Sphinx (search engine)

Sphinx

Developer(s)	Andrew Aksyonoff
Initial release	2001 (2001)
Stable release	2.2.7 / 20 January 2015 (2015-01-20)
Preview release	2.3.2-dev / 3 March 2015 (2015-03-03)
Development status	Active
Written in	C++
Operating system	Linux, Windows, Solaris, FreeBSD, NetBSD, Mac OS, AIX
Type	Search and index
License	GPLv2 and commercial
Website	www.sphinxsearch.com

Sphinx is a free software/open source Fulltext search engine designed to provide full-text search functionality to client applications.

Overview

Like other DBMS's, Sphinx can be used as a stand-alone server. It can be used to communicate with other DBMS's by using native protocols of MySQL, MariaDB and PostgreSQL, or by using ODBC with ODBC-compliant DBMS's. And, Sphinx can also be used as a storage engine ("SphinxSE") for MySQL and its forks. MariaDB, a fork of MySQL, is distributed with SphinxSE.^[1]

SphinxAPI

If Sphinx is executed as a stand-alone server, it is possible to use SphinxAPI to connect an application to it. Official implementations of the API are available for PHP, Java, Perl, Ruby and Python languages. Unofficial implementations for other languages, as well as various third party^[2] plugins and modules are also available. Other data sources can be indexed via pipe in a custom XML format.^[3]

SphinxQL

The Sphinx search daemon supports MySQL binary network protocol and can be accessed with the regular MySQL API. Sphinx also supports a subset of SQL (SphinxQL). It supports standard querying of all index types with SELECT, modifying RealTime indexes with INSERT, REPLACE, and DELETE, and more.

SphinxSE

When using MariaDB or MySQL, the Sphinx searchd can also query via a table running with SphinxSE engine. The sphinx query is passed to searchd via the reserved query field.

Full-text fields

Full-text fields (or just fields for brevity) are the textual document contents that get indexed by Sphinx, and can be (quickly) searched for keywords. Fields are named, and you can limit your searches to a single field (e.g. search through "title" only) or a subset of fields (e.g. to "title" and "abstract" only). Sphinx's index format generally supports up to 256 fields. Note that the original contents of the fields are not stored in the Sphinx index. The text that you send to Sphinx gets processed, and a full-text index (a special data structure that enables quick searches for a keyword) gets built from that text. But the original text contents are then simply discarded. Sphinx assumes that you store those contents elsewhere anyway.

Attributes

Attributes are additional values associated with each document that can be used to perform additional filtering and sorting during search. Attributes are named. Attribute names are case insensitive. Attributes are not full-text indexed; they are stored in the index as is. Currently supported attribute types are:

• unsigned integers (1-bit to 32-bit wide);
• UNIX timestamps;
• floating point values (32-bit, IEEE 754 single precision);
• string ordinals (specially computed integers);
• strings(since 1.10-beta);
• JSON(since 2.1.1-beta);^[4][5]
• MVA, multi-value attributes (variable-length lists of 32-bit unsigned integers).

More about JSON Attributes in Sphinx

Sphinx, like classic SQL databases, works with a so-called fixed schema, that is, a set of attribute columns. These work well when most of the data you store actually has values. However, mapping sparse data to static columns can be very cumbersome. Assume for example that you’re running a price comparison or an auction site with many different products categories. Some of the attributes like the price or the vendor are identical across all goods. But from there, for laptops, you also need to store the weight, screen size, HDD type, RAM size, etc. And, say, for shovels, you probably want to store the color, the handle length, and so on. So it’s manageable across a single category, but all the distinct fields that you need for all the goods across all the categories are legion. The JSON field can be used to overcome this. Inside the JSON attribute you don’t need a fixed structure. You can have various keys which may or may not be present in all documents. When you try to filter on one of these keys, Sphinx will ignore documents that don’t have the key in the JSON attribute and will work only with those documents that have it.

License

Sphinx is dual licensed:

1. GNU General Public License version 2
2. and, commercial licensing is available for use-cases which are not within the terms of the GNU GPLv2.

Sphinx use examples

• Craigslist.org^[6]
• Recruitment.aleph-graymatter.com^[7]
• Tradebit.com^[8]
• vBulletin.com^[9]
• Mediawiki Extension^[10]
• Boardreader.com^[11]

Feature list

• Batch and incremental (soft real-time) full-text indexing.
• Support for non-text attributes (scalars, strings, sets, JSON).
• Direct indexing of SQL databases. Native support for MySQL, MariaDB, PostgreSQL, MSSQL, plus ODBC connectivity.
• XML documents indexing support.
• Distributed searching support out of the box.
• Integration via access APIs.
• SQL-like syntax support via MySQL protocol (since 0.9.9)
• Full-text searching syntax.
• Database-like result set processing.
• Relevance ranking utilizing additional factors besides standard BM25.
• Text processing support for SBCS and UTF-8 encodings, stopwords, indexing of words known not to appear in the database ("hitless"), stemming, word forms, tokenizing exceptions, and "blended characters" (dual-indexing as both a real character and a word separator).
• Supports UDF (since 2.0.1).

Performance and scalability

• Indexing speed of up to 10-15 MB/sec per core and HDD.
• Searching speed of over 500 queries/sec against 1,000,000 document/1.2 GB collection using a 2-core desktop system with 2 GB of RAM.^[12]
• The biggest known installation using Sphinx, Boardreader.com, indexes 16 billion documents.
• The busiest known installation, Craigslist, is rumored to serve over 250,000,000 queries/day.^[13] or 50 billion page views/month ^[14]

See also

• List of information retrieval libraries

References

External links

Wikibooks has a book on the topic of: Sphinx Search

• Official site
• Sphinx Documentation
• SphinxSE documentation
• OurSQL Podcast: Episode about Sphinx
• Andrew Aksyonoff (Sphinx's original author) Presents Sphinx basics
• Bill Karwin of Percona discusses various full text search engines
• Replacing MySQL full-text search with Sphinx
• Search beyond MySQL with Sphinx
• How we improved search performance by 2x

Further reading

• Aksyonoff, Andrew (2011). Introduction to Search with Sphinx: From installation to relevance tuning. O'Reilly Media. ISBN 978-0-596-80955-3. 
• Ali, Abbas (2011). Sphinx Search Beginner's Guide. Birmingham, England: Packt Publishing. ISBN 978-1-84951-254-1.