 330000, … }
]
}
Fields can contain an
array of sub-documents
Typed field values
Fields can contain arrays

11. Document Model
class Item(Object):
def __init__(self, name, car ,date):
self.name = name
self.car = car
self.date = date
class Car(Object):
def __init__(self, brand, manufactor,
date):
self.brand = brand
self.manufactor = manufactor
self.date = date
Natural
Representation
Flexible Schema
Aligned with
Development
{ _id: 1,
'greetings':'hello'
}
{ _id: 2,
'k':'greetings',
'v': 'hello'
}
{ _id: 1,
'k':'greetings',
'v': 'hello'
}
{ _id: 2,
'car':{ 'manufactor': 'somecarmaker',
'brand': 'somebrand',
'date': ISODate("2016-06-27")
}
'date': ISODate("2016-06-27")
}

12. What to Consider
Change Rate ConcurrencyData Structure Data Lifecycle

13. What to Consider
Data Structure
users accounts reviews products

14. What to Consider
Data Structure
accounts
users
products
reviews

15. What to Consider
Data Structure
users accounts reviews products

16. What to Consider
Data Structure
Client1 Client2 Client3 Client4

17. What to Consider
{
_id: 1,
model : "ford"
year: 2014,
picture: BinData(2, "afGGAF677..."),
}
{
_id: 1,
model : "ford"
date: {year: 2014, month: 5, day: 1},
picture: "AAFF123BEFC...",
}
{
_id: 1,
model : ObjectId("21213312"),
date: ISODate("20140501"),
picture: "AAFF123BEFC...",
}
Change Rate

18. What to Consider
{
_id: 1,
model : "ford"
year: 2014,
picture: BinData(2, "afGGAF677..."),
}
{
_id: 1,
model : "ford"
date: {year: 2014, month: 5, day: 1},
picture: "AAFF123BEFC...",
}
{
_id: 1,
model : ObjectId("21213312"),
date: ISODate("20140501"),
picture: "AAFF123BEFC...",
}
Different data types
Change Rate

19. What to Consider
{
_id: 1,
model : "ford"
year: 2014,
picture: BinData(2, "afGGAF677..."),
}
{
_id: 1,
model : "ford"
date: {year: 2014, month: 5, day: 1},
picture: "AAFF123BEFC...",
}
{
_id: 1,
model : ObjectId("21213312"),
date: ISODate("20140501"),
picture: "AAFF123BEFC...",
}
Different field structure
Change Rate

20. What to Consider
{
"product_id": "b872ad6e34f87102cf866fead4e10e29",
"purchases":{
"2016": {
"06": 2823,
"05": 5535,
...
"total": 1222312
},
"2015": {...},
"2014": {...},
"2013": {...},
}
}
Data Lifecycle

21. What to Consider
{
"product_id": "b872ad6e34f87102cf866fead4e10e29",
"purchases":{
"2016": {
"06": 2823,
"05": 5535,
...
"total": 1222312
},
"2015": {...},
"2014": {...},
"2013": {...},
}
}
What we actually
read and write
Data Lifecycle

22. What to Consider
{
"product_id": "b872ad6e34f87102cf866fead4e10e29",
"purchases":{
"2016": {
"06": 2823,
"05": 5535,
...
"total": 1222312
},
"2015": {...},
"2014": {...},
"2013": {...},
}
}
What we don't
anymore
Data Lifecycle

23. What to Consider
Concurrency

24. What to Consider
Concurrency

25. What to Consider
Concurrency

26. What to Consider
Concurrency

27. MMAPv1

28. Disclaimer!
WiredTiger is our default Storage Engine - 3.2
onwards

29. MMAPv1 / Basics
• Data is Mapped into virtual Memory for
Fast access
• Documents pointers are request per
access
• If in Memory = fast
• If not = Disk seek
• Indexes follow the same structure
• Allocation based on Database per file

30. db.collection.update(
{a: 1},
{ $set: {
b: 1,
c: {$inc:10},
d: {$push: ["hello"]
})
$set Operator
MMAPv1 / Schema Design Best Practices

31. db.collection.insert(
{
_id: 1,
name: 'Norberto',
parking_tickets: {},
eat_outs:[
null,
null,
null,
null
]
}
)
Document
Pre-allocation
db.collection.update(
{a: 1},
{ $set: {
b: 1,
c: {$inc:10},
d: {$push: ["hello"]
})
$set Operator
MMAPv1 / Schema Design Best Practices

32. db.collection.insert(
{
_id: 1,
name: 'Norberto',
parking_tickets: {},
eat_outs:[
null,
null,
null,
null
]
}
)
Document
Pre-allocation
db.collection.update(
{a: 1},
{ $set: {
b: 1,
c: {$inc:10},
d: {$push: ["hello"]
})
$set Operator
db.movies.update(
{_id: "b872ad6e34"},
{$push:{
reviews: {
$each:
["great", "5*","awful"],
$slice: 10
}
}})
Keep Documents
Small
MMAPv1 / Schema Design Best Practices

