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
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
150
AI: The stuff that nobody shows you
jnunemaker
PRO
7
670
Atom
jnunemaker
PRO
10
5.1k
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
9.9k
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
New "Type" system on PicoRuby
pocke
1
390
Talking to terminals (and how they talk back) (KotlinConf 2026)
jakewharton
PRO
1
160
tsserverとは何だったのか、これからどうなるのか
nowaki28
1
430
Lemonade + Foundry Toolkit でお手軽アプリ開発
seosoft
1
250
新規プロダクトを高速で生み出すハーネスエンジニアリング
seanchas116
18
7.6k
不変条件と整合性境界—ビジネスが決める設計判断と実現パターン / Invariants and Consistency Boundaries
nrslib
11
3.1k
AIとRubyの静的型付け
ukin0k0
0
480
TSKaigi2026-静的解析への投資がAI時代のコード品質を支える ── カスタムESLintルールの設計と運用
hayatokudou
7
1.3k
AI時代のUIはどこへ行く?その2!
yusukebe
15
4.8k
さぁV100、メモリをお食べ・・・
nilpe
0
120
技術記事、AIに書かせるか、自分で書くか? 〜それでも私が自分の手で書く理由〜 / #QiitaConference
jnchito
2
1.2k
誰も頼んでない機能を出荷した話
zekutax
0
150
Featured
See All Featured
How GitHub (no longer) Works
holman
316
150k
Build The Right Thing And Hit Your Dates
maggiecrowley
39
3.2k
Sam Torres - BigQuery for SEOs
techseoconnect
PRO
0
280
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
37
6.5k
The MySQL Ecosystem @ GitHub 2015
samlambert
251
13k
Cheating the UX When There Is Nothing More to Optimize - PixelPioneers
stephaniewalter
287
14k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
How to Ace a Technical Interview
jacobian
281
24k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
49
3.4k
コードの90%をAIが書く世界で何が待っているのか / What awaits us in a world where 90% of the code is written by AI
rkaga
61
44k
How to Build an AI Search Optimization Roadmap - Criteria and Steps to Take #SEOIRL
aleyda
1
2.1k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
25
1.9k
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