meeteor-mongodb.pdf

1. how uses Wednesday, April 11, 12
2. Brandon Hilkert @brandonhilkert http://meeteor.com Wednesday, April 11, 12
3. http://meeteor.com what is Wednesday, April 11, 12
4. EASY FAST and Wednesday, April 11, 12
5. we’re PRODUCT people, not SERVER people Wednesday, April 11, 12
6. Rails Nginx EC2 MySQL RDS platform Wednesday, April 11, 12
7. 2 pain points Wednesday, April 11, 12
8. 1 user signup Avg. 50 sec. Wednesday, April 11, 12
9. 1 user signup FAST? Avg. 50 sec. Wednesday, April 11, 12
10. 2 matching guru Wednesday, April 11, 12
11. Wednesday, April 11, 12
12. join spaghetti Wednesday, April 11, 12
13. DISCLAIMER! DISCLAIMER! DISCLAIMER! DISCLAIMER! DISCLAIMER! Wednesday, April 11, 12
14. FASTER! Need to get Wednesday, April 11, 12
15. SQL vs. NoSQL early 2011 Wednesday, April 11, 12
16. flame wars are not always a BAD THING? Wednesday, April 11, 12
17. 1 awareness Wednesday, April 11, 12
18. 2 o.s.s. Wednesday, April 11, 12
19. who CAREs? Wednesday, April 11, 12
20. Wednesday, April 11, 12
21. industries industries employers employers interests interests skills skills Wednesday, April 11, 12
22. document store great for comparisons if attributes are contained no more joins...sort of Wednesday, April 11, 12
23. mongoDB vs. couchDB Wednesday, April 11, 12
24. mongoDB winner! Wednesday, April 11, 12
25. data types Users id name email location 3 “Brandon” “b@m.com” “Philly” User_Interests id user_id interest_id 1 3 4 Interests id name 4 “HTML” mysql many-to-many Wednesday, April 11, 12
26. data types Users id name email location interests 3 “Brandon” “b@m.com” “Philly” [“Ruby”, “MongoDB”] mongodb more NATURAL? User.all(interests: “MongoDB”) array Wednesday, April 11, 12
27. embedded documents Users id name email location 3 “Brandon” “b@m.com” “Philly” User_Jobs id user_id job_id 1 3 4 Jobs id employer_id position description 4 7 “Developer” “Web” many-to-many Employers id name location industry 7 “Meeteor” “Philly” “Internet” mysql Wednesday, April 11, 12
28. embedded documents mongodb class User include MongoMapper::Document key :first_name, String key :last_name, String key :headline, String key :email, String many :jobs end class Job include MongoMapper::EmbeddedDocument key :employer, String key :position, String key :description, String key :industry, String end Wednesday, April 11, 12
29. embedded documents mongodb Users id name email location jobs user.jobs.first.employer => “Meeteor” 3 “Brandon” “b@m.com” “Philly” [{:_id => BSON::ObjectId('4e4efad0d052fc3ea0009a7a'), :employer => “Meeteor”, :position => “Founder”, :description => “Create networking application”, :industry => “Internet” }] embedded document Wednesday, April 11, 12
30. conversion? ~ 40 hours of which ~20 hours tinkering Wednesday, April 11, 12
31. RESULTS user signup 50 sec. 3 sec. Wednesday, April 11, 12
32. RESULTS matching guru 2 queries with a crap load of joins 2 SIMPLE queries Wednesday, April 11, 12
33. Rails Heroku MongoDB MongoHQ platform revised we’re PRODUCT people, remember? Wednesday, April 11, 12
34. how to not make life miserable after converting... slow queries indexing db.system.profile.find({millis:{$gt:2000}}).sort({$natural:-1}) User.ensure_index(:interests) User.ensure_index("jobs.employer") AnalyticLog.ensure_index([[:user_id, 1], [:type, 1]]) Wednesday, April 11, 12
35. questions? Brandon Hilkert @brandonhilkert Wednesday, April 11, 12