The third session in our eight-part webinar series on "Building an application with MongoDB" to learn best practices, tips and tricks from our Solution Architects and learn how easy it is to start building applications with MongoDB. This session - presented by Daniel Roberts, Solutions Architect at MongoDB - discusses queries and updates and the interaction between an application and a database. Next in the Series: March 6th 2014 - Build an Application Series - Session 4 - Indexing This session will focus on indexing strategies for the application, including geo spatial and full text search March 20th 2014 - Build an Application Series - Session 5 - Reporting in your application This session covers Reporting and Aggregation Framework and Building application usage reports April 3th 2014 - Operations for your application - Session 6 - Deploying the application By this stage, we will have built the application. Now we need to deploy it. We will discuss architecture for High Availability and scale out April 17th 2014 - Operations for your application - Session 7 - Backup and DR This webinar will discuss back up and restore options. Learn what you should do in the event of a failure and how to perform a backup and recovery of the data in your applications May 6th 2014 - Operations for your application - Session 8 - Monitoring and Performance Tuning The final webinar of the series will discuss what metrics are important and how to manage and monitor your application for key performance. Daniel Roberts: About the speaker Daniel Roberts is a Solutions Architect based in London. Prior to MongoDB Daniel worked at Oracle for 11 years in a number of different positions, including Oracle's middleware technologies and strategy. Prior roles include consulting, product management, business development and more recently as a solution architect for financial services. Daniel has also worked for Novell, ICL and as a freelance contractor. He has a degree in Computer Science from Nottingham Trent University in the UK.

1. Application Development Series
Back to Basics
Interacting with the database
Daniel Roberts
@dmroberts
#MongoDBBasics

2. Agenda
• Recap from last session
• MongoDB Inserts & Queries
– ObjectId
– Returning documents – cursors
– Projections
• MongoDB Update operators
– Fixed Buckets
– Pre Aggregated Reports
• Write Concern
– Durability vs Performance trade off
2

3. Q&A
• Virtual Genius Bar
– Use the chat to post
questions
– EMEA Solution
Architecture / Support
team are on hand
– Make use of them
during the sessions!!!
3

4. Recap from last time….

5. Architecture
• Looked at the application architecture
– JSON / RESTful
– Python based
HTTP(S) REST
Client-side
JSON
Python web
app
(BSON)
(eg AngularJS)
Pymongo driver
5

6. Schema and Architecture
• Schema design
– Modeled
•
•
•
•
6
Articles
Comments
Interactions
Users

7. Modeling Articles
Articles collection
def get_article(article_id)
def get_articles():
def create_article():
METHODS
{
'_id' :
'text':
• Posting articles
•
'Article content…',
'date' : ISODate(...),
insert
'title' :
• Get List of articles
•
ObjectId(...),
‟Intro to MongoDB',
'author' : 'Dan Roberts',
Return Cursor
'tags' :
• Get individual article
[
]
}
7
'mongodb',
'database',
'nosql‟

8. Modeling Comments
Comments collection
METHODS
def add_comment(article_id):
def get_comments(article_id):
{
• Storing comments
• Quickly retrieve most
recent comments
• Add new comments
to document
• „Bucketing‟
8
„_id‟ : ObjectId(..),
„article_id‟ : ObjectId(..),
„page‟ : 1,
„count‟ : 42
„comments‟ : [
{
„text‟ : „A great
article, helped me understand
schema design‟,
„date‟ : ISODate(..),
„author‟ : „johnsmith‟
},
…
}

9. Modeling Interactions
Interactions collection
METHODS
def add_interaction(article_id, type):
{
„_id‟ : ObjectId(..),
„article_id‟ : ObjectId(..),
„section‟ : „schema‟,
„date‟ : ISODate(..),
„daily‟: { „views‟ : 45,
„comments‟ : 150 }
„hours‟ : {
0:{
„views‟ : 10 },
1:{
„views‟ : 2 },
…
23 : { „views‟ : 14,
„comments‟ : 10 }
}
• Used for reporting on
articles
• Create “preaggregated” reports
}
9

10. Inserting / Querying

11. Inserting documents
• Driver generates ObjectId() for _id
– if not specified
– 12 bytes - 4-byte
epoch, 3-byte machine id, a 2-byte process id, and a 3-byte
counter.
>db.articles.insert({
'text':
'Article content…‟,
'date' :
ISODate(...),
'title' :
‟Intro to MongoDB‟,
'author' : 'Dan Roberts‟,
'tags' :
[
'mongodb',
'database',
'nosql‟
]
});
11

12. Comparison Operators
$gt, $gte, $in, $lt, $lte, $ne, $nin
• Use to query documents
db.articles.find( { 'title' : ‟Intro to MongoDB‟ } )
db.articles.find( { ‟date' : { „$lt‟ :
{ISODate("2014-02-19T00:00:00.000Z") }} )
db.articles.find( { „tags‟ : { „$in‟ : [„nosql‟, „database‟] } } );
•
Logical: $or, $and, $not, $nor
•
Evaluation: $mod, $regex, $where Geospatial: $geoWithin, $geoIntersects, $near, $nearSphere
12
Element: $exists, $type

13. Cursors
• Find returns a cursor
– Use to iterate over the results
– cursor has many methods
>var cursor = db.articles.find (
{ ‟author' : ‟Dan Roberts‟ }
>cursor.hasNext()
true
>cursor.next()
{
'_id' :
ObjectId(...),
'text':
'Article content…‟,
'date' : ISODate(...),
'title' : ‟Intro to MongoDB‟,
'author' : 'Dan Roberts‟,
'tags' : [
'mongodb', 'database‟, 'nosql’
]
}
13
)

