SlideShare a Scribd company logo
1 
Rakuten Ichiba. 
Vol.01 Oct/25/2014 
Takao Shiono 
ISDOD(Ichiba Service Development and Operation Department), Rakuten Inc.
2 
Objective 
The purpose of this presentation is to introduce our 
company ,Rakuten and share the issues for our futu 
re development.
3 
Agenda 
1.About Rakuten 
1-1. Japan Business 
1-2. Global Business 
1-3. Business KPI 
2.System Situation 
2-1. Network 
2-2. Database 
2-3. Application 
2-4. Summary 
3.Organization
4 
0. Introduce myself.
5 
0. About me 
About my Career. 
2014/04/01 Rakuten Ichiba Development and Operation Department manager. 
2013/06/27 Board of director of STYLIFE. 
2012/03/30 Board of director of NETS PARTNERS.(- 1st Dec 2012.) 
2011/11/17 Executive officer of RAKUTEN.Inc. 
2011/10/22 Development Managing Officer. 
2011/01/01 Japan Ichiba Section Manager & Senior Service Producer of Japan Rakuten Ichiba. 
2009/05/01 Shopping & Auction Section Vice manager & Senior Service Producer of Auction. 
2008/07/01 Portal Service Section Manager & Senior Service Producer of Infoseek. 
2008/02/01 New Service Division Vice manager. 
2007/04/01 Portal Produce Department manager. 
2006/04/01 Portal media company Produce department. 
2005/12/01 Portal media company Infoseek CWD/MKT Department manager. 
2005/01/01 Corporate Development planning department & Quality Assurance team Supervisor. 
2004/04/01 Rakuten Ichiba ID produce department. 
2004/02/01 Development Head Office.
6 
1. Rakuten
7 
Rakuten,Inc. 
Founded: February 7, 1997 
IPO: April 19, 2000 (JASDAQ Stock Exchange) 
Office: Rakuten Tower (Tokyo, Japan) 
Employees: 9,311 (as of Dec. 2012) 
Market Cap: JPY 2,332 Billion (as of Jan 17, 2014)
8 
Uniqueness 
Most E-commerce 
Controllable Middleman. 
Efficiency 
Direct Sales
9 
Uniqueness 
RakutenE-commerce 
Entertainment 
Bazaar 
Platform 
Encounter Platform
10 
Rakuten Ecosystem
11 
Expanding Business Portfolio 
Taiwan 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
12 
1-1. Japan Business
13 
Service for Japan Customer 
E-Commerce Personal Finance 
Digital Contents 
Travel / Booking Communication Pro Sports
14 
About Rakuten Ichiba in Japan 
http://global.rakuten.com/corp/about/strength/data.html
15 
About Rakuten Ichiba in Japan 
http://global.rakuten.com/corp/about/strength/data.html
16 
About Rakuten Ichiba in Japan
17 
1-2. Global Business
18 
Global Expansion 
Rapidly Expanding Worldwide from 2010 
English-nization 
/Globalization.
19 
Global Expansion 
E-Commerce 
eBook 
Travel 
Other services & businesses 
Rakuten Institute of Technology 
Development center 
Head Office / Regional Headquarters 
Head Office 
• E-commerce in 14 countries and regions 
• All services and businesses in 28 countries
20 
Expanding Rakuten Ecosystem 
EU Japan US 
ASIA
21 
Brand Awareness 
Taiwan Indonesia Singapore 
89% 72% 54% 
 * Aided awareness among general internet users. 
 Survey Method: Internet survey (panel sampling), July 
2014 
Malaysia 
54%
22 
1-3. Business KPI
23 
Rakuten Ichiba GMS 
1,000 
900 
800 
700 
600 
500 
400 
300 
200 
100 
0 
$ 1 = JPY 79 over $ 13 Billion 
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 
(JPY bn) 
2010 2011 2020? 
10,000 
・・・ 
over 1 trillion
24 
The BigData in Rakuten 
• 93,870,000+ users 
• 800,000,000+ purchase info 
• 100,000,000+ reviews 
• 3,000,000+ hotel booking per month 
• 41,000+ merchants 
• 60,000+ hotels 
• Bank, Credit Card…. 
• Tremendous amount of search queries 
• Several hundreds GB access log per day 
• etc 
• increasing more and more.
25 
Rakuten Data Explosion 
200000000 
180000000 
160000000 
140000000 
120000000 
100000000 
80000000 
60000000 
40000000 
20000000 
