MongoDB at CodeMash 2.0.1.0

open-source, high-performance, schema-free, document-oriented database

One-Size-Fits-All No Longer RDBMS (Oracle, MySQL) Non-relational New gen. OLAP (vertica, aster, greenplum) operational stores (“NoSQL”)

NoSQL really means: non-relational next generation operational datastores and databases

Scaling out no joins + light transactional semantics = horizontally scalable architectures

Data models no joins + light transactional semantics = horizontally scalable architectures important side effect : new data models = improved ways to develop applications

Data Models Key/Value Tabular Document-based

Data Models Key/Value memcached, dynamo, voldemort Tabular bigtable, cassandra, hbase, hypertable Document-oriented mongodb, couchdb. JSON stores

JSON-style documents

Schema-free • Loosening constraints - added ﬂexibility • Dynamically typed languages • Migrations

Dynamic queries • Administration • Ease of development • Familiarity

Focus on performance

Replication

Auto-sharding

Many supported platforms / languages

Good at • The web • Caching • High volume data • Scalability

Less good at • Highly transactional • Ad-hoc business intelligence • Problems that require SQL

MongoDB Basics

Document • Unit of storage (think row) • BSON (Binary JSON) • Represented is language dependent

Collection • Schema-free equivalent of a table • Logical groups of documents • Indexes are per-collection

_id • Special key • Present in all documents • Unique across a Collection • Any type you want

Blog back-end

Post {author: “mike”, date: new Date(), text: “my blog post...”, tags: [“mongodb”, “codemash”]}

Comment {author: “eliot”, date: new Date(), text: “great post!”}

New post post = {author: “mike”, date: new Date(), text: “my blog post...”, tags: [“mongodb”, “codemash”]} db.posts.save(post)

Embedding a comment c = {author: “eliot”, date: new Date(), text: “great post!”} db.posts.update({_id: post._id}, {$push: {comments: c}})

Posts by author db.posts.find({author: “mike”})

Last 10 posts db.posts.find() .sort({date: -1}) .limit(10)

Posts in the last week last_week = new Date(2010, 0, 6) db.posts.find({date: {$gt: last_week}})

Posts ending with ‘Mash’ db.posts.find({text: /Mash$/})

Posts with a tag db.posts.find({tags: “mongodb”}) ... and fast db.posts.ensureIndex({tags: 1})

Counting posts db.posts.count() db.posts.find({author: “mike”}).count()

Basic paging page = 2 page_size = 15 db.posts.find().limit(page_size) .skip(page * page_size)

Migration: adding titles • Easy - just start adding them: post = {author: “mike”, date: new Date(), text: “another blog post...”, tags: [“codemash”], title: “Review from CodeMash”} post_id = db.posts.save(post)

Advanced queries • $gt, $lt, $gte, $lte, $ne, $all, $in, $nin • where() db.posts.find({$where: “this.author == ‘mike’”})

Other cool stuff • Aggregation and map reduce • Capped collections • Unique indexes • Mongo shell • GridFS

• Download MongoDB http://www.mongodb.org • Try it out • Let us know what you think!

• http://www.mongodb.org • irc.freenode.net#mongodb • mongodb-user on google groups • @mongodb, @mdirolf • mike@10gen.com • http://www.slideshare.net/mdirolf

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MongoDB at CodeMash 2.0.1.0

by Mike Dirolf

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