Sphinx 0.9.9-rc2 reference manual

Prototype: function GetLastError()

Returns last error message, as a string, in human readable format. If there were no errors during the previous API call, empty string is returned.

You should call it when any other function (such as Query()) fails (typically, the failing function returns false). The returned string will contain the error description.

The error message is not reset by this call; so you can safely call it several times if needed.

Prototype: function GetLastWarning ()

Returns last warning message, as a string, in human readable format. If there were no warnings during the previous API call, empty string is returned.

You should call it to verify whether your request (such as Query()) was completed but with warnings. For instance, search query against a distributed index might complete succesfully even if several remote agents timed out. In that case, a warning message would be produced.

The warning message is not reset by this call; so you can safely call it several times if needed.

Prototype: function SetServer ( $host, $port )

Sets searchd host name and TCP port. All subsequent requests will use the new host and port settings. Default host and port are 'localhost' and 9312, respectively.

Prototype: function SetRetries ( $count, $delay=0 )

Sets distributed retry count and delay.

On temporary failures searchd will attempt up to $count retries per agent. $delay is the delay between the retries, in milliseconds. Retries are disabled by default. Note that this call will not make the API itself retry on temporary failure; it only tells searchd to do so. Currently, the list of temporary failures includes all kinds of connect() failures and maxed out (too busy) remote agents.

Prototype: function SetConnectTimeout ( $timeout )

Sets the time allowed to spend connecting to the server before giving up.

Under some circumstances, the server can be delayed in responding, either due to network delays, or a query backlog. In either instance, this allows the client application programmer some degree of control over how their program interacts with searchd when not available, and can ensure that the client application does not fail due to exceeding the script execution limits (especially in PHP).

In the event of a failure to connect, an appropriate error code should be returned back to the application in order for application-level error handling to advise the user.

Prototype: function SetArrayResult ( $arrayresult )

PHP specific. Controls matches format in the search results set (whether matches should be returned as an array or a hash).

$arrayresult argument must be boolean. If $arrayresult is false (the default mode), matches will returned in PHP hash format with document IDs as keys, and other information (weight, attributes) as values. If $arrayresult is true, matches will be returned as a plain array with complete per-match information including document ID.

Introduced along with GROUP BY support on MVA attributes. Group-by-MVA result sets may contain duplicate document IDs. Thus they need to be returned as plain arrays, because hashes will only keep one entry per document ID.

Prototype: function IsConnectError ()

Checks whether the last error was a network error on API side, or a remote error reported by searchd. Returns true if the last connection attempt to searchd failed on API side, false otherwise (if the error was remote, or there were no connection attempts at all). Introduced in version 0.9.9-rc1.

Prototype: function SetLimits ( $offset, $limit, $max_matches=0, $cutoff=0 )

Sets offset into server-side result set ($offset) and amount of matches to return to client starting from that offset ($limit). Can additionally control maximum server-side result set size for current query ($max_matches) and the threshold amount of matches to stop searching at ($cutoff). All parameters must be non-negative integers.

First two parameters to SetLimits() are identical in behavior to MySQL LIMIT clause. They instruct searchd to return at most $limit matches starting from match number $offset. The default offset and limit settings are 0 and 20, that is, to return first 20 matches.

max_matches setting controls how much matches searchd will keep in RAM while searching. All matching documents will be normally processed, ranked, filtered, and sorted even if max_matches is set to 1. But only best N documents are stored in memory at any given moment for performance and RAM usage reasons, and this setting controls that N. Note that there are two places where max_matches limit is enforced. Per-query limit is controlled by this API call, but there also is per-server limit controlled by max_matches setting in the config file. To prevent RAM usage abuse, server will not allow to set per-query limit higher than the per-server limit.

You can't retrieve more than max_matches matches to the client application. The default limit is set to 1000. Normally, you must not have to go over this limit. One thousand records is enough to present to the end user. And if you're thinking about pulling the results to application for further sorting or filtering, that would be much more efficient if performed on Sphinx side.

$cutoff setting is intended for advanced performance control. It tells searchd to forcibly stop search query once $cutoff matches had been found and processed.

Prototype: function SetMaxQueryTime ( $max_query_time )

Sets maximum search query time, in milliseconds. Parameter must be a non-negative integer. Default valus is 0 which means "do not limit".

Similar to $cutoff setting from SetLimits(), but limits elapsed query time instead of processed matches count. Local search queries will be stopped once that much time has elapsed. Note that if you're performing a search which queries several local indexes, this limit applies to each index separately.

Prototype: function SetOverride ( $attrname, $attrtype, $values )

Sets temporary (per-query) per-document attribute value overrides. Only supports scalar attributes. $values must be a hash that maps document IDs to overridden attribute values. Introduced in version 0.9.9-rc1.

Override feature lets you "temporary" update attribute values for some documents within a single query, leaving all other queries unaffected. This might be useful for personalized data. For example, assume you're implementing a personalized search function that wants to boost the posts that the user's friends recommend. Such data is not just dynamic, but also personal; so you can't simply put it in the index because you don't want everyone's searches affected. Overrides, on the other hand, are local to a single query and invisible to everyone else. So you can, say, setup a "friends_weight" value for every document, defaulting to 0, then temporary override it with 1 for documents 123, 456 and 789 (recommended by exactly the friends of current user), and use that value when ranking.

Prototype: function SetSelect ( $clause )

Sets the select clause, listing specific attributes to fetch, and expressions to compute and fetch. Clause syntax mimics SQL. Introduced in version 0.9.9-rc1.

SetSelect() is very similar to the part of a typical SQL query between SELECT and FROM. It lets you choose what attributes (columns) to fetch, and also what expressions over the columns to compute and fetch. A certain difference from SQL is that expressions must always be aliased to a correct identifier (consisting of letters and digits) using 'AS' keyword. SQL also lets you do that but does not require to. Sphinx enforces aliases so that the computation results can always be returned under a "normal" name in the result set, used in other clauses, etc.

Everything else is basically identical to SQL. Star ('*') is supported. Functions are supported. Arbitrary amount of expressions is supported. Computed expressions can be used for sorting, filtering, and grouping, just as the regular attributes.

Starting with version 0.9.9-rc2, aggregate functions (AVG(), MIN(), MAX(), SUM()) are supported when using GROUP BY.

Expression sorting (Section 4.5, “SPH_SORT_EXPR mode”) and geodistance functions (Section 6.4.5, “SetGeoAnchor”) are now internally implemented using this computed expressions mechanism, using magic names '@expr' and '@geodist' respectively.

Example:

$cl->SetSelect ( "*, @weight+(user_karma+ln(pageviews))*0.1 AS myweight" );
$cl->SetSelect ( "exp_years, salary_gbp*{$gbp_usd_rate} AS salary_usd,
   IF(age>40,1,0) AS over40" );
$cl->SetSelect ( "*, AVG(price) AS avgprice" );

Prototype: function SetMatchMode ( $mode )

Sets full-text query matching mode, as described in Section 4.1, “Matching modes”. Parameter must be a constant specifying one of the known modes.

WARNING: (PHP specific) you must not take the matching mode constant name in quotes, that syntax specifies a string and is incorrect:

$cl->SetMatchMode ( "SPH_MATCH_ANY" ); // INCORRECT! will not work as expected
$cl->SetMatchMode ( SPH_MATCH_ANY ); // correct, works OK

Prototype: function SetRankingMode ( $ranker )

Sets ranking mode. Only available in SPH_MATCH_EXTENDED2 matching mode at the time of this writing. Parameter must be a constant specifying one of the known modes.

By default, Sphinx computes two factors which contribute to the final match weight. The major part is query phrase proximity to document text. The minor part is so-called BM25 statistical function, which varies from 0 to 1 depending on the keyword frequency within document (more occurrences yield higher weight) and within the whole index (more rare keywords yield higher weight).

However, in some cases you'd want to compute weight differently - or maybe avoid computing it at all for performance reasons because you're sorting the result set by something else anyway. This can be accomplished by setting the appropriate ranking mode.

Currently implemented modes are:

Prototype: function SetSortMode ( $mode, $sortby="" )

Set matches sorting mode, as described in Section 4.5, “Sorting modes”. Parameter must be a constant specifying one of the known modes.

WARNING: (PHP specific) you must not take the matching mode constant name in quotes, that syntax specifies a string and is incorrect:

$cl->SetSortMode ( "SPH_SORT_ATTR_DESC" ); // INCORRECT! will not work as expected
$cl->SetSortMode ( SPH_SORT_ATTR_ASC ); // correct, works OK

Prototype: function SetWeights ( $weights )

Binds per-field weights in the order of appearance in the index. DEPRECATED, use SetFieldWeights() instead.

Prototype: function SetFieldWeights ( $weights )

Binds per-field weights by name. Parameter must be a hash (associative array) mapping string field names to integer weights.

Match ranking can be affected by per-field weights. For instance, see Section 4.4, “Weighting” for an explanation how phrase proximity ranking is affected. This call lets you specify what non-default weights to assign to different full-text fields.

The weights must be positive 32-bit integers. The final weight will be a 32-bit integer too. Default weight value is 1. Unknown field names will be silently ignored.

There is no enforced limit on the maximum weight value at the moment. However, beware that if you set it too high you can start hitting 32-bit wraparound issues. For instance, if you set a weight of 10,000,000 and search in extended mode, then maximum possible weight will be equal to 10 million (your weight) by 1 thousand (internal BM25 scaling factor, see Section 4.4, “Weighting”) by 1 or more (phrase proximity rank). The result is at least 10 billion that does not fit in 32 bits and will be wrapped around, producing unexpected results.

Prototype: function SetIndexWeights ( $weights )

Sets per-index weights, and enables weighted summing of match weights across different indexes. Parameter must be a hash (associative array) mapping string index names to integer weights. Default is empty array that means to disable weighting summing.

When a match with the same document ID is found in several different local indexes, by default Sphinx simply chooses the match from the index specified last in the query. This is to support searching through partially overlapping index partitions.

However in some cases the indexes are not just partitions, and you might want to sum the weights across the indexes instead of picking one. SetIndexWeights() lets you do that. With summing enabled, final match weight in result set will be computed as a sum of match weight coming from the given index multiplied by respective per-index weight specified in this call. Ie. if the document 123 is found in index A with the weight of 2, and also in index B with the weight of 3, and you called SetIndexWeights ( array ( "A"=>100, "B"=>10 ) ), the final weight return to the client will be 2*100+3*10 = 230.

Prototype: function SetIDRange ( $min, $max )

Sets an accepted range of document IDs. Parameters must be integers. Defaults are 0 and 0; that combination means to not limit by range.

After this call, only those records that have document ID between $min and $max (including IDs exactly equal to $min or $max) will be matched.

Prototype: function SetFilter ( $attribute, $values, $exclude=false )

Adds new integer values set filter.

