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Introduction to MongoDB
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Mike Dirolf
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Intro to MongoDB given 4/2010 at Philly ETE
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Introduction to MongoDB
1.
open-‐source, high-‐performance,
document-‐oriented database
2.
Non-relational
Operational Stores (“NoSQL”) New Gen. OLAP RDBMS (vertica, aster, greenplum) (Oracle, MySQL)
3.
NoSQL Really Means:
non-‐relational, next-‐generation operational datastores and databases
4.
no joins +
no complex transactions Horizontally Scalable Architectures
5.
no joins +
no complex transactions New Data Models
6.
New Data Models improved
ways to develop applications?
7.
Data Models
Key / Value memcached, Dynamo Tabular BigTable Document Oriented MongoDB, CouchDB, JSON stores
8.
• memcached scalability &
performance • key/value • RDBMS depth of functionality
9.
JSON-style Documents
represented as BSON {“hello”: “world”} x16x00x00x00x02hello x00x06x00x00x00world x00x00 http://bsonspec.org
10.
Flexible “Schemas”
{“author”: “eliot”, {“author”: “mike”, “text”: “...”, “text”: “...”} “tags”: [“mongodb”]}
11.
Dynamic Queries
12.
Atomic Update
Modifiers
13.
Focus on Performance
14.
Replication
master slave master master slave slave slave slave master master slave master
15.
Auto-sharding
Shards mongod mongod mongod ... Config mongod mongod mongod Servers mongod mongod mongod mongos mongos ... client
16.
Many Supported Platforms /
Languages
17.
Best Use Cases
T Scaling Out Caching The Web High Volume
18.
Less Good At
highly transactional ad-‐hoc business intelligence problems that require SQL
19.
A Quick Aside _id
special key present in all documents unique across a Collection any type you want
20.
Post {author: “mike”, date:
new Date(), text: “my blog post...”, tags: [“mongodb”, “intro”]}
21.
Comment {author: “eliot”, date:
new Date(), text: “great post!”}
22.
New Post post =
{author: “mike”, date: new Date(), text: “my blog post...”, tags: [“mongodb”, “intro”]} db.posts.save(post)
23.
Embedding a Comment c
= {author: “eliot”, date: new Date(), text: “great post!”} db.posts.update({_id: post._id}, {$push: {comments: c}})
24.
Posts by Author db.posts.find({author:
“mike”})
25.
Last 10 Posts db.posts.find()
.sort({date: -‐1}) .limit(10)
26.
Posts Since April
1 april_1 = new Date(2010, 3, 1) db.posts.find({date: {$gt: april_1}})
27.
Posts Ending With
‘Tech’ db.posts.find({text: /Tech$/})
28.
Posts With a
Tag db.posts.find({tags: “mongodb”}) ...and Fast (multi-‐key indexes) db.posts.ensureIndex({tags: 1})
29.
Indexing / Querying
on Embedded Docs (dot notation) db.posts.ensureIndex({“comments.author”: 1}) db.posts.find({“comments.author”: “eliot”})
30.
Counting Posts db.posts.count() db.posts.find({author: “mike”}).count()
31.
Basic Paging page =
2 page_size = 15 db.posts.find().limit(page_size) .skip(page * page_size)
32.
Migration: Adding Titles
(just start adding them) post = {author: “mike”, date: new Date(), text: “another blog post...”, tags: [“mongodb”], title: “MongoDB for Fun and Profit”} post_id = db.posts.save(post)
33.
Advanced Queries
$gt, $lt, $gte, $lte, $ne, $all, $in, $nin db.posts.find({$where: “this.author == ‘mike’ || this.title == ‘foo’”})
34.
Other Cool Stuff aggregation
and map/reduce capped collections unique indexes mongo shell GridFS geo
35.
slides will be
up on http://dirolf.com Download MongoDB http://www.mongodb.org and let us know what you think @mdirolf @mongodb
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