KEMBAR78
Introduction to MongoDB | PDF
open-­‐source,	
  high-­‐performance,	
  
 document-­‐oriented	
  database
Non-relational
                         Operational Stores
                                    (“NoSQL”)




New Gen. OLAP                                     RDBMS
(vertica,	
  aster,	
  greenplum)               (Oracle,	
  MySQL)
NoSQL Really Means:
 non-­‐relational,	
  next-­‐generation	
  
 operational	
  datastores	
  and	
  databases
no	
  joins
+   no	
  complex	
  transactions

Horizontally Scalable
        Architectures
no	
  joins
+   no	
  complex	
  transactions

    New Data Models
New Data Models
improved	
  ways	
  to	
  develop	
  applications?
Data Models
           Key	
  /	
  Value
      memcached,	
  Dynamo

             Tabular
              BigTable

     Document	
  Oriented
MongoDB,	
  CouchDB,	
  JSON	
  stores
• memcached
scalability	
  &	
  performance



                                      • key/value



                                                                            •   RDBMS




                                             depth	
  of	
  functionality
JSON-style Documents
           represented	
  as	
  BSON

      {“hello”:	
  “world”}

  x16x00x00x00x02hello
  x00x06x00x00x00world
  x00x00


                            http://bsonspec.org
Flexible “Schemas”

                        {“author”:	
  “eliot”,
{“author”:	
  “mike”,
                        	
  “text”:	
  “...”,
	
  “text”:	
  “...”}
                        	
  “tags”:	
  [“mongodb”]}
Dynamic Queries
Atomic Update
  Modifiers
Focus on Performance
Replication
                            master   slave

        master
                            master   slave


slave       slave   slave   master   master

                             slave   master
Auto-sharding
                   Shards
          mongod   mongod    mongod
                                            ...
Config     mongod   mongod    mongod
Servers

mongod

mongod

mongod
                   mongos    mongos   ...


                    client
Many Supported
Platforms / Languages
Best Use Cases
                                        T

Scaling	
  Out
                              Caching
                 The	
  Web

            High	
  Volume
Less Good At
     highly	
  transactional


ad-­‐hoc	
  business	
  intelligence


problems	
  that	
  require	
  SQL
A Quick Aside
_id                  special	
  key
  present	
  in	
  all	
  documents
 unique	
  across	
  a	
  Collection
           any	
  type	
  you	
  want
Post

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

{author:	
  “eliot”,
	
  date:	
  new	
  Date(),
	
  text:	
  “great	
  post!”}
New Post
post	
  =	
  {author:	
  “mike”,
	
  	
  date:	
  new	
  Date(),
	
  	
  text:	
  “my	
  blog	
  post...”,
	
  	
  tags:	
  [“mongodb”,	
  “intro”]}

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 Since April 1

april_1	
  =	
  new	
  Date(2010,	
  3,	
  1)

db.posts.find({date:	
  {$gt:	
  april_1}})
Posts Ending With ‘Tech’


db.posts.find({text:	
  /Tech$/})
Posts With a Tag
db.posts.find({tags:	
  “mongodb”})


          ...and Fast
                 (multi-­‐key	
  indexes)

db.posts.ensureIndex({tags:	
  1})
Indexing / Querying
    on Embedded Docs
                            (dot	
  notation)

db.posts.ensureIndex({“comments.author”:	
  1})

db.posts.find({“comments.author”:	
  “eliot”})
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
                                        (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)
Advanced Queries

             $gt,	
  $lt,	
  $gte,	
  $lte,	
  $ne,	
  $all,	
  $in,	
  $nin


db.posts.find({$where:	
  “this.author	
  ==	
  ‘mike’	
  ||
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  this.title	
  ==	
  ‘foo’”})
Other Cool Stuff
aggregation	
  and	
  map/reduce
capped	
  collections
unique	
  indexes
mongo	
  shell
GridFS
geo
slides	
  will	
  be	
  up	
  on	
  http://dirolf.com




Download MongoDB
         http://www.mongodb.org




   and	
  let	
  us	
  know	
  what	
  you	
  think
       @mdirolf	
  	
  	
  	
  @mongodb

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.
  • 12.
    Atomic Update Modifiers
  • 13.
  • 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.
  • 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},                                  {$push:  {comments:  c}})
  • 24.
  • 25.
    Last 10 Posts db.posts.find()                .sort({date:  -­‐1})                .limit(10)
  • 26.
    Posts Since April1 april_1  =  new  Date(2010,  3,  1) db.posts.find({date:  {$gt:  april_1}})
  • 27.
    Posts Ending With‘Tech’ db.posts.find({text:  /Tech$/})
  • 28.
    Posts With aTag 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.
  • 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