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
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
John Nunemaker
PRO
November 13, 2012
Programming
11
1k
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
AI: The stuff that nobody shows you
jnunemaker
PRO
3
330
Atom
jnunemaker
PRO
10
4.6k
Addicted to Stable
jnunemaker
PRO
32
2.8k
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
9.7k
Why NoSQL?
jnunemaker
PRO
10
990
Don't Repeat Yourself, Repeat Others
jnunemaker
PRO
7
3.5k
I Have No Talent
jnunemaker
PRO
14
1k
Other Decks in Programming
See All in Programming
Agent Skills Workshop - AIへの頼み方を仕組み化する
gotalab555
12
6.8k
Package Management Learnings from Homebrew
mikemcquaid
0
280
AIに仕事を丸投げしたら、本当に楽になれるのか
dip_tech
PRO
0
160
個人開発は儲からない - それでも開発開始1ヶ月で300万円売り上げた方法
taishiyade
0
110
Premier Disciplin for Micro Frontends Multi Version/ Framework Scenarios @OOP 2026, Munic
manfredsteyer
PRO
0
190
朝日新聞のデジタル版を支えるGoバックエンド ー価値ある情報をいち早く確実にお届けするために
junkiishida
1
260
ノイジーネイバー問題を解決する 公平なキューイング
occhi
0
130
Ruby x Terminal
a_matsuda
4
370
PostgreSQL を使った快適な go test 環境を求めて
otakakot
0
320
DSPy入門 Pythonで実現する自動プロンプト最適化 〜人手によるプロンプト調整からの卒業〜
seaturt1e
1
270
AIコーディングの理想と現実 2026 | AI Coding: Expectations vs. Reality 2026
tomohisa
0
590
AI時代でも変わらない技術コミュニティの力~10年続く“ゆるい”つながりが生み出す価値
n_takehata
2
460
Featured
See All Featured
Money Talks: Using Revenue to Get Sh*t Done
nikkihalliwell
0
170
A Tale of Four Properties
chriscoyier
162
24k
Product Roadmaps are Hard
iamctodd
PRO
55
12k
Bridging the Design Gap: How Collaborative Modelling removes blockers to flow between stakeholders and teams @FastFlow conf
baasie
0
470
Measuring Dark Social's Impact On Conversion and Attribution
stephenakadiri
1
140
How to audit for AI Accessibility on your Front & Back End
davetheseo
0
200
Dealing with People You Can't Stand - Big Design 2015
cassininazir
367
27k
Docker and Python
trallard
47
3.7k
Agile that works and the tools we love
rasmusluckow
331
21k
For a Future-Friendly Web
brad_frost
183
10k
Leading Effective Engineering Teams in the AI Era
addyosmani
9
1.7k
Pawsitive SEO: Lessons from My Dog (and Many Mistakes) on Thriving as a Consultant in the Age of AI
davidcarrasco
0
77
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