Scott Hernandez

©"Copyright"2010"10gen"Inc."

Release History

•  First release – February 2009 •  v1.0 - August 2009 •  v1.2 - December 2009 – MapReduce, ++ •  v1.4 - March 2010 – Concurrency, Geo •  V1.6 - August 2010 – Sharding, Replica Sets •  V1.8 – March 2011 – Journaling, Geosphere •  V2.0 -- Sep 2011 – V1 Indexes, Concurrency

Types of Non-Relational Data Models

•  Key-value stores •  Document stores •  Column-oriented databases •  Graph databases

What is MongoDB

•  Document Store •  Horizontally Scalable •  High Performance

MongoDB vs Traditional RDBMS

databases"

contain"rows"

server"

contain"tables""

collections"documents"

schema"

joins"

Terminology

RDBMS& Mongo&Table,"View" Collection"

Row(s)" JSON"Document"

Index" Index"

Join" Embedded"Document"

Partition" Shard"

Partition"Key" Shard"Key"

MongoDB is a Single-Master System

•  All writes are to a primary (master) •  Failure of the primary is detected, and a new

one is elected •  Application writes get an error if there is no

quorum to elect a new master •  Reads can continue

Consistency Models

•  Relational databases support transactions •  Can only see committed changes •  Commits/aborts span multiple changes •  Read-only transaction flavors

•  Read committed, repeatable read, etc

•  Single vs Multi-Master

Single Master

•  All writes go to a single master and then replicated

•  Replication can provide read scalability •  Writing becomes a bottleneck

•  Physical limitations (seek time) •  Throughput of a single I/O subsystem

Single Master - Sharding

•  Partition the primary key space via hashing •  Set up a duplicate system for each shard

•  The write-rate limitation now applies to each shard

•  Joins or aggregation across shards are problematic

•  Can the data be re-sharded on a live system? •  Can shards be re-balanced on a live system?

MongoDB Storage Management

•  Memory-mapped Database files •  Files are (pre)allocated as needed •  Indexes (B*-trees) point to documents

Documents

Blog Post Document"" p = { author: “sridhar”," date: new Date()," title: “Using the C# driver with MongoDB”," tags: [“NoSQL”, “Mongo”, “MongoDB”]}""> db.posts.save(p)"

Querying

>db.posts.find()"" { _id : ObjectId("4c4ba5c0672c685e5e8aabf3")," author : “sridhar", " date : “Mon Jul 11 2011 19:47:11 GMT-0700 (PDT)", " title: “Using the C# driver with MongoDB”," tags: [“NoSQL”, “Mongo”, “MongoDB”]} " "

Secondary Indexes Create index on any Field in Document"" // 1 means ascending, -1 means descending"" >db.posts.ensureIndex({author: 1})"" >db.posts.find({author: ʻsridhar'}) " " { _id : ObjectId("4c4ba5c0672c685e5e8aabf3")," author : “sridhar", " ... }"

Query Operators •  Conditional Operators "

•  $all, $exists, $mod, $ne, $in, $nin, $nor, $or, $size, $type"•  $lt, $lte, $gt, $gte""// find posts with any tags "> db.posts.find( {tags: {$exists: true }} )""// find posts matching a regular expression"> db.posts.find( {author: /^sri*/i } )""// count posts by author"> db.posts.find( {author: ʻsridharʼ} ).count()"

Atomic Operations

•  $set, $unset, $inc, $push, $pushAll, $pull, $pullAll, $bit"

> comment = { author: “fred”, " date: new Date()," text: “Interesting blog post”}"" > db.posts.update( { _id: “...” }, "

" "$push: {comments: comment} );""

Nested Documents

{ _id : ObjectId("4c4ba5c0672c685e5e8aabf3"), " author : “sridhar"," date : “Mon Jul 11 2011 19:47:11 GMT-0700 (PDT)", " text : “Using the C# driver with MongoDB"," tags : [ “NoSQL", “Mongo", “MongoDB" ]," comments : ["

"{"" "author : "Fred","" "date : “Mon Jul 11 2011 20:51:03 GMT-0700 (PDT)","" "text : “Interesting blog post"""}"

]}"

Indexes // Index nested documents > db.posts.ensureIndex( “comments.author”:1 ) ! db.posts.find({‘comments.author’:’Fred’})

// Index on tags > db.posts.ensureIndex( tags: 1) > db.posts.find( { tags: ’Mongo’ } ) // geospatial index > db.posts.ensureIndex( “author.location”: “2d” ) > db.posts.find( “author.location” : { $near : [22,42] } )

MongoDB – More

•  Geo-spatial queries •  Require a geo index •  Find points near a given point •  Find points within a polygon/sphere

•  Built-in Map-Reduce •  The caller provides map and reduce functions

written in JavaScript

Scaling MongoDB

•  Replication - Read scalability •  Master/Slave •  Replica Sets

•  Sharding – Read and write scalability •  Collections are sharded •  Each shard is served by its own replica set •  Shard key ranges are automatically balanced

Primary"

Secondary"

Secondary"

Primary"

Secondary"

Secondary"

Primary"

Secondary"

Secondary"

Primary"

Secondary"

Secondary"

Key Range"0..30"

Key Range"31..60"

Key Range"61..90"

Key Range"91.. 100"

MongoS" MongoS" MongoS"

Read"Write"

MongoS"

MongoDB Access

•  Drivers are available in many languages •  10gen supported

•  C, C# (.Net), C++, Erlang, Haskell, Java, JavaScript, Perl, PHP, Python, Ruby, Scala

•  Community supported •  Clojure, ColdFusion, F#, Go, Groovy, Lua, R •  http://www.mongodb.org/display/DOCS/Overview+-

+Writing+Drivers+and+Tools

MongoDB Availability

•  Source •  https://github.com/mongodb/mongo

•  Server •  License: AGPL •  http://www.mongodb.org/downloads

•  Drivers •  License: Apache •  http://www.mongodb.org/display/DOCS/Drivers

@mongodb"

©"Copyright"2010"10gen"Inc."

conferences,"appearances,"and"meetups"http://www.10gen.com/events"

"

http://bit.ly/mongoQ""

Facebook""""""""""|"""""""""Twitter"""""""""|"""""""""LinkedIn"http://linkd.in/joinmongo"

download at mongodb.org

We’re"Hiring"!"Engineers,"Sales,"Evangelist,"Marketing,"Support,"Developers""

•  Use cases •  Case studies

Use cases and customers

Content Management

Gaming

Analytics

©"Copyright"2010"10gen"Inc."

try at try.mongodb.org

@mongodb"

©"Copyright"2010"10gen"Inc."

conferences,"appearances,"and"meetups"http://www.10gen.com/events"

"

http://bit.ly/mongoQ""

Facebook""""""""""|"""""""""Twitter"""""""""|"""""""""LinkedIn"http://linkd.in/joinmongo"

download at mongodb.org

We’re"Hiring"!"sridhar@10gen.com"

@snanjund"