Download as KEY, PPTX
![# Post
{
title: “Getting started with MongoDB”,
body: “blah blah blah ... “,
created: Date(’09-06-2010’),
tags: [1, 2]
}
# Comments # Tags
{
{
id: 1,
body: “I did not have relations..”,
name: “example”
user_id: 1,
},
{
post_id: 1,
id: 2,
created: Date(’09-06-2010’),
name: “lol”
}
}](https://image.slidesharecdn.com/mongodb-100614182454-phpapp02/85/Introduction-to-MongoDB-24-320.jpg)
![# Posts
{
title: “Getting started with MongoDB”,
body: “blah blah blah ... “,
created: Date(’09-06-2010’),
Array tags: [ ‘example’, ‘bill clinton’ ],
comments: [
{ author: “Bill”, comment: “I did not have relations” },
{ author: “Monica”, comment: “LOL” }
]
}
Array of hashes](https://image.slidesharecdn.com/mongodb-100614182454-phpapp02/85/Introduction-to-MongoDB-26-320.jpg)
Introduction to MongoDB
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- 5. Introduction Document Relational Orientated Database Database
- 6. Introduction Document Relational Orientated Database Database NoSQL Bra.
- 7. What is MongoDB? • Scalable high-performance open source, document- orientated database • Built for speed • Rich document based queries • Full index support • Replication and Failover • Auto Sharding • Map / Reduce
- 8. Why use MongoDB? • SQL was invented in the 70’s to store data • MongoDB stores documents / objects • We work with objects (Ruby) • We need databases to persist our objects • So why not just store objects directly?
- 9. What its greatfor • Websites • Caching • High scalability • Storage of program objects and JSON
- 10. What its notgreat for • Highly transactional applications • Problems requiring SQL
- 11.
- 12.
- 13. When I Say Think Database Database
- 14. When I Say Think Database Database • Made up of multiple collections • Are created on-the-fly when first referenced
- 15.
- 16. When I Say Think Collection Table
- 17. When I Say Think Collection Table • Schema-less • Indexable by one or more keys • Created on-the-fly when first referenced • Capped collections: Fixed size, older records dropped after limit reached
- 18.
- 19. When I Say Think Document Record / Row
- 20. When I Say Think Document Record / Row • Stored in a collection • Can have _id key - Works like primary keys in MySQL • Supports relationships: embedded or referential • Document storage in BSON
- 21. When I Say Think Document Record / Row • Stored in a collection • Can have _id key - Works like primary keys in MySQL • Supports relationships: embedded or referential • Document storage in BSON JSONS Binary Brother
- 22.
- 23. Referential / Normalised • Same as SQL • “First class” objects that are at top level • Many to many relationships has_many User Blog Post belongs_to
- 24. # Post { title: “Getting started with MongoDB”, body: “blah blah blah ... “, created: Date(’09-06-2010’), tags: [1, 2] } # Comments # Tags { { id: 1, body: “I did not have relations..”, name: “example” user_id: 1, }, { post_id: 1, id: 2, created: Date(’09-06-2010’), name: “lol” } }
- 25. Embedded • Embedded is pre-joining • Embed when document always appears with parent • 4MB document size limit Blog Post Post Title Post Body Comments
- 26. # Posts { title: “Getting started with MongoDB”, body: “blah blah blah ... “, created: Date(’09-06-2010’), Array tags: [ ‘example’, ‘bill clinton’ ], comments: [ { author: “Bill”, comment: “I did not have relations” }, { author: “Monica”, comment: “LOL” } ] } Array of hashes
- 27. Ruby MongoDB
- 28. MongoMapper http://github.com/jnunemaker/mongomapper • Typecasting • Callbacks (ActiveSupport Callbacks) • Validations • Connection and database can differ per document • Has create, update methods • Find: id, ids, :all, :first, :last • Associations (has_one, has_many, many_to_many)
- 29. http://www.mongoid.org • Named scopes / chainable criteria • Versioning of your documents • Full callback support on documents AND embedded documents • Proper master/slave distribution • Optimised for use with extremely large datasets This is what we use!
- 30.
- 31. Conclusions • NoSQL is pretty scary / We’re used to SQL • It’s the future.
- 32. Chat to usonline: twitter: @platform45
- 33.
Editor's Notes
- #4 Old man - SQL DoD - MongoDB
- #5 Old man - SQL DoD - MongoDB
- #6 Old man - SQL DoD - MongoDB
- #7 Document Orientated: It isnt stored as records and tables, information stored as documents or objects Build for speed: No transaction log / removed anything that would slow it down Rich document based queries: Users can find documents based on any search criteria / similar to SQL Full index support: Index on any attribute - similar to SQL Replication and failover: Supports replication of data between servers for failover and redundancy Auto sharding: Scale horizontally without compromising functionality - EVERY EASY - NO JOINS Map Reduce - Database itself can perform advanced aggregation and data processing
- #9 Websites: Object orientated programming languages - Easy persistence of objects Caching: Extremely fast High scalability: Easy Auto sharding and replication and failover
- #10 * SQL writes to transaction log (for data durability) * Performance loss * MongoDB doesn’t do this - Uses replication
- #11 Similarities and Differences between SQL and document orientated databases
- #12 No need for any rake db:creates or rake db:setup
- #13 No need for any rake db:creates or rake db:setup
- #14 Like a table in MySQL EXCEPT!!! Capped collections: Extremely fast, atomic writes, good for log files
- #15 Like a table in MySQL EXCEPT!!! Capped collections: Extremely fast, atomic writes, good for log files
- #19 Next up is relations - which is one of the major differences or advantages over SQL
- #20 First class - objects that can stand alone (users -> blog posts)
- #21 Similar to MySQL Tags: Array of ID’s Many to many Comments: belongs_to / has_many
- #24 Using mongodb with ruby
- #25 First up: Mongomapper by jnunemaker Works for OrderedList Typecasting: Mongodb doesnt understand types - MongoMapper creates the typecasting
- #26 Durran - Hashrocket