0 
The number of item 
1997 2005 2006 2007 2008 2009 2010 2011 2012 2013
26 
2. System Situation
27 
2-1. Network
28 
Network Traffic Between 2005 to 2008 
22.0G 
20.0G 
18.0G 
15.0G 
14.0G 
12.0G 
10.0G 
8.0G 
6.0G 
4.0G 
2.0G 
2007/12 2008/12 
16.0G 
トラフィックトレンドの実績と予測 
2009/12 2010/12 2011/12 
2005/12 2006/12
29 
Network Traffic Between 2005 to 2008 
22.0G 
20.0G 
18.0G 
15.0G 
14.0G 
12.0G 
10.0G 
8.0G 
6.0G 
4.0G 
2.0G 
2007/12 2008/12 
16.0G 
トラフィックトレンドの実績と予測 
2009/12 2010/12 2011/12 
2005/12 2006/12
30 
Network Traffic From 2009. 
Victory sale 108Gbits/sec 
Super sale 67Gbits/sec 
Super sale 42Gbits/sec 
2009 2010 2011 2012 2013
31 
Reason of Data Increase
32 
2-2. Database
33 
History of Database 
M9000 
(2009) 
ExaData 
(2013) 
SF E25K 
(2004) 
SF 15K 
(2002) 
E10K 
(2001) 
E4500 
(1999) 
E420R 
(1999) 
E450 
(1997) 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Many APP 
Many DB 
34 
History of Database 
Few APP 
App App App App App 
App App App App 
Few DB 
Nothing changed for over 10 years
35 
Issues 
Data have been increasing day by day 
We have to set the capacity size manually. It is a database specification. 
- Max extents 
- Max pagesize 
- Highly loaded Database. 
Too much maintenance 
We have to : 
- Increase capacity 
- Change HW/SW for EOSL 
- Version up Software 
- Patch Software 
Difficult to manage/use the data 
Causes: 
- A large number of dependency ( Node=755, Edge=1,233 ) 
- Too many connections ( 1DB ⇔ 66 Application ) 
- Diverse versions ( OS, MW, programing language, script )
36 
2-3. Application
37 
Case 1 
DB has not been abstracted. 
Each App connect to DB directly.
38 
2-3. Application 
Case 1. 
App A App B App C 
API α 
DB 
App D 
Merchant / Consumer 
Front 
API 
Data 
If we need to change our database…
39 
2-3. Application 
Case 1. 
App A App B App C 
API α 
DB 
App D 
Merchant / Consumer 
Front 
API 
Data 
We have to modify & test many applications.
40 
2-3. Application 
Case 1. 
App A App B App C 
API α 
DB 
App D 
Merchant / Consumer 
Front 
API 
Data 
We will integrate many connections to a single API.
41 
2-3. Application 
Case 2 
2 phase commit.
42 
It has to do INSERT to Order DB and do UPDATE 
to Inventory DB at the same time. 
If either one fails, data mismatch will occur. It is 
API 
really risky. 
Mobile 
Application 
Order complete 
Application 
Order Inventory 
PC 
Order Management tool for Merchant. 
R 
Case2. 
2-3. Application
43 
2-3. Application 
Order complete 
We are abolishing 2 phase commit. 
Order DB will be separated from Order application. 
New API 
Mobile 
Application 
Application 
Order Inventory 
PC 
Order Management tool for Merchant. 
R 
Queue 
Case2.
44 
2-4. Summary
45 
Action plans for future development 
1. Reduce management difficulties 
Reduce App server 
Reduce DB server 
2. Reconstruct Application 
Reduce too much dependence on DB 
‐ Decrease test scope 
‐ Decrease development scope 
3. Stop 2 Phase Commit (Change the 
architecture) 
‐ Decrease difficult session control 
4. Reconstruct DB schema and design
46 
3. Organization
47 
Hiring Talented Engineers 
Many employees have come to Japan.
48 
Hiring Talented Engineers 
0 50 100 150 200 
Japan 
China 
India 
Korea 
USA 
Bangladesh 
Philippines 
Taiwan 
England 
Indonesia 
Australia 
Canada 
Sri Lanka 
Brazil 
Algeria 
Argentine 
Swiss 
Thailand 
Chile 
Nepal 
Pakistan 
Hungary 
Republic 
Vietnam 
Hong Kong 
Other 
25+
49 
Next Challenge
50 
Ideal Goal 
Engineers from our overseas companies will 
become able to develop RMS together.
51 
Summary 
The purpose of this presentation is to int 
roduce our company ,Rakuten and share 
the issues for our future development.
52

