Mysql to mongo

MYSQL TO MONGO (FTW) Thinking Differently About Schema Design

@AJSHARP Alex Sharp Lead Developer, OptimisCorp alexjsharp.com github.com/ajsharp

CVBEAST Mongo has many cool features such as schema- free, aggregation w map/reduce and many others Side project interested more in domain modeling more than performance and scaling benefits of Mongo EMBEDDED OBJECTS

CVBEAST App to represent people’s curriculum vitae, but not in an academic sense

CVBEAST Focus on “micro” experiences not suitable for a typical CV (deﬁnitely not suitable for a resumé)

CVBEAST Simple object model, centered around highlighting attributes of a person

CVBEAST Started out building with MySQL, b/c it’s familiar

OBJECT MODEL Person has a CV has many Experience has many ... ... ...

OBJECT MODEL Person has a CV links, tags, and has many other arbitrary properties Experience has many ... ... ...

RELATIONAL SCHEMA people - id - name - ... cvs - id - person_id - ... experiences - id - cv_id - ...

RELATIONAL SCHEMA Lots of pointless JOINs

RELATIONAL SCHEMA people - id - name - ... cvs - id - person_id - ... experiences - id - cv_id - ...

RELATIONAL SCHEMA people - id - name - ... cvs tags - id - id - name - person_id - ... - ... links experiences - id - name - id - ... - cv_id - ...

not b/c of premature optimization this bothers me

It misrepresents the object model at the storage layer

It also became difﬁcult to work with despite my familiarity with MySQL

It makes sense to store object relationships in ﬁrst-class entities/documents/tables

But true object properties should be stored as properties

Not relationships.

Especially when properties have no practical meaning without the parent

CAVEAT This is not always the case. ;-) if you need to: * store LOTS of embedded objects (i.e. papermill)

EXAMPLE Experience Links

EXPERIENCE.LINKS = [...] Dead-simple collection of links attached to an experience

RUBY MODEL CODE class Person include Mongoid::Document field :keywords, :type => Array index :keywords index 'cv.experiences.tags' end

class Experience include Mongoid::Document embeds_many :links end class Link include Mongoid::Document field :url field :title embedded_in :experience, :inverse_of => :links end

class Experience include Mongoid::Document embeds_many :links end Both models are embedded in the person collection class Link include Mongoid::Document field :url field :title embedded_in :experience, :inverse_of => :links end

EXPERIENCE.LINKS = [...] A link is only relevant inside the context of an experience object.

EXPERIENCE.LINKS = [...] In other words, it is a property, not a relationship.

EXPERIENCE.LINKS = [...] Mongo brings the storage layer closer to the object model

EXPERIENCE.LINKS = [...] { "title": "Presented at MongoLA", "links": [ { "title": "Event Site", "url": "http://www.10gen.com/conferences/mongola2011"}, { "title": "Slides", "url": "http://alexjsharp.com/posts/mongola-2010-slides"} ] }

EXAMPLE Embedded Search

MYSQL An exercise in masochism

The difﬁculty in MySQL came in working with properties of a person

These properties are represented as tables

And tables must be joined

SIMPLE SEARCH QUERY select * from people inner join cvs on cvs.person_id = people.id inner join experiences on experiences.cv_id = cvs.id inner join tags on tags.experience_id = experiences.id where tags.name = 'ruby';

INDEXES NEEDED - tags.experience_id - tags.name - experiences.cv_id - cvs.person_id

Seems extremely unnecessary for such a simple object model

MONGO An exercise in ... not masochism

Embedded objects make this query easy.

MONGO DOCUMENT “SCHEMA” {"name": "Alex Sharp", "cv": { "experiences": [ { "title": "spoke at MongoLA", "date" : "Thu Jan 13 2011", "tags" : ["mongodb", "speaking"] }, {"title": "..."} ] } }

MONGO DOCUMENT “SCHEMA” {"name": "Alex Sharp", "cv": { "experiences": [ { "title": "spoke at MongoLA", "date" : "Thu Jan 13 2011", "tags" : ["mongodb", "speaking"] }, {"title": "..."} ] } } we want to search for these

RUBY MODEL CODE class Person include Mongoid::Document field :keywords, :type => Array index :keywords index 'cv.experiences.tags' end

RUBY MODEL CODE class Cv include Mongoid::Document embeds_many :experiences end class Experience include Mongoid::Document field :tags, :type => Array, :default => [] embedded_in :cv, :inverse_of => :experiences embeds_many :links after_save lambda { |exp| exp.cv.person.update_keywords } end

RUBY MODEL CODE class Cv include Mongoid::Document simple property embeds_many :experiences end (not relationship) class Experience include Mongoid::Document field :tags, :type => Array, :default => [] embedded_in :cv, :inverse_of => :experiences embeds_many :links after_save lambda { |exp| exp.cv.person.update_keywords } end

RUBY SEARCH CODE class Person # i.e. db.people.find({"cv.experiences.tags": "ruby"}) def self.search_by_tag(term) collection.find('cv.experiences.tags' => 'ruby') end end

COMPARISON select * from people inner join cvs on cvs.person_id = people.id inner join experiences on experiences.cv_id = cvs.id inner join tags on tags.experience_id = experiences.id where tags.name = 'ruby'; vs db.people.find('cv.experiences.tags' => 'ruby')

WINS: IMPEDENCE MIS-MATCH Object persistence format is closer to application usage format

WINS: F(X)-ALITY Plus, we don’t lose any functionality.

WINS: FAMILIARITY Indexing principles are extremely familiar to relational database users.

WINS: FAMILIARITY Only simpler ;)

WINS: SIMPLICITY Query syntax is simple.

WINS: SIMPLICITY Dot notation > JOIN semantics ﬁlth

SUMMARY Mongo is perfectly suited for an app like CVBeast.

SUMMARY Where a relational DB forces storing object properties as relationships

SUMMARY Mongo narrows this mismatch considerably

SUMMARY A CV is a document...

SUMMARY So a document-oriented datastore seems appropriate.

SUMMARY Many object models have this tree-like structure.

SUMMARY Be willing to step outside of your comfort zone

SUMMARY And use Mongo when it’s practical.

http://www.luca-canducci.com	326
http://alexjsharp.com	46
http://lanyrd.com	32
http://www.alexjsharp.com	7
http://paper.li	1
http://www.mefeedia.com	1

Mysql to mongo

by Alex Sharp on Jan 13, 2011

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Mysql to mongo — Presentation Transcript