Webinar: Building Web Applications with MongoDB and Spring
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The webinar will discuss building web applications with MongoDB and Spring, starting at 11:00 AM EDT. Attendees should connect their audio via the broadcast or dial-in number listed. A recording of the webinar will be available 24 hours after it concludes.
![What is a Comment?
{
title: “What is new in 2.2 MongoDB”,
date : new Date(),
author : “Fred”
text : “.......”
tags : [“mongodb”, “nosql”]
comments : [
{author : “chris”, text: “this is great” , date : new Date()},
{author : “tom”, text: “rock on”, date : new Date()}
]](https://image.slidesharecdn.com/mongodbspringdata-121101142336-phpapp02/85/Webinar-Building-Web-Applications-with-MongoDB-and-Spring-13-320.jpg)
![What is a Comment?
{
title: “What is new in 2.2 MongoDB”,
....
comments : [
{author : “chris”, text: “this is great” , date : new Date()},
{author : “tom”, text: “rock on”, date : new Date()}
],
comments_count : 2
}](https://image.slidesharecdn.com/mongodbspringdata-121101142336-phpapp02/85/Webinar-Building-Web-Applications-with-MongoDB-and-Spring-16-320.jpg)
Webinar: Building Web Applications with MongoDB and Spring
- 1. @MongoDB Webinar Building Web Applications with MongoDB and Spring will begin at 11:00 AM EDT / 8:00 AM PDT / 3:00 PM UTC Audio should start immediately when you log into the event via Audio Broadcast. You will need a Voip headset and reliable internet connection for Audio Broadcast. If you are having issues connecting, please dial 1-877-668-4493; Access code: 669 104 658. There is a Q&A following the webinar. A recording of the webinar will be available 24 hours after the event is complete.
- 2. IT needs are evolving... Agile Development • Iterative • Continuous Data Volume, Type & Use • Trillions of records • 100’s of millions of queries per second • Real-Time Analytics • Unstructured / semi- New Hardware structured Architectures • Commodity servers • Cloud Computing • Horizontal Scaling
- 3. Is there a better way?
- 4. Terminology RDBMS MongoDB Table Collection Row(s) JSON Document Index Index Join Embedding & Linking Partition Shard Partition Key Shard Key
- 5. Lets build a Spring Data MongoDB App!
- 6. Welcome to Dev News User Story 1: As a user I should be able to create “News Articles”
- 7. What is a News Article? { title: “What is new in 2.2 MongoDB”, date : new Date(), author : “Fred” text : “.......” }
- 8. Example 1 - Create
- 9. Welcome to Dev News User Story 1: As a user I should be able to create “News Articles” User Story 2: As a user I should be able to find a “News Articles” by Name
- 10. Example 2 - Query
- 11. Example 3 - Repo
- 12. Welcome to Dev News User Story 1: As a user I should be able to create “News Articles” User Story 2: As a user I should be able to find a “News Articles” by Name User Story 3: As a user I should be able to comment on “News Articles”
- 13. What is a Comment? { title: “What is new in 2.2 MongoDB”, date : new Date(), author : “Fred” text : “.......” tags : [“mongodb”, “nosql”] comments : [ {author : “chris”, text: “this is great” , date : new Date()}, {author : “tom”, text: “rock on”, date : new Date()} ]
- 14. Example 4 - Comments
- 15. Welcome to Dev News User Story 1: As a user I should be able to create “News Articles” User Story 2: As a user I should be able to find a “News Articles” by Name User Story 3: As a user I should be able to comment on “News Articles” User Story 4: As a user I want to know how many comments are on a “Articles”
- 16. What is a Comment? { title: “What is new in 2.2 MongoDB”, .... comments : [ {author : “chris”, text: “this is great” , date : new Date()}, {author : “tom”, text: “rock on”, date : new Date()} ], comments_count : 2 }
- 17. Example 5 - Inc
- 18. Least durability - Don't use! Driver Primary write apply in memory
- 19. Wait for Journal Sync Same as RDBMS Driver Primary write getLastError apply in memory j:true Write to journal
- 20. More durability Driver Primary Secondary write getLastError apply in memory w:2 replicate
- 21. Replica Set Data Protection Multiple copies of the data Spread across Data Centers, AZs High Availability Automated Failover Automated Recovery
- 22. Replica Sets Java Write App Primary Asynchronous Replication Read Secondary Secondary
- 23. Replica Sets Java Write App Primary Read Secondary Secondary
- 24. Replica Sets Java App Primary Write Primary Automatic Election of new Primary Read Secondary
- 25. Replica Sets Java App Recovering Write New primary serves data Primary Read Secondary
- 26. Replica Sets Java App Secondary Write Primary Read Secondary
- 27. Durability Summary Memory Journal Secondary Other Data Center RDBMS Default "Fire & Forget" w=1 w=1 j=true w="majority" w=n w="myTag" Less More
- 28. Example 6 - Write Concern
- 30. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1
- 31. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1 v1
- 32. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1 Read v1
- 33. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1 reads v1 Read v1
- 34. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1 reads v1 Read v1 Update v2
- 35. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1 reads v1 Read v1 Update v2 v2
- 36. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1 reads v1 Read v1 Update v2 Read v2
- 37. Understanding Eventual Consistency Thread #1 Primary Secondary Insert v1 reads v1 Read v1 Update v2 reads v2 Read v2
- 38. Understanding Eventual Consistency Thread #1 Primary Secondary Thread #2 Insert v1 Read v1 Update v2 Read v2
- 39. Understanding Eventual Consistency Thread #1 Primary Secondary Thread #2 Insert v1 Read v1 Update v2 Read v2
- 40. Understanding Eventual Consistency Thread #1 Primary Secondary Thread #2 Insert v1 v1 does not exist on Read Secondary v1 Update v2 Read v2
- 41. Understanding Eventual Consistency Thread #1 Primary Secondary Thread #2 Insert v1 v1 does not exist on Read Secondary v1 Update v2 Reads v1 but Primary at v2 Read v2 Read v2
- 42. Example 7 - Eventual Consistency
- 43. Questions • MongoDB 2.2 – Improved concurrency – Tag-aware sharding – Aggregation framework – TTL collections • Free online MongoDB training – Develop – Deploy – Classes start Oct. 2012
Editor's Notes
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- #3: Evolutions in computing are significantly impacting the traditional RDBMS.\nVolume of data is magnitudes higher than previously\ntens of millions quereis a second\nstructured and unstructured data\ncloud computing and storage\nscaling horizontally not vertically due reaching the capacity. buying a bigger box\ncommodity servers not expensive sans\nand developers are not doing waterfall development anymore, they want to be more agile\nflexible in their data models..\n
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