More Related Content

Similar to [Rakuten TechConf2014] [A-4] Rakuten Ichiba

Case Study of Financial Web System Development and Operations with Oracle Web...
Case Study of Financial Web System Development and Operations with Oracle Web...Case Study of Financial Web System Development and Operations with Oracle Web...
Case Study of Financial Web System Development and Operations with Oracle Web...
Hirofumi Iwasaki
 
Informatica to ODI Migration – What, Why and How | Informatica to Oracle Dat...
Informatica to ODI Migration – What, Why and How |  Informatica to Oracle Dat...Informatica to ODI Migration – What, Why and How |  Informatica to Oracle Dat...
Informatica to ODI Migration – What, Why and How | Informatica to Oracle Dat...
Jade Global
 
Akram_Resume_ETL_Informatica
Akram_Resume_ETL_InformaticaAkram_Resume_ETL_Informatica
Akram_Resume_ETL_InformaticaAkram Bhuyan
 
[RakutenTechConf2013] [C-1] Rakuten new infrastructure
[RakutenTechConf2013] [C-1] Rakuten new infrastructure[RakutenTechConf2013] [C-1] Rakuten new infrastructure
[RakutenTechConf2013] [C-1] Rakuten new infrastructure
Rakuten Group, Inc.
 
Energy Management Solution - iARMS-EMS/PMS
Energy Management Solution - iARMS-EMS/PMSEnergy Management Solution - iARMS-EMS/PMS
Energy Management Solution - iARMS-EMS/PMS
Envision Enterprise Solutions America Inc.
 
Resume - Mukesh Mishra_March_2016
Resume - Mukesh Mishra_March_2016Resume - Mukesh Mishra_March_2016
Resume - Mukesh Mishra_March_2016Mukesh Mishra
 
Shanish_SQL_PLSQL_Profile
Shanish_SQL_PLSQL_ProfileShanish_SQL_PLSQL_Profile
Shanish_SQL_PLSQL_ProfileShanish Jain
 
Business Utility Application
Business Utility ApplicationBusiness Utility Application
Business Utility Application
IRJET Journal
 
Webinar - How to Get Real-Time Network Management Right?
Webinar - How to Get Real-Time Network Management Right?Webinar - How to Get Real-Time Network Management Right?
Webinar - How to Get Real-Time Network Management Right?
ManageEngine
 
Facilitating DevOps Execution in an All Digital Environment
Facilitating DevOps Execution in an All Digital EnvironmentFacilitating DevOps Execution in an All Digital Environment
Facilitating DevOps Execution in an All Digital Environment
Kurt Andersen
 
Sap safe haborstatement
Sap safe haborstatementSap safe haborstatement
Sap safe haborstatement
Company Spotlight
 
Nitin_updated_Profile
Nitin_updated_ProfileNitin_updated_Profile
Nitin_updated_ProfileNitin Saxena
 
Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...
Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...
Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...
Hirofumi Iwasaki
 
SAP TechEd 2016 Barcelona TEC123 Session Presentation
SAP TechEd 2016 Barcelona TEC123 Session PresentationSAP TechEd 2016 Barcelona TEC123 Session Presentation
SAP TechEd 2016 Barcelona TEC123 Session Presentation
Core To Edge
 
Saba resume
Saba resumeSaba resume
Saba resume
Saba Malik
 
[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...
[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...
[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...
Rakuten Group, Inc.
 

