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Object-document mapper and lightweight API adapter for ElasticSearch


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Elastictastic is an object-document mapper and lightweight API adapter for ElasticSearch. Elastictastic's primary use case is to define model classes which use ElasticSearch as a primary document-oriented data store, and to expose ElasticSearch's search functionality to query for those models.

Build Status


Elastictastic requires Ruby 1.9 and ActiveSupport 3. Elastictastic does not require Rails, but if you do run Rails, Elastictastic will only work with Rails 3.

You will also need a running ElasticSearch instance (or cluster). For local development, you can easily download and install a copy, or your preferred package manager might have it available.


Just add it to your Gemfile:

gem 'elastictastic'

Defining models

Elastictastic's setup DSL will be familiar to those who have used other Ruby object-document mappers such as Mongoid. Persisted models mix in the Elastictastic::Document module, and fields are defined with the field class macro:

class Post
  include Elastictastic::Document

  field :title

The field method can take options; the options available here are simply those that are available in a field mapping in ElasticSearch. Elastictastic is (mostly) agnostic to the options you pass in; they're just used to generate the mapping for ElasticSearch.

By default, ElasticSearch assigns fields a string type. An example of how one might define a field with some options:

class Post
  include Elastictastic::Document

  field :comments_count, :type => :integer, :store => 'yes'


ElasticSearch allows you to define multi-fields, which index the same data in multiple ways. To define a multi-field in Elastictastic, you may pass a block to the field macro, in which the alternate fields are defined using the same DSL:

field :title, :type => 'string', :index => 'analyzed' do
  field :unanalyzed, :type => 'string', :index => 'not_analyzed'

The arguments passed to the outer field method are used for the default field mapping; thus, the above is the same as the following:

field :title,
  :type => 'string',
  :fields => {
    :unanalyzed => { :type => 'string', :index => 'not_analyzed' }

Document Boost

Defining a document boost will increase or decrease a document's score in search results based on the value of a field in the document. A boost of 1.0 is neutral. To define a boost field, use the boost class macro:

class Post
  include Elastictastic::Document

  field :score, :type => 'integer'
  boost :score

By default, if the boost field is empty, a score of 1.0 will be applied. You can override this by passing a 'null_value' option into the boost method.

Embedded objects

ElasticSearch supports deep nesting of properties by way of object fields. To define embedded objects in your Elastictastic models, use the embed class macro:

class Post
  include Elastictastic::Document

  embed :author
  embed :recent_comments, :class_name => 'Comment' 

The class that's embedded should include the Elastictastic::NestedDocument mixin, which exposes the same configuration DSL as Elastictastic::Document but does not give the class the functionality of a top-level persistent object:

class Author
  include Elastictastic::NestedDocument

  field :name
  field :email, :index => 'not_analyzed'

Parent-child relationships

You may define parent-child relationships for your documents using the has_many and belongs_to macros:

class Blog
  include Elastictastic::Document

  has_many :posts
class Post
  include Elastictastic::Document

  belongs_to :blog

Unlike in, say, ActiveRecord, an Elastictastic document can only specify one parent (belongs_to) relationship. A document can have as many children (has_many) as you would like.

The parent/child relationship has far-reaching consequences in ElasticSearch, and as such you will generally interact with child documents via the parent's association collection. For instance, this is the standard way to create a new child instance:

post =

The above will return a new Post object whose parent is the blog; the blog.posts collection will retain a reference to the transient post instance, and will auto-save it when the blog is saved.

You may also create a child instance independently and then add it to a parent's child collection; however, you must do so before saving the child instance, as ElasticSeach requires types that define parents to have a parent. The following code block has the same outcome as the previous one:

post =
blog.posts << post

In most other respects, the blog.posts collection behaves the same as a search scope (more on that below), except that enumeration methods (#each, #map, etc.) will return unsaved child instances along with instances persisted in ElasticSearch.

