Fuzzy line matching with rails (Tire) and ElasticSearch

Question

I have a Rails application that is now configured with ElasticSearch and Tire gem to search by model, and I was wondering how I can configure my application to fuzzy match rows at specific indices in the model. I have my model configured to index things like name, description, etc., but I want to fuzzy string matching on some of them, and I'm not sure where to do it. I want to add my code below if you want to comment! Thanks!

In the controller:

def search @resource = Resource.search(params[:q], :page => (params[:page] || 1), :per_page =>15, load: true ) end 

In the model:

 class Resource < ActiveRecord::Base include Tire::Model::Search include Tire::Model::Callbacks belongs_to :user has_many :resource_views, :class_name => 'UserResourceView' has_reputation :votes, source: :user, aggregated_by: :sum attr_accessible :title, :description, :link, :tag_list, :user_id, :youtubeID acts_as_taggable mapping do indexes :id, :index => :not_analyzed indexes :title, :analyzer => 'snowball', :boost => 40 indexes :tag_list, :analyzer => 'snowball', :boost => 8 indexes :description, :analyzer => 'snowball', :boost => 2 indexes :user_id, :analyzer => 'snowball' end end 

Answer 1

Try creating your own analyzers to achieve other launch-related features, etc. Check out my example (this example also uses Mongoid and attachments, don't look at it if you don't need one):

 class Document include Mongoid::Document include Mongoid::Timestamps include Tire::Model::Search include Tire::Model::Callbacks field :filename, type: String field :md5, type: String field :tags, type: String field :size, type: String index({md5: 1}, {unique: true}) validates_uniqueness_of :md5 DEFAULT_PAGE_SIZE = 10 settings :analysis => { :filter => { :ngram_filter => { :type => "edgeNGram", :min_gram => 2, :max_gram => 12 }, :custom_word_delimiter => { :type => "word_delimiter", :preserve_original => "true", :catenate_all => "true", } }, :analyzer => { :index_ngram_analyzer => { :type => "custom", :tokenizer => "standard", :filter => ["lowercase", "ngram_filter", "asciifolding", "custom_word_delimiter"] }, :search_ngram_analyzer => { :type => "custom", :tokenizer => "standard", :filter => ["standard", "lowercase", "ngram_filter", "custom_word_delimiter"] }, :suggestions => { :tokenizer => "standard", :filter => ["suggestions_shingle"] } } } do mapping { indexes :id, index: :not_analyzed indexes :filename, :type => 'string', :store => 'yes', :boost => 100, :search_analyzer => :search_ngram_analyzer, :index_analyzer => :index_ngram_analyzer indexes :tags, :type => 'string', :store => 'yes', :search_analyzer => :search_ngram_analyzer, :index_analyzer => :index_ngram_analyzer indexes :attachment, :type => 'attachment', :fields => { :content_type => {:store => 'yes'}, :author => {:store => 'yes', :analyzer => 'keyword'}, :title => {:store => 'yes'}, :attachment => {:term_vector => 'with_positions_offsets', :boost => 90, :store => 'yes', :search_analyzer => :search_ngram_analyzer, :index_analyzer => :index_ngram_analyzer}, :date => {:store => 'yes'} } } end def to_indexed_json self.to_json(:methods => [:attachment]) end def attachment path_to_file = "#{Rails.application.config.document_library}#{path}/#{filename}" Base64.encode64(open(path_to_file) { |file| file.read }) end def self.search(query, options) tire.search do query { string "#{query}", :default_operator => :AND, :default_field => 'attachment', :fields => ['filename', 'attachment', 'tags'] } highlight :attachment page = (options[:page] || 1).to_i search_size = options[:per_page] || DEFAULT_PAGE_SIZE from (page -1) * search_size size search_size sort { by :_score, :desc } if (options[:facet]) filter :terms, :tags => [options[:facet]] facet 'global-tags', :global => true do terms :tags end facet 'current-tags' do terms :tags end end end end end 

Hope this helps,