Similar to [Rakuten TechConf2014] [A-4] Rakuten Ichiba (20)

Case Study of Financial Web System Development and Operations with Oracle Web...
Case Study of Financial Web System Development and Operations with Oracle Web...Case Study of Financial Web System Development and Operations with Oracle Web...
Case Study of Financial Web System Development and Operations with Oracle Web...
 
Informatica to ODI Migration – What, Why and How | Informatica to Oracle Dat...
Informatica to ODI Migration – What, Why and How |  Informatica to Oracle Dat...Informatica to ODI Migration – What, Why and How |  Informatica to Oracle Dat...
Informatica to ODI Migration – What, Why and How | Informatica to Oracle Dat...
 
Akram_Resume_ETL_Informatica
Akram_Resume_ETL_InformaticaAkram_Resume_ETL_Informatica
Akram_Resume_ETL_Informatica
 
[RakutenTechConf2013] [C-1] Rakuten new infrastructure
[RakutenTechConf2013] [C-1] Rakuten new infrastructure[RakutenTechConf2013] [C-1] Rakuten new infrastructure
[RakutenTechConf2013] [C-1] Rakuten new infrastructure
 
SaurabhKasyap
SaurabhKasyapSaurabhKasyap
SaurabhKasyap
 
Rushindra-CV
Rushindra-CVRushindra-CV
Rushindra-CV
 
Rushindra-CV
Rushindra-CVRushindra-CV
Rushindra-CV
 
Energy Management Solution - iARMS-EMS/PMS
Energy Management Solution - iARMS-EMS/PMSEnergy Management Solution - iARMS-EMS/PMS
Energy Management Solution - iARMS-EMS/PMS
 
Resume - Mukesh Mishra_March_2016
Resume - Mukesh Mishra_March_2016Resume - Mukesh Mishra_March_2016
Resume - Mukesh Mishra_March_2016
 
Shanish_SQL_PLSQL_Profile
Shanish_SQL_PLSQL_ProfileShanish_SQL_PLSQL_Profile
Shanish_SQL_PLSQL_Profile
 
Business Utility Application
Business Utility ApplicationBusiness Utility Application
Business Utility Application
 
Webinar - How to Get Real-Time Network Management Right?
Webinar - How to Get Real-Time Network Management Right?Webinar - How to Get Real-Time Network Management Right?
Webinar - How to Get Real-Time Network Management Right?
 
Facilitating DevOps Execution in an All Digital Environment
Facilitating DevOps Execution in an All Digital EnvironmentFacilitating DevOps Execution in an All Digital Environment
Facilitating DevOps Execution in an All Digital Environment
 
Sap safe haborstatement
Sap safe haborstatementSap safe haborstatement
Sap safe haborstatement
 
Nitin_updated_Profile
Nitin_updated_ProfileNitin_updated_Profile
Nitin_updated_Profile
 
Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...
Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...
Java EE 6 Adoption in One of the World’s Largest Online Financial Systems [Ja...
 
SAP TechEd 2016 Barcelona TEC123 Session Presentation
SAP TechEd 2016 Barcelona TEC123 Session PresentationSAP TechEd 2016 Barcelona TEC123 Session Presentation
SAP TechEd 2016 Barcelona TEC123 Session Presentation
 
Saba Resume
Saba ResumeSaba Resume
Saba Resume
 
Saba resume
Saba resumeSaba resume
Saba resume
 
[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...
[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...
[Rakuten TechConf2014] [Fukuoka] Case Study of Financial Web Systems Developm...
 

More from Rakuten Group, Inc.

コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話
コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話
コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話
Rakuten Group, Inc.
 