On this call, additional new filter is added to the existing list of filters. $attribute must be a string with attribute name. $values must be a plain array containing integer values. $exclude must be a boolean value; it controls whether to accept the matching documents (default mode, when $exclude is false) or reject them.

Only those documents where $attribute column value stored in the index matches any of the values from $values array will be matched (or rejected, if $exclude is true).

Prototype: function SetFilterRange ( $attribute, $min, $max, $exclude=false )

Adds new integer range filter.

On this call, additional new filter is added to the existing list of filters. $attribute must be a string with attribute name. $min and $max must be integers that define the acceptable attribute values range (including the boundaries). $exclude must be a boolean value; it controls whether to accept the matching documents (default mode, when $exclude is false) or reject them.

Only those documents where $attribute column value stored in the index is between $min and $max (including values that are exactly equal to $min or $max) will be matched (or rejected, if $exclude is true).

Prototype: function SetFilterFloatRange ( $attribute, $min, $max, $exclude=false )

Adds new float range filter.

On this call, additional new filter is added to the existing list of filters. $attribute must be a string with attribute name. $min and $max must be floats that define the acceptable attribute values range (including the boundaries). $exclude must be a boolean value; it controls whether to accept the matching documents (default mode, when $exclude is false) or reject them.

Only those documents where $attribute column value stored in the index is between $min and $max (including values that are exactly equal to $min or $max) will be matched (or rejected, if $exclude is true).

Prototype: function SetGeoAnchor ( $attrlat, $attrlong, $lat, $long )

Sets anchor point for and geosphere distance (geodistance) calculations, and enable them.

$attrlat and $attrlong must be strings that contain the names of latitude and longitude attributes, respectively. $lat and $long are floats that specify anchor point latitude and longitude, in radians.

Once an anchor point is set, you can use magic "@geodist" attribute name in your filters and/or sorting expressions. Sphinx will compute geosphere distance between the given anchor point and a point specified by latitude and lognitude attributes from each full-text match, and attach this value to the resulting match. The latitude and longitude values both in SetGeoAnchor and the index attribute data are expected to be in radians. The result will be returned in meters, so geodistance value of 1000.0 means 1 km. 1 mile is approximately 1609.344 meters.

Prototype: function SetGroupBy ( $attribute, $func, $groupsort="@group desc" )

Sets grouping attribute, function, and groups sorting mode; and enables grouping (as described in Section 4.6, “Grouping (clustering) search results ”).

$attribute is a string that contains group-by attribute name. $func is a constant that chooses a function applied to the attribute value in order to compute group-by key. $groupsort is a clause that controls how the groups will be sorted. Its syntax is similar to that described in Section 4.5, “SPH_SORT_EXTENDED mode”.

Grouping feature is very similar in nature to GROUP BY clause from SQL. Results produces by this function call are going to be the same as produced by the following pseudo code:

SELECT ... GROUP BY $func($attribute) ORDER BY $groupsort

Note that it's $groupsort that affects the order of matches in the final result set. Sorting mode (see Section 6.3.3, “SetSortMode”) affect the ordering of matches within group, ie. what match will be selected as the best one from the group. So you can for instance order the groups by matches count and select the most relevant match within each group at the same time.

Starting with version 0.9.9-rc2, aggregate functions (AVG(), MIN(), MAX(), SUM()) are supported through SetSelect() API call when using GROUP BY.

Prototype: function SetGroupDistinct ( $attribute )

Sets attribute name for per-group distinct values count calculations. Only available for grouping queries.

$attribute is a string that contains the attribute name. For each group, all values of this attribute will be stored (as RAM limits permit), then the amount of distinct values will be calculated and returned to the client. This feature is similar to COUNT(DISTINCT) clause in standard SQL; so these Sphinx calls:

$cl->SetGroupBy ( "category", SPH_GROUPBY_ATTR, "@count desc" );
$cl->SetGroupDistinct ( "vendor" );

can be expressed using the following SQL clauses:

SELECT id, weight, all-attributes,
	COUNT(DISTINCT vendor) AS @distinct,
	COUNT(*) AS @count
FROM products
GROUP BY category
ORDER BY @count DESC

In the sample pseudo code shown just above, SetGroupDistinct() call corresponds to COUNT(DISINCT vendor) clause only. GROUP BY, ORDER BY, and COUNT(*) clauses are all an equivalent of SetGroupBy() settings. Both queries will return one matching row for each category. In addition to indexed attributes, matches will also contain total per-category matches count, and the count of distinct vendor IDs within each category.

Prototype: function Query ( $query, $index="*", $comment="" )

Connects to searchd server, runs given search query with current settings, obtains and returns the result set.

$query is a query string. $index is an index name (or names) string. Returns false and sets GetLastError() message on general error. Returns search result set on success. Additionally, the contents of $comment are sent to the query log, marked in square brackets, just before the search terms, which can be very useful for debugging. Currently, the comment is limited to 128 characters.

Default value for $index is "*" that means to query all local indexes. Characters allowed in index names include Latin letters (a-z), numbers (0-9), minus sign (-), and underscore (_); everything else is considered a separator. Therefore, all of the following samples calls are valid and will search the same two indexes:

$cl->Query ( "test query", "main delta" );
$cl->Query ( "test query", "main;delta" );
$cl->Query ( "test query", "main, delta" );

Index specification order matters. If document with identical IDs are found in two or more indexes, weight and attribute values from the very last matching index will be used for sorting and returning to client (unless explicitly overridden with SetIndexWeights()). Therefore, in the example above, matches from "delta" index will always win over matches from "main".

On success, Query() returns a result set that contains some of the found matches (as requested by SetLimits()) and additional general per-query statistics. The result set is a hash (PHP specific; other languages might utilize other structures instead of hash) with the following keys and values:

It should be noted that Query() carries out the same actions as AddQuery() and RunQueries() without the intermediate steps; it is analoguous to a single AddQuery() call, followed by a corresponding RunQueries(), then returning the first array element of matches (from the first, and only, query.)

Prototype: function AddQuery ( $query, $index="*", $comment="" )

Adds additional query with current settings to multi-query batch. $query is a query string. $index is an index name (or names) string. Additionally if provided, the contents of $comment are sent to the query log, marked in square brackets, just before the search terms, which can be very useful for debugging. Currently, this is limited to 128 characters. Returns index to results array returned from RunQueries().

Batch queries (or multi-queries) enable searchd to perform internal optimizations if possible. They also reduce network connection overheads and search process creation overheads in all cases. They do not result in any additional overheads compared to simple queries. Thus, if you run several different queries from your web page, you should always consider using multi-queries.

For instance, running the same full-text query but with different sorting or group-by settings will enable searchd to perform expensive full-text search and ranking operation only once, but compute multiple group-by results from its output.

This can be a big saver when you need to display not just plain search results but also some per-category counts, such as the amount of products grouped by vendor. Without multi-query, you would have to run several queries which perform essentially the same search and retrieve the same matches, but create result sets differently. With multi-query, you simply pass all these querys in a single batch and Sphinx optimizes the redundant full-text search internally.

AddQuery() internally saves full current settings state along with the query, and you can safely change them afterwards for subsequent AddQuery() calls. Already added queries will not be affected; there's actually no way to change them at all. Here's an example:

$cl->SetSortMode ( SPH_SORT_RELEVANCE );
$cl->AddQuery ( "hello world", "documents" );

$cl->SetSortMode ( SPH_SORT_ATTR_DESC, "price" );
$cl->AddQuery ( "ipod", "products" );

$cl->AddQuery ( "harry potter", "books" );

$results = $cl->RunQueries ();

With the code above, 1st query will search for "hello world" in "documents" index and sort results by relevance, 2nd query will search for "ipod" in "products" index and sort results by price, and 3rd query will search for "harry potter" in "books" index while still sorting by price. Note that 2nd SetSortMode() call does not affect the first query (because it's already added) but affects both other subsequent queries.

Additionally, any filters set up before an AddQuery() will fall through to subsequent queries. So, if SetFilter() is called before the first query, the same filter will be in place for the second (and subsequent) queries batched through AddQuery() unless you call ResetFilters() first. Alternatively, you can add additional filters as well.

This would also be true for grouping options and sorting options; no current sorting, filtering, and grouping settings are affected by this call; so subsequent queries will reuse current query settings.

AddQuery() returns an index into an array of results that will be returned from RunQueries() call. It is simply a sequentially increasing 0-based integer, ie. first call will return 0, second will return 1, and so on. Just a small helper so you won't have to track the indexes manualy if you need then.

Prototype: function RunQueries ()

Connect to searchd, runs a batch of all queries added using AddQuery(), obtains and returns the result sets. Returns false and sets GetLastError() message on general error (such as network I/O failure). Returns a plain array of result sets on success.

Each result set in the returned array is exactly the same as the result set returned from Query().

Note that the batch query request itself almost always succeds - unless there's a network error, blocking index rotation in progress, or another general failure which prevents the whole request from being processed.

However individual queries within the batch might very well fail. In this case their respective result sets will contain non-empty "error" message, but no matches or query statistics. In the extreme case all queries within the batch could fail. There still will be no general error reported, because API was able to succesfully connect to searchd, submit the batch, and receive the results - but every result set will have a specific error message.

Prototype: function ResetFilters ()

Clears all currently set filters.

This call is only normally required when using multi-queries. You might want to set different filters for different queries in the batch. To do that, you should call ResetFilters() and add new filters using the respective calls.

Prototype: function ResetGroupBy ()

Clears all currently group-by settings, and disables group-by.

This call is only normally required when using multi-queries. You can change individual group-by settings using SetGroupBy() and SetGroupDistinct() calls, but you can not disable group-by using those calls. ResetGroupBy() fully resets previous group-by settings and disables group-by mode in the current state, so that subsequent AddQuery() calls can perform non-grouping searches.

Prototype: function BuildExcerpts ( $docs, $index, $words, $opts=array() )

Excerpts (snippets) builder function. Connects to searchd, asks it to generate excerpts (snippets) from given documents, and returns the results.

$docs is a plain array of strings that carry the documents' contents. $index is an index name string. Different settings (such as charset, morphology, wordforms) from given index will be used. $words is a string that contains the keywords to highlight. They will be processed with respect to index settings. For instance, if English stemming is enabled in the index, "shoes" will be highlighted even if keyword is "shoe". Starting with version 0.9.9-rc1, keywords can contain wildcards, that work similarly to star-syntax available in queries. $opts is a hash which contains additional optional highlighting parameters:

Returns false on failure. Returns a plain array of strings with excerpts (snippets) on success.

Prototype: function UpdateAttributes ( $index, $attrs, $values )

Instantly updates given attribute values in given documents. Returns number of actually updated documents (0 or more) on success, or -1 on failure.

$index is a name of the index (or indexes) to be updated. $attrs is a plain array with string attribute names, listing attributes that are updated. $values is a hash where key is document ID, and value is a plain array of new attribute values.

