Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
MongoDB for Analytics - John Nunemaker, Ordered...
Search
mongodb
November 01, 2011
Technology
7.7k
9
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
MongoDB for Analytics - John Nunemaker, Ordered List
MongoChicago 2011
mongodb
November 01, 2011
More Decks by mongodb
See All by mongodb
NoSQL Now! 2012
mongodb
18
3.4k
MongoDB 2.2 At the Silicon Valley MongoDB User Group
mongodb
9
1.5k
Turning off the LAMP Hunter Loftis, Skookum Digital Works
mongodb
2
1.6k
Mobilize Your MongoDB! Developing iPhone and Android Apps in the Cloud Grant Shipley, Red Hat
mongodb
0
590
Beanstalk Data - MongoDB In Production Chris Siefken, CTO Beanstalk Data
mongodb
0
600
New LINQ support in C#/.NET driver Robert Stam, 10gen
mongodb
9
41k
Welcome and Keynote Aaron Heckman, 10gen
mongodb
0
560
Webinar Introduction to MongoDB's Java Driver
mongodb
1
1.3k
Webinar Intro to Schema Design
mongodb
4
1.9k
Other Decks in Technology
See All in Technology
3つのアプローチで目指す チームを強くするAI駆動開発
thkt
0
150
Claude Code本は、どのように執筆チームで書かれたか
oikon48
1
360
おそらく日本で唯一のDevRelインターン生として
husengs7
0
170
AIがコードを書く時代に、エンジニアは何で自分の価値を証明するのか / In an era where AI writes code how do engineers prove their value
carta_engineering
2
830
AIに攻撃される前に、AIに攻撃させる
tsuchikazu
0
170
LLM機能を自作して分かるSnowflake Cortex AIの強み
nayuts
0
360
宣言型部分更新は何を解決しどこへ向かうのか
shuta13
0
310
Post AI時代のリファクタリング実践記 / Refactoring in the post AI era
kaminashi
1
110
事業活動を AI Ready にする攻めと守りのデータエンジニアリング / data-engineering-for-ai-ready-business
pei0804
7
2.5k
"優秀な誰か"の下位互換にならないために
yut0naga1_fa
1
1.7k
【Data Engineering Summit2026_登壇資料】医療ビッグデータ×AIエージェントを支えるデータ基盤とハーネスエンジニアリング
jmdc_presentation
0
100
SREでアラート疲れを 解決しよう!
kairim0
1
220
Featured
See All Featured
Bootstrapping a Software Product
garrettdimon
PRO
306
120k
Why Your Marketing Sucks and What You Can Do About It - Sophie Logan
marketingsoph
0
430
Building Better People: How to give real-time feedback that sticks.
wjessup
370
20k
Lightning talk: Run Django tests with GitHub Actions
sabderemane
0
300
Mind Mapping
helmedeiros
1
400
Performance Is Good for Brains [We Love Speed 2024]
tammyeverts
12
1.9k
YesSQL, Process and Tooling at Scale
rocio
174
15k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
37
6.6k
BBQ
matthewcrist
90
10k
Accessibility Awareness
sabderemane
1
240
We Are The Robots
honzajavorek
0
390
Git: the NoSQL Database
bkeepers
PRO
433
67k
Transcript
Ordered List John Nunemaker MongoChi 2011 October 18, 2011 MongoDB
for Analytics A loving conversation with @jnunemaker
Background As presented through interpretive dance
None
None
None
~1 month Of evenings and weekends
~4 dog years Since public launch
~6 tiny servers 2 web, 2 app, 2 db
~1-2 Million Page views per day
None
None
Implementation Imma show you how we do what we do
baby
Doing It Live No aggregate querying
get('/track.gif') do Hit.record(...) TrackGif end
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
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' => "#{site_id}:#{hash}"}
Reads [['sid', 1], ['v', -1]]
Growth The best laid plans of mice and men
Partition Hot Data Currently using collections for time frames
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
Ordered List Thank you!
[email protected]
John Nunemaker MongoChi 2011 October
18, 2011 @jnunemaker