楽天における安全な秘匿情報管理への道のり
楽天における安全な秘匿情報管理への道のり楽天における安全な秘匿情報管理への道のり
楽天における安全な秘匿情報管理への道のり
Rakuten Group, Inc.
 
What Makes Software Green?
What Makes Software Green?What Makes Software Green?
What Makes Software Green?
Rakuten Group, Inc.
 
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
Rakuten Group, Inc.
 
DataSkillCultureを浸透させる楽天の取り組み
DataSkillCultureを浸透させる楽天の取り組みDataSkillCultureを浸透させる楽天の取り組み
DataSkillCultureを浸透させる楽天の取り組み
Rakuten Group, Inc.
 
大規模なリアルタイム監視の導入と展開
大規模なリアルタイム監視の導入と展開大規模なリアルタイム監視の導入と展開
大規模なリアルタイム監視の導入と展開
Rakuten Group, Inc.
 
楽天における大規模データベースの運用
楽天における大規模データベースの運用楽天における大規模データベースの運用
楽天における大規模データベースの運用
Rakuten Group, Inc.
 
楽天サービスを支えるネットワークインフラストラクチャー
楽天サービスを支えるネットワークインフラストラクチャー楽天サービスを支えるネットワークインフラストラクチャー
楽天サービスを支えるネットワークインフラストラクチャー
Rakuten Group, Inc.
 
楽天の規模とクラウドプラットフォーム統括部の役割
楽天の規模とクラウドプラットフォーム統括部の役割楽天の規模とクラウドプラットフォーム統括部の役割
楽天の規模とクラウドプラットフォーム統括部の役割
Rakuten Group, Inc.
 
Rakuten Services and Infrastructure Team.pdf
Rakuten Services and Infrastructure Team.pdfRakuten Services and Infrastructure Team.pdf
Rakuten Services and Infrastructure Team.pdf
Rakuten Group, Inc.
 
The Data Platform Administration Handling the 100 PB.pdf
The Data Platform Administration Handling the 100 PB.pdfThe Data Platform Administration Handling the 100 PB.pdf
The Data Platform Administration Handling the 100 PB.pdf
Rakuten Group, Inc.
 
Supporting Internal Customers as Technical Account Managers.pdf
Supporting Internal Customers as Technical Account Managers.pdfSupporting Internal Customers as Technical Account Managers.pdf
Supporting Internal Customers as Technical Account Managers.pdf
Rakuten Group, Inc.
 
Making Cloud Native CI_CD Services.pdf
Making Cloud Native CI_CD Services.pdfMaking Cloud Native CI_CD Services.pdf
Making Cloud Native CI_CD Services.pdf
Rakuten Group, Inc.
 
How We Defined Our Own Cloud.pdf
How We Defined Our Own Cloud.pdfHow We Defined Our Own Cloud.pdf
How We Defined Our Own Cloud.pdf
Rakuten Group, Inc.
 
Travel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech infoTravel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech info
Rakuten Group, Inc.
 
Travel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech infoTravel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech info
Rakuten Group, Inc.
 
OWASPTop10_Introduction
OWASPTop10_IntroductionOWASPTop10_Introduction
OWASPTop10_Introduction
Rakuten Group, Inc.
 
Introduction of GORA API Group technology
Introduction of GORA API Group technologyIntroduction of GORA API Group technology
Introduction of GORA API Group technology
Rakuten Group, Inc.
 
100PBを越えるデータプラットフォームの実情
100PBを越えるデータプラットフォームの実情100PBを越えるデータプラットフォームの実情
100PBを越えるデータプラットフォームの実情
Rakuten Group, Inc.
 
社内エンジニアを支えるテクニカルアカウントマネージャー
社内エンジニアを支えるテクニカルアカウントマネージャー社内エンジニアを支えるテクニカルアカウントマネージャー
社内エンジニアを支えるテクニカルアカウントマネージャー
Rakuten Group, Inc.
 

More from Rakuten Group, Inc. (20)

コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話
コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話
コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話
 
楽天における安全な秘匿情報管理への道のり
楽天における安全な秘匿情報管理への道のり楽天における安全な秘匿情報管理への道のり
楽天における安全な秘匿情報管理への道のり
 
What Makes Software Green?
What Makes Software Green?What Makes Software Green?
What Makes Software Green?
 