$index can be either a single index name or a list, like in Query(). Unlike Query(), wildcard is not allowed and all the indexes to update must be specified explicitly. The list of indexes can include distributed index names. Updates on distributed indexes will be pushed to all agents.

The updates only work with docinfo=extern storage strategy. They are very fast because they're working fully in RAM, but they can also be made persistent: updates are saved on disk on clean searchd shutdown initiated by SIGTERM signal. With additional restrictions, updates are also possible on MVA attributes; refer to mva_updates_pool directive for details.

Usage example:

$cl->UpdateAttributes ( "test1", array("group_id"), array(1=>array(456)) );
$cl->UpdateAttributes ( "products", array ( "price", "amount_in_stock" ),
	array ( 1001=>array(123,5), 1002=>array(37,11), 1003=>(25,129) ) );

The first sample statement will update document 1 in index "test1", setting "group_id" to 456. The second one will update documents 1001, 1002 and 1003 in index "products". For document 1001, the new price will be set to 123 and the new amount in stock to 5; for document 1002, the new price will be 37 and the new amount will be 11; etc.

Prototype: function BuildKeywords ( $query, $index, $hits )

Extracts keywords from query using tokenizer settings for given index, optionally with per-keyword occurrence statistics. Returns an array of hashes with per-keyword information.

$query is a query to extract keywords from. $index is a name of the index to get tokenizing settings and keyword occurrence statistics from. $hits is a boolean flag that indicates whether keyword occurrence statistics are required.

Usage example:

$keywords = $cl->BuildKeywords ( "this.is.my query", "test1", false );

Prototype: function EscapeString ( $string )

Escapes characters that are treated as special operators by the query language parser. Returns an escaped string.

$string is a string to escape.

This function might seem redundant because it's trivial to implement in any calling application. However, as the set of special characters might change over time, it makes sense to have an API call that is guaranteed to escape all such characters at all times.

Usage example:

$escaped = $cl->EscapeString ( "escaping-sample@query/string" );

Prototype: function Status ()

Queries searchd status, and returns an array of status variable name and value pairs.

Usage example:

$status = $cl->Status ();
foreach ( $status as $row )
	print join ( ": ", $row ) . "\n";

Prototype: function Open ()

Opens persistent connection to the server.

Prototype: function Close ()

Closes previously opened persistent connection.

Skips steps 1-3 if using already prepared delta tarball.

Skip steps 1-2 if using already prepared delta tarball.

mysql> show engines;
+------------+----------+-------------------------------------------------------------+
| Engine     | Support  | Comment                                                     |
+------------+----------+-------------------------------------------------------------+
| MyISAM     | DEFAULT  | Default engine as of MySQL 3.23 with great performance      |
  ...
| SPHINX     | YES      | Sphinx storage engine                                       |
  ...
+------------+----------+-------------------------------------------------------------+
13 rows in set (0.00 sec)

Data source type. Mandatory, no default value. Known types are mysql, pgsql, mssql, xmlpipe and xmlpipe2, and odbc.

All other per-source options depend on source type selected by this option. Names of the options used for SQL sources (ie. MySQL, PostgreSQL, MS SQL) start with "sql_"; names of the ones used for xmlpipe and xmlpipe2 start with "xmlpipe_". All source types except xmlpipe are conditional; they might or might not be supported depending on your build settings, installed client libraries, etc. mssql type is currently only available on Windows. odbc type is available both on Windows natively and on Linux through UnixODBC library.

Example:

type = mysql

SQL server host to connect to. Mandatory, no default value. Applies to SQL source types (mysql, pgsql, mssql) only.

In the simplest case when Sphinx resides on the same host with your MySQL or PostgreSQL installation, you would simply specify "localhost". Note that MySQL client library chooses whether to connect over TCP/IP or over UNIX socket based on the host name. Specifically "localhost" will force it to use UNIX socket (this is the default and generally recommended mode) and "127.0.0.1" will force TCP/IP usage. Refer to MySQL manual for more details.

Example:

sql_host = localhost

SQL server IP port to connect to. Optional, default is 3306 for mysql source type and 5432 for pgsql type. Applies to SQL source types (mysql, pgsql, mssql) only. Note that it depends on sql_host setting whether this value will actually be used.

Example:

sql_port = 3306

SQL user to use when connecting to sql_host. Mandatory, no default value. Applies to SQL source types (mysql, pgsql, mssql) only.

Example:

sql_user = test

SQL user password to use when connecting to sql_host. Mandatory, no default value. Applies to SQL source types (mysql, pgsql, mssql) only.

Example:

sql_pass = mysecretpassword

SQL database (in MySQL terms) to use after the connection and perform further queries within. Mandatory, no default value. Applies to SQL source types (mysql, pgsql, mssql) only.

Example:

sql_db = test

UNIX socket name to connect to for local SQL servers. Optional, default value is empty (use client library default settings). Applies to SQL source types (mysql, pgsql, mssql) only.

On Linux, it would typically be /var/lib/mysql/mysql.sock. On FreeBSD, it would typically be /tmp/mysql.sock. Note that it depends on sql_host setting whether this value will actually be used.

Example:

sql_sock = /tmp/mysql.sock

MySQL client connection flags. Optional, default value is 0 (do not set any flags). Applies to mysql source type only.

This option must contain an integer value with the sum of the flags. The value will be passed to mysql_real_connect() verbatim. The flags are enumerated in mysql_com.h include file. Flags that are especially interesting in regard to indexing, with their respective values, are as follows:

For instance, you can specify 2080 (2048+32) to use both compression and SSL, or 32768 to use new authentication only. Initially, this option was introduced to be able to use compression when the indexer and mysqld are on different hosts. Compression on 1 Gbps links is most likely to hurt indexing time though it reduces network traffic, both in theory and in practice. However, enabling compression on 100 Mbps links may improve indexing time significantly (upto 20-30% of the total indexing time improvement was reported). Your mileage may vary.

Example:

mysql_connect_flags = 32 # enable compression

SSL certificate settings to use for connecting to MySQL server. Optional, default values are empty strings (do not use SSL). Applies to mysql source type only.

These directives let you set up secure SSL connection between indexer and MySQL. The details on creating the certificates and setting up MySQL server can be found in MySQL documentation.

Example:

mysql_ssl_cert = /etc/ssl/client-cert.pem
mysql_ssl_key = /etc/ssl/client-key.pem
mysql_ssl_ca = /etc/ssl/cacert.pem

ODBC DSN to connect to. Mandatory, no default value. Applies to odbc source type only.

ODBC DSN (Data Source Name) specifies the credentials (host, user, password, etc) to use when connecting to ODBC data source. The format depends on specific ODBC driver used.

Example:

odbc_dsn = Driver={Oracle ODBC Driver};Dbq=myDBName;Uid=myUsername;Pwd=myPassword

Pre-fetch query, or pre-query. Multi-value, optional, default is empty list of queries. Applies to SQL source types (mysql, pgsql, mssql) only.

Multi-value means that you can specify several pre-queries. They are executed before the main fetch query, and they will be exectued exactly in order of appeareance in the configuration file. Pre-query results are ignored.

Pre-queries are useful in a lot of ways. They are used to setup encoding, mark records that are going to be indexed, update internal counters, set various per-connection SQL server options and variables, and so on.

Perhaps the most frequent pre-query usage is to specify the encoding that the server will use for the rows it returnes. It must match the encoding that Sphinx expects (as specified by charset_type and charset_table options). Two MySQL specific examples of setting the encoding are:

sql_query_pre = SET CHARACTER_SET_RESULTS=cp1251
sql_query_pre = SET NAMES utf8

Also specific to MySQL sources, it is useful to disable query cache (for indexer connection only) in pre-query, because indexing queries are not going to be re-run frequently anyway, and there's no sense in caching their results. That could be achieved with:

sql_query_pre = SET SESSION query_cache_type=OFF

Example:

sql_query_pre = SET NAMES utf8
sql_query_pre = SET SESSION query_cache_type=OFF

Main document fetch query. Mandatory, no default value. Applies to SQL source types (mysql, pgsql, mssql) only.

There can be only one main query. This is the query which is used to retrieve documents from SQL server. You can specify up to 32 full-text fields (formally, upto SPH_MAX_FIELDS from sphinx.h), and an arbitrary amount of attributes. All of the columns that are neither document ID (the first one) nor attributes will be full-text indexed.

Document ID MUST be the very first field, and it MUST BE UNIQUE UNSIGNED POSITIVE (NON-ZERO, NON-NEGATIVE) INTEGER NUMBER. It can be either 32-bit or 64-bit, depending on how you built Sphinx; by default it builds with 32-bit IDs support but --enable-id64 option to configure allows to build with 64-bit document and word IDs support.

Example:

sql_query = \
	SELECT id, group_id, UNIX_TIMESTAMP(date_added) AS date_added, \
		title, content \
	FROM documents

Range query setup. Optional, default is empty. Applies to SQL source types (mysql, pgsql, mssql) only.

Setting this option enables ranged document fetch queries (see Section 3.7, “Ranged queries”). Ranged queries are useful to avoid notorious MyISAM table locks when indexing lots of data. (They also help with other less notorious issues, such as reduced performance caused by big result sets, or additional resources consumed by InnoDB to serialize big read transactions.)

The query specified in this option must fetch min and max document IDs that will be used as range boundaries. It must return exactly two integer fields, min ID first and max ID second; the field names are ignored.

When ranged queries are enabled, sql_query will be required to contain $start and $end macros (because it obviously would be a mistake to index the whole table many times over). Note that the intervals specified by $start..$end will not overlap, so you should not remove document IDs that are exactly equal to $start or $end from your query. The example in Section 3.7, “Ranged queries”) illustrates that; note how it uses greater-or-equal and less-or-equal comparisons.

Example:

sql_query_range = SELECT MIN(id),MAX(id) FROM documents

Range query step. Optional, default is 1024. Applies to SQL source types (mysql, pgsql, mssql) only.

Only used when ranged queries are enabled. The full document IDs interval fetched by sql_query_range will be walked in this big steps. For example, if min and max IDs fetched are 12 and 3456 respectively, and the step is 1000, indexer will call sql_query several times with the following substitutions:

Example:

sql_range_step = 1000

Kill-list query. Optional, default is empty (no query). Applies to SQL source types (mysql, pgsql, mssql) only. Introduced in version 0.9.9-rc1.

This query is expected to return a number of 1-column rows, each containing just the document ID. The returned document IDs are stored within an index. Kill-list for a given index suppresses results from other indexes, depending on index order in the query. The intended use is to help implement deletions and updates on existing indexes without rebuilding (actually even touching them), and especially to fight phantom results problem.

