Proud to be polyglot
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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 Java platform with other technologies such as NodeJS and AngularJS to build application in a more productive way. This is also the opportunity to talk about the new Command Query Responsibility Segregation (CQRS) pattern to allow developers to be more effective and deliver the proper application to the user quicker. This presentation was delivered during Devfest Nantes 2014
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Proud to be polyglot
- 1. DevFest Tugdual Grall Technical Evangelist tug@mongodb.com @tgrall
- 2. Proud to be Polyglot! Tugdual Grall Technical Evangelist tug@mongodb.com @tgrall
- 3. Modern Applications • Modern Applications Must Manage any type of data Scale Be fault tolerant Adapt to change
- 4. Current Architecture • Mono-Technology • Single “language/architecture” • Single Database : RDBMS ! • One size fits all approach JSP/JSF Services Messaging JTA DAO/JPA
- 5. Is it good for me? • Many files • XML, Sources, .. • Does Hibernate/JPA is good for all? • Impedance mismatch • Need to scale • from 0 to 50millions users in 6 weeks • How to add new features easily? • changing code, updating data structure, ... • and all this for yesterday!
- 6. One size does NOT fit all!
- 7. Look at our data….
- 8. Big Data
- 9. Big Users http://www.theconnectivist.com/ & Cisco
- 10. Stay up! . . . Application ! Scale out Add more “Web” servers RDBMS ! Scale Up Get bigger server App Server RDBMS
- 11. Scaling out RDBMS . . . App Server . . . Memcached . . . MySQL • Run Many SQL Servers ! • Data could be sharded • Done by the application code ! • Caching Layer
- 12. NoSQL to Scale out! . . . Application ! Scale out Add more “Web” servers NoSQL ! Scale Out Add more servers App Server . . . NoSQL
- 13. Operational vs Analytics Databases Applications, Interactions Warehouse, Analytics
- 14. Polyglot Persistence Big Data/Analysis Document RDBMS • Log Capture • Recommendations • Predictions • Ad Campaign • Products • User Profiles • Game Actions • Sessions • Shopping Cart • Financial Data • Reporting
- 15. Developer New Skills • Understand the pros/cons of each solutions – Programming API – How to access the data? (API, Query Languages) • Learn how to design data model – De-normalizing and duplicate data is not a problem • Integrate each solution to your application • Note: This is something you already do ! – Operational RDBMS and Data Warehouse
- 16. Data Service Layer • Wrap data call in Services – loosely coupled . . . App Server
- 17. Use Case : Personalization WebSite / Application Personalization Database LogsLogs Data Processing Application Data
- 18. Use Case : Mobile / API PIM Database • Legacy Application • Product Information NoSQL • REST API • Product Data • Additional Metadata
- 19. Now What?
- 20. 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, ...
- 21. 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?
- 22. Examples • Simple CRUD Application – Use the JavaEE stack with JPA and JSF? – Use Spring ? – Use tools like Play!, Grails, Rails, MEAN ?
- 23. How to chose? • Maturity/Supportability • Features Set • Learning Curve • Productivity
- 24. Polyglot Programming in Action • Build a new database – Save and retrieve data on disk – Cache the data on RAM – Build a query engine – Build replication and sharding – Build a Monitoring engine & console – Build a Backup/Restore Solution
- 25. Polyglot Programming in Action • Data access, caching, and replication – C/C++ is the fastest way to interact with I/O – Leverage existing Caching layer & I/O – memory-mapped file • Query & Indexing – Leverage C/C++, and expose native JS engine • Management – Web Console : Java & HTML/CSS – Agent : GoLang
- 26. MongoDB & MMS
- 27. Use Case : Second Screen Experience . . . Node.js + Socket IO Play! ApplicaIon Python Scripts
- 29. 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 code?
- 30. Tugdual Grall Technical Evangelist tug@mongodb.com @tgrall Questions?