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
 
DataSkillCultureを浸透させる楽天の取り組み
DataSkillCultureを浸透させる楽天の取り組みDataSkillCultureを浸透させる楽天の取り組み
DataSkillCultureを浸透させる楽天の取り組み
 
大規模なリアルタイム監視の導入と展開
大規模なリアルタイム監視の導入と展開大規模なリアルタイム監視の導入と展開
大規模なリアルタイム監視の導入と展開
 
楽天における大規模データベースの運用
楽天における大規模データベースの運用楽天における大規模データベースの運用
楽天における大規模データベースの運用
 
楽天サービスを支えるネットワークインフラストラクチャー
楽天サービスを支えるネットワークインフラストラクチャー楽天サービスを支えるネットワークインフラストラクチャー
楽天サービスを支えるネットワークインフラストラクチャー
 
楽天の規模とクラウドプラットフォーム統括部の役割
楽天の規模とクラウドプラットフォーム統括部の役割楽天の規模とクラウドプラットフォーム統括部の役割
楽天の規模とクラウドプラットフォーム統括部の役割
 
Rakuten Services and Infrastructure Team.pdf
Rakuten Services and Infrastructure Team.pdfRakuten Services and Infrastructure Team.pdf
Rakuten Services and Infrastructure Team.pdf
 
The Data Platform Administration Handling the 100 PB.pdf
The Data Platform Administration Handling the 100 PB.pdfThe Data Platform Administration Handling the 100 PB.pdf
The Data Platform Administration Handling the 100 PB.pdf
 
Supporting Internal Customers as Technical Account Managers.pdf
Supporting Internal Customers as Technical Account Managers.pdfSupporting Internal Customers as Technical Account Managers.pdf
Supporting Internal Customers as Technical Account Managers.pdf
 
Making Cloud Native CI_CD Services.pdf
Making Cloud Native CI_CD Services.pdfMaking Cloud Native CI_CD Services.pdf
Making Cloud Native CI_CD Services.pdf
 
How We Defined Our Own Cloud.pdf
How We Defined Our Own Cloud.pdfHow We Defined Our Own Cloud.pdf
How We Defined Our Own Cloud.pdf
 
Travel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech infoTravel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech info
 
Travel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech infoTravel & Leisure Platform Department's tech info
Travel & Leisure Platform Department's tech info
 
OWASPTop10_Introduction
OWASPTop10_IntroductionOWASPTop10_Introduction
OWASPTop10_Introduction
 
Introduction of GORA API Group technology
Introduction of GORA API Group technologyIntroduction of GORA API Group technology
Introduction of GORA API Group technology
 
100PBを越えるデータプラットフォームの実情
100PBを越えるデータプラットフォームの実情100PBを越えるデータプラットフォームの実情
100PBを越えるデータプラットフォームの実情
 
社内エンジニアを支えるテクニカルアカウントマネージャー
社内エンジニアを支えるテクニカルアカウントマネージャー社内エンジニアを支えるテクニカルアカウントマネージャー
社内エンジニアを支えるテクニカルアカウントマネージャー
 

Recently uploaded

DevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA ConnectDevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA Connect
Kari Kakkonen
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neo4j
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Matthew Sinclair
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Paige Cruz
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
Aftab Hussain
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
ControlCase
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
Guy Korland
 
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
SOFTTECHHUB
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Neo4j
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
SOFTTECHHUB
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
James Anderson
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
Alpen-Adria-Universität
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
Alan Dix
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Neo4j
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Safe Software
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems S.M.S.A.
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
RinaMondal9
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
DanBrown980551
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
Matthew Sinclair
 

Recently uploaded (20)

DevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA ConnectDevOps and Testing slides at DASA Connect
DevOps and Testing slides at DASA Connect
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
 