Syncing your mapping

Before you start creating documents with Elastictastic, you need to make ElasticSearch aware of your document structure. To do this, use the sync_mapping method:


If you have a complex multi-index topology, you may want to consider using ElasticSearch templates to manage mappings and other index settings; Elastictastic doesn't provide any explicit support for this at the moment, although you can use e.g. Post.mapping to retrieve the mapping structure which you can then merge into your template.

Reserved attributes

All Elastictastic::Document models have an id and an index field, which combine to define the full resource locator for the document in ElasticSearch. You should not define fields or methods with these names. You may, however, set the id explicitly on new (not yet saved) model instances.


Elastictastic documents include all the usual ActiveModel functionality: validations, lifecycle hooks, observers, dirty-tracking, mass-assignment security, and the like. If you would like to squeeze a bit of extra performance out of the library at the cost of convenience, you can include the Elastictastic::BasicDocument module instead of Elastictastic::Document.


Elastictastic models are persisted the usual way, namely by calling save:

post =
post.title = 'You know, for search.'

To retrieve a document from the data store, use find:


You can look up multiple documents by ID:

Post.find('123', '456')

You can also pass an array of IDs; the following will return a one-element array:


For child documents, you must perform GET requests using the parent's association collection:

post =

blog.posts.find( # this will return the post
Post.find(       # but this won't!

Specifying the index

Elastictastic defines a default index for your documents. If you're using Rails, the default index is your application's name suffixed with the current environment; outside of Rails, the default index is simply "default". You can change this using the default_index configuration key.

When you want to work with documents in an index other than the default, use the in_index class method:

new_post = Post.in_index('my_special_index').new # create in an index
post = Post.in_index('my_special_index').find('123') # retrieve from an index

To retrieve documents from multiple indices at the same time, pass a hash into find where the keys are index names and the values are the IDs you wish to retrieve from that index:

Post.find('default' => ['123', '456'], 'my_special_index' => '789')

Bulk operations

If you are writing a large amount of data to ElasticSearch in a single process, use of the bulk API is encouraged. To perform bulk operations using Elastictastic, simply wrap your operations in a bulk block:

Elastictastic.bulk do
  params[:posts].each do |post_params|
    post =

All create, update, and destroy operations inside the block will be executed in a single bulk request when the block completes. If you are performing an indefinite number of operations in a bulk block, you can pass an :auto_flush option to flush the bulk buffer after the specified number of operations:

Elastictastic.bulk(:auto_flush => 100) do
  150.times {! }

The above will perform two bulk requests: the first after the first 100 operations, and the second when the block completes.

You can alternatively pass an :auto_flush_bytes option to flush the bulk buffer after it reaches the specified number of bytes:

Elastictastic.bulk(:auto_flush_bytes => 48 * 100) do
  150.times {! }

Assuming, as in the specs in this project. that '!' sends a 48-byte operation to Elastic Search, this will cause two batches of requests: one with 100 Posts, and one with 50.

Note that the nature of bulk writes means that any operation inside a bulk block is essentially asynchronous: instances are not created, updated, or destroyed immediately upon calling save or destroy, but rather when the bulk block exits. You may pass a block to save and destroy to provide a callback for when the instance is actually persisted and its local state updated. Let's say, for instance, we wish to expand the example above to pass the IDs of the newly created posts to our view layer:

@ids = []
Elastictastic.bulk do
  params[:posts].each do |post_params|
    post = do |e|
      @ids <<

If the save was not successful (due to a duplicate ID or a version mismatch, for instance), the e argument to the block will be passed an exception object; if the save was successful, the argument will be nil.

Concurrent document creation

When Elastictastic creates a document with an application-defined ID, it uses the _create verb in ElasticSearch, ensuring that a document with that ID does not already exist. If the document does already exist, an Elastictastic::ServerError::DocumentAlreadyExistsEngineException will be raised. In the case where multiple processes may attempt concurrent creation of the same document, you can gracefully handle concurrent creation using the ::create_or_update class method on your document class. This will first attempt to create the document; if a document with that ID already exists, it will then load the document and modify it using the block passed:

Post.create_or_update('1') do |post|
	post.title = 'My Post'

In the above case, Elastictastic will first attempt to create a new post with ID "1" and title "My Post". If a Post with that ID already exists, it will load it, set its title to "My Post", and save it. The update uses the ::update method (see next section) to ensure that concurrent modification doesn't cause data to be lost.