Let us dissect an example. Assume we have two indexes, 'main' and 'delta'. Assume that documents 2, 3, and 5 were deleted since last reindex of 'main', and documents 7 and 11 were updated (ie. their text contents were changed). Assume that a keyword 'test' occurred in all these mentioned documents when we were indexing 'main'; still occurs in document 7 as we index 'delta'; but does not occur in document 11 any more. We now reindex delta and then search through both these indexes in proper (least to most recent) order:

$res = $cl->Query ( "test", "main delta" );

First, we need to properly handle deletions. The result set should not contain documents 2, 3, or 5. Second, we also need to avoid phantom results. Unless we do something about it, document 11 will appear in search results! It will be found in 'main' (but not 'delta'). And it will make it to the final result set unless something stops it.

Kill-list, or K-list for short, is that something. Kill-list attached to 'delta' will suppress the specified rows from all the preceding indexes, in this case just 'main'. So to get the expected results, we should put all the updated and deleted document IDs into it.

Example:

sql_query_killlist = \
	SELECT id FROM documents WHERE updated_ts>=@last_reindex UNION \
	SELECT id FROM documents_deleted WHERE deleted_ts>=@last_reindex

Unsigned integer attribute declaration. Multi-value (there might be multiple attributes declared), optional. Applies to SQL source types (mysql, pgsql, mssql) only.

The column value should fit into 32-bit unsigned integer range. Values outside this range will be accepted but wrapped around. For instance, -1 will be wrapped around to 2^32-1 or 4,294,967,295.

You can specify bit count for integer attributes by appending ':BITCOUNT' to attribute name (see example below). Attributes with less than default 32-bit size, or bitfields, perform slower. But they require less RAM when using extern storage: such bitfields are packed together in 32-bit chunks in .spa attribute data file. Bit size settings are ignored if using inline storage.

Example:

sql_attr_uint = group_id
sql_attr_uint = forum_id:9 # 9 bits for forum_id

Boolean attribute declaration. Multi-value (there might be multiple attributes declared), optional. Applies to SQL source types (mysql, pgsql, mssql) only. Equivalent to sql_attr_uint declaration with a bit count of 1.

Example:

sql_attr_bool = is_deleted # will be packed to 1 bit

64-bit signed integer attribute declaration. Multi-value (there might be multiple attributes declared), optional. Applies to SQL source types (mysql, pgsql, mssql) only. Note that unlike sql_attr_uint, these values are signed. Introduced in version 0.9.9-rc1.

Example:

sql_attr_bigint = my_bigint_id

UNIX timestamp attribute declaration. Multi-value (there might be multiple attributes declared), optional. Applies to SQL source types (mysql, pgsql, mssql) only.

The column value should be a timestamp in UNIX format, ie. 32-bit unsigned integer number of seconds elapsed since midnight, January 01, 1970, GMT. Timestamps are internally stored and handled as integers everywhere. But in addition to working with timestamps as integers, it's also legal to use them along with different date-based functions - such as time segments sorting mode, or day/week/month/year extraction for GROUP BY. Note that DATE or DATETIME column types in MySQL can not be directly used as timestamps; you need to explicitly convert such columns using UNIX_TIMESTAMP function.

Example:

sql_attr_timestamp = UNIX_TIMESTAMP(added_datetime) AS added_ts

Ordinal string number attribute declaration. Multi-value (there might be multiple attributes declared), optional. Applies to SQL source types (mysql, pgsql, mssql) only.

This attribute type (so-called ordinal, for brevity) is intended to allow sorting by string values, but without storing the strings themselves. When indexing ordinals, string values are fetched from database, temporarily stored, sorted, and then replaced by their respective ordinal numbers in the array of sorted strings. So, the ordinal number is an integer such that sorting by it produces the same result as if lexicographically sorting by original strings. by string values lexicographically.

Earlier versions could consume a lot of RAM for indexing ordinals. Starting with revision r1112, ordinals accumulation and sorting also runs in fixed memory (at the cost of using additional temporary disk space), and honors mem_limit settings.

Ideally the strings should be sorted differently, depending on the encoding and locale. For instance, if the strings are known to be Russian text in KOI8R encoding, sorting the bytes 0xE0, 0xE1, and 0xE2 should produce 0xE1, 0xE2 and 0xE0, because in KOI8R value 0xE0 encodes a character that is (noticeably) after characters encoded by 0xE1 and 0xE2. Unfortunately, Sphinx does not support that at the moment and will simply sort the strings bytewise.

Note that the ordinals are by construction local to each index, and it's therefore impossible to merge ordinals while retaining the proper order. The processed strings are replaced by their sequential number in the index they occurred in, but different indexes have different sets of strings. For instance, if 'main' index contains strings "aaa", "bbb", "ccc", and so on up to "zzz", they'll be assigned numbers 1, 2, 3, and so on up to 26, respectively. But then if 'delta' only contains "zzz" the assigned number will be 1. And after the merge, the order will be broken. Unfortunately, this is impossible to workaround without storing the original strings (and once Sphinx supports storing the original strings, ordinals will not be necessary any more).

Example:

sql_attr_str2ordinal = author_name

Floating point attribute declaration. Multi-value (there might be multiple attributes declared), optional. Applies to SQL source types (mysql, pgsql, mssql) only.

The values will be stored in single precision, 32-bit IEEE 754 format. Represented range is approximately from 1e-38 to 1e+38. The amount of decimal digits that can be stored precisely is approximately 7. One important usage of the float attributes is storing latitude and longitude values (in radians), for further usage in query-time geosphere distance calculations.

Example:

sql_attr_float = lat_radians
sql_attr_float = long_radians

Multi-valued attribute (MVA) declaration. Multi-value (ie. there may be more than one such attribute declared), optional. Applies to SQL source types (mysql, pgsql, mssql) only.

Plain attributes only allow to attach 1 value per each document. However, there are cases (such as tags or categories) when it is desired to attach multiple values of the same attribute and be able to apply filtering or grouping to value lists.

The declaration format is as follows (backslashes are for clarity only; everything can be declared in a single line as well):

sql_attr_multi = ATTR-TYPE ATTR-NAME 'from' SOURCE-TYPE \
	[;QUERY] \
	[;RANGE-QUERY]

where

Example:

sql_attr_multi = uint tag from query; SELECT id, tag FROM tags
sql_attr_multi = uint tag from ranged-query; \
	SELECT id, tag FROM tags WHERE id>=$start AND id<=$end; \
	SELECT MIN(id), MAX(id) FROM tags

Post-fetch query. Optional, default value is empty. Applies to SQL source types (mysql, pgsql, mssql) only.

This query is executed immediately after sql_query completes successfully. When post-fetch query produces errors, they are reported as warnings, but indexing is not terminated. It's result set is ignored. Note that indexing is not yet completed at the point when this query gets executed, and further indexing still may fail. Therefore, any permanent updates should not be done from here. For instance, updates on helper table that permanently change the last successfully indexed ID should not be run from post-fetch query; they should be run from post-index query instead.

Example:

sql_query_post = DROP TABLE my_tmp_table

Post-index query. Optional, default value is empty. Applies to SQL source types (mysql, pgsql, mssql) only.

This query is executed when indexing is fully and succesfully completed. If this query produces errors, they are reported as warnings, but indexing is not terminated. It's result set is ignored. $maxid macro can be used in its text; it will be expanded to maximum document ID which was actually fetched from the database during indexing.

Example:

sql_query_post_index = REPLACE INTO counters ( id, val ) \
    VALUES ( 'max_indexed_id', $maxid )

Ranged query throttling period, in milliseconds. Optional, default is 0 (no throttling). Applies to SQL source types (mysql, pgsql, mssql) only.

Throttling can be useful when indexer imposes too much load on the database server. It causes the indexer to sleep for given amount of milliseconds once per each ranged query step. This sleep is unconditional, and is performed before the fetch query.

Example:

sql_ranged_throttle = 1000 # sleep for 1 sec before each query step

Document info query. Optional, default is empty. Applies to mysql source type only.

Only used by CLI search to fetch and display document information, only works with MySQL at the moment, and only intended for debugging purposes. This query fetches the row that will be displayed by CLI search utility for each document ID. It is required to contain $id macro that expands to the queried document ID.

Example:

sql_query_info = SELECT * FROM documents WHERE id=$id

Shell command that invokes xmlpipe stream producer. Mandatory. Applies to xmlpipe and xmlpipe2 source types only.

Specifies a command that will be executed and which output will be parsed for documents. Refer to Section 3.8, “xmlpipe data source” or Section 3.9, “xmlpipe2 data source” for specific format description.

Example:

xmlpipe_command = cat /home/sphinx/test.xml

xmlpipe field declaration. Multi-value, optional. Applies to xmlpipe2 source type only. Refer to Section 3.9, “xmlpipe2 data source”.

Example:

xmlpipe_field = subject
xmlpipe_field = content

xmlpipe integer attribute declaration. Multi-value, optional. Applies to xmlpipe2 source type only. Syntax fully matches that of sql_attr_uint.

Example:

xmlpipe_attr_uint = author

xmlpipe boolean attribute declaration. Multi-value, optional. Applies to xmlpipe2 source type only. Syntax fully matches that of sql_attr_bool.

Example:

xmlpipe_attr_bool = is_deleted # will be packed to 1 bit

xmlpipe UNIX timestamp attribute declaration. Multi-value, optional. Applies to xmlpipe2 source type only. Syntax fully matches that of sql_attr_timestamp.

Example:

xmlpipe_attr_timestamp = published

xmlpipe string ordinal attribute declaration. Multi-value, optional. Applies to xmlpipe2 source type only. Syntax fully matches that of sql_attr_str2ordinal.

Example:

xmlpipe_attr_str2ordinal = author_sort

xmlpipe floating point attribute declaration. Multi-value, optional. Applies to xmlpipe2 source type only. Syntax fully matches that of sql_attr_float.

Example:

xmlpipe_attr_float = lat_radians
xmlpipe_attr_float = long_radians

xmlpipe MVA attribute declaration. Multi-value, optional. Applies to xmlpipe2 source type only.

This setting declares an MVA attribute tag in xmlpipe2 stream. The contents of the specified tag will be parsed and a list of integers that will constitute the MVA will be extracted, similar to how sql_attr_multi parses SQL column contents when 'field' MVA source type is specified.

Example:

xmlpipe_attr_multi = taglist

Perform Sphinx-side UTF-8 validation and filtering to prevent XML parser from choking on non-UTF-8 documents. Optional, default is 0. Applies to xmlpipe2 source type only.

Under certain occasions it might be hard or even impossible to guarantee that the incoming XMLpipe2 document bodies are in perfectly valid and conforming UTF-8 encoding. For instance, documents with national single-byte encodings could sneak into the stream. libexpat XML parser is fragile, meaning that it will stop processing in such cases. UTF8 fixup feature lets you avoid that. When fixup is enabled, Sphinx will preprocess the incoming stream before passing it to the XML parser and replace invalid UTF-8 sequences with spaces.

