Proud to be Polyglot - Riviera Dev 2015
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New developers and teams are now polyglot : - they use multiple programming languages (Java, Javascript, Ruby, ...) - they use multiple persistence store (RDBMS, NoSQL, Hadoop) In this talk you will learn about the benefits if being polyglot: use the good language or framework for the good cause, select the good persistence for specific constraints. This presentation will show how developer could mix the Python, NodeJS, AngularJS, SQL with Drill for Hadoop and MongoDB.
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Proud to be Polyglot - Riviera Dev 2015
- 1. © 2014 MapR Technologies ‹#›© 2014 MapR Technologies Proud to be Polyglot! Tugdual Grall @tgrall June 11, 2015
- 2. © 2015 MapR Technologies ‹#›@tgrall Modern Applications • Modern Applications Must • Manage any type of data • Scale • Be fault tolerant • Adapt to change
- 3. © 2015 MapR Technologies ‹#›@tgrall Current Architecture • Mono-Technology • Single “language/architecture” • Single Database : RDBMS • One size fits all approach JSP/JSF Services Messaging JTA DAO/JPA
- 4. © 2015 MapR Technologies ‹#›@tgrall Is it good for me? • Many Files • XML, Sources, Configuration, … • Does Hibernate/JPA is good for all? • Impedance mismatch • Need to scale • From 0 to 50 millions users in 6 weeks • 1Tb of data each day • How easy is to add new features? • Changing code, updating data structure, … • And all this for yesterday !
- 5. © 2014 MapR Technologies ‹#›@tgrall One size does NOT fit all!
- 6. © 2014 MapR Technologies ‹#›@tgrall Let’s look at our data… 6
- 7. © 2014 MapR Technologies ‹#› Big Data
- 8. © 2014 MapR Technologies ‹#› Big Users http://www.theconnectivist.com/ & Cisco
- 9. © 2015 MapR Technologies ‹#›@tgrall . . . App Server RDBMS Application Scale out Add more “Web” servers RDBMS Scale Up Get bigger server Stay up!…. and Scale
- 10. © 2015 MapR Technologies ‹#›@tgrall Scaling out RDBMS • Run many RDBMS Servers • Data could be partitioned • Done by the application code • Caching Layer . . . App Server . . . Memcached . . . MySQL
- 11. © 2015 MapR Technologies ‹#›@tgrall NoSQL to Scale Out! . . . NoSQL App Server . . . Application Scale out Add more “Web” servers NoSQL Scale Out Add more servers
- 12. © 2015 MapR Technologies ‹#›@tgrall Operational vs Analytics Databases Warehouse,AnalyticsApplications, Interactions
- 13. © 2015 MapR Technologies ‹#›@tgrall Polyglot Persistence Big Data/Analysis NoSQL RDBMS • Log Capture • Recommendations • Predictions • Ad Campaign • Products • User Profiles • Game Actions • Sessions • Shopping Cart • Financial Data • Reporting
- 14. © 2015 MapR Technologies ‹#›@tgrall
- 15. © 2015 MapR Technologies ‹#›@tgrall Data Service Layer • Wrap data call in Services – loosely coupled . . . App Server
- 16. © 2015 MapR Technologies ‹#›@tgrall Use Case : Personalization WebSite / Application Personalization Database Data Processing Logs Application Data
- 17. © 2015 MapR Technologies ‹#›@tgrall Use Case : Mobile / API PIM Database • Legacy Application • Product Information NoSQL • REST API • Product Data • Additional Metadata
- 18. © 2014 MapR Technologies ‹#› Now What? Now What?
- 19. © 2015 MapR Technologies ‹#›@tgrall Why multiple languages? • Sometimes we have no choice • HTML/CSS/JavaScript + Server Side • Mobile Native Applications • Java/.Net are slow movers • Java EE 5.0 is still mainstream (2006!!) • Many languages and frameworks • Scala, Clojure, Groovy, Dart, Go, Ruby, Python, F#, Erlang, Node.js, Rails, Play!, Grails, ...
- 20. © 2015 MapR Technologies ‹#›@tgrall Examples • Realtime interaction with WebSockets : • Wait for Java EE 7 to supported by your IT? • Hack your app server and application with Continuation ? • Use Node.js and Socket.io ? • Data Collection and Treatment? • Find a library? • Create your library? • Use Java 8 and Lambdas? • Use Scala?
- 21. © 2015 MapR Technologies ‹#›@tgrall Examples • Simple CRUD Application • Use the JavaEE stack with JPA and JSF? • Use Spring ? • Use tools like Play!, Grails, Rails, MEAN ?
- 22. © 2015 MapR Technologies ‹#›@tgrall How to chose? • Maturity/Supportability • Features Set • Learning Curve • Productivity
- 23. © 2015 MapR Technologies ‹#›@tgrall Use Case : Second Screen Experience . . . Node.js + Socket IO Play! Application Python Scripts
- 24. © 2015 MapR Technologies ‹#›@tgrall Use Case : Recommendation WebSite / Application Machine Learning / Recommendation Data Processing UserActivity Application Data
- 25. © 2014 MapR Technologies ‹#›@tgrall Demonstration
- 26. © 2015 MapR Technologies ‹#›@tgrall Conclusion • Use the good tool for the good task • Do not try to “hack” something when you have a simpler solution • Think about your users first... so deliver and get feedback • Learning is part of our job ! • And this will help you and your project • What about maintenance? • Do you think it is easier to maintain complex old code?
- 27. © 2014 MapR Technologies ‹#› Questions
- 28. © 2014 MapR Technologies ‹#›© 2014 MapR Technologies Proud to be Polyglot! Tugdual Grall @tgrall June 11, 2015