Introduction to MongoDB
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This document provides an introduction to MongoDB, highlighting its features as a scalable, high-performance, open-source, document-oriented database designed for modern applications. It discusses the benefits of MongoDB over traditional SQL databases, such as schema-less collection structures and simplified queries, while also noting its limitations in highly transactional applications. Additionally, it touches on indexing, document models, updates, and deployment, concluding with a call for job applications at Pipal Tech Ventures.
![Understanding the Document Model.
var p = {
‘_id’: ‘3432’,
‘author’: DBRef(‘User’, 2),
‘title’: ‘Introduction to MongoDB’,
‘body’: ‘MongoDB is an open sources.. ‘,
‘timestamp’: Date(’01-04-12’),
‘tags’: [‘MongoDB’, ‘NoSQL’],
‘comments’: [{‘author’: DBRef(‘User’, 4),
‘date’: Date(’02-04-12’),
‘text’: ‘Did you see.. ‘,
‘upvotes’: 7, … ]
}
> db.posts.save(p);](https://image.slidesharecdn.com/mongodb-120401144140-phpapp01/85/Introduction-to-MongoDB-11-320.jpg)
![What about Queries? So Simple
// find posts which has ‘MongoDB’ tag.
> db.posts.find({tags: ‘MongoDB’});
// find posts by author’s comments.
> db.posts.find({‘comments.author’:
DBRef(‘User’,2)}).count();
// find posts written after 31st March.
> db.posts.find({‘timestamp’: {‘gte’: Date(’31-03-12’)}});
// find posts written by authors around [22, 42]
> db.posts.find({‘author.location’: {‘near’:[22, 42]});
$gt, $lt, $gte, $lte, $ne, $all, $in, $nin, count, limit, skip, group, etc…](https://image.slidesharecdn.com/mongodb-120401144140-phpapp01/85/Introduction-to-MongoDB-13-320.jpg)
Introduction to MongoDB
- 1. Introduction to MongoDB Raviteja Dodda Co-Founder, Pipal Tech Ventures [email protected] Twitter, Facebook - @raviteja2007 April 1st, 2012
- 2. The Great Divide MongoDB - Sweet Spot: Easy, Flexible and Scalable
- 3. What is MongoDB ? • Scalable High-Performance Open-source, Document-orientated database. • Built for Speed • Rich Document based queries for Easy readability. • Full Index Support for High Performance. • Replication and Failover for High Availability. • Auto Sharding for Easy Scalability. • Map / Reduce for Aggregation.
- 4. Why use MongoDB? • SQL was invented in the 70’s to store data. • MongoDB stores documents (or) objects. • Now-a-days, everyone works with objects (Python/Ruby/Java/etc.) • And we need Databases to persist our objects. Then why not store objects directly ? • Embedded documents and arrays reduce need for joins. No Joins and No-multi document transactions.
- 5. What is MongoDB great for? • RDBMS replacement for Web Applications. • Semi-structured Content Management. • Real-time Analytics & High-Speed Logging. • Caching and High Scalability Web 2.0, Media, SAAS, Gaming HealthCare, Finance, Telecom, Government
- 6. Not great for? • Highly Transactional Applications. • Problems requiring SQL. Some Companies using MongoDB in Production
- 7. Let’s Dive in !
- 8. When I say Think Database Database • Made up of Multiple Collections. • Created on-the-fly when referenced for the first time.
- 9. When I say Think Collection Table • Schema-less, and contains Documents. • Indexable by one/more keys. • Created on-the-fly when referenced for the first time. • Capped Collections: Fixed size, older records get dropped after reaching the limit.
- 10. When I say Think Document Record/Row • Stored in a Collection. • Can have _id key – works like Primary keys in MySQL. • Supported Relationships – Embedded (or) References. • Document storage in BSON (Binary form of JSON).
- 11. Understanding the Document Model. var p = { ‘_id’: ‘3432’, ‘author’: DBRef(‘User’, 2), ‘title’: ‘Introduction to MongoDB’, ‘body’: ‘MongoDB is an open sources.. ‘, ‘timestamp’: Date(’01-04-12’), ‘tags’: [‘MongoDB’, ‘NoSQL’], ‘comments’: [{‘author’: DBRef(‘User’, 4), ‘date’: Date(’02-04-12’), ‘text’: ‘Did you see.. ‘, ‘upvotes’: 7, … ] } > db.posts.save(p);
- 12. Secondary Indexes Create Index on any field in the document // 1 means ascending, -1 means descending > db.posts.ensureIndex({‘author’: 1}); //Index Nested Documents > db.posts.ensureIndex(‘comments.author’: 1); // Index on tags > db.posts.ensureIndex({‘tags’: 1}); // Geo-spatial Index > db.posts.ensureIndex({‘author.location’: ‘2d’});
- 13. What about Queries? So Simple // find posts which has ‘MongoDB’ tag. > db.posts.find({tags: ‘MongoDB’}); // find posts by author’s comments. > db.posts.find({‘comments.author’: DBRef(‘User’,2)}).count(); // find posts written after 31st March. > db.posts.find({‘timestamp’: {‘gte’: Date(’31-03-12’)}}); // find posts written by authors around [22, 42] > db.posts.find({‘author.location’: {‘near’:[22, 42]}); $gt, $lt, $gte, $lte, $ne, $all, $in, $nin, count, limit, skip, group, etc…
- 14. What about Updates? Atomic Operations makes it simple db.posts.update({_id: ‘3432’}, {‘title’: ‘Introduction to MongoDB (updated)’, ‘text’: ‘Updated text’, ${addToSet: {‘tags’: ‘webinar’}}); $set, $unset $push, $pull, $pop, $addToSet $inc, $decr, many more… Where are my joins and transactions? !!!
- 15. Some Cool features • Geo-spatial Indexes for Geo-spatial queries. $near, $within_distance, Bound queries (circle, box) • GridFS Stores Large Binary Files. • Map/Reduce GROUP BY in SQL, map/reduce in MongoDB.
- 17. Replica Sets
- 18. Sharding
- 19. How do we use MongoDB at Pipal Python MongoDB MongoEngine PyMongo based ORM – A Separate Topic ! Btw, Pipal is hiring at Bangalore Backend Engineers, Frontend Engineers, System-Administrators Send us your resume at [email protected]
- 20. Questions? Next Steps: http://mongodb.org, Twitter: @mongodb Thank You Stay Hungry, Stay Foolish !!! - Steve Jobs