Example:

xmlpipe_fixup_utf8 = 1

MS SQL Windows authentication flag. Boolean, optional, default value is 0 (false). Applies to mssql source type only. Introduced in version 0.9.9-rc1.

Whether to use currently logged in Windows account credentials for authentication when connecting to MS SQL Server. Note that when running searchd as a service, account user can differ from the account you used to install the service.

Example:

mssql_winauth = 1

MS SQL encoding type flag. Boolean, optional, default value is 0 (false). Applies to mssql source type only. Introduced in version 0.9.9-rc1.

Whether to ask for Unicode or single-byte data when querying MS SQL Server. This flag must be in sync with charset_type directive; that is, to index Unicode data, you must set both charset_type in the index (to 'utf-8') and mssql_unicode in the source (to 1). For reference, MS SQL will actually return data in UCS-2 encoding instead of UTF-8, but Sphinx will automatically handle that.

Example:

mssql_unicode = 1

Columns to unpack using zlib (aka deflate, aka gunzip). Multi-value, optional, default value is empty list of columns. Applies to SQL source types (mysql, pgsql, mssql) only. Introduced in version 0.9.9-rc1.

Columns specified using this directive will be unpacked by indexer using standard zlib algorithm (called deflate and also implemented by gunzip). When indexing on a different box than the database, this lets you offload the database, and save on network traffic. The feature is only available if zlib and zlib-devel were both available during build time.

Example:

unpack_zlib = col1
unpack_zlib = col2

Columns to unpack using MySQL UNCOMPRESS() algorithm. Multi-value, optional, default value is empty list of columns. Applies to SQL source types (mysql, pgsql, mssql) only. Introduced in version 0.9.9-rc1.

Columns specified using this directive will be unpacked by indexer using modified zlib algorithm used by MySQL COMPRESS() and UNCOMPRESS() functions. When indexing on a different box than the database, this lets you offload the database, and save on network traffic. The feature is only available if zlib and zlib-devel were both available during build time.

Example:

unpack_mysqlcompress = body_compressed
unpack_mysqlcompress = description_compressed

Buffer size for UNCOMPRESS()ed data. Optional, default value is 16M. Introduced in version 0.9.9-rc1.

When using unpack_mysqlcompress, due to implementation intrincacies it is not possible to deduce the required buffer size from the compressed data. So the buffer must be preallocated in advance, and unpacked data can not go over the buffer size. This option lets you control the buffer size, both to limit indexer memory use, and to enable unpacking of really long data fields if necessary.

Example:

unpack_mysqlcompress_maxsize = 1M

Index type. Optional, default is empty (index is plain local index). Known values are empty string or 'distributed'.

Sphinx supports two different types of indexes: local, that are stored and processed on the local machine; and distributed, that involve not only local searching but querying remote searchd instances over the network as well. Index type settings lets you choose this type. By default, indexes are local. Specifying 'distributed' for type enables distributed searching, see Section 4.7, “Distributed searching”.

Example:

type = distributed

Adds document source to local index. Multi-value, mandatory.

Specifies document source to get documents from when the current index is indexed. There must be at least one source. There may be multiple sources, without any restrictions on the source types: ie. you can pull part of the data from MySQL server, part from PostgreSQL, part from the filesystem using xmlpipe2 wrapper.

However, there are some restrictions on the source data. First, document IDs must be globally unique across all sources. If that condition is not met, you might get unexpected search results. Second, source schemas must be the same in order to be stored within the same index.

No source ID is stored automatically. Therefore, in order to be able to tell what source the matched document came from, you will need to store some additional information yourself. Two typical approaches include:

Example:

source = srcpart1
source = srcpart2
source = srcpart3

Index files path and file name (without extension). Mandatory.

Path specifies both directory and file name, but without extension. indexer will append different extensions to this path when generating final names for both permanent and temporary index files. Permanent data files have several different extensions starting with '.sp'; temporary files' extensions start with '.tmp'. It's safe to remove .tmp* files is if indexer fails to remove them automatically.

For reference, different index files store the following data:

Example:

path = /var/data/test1

Document attribute values (docinfo) storage mode. Optional, default is 'extern'. Known values are 'none', 'extern' and 'inline'.

Docinfo storage mode defines how exactly docinfo will be physically stored on disk and RAM. "none" means that there will be no docinfo at all (ie. no attributes). Normally you need not to set "none" explicitly because Sphinx will automatically select "none" when there are no attributes configured. "inline" means that the docinfo will be stored in the .spd file, along with the document ID lists. "extern" means that the docinfo will be stored separately (externally) from document ID lists, in a special .spa file.

Basically, externally stored docinfo must be kept in RAM when querying. for performance reasons. So in some cases "inline" might be the only option. However, such cases are infrequent, and docinfo defaults to "extern". Refer to Section 3.2, “Attributes” for in-depth discussion and RAM usage estimates.

Example:

docinfo = inline

Memory locking for cached data. Optional, default is 0 (do not call mlock()).

For search performance, searchd preloads a copy of .spa and .spi files in RAM, and keeps that copy in RAM at all times. But if there are no searches on the index for some time, there are no accesses to that cached copy, and OS might decide to swap it out to disk. First queries to such "cooled down" index will cause swap-in and their latency will suffer.

Setting mlock option to 1 makes Sphinx lock physical RAM used for that cached data using mlock(2) system call, and that prevents swapping (see man 2 mlock for details). mlock(2) is a privileged call, so it will require searchd to be either run from root account, or be granted enough privileges otherwise. If mlock() fails, a warning is emitted, but index continues working.

Example:

mlock = 1

A list of morphology preprocessors to apply. Optional, default is empty (do not apply any preprocessor).

Morphology preprocessors can be applied to the words being indexed to replace different forms of the same word with the base, normalized form. For instance, English stemmer will normalize both "dogs" and "dog" to "dog", making search results for both searches the same.

Built-in preprocessors include English stemmer, Russian stemmer (that supports UTF-8 and Windows-1251 encodings), Soundex, and Metaphone. The latter two replace the words with special phonetic codes that are equal is words are phonetically close. Additional stemmers provided by Snowball project libstemmer library can be enabled at compile time using --with-libstemmer configure option. Built-in English and Russian stemmers should be faster than their libstemmer counterparts, but can produce slightly different results, because they are based on an older version. Metaphone implementation is based on Double Metaphone algorithm and indexes the primary code.

Built-in values that be used in morphology option are: 'none', 'stem_en', 'stem_ru', 'stem_enru', 'soundex', and 'metaphone'. Additional values provided by libstemmer are in 'libstemmer_XXX' format, where XXX is libstemmer algorithm codename (refer to libstemmer_c/libstemmer/modules.txt for a complete list).

Several stemmers can be specified (comma-separated). They will be applied to incoming words in the order they are listed, and the processing will stop once one of the stemmers actually modifies the word. Also when wordforms feature is enabled the word will be looked up in word forms dictionary first, and if there is a matching entry in the dictionary, stemmers will not be applied at all. Or in other words, wordforms can be used to implement stemming exceptions.

Example:

morphology = stem_en, libstemmer_sv

Minimum word length at which to enable stemming. Optional, default is 1 (stem everything). Introduced in version 0.9.9-rc1.

Stemmers are not perfect, and might sometimes produce undesired results. For instance, running "gps" keyword through Porter stemmer for English results in "gp", which is not really the intent. min_stemming_len feature lets you suppress stemming based on the source word length, ie. to avoid stemming too short words. Keywords that are shorter than the given threshold will not be stemmed. Note that keywords that are exactly as long as specified will be stemmed. So in order to avoid stemming 3-character keywords, you should specify 4 for the value. For more finely grained control, refer to wordforms feature.

Example:

min_stemming_len = 4

Stopword files list (space separated). Optional, default is empty.

Stopwords are the words that will not be indexed. Typically you'd put most frequent words in the stopwords list because they do not add much value to search results but consume a lot of resources to process.

You can specify several file names, separated by spaces. All the files will be loaded. Stopwords file format is simple plain text. The encoding must match index encoding specified in charset_type. File data will be tokenized with respect to charset_table settings, so you can use the same separators as in the indexed data. The stemmers will also be applied when parsing stopwords file.

While stopwords are not indexed, they still do affect the keyword positions. For instance, assume that "the" is a stopword, that document 1 contains the line "in office", and that document 2 contains "in the office". Searching for "in office" as for exact phrase will only return the first document, as expected, even though "the" in the second one is stopped.

Example:

stopwords = /usr/local/sphinx/data/stopwords.txt
stopwords = stopwords-ru.txt stopwords-en.txt

Word forms dictionary. Optional, default is empty.

Word forms are applied after tokenizing the incoming text by charset_table rules. They essentialy let you replace one word with another. Normally, that would be used to bring different word forms to a single normal form (eg. to normalize all the variants such as "walks", "walked", "walking" to the normal form "walk"). It can also be used to implement stemming exceptions, because stemming is not applied to words found in the forms list.

Dictionaries are used to normalize incoming words both during indexing and searching. Therefore, to pick up changes in wordforms file it's required to reindex and restart searchd.

Word forms support in Sphinx is designed to support big dictionaries well. They moderately affect indexing speed: for instance, a dictionary with 1 million entries slows down indexing about 1.5 times. Searching speed is not affected at all. Additional RAM impact is roughly equal to the dictionary file size, and dictionaries are shared across indexes: ie. if the very same 50 MB wordforms file is specified for 10 different indexes, additional searchd RAM usage will be about 50 MB.

Dictionary file should be in a simple plain text format. Each line should contain source and destination word forms, in exactly the same encoding as specified in charset_type, separated by "greater" sign. Rules from the charset_table will be applied when the file is loaded. So basically it's as case sensitive as your other full-text indexed data, ie. typically case insensitive. Here's the file contents sample:

walks > walk
walked > walk
walking > walk

There is bundled spelldump utility that helps you create a dictionary file in the format Sphinx can read from source .dict and .aff dictionary files in ispell or MySpell format (as bundled with OpenOffice).

Starting with version 0.9.9-rc1, you can map several source words to a single destination word. Because the work happens on tokens, not the source text, differences in whitespace and markup are ignored.

core 2 duo > c2d
e6600 > c2d
core 2duo > c2d

Example:

wordforms = /usr/local/sphinx/data/wordforms.txt

Tokenizing exceptions file. Optional, default is empty.

Exceptions allow to map one or more tokens (including tokens with characters that would normally be excluded) to a single keyword. They are similar to wordforms in that they also perform mapping, but have a number of important differences.

Short summary of the differences is as follows:

The expected file format is also plain text, with one line per exception, and the line format is as follows:

map-from-tokens => map-to-token

Example file:

AT & T => AT&T
AT&T => AT&T
Standarten   Fuehrer => standartenfuhrer
Standarten Fuhrer => standartenfuhrer
MS Windows => ms windows
Microsoft Windows => ms windows
C++ => cplusplus
c++ => cplusplus
C plus plus => cplusplus

All tokens here are case sensitive: they will not be processed by charset_table rules. Thus, with the example exceptions file above, "At&t" text will be tokenized as two keywords "at" and "t", because of lowercase letters. On the other hand, "AT&T" will match exactly and produce single "AT&T" keyword.