33. Wired Tiger

34. WiredTiger / Basics
• MVCC Storage Engine
• Compression
• Document Level Concurrency Control
• Better resource allocation
WiredTiger Engine
Schema &
Cursors
Python API C API Java API
Database
Files
Transactions
Page
read/write
Logging
Column
storage
Block
management
Row
storage
Snapshots
Log Files
Cache

35. WiredTiger/ Schema Design Best Practices

36. Cache Size
WiredTiger/ Schema Design Operational Best Practices
Disk
RAM

37. Cache Size
WiredTiger/ Operational Best Practices
Disk
RAM
cacheSizeGB

38. Cache Size
WiredTiger/ Operational Best Practices
Disk
RAM
cacheSizeGB
Heap
OS

39. Document Level
Concurrency
Control
Cache Size
WiredTiger/ Operational Best Practices
Disk
RAM
cacheSizeGB
Heap
OS mongod
Collection
Collection
Collection

40. Document Level
Concurrency
Control
Cache Size
WiredTiger/ Operational Best Practices
Disk
RAM
cacheSizeGB
Heap
OS mongod
Collection
Doc1
Doc2
Doc3
Doc4
Doc5
Doc6
DocX

41. Document Level
Concurrency
Control
MMAPv1/ Operational Best Practices
mongod
Collection1
doc1
Collection2
doc2
Collection2
doc3
Collection4
doc4
Collection5
doc5
Collection6
doc6
Collection7
doc7
CollectionX
docX

42. Document Level
Concurrency
Control
MMAPv1/ Operational Best Practices
mongod
Collection1
doc1
Collection2
doc2
Collection2
doc3
Collection4
doc4
Collection5
doc5
Collection6
doc6
Collection7
doc7
CollectionX
docX

43. Document Level
Concurrency
Control
Cache Size Compression
WiredTiger/ Operational Best Practices
Disk
RAM
cacheSizeGB
Heap
OS mongod
Collection
Collection
Collection
Doc1
Doc2
Doc3
Doc4
Doc5
Doc6
DocX
RAM
{
"message": "hello
MongoDB World",
"user": "Norberto",
"channel": "twitter",
"comments": [
{"text":"howdy",
"user":"Ross"}]
}

44. Document Level
Concurrency
Control
Cache Size Compression
WiredTiger/ Operational Best Practices
Disk
RAM
cacheSizeGB
Heap
OS mongod
Collection
Collection
Collection
Doc1
Doc2
Doc3
Doc4
Doc5
Doc6
DocX
RAM
gzip(0x001231400122
2321)

45. WiredTiger/ Schema Design - Compression
{
"product_id": "b872ad6e34",
"name": "MongoDB Atlas",
"company": "MongoDB",
"description": "MongoDBAAS",
"comments": [
{"text":"Beautiful"}
]
}

46. WiredTiger/ Schema Design - Compression
{
"product_id": "b872ad6e34",
"name": "MongoDB Atlas",
"company": "MongoDB",
"description": "MongoDBAAS",
"comments": [
{"text":"Beautiful"}
]
}
MMAPv1
{
"pid": "b872ad6e34",
"n": "MongoDB Atlas",
"c": "MongoDB",
"d": "MongoDBAAS",
"cs": [
{"t":"Beautiful"}
]
}

47. WiredTiger/ Schema Design - Compression
{
"product_id": "b872ad6e34",
"name": "MongoDB Atlas",
"company": "MongoDB",
"description": "MongoDBAAS",
"comments": [
{"text":"Beautiful"}
]
}
WiredTiger

48. WiredTiger/ Schema Design – Index Prefix Compression
{
"user": "Norberto",
"country": "Portugal",
"last_comment": ”European Champions!!!",
}

49. WiredTiger/ Schema Design – Index Prefix Compression
{
"user": "Norberto",
"country": "Portugal",
"last_comment": "Iceland beat England :-)",
}
db.users.createIndex( {"country": 1} )
Australia-Zimbabwe
A-N N-Z
N-Q Q-Z…
record_id: 0x12311

50. WiredTiger/ Schema Design – Index Prefix Compression
{
"user": "Norberto",
"country": "Portugal",
"last_comment": "Iceland beat England :-)",
}
db.users.createIndex( {"country": 1} )
Australia-Zimbabwe
A-N N-Z
N-Q Q-Z…
{
key: "Por",
record_id: 0x12311
}
record_id: 0x12311
{
key: "Por",
record_id: 0x123BB
}
{
key: "Pol",
record_id: 0xF23CB
}

51. Picking a Storage
Engine Matters ?

52. In-place Updates
Memory
{
country: "Portugal",
star: "Cristiano"
}
{
country: "Iceland",
star: "Hannes Magnusson"
}
{
country: "Netherlands",
star: "Arthur Viegers"
}
{
country: "Portugal",
star: "Crestiano"
}

