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
広告配信サーバーと広告配信比率最適化問題
Search
Ken Wagatsuma
February 10, 2018
Technology
1.1k
1
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
広告配信サーバーと広告配信比率最適化問題
Lightening Talk at
https://techconf.cookpad.com/2018/
Ken Wagatsuma
February 10, 2018
More Decks by Ken Wagatsuma
See All by Ken Wagatsuma
Pregel Graph Compute Engines - Supersteps Exampls
kenju
0
270
Kafka on Kubernetes with Strimzi
kenju
0
230
AWS DynamoDB Accelerator (DAX) 101
kenju
2
7.4k
Moden browser introduction
kenju
1
490
Cookpad summer internship 2019 - API
kenju
0
11k
Introduction to Design Patterns
kenju
0
170
GraphQL Asia 2019 "Re-architecture of a decade-old app with BFF/GraphQL"
kenju
0
9.4k
Introduction to TypeScript
kenju
0
820
Introduction to Programmatic Ad
kenju
0
320
Other Decks in Technology
See All in Technology
DevelopersIO 2026 Tokyo 現時点の衛星通信サービスの現状を整理してみる
maroon1st
0
140
Railsで挑む大量データ永続化 〜600億件を永続化するための設計とボトルネックとの戦い〜
occhi
1
1k
Turning Repos into the Product Second Brain with an LLM Wiki
linedevth
0
130
ストレスなくAIと付き合いたい!こんなときどうしてる?
namiki64
4
660
FinOps Agentが生んだ技術負債:コスト自動調査の落とし穴と解消までの道のり
oasis1994liveforever
3
250
アカウント統制の健康診断
kenichinakamura
1
110
企画を Software Factory-ready にする——開発が高速になったとき、PdMの仕事はどう変わったか
yachibit
1
130
小規模OSSモデルは サイバーセキュリティ業務に どこまで使えるか
bbrbbq
0
170
古い指輪から広がった JAVA コミュニティ とのつながり
yamad
0
140
野良MCPサーバーを排除せよ!MCPサーバーのガバナンス
yukiogawa
1
150
Tofu-Controller lightning talk @ Containerday 2026
gionn
0
170
What Is JetBrains Air
x5gtrn
PRO
0
140
Featured
See All Featured
Navigating Weather and Climate Data
rabernat
0
560
More Than Pixels: Becoming A User Experience Designer
marktimemedia
3
570
職位にかかわらず全員がリーダーシップを発揮するチーム作り / Building a team where everyone can demonstrate leadership regardless of position
madoxten
69
67k
A brief & incomplete history of UX Design for the World Wide Web: 1989–2019
jct
2
540
Code Reviewing Like a Champion
maltzj
529
40k
Tips & Tricks on How to Get Your First Job In Tech
honzajavorek
1
810
Practical Orchestrator
shlominoach
192
12k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
46
3k
Avoiding the “Bad Training, Faster” Trap in the Age of AI
tmiket
0
280
The SEO identity crisis: Don't let AI make you average
varn
0
590
Jamie Indigo - Trashchat’s Guide to Black Boxes: Technical SEO Tactics for LLMs
techseoconnect
PRO
0
710
Java REST API Framework Comparison - PWX 2021
mraible
34
9.8k
Transcript
ࠂ৴αʔόʔͱ ࠂ৴ൺ࠷దԽ ϝσΟΞϓϩμΫτ։ൃ෦ ,FOKV8BHBUTVNB
8IP Kenju Wagatsuma (github.com/kenju) • ϝσΟΞϓϩμΫτ։ൃ෦ • αʔόʔαΠυΤϯδχΞ • ͖ͳͷɿRuby,
ίʔώʔ, ϩδΧϧΫοΩϯά • ݏ͍ͳͷɿ1ϲ݄લʹॻ͍ͨࣗͷίʔυ
ϝσΟΞϓϩμΫτ։ൃ෦ ୲αʔϏεɿ ࠂ৴, storeTV, cookpadTV, OEM, ͦͷଞଟ ࢀߟɿ ։ൃऀϒϩάʰΫοΫύουͷࠂΤϯδχΞԿΛ ͍ͬͯΔͷ͔ʱ
ຊ͍ͨ͜͠ͱɻ ϝσΟΞϓϩμΫτ։ൃ෦Ͱ ͲΜͳϓϩδΣΫτΛ͍ͬͯΔͷ͔ʁ
νʔϜʹೖͬͯϲ݄ޙʹऔΓΜͩϓϩδΣΫτ ΫοΫύουͷࠂ৴αʔόʔʹ͓͚Δ ࠂ৴ൺͷࣗಈ࠷దԽϓϩδΣΫτɻ
ݫ͍͠εέδϡʔϧ • ϝσΟΞϓϩμΫτ։ൃ෦δϣΠϯ - 10݄த० • ͓खฒΈഈݟϓϩδΣΫτ - ~11݄த० •
৴࠷దԽτϥΠΞϧ - 12/4(݄) 10:00 - 12/11(݄) 10:00 ???