Note that this map-to keyword is a) always interpereted as a single word, and b) is both case and space sensitive! In our sample, "ms windows" query will not match the document with "MS Windows" text. The query will be interpreted as a query for two keywords, "ms" and "windows". And what "MS Windows" gets mapped to is a single keyword "ms windows", with a space in the middle. On the other hand, "standartenfuhrer" will retrieve documents with "Standarten Fuhrer" or "Standarten Fuehrer" contents (capitalized exactly like this), or any capitalization variant of the keyword itself, eg. "staNdarTenfUhreR". (It won't catch "standarten fuhrer", however: this text does not match any of the listed exceptions because of case sensitivity, and gets indexed as two separate keywords.)

Whitespace in the map-from tokens list matters, but its amount does not. Any amount of the whitespace in the map-form list will match any other amount of whitespace in the indexed document or query. For instance, "AT & T" map-from token will match "AT    &  T" text, whatever the amount of space in both map-from part and the indexed text. Such text will therefore be indexed as a special "AT&T" keyword, thanks to the very first entry from the sample.

Exceptions also allow to capture special characters (that are exceptions from general charset_table rules; hence the name). Assume that you generally do not want to treat '+' as a valid character, but still want to be able search for some exceptions from this rule such as 'C++'. The sample above will do just that, totally independent of what characters are in the table and what are not.

Exceptions are applied to raw incoming document and query data during indexing and searching respectively. Therefore, to pick up changes in the file it's required to reindex and restart searchd.

Example:

exceptions = /usr/local/sphinx/data/exceptions.txt

Minimum indexed word length. Optional, default is 1 (index everything).

Only those words that are not shorter than this minimum will be indexed. For instance, if min_word_len is 4, then 'the' won't be indexed, but 'they' will be.

Example:

min_word_len = 4

Character set encoding type. Optional, default is 'sbcs'. Known values are 'sbcs' and 'utf-8'.

Different encodings have different methods for mapping their internal characters codes into specific byte sequences. Two most common methods in use today are single-byte encoding and UTF-8. Their corresponding charset_type values are 'sbcs' (stands for Single Byte Character Set) and 'utf-8'. The selected encoding type will be used everywhere where the index is used: when indexing the data, when parsing the query against this index, when generating snippets, etc.

Note that while 'utf-8' implies that the decoded values must be treated as Unicode codepoint numbers, there's a family of 'sbcs' encodings that may in turn treat different byte values differently, and that should be properly reflected in your charset_table settings. For example, the same byte value of 224 (0xE0 hex) maps to different Russian letters depending on whether koi-8r or windows-1251 encoding is used.

Example:

charset_type = utf-8

Accepted characters table, with case folding rules. Optional, default value depends on charset_type value.

charset_table is the main workhorse of Sphinx tokenizing process, ie. the process of extracting keywords from document text or query txet. It controls what characters are accepted as valid and what are not, and how the accepted characters should be transformed (eg. should the case be removed or not).

You can think of charset_table as of a big table that has a mapping for each and every of 100K+ characters in Unicode (or as of a small 256-character table if you're using SBCS). By default, every character maps to 0, which means that it does not occur within keywords and should be treated as a separator. Once mentioned in the table, character is mapped to some other character (most frequently, either to itself or to a lowercase letter), and is treated as a valid keyword part.

The expected value format is a commas-separated list of mappings. Two simplest mappings simply declare a character as valid, and map a single character to another single character, respectively. But specifying the whole table in such form would result in bloated and barely manageable specifications. So there are several syntax shortcuts that let you map ranges of characters at once. The complete list is as follows:

Control characters with codes from 0 to 31 are always treated as separators. Characters with codes 32 to 127, ie. 7-bit ASCII characters, can be used in the mappings as is. To avoid configuration file encoding issues, 8-bit ASCII characters and Unicode characters must be specified in U+xxx form, where 'xxx' is hexadecimal codepoint number. This form can also be used for 7-bit ASCII characters to encode special ones: eg. use U+20 to encode space, U+2E to encode dot, U+2C to encode comma.

Example:

# 'sbcs' defaults for English and Russian
charset_table = 0..9, A..Z->a..z, _, a..z, \
	U+A8->U+B8, U+B8, U+C0..U+DF->U+E0..U+FF, U+E0..U+FF

# 'utf-8' defaults for English and Russian
charset_table = 0..9, A..Z->a..z, _, a..z, \
	U+410..U+42F->U+430..U+44F, U+430..U+44F

Ignored characters list. Optional, default is empty.

Useful in the cases when some characters, such as soft hyphenation mark (U+00AD), should be not just treated as separators but rather fully ignored. For example, if '-' is simply not in the charset_table, "abc-def" text will be indexed as "abc" and "def" keywords. On the contrary, if '-' is added to ignore_chars list, the same text will be indexed as a single "abcdef" keyword.

The syntax is the same as for charset_table, but it's only allowed to declare characters, and not allowed to map them. Also, the ignored characters must not be present in charset_table.

Example:

ignore_chars = U+AD

Minimum word prefix length to index. Optional, default is 0 (do not index prefixes).

Prefix indexing allows to implement wildcard searching by 'wordstart*' wildcards (refer to enable_star option for details on wildcard syntax). When mininum prefix length is set to a positive number, indexer will index all the possible keyword prefixes (ie. word beginnings) in addition to the keywords themselves. Too short prefixes (below the minimum allowed length) will not be indexed.

For instance, indexing a keyword "example" with min_prefix_len=3 will result in indexing "exa", "exam", "examp", "exampl" prefixes along with the word itself. Searches against such index for "exam" will match documents that contain "example" word, even if they do not contain "exam" on itself. However, indexing prefixes will make the index grow significantly (because of many more indexed keywords), and will degrade both indexing and searching times.

There's no automatic way to rank perfect word matches higher in a prefix index, but there's a number of tricks to achieve that. First, you can setup two indexes, one with prefix indexing and one without it, search through both, and use SetIndexWeights() call to combine weights. Second, you can enable star-syntax and rewrite your extended-mode queries:

# in sphinx.conf
enable_star = 1

// in query
$cl->Query ( "( keyword | keyword* ) other keywords" );

Example:

min_prefix_len = 3

Minimum infix prefix length to index. Optional, default is 0 (do not index infixes).

For instance, indexing a keyword "test" with min_infix_len=2 will result in indexing "te", "es", "st", "tes", "est" infixes along with the word itself. Searches against such index for "es" will match documents that contain "test" word, even if they do not contain "es" on itself. However, indexing infixes will make the index grow significantly (because of many more indexed keywords), and will degrade both indexing and searching times.

There's no automatic way to rank perfect word matches higher in an infix index, but the same tricks as with prefix indexes can be applied.

Example:

min_infix_len = 3

The list of full-text fields to limit prefix indexing to. Optional, default is empty (index all fields in prefix mode).

Because prefix indexing impacts both indexing and searching performance, it might be desired to limit it to specific full-text fields only: for instance, to provide prefix searching through URLs, but not through page contents. prefix_fields specifies what fields will be prefix-indexed; all other fields will be indexed in normal mode. The value format is a comma-separated list of field names.

Example:

prefix_fields = url, domain

The list of full-text fields to limit infix indexing to. Optional, default is empty (index all fields in infix mode).

Similar to prefix_fields, but lets you limit infix-indexing to given fields.

Example:

infix_fields = url, domain

Enables star-syntax (or wildcard syntax) when searching through prefix/infix indexes. Optional, default is is 0 (do not use wildcard syntax), for compatibility with 0.9.7. Known values are 0 and 1.

This feature enables "star-syntax", or wildcard syntax, when searching through indexes which were created with prefix or infix indexing enabled. It only affects searching; so it can be changed without reindexing by simply restarting searchd.

The default value is 0, that means to disable star-syntax and treat all keywords as prefixes or infixes respectively, depending on indexing-time min_prefix_len and min_infix_len settings. The value of 1 means that star ('*') can be used at the start and/or the end of the keyword. The star will match zero or more characters.

For example, assume that the index was built with infixes and that enable_star is 1. Searching should work as follows:

Example:

enable_star = 1

N-gram lengths for N-gram indexing. Optional, default is 0 (disable n-gram indexing). Known values are 0 and 1 (other lengths to be implemented).

N-grams provide basic CJK (Chinese, Japanse, Koreasn) support for unsegmented texts. The issue with CJK searching is that there could be no clear separators between the words. Ideally, the texts would be filtered through a special program called segmenter that would insert separators in proper locations. However, segmenters are slow and error prone, and it's common to index contiguous groups of N characters, or n-grams, instead.

When this feature is enabled, streams of CJK characters are indexed as N-grams. For example, if incoming text is "ABCDEF" (where A to F represent some CJK characters) and length is 1, in will be indexed as if it was "A B C D E F". (With length equal to 2, it would produce "AB BC CD DE EF"; but only 1 is supported at the moment.) Only those characters that are listed in ngram_chars table will be split this way; other ones will not be affected.

Note that if search query is segmented, ie. there are separators between individual words, then wrapping the words in quotes and using extended mode will resut in proper matches being found even if the text was not segmented. For instance, assume that the original query is BC DEF. After wrapping in quotes on the application side, it should look like "BC" "DEF" (with quotes). This query will be passed to Sphinx and internally split into 1-grams too, resulting in "B C" "D E F" query, still with quotes that are the phrase matching operator. And it will match the text even though there were no separators in the text.

Even if the search query is not segmented, Sphinx should still produce good results, thanks to phrase based ranking: it will pull closer phrase matches (which in case of N-gram CJK words can mean closer multi-character word matches) to the top.

Example:

ngram_len = 1

N-gram characters list. Optional, default is empty.

To be used in conjunction with in ngram_len, this list defines characters, sequences of which are subject to N-gram extraction. Words comprised of other characters will not be affected by N-gram indexing feature. The value format is identical to charset_table.

Example:

ngram_chars = U+3000..U+2FA1F

Phrase boundary characters list. Optional, default is empty.

This list controls what characters will be treated as phrase boundaries, in order to adjust word positions and enable phrase-level search emulation through proximity search. The syntax is similar to charset_table. Mappings are not allowed and the boundary characters must not overlap with anything else.

On phrase boundary, additional word position increment (specified by phrase_boundary_step) will be added to current word position. This enables phrase-level searching through proximity queries: words in different phrases will be guaranteed to be more than phrase_boundary_step distance away from each other; so proximity search within that distance will be equivalent to phrase-level search.

