Getting Started

Getting Started

This walkthrough will guide you through setting up an index for Sphinx and accessing it from a .NET application using the native API. The index will be created for the Sakila sample database provided by MySQL.

Prerequisites

A working installation of a MySQL Server and Visual Studio 2008 or 2010.

Walkthrough

Download and install the Sakila sample database

Download the Sakila database from here.
Install the database as described here.

Download and install the Sphinx search engine

Download Sphinx from here. The choice of operating system is irrelevant for SphinxConnector.NET.
Install Sphinx as described here.

Create an index for the Sakila database

Create a file named sphinx.conf in the directory where the Sphinx executable files reside (usually the bin directory) and copy the following text into the file:

Copy

source sakila
{
    type                    = mysql

    sql_host                = localhost
    sql_user                = #add MySQL user name here
    sql_pass                = #add password here
    sql_db                  = sakila

    sql_port                = 3306 

    sql_query                                = SELECT film_id, title, title AS title_ord, description, release_year, rental_rate, language_id, \
                                                             length, UNIX_TIMESTAMP(last_update) AS last_update, 0 AS recommended_by_friends \
                                                            FROM film f;

    sql_attr_str2ordinal        = title_ord
    sql_attr_uint                        = release_year
    sql_attr_float                        = rental_rate
    sql_attr_uint                        = language_id
    sql_attr_uint                        = length
    sql_attr_timestamp                = last_update
    sql_attr_multi                        = uint actor_id from query; SELECT film_id, actor_id FROM film_actor;
    sql_attr_multi                        = uint rating from query; SELECT film_id, CRC32(rating) FROM film;
    sql_attr_bool                        = recommended_by_friends
}

index sakila
{

    source                  = sakila
    path                    = sakila
    charset_type                     = utf-8

    min_word_len            = 1
    min_prefix_len          = 0
    min_infix_len                  = 1
}

searchd
{
        listen                                         = localhost:9312
        listen                                         = localhost:9306:mysql41
        query_log_format                 = sphinxql
        compat_sphinxql_magics        = 0
        log                                                = searchd.log
        query_log                                = query.log
        pid_file                                = searchd.pid
        max_matches                         = 1000
        workers                                 = threads        
        binlog_path                         =
}

indexer
{
        mem_limit                                 = 256M
}

In the source section of the config file you need to modify the following settings for your installation of MySQL:
- sql_user
- sql_pass
- sql_host
- sql_port
Note
You may also need to modify the address or listen setting in the searchd section, depending on whether you installed Sphinx locally or on a remote machine.

Note
You may also need to modify the address or listen setting in the searchd section, depending on whether you installed Sphinx locally or on a remote machine.

Now open a command line/terminal window and switch to the directory where the indexer executable resides. To create the index type indexer.exe sakila if you are using Windows or ./indexer sakila if you are using Linux or Windows PowerShell.

You should now see output similar to this:

Copy

Sphinx 2.0.4-id64-release (r3135)
Copyright (c) 2001-2012, Andrew Aksyonoff
Copyright (c) 2008-2012, Sphinx Technologies Inc (http://sphinxsearch.com)
using config file './sphinx.conf'...
indexing index 'sakila'...
collected 1000 docs, 0.1 MB
collected 6462 attr values
sorted 0.0 Mvalues, 100.0% done
sorted 0.5 Mhits, 98.2% done
total 1000 docs, 108077 bytes
total 0.313 sec, 344736 bytes/sec, 3189.73 docs/sec
total 10 reads, 0.002 sec, 285.2 kb/call avg, 0.2 msec/call avg
total 17 writes, 0.044 sec, 397.8 kb/call avg, 2.6 msec/call avg

The index has been created and can now be accessed from SphinxConnector.NET.

Start the Sphinx search daemon by typing searchd or ./searchd (under Linux add --console to have the log written to the console).

Create a Visual Studio project

Start Visual Studio and create a new Console Application named SphinxConnectorDemo.
Add a reference to SphinxConnector.dll to your project. Either add SphinxConnector.NET via NuGet to your project, or manually add a reference to SphinxConnector.dll and Common.Logging to your project. You'll find these files in the Required Libs folder of the SphinxConnector.NET ZIP package.

Replace the code in your Program.cs file with the following:

Copy

using System;

using SphinxConnector;

namespace SphinxConnectorDemo
{
    class Program
    {
        static void Main(string[] args)
        {
            SphinxClient sphinxClient = new SphinxClient();
            SphinxSearchResult sphinxSearchResult = sphinxClient.Query("room", "sakila");

            foreach (SphinxMatch match in sphinxSearchResult.Matches)
            {
                Console.WriteLine("DocumentId {0} Weight {1}", match.DocumentId, match.Weight);
            }

            Console.ReadLine();
        }
    }
}

Note
If necessary, adjust the parameters to the constructor of the SphinxClient class.

Now hit F5 and you should see output similar to this:
DocumentId 52 Weight 1
DocumentId 87 Weight 1
DocumentId 743 Weight 1

Next Steps

Check out the documentation on methods of the SphinxSearchOptions class to see how you can set filters on attributes, set weights on fields and much more.