This document provides an overview of the Ferret Ruby search engine. It discusses what Ferret is, key concepts like indexes and documents, how to install and index documents in Ferret, how to perform searches using the Ferret Query Language (FQL), and how to integrate Ferret into Rails applications using the Acts As Ferret plugin. The document also provides pointers to online and printed resources for learning more about Ferret and full-text search engines.

1. Ferret
A Ruby Search Engine
Brian Sam-Bodden

2. Agenda
• What is Ferret?
• Concepts
• Fields
• Indexing
• Installing Ferret

3. Agenda
• The Recipe
• Documents
• Ferret::Index::Index
• FQL
• Ferret in you App

4. Agenda
• Ferret in Rails
• Resources

5. What is Ferret?
• Information Retrieval (IR) Library
• Full-featured Text Search Engine
• Inspired on the Search Engine
• Port to Ruby by David Balmain

6. What is Ferret?
• Initially a 100% pure Ruby port
• Since 0.9 many core functions are
implemented in C
• Fast! Now Faster than Lucene ;-)

7. Concepts

8. Concepts
• Index : Sequence of documents

9. Concepts
• Index : Sequence of documents
• Document : Sequence of fields

10. Concepts
• Index : Sequence of documents
• Document : Sequence of fields
• Field : Named sequence of terms

11. Concepts
• Index : Sequence of documents
• Document : Sequence of fields
• Field : Named sequence of terms
• Term : A text string, keyed by field name

12. Fields of a Document in
an Index

13. Fields of a Document in
an Index
• Fields are individually searchable units
that are:

14. Fields of a Document in
an Index
• Fields are individually searchable units
that are:
• Stored: The original Terms of the fields are store

15. Fields of a Document in
an Index
• Fields are individually searchable units
that are:
• Stored: The original Terms of the fields are store
• Indexed: Inverted to rapidly find all Documents
containing any of the Terms

16. Fields of a Document in
an Index
• Fields are individually searchable units
that are:
• Stored: The original Terms of the fields are store
• Indexed: Inverted to rapidly find all Documents
containing any of the Terms
• Tokenized: Individual Terms extracted are
indexed

17. Fields of a Document in
an Index
• Fields are individually searchable units
that are:
• Stored: The original Terms of the fields are store
• Indexed: Inverted to rapidly find all Documents
containing any of the Terms
• Tokenized: Individual Terms extracted are
indexed
• Vectored: Frequency and location of Terms are
stored

18. It’s all about Indexing
• Indexing is the processing of a source
document into plain text tokens that Ferret
can manipulate
• For any non-plaintext sources such as PDF,
Word, Excel you need to:
• Extract
• Analyze

19. Installing Ferret

20. Installing Ferret
gem install ferret

21. Installing Ferret

22. Installing Ferret

23. Installing Ferret
}

24. Installing Ferret
} Pick the latest version
for your platform

25. The Recipe

26. The Recipe
1. Create some Documents

27. The Recipe
1. Create some Documents
2. Create an Index

28. The Recipe
1. Create some Documents
2. Create an Index
3. Adding Documents to the Index

29. The Recipe
1. Create some Documents
2. Create an Index
3. Adding Documents to the Index
4. Perform some Queries

30. Example Documents
Create some Documents

31. Example Documents
Create some Documents
“Any String is a Document”

32. Example Documents
Create some Documents

33. Example Documents
Create some Documents
[“This”, “is also”, “a document”]

34. Example Documents
Create some Documents

35. Example Documents
Create some Documents

36. Ferret::Index::Index
Create an Index

37. Ferret::Index::Index
Create an Index
• Indexes are encapsulated by the class

38. Ferret::Index::Index
Create an Index
• Indexes are encapsulated by the class
➡ Ferret::Index::Index

39. Ferret::Index::Index
Create an Index
• Indexes are encapsulated by the class
➡ Ferret::Index::Index
• Use the alias Ferret::I for convenience

