1. Solutions Architect, MongoDB
Marc Schwering
#MongoDBBasics @MongoDB @m4rcsch
Applikationsentwicklung mit MongoDB
Interaktion mit der Datenbank

2. 2
• 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
Agenda

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

4. Recap from last time….

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

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

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

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

9. 9
Modeling Interactions
• Used for reporting on
articles
• Create “pre-
aggregated” reports
{
‘_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 }
}
}
Interactions collection
METHODS def add_interaction(article_id, type):

10. Inserting / Querying

11. 11
>db.articles.insert({
'text': 'Article content…’,
'date' : ISODate(...),
'title' : ’Intro to MongoDB’,
'author' : 'Dan Roberts’,
'tags' : [ 'mongodb',
'database',
'nosql’
]
});
• 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.
Inserting documents

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

13. 13
• Find returns a cursor
– Use to iterate over the results
– cursor has many methods
Cursors
>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’ ]
}

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

15. Updates

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

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

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

19. 19
Analytics – Pre-Aggregated reports
• Used for reporting on
articles
• Create “pre-
aggregated” reports
{
‘_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 }
}
}
Interactions collections
METHOD def add_interaction(article_id, type):

20. 20
• Use $inc to increment multiple counters.
• Single Atomic operation.
• Increment daily and hourly counters.
Incrementing Counters
>db.interactions.update(
{‘article_id’ : ObjectId(..)},
{
‘$inc’ : {
‘daily.views’:1,
‘daily.comments’:1
‘hours.8.views’:1
‘hours.8.comments’:1
}
)
{
‘_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. 21
• Increment new counters
Incrementing Counters 2
>db.interactions.update(
{‘article_id’ : ObjectId(..)},
{
‘$inc’ : {
‘daily.views’:1,
‘daily.comments’:1,
‘hours.8.views’:1,
‘hours.8.comments’:1,
‘referrers.bing’ : 1
}
)
{
‘_id’ : ObjectId(..),
‘article_id’ : ObjectId(..),
‘section’ : ‘schema’,
‘date’ : ISODate(..),
‘daily’: { ‘views’ : 45,
‘comments’ : 150 }
‘hours’ : {
…..
}
‘referrers’ : {
‘google’ : 27
}
}

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

23. Durability

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

25. 25
Unacknowledged

26. 26
MongoDB Acknowledged
Default Write Concern

27. 27
Wait for Journal Sync

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

29. 29
Wait for Replication

30. Summary

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

32. 32
– Indexing
• Indexing strategies
• Tuning Queries
– Text Search
– Geo Spatial
– Query Profiler
Next Session – in two weeks!

33. 33
• Public Training in Berlin 3-5 June:
http://bit.ly/MongoDBEssentialsBER14
• Meet me at Berlin-Buzzwords 26th June :
http://bit.ly/Marc_at_Buzz
• MongoDB World: http://bit.ly/MongoDB_World
Discount Code: 25MarcSchwering
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