ղܾ͍ͨ͠՝ • ʑͷखӡ༻ʹΑΔνϡʔχϯά͕ඞཁ - => ࡞ۀ͕ൃੜ • ӡ༻ऀͷܦݧͱצʹཔͬͨνϡʔχϯά - =>
ҟಈ࣌ಋೖ࣌ͷίετ͕ߴա͗ • ࠷దͳࡏݿൺΛࣗಈͰௐͰ͖ͳ͍ - => ࠂܝग़ͷػձଛࣦ
Ͳ͏ղܾ͢Δ͔ • ࡏݿׂྔͱ࣮͔Β࠷దͳ৴ൺͷิ ਖ਼Λߦ͏ - ΠϯϓϨογϣϯϕʔε͔ΒΫϦοΫϕʔεͷ৴ - ΫϦοΫ༧ଌΛར༻ͨ͠ൺͷࣗಈ࠷దԽ - ϦΞϧλΠϜूܭσʔλΛ׆༻ͨ͠ΞʔΩςΫνϟ
‣ Lambda Architecture ʹ͓͚Δ Speed Layer
l4QFFE-BZFSzPO"84 • Kinesis, DynamoDB, Lambda Λ׆༻ͨ͠ Speed Layer (from Lambda
Architecture) • طଘͷετϦʔϜʹɺΫ ϦοΫܭࢉϨΠϠʔΛ Ճ͚ͨͩ͠ = ઌਓͷݞ ʹΔ
ৄ͍ͪ͜͠Β ࢀߟɿ ʰCookpad Tech Kitchen #9 ʙ1ߦͷϩάͷ͜͏ ଆʙ Λ։࠵͠·ͨ͠ʂʱ
ΫϦοΫ༧ଌ͍͠ʂʂʂ • ޯϒʔεςΟϯάܾఆʢGBDTʣΛ༻͍ͨࠂ͝ͱͷΫϦοΫ༧ଌ - Facebook https://code.facebook.com/posts/975025089299409/evaluating-boosted-decision-trees-for-billions-of-users - SmartNews https://speakerdeck.com/komiya_atsushi/gbdt-niyorukuritukulu-yu-ce-wogao-su-hua-sitai-number-oresikanaito-vol-dot-4 •
ଟόϯσΟοτͷҰछͰ͋ΔMortal Multi-Armed BanditsͷԠ༻ - Voyage Group http://techlog.voyagegroup.com/entry/2015/04/03/114547ɹ • Neural Networkͷ૯߹֨ಆٕʢ͕͢͞Googleʣ - Google http://www.eecs.tufts.edu/~dsculley/papers/ad-click-prediction.pdfɹ • ৴པͱ࣮ͷϩδεςΟοΫճؼʢୠܻ͕͠ԯϨϕϧʣ - Criteo http://olivier.chapelle.cc/pub/ngdstone.pdfɹ
ؒʹ߹Θͳ͍ʂ • τϥΠΞϧͳΜͱͯ͠ʹ࣮ࢪ͍ͨ͠ - վળͷαΠΫϧΛճͨ͢Ί • QCDͰݴ͏ͳΒɺDelivery, QualityΛ༏ઌ - ͳΜͱͯؒ͠ʹ߹Θ͍ͤͨʂ
• ࠷ॳ͔Βᘳͳਫ਼༧ଌ·ͣෆՄೳ - ػցֶशͰղܾ͠ͳͯ͘Α͍͔·ͣߟ͑Δ - ࢀߟɿʰࣄͰ͡ΊΔػցֶशʱ
ҠಈฏۉԞ͕ਂ͍ • SMA (Simple Moving Average) = ۙ N ݸͷॏΈ͚ͷͳ͍୯७ͳฏۉ
• WMA (Weighted Moving Average) = ΑΓ࠷ۙͷσʔλʹॏΈ͚ • EWMA (Exponentially Weighted Moving Average) = ࢦؔతʹॏΈ͚ • MMA (Modified Moving Average) = EWMAͷѥछ ଞʹTriangle MA, Sine Weighted MA, KZ Filtering,...etc ࢀߟɿhttps://en.wikipedia.org/wiki/Moving_average#Simple_moving_averag
աڈϩάΛݩʹΞϧΰϦζϜͷਫ਼Λੳ • Jupyter Notebook / Python - ࢀߟɿ։ൃऀϒϩάʰRailsΤϯ δχΞʹཱͭJupyter Notebook
ͱiRubyʱ • ൺֱͨ͠ΞϧΰϦζϜ - Total Average - Cumulative Average - Simple Moving Average (3 Hours) - Simple Moving Average (6 Hours)
τϥΠΞϧ݁Ռ • ิਖ਼ͷϩδοΫʹ՝ ͕ݟ͔ͭͬͨ ͷɺτϥΠΞϧͱ͠ ͯޭ
ظతνϡʔχϯά • Speed Layer ͷ࠶ઃܭɾຏ͖ࠐΈ - ετϦʔϜॲཧʹԊͬͨσʔλͷྲྀΕ • ෛ࠴ =
ະୡ ΛՃຯͨ͠ϩδοΫ - ୈҰ࣍τϥΠΞϧΛ͍ͬͯͳ͔ͬͨΒݟ͑ͳ͔ͬͨ՝ • ҠಈฏۉΞϧΰϦζϜͷվળ - Batch LayerͰΦϑϥΠϯͰܭࢉ&࠷ਫ਼͕ྑ͍ͷΛબ - Gem࡞ͬͨ https://github.com/kenju/moving_avg-ruby
தظͰ͍͖ͬͯ • ΫϦοΫ༧ଌਫ਼ͷߋͳΔ্ˍ৽نࠂ։ൃ - ػցֶशϨΠϠʔͷຊ൪ಋೖ • Lambda Architectureͷຏ͖ࠐΈ - ࢀߟɿ։ൃऀϒϩάʰαʔόʔϨεͳόοΫΞοϓγεςϜ
Λ AWS SAM Λ༻͍ͯγϡοͱߏங͢Δʱ • ࠂ৴αʔόʔࣗମͷѹతվળ - ։ൃج൫ͷڥඋ - ύϑΥʔϚϯε࠷దԽɺϨΨγʔίʔυͷվળ
ຖͷྉཧΛָ͠Έʹ͢Δ 5IBOLZPV