Got questions on Sphinx, the open source search engine? Not sure if it’s the right tool for you? You’re in the right place – we’ve put together an FAQ on Sphinx. It should help you make the right decision about the software that powers your search.
If you’ve got questions on the other kind of Sphinx, we recommend you look here instead.
Sphinx is a full-text search engine (generally standalone) which provides fast, relevant, efficient full-text search functionality to third-party applications. It was especially created to facilitate searches on SQL databases and integrates very well with scripting languages; such as PHP, Python, Perl, Ruby, and Java.
Some of the major features of Sphinx include:
Sphinx was developed and tested mostly on UNIX based systems. All modern UNIX based operating systems with an ANSI compliant compiler should be able to compile and run Sphinx without any issues. However, Sphinx has also been found running on the following operating systems without any issues.
The configure command gets the details of our machine and also checks for all dependencies. If any of the dependency is missing, it will throw an error.
There are many options that can be passed to the configure command but we will take a look at a few important ones:
Full-text search is one of the techniques for searching a document or database stored on a computer. While searching, the search engine goes through and examines all of the words stored in the document and tries to match the search query against those words. A complete examination of all the words (text) stored in the document is undertaken and hence it is called a full-text search.
Full-text search excels in searching large volumes of unstructured text quickly and effectively. It returns pages based on how well they match the user’s query.
The following points are some of the major advantages of full-text search:
You should use full-text search when:
If you’re looking for a good Database Management System (DBMS), there are plenty of options available with support for full-text indexing and searches, such as MySQL, PostgreSQL, and SQL Server. There are also external full-text search engines, such as Lucene and Solr. Let’s see the advantages of using Sphinx over the DBMS’s full-text searching capabilities and other external search engines:
Indexes in Sphinx are a bit different from indexes we have in databases. The data that Sphinx indexes is a set of structured documents and each document has the same set of fields. This is very similar to SQL, where each row in the table corresponds to a document and each column to a field. Sphinx builds a special data structure that is optimized for answering full-text search queries. This structure is called an index and the process of creating an index from the data is called indexing. The indexes in Sphinx can also contain attributes that are highly optimized for filtering. These attributes are not full-text indexed and do not contribute to matching. However, they are very useful at filtering out the results we want based on attribute values. There can be different types of indexes suited for different tasks. The index type, which has been implemented in Sphinx, is designed for maximum indexing and searching speed.
MVAs are a special type of attribute in Sphinx that make it possible to attach multiple values to every document. These attributes are especially useful in cases where each document can have multiple values for the same property (field).
Weighting decides which document gets priority over other documents and appear at the top. In Sphinx, weighting depends on the search mode. Weight can also be referred to as ranking. There are two major parts which are used in weighting functions:
Index merging is more efficient than indexing the data from scratch, that is, all over again. In this technique we define a delta index in the Sphinx configuration file. The delta index always gets the new data to be indexed. However, the main index acts as an archive and holds data that never changes.
Programmers normally issue search queries using one or more client libraries that relate to the database on which the search is to be performed. Some programmers may also find it easier to write an SQL query than to use the Sphinx Client API library.
SphinxQL is used to issue search queries in the form of SQL queries. These queries can be fired from any client of the database in question, and returns the results in the way that a normal query would. Currently MySQL binary network protocol is supported and this enables Sphinx to be accessed with the regular MySQL API.
In a Geo-distance search, you can find geo coordinates nearby to the base anchor point. Thus you can use this technique to find the nearby places to the given location. It can be useful in many applications like hotel search, property search, restaurant search, tourist destination search etc.
Sphinx makes it very easy to perform a geo-distance search by providing an API method wherein you can set the anchor point (if you have latitude and longitude in your index) and all searches performed thereafter will return the results with a magic attribute “@geodist” holding the values of distance from the anchor point. You can then filter or sort your results based on this attribute.
Further resources on this subject:
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