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Dynamoid

Dynamoid is an ORM for Amazon's DynamoDB for Ruby applications. It provides similar functionality to ActiveRecord and improves on Amazon's existing HashModel by providing better searching tools and native association support.

DynamoDB is not like other document-based databases you might know, and is very different indeed from relational databases. It sacrifices anything beyond the simplest relational queries and transactional support to provide a fast, cost-efficient, and highly durable storage solution. If your database requires complicated relational queries and transaction support, then this modest Gem cannot provide them for you, and neither can DynamoDB. In those cases you would do better to look elsewhere for your database needs.

But if you want a fast, scalable, simple, easy-to-use database (and a Gem that supports it) then look no further!

Installation

Installing Dynamoid is pretty simple. First include the Gem in your Gemfile:

gem 'dynamoid', '~> 1'

Prerequisities

Dynamoid depends on the aws-sdk, and this is tested on the current version of aws-sdk (> 2), rails (> 4). Hence the configuration as needed for aws to work will be dealt with by aws setup.

Here are the steps to setup aws-sdk.

gem 'aws-sdk', '~>2'

(or) include the aws-sdk in your Gemfile.

NOTE: Dynamoid-1.0 doesn't support aws-sdk Version 1 (Use Dynamoid Major Version 0 for aws-sdk 1)

Configure AWS access: Reference

For example, to configure AWS access:

Create config/initializers/aws.rb as follows:

  Aws.config.update({
    region: 'us-west-2',
    credentials: Aws::Credentials.new('REPLACE_WITH_ACCESS_KEY_ID', 'REPLACE_WITH_SECRET_ACCESS_KEY'),
  })

For a full list of the DDB regions, you can go here.

Then you need to initialize Dynamoid config to get it going. Put code similar to this somewhere (a Rails initializer would be a great place for this if you're using Rails):

  Dynamoid.configure do |config|
    config.adapter = 'aws_sdk_v2' # This adapter establishes a connection to the DynamoDB servers using Amazon's own AWS gem.
    config.namespace = "dynamoid_app_development" # To namespace tables created by Dynamoid from other tables you might have. Set to nil to avoid namespacing.
    config.warn_on_scan = true # Output a warning to the logger when you perform a scan rather than a query on a table.
    config.read_capacity = 100 # Read capacity for your tables
    config.write_capacity = 20 # Write capacity for your tables
    config.endpoint = 'https://localhost:3000' # [Optional]. If provided, it communicates with the DB listening at the endpoint. This is useful for testing with [Amazon Local DB] (https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Tools.DynamoDBLocal.html). 
  end

Once you have the configuration set up, you need to move on to making models.

Setup

You must include Dynamoid::Document in every Dynamoid model.

class User
  include Dynamoid::Document

end

Table

Dynamoid has some sensible defaults for you when you create a new table, including the table name and the primary key column. But you can change those if you like on table creation.

class User
  include Dynamoid::Document

  table :name => :awesome_users, :key => :user_id, :read_capacity => 400, :write_capacity => 400
end

These fields will not change an existing table: so specifying a new read_capacity and write_capacity here only works correctly for entirely new tables. Similarly, while Dynamoid will look for a table named awesome_users in your namespace, it won't change any existing tables to use that name; and if it does find a table with the correct name, it won't change its hash key, which it expects will be user_id. If this table doesn't exist yet, however, Dynamoid will create it with these options.

Fields

You'll have to define all the fields on the model and the data type of each field. Every field on the object must be included here; if you miss any they'll be completely bypassed during DynamoDB's initialization and will not appear on the model objects.

By default, fields are assumed to be of type :string. Other built-in types are :integer, :number, :set, :array, :datetime, :boolean, and :serialized. If built-in types do not suit you, you can use a custom field type represented by an arbitrary class, provided that the class supports a compatible serialization interface. The primary use case for using a custom field type is to represent your business logic with high-level types, while ensuring portability or backward-compatibility of the serialized representation.

You get magic columns of id (string), created_at (datetime), and updated_at (datetime) for free.

class User
  include Dynamoid::Document

  field :name
  field :email
  field :rank, :integer
  field :number, :number
  field :joined_at, :datetime
  field :hash, :serialized

end

You can optionally set a default value on a field using either a plain value or a lambda:

  field :actions_taken, :integer, {default: 0}
  field :joined_at, :datetime, {default: ->(){Time.now}}

To use a custom type for a field, suppose you have a Money type.

  class Money
    # ... your business logic ...
    
    def dynamoid_dump
      "serialized representation as a string"
    end
    
    def self.dynamoid_load(serialized_str)
      # parse serialized representation and return a Money instance
      Money.new(...)
    end
  end
  
  class User
    include Dynamoid::Document
    
    field :balance, Money
  end

If you want to use a third-party class (which does not support #dynamoid_dump and .dynamoid_load) as your field type, you can use an adapter class providing .dynamoid_dump and .dynamoid_load class methods for your third-party class. (.dynamoid_load can remain the same from the previous example; here we just add a level of indirection for serializing.) Example:

  # Third-party Money class
  class Money; end
  
  class MoneyAdapter
    def self.dynamoid_load(money_serialized_str)
      Money.new(...)
    end
    
    def self.dynamoid_dump(money_obj)
      money_obj.value.to_s
    end
  end
  
  class User
    include Dynamoid::Document
    
    field :balance, MoneyAdapter
  end

Lastly, you can control the data type of your custom-class-backed field at the DynamoDB level. This is especially important if you want to use your custom field as a numeric range or for number-oriented queries. By default custom fields are persisted as a string attribute, but your custom class can override this with a .dynamoid_field_type class method, which would return either :string or :number. (DynamoDB supports some other attribute types, but Dynamoid yet does not.)

