Mongo db japan

Roger Bodamer @rogerb

Baseball World Series Giants lead 3-1 over Rangers

What is MongoDB? quick introduction design session deploy mongodb scaling

MongoDB adoption is very strong 90,000 Database downloads per month

Over 1,000 Production Deployments

Platform and Language support MongoDB is Implemented in C++ for best performance Platforms 32/64 bit • Windows • Linux, Mac OS-X, FreeBSD, Solaris

Platform and Language support MongoDB is Implemented in C++ for best performance Platforms 32/64 bit • Windows • Linux, Mac OS-X, FreeBSD, Solaris Language drivers for • Ruby / Ruby-on-Rails • Java / C# / JavaScript • C / C++ • Erlang • Python, Perl • others... .. and much more ! ..

NoSQL Really Means: non-‐relational, next-‐generation operational datastores and databases

RDBMS (Oracle, MySQL)

RDBMS (Oracle, MySQL) New Gen. OLAP (vertica, aster, greenplum)

RDBMS (Oracle, MySQL) New Gen. Non-relational OLAP Operational (vertica, aster, Stores greenplum) (“NoSQL”)

Philosophy: maximize features -‐ up to the “knee” in the curve, then stop • memcached scalability & performance • key/value • RDBMS depth of functionality

no joins + no complex transactions Horizontally Scalable Architectures

no joins + no complex transactions New Data Models

New Data Models -‐> Improved ways to develop

Terminology RDBMS MongoDB Table Collection Row(s) JSON Document Index Index Join Embedding & Linking Partition Shard Partition Key Shard Key

MongoDB Design Session

MongoDB Design Session Blog Post Document p = {author: “roger”, date: new Date(), text: “Spirited Away”, tags: [“Tezuka”, “Manga”]} >db.posts.save(p)

Query Posts Collection >db.posts.ﬁnd() { _id : ObjectId("4c4ba5c0672c685e5e8aabf3"), author : "roger", date : "Sat Jul 24 2010 19:47:11 GMT-0700 (PDT)", text : "Spirited Away", tags : [ "Tezuka", "Manga" ] } Notes: - _id is unique, but can be anything you’d like

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

Query operators Conditional operators: $ne, $in, $nin, $mod, $all, $size, $exists, $type, .. $lt, $lte, $gt, $gte, $ne, ... // ﬁnd posts with any tags >db.posts.ﬁnd({tags: {$exists: true}})

Query operators Conditional operators: $ne, $in, $nin, $mod, $all, $size, $exists, $type, .. $lt, $lte, $gt, $gte, $ne, // find posts with any tags >db.posts.find({tags: {$exists: true}}) Regular expressions: // posts where author starts with r >db.posts.find({author: /^r*/i })

Query operators Conditional operators: $ne, $in, $nin, $mod, $all, $size, $exists, $type, .. $lt, $lte, $gt, $gte, $ne, // find posts with any tags >db.posts.find({tags: {$exists: true}}) Regular expressions: // posts where author starts with k >db.posts.find({author: /^k*/i }) Counting: // posts written by roger >db.posts.find({author: “roger”}).count()

Extending the Schema Adding Comments to Blog comment = {author: “fred”, date: new Date(), text: “Best Movie Ever”} update = { ‘$push’: {comments: comment}} >db.posts.update({_id: “...” }, update)

{ _id : ObjectId("4c4ba5c0672c685e5e8aabf3"), author : "roger", date : "Sat Jul 24 2010 19:47:11 GMT-0700 (PDT)", text : "Spirited Away", tags : [ "Tezuka", "Manga" ], comments : [ { author : "Fred", date : "Sat Jul 24 2010 20:51:03 GMT-0700 (PDT)", text : "Best Movie Ever" } ]}

Secondary Index // create index on nested documents: >db.posts.ensureIndex({"comments.author": 1}) >db.posts.ﬁnd({comments.author:”Fred”})

Deploying MongoDB

Deploying MongoDB Primary Read / Write

Deploying MongoDB Primary Read / Write Replication Secondary

Setting Up MongoDB Primary Read / Write Replication Secondary Replication Secondary for Backup

Setting Up MongoDB Primary Read / Write Replication Secondary Read Replication Secondary for Backup

Setting Up MongoDB Replicaset Primary Read / Write Replication Secondary Read Replication Secondary for Backup

Read Scalability : Replication read ReplicaSet 1 Primary Secondary Secondary write

Write Scalability: Sharding read key range key range key range 0 .. 30 31 .. 60 61 .. 100 ReplicaSet 1 ReplicaSet 2 ReplicaSet 3 Primary Primary Primary Secondary Secondary Secondary Secondary Secondary Secondary write

Monitoring • We like Munin .. • ... but other frameworks work as well • Primary function: • Measure stats over time • Tells you what is going on with your system

MongoDB makes building applications easy Designed a Blog Schema Evolved the Schema Deployed MongoDB Scale MongoDB

MongoDB makes building applications easy Map / Reduce Capped Collections Tail-able Cursors Geo Indexing .. and much more ! ..

download at mongodb.org We’re Hiring ! roger@10gen.com conferences, appearances, and meetups http://www.10gen.com/events Facebook | Twitter | LinkedIn http://bit.ly/mongoG @mongodb http://linkd.in/joinmongo

Mongo db japan

by rogerbodamer on Nov 01, 2010

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