Briefly described typical test search tasks (e.g. full text search, phrase match) and possible solutions. Provided review of the most popular text search gems.

1. SOLVINGTEXT SEARCH
PROBLEMS WITH RUBY ON
RAILS
by Andrii Gladkyi

2. INTRODUCTION

3. ME
• 15 years of dev experience
• Desktop (Delphi/C#/C++)
• Web (Ruby/JavaScript)
• 5 Ruby projects having text
search solutions

4. AGENDA
• Full text search
• Phrase match
• Filters/Facets

5. FULLTEXT SEARCH
• Search for a phrase within
document
• Partial matches
• Order by relevance
• Phrase highlights
• Similar matches
• Typos correction

6. SOLUTIONS
• RDBMS search
• Sphinx
• ElasticSearch

7. RDBMS SEARCH
• No external dependencies
• Relatively slow
• Provides only basic FTS
features
(PostgreSQL)

8. EXAMPLE
ALTER TABLE documents ADD COLUMN fts_col tsvector;
CREATE INDEX fts_idx ON documents USING GIN (fts_col);
UPDATE documents SET fts_col = to_tsvector(title || ' ' || content);
SELECT * FROM documents WHERE fts_col @@ to_tsquery('text to find');
Requirement: Search within document's title and content
Implementation:

9. PG_SEARCH GEM
github.com/casecommons/pg_search

10. PG_SEARCH HIGHLIGHTS
• Actively maintained
• 99% test coverage
• Dependencies:ActiveRecord 4.2+,ActiveSupport
• Single/multimodel search

11. QUICK START
class Document < ActiveRecord::Base
include PgSearch
pg_search_scope :search_full_text, against: {
title: 'A',
content: 'B'
}
end
Document.search_full_text('text to find')
Single model search

12. REVIEW
• Simple setup
• No external dependencies
• AR-compatible output
• PostgreSQL extensions
• Order by relevance
• PostgreSQL only :)
• Multimodel indexex need to
be rebuilt
• Only basic FTS features
Pros: Cons:

13. SPHINX SEARCH ENGINE
• RDBMS connections
• MySQL storage engine
option
• SQL-like queries
• Facets

14. THINKING_SPHINX GEM
github.com/pat/thinking-sphinx

15. THINKING_SPHINX HIGHLIGHTS
• Very mature (~10 years) project
• Supports ActiveRecord 3.1+
• Well documented
• Requires mysql gem to be installed

16. QUICK START
ThinkingSphinx::Index.define :document, with: :real_time do
indexes title
indexes content
end
after_save ThinkingSphinx::RealTime.callback_for(:document)
rake ts:regenerate
Document.search('text to find')

17. REVIEW
• Field weights
• Facets
• Advanced filters
• Different indexing strategies
(realtime and SQL)
• Deltas for SQL-backed
indexes
• Delta indexes may cause
data inconsistency
Pros: Cons:

18. ELASTICSEARCH ENGINE
• REST HTTP interface
• Scalable
• Aggregations
• Powerful mappings

19. SEARCHKICK GEM
github.com/ankane/searchkick

20. SEARCHKICK HIGHLIGHTS
• Developed for own needs
• AR-like query language
• Supports ActiveModel 4.1+
• Zero downtime reindex

21. QUICK START
class Document < ActiveRecord::Base
searchkick
end
Document.reindex
Document.search('text to find')

22. REVIEW
• Tons of features
• Bulk document updates
• Autocomplete
• Facets
• Very opinionated
development
• Documentation issues
• Default setup doesn't match
any practical requirements...
• ... therefore a reconfiguration
is a must
Pros: Cons:

23. SEARCHKICK ALTERNATIVES
github.com/elastic/elasticsearch-rails
github.com/toptal/chewy

24. CONCLUSION
• Use RDBMS search for a simple search within
a small and defined set of documents
• Want to scale/advanced features - try
ElasticSearch or Sphinx

25. PHRASE MATCH
• Search by exact name
• No irrelevant matches

26. RANSACK GEM
github.com/activerecord-hackery/ransack

27. RANSACK HIGHLIGHTS
• Works on the top of RDBMS search/filtering
• Case insensitive match by default
• Able to build search forms
• Rails 3-5.1 compatible

28. QUICK START
def index
@q = Document.ransack(params[:q])
@documents = @q.result(distinct: true)
end
<%= search_form_for @q do |f| %>
<%= f.label :title_cont %>
<%= f.search_field :title_cont %>
<%= f.submit %>
<% end %>
SELECT * FROM documents WHERE title ILIKE '%title%';
Executes:

29. MATCHERS

30. HOWTO SPEED UPTHE SEARCH?
(in PostgreSQL)

31. HOWTO SPEED UPTHE SEARCH?
(in PostgreSQL + Ruby on Rails)
class IndexDocuments < ActiveRecord::Migration[5.1]
def change
enable_extension 'pg_trgm'
add_index(:documents, 'title gin_trgm_ops', using: :gin)
end
end

32. REVIEW
• Search/filter forms
• Simple AR-compatible
interface
• Sort helpers
• Powerful matches
• Good documentation
• Memory consumption issues
• No out-of-box ranking (may
be implemented manually)
Pros: Cons:

33. FACETS
• Hide irrelevant facets
• Count documents
• Filter by facet value

34. FACETS IMPLEMENTATION
• Sphinx, ElasticSearch - built in
• Must implement manually when RDBMS search

35. CONCLUSIONS

36. QUESTIONS