Free open-source SQL full-text search engine

An acronym for SQL Phrase Index Developed by Andrew Aksyonoff

database search Using SQL directly: like "%text%" impractical for large text fields. no relevance ranking.

full text search searches all words in every document

against query. moves processing load out of DB. relvance ranking. other advanced features.

2 step process indexing▪ scan text and build a list of search terms.

searching▪ search into index to get refrences to data.

High indexing speed. upto 10 MB/sec on modern CPUs.

High search speed. avg query is under 0.1 sec on 2-4 GB

text collections.High scalability.

upto 100 GB text, upto 100M documents on a single CPU.

Supports distributed searching. can be extended to multiple servers.

Supports phrase proximity ranking. providing good relevance.

Supports stopwords. exclude common words like – a, an, the, with, in

Supports different search modes "match all", "match phrase" and "match any"

Supports relevance modification on the fly.

Key Sphinx features are its speed and phrase proximity ranking.

boardreader.com Indexes over 2 billion documents, BoardReader forum

search engine is the biggest Sphinx installation at present.

mininova.org Mininova, popular BitTorrent search engine, serves 3-5

million searches daily.

thepiratebay.org The Pirate Bay and (forthcoming) SuprNova moved to Sphinx

recently.

netlog.com NetLog, a large social network site with over 35 million

registered users, uses Sphinx for pretty every kind of search imaginable - people, photo, blog, event, music, and video searches. 12 million daily queries against 100+ GB indexes are handled by just 2 quad-core search boxes.

Sphinx can be downloaded from http://www.sphinxsearch.com/

Its distribution contains the following programs:

indexer utility to create fulltext indices

searchd daemon to search through fulltext indices

search test utility to query fulltext indices from

command line sphinxapi

set of API libraries for Ruby, Python, Perl, Java.

Configuration settings for indexer and searchd

Indexes, Fields, Attributes. Each index has a document id, some

fields, and some attributes. The id has to be unique, generally it’s the

primary key. The fields contain the text that is to be

searched. The attributes contain the data used for

sorting, filtering and grouping.

thinking_sphinx Pat Allan also developed the underlying API for Sphinx,

Riddle. git://github.com/freelancing-god/thinking-

sphinx.git

ultrasphinx Evan Weaver svn://rubyforge.org/var/svn/fauna/ultrasphinx/

trunk

Can be installed simply by ruby script\plugin install

<path_to_plugin>

No need to write the sphinx configuration file, plugins take care of this.

field aliasing indexes full_name, :as => :name

field merging [first_name, last_name], :as => :name

field weighting set_property :field_weights => {:

last_name =>2, :first_name => 1} User.search "aaa", :field_weights =>

{ :first_name => 1, :last_name => 2} index computed value

indexes "age > 15", :as => :minor

sorting (using attributes and fields) :sortable => true has created_at User.search("user", :order

=> :first_name, :sort_mode => :desc) User.search("user", :order => "created_at

DESC") filtering (using attributes and fields)

User.search :conditions => {:name => "aaa"} User.search :with => {:age => 10} User.search :without => {:age => 10}

add custom SQL conditions to index where "first_name = 'aaa'"

drop-in compatibility with will_paginate User.search "aaa", :page => (params[:page]

|| 1) geodistance

has :latit has :longit set_property :latitude_attr

=> :latit, :longitude_attr => :longit Address.search "pizza hut", :geo => [1.234,

4.567], :order => "@geodist asc" delta index support

set_property :delta => true

searching across multiple models indexes posts.name indexes posts.comments.name

comprehensive rake tasks rake ts:conf rake ts:in rake ts:start, restart, stop

multiple deployment environments rake ts:config RAILS_ENV=production

one-to-one user has_one blog indexes blog.name

one-to-many blog has_many posts indexes posts.name

many-to-many (through) posts has_many comments through records comments has_many posts through records indexes comments.name

deeply nested▪ blog has_many posts▪ posts has_many comments▪ indexes posts.comments.name

STI▪ User.search("user", :with => {:class_crc =>

Teacher.to_crc32}) polymorphic▪ user has_one phone▪ company has_one phone▪ indexes phone.name▪ where "callable_type = 'User'“

You can run the index task while Sphinx is running, and it’ll reload the indexes automatically.

As of version 0.9.9, your configuration will automatically be reloaded.

Keep in mind that if any keywords for Ruby methods - such as id or name - clash with your column names, you need to use the symbol version.

Sphinx connects to DB directly, so don’t expect that any of the model methods can be indexed.

You can extract commands for indexing and starting search daemon into scripts for fast access. indexer --config

config/development.sphinx.conf --all searchd --config

config/development.sphinx.conf skip this warning

distributed index 'model_name' can not be directly indexed; skipping.

Almost has all thinking_sphinx features with some additional features: excerpt highlighting spellcheck fields* faceting on text, date, and numeric fields*

*will be demonstrated in next presentation

sphinx http://www.sphinxsearch.com/

ultrasphinx http://blog.evanweaver.com/files/doc/

fauna/ultrasphinx/files/README.html thinking_sphinx

http://ts.freelancing-gods.com/ http://groups.google.com/group/

thinking-sphinx/