53. In-place Updates
Memory
{
country: "Portugal",
star: "Cristiano"
}
{
country: "Iceland",
star: "Hannes Magnusson"
}
{
country: "Netherlands",
star: "Arthur Viegers"
}
db.teams.update({country: "Portugal"},
{"$set": {
"star": "Cristiano Ronaldo"
}})
{
country: "Portugal",
star: "Cristiano Ronaldo"
}
MMAPv1

54. In-place Updates
Memory
{
country: "Portugal",
star: "Crestiano"
}
db.teams.update({country: "Portugal"},
{"$set": {
"star": "Cristiano Ronaldo"
}})
{
country: "Portugal",
star: "Cristiano Ronaldo"
}
WiredTiger
version 1
version 2

55. In-place Updates
Memory
{
country: "Portugal",
star: "Crestiano"
}
{
country: "Portugal",
star: "Cristiano Ronaldo"
}
WiredTiger
version 1version 2

56. Insert Heavy
server
db.pool.insert(
{
"subject": "Euro 2016",
"winner": "Portugal"
}
)
mongod

57. Insert Heavy
Server 1
mongod
db.pool.insert(
{
"subject": "Euro 2016",
"winner": "Portugal"
}
)
MMAPv1
Server 2
mongod
Server 3
mongod
Sharding

58. Insert Heavy
server
mongod
db.pool.insert(
{
"subject": "Euro 2016",
"winner": "Portugal"
}
)
mongod
mongod
MMAPv1
Micro-Sharding

59. https://www.mongodb.com/blog/post/mongodb-single-
platform-all-financial-data-ahl

60. Insert Heavy
server
db.pool.insert(
{
"subject": "Euro 2016",
"winner": "Portuaal"
}
)
mongod
WiredTiger
CPU availability

61. Insert Heavy
server
mongod
db.pool.insert(
{
"subject": "Euro 2016",
"winner": "Portuaal"
}
)
WiredTiger
server
mongod
server
mongod
Sharding

62. Buckets {
"product_id": "b872ad6e34f87...",
"visits":{
"store1": {
"Jan_31": 2823,
"Jan_30": 5535,
...
"total": 1222312
},
"store_2": {
"Jan_31": 2823,
"Jan_28": 5535,
...
"total": 1222312
},
}
}

63. Buckets {
"product_id": "b872ad6e34f87...",
"visits":{
"store1": {
"Jan_31": 2823,
"Jan_30": 5535,
...
"total": 1222312
},
"store_2": {
"Jan_31": 2823,
"Jan_28": 5535,
...
"total": 1222312
},
}
}
db.visits.update(
{"product_id": "b872ad6e34f87...."},
{"$inc": {
"store_2.March_19": 10,
"store_1.April_1": 68,
"stores.total": 78
}
)

64. Buckets {
"product_id": "b872ad6e34f87...",
"visits":{
"store1": {
"Jan_31": 2823,
"Jan_30": 5535,
"April_1": 10,
"total": 1222312
},
"store_2": {
"Jan_31": 2823,
"Jan_28": 5535,
"March_19": 68,
"total": 1222312
},
}
}
In-place update
MMAPv1

65. Buckets
{
"product_id": "b872ad6e34f87...",
"visits":{
"store1": {
"Jan_31": 2823,
"Jan_30": 5535,
...
"total": 1222312
},
"store_2": {
"Jan_31": 2823,
"Jan_28": 5535,
...
"total": 1222312
},
}
}
New version
{
"product_id": "b872ad6e34f87...",
"visits":{
"store1": {
"Jan_31": 2823,
"Jan_30": 5610,
"April_1": 10,
"total": 1222312
},
"store_2": {
"Jan_31": 2823,
"Jan_28": 5545,
"March_19": 68,
"total": 12229032
},
}
}
WiredTiger

66. Moving to WiredTiger

67. What to Look For
Bucketing Read/Write RatioIn-place Update

68. Update Process
• Apply changes to your schema design
• Check if there's any performance regression
• Make sure you have CPU resources available
• Swap secondary nodes
• Swap primary
• Enjoy the increased performance!

69. Example of Document Definition
• App1
- Realtime dashboard
- Ad hoc queries
- User profiles
• App2
- Heavy writes batch process
- Analytics workload
- Multi-tenant application

70. Example of Document Definition
• App1
- Realtime dashboard
- Ad hoc queries
- User profiles
• App2
- Heavy writes batch process
- Analytics workload
- Multi-tenant application
WiredTiger or MMAPv1

71. Example of Document Definition
• App1
- Realtime dashboard
- Ad hoc queries
- User profiles
• App2
- Heavy writes batch process
- Analytics workload
- Multi-tenant application
WiredTiger or MMAPv1 WiredTiger

72. Market Size
$36 Billion
Partners
1,000+
International Offices
15
Global Employees
575+
Downloads Worldwide
15,000,000+
Make a GIANT Impact
www.mongodb.com/careers
http://grnh.se/pj10su

73. https://university.mongodb.com/courses/M310/about
M310: MongoDB Security

74. Feel free to reach out!
Twitter: @nleite
norberto@mongodb.com
#mongodbeurope

75. Obrigado