Associations

Just like in ActiveRecord (or your other favorite ORM), Dynamoid uses associations to create links between models.

The only supported associations (so far) are has_many, has_one, has_and_belongs_to_many, and belongs_to. Associations are very simple to create: just specify the type, the name, and then any options you'd like to pass to the association. If there's an inverse association either inferred or specified directly, Dynamoid will update both objects to point at each other.

class User
  include Dynamoid::Document

  ...

  has_many :addresses
  has_many :students, :class => User
  belongs_to :teacher, :class_name => :user
  belongs_to :group
  has_one :role
  has_and_belongs_to_many :friends, :inverse_of => :friending_users

end

class Address
  include Dynamoid::Document

  ...

  belongs_to :address # Automatically links up with the user model

end

Contrary to what you'd expect, association information is always contained on the object specifying the association, even if it seems like the association has a foreign key. This is a side effect of DynamoDB's structure: it's very difficult to find foreign keys without an index. Usually you won't find this to be a problem, but it does mean that association methods that build new models will not work correctly -- for example, user.addresses.new returns an address that is not associated to the user. We'll be correcting this soon.

Validations

Dynamoid bakes in ActiveModel validations, just like ActiveRecord does.

class User
  include Dynamoid::Document

  ...

  validates_presence_of :name
  validates_format_of :email, :with => /@/
end

To see more usage and examples of ActiveModel validations, check out the ActiveModel validation documentation.

Callbacks

Dynamoid also employs ActiveModel callbacks. Right now, callbacks are defined on save, update, destroy, which allows you to do before_ or after_ any of those.

class User
  include Dynamoid::Document

  ...

  before_save :set_default_password
  after_create :notify_friends
  after_destroy :delete_addresses
end

Usage

Object Creation

Dynamoid's syntax is generally very similar to ActiveRecord's. Making new objects is simple:

u = User.new(:name => 'Josh')
u.email = '[email protected]'
u.save

Save forces persistence to the datastore: a unique ID is also assigned, but it is a string and not an auto-incrementing number.

u.id # => "3a9f7216-4726-4aea-9fbc-8554ae9292cb"

To use associations, you use association methods very similar to ActiveRecord's:

address = u.addresses.create
address.city = 'Chicago'
address.save

Querying

Querying can be done in one of three ways:

Address.find(address.id)              # Find directly by ID.
Address.where(:city => 'Chicago').all # Find by any number of matching criteria... though presently only "where" is supported.
Address.find_by_city('Chicago')       # The same as above, but using ActiveRecord's older syntax.

And you can also query on associations:

u.addresses.where(:city => 'Chicago').all

But keep in mind Dynamoid -- and document-based storage systems in general -- are not drop-in replacements for existing relational databases. The above query does not efficiently perform a conditional join, but instead finds all the user's addresses and naively filters them in Ruby. For large associations this is a performance hit compared to relational database engines.

You can also limit the number of evaluated records, or select a record from which to start, to support pagination:

Address.eval_limit(5).start(address) # Only 5 addresses.

For large queries that return many rows, Dynamoid can use AWS' support for requesting documents in batches:

#Do some maintenance on the entire table without flooding DynamoDB
Address.all(batch_size: 100).each { |address| address.do_some_work; sleep(0.01) }
Address.limit(10_000).batch(100). each {  } #batch specified as part of a chain

Consistent Reads

Querying supports consistent reading. By default, DynamoDB reads are eventually consistent: if you do a write and then a read immediately afterwards, the results of the previous write may not be reflected. If you need to do a consistent read (that is, you need to read the results of a write immediately) you can do so, but keep in mind that consistent reads are twice as expensive as regular reads for DynamoDB.

Address.find(address.id, :consistent_read => true)  # Find an address, ensure the read is consistent.
Address.where(:city => 'Chicago').consistent.all    # Find all addresses where the city is Chicago, with a consistent read.

Range Finding

If you have a range index, Dynamoid provides a number of additional other convenience methods to make your life a little easier:

User.where("created_at.gt" => DateTime.now - 1.day).all
User.where("created_at.lt" => DateTime.now - 1.day).all

It also supports .gte and .lte. Turning those into symbols and allowing a Rails SQL-style string syntax is in the works. You can only have one range argument per query, because of DynamoDB's inherent limitations, so use it sensibly!

Concurrency

Dynamoid supports basic, ActiveRecord-like optimistic locking on save operations. Simply add a lock_version column to your table like so:

class MyTable
  ...
  
  field :lock_version, :integer
  
  ...
end

In this example, all saves to MyTable will raise an Dynamoid::Errors::StaleObjectError if a concurrent process loaded, edited, and saved the same row. Your code should trap this exception, reload the row (so that it will pick up the newest values), and try the save again.

Calls to update and update! also increment the lock_version, however they do not check the existing value. This guarantees that a update operation will raise an exception in a concurrent save operation, however a save operation will never cause an update to fail. Thus, update is useful & safe only for doing atomic operations (e.g. increment a value, add/remove from a set, etc), but should not be used in a read-modify-write pattern.

Credits

Dynamoid borrows code, structure, and even its name very liberally from the truly amazing Mongoid. Without Mongoid to crib from none of this would have been possible, and I hope they don't mind me reusing their very awesome ideas to make DynamoDB just as accessible to the Ruby world as MongoDB.

Also, without contributors the project wouldn't be nearly as awesome. So many thanks to:

Running the tests

Running the tests is fairly simple. In one window, run bin/start_dynamodblocal, and in the other, use rake.

Build Status Coverage Status

Copyright

Copyright (c) 2012 Josh Symonds.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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