14. Projections
• Return only the attributes needed
– Boolean 0 or 1 syntax select attributes
– Improved efficiency
>var cursor = db.articles.find( { ‟author' : ‟Dan Roberts‟ } , {‘_id’:0, ‘title’:1})
>cursor.hasNext()
true
>cursor.next()
{ "title" : "Intro to MongoDB" }
14

15. Updates

16. Update Operators
$each, $slice, $sort, $inc, $push
$inc, $rename, $setOnInsert, $set, $unset, $max, $min
$, $addToSet, $pop, $pullAll, $pull, $pushAll, $push
$each, $slice, $sort
>db.articles.update(
{
{ '_id' : ObjectId(...)},
{ '$push' :
{'comments' : „Great
article!’ }
}
)
16
}
'text':
'Article content…‟
'date' :
ISODate(...),
'title' :
‟Intro to MongoDB‟,
'author' : 'Dan Roberts‟,
'tags' :
['mongodb',
'database‟,'nosql’ ],
’comments' :
[‘Great article!’ ]

17. Update Operators
Push to a fixed size array with…
$push, $each, $slice
{
>db.articles.update(
{ '_id' : ObjectId(...)},
{ '$push' : {'comments' :
{
'$each' : [„Excellent‟],
'$slice' : -3}},
})
17
}
'text':
'Article content…‟
'date' :
ISODate(...),
'title' :
‟Intro to MongoDB‟,
'author' : 'Dan Roberts‟,
'tags' :
['mongodb',
'database‟,'nosql’ ],
’comments' :
[‘Great
article!’, ‘More
please’, ‘Excellent’ ]

18. Update Operators - Bucketing
•
Push 10 comments to a document (bucket).
•
Automatically create a new document.
•
Use {upsert: true} instead of insert.
>db.comments.update(
{„c‟: {„$lt‟:10}},
{
„$inc‟ : {c:1},
'$push' : {
'comments' :
„Excellent‟
}
},
{ upsert : true }
)
18
{
„_id‟ : ObjectId( … )
„c‟ : 3,
’comments' :
[‘Great article!’,
‘More please’,
‘Excellent’ ]
}

19. Analytics – Pre-Aggregated reports
Interactions collections
METHOD
def add_interaction(article_id, type):
{
„_id‟ : ObjectId(..),
„article_id‟ : ObjectId(..),
„section‟ : „schema‟,
„date‟ : ISODate(..),
„daily‟: { „views‟ : 45,
„comments‟ : 150 }
„hours‟ : {
0:{
„views‟ : 10 },
1:{
„views‟ : 2 },
…
23 : { „views‟ : 14,
„comments‟ : 10 }
}
• Used for reporting on
articles
• Create “preaggregated” reports
}
19

20. Incrementing Counters
•
Use $inc to increment multiple counters.
•
Single Atomic operation.
•
Increment daily and hourly counters.
{
>db.interactions.update(
{„article_id‟ : ObjectId(..)},
{
„$inc‟ : {
„daily.views‟:1,
„daily.comments‟:1
„hours.8.views‟:1
„hours.8.comments‟:1
}
)
}
20
„_id‟ : ObjectId(..),
„article_id‟ : ObjectId(..),
„section‟ : „schema‟,
„date‟ : ISODate(..),
„daily‟: { „views‟ : 45,
„comments‟ : 150 }
„hours‟ : {
0:{
„views‟ : 10 },
1:{
„views‟ : 2 },
…
23 : { „views‟ : 14,
„comments‟ : 10 }
}

21. Incrementing Counters 2
• Increment new counters
{
„_id‟ : ObjectId(..),
„article_id‟ : ObjectId(..),
„section‟ : „schema‟,
„date‟ : ISODate(..),
„daily‟: { „views‟ : 45,
„comments‟ : 150 }
„hours‟ : {
…..
}
„referrers‟ : {
„google‟ : 27
}
>db.interactions.update(
{„article_id‟ : ObjectId(..)},
{
„$inc‟ : {
„daily.views‟:1,
„daily.comments‟:1,
„hours.8.views‟:1,
„hours.8.comments‟:1,
‘referrers.bing’ : 1
}
)
21
}

22. Incrementing Counters 2
• Increment new counters
{
„_id‟ : ObjectId(..),
„article_id‟ : ObjectId(..),
„section‟ : „schema‟,
„date‟ : ISODate(..),
„daily‟: { „views‟ : 45,
„comments‟ : 150 }
„hours‟ : {
…..
}
„referrers‟ : {
„google‟ : 27,
‘bing’ : 1
}
>db.interactions.update(
{„article_id‟ : ObjectId(..)},
{
„$inc‟ : {
„daily.views‟:1,
„daily.comments‟:1,
„hours.8.views‟:1,
„hours.8.comments‟:1,
‘referrers.bing’ : 1
}
)
}
22

23. Durability

24. Durability
•
With MongoDB you get to choose
•
•
•
•
Write Concerns
•
•
•
Report on success of write operations
getLastError called from driver
Trade off
•
24
In memory
On disk
Multiple servers
Latency of response

25. Unacknowledged
25

26. MongoDB Acknowledged
Default Write Concern
26

27. Wait for Journal Sync
27

28. Replica Sets
• Replica Set – two or more copies
• “Self-healing” shard
• Addresses many concerns:
- High Availability
- Disaster Recovery
- Maintenance
28

29. Wait for Replication
29

30. Summary

31. Summary
• Interacting with the database
– Queries and projections
– Inserts and Upserts
– Update Operators
– Bucketing
– Pre Aggregated reports
• basis for fast analytics
31

32. Next Session – 6th March
– Indexing
• Indexing strategies
• Tuning Queries
– Text Search
– Geo Spatial
– Query Profiler
32