Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
MongoDB for Analytics
Search
John Nunemaker
PRO
November 13, 2012
Programming
10
800
MongoDB for Analytics
Presented at MongoChicago on November 13, 2012.
John Nunemaker
PRO
November 13, 2012
Tweet
Share
More Decks by John Nunemaker
See All by John Nunemaker
Atom
jnunemaker
PRO
9
4.1k
Addicted to Stable
jnunemaker
PRO
32
2.4k
MongoDB for Analytics
jnunemaker
PRO
21
2.2k
MongoDB for Analytics
jnunemaker
PRO
16
30k
Why You Should Never Use an ORM
jnunemaker
PRO
54
9.1k
Why NoSQL?
jnunemaker
PRO
10
890
Don't Repeat Yourself, Repeat Others
jnunemaker
PRO
7
3.3k
I Have No Talent
jnunemaker
PRO
14
920
Why MongoDB Is Awesome
jnunemaker
PRO
18
4.3k
Other Decks in Programming
See All in Programming
AWS Lambdaから始まった Serverlessの「熱」とキャリアパス / It started with AWS Lambda Serverless “fever” and career path
seike460
PRO
1
260
Enabling DevOps and Team Topologies Through Architecture: Architecting for Fast Flow
cer
PRO
0
330
レガシーシステムにどう立ち向かうか 複雑さと理想と現実/vs-legacy
suzukihoge
14
2.2k
TypeScript Graph でコードレビューの心理的障壁を乗り越える
ysk8hori
2
1.1k
3rd party scriptでもReactを使いたい! Preact + Reactのハイブリッド開発
righttouch
PRO
1
600
距離関数を極める! / SESSIONS 2024
gam0022
0
280
[Do iOS '24] Ship your app on a Friday...and enjoy your weekend!
polpielladev
0
110
よくできたテンプレート言語として TypeScript + JSX を利用する試み / Using TypeScript + JSX outside of Web Frontend #TSKaigiKansai
izumin5210
6
1.7k
NSOutlineView何もわからん:( 前編 / I Don't Understand About NSOutlineView :( Pt. 1
usagimaru
0
340
cmp.Or に感動した
otakakot
3
180
役立つログに取り組もう
irof
28
9.6k
みんなでプロポーザルを書いてみた
yuriko1211
0
260
Featured
See All Featured
The Invisible Side of Design
smashingmag
298
50k
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
42
9.2k
How to Think Like a Performance Engineer
csswizardry
20
1.1k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
126
18k
Documentation Writing (for coders)
carmenintech
65
4.4k
A Modern Web Designer's Workflow
chriscoyier
693
190k
Designing Experiences People Love
moore
138
23k
How STYLIGHT went responsive
nonsquared
95
5.2k
Put a Button on it: Removing Barriers to Going Fast.
kastner
59
3.5k
Mobile First: as difficult as doing things right
swwweet
222
8.9k
Intergalactic Javascript Robots from Outer Space
tanoku
269
27k
Thoughts on Productivity
jonyablonski
67
4.3k
Transcript
GitHub John Nunemaker MongoChicago 2012 November 12, 2012 MongoDB for
Analytics A loving conversation with @jnunemaker
Background How hernias can be good for you
None
None
1 month Of evenings and weekends
18 months Since public launch
10-15 Million Page views per day
2.7 Billion Page views to date
13 tiny servers 2 web, 6 app, 3 db, 2
queue
requests/sec
ops/sec
cpu %
lock %
Implementation How we do what we do
Doing It (mostly) Live No aggregate querying
None
None
get('/track.gif') do track_service.record(...) TrackGif end
class TrackService def record(attrs) message = MessagePack.pack(attrs) @client.set(@queue, message) end
end
class TrackProcessor def run loop { process } end def
process record @client.get(@queue) end def record(message) attrs = MessagePack.unpack(message) Hit.record(attrs) end end
http://bit.ly/rt-kestrel
class Hit def record site.atomic_update(site_updates) Resolution.record(self) Technology.record(self) Location.record(self) Referrer.record(self) Content.record(self)
Search.record(self) Notification.record(self) View.record(self) end end
class Resolution def record(hit) query = {'_id' => "..."} update
= {'$inc' => {}} update['$inc']["sx.#{hit.screenx}"] = 1 update['$inc']["bx.#{hit.browserx}"] = 1 update['$inc']["by.#{hit.browsery}"] = 1 collection(hit.created_on) .update(query, update, :upsert => true) end end end
Pros
Pros Space
Pros Space RAM
Pros Space RAM Reads
Pros Space RAM Reads Live
Cons
Cons Writes
Cons Writes Constraints
Cons Writes Constraints More Forethought
Cons Writes Constraints More Forethought No raw data
http://bit.ly/rt-counters http://bit.ly/rt-counters2
Time Frame Minute, hour, month, day, year, forever?
# of Variations One document vs many
Single Document Per Time Frame
None
{ "t" => 336381, "u" => 158951, "2011" => {
"02" => { "18" => { "t" => 9, "u" => 6 } } } }
{ '$inc' => { 't' => 1, 'u' => 1,
'2011.02.18.t' => 1, '2011.02.18.u' => 1, } }
Single Document For all ranges in time frame
None
{ "_id" =>"...:10", "bx" => { "320" => 85, "480"
=> 318, "800" => 1938, "1024" => 5033, "1280" => 6288, "1440" => 2323, "1600" => 3817, "2000" => 137 }, "by" => { "480" => 2205, "600" => 7359,
"600" => 7359, "768" => 4515, "900" => 3833, "1024"
=> 2026 }, "sx" => { "320" => 191, "480" => 179, "800" => 195, "1024" => 1059, "1280" => 5861, "1440" => 3533, "1600" => 7675, "2000" => 1279 } }
{ '$inc' => { 'sx.1440' => 1, 'bx.1280' => 1,
'by.768' => 1, } }
Many Documents Search terms, content, referrers...
None
[ { "_id" => "<oid>:<hash>", "t" => "ruby class variables",
"sid" => BSON::ObjectId('<oid>'), "v" => 352 }, { "_id" => "<oid>:<hash>", "t" => "ruby unless", "sid" => BSON::ObjectId('<oid>'), "v" => 347 }, ]
Writes {'_id' => "#{sid}:#{hash}"}
Reads [['sid', 1], ['v', -1]]
Growth Don’t say shard, don’t say shard...
Partition Hot Data Currently using collections for time frames
[ "content.2011.7", "content.2011.8", "content.2011.9", "content.2011.10", "content.2011.11", "content.2011.12", "content.2012.1", "content.2012.2", "content.2012.3",
"content.2012.4", ]
[ "resolutions.2011", "resolutions.2012", ]
Move
Move BigintMove
Move BigintMove MakeYouWannaMove
Move BigintMove MakeYouWannaMove DaMove
Move BigintMove MakeYouWannaMove DaMove SmoothMove
Move BigintMove MakeYouWannaMove DaMove SmoothMove NightMove
Move BigintMove MakeYouWannaMove DaMove SmoothMove NightMove DanceMove
Bigger, Faster Server More CPU, RAM, Disk Space
Users Sites Content Referrers Terms Engines Resolutions Locations Users Sites
Content Referrers Terms Engines Resolutions Locations
Partition by Function Spread writes across a few servers
Users Sites Content Referrers Terms Engines Resolutions Locations
Partition by Server Spread writes across a ton of servers,
way down the road, not worried yet
GitHub Thank you!
[email protected]
John Nunemaker MongoChicago 2012 November 12,
2012 @jnunemaker