MongoDB Strange Loop 2009
1 like1,730 views
MongoDB is an open-source, schema-free, document-oriented database that provides high performance, flexibility and scalability. It uses JSON-like documents with dynamic schemas, instead of the traditional table-based relational database structure. MongoDB is especially useful for web applications, caching, and scaling to handle large volumes of data. While it is less suited to highly transactional workloads or problems requiring SQL, MongoDB provides a simple interface and scales horizontally across commodity servers.
![Post
{author: “mike”,
date: new Date(),
text: “my blog post...”,
tags: [“mongodb”, “strange”, “loop”]}](https://image.slidesharecdn.com/strangeloop-091026083822-phpapp02/85/MongoDB-Strange-Loop-2009-22-320.jpg)
![New post
post = {author: “mike”,
date: new Date(),
text: “my blog post...”,
tags: [“mongodb”, “strange”, “loop”]}
db.posts.save(post)](https://image.slidesharecdn.com/strangeloop-091026083822-phpapp02/85/MongoDB-Strange-Loop-2009-24-320.jpg)
![Migration: adding titles
• Easy - just start adding them:
post = {author: “mike”,
date: new Date(),
text: “another blog post...”,
tags: [“strange”, “loop”],
title: “Review from Strange Loop”}
post_id = db.posts.save(post)](https://image.slidesharecdn.com/strangeloop-091026083822-phpapp02/85/MongoDB-Strange-Loop-2009-33-320.jpg)
More Related Content
What's hot (20)
Similar to MongoDB Strange Loop 2009 (20)
More from Mike Dirolf (11)
Recently uploaded (20)
MongoDB Strange Loop 2009
- 3. RDBMS • Great for many applications • Shortcomings • Scalability • Flexibility
- 4. CAP theorem • Consistency • Availability • Tolerance to network Partitions • Pick two http://www.cs.berkeley.edu/~brewer/cs262b-2004/PODC-keynote.pdf
- 5. ACID vs BASE • Atomicity • Basically Available • Consistency • Soft state • Isolation • Eventually consistent • Durability
- 6. Compared to key-value stores
- 9. Schema-free • Loosening constraints - added flexibility • Dynamically typed languages • Migrations
- 10. Dynamic queries • Administration • Ease of development • Familiarity
- 12. Replication
- 13. Auto-sharding
- 14. Many supported platforms / languages
- 15. Good at • The web • Caching • High volume data • Scalability
- 16. Less good at • Highly transactional • Ad-hoc business intelligence • Problems that require SQL
- 17. MongoDB Basics
- 18. Document • Unit of storage (think row) • BSON (Binary JSON)
- 19. Collection • Schema-free equivalent of a table • Logical groups of documents • Indexes are per-collection
- 20. _id • Special key • Present in all documents • Unique across a Collection • Any type you want
- 21. Blog back-end
- 22. Post {author: “mike”, date: new Date(), text: “my blog post...”, tags: [“mongodb”, “strange”, “loop”]}
- 23. Comment {author: “eliot”, date: new Date(), text: “great post!”}
- 24. New post post = {author: “mike”, date: new Date(), text: “my blog post...”, tags: [“mongodb”, “strange”, “loop”]} db.posts.save(post)
- 25. Embedding a comment c = {author: “eliot”, date: new Date(), text: “great post!”} db.posts.update({_id: post._id}, {$push: {comments: c}})
- 26. Posts by author db.posts.find({author: “mike”})
- 27. Last 10 posts db.posts.find() .sort({date: -1}) .limit(10)
- 28. Posts in the last week last_week = new Date(2009, 9, 9) db.posts.find({date: {$gt: last_week}})
- 29. Posts ending with ‘Loop’ db.posts.find({text: /loop$/})
- 30. Posts with a tag db.posts.find({tag: “mongodb”}) ... and fast db.posts.ensureIndex({tag: 1})
- 32. Basic paging page = 2 page_size = 15 db.posts.find().limit(page_size) .skip(page * page_size)
- 33. Migration: adding titles • Easy - just start adding them: post = {author: “mike”, date: new Date(), text: “another blog post...”, tags: [“strange”, “loop”], title: “Review from Strange Loop”} post_id = db.posts.save(post)
- 34. Advanced queries • $gt, $lt, $gte, $lte, $ne, $all, $in, $nin • where() db.posts.find({$where: “this.author == ‘mike’”})
- 35. Sharding
- 36. Terminology • Shard key • Chunk • Range of the value space • (collection, key, min_val, max_val) • Shard • Single node (or replica pair) • Responsible for set of chunks
- 39. Other cool stuff • Aggregation and map reduce • Capped collections • Unique indexes • Mongo shell • GridFS
- 40. • Download MongoDB http://www.mongodb.org • Try it out • Let us know what you think!
- 41. • http://www.mongodb.org • irc.freenode.net#mongodb • mongodb-user on google groups • @mongodb, @mdirolf • [email protected] • http://www.slideshare.net/mdirolf
Editor's Notes
- #2: Mike Dirolf, 10gen sponsors MongoDB Thanks Plan: A little about what makes MongoDB interesting Some flavor for the API / querying possibilities Sharding Questions
- #5: C - The client perceives that a set of operations has occurred all at once A - Every operation must terminate in an intended response P - Operations will complete even if individual components are unavailable Horizontal scaling necessitates P, so forced to choose C or A
- #6: Transaction is all or none Consistent state at beginning + end of transaction Transaction behaves as if only operation Upon completion, operation will not be reversed Sacrifice consistency for availability
- #9: More complex than just Key-Value Secondary Indexes Embedded Documents
- #11: Compare to Couch
- #12: No Separate Caching Layer
- #13: Master-Slave Replica Pairs For Failover
- #14: Infinite Scalability
- #25: Collection (logical groupings of documents) Indexes are per-collection
- #37: Order Preserving Partitioning Split Migrate
- #38: Process Diagram Global vs Targeted Operations Config Servers Use Two Phase Commit
- #39: Server Layout
- #41: blog post twitter