Phrase boundary condition will be raised if and only if such character is followed by a separator; this is to avoid abbreviations such as S.T.A.L.K.E.R or URLs being treated as several phrases.

Example:

phrase_boundary = ., ?, !, U+2026 # horizontal ellipsis

Phrase boundary word position increment. Optional, default is 0.

On phrase boundary, current word position will be additionally incremented by this number. See phrase_boundary for details.

Example:

phrase_boundary_step = 100

Whether to strip HTML markup from incoming full-text data. Optional, default is 0. Known values are 0 (disable stripping) and 1 (enable stripping).

Stripping does not work with xmlpipe source type (it's suggested to upgrade to xmlpipe2 anyway). It should work with properly formed HTML and XHTML, but, just as most browsers, may produce unexpected results on malformed input (such as HTML with stray <'s or unclosed >'s).

Only the tags themselves, and also HTML comments, are stripped. To strip the contents of the tags too (eg. to strip embedded scripts), see html_remove_elements option. There are no restrictions on tag names; ie. everything that looks like a valid tag start, or end, or a comment will be stripped.

Example:

html_strip = 1

A list of markup attributes to index when stripping HTML. Optional, default is empty (do not index markup attributes).

Specifies HTML markup attributes whose contents should be retained and indexed even though other HTML markup is stripped. The format is per-tag enumeration of indexable attributes, as shown in the example below.

Example:

html_index_attrs = img=alt,title; a=title;

A list of HTML elements for which to strip contents along with the elements themselves. Optional, default is empty string (do not strip contents of any elements).

This feature allows to strip element contents, ie. everything that is between the opening and the closing tags. It is useful to remove embedded scripts, CSS, etc. Short tag form for empty elements (ie. <br />) is properly supported; ie. the text that follows such tag will not be removed.

The value is a comma-separated list of element (tag) names whose contents should be removed. Tag names are case insensitive.

Example:

html_remove_elements = style, script

Local index declaration in the distributed index. Multi-value, optional, default is empty.

This setting is used to declare local indexes that will be searched when given distributed index is searched. All local indexes will be searched sequentially, utilizing only 1 CPU or core; to parallelize processing, you can configure searchd to query itself (refer to Section 9.2.28, “agent” for the details). There might be several local indexes declared per each distributed index. Any local index can be mentioned several times in other distributed indexes.

Example:

local = chunk1
local = chunk2

Remote agent declaration in the distributed index. Multi-value, optional, default is empty.

This setting is used to declare remote agents that will be searched when given distributed index is searched. The agents can be thought of as network pointers that specify host, port, and index names. In the basic case agents would correspond to remote physical machines. More formally, that is not always correct: you can point several agents to the same remote machine; or you can even point agents to the very same single instance of searchd (in order to utilize many CPUs or cores).

The value format is as follows:

agent = specification:remote-indexes-list
specification = hostname ":" port | path

Where 'hostname' is remote host name; 'port' is remote TCP port; 'path' is Unix-domain socket path and 'remote-indexes-list' is a comma-separated list of remote index names.

All agents will be searched in parallel. However, all indexes specified for a given agent will be searched sequentially in this agent. This lets you fine-tune the configuration to the hardware. For instance, if two remote indexes are stored on the same physical HDD, it's better to configure one agent with several sequentially searched indexes to avoid HDD steping. If they are stored on different HDDs, having two agents will be advantageous, because the work will be fully parallelized. The same applies to CPUs; though CPU performance impact caused by two processes stepping on each other is somewhat smaller and frequently can be ignored at all.

On machines with many CPUs and/or HDDs, agents can be pointed to the same machine to utilize all of the hardware in parallel and reduce query latency. There is no need to setup several searchd instances for that; it's legal to configure the instance to contact itself. Here's an example setup, intended for a 4-CPU machine, that will use up to 4 CPUs in parallel to process each query:

index dist
{
	type = distributed
	local = chunk1
	agent = localhost:9312:chunk2
	agent = localhost:9312:chunk3
	agent = localhost:9312:chunk4
}

Note how one of the chunks is searched locally and the same instance of searchd queries itself to launch searches through three other ones in parallel.

Example:

agent = localhost:9312:chunk2 # contact itself
agent = /var/run/searchd.s:chunk2
agent = searchbox2:9312:chunk3,chunk4 # search remote indexes

Remote blackhole agent declaration in the distributed index. Multi-value, optional, default is empty. Introduced in version 0.9.9-rc1.

agent_blackhole lets you fire-and-forget queries to remote agents. That is useful for debugging (or just testing) production clusters: you can setup a separate debugging/testing searchd instance, and forward the requests to this instance from your production master (aggregator) instance without interfering with production work. Master searchd will attempt to connect and query blackhole agent normally, but it will neither wait nor process any responses. Also, all network errors on blackhole agents will be ignored. The value format is completely identical to regular agent directive.

Example:

agent_blackhole = testbox:9312:testindex1,testindex2

Remote agent connection timeout, in milliseconds. Optional, default is 1000 (ie. 1 second).

When connecting to remote agents, searchd will wait at most this much time for connect() call to complete succesfully. If the timeout is reached but connect() does not complete, and retries are enabled, retry will be initiated.

Example:

agent_connect_timeout = 300

Remote agent query timeout, in milliseconds. Optional, default is 3000 (ie. 3 seconds).

After connection, searchd will wait at most this much time for remote queries to complete. This timeout is fully separate from connection timeout; so the maximum possible delay caused by a remote agent equals to the sum of agent_connection_timeout and agent_query_timeout. Queries will not be retried if this timeout is reached; a warning will be produced instead.

Example:

agent_query_timeout = 10000 # our query can be long, allow up to 10 sec

Whether to pre-open all index files, or open them per each query. Optional, default is 0 (do not preopen).

This option tells searchd that it should pre-open all index files on startup (or rotation) and keep them open while it runs. Currently, the default mode is not to pre-open the files (this may change in the future). Preopened indexes take a few (currently 2) file descriptors per index. However, they save on per-query open() calls; and also they are invulnerable to subtle race conditions that may happen during index rotation under high load. On the other hand, when serving many indexes (100s to 1000s), it still might be desired to open the on per-query basis in order to save file descriptors.

This directive does not affect indexer in any way, it only affects searchd.

Example:

preopen = 1

Whether to keep the dictionary file (.spi) for this index on disk, or precache it in RAM. Optional, default is 0 (precache in RAM). Introduced in version 0.9.9-rc1.

The dictionary (.spi) can be either kept on RAM or on disk. The default is to fully cache it in RAM. That improves performance, but might cause too much RAM pressure, especially if prefixes or infixes were used. Enabling ondisk_dict results in 1 additional disk IO per keyword per query, but reduces memory footprint.

This directive does not affect indexer in any way, it only affects searchd.

Example:

ondisk_dict = 1

Whether to enable in-place index inversion. Optional, default is 0 (use separate temporary files). Introduced in version 0.9.9-rc1.

inplace_enable greatly reduces indexing disk footprint, at a cost of slightly slower indexing (it uses around 2x less disk, but yields around 90-95% the original performance).

Indexing involves two major phases. The first phase collects, processes, and partially sorts documents by keyword, and writes the intermediate result to temporary files (.tmp*). The second phase fully sorts the documents, and creates the final index files. Thus, rebuilding a production index on the fly involves around 3x peak disk footprint: 1st copy for the intermediate temporary files, 2nd copy for newly constructed copy, and 3rd copy for the old index that will be serving production queries in the meantime. (Intermediate data is comparable in size to the final index.) That might be too much disk footprint for big data collections, and inplace_enable allows to reduce it. When enabled, it reuses the temporary files, outputs the final data back to them, and renames them on completion. However, this might require additional temporary data chunk relocation, which is where the performance impact comes from.

This directive does not affect searchd in any way, it only affects indexer.

Example:

inplace_enable = 1

In-place inversion fine-tuning option. Controls preallocated hitlist gap size. Optional, default is 0. Introduced in version 0.9.9-rc1.

This directive does not affect searchd in any way, it only affects indexer.

Example:

inplace_hit_gap = 1M

In-place inversion fine-tuning option. Controls preallocated docinfo gap size. Optional, default is 0. Introduced in version 0.9.9-rc1.

This directive does not affect searchd in any way, it only affects indexer.

Example:

inplace_docinfo_gap = 1M

In-place inversion fine-tuning option. Controls relocation buffer size within indexing memory arena. Optional, default is 0.1. Introduced in version 0.9.9-rc1.

This directive does not affect searchd in any way, it only affects indexer.

Example:

inplace_reloc_factor = 0.1

In-place inversion fine-tuning option. Controls in-place write buffer size within indexing memory arena. Optional, default is 0.1. Introduced in version 0.9.9-rc1.

This directive does not affect searchd in any way, it only affects indexer.

Example:

inplace_write_factor = 0.1

Whether to index the original keywords along with the stemmed/remapped versions. Optional, default is 0 (do not index). Introduced in version 0.9.9-rc1.

When enabled, index_exact_words forces indexer to put the raw keywords in the index along with the stemmed versions. That, in turn, enables exact form operator in the query language to work. This impacts the index size and the indexing time. However, searching performance is not impacted at all.

Example:

index_exact_words = 1

Position increment on overshort (less that min_word_len) keywords. Optional, allowed values are 0 and 1, default is 1. Introduced in version 0.9.9-rc1.

This directive does not affect searchd in any way, it only affects indexer.

Example:

overshort_step = 1

Position increment on stopwords. Optional, allowed values are 0 and 1, default is 1. Introduced in version 0.9.9-rc1.

This directive does not affect searchd in any way, it only affects indexer.

Example:

stopword_step = 1

Indexing RAM usage limit. Optional, default is 32M.

Enforced memory usage limit that the indexer will not go above. Can be specified in bytes, or kilobytes (using K postfix), or megabytes (using M postfix); see the example. This limit will be automatically raised if set to extremely low value causing I/O buffers to be less than 8 KB; the exact lower bound for that depends on the indexed data size. If the buffers are less than 256 KB, a warning will be produced.

Maximum possible limit is 2047M. Too low values can hurt indexing speed, but 256M to 1024M should be enough for most if not all datasets. Setting this value too high can cause SQL server timeouts. During the document collection phase, there will be periods when the memory buffer is partially sorted and no communication with the database is performed; and the database server can timeout. You can resolve that either by raising timeouts on SQL server side or by lowering mem_limit.

Example:

mem_limit = 256M
# mem_limit = 262144K # same, but in KB
# mem_limit = 268435456 # same, but in bytes

Maximum I/O operations per second, for I/O throttling. Optional, default is 0 (unlimited).

I/O throttling related option. It limits maximum count of I/O operations (reads or writes) per any given second. A value of 0 means that no limit is imposed.

indexer can cause bursts of intensive disk I/O during indexing, and it might desired to limit its disk activity (and keep something for other programs running on the same machine, such as searchd). I/O throttling helps to do that. It works by enforcing a minimum guaranteed delay between subsequent disk I/O operations performed by indexer. Modern SATA HDDs are able to perform up to 70-100+ I/O operations per second (that's mostly limited by disk heads seek time). Limiting indexing I/O to a fraction of that can help reduce search performance dedgradation caused by indexing.

