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
1.1k
11
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
MongoDB for Analytics
Presented at MongoChicago on November 13, 2012.
John Nunemaker
PRO
November 13, 2012
More Decks by John Nunemaker
See All by John Nunemaker
Remote First: Building Distributed Teams that Win
jnunemaker
PRO
1
170
AI: The stuff that nobody shows you
jnunemaker
PRO
8
740
Atom
jnunemaker
PRO
10
5.1k
Addicted to Stable
jnunemaker
PRO
32
2.9k
MongoDB for Analytics
jnunemaker
PRO
21
2.3k
MongoDB for Analytics
jnunemaker
PRO
16
30k
Why You Should Never Use an ORM
jnunemaker
PRO
61
9.9k
Why NoSQL?
jnunemaker
PRO
10
1k
Don't Repeat Yourself, Repeat Others
jnunemaker
PRO
7
3.5k
Other Decks in Programming
See All in Programming
LaravelLive Japan の裏方のすべて — 第188回 PHP勉強会@東京 (2026-06-24)
suguruooki
2
130
Javaの型とAI時代に型が大事な理由 / java types and type in AI era
kishida
2
150
エージェンティックRAGにAWSで入門しよう!
har1101
9
1.8k
肥大化するレガシーコードに立ち向かうためのインターフェース分離と依存の逆転 / JJUG CCC 2026 Spring
hirokunimaeta
0
630
ECSアプリログをFireLensでコスト削減しようとしたけど諦めた話 in Fargate×Node.js
akihisaikeda
2
4.2k
生成AI時代にこそ効くGo | Why Go Works in the Age of Generative AI
mom0tomo
8
3.3k
ランチタイムLT会3周年!ランチタイムLT会を3年間続けられたお話
y0hgi
1
110
Webフレームワークの ベンチマークについて
yusukebe
0
180
決定論的オーケストレーションの設計と実装 / Design and Implementation of Deterministic Orchestration
nrslib
4
1.5k
過去最大のMCPアップデート! 2026-07-28 RC版の謎に迫る
licux
6
400
Creating Composable Callables in Contemporary C++
rollbear
0
170
フロントエンドとバックエンドで「1文字」を揃えよう
youkidearitai
PRO
0
750
Featured
See All Featured
Organizational Design Perspectives: An Ontology of Organizational Design Elements
kimpetersen
PRO
1
750
What’s in a name? Adding method to the madness
productmarketing
PRO
24
4.1k
Building Experiences: Design Systems, User Experience, and Full Site Editing
marktimemedia
0
540
Optimising Largest Contentful Paint
csswizardry
37
3.7k
SEO for Brand Visibility & Recognition
aleyda
0
4.6k
The World Runs on Bad Software
bkeepers
PRO
72
12k
Taking LLMs out of the black box: A practical guide to human-in-the-loop distillation
inesmontani
PRO
3
2.3k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
55k
ReactJS: Keep Simple. Everything can be a component!
pedronauck
666
130k
Highjacked: Video Game Concept Design
rkendrick25
PRO
1
400
Speed Design
sergeychernyshev
33
1.9k
Being A Developer After 40
akosma
91
590k
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