Why Node, Express and Postgres - presented 23 Feb 15, Talkjs, Microsoft Auditorium
- 1. WEB SERVICES Why Node, Express and Postgres?
- 2. ABOUT ME. • Programming as a hobby. • Final student, NTU (Biz IT). • Mainly involved in tech-related entrepreneurial projects. • Latest project is VogueVerve.com.
- 3. CONTENTS. • Nodejs • Expressjs • Node modules – Passport – Sequelize – Bluebird • Postgres, Mongo, Couchbase
- 4. IT’S SIMPLE. IT’S JS FRONT-TO-BACK.
- 5. WHAT IS NODEJS? • It is a server side Javascript runtime environment. • Powered by Chrome V8. • Main intention of real-time communication. • It can be a standalone server.
- 6. WHO USES IT?
- 7. MAIN ATTRIBUTES. • Single threaded. • Async, non-blocking I/O. • Event-oriented.
- 8. IT DOESN’T WAIT FOR ANYTHING.
- 9. USING JS FOR SERVER-SIDE APPLICATION SOUNDED LIKE A BAD IDEA. Search “Node.js is cancer”
- 11. HOW TO NODE? • Delegate computationally intensive tasks to lower-level languages like C++. • Make clusters (to combat single-threading). • Node errors will crash the server. Gotta catch ‘em all.
- 12. MODULAR CONCEPT.
- 13. NPM REPOSITORY. • Modularity and versioning. • Updates and releases. • The best thing since beer.
- 14. WHAT IS EXPRESS?
- 15. EXPRESS. • It is a Node Module. • The most popular web framework for Node. • “Sinatra inspired”. • Makes building web application incredibly easy.
- 16. ROUTE HANDLING
- 17. `REQ` AND `RES` OBJECTS. • `req` comes for the user. • `res` is sent back to the user. • I use it extensively for “API- styled” web platform.
- 18. REQ AND RES OBJECTS
- 19. API IN 3 SIMPLE STEPS
- 20. NODE MODULES
- 21. PASSPORTJS. • Authentication API. • Supports almost any kind of authentication framework. • FaceBook, Twitter, Google OAuth modules already available.
- 22. AN EXAMPLE
- 23. HOW TO USE IT? • Documentation is abit skimpy and untelling. • Learn by example: https://scotch.io/tutorials/easy- node-authentication-setup- and-local
- 24. SEQUELIZEJS. • Object-Relational-Mapper (ORM) • Works with MySQL, Postgres and others. • Promise-styled. Very intuitive and maintainable code. • Support transactions.
- 26. ACTIVE RECORDS
- 27. RAW QUERIES? • You get replacements for free.
- 28. BLUEBIRD. • Very good performance. • Prevents `callback hell` in asynchronous coding. • Makes code very readable. • Parallelism.
- 29. WHY ARE PROMISES SO GOOD? Because it’s very intuitive and readable. Codes that solves a problem but cannot be easily understood, is a problem.
- 30. CALLBACK HELL
- 32. SOME ADVICES • Don’t use modules that are not well-maintained. • Worry about performance, but not too much.
- 37. MONGO AND COUCH - JSON Denormalized into a single document. Fast.
- 38. IN THE MIDDLE Use MongoDB/Couchbase + a lot of indexing OR SQL with many many joins SQL with serialized/encoded arrays
- 39. THE OLD WAYS • Joins are slow. • Serializing can be problematic. • Atomic updates impossible. • Values cannot be used as selection criteria.
- 40. MONGO AND COUCHBASE CAN HANDLE SOME “RELATIONAL” NEEDS AND STILL REMAIN FAST. BUT…
- 41. THE PROBLEM • What if Joe changes name? • What if a new field is added to users?
- 42. YOU MAY REACH A POINT WHERE THERE IS JUST TOO MUCH TO REPLICATE.
- 43. YOU CAN DO THIS AND IT IS STILL PROBABLY FAST You find yourself trying to do “joining”. Are there any ORMs for Mongo/Couchbase?
- 44. CHANGE IS THE ROOT OF ALL PROBLEMS. Will your data become more relational than it is now? http://www.sarahmei.com/blog/2013/11 /11/why-you-should-never-use- mongodb/
- 45. POSTGRES JSON AND HSTORE • A field that can contain “array- structured” data. • Atomic operations: Key/values can be searched for and indexed. • Fast. • Best thing since NPM, and beer.
- 46. A VERY FLEXIBLE STRUCTURE id name data 1 Mary { “country”: “Singapore”, “dataMeta”: { “following”: “299”, “followers”: “484” }} 2 Lucy { “country”: “France”} 3 Jane null 4 Tom {“dataMeta”: { “following”: “479” }} 5 Dick {“dataMeta”: { “following”: “12”, followers: “40”}}
- 47. WHAT ABOUT THE NEED FOR SPEED?
- 48. PERFORMANCE • Different sources will stake different claims. • Comparing apples with oranges. • They are all quite fast.
- 49. TEST USING YOUR DATA STRUCTURE AND YOUR TYPICAL ROUTINE.
- 50. IT IS NOT PERFECT • Only HSTORE supports atomic updates, JSON does not. • HSTORE does not support nested structure. • Postgres JSON is very new. Library support is adequate but not mature.
- 52. CONCLUSION ON PG • It is a RDB that is very capable of handling schemaless data. • Don’t over-normalize your data. • Use relations and constraints for critical portions of your data.
- 53. 1. SERVER-SIDE JAVASCRIPT IS A GOOD IDEA.
- 54. 2. IF YOU ARE BUILDING A WEB SERVICE, USE EXPRESS.
- 55. 3. ASK NOT WHAT A TECH CAN DO FOR YOU. ASK WHAT IT CANNOT DO.
- 56. KEEP IN TOUCH! • Facebook: /calvintwr • Email: calvin14@gmail.com