40. Ferret::Index::Index
Create an Index
• Indexes are encapsulated by the class
➡ Ferret::Index::Index
• Use the alias Ferret::I for convenience
• Index can be persistent

41. Ferret::Index::Index
Create an Index
• Indexes are encapsulated by the class
➡ Ferret::Index::Index
• Use the alias Ferret::I for convenience
• Index can be persistent
➡ index = Ferret::I.new(:path = > ‘/somepath’)

42. Ferret::Index::Index
Create an Index
• Indexes are encapsulated by the class
➡ Ferret::Index::Index
• Use the alias Ferret::I for convenience
• Index can be persistent
➡ index = Ferret::I.new(:path = > ‘/somepath’)
• Or, completely in Memory

43. Ferret::Index::Index
Create an Index
• Indexes are encapsulated by the class
➡ Ferret::Index::Index
• Use the alias Ferret::I for convenience
• Index can be persistent
➡ index = Ferret::I.new(:path = > ‘/somepath’)
• Or, completely in Memory
➡ index = Ferret::I.new()

44. Ferret::Index::Index
Adding Documents to the Index
• Index provides the add_document
method
• It also provides the << alias
• Adding documents is then as easy as:
➡ index << “This is a document”
➡ index << {:first => “Bob”, :last => “Smith”}

45. Ferret::Index::Index
Perform some Queries

46. Ferret::Index::Index
Perform some Queries
• Index provides the search and
search_each methods

47. Ferret::Index::Index
Perform some Queries
• Index provides the search and
search_each methods
• search method takes a query and a an
optional set of parameters:

48. Ferret::Index::Index
Perform some Queries
• Index provides the search and
search_each methods
• search method takes a query and a an
optional set of parameters:
➡ search(query, options = {})

49. Ferret::Index::Index
Perform some Queries
• Index provides the search and
search_each methods
• search method takes a query and a an
optional set of parameters:
➡ search(query, options = {})
• The search_each method provides an
iterator block

50. Ferret::Index::Index
Perform some Queries
• Index provides the search and
search_each methods
• search method takes a query and a an
optional set of parameters:
➡ search(query, options = {})
• The search_each method provides an
iterator block
➡ search_each(query, options = {}) {|doc, score| ... }

51. Playing with Ferret in irb

52. Playing with Ferret in irb

53. Ferret Query Language
• Ferret own Query Language, FQL is a
powerful way to specify search queries
• FQL supports many query types,
including:
• Term • Range
• Phrase • Wild
• Field • Fuzz
• Boolean

54. Index.explain
• The explain method of Index describes
how a document score against a query
• Very useful for debugging
• and for learning how Ferret works

55. Index.explain

56. Ferret in your App
Application
Database Web
User
Manual
File System
Input
Get User’s Present
Gather Data Search Results
Query
Index
Documents Search Index
Ferret
Index

57. Ferret in Rails
• Acts As Ferret is an ActiveRecord
extension
• Available as a plugin
• Provides a simplified interface to
Ferret
• Maintained by Jens Kramer

58. Ferret in Rails
• Adding an index to an ActiveRecord
model is as simple as:

59. Ferret in Rails
• Adding an index to an ActiveRecord
model is as simple as:

60. Ferret in Rails
• Simple model has two searchable
fields title and body:

61. Ferret in Rails
• After a quick rake db:migrate we now
have some data to play with
• Fire up the Rails Console and let’s see
what acts_as_ferret can do for our
models

62. Ferret in Rails

63. Want more?
• Ferret is improving constantly
• Acts As Ferret seems to catch up
quickly
• Real-life usage seems to require some
good engineering on your part
• Background indexing
• Hot swap of indexes?

64. Want more?
• We only covered the simplest
constructs in Ferret
• Ferret’s API provides enough
flexibility for the most demanding
searching needs

65. Online Resources
• http://ferret.davebalmain.com
• http://lucene.apache.org
• http://lucenebook.com
• http://projects.jkraemer.net/acts_as_ferret

66. In-Print Resources

67. Thanks!