Example:

max_iops = 40

Maximum allowed I/O operation size, in bytes, for I/O throttling. Optional, default is 0 (unlimited).

I/O throttling related option. It limits maximum file I/O operation (read or write) size for all operations performed by indexer. A value of 0 means that no limit is imposed. Reads or writes that are bigger than the limit will be split in several smaller operations, and counted as several operation by max_iops setting. At the time of this writing, all I/O calls should be under 256 KB (default internal buffer size) anyway, so max_iosize values higher than 256 KB must not affect anything.

Example:

max_iosize = 1048576

Maximum allowed field size for XMLpipe2 source type, bytes. Optional, default is 2 MB.

Example:

max_xmlpipe2_field = 8M

Write buffer size, bytes. Optional, default is 1 MB.

Write buffers are used to write both temporary and final index files when indexing. Larger buffers reduce the number of required disk writes. Memory for the buffers is allocated in addition to mem_limit. Note that several (currently up to 4) buffers for different files will be allocated, proportionally increasing the RAM usage.

Example:

write_buffer = 4M

This setting lets you specify IP address and port, or Unix-domain socket path, that searchd will listen on. Introduced in version 0.9.9-rc1.

The informal grammar for listen setting is:

listen = ( address ":" port | port | path ) [ ":" protocol ]

I.e. you can specify either an IP address (or hostname) and port number, or just a port number, or Unix socket path. If you specify port number but not the address, searchd will listen on all network interfaces. Unix path is identified by a leading slash.

Starting with version 0.9.9-rc2, you can also specify a protocol handler (listener) to be used for connections on this socket. Supported protocol values are 'sphinx' (Sphinx 0.9.x API protocol) and 'mysql41' (MySQL protocol used since 4.1 upto at least 5.1). More details on MySQL protocol support can be found in Section 4.9, “MySQL protocol support and SphinxQL” section.

Examples:

listen = localhost
listen = localhost:5000
listen = 192.168.0.1:5000
listen = /var/run/sphinx.s
listen = 9312
listen = localhost:9306:mysql41

There can be multiple listen directives, searchd will listen for client connections on all specified ports and sockets. If no listen directive is found then the server will listen on all available interfaces using the default port (which is 9312).

Unix-domain sockets are not supported on Windows.

Interface IP address to bind on. Optional, default is 0.0.0.0 (ie. listen on all interfaces). DEPRECATED, use listen instead.

address setting lets you specify which network interface searchd will bind to, listen on, and accept incoming network connections on. The default value is 0.0.0.0 which means to listen on all interfaces. At the time, you can not specify multiple interfaces.

Example:

address = 192.168.0.1

searchd TCP port number. DEPRECATED, use listen instead. Used to be mandatory. Default port number is 9312.

Example:

port = 9312

Log file name. Optional, default is 'searchd.log'. All searchd run time events will be logged in this file.

Example:

log = /var/log/searchd.log

Query log file name. Optional, default is empty (do not log queries). All search queries will be logged in this file. The format is described in Section 4.8, “searchd query log format”.

Example:

query_log = /var/log/query.log

Network client request read timeout, in seconds. Optional, default is 5 seconds. searchd will forcibly close the client connections which fail to send a query within this timeout.

Example:

read_timeout = 1

Maximum time to wait between requests (in seconds) when using persistent connections. Optional, default is five minutes.

Example:

client_timeout = 3600

Maximum amount of children to fork (or in other words, concurrent searches to run in parallel). Optional, default is 0 (unlimited).

Useful to control server load. There will be no more than this much concurrent searches running, at all times. When the limit is reached, additional incoming clients are dismissed with temporarily failure (SEARCHD_RETRY) status code and a message stating that the server is maxed out.

Example:

max_children = 10

searchd process ID file name. Mandatory.

PID file will be re-created (and locked) on startup. It will contain head daemon process ID while the daemon is running, and it will be unlinked on daemon shutdown. It's mandatory because Sphinx uses it internally for a number of things: to check whether there already is a running instance of searchd; to stop searchd; to notify it that it should rotate the indexes. Can also be used for different external automation scripts.

Example:

pid_file = /var/run/searchd.pid

Maximum amount of matches that the daemon keeps in RAM for each index and can return to the client. Optional, default is 1000.

Introduced in order to control and limit RAM usage, max_matches setting defines how much matches will be kept in RAM while searching each index. Every match found will still be processed; but only best N of them will be kept in memory and return to the client in the end. Assume that the index contains 2,000,000 matches for the query. You rarely (if ever) need to retrieve all of them. Rather, you need to scan all of them, but only choose "best" at most, say, 500 by some criteria (ie. sorted by relevance, or price, or anything else), and display those 500 matches to the end user in pages of 20 to 100 matches. And tracking only the best 500 matches is much more RAM and CPU efficient than keeping all 2,000,000 matches, sorting them, and then discarding everything but the first 20 needed to display the search results page. max_matches controls N in that "best N" amount.

This parameter noticeably affects per-query RAM and CPU usage. Values of 1,000 to 10,000 are generally fine, but higher limits must be used with care. Recklessly raising max_matches to 1,000,000 means that searchd will have to allocate and initialize 1-million-entry matches buffer for every query. That will obviously increase per-query RAM usage, and in some cases can also noticeably impact performance.

CAVEAT EMPTOR! Note that there also is another place where this limit is enforced. max_matches can be decreased on the fly through the corresponding API call, and the default value in the API is also set to 1,000. So in order to retrieve more than 1,000 matches to your application, you will have to change the configuration file, restart searchd, and set proper limit in SetLimits() call. Also note that you can not set the value in the API higher than the value in the .conf file. This is prohibited in order to have some protection against malicious and/or malformed requests.

Example:

max_matches = 10000

Prevents searchd stalls while rotating indexes with huge amounts of data to precache. Optional, default is 1 (enable seamless rotation).

Indexes may contain some data that needs to be precached in RAM. At the moment, .spa, .spi and .spm files are fully precached (they contain attribute data, MVA data, and keyword index, respectively.) Without seamless rotate, rotating an index tries to use as little RAM as possible and works as follows:

However, if there's a lot of attribute or dictionary data, then preloading step could take noticeble time - up to several minutes in case of preloading 1-5+ GB files.

With seamless rotate enabled, rotation works as follows:

Seamless rotate comes at the cost of higher peak memory usage during the rotation (because both old and new copies of .spa/.spi/.spm data need to be in RAM while preloading new copy). Average usage stays the same.

Example:

seamless_rotate = 1

Whether to forcibly preopen all indexes on startup. Optional, default is 0 (do not preopen). Enforces enabled preopen on all served indexes, to avoid manually specifying it in every index.

Example:

preopen_indexes = 1

Whether to unlink .old index copies on succesful rotation. Optional, default is 1 (do unlink).

Example:

unlink_old = 0

When calling UpdateAttributes() to update document attributes in real-time, changes are first written to the in-memory copy of attributes (docinfo must be set to extern). Then, once searchd shuts down normally (via SIGTERM being sent), the changes are written to disk. Introduced in version 0.9.9-rc1.

Starting with 0.9.9-rc1, it is possible to tell searchd to periodically write these changes back to disk, to avoid them being lost. The time between those intervals is set with attr_flush_period, in seconds.

It defaults to 0, which disables the periodic flushing, but flushing will still occur at normal shut-down.

Example:

attr_flush_period = 900 # persist updates to disk every 15 minutes

Instance-wide defaults for ondisk_dict directive. Optional, default it 0 (precache dictionaries in RAM). Introduced in version 0.9.9-rc1.

This directive lets you specify the default value of ondisk_dict for all the indexes served by this copy of searchd. Per-index directive take precedence, and will overwrite this instance-wide default value, allowing for fine-grain control.

Example:

ondisk_dict_default = 1 # keep all dictionaries on disk

Maximum allowed network packet size. Limits both query packets from clients, and response packets from remote agents in distributed environment. Only used for internal sanity checks, does not directly affect RAM use or performance. Optional, default is 8M. Introduced in version 0.9.9-rc1.

Example:

max_packet_size = 32M

Shared pool size for in-memory MVA updates storage. Optional, default size is 1M. Introduced in version 0.9.9-rc1.

This setting controls the size of the shared storage pool for updated MVA values. Specifying 0 for the size disable MVA updates at all. Once the pool size limit is hit, MVA update attempts will result in an error. However, updates on regular (scalar) attributes will still work. Due to internal technical difficulties, currently it is not possible to store (flush) any updates on indexes where MVA were updated; though this might be implemented in the future. In the meantime, MVA updates are intended to be used as a measure to quickly catchup with latest changes in the database until the next index rebuild; not as a persistent storage mechanism.

Example:

mva_updates_pool = 16M

Path (formally prefix) for the crash log files. Optional, default is empty (do not create crash logs). Introduced in version 0.9.9-rc1.

This is a debugging setting, to help catch rare offending queries causing crashes without otherwise affecting production instances. When enabled, searchd will intercept crash signals such as SIGSEGV, and dump offending query packets to files named "crash_log_path.PID", where PID is crashed process ID.

Example:

crash_log_path = /home/sphinx/log/crashlog

Maximum allowed per-query filter count. Only used for internal sanity checks, does not directly affect RAM use or performance. Optional, default is 256. Introduced in version 0.9.9-rc1.

Example:

max_filters = 1024

Maximum allowed per-filter values count. Only used for internal sanity checks, does not directly affect RAM use or performance. Optional, default is 4096. Introduced in version 0.9.9-rc1.

Example:

max_filter_values = 16384

TCP listen backlog. Optional, default is 5.

Windows builds currently (as of 0.9.9) can only process the requests one by one. Concurrent requests will be enqueued by the TCP stack on OS level, and requests that can not be enqueued will immediately fail with "connection refused" message. listen_backlog directive controls the length of the connection queue. Non-Windows builds should work fine with the default value.

Example:

listen_backlog = 20

Per-keyword read buffer size. Optional, default is 256K.

For every keyword occurrence in every search query, there are two associated read buffers (one for document list and one for hit list). This setting lets you control their sizes, increasing per-query RAM use, but possibly decreasing IO time.

Example:

read_buffer = 1M

Unhinted read size. Optional, default is 32K.

When querying, some reads know in advance exactly how much data is there to be read, but some currently do not. Most prominently, hit list size in not currently known in advance. This setting lest you control how much data to read in such cases. It will impact hit list IO time, reducing it for lists larger than unhinted read size, but raising it for smaller lists. It will not affect RAM use because read buffer will be already allocated. So it should be not greater than read_buffer.

Example:

read_unhinted = 32K