MongoDB NoSQL and all of its awesomeness
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MongoDB is a scalable, high-performance, open-source NoSQL database that uses a JSON-style document storage format called BSON. It offers advantages such as flexibility with a dynamic schema, fast indexing, and easy scaling, but has drawbacks including non-transactional properties and document size limitations. The document also provides examples of CRUD operations and tips for efficient usage.
![Mongo Document Storage Structure
Document structure inside of the "BlogPost" collection:
{
'id': 12345,
'name': 'Hello World',
'author_id': 112233,
'content': 'This is my blog post content. Woot woot!',
'comments': [
{'user_id': 4321, 'comment': 'Awesome blog!'},
{'user_id': 1234, 'comment': 'Totally Agree'}
],
'tags': ['hello', 'world']
}](https://image.slidesharecdn.com/mongodbandallofitsawesomeness-120330144700-phpapp02/85/MongoDB-NoSQL-and-all-of-its-awesomeness-9-320.jpg)
![Demo Code: Insert
doc2 = {'id': 67890,
doc = {'id': 12345,
'name': 'Another Hello World',
'name': 'Hello World',
'author_id': 112233,
'author_id': 112233,
'content': 'This is my second blog post',
'content': 'This is my blog post content. Woot woot!',
'comments': [
'comments': [
{'user_id': 4321, 'comment': 'Even better than
{'user_id': 4321, 'comment': 'Awesome blog!'},
the first!'},
{'user_id': 1234, 'comment': 'Totally Agree'}
{'user_id': 1234, 'comment': 'You rock'}
],
],
'tags': ['hello', 'world']
'tags': ['jimmy', 'buffet']
}
}
db.blogpost.insert(doc)
db.blogpost.insert(doc2)](https://image.slidesharecdn.com/mongodbandallofitsawesomeness-120330144700-phpapp02/85/MongoDB-NoSQL-and-all-of-its-awesomeness-11-320.jpg)
MongoDB NoSQL and all of its awesomeness
- 1. MongoDB and NoSQL ...and all of its awesomeness....
- 2. What is MongoDB? ● MongoDB (from 'humongous') is a scalable, high-performance, open source NoSQL database. ● JSON-style document storage ○ actually BSON (Binary JSON) ● Awesome
- 3. Terminology ● db > collection > document ● collection = table ● document = row ● Database is made of of collections ● Collections are made up of documents
- 4. Why Should I Use MongoDB (Pros) ● Flexible: database changes are easy because it's a dynamic schema. ● Fast: Indexes are stored in memory which alleviates need for additional cache dependency ● Easy to scale with replica sets, sharding ● Atomic updates: All fail or all succeed
- 5. Why to Not Use MongoDB (Cons) ● Non transactional ● Document Size Limitations 16MB ● Ambiguous keys when shortened
- 6. MongoDB Syntax INSERT > db.foo.insert(doc_or_docs) SELECT > db.foo.find(criteria) UPDATE > db.foo.update(criteria, updates, upsert, multi) DELETE > db.foo.remove(criteria)
- 7. Blog Post Example ● Create a Blog Post ● Retrieve a Blog Post ● Update a Blog Post ○ $inc, $set, $unset, $push, $pushAll, $addToSet and $each, $pop, $pull, $pullAll, $rename ● Delete a Blog Post
- 8. Define the Model class BlogPost(): In SQL world, most of you already can id see this would require 3 separate name tables: content 1. BlogPosts author_id 2. Comments 3. Tags class Comments(): author_id comment blog_id class Tags(): name blog_id
- 9. Mongo Document Storage Structure Document structure inside of the "BlogPost" collection: { 'id': 12345, 'name': 'Hello World', 'author_id': 112233, 'content': 'This is my blog post content. Woot woot!', 'comments': [ {'user_id': 4321, 'comment': 'Awesome blog!'}, {'user_id': 1234, 'comment': 'Totally Agree'} ], 'tags': ['hello', 'world'] }
- 10. Demo Enough talking...show some freaking code...
- 11. Demo Code: Insert doc2 = {'id': 67890, doc = {'id': 12345, 'name': 'Another Hello World', 'name': 'Hello World', 'author_id': 112233, 'author_id': 112233, 'content': 'This is my second blog post', 'content': 'This is my blog post content. Woot woot!', 'comments': [ 'comments': [ {'user_id': 4321, 'comment': 'Even better than {'user_id': 4321, 'comment': 'Awesome blog!'}, the first!'}, {'user_id': 1234, 'comment': 'Totally Agree'} {'user_id': 1234, 'comment': 'You rock'} ], ], 'tags': ['hello', 'world'] 'tags': ['jimmy', 'buffet'] } } db.blogpost.insert(doc) db.blogpost.insert(doc2)
- 12. Demo Code: Retrieve Return the whole doc: ● db.blogpost.findOne() ● db.blogpost.findOne({'id': 12345}) Only return specific fields: ● db.blogpost.findOne({}, {'name':1, 'author_id':1}) Exclude specific fields: ● db.blogpost.findOne({}, {'comments': 0}) Find all blog posts by author 112233: ● db.blogpost.find({'id': 112233}).pretty()
- 13. Demo Code: Update Update all posts by Author_id: ● db.blogpost.update({'author_id': 112233}, {'$set':{'is_featured': true}}, false, true) Update all posts by author_id using tag "buffet": ● db.blogpost.update({'author_id': 112233, 'tags': 'buffet'}, {'$set':{'rock_star': true}}, false, true) Update all posts by author_id where comment == 'You rock': ● db.blogpost.update({'author_id': 112233, 'comments.comment': 'You rock'}, {'$set':{'comments.$.about_rock': true}}, false, true) Add tag to all posts by author_id: ● db.blogpost.update({'author_id': 112233}, {'$addToSet':{'tags': 'word up'}}, false, true)
- 14. Demo Code: Delete Remove by document id: ● db.blogpost.remove({'id': 12345}) Remove all posts by author_id: ● db.blogpost.remove({'author_id': 112233}) Remove all blog posts: ● db.blogpost.remove({})
- 15. Tips ● Use small keys ○ a collection with 1,000,000 documents with keys like: {'first_name': 'Troy', 'last_name': 'Grosfield'} will take longer to search than a 1,000,000 documents with small keys such as: {'fn': 'Troy', 'ln': 'Grosfield'} ● Be smart with your indexes ● Design documents wisely
- 16. Hope you Enjoyed! twitter: @troygrosfield website: http://troygrosfield.com blog: http://blog.troygrosfield.com Resources: ● http://mongodb.org/