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
 

[Rakuten TechConf2014] [A-4] Rakuten Ichiba

  • 1. 1 Rakuten Ichiba. Vol.01 Oct/25/2014 Takao Shiono ISDOD(Ichiba Service Development and Operation Department), Rakuten Inc.
  • 2. 2 Objective The purpose of this presentation is to introduce our company ,Rakuten and share the issues for our futu re development.
  • 3. 3 Agenda 1.About Rakuten 1-1. Japan Business 1-2. Global Business 1-3. Business KPI 2.System Situation 2-1. Network 2-2. Database 2-3. Application 2-4. Summary 3.Organization
  • 4. 4 0. Introduce myself.
  • 5. 5 0. About me About my Career. 2014/04/01 Rakuten Ichiba Development and Operation Department manager. 2013/06/27 Board of director of STYLIFE. 2012/03/30 Board of director of NETS PARTNERS.(- 1st Dec 2012.) 2011/11/17 Executive officer of RAKUTEN.Inc. 2011/10/22 Development Managing Officer. 2011/01/01 Japan Ichiba Section Manager & Senior Service Producer of Japan Rakuten Ichiba. 2009/05/01 Shopping & Auction Section Vice manager & Senior Service Producer of Auction. 2008/07/01 Portal Service Section Manager & Senior Service Producer of Infoseek. 2008/02/01 New Service Division Vice manager. 2007/04/01 Portal Produce Department manager. 2006/04/01 Portal media company Produce department. 2005/12/01 Portal media company Infoseek CWD/MKT Department manager. 2005/01/01 Corporate Development planning department & Quality Assurance team Supervisor. 2004/04/01 Rakuten Ichiba ID produce department. 2004/02/01 Development Head Office.
  • 7. 7 Rakuten,Inc. Founded: February 7, 1997 IPO: April 19, 2000 (JASDAQ Stock Exchange) Office: Rakuten Tower (Tokyo, Japan) Employees: 9,311 (as of Dec. 2012) Market Cap: JPY 2,332 Billion (as of Jan 17, 2014)
  • 8. 8 Uniqueness Most E-commerce Controllable Middleman. Efficiency Direct Sales
  • 9. 9 Uniqueness RakutenE-commerce Entertainment Bazaar Platform Encounter Platform
  • 11. 11 Expanding Business Portfolio Taiwan 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
  • 12. 12 1-1. Japan Business
  • 13. 13 Service for Japan Customer E-Commerce Personal Finance Digital Contents Travel / Booking Communication Pro Sports
  • 14. 14 About Rakuten Ichiba in Japan http://global.rakuten.com/corp/about/strength/data.html
  • 15. 15 About Rakuten Ichiba in Japan http://global.rakuten.com/corp/about/strength/data.html
  • 16. 16 About Rakuten Ichiba in Japan
  • 17. 17 1-2. Global Business
  • 18. 18 Global Expansion Rapidly Expanding Worldwide from 2010 English-nization /Globalization.
  • 19. 19 Global Expansion E-Commerce eBook Travel Other services & businesses Rakuten Institute of Technology Development center Head Office / Regional Headquarters Head Office • E-commerce in 14 countries and regions • All services and businesses in 28 countries
  • 20. 20 Expanding Rakuten Ecosystem EU Japan US ASIA
  • 21. 21 Brand Awareness Taiwan Indonesia Singapore 89% 72% 54%  * Aided awareness among general internet users.  Survey Method: Internet survey (panel sampling), July 2014 Malaysia 54%
  • 23. 23 Rakuten Ichiba GMS 1,000 900 800 700 600 500 400 300 200 100 0 $ 1 = JPY 79 over $ 13 Billion 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 (JPY bn) 2010 2011 2020? 10,000 ・・・ over 1 trillion
  • 24. 24 The BigData in Rakuten • 93,870,000+ users • 800,000,000+ purchase info • 100,000,000+ reviews • 3,000,000+ hotel booking per month • 41,000+ merchants • 60,000+ hotels • Bank, Credit Card…. • Tremendous amount of search queries • Several hundreds GB access log per day • etc • increasing more and more.