Optimistic locking

Elastictastic provides optimistic locking via ElasticSearch's built-in document versioning. When a document is retrieved from persistence, it carries a version, which is a number that increments from 1 on each update. When Elastictastic models are updated, the document version that it carried when it was loaded is passed into the update operation; if this version does not match ElasticSearch's current version for that document, it indicates that another process has modified the document concurrently, and an Elastictastic::ServerError::VersionConflictEngineException is raised. This prevents data loss through concurrent conflicting updates.

The easiest way to guard against concurrent modification is to use the ::update class method to make changes to existing documents. Consider the following example:

Post.update('12345') do |post|
  post.title = 'New Title'

In the above, the Post with ID '12345' is loaded from ElasticSearch and yielded to the block. When the block completes, the instance is saved back to ElasticSearch. If this save results in a version conflict, a new instance is loaded from ElasticSearch and the block is run again. The process repeats until a successful update.

This method will work inside a bulk operation, but note that if the first update generates a version conflict, additional updates will occur in discrete requests, not as part of any bulk operation.

If you wish to safely update documents retrieved from a search scope (see below), use the update_each method:

Post.query { constant_score { filter { term(:blog_id => 1) }}}.update_each do |post|
  post.title = post.title.upcase


ElasticSearch is, above all, a search tool. Accordingly, aside from direct lookup by ID, all retrieval of documents is done via the search API. Elastictastic models have class methods corresponding to the top-level keys in the ElasticSearch search API; you may chain these much as in ActiveRecord or Mongoid:

Post.query(:query_string => { :query => 'pizza' }).facets(:cuisine => { :term => { :field => :tags }}).from(10).size(10)
# Generates {"query": {"query_string": {"query": "pizza"}}, "facets": {"cuisine": {"term": {"field": "tags" }}}, "from": 10, "size": 10}

Elastictastic also has an alternate block-based query builder, if you prefer:

Post.query do
  query_string { query('pizza') }
end.facets { cuisine { term { field :tags }}}.from(10).size(10)
# Same effect as the previous example

The scopes that are generated by the preceding calls act as collections of matching documents; thus all the usual Enumerable methods are available:

Post.query(:query_string => { :query => 'pizza' }).each do |post|
  puts post.title

You may access other components of the response using hash-style access; this will return a Hashie::Mash which allows hash-style or object-style access:

Post.facets(:cuisine => { :term => { :field => :tags }})['facets'].each_pair do |name, facet|
  facet.terms.each { |term| puts "#{term.term}: #{term.count}" }

You can also call count on a scope; this will give the total number of documents matching the query.

In some situations, you may wish to access metadata about search results beyond simply the result document. To do this, use the #find_each method, which yields a Hashie::Mash containing the raw ElasticSearch hit object in the second argument:

Post.highlight { fields(:title => {}) }.find_each do |post, hit|
  puts "Post #{} matched the query string in the title field: #{hit.highlight['title']}"

Search scopes also expose a #find_in_batches method, which also yields the raw hit. The following code gives the same result as the previous example:

Post.highlight { fields(:title => {}) }.find_in_batches do |batch|
  batch.each do |post, hit|
    puts "Post #{} matched the query string in the title field: #{hit.highlight['title']}"

Both find_each and find_in_batches accept a :batch_size option.

Support & Bugs

If you find a bug, feel free to open an issue on GitHub. Pull requests are most welcome.

For questions or feedback, hit up our mailing list at or find outoftime on the #elasticsearch IRC channel on Freenode.


Elastictastic is distributed under the MIT license. See the attached LICENSE file for all the sordid details.


Object-document mapper and lightweight API adapter for ElasticSearch







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