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
October 18, 2011
Programming
16
30k
MongoDB for Analytics
Presented at Mongo Chicago 2011.
John Nunemaker
PRO
October 18, 2011
Tweet
Share
More Decks by John Nunemaker
See All by John Nunemaker
Atom
jnunemaker
PRO
10
4.2k
MongoDB for Analytics
jnunemaker
PRO
11
840
Addicted to Stable
jnunemaker
PRO
32
2.5k
MongoDB for Analytics
jnunemaker
PRO
21
2.2k
Why You Should Never Use an ORM
jnunemaker
PRO
55
9.2k
Why NoSQL?
jnunemaker
PRO
10
910
Don't Repeat Yourself, Repeat Others
jnunemaker
PRO
7
3.3k
I Have No Talent
jnunemaker
PRO
14
940
Why MongoDB Is Awesome
jnunemaker
PRO
18
4.4k
Other Decks in Programming
See All in Programming
Domain-Driven Transformation
hschwentner
2
1.9k
さいきょうのレイヤードアーキテクチャについて考えてみた
yahiru
3
750
SRE、開発、QAが協業して挑んだリリースプロセス改革@SRE Kaigi 2025
nealle
3
4.3k
Bedrock Agentsレスポンス解析によるAgentのOps
licux
3
840
CNCF Project の作者が考えている OSS の運営
utam0k
6
710
ASP. NET CoreにおけるWebAPIの最新情報
tomokusaba
0
370
法律の脱レガシーに学ぶフロントエンド刷新
oguemon
5
740
Immutable ActiveRecord
megane42
0
140
第3回関東Kaggler会_AtCoderはKaggleの役に立つ
chettub
3
1k
『品質』という言葉が嫌いな理由
korimu
0
160
TokyoR116_BeginnersSession1_環境構築
kotatyamtema
0
110
『GO』アプリ バックエンドサーバのコスト削減
mot_techtalk
0
140
Featured
See All Featured
KATA
mclloyd
29
14k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
33
2.1k
Designing on Purpose - Digital PM Summit 2013
jponch
117
7.1k
Code Reviewing Like a Champion
maltzj
521
39k
How To Stay Up To Date on Web Technology
chriscoyier
790
250k
Product Roadmaps are Hard
iamctodd
PRO
50
11k
Intergalactic Javascript Robots from Outer Space
tanoku
270
27k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
46
2.3k
Six Lessons from altMBA
skipperchong
27
3.6k
GitHub's CSS Performance
jonrohan
1030
460k
A Philosophy of Restraint
colly
203
16k
StorybookのUI Testing Handbookを読んだ
zakiyama
28
5.5k
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