  • 25. 25 Rakuten Data Explosion 200000000 180000000 160000000 140000000 120000000 100000000 80000000 60000000 40000000 20000000 0 The number of item 1997 2005 2006 2007 2008 2009 2010 2011 2012 2013
  • 26. 26 2. System Situation
  • 28. 28 Network Traffic Between 2005 to 2008 22.0G 20.0G 18.0G 15.0G 14.0G 12.0G 10.0G 8.0G 6.0G 4.0G 2.0G 2007/12 2008/12 16.0G トラフィックトレンドの実績と予測 2009/12 2010/12 2011/12 2005/12 2006/12
  • 29. 29 Network Traffic Between 2005 to 2008 22.0G 20.0G 18.0G 15.0G 14.0G 12.0G 10.0G 8.0G 6.0G 4.0G 2.0G 2007/12 2008/12 16.0G トラフィックトレンドの実績と予測 2009/12 2010/12 2011/12 2005/12 2006/12
  • 30. 30 Network Traffic From 2009. Victory sale 108Gbits/sec Super sale 67Gbits/sec Super sale 42Gbits/sec 2009 2010 2011 2012 2013
  • 31. 31 Reason of Data Increase
  • 33. 33 History of Database M9000 (2009) ExaData (2013) SF E25K (2004) SF 15K (2002) E10K (2001) E4500 (1999) E420R (1999) E450 (1997) 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
  • 34. Many APP Many DB 34 History of Database Few APP App App App App App App App App App Few DB Nothing changed for over 10 years
  • 35. 35 Issues Data have been increasing day by day We have to set the capacity size manually. It is a database specification. - Max extents - Max pagesize - Highly loaded Database. Too much maintenance We have to : - Increase capacity - Change HW/SW for EOSL - Version up Software - Patch Software Difficult to manage/use the data Causes: - A large number of dependency ( Node=755, Edge=1,233 ) - Too many connections ( 1DB ⇔ 66 Application ) - Diverse versions ( OS, MW, programing language, script )
  • 37. 37 Case 1 DB has not been abstracted. Each App connect to DB directly.
  • 38. 38 2-3. Application Case 1. App A App B App C API α DB App D Merchant / Consumer Front API Data If we need to change our database…
  • 39. 39 2-3. Application Case 1. App A App B App C API α DB App D Merchant / Consumer Front API Data We have to modify & test many applications.
  • 40. 40 2-3. Application Case 1. App A App B App C API α DB App D Merchant / Consumer Front API Data We will integrate many connections to a single API.
  • 41. 41 2-3. Application Case 2 2 phase commit.
  • 42. 42 It has to do INSERT to Order DB and do UPDATE to Inventory DB at the same time. If either one fails, data mismatch will occur. It is API really risky. Mobile Application Order complete Application Order Inventory PC Order Management tool for Merchant. R Case2. 2-3. Application
  • 43. 43 2-3. Application Order complete We are abolishing 2 phase commit. Order DB will be separated from Order application. New API Mobile Application Application Order Inventory PC Order Management tool for Merchant. R Queue Case2.
  • 45. 45 Action plans for future development 1. Reduce management difficulties Reduce App server Reduce DB server 2. Reconstruct Application Reduce too much dependence on DB ‐ Decrease test scope ‐ Decrease development scope 3. Stop 2 Phase Commit (Change the architecture) ‐ Decrease difficult session control 4. Reconstruct DB schema and design
  • 47. 47 Hiring Talented Engineers Many employees have come to Japan.
  • 48. 48 Hiring Talented Engineers 0 50 100 150 200 Japan China India Korea USA Bangladesh Philippines Taiwan England Indonesia Australia Canada Sri Lanka Brazil Algeria Argentine Swiss Thailand Chile Nepal Pakistan Hungary Republic Vietnam Hong Kong Other 25+
  • 50. 50 Ideal Goal Engineers from our overseas companies will become able to develop RMS together.
  • 51. 51 Summary The purpose of this presentation is to int roduce our company ,Rakuten and share the issues for our future development.
  • 52. 52