Setting variables online


SET [GLOBAL] server_variable_name = value
SET [INDEX index_name] GLOBAL @user_variable_name = (int_val1 [, int_val2, ...])
SET NAMES value [COLLATE value]
SET @@dummy_variable = ignored_value

The SET statement in Manticore Search allows you to modify variable values. Variable names are case-insensitive, and no variable value changes will persist after a server restart.

Manticore Search supports the SET NAMES statement and SET @@variable_name syntax for compatibility with third-party MySQL client libraries, connectors, and frameworks that may require running these statements when connecting. However, these statements do not have any effect on Manticore Search itself.

There are four classes of variables in Manticore Search:

  1. Per-session server variable: set var_name = value
  2. Global server variable: set global var_name = value
  3. Global user variable: set global @var_name = (value)
  4. Global distributed variable: set index dist_index_name global @var_name = (value)

Global user variables are shared between concurrent sessions. The only supported value type is a list of BIGINTs, and these variables can be used with the IN() operator for filtering purposes. The primary use case for this feature is to upload large lists of values to searchd once and reuse them multiple times later, reducing network overhead. Global user variables can be transferred to all agents of a distributed table or set locally in the case of a local table defined in a distributed table. Example:

// in session 1
mysql> SET GLOBAL @myfilter=(2,3,5,7,11,13);
Query OK, 0 rows affected (0.00 sec)

// later in session 2
mysql> SELECT * FROM test1 WHERE group_id IN @myfilter;
| id   | weight | group_id | date_added | title           | tag  |
|    3 |      1 |        2 | 1299338153 | another doc     | 15   |
|    4 |      1 |        2 | 1299338153 | doc number four | 7,40 |
2 rows in set (0.02 sec)

Manticore Search supports per-session and global server variables that affect specific server settings in their respective scopes. Below is a list of known per-session and global server variables:

Known per-session server variables:

  • AUTOCOMMIT = {0 | 1} determines if data modification statements should be implicitly wrapped by BEGIN and COMMIT.
  • COLLATION_CONNECTION = collation_name selects the collation for ORDER BY or GROUP BY on string values in subsequent queries. Refer to Collations for a list of known collation names.
  • WAIT_TIMEOUT = <value> sets connection timeout, either per session or global. Global can only be set on a VIP connection.
  • PROFILING = {0 | 1} enables query profiling in the current session. Defaults to 0. See also show profile.
  • MAX_THREADS_PER_QUERY = <POSITIVE_INT_VALUE> redefines max_threads_per_query in the runtime. Per-session variable influences only the queries run in the same session (connection), i.e. up to disconnect. Value 0 means 'no limit'. If both per-session and the global variables are set, the per-session one has a higher priority.
  • ro = {1 | 0} switches session to read-only mode or back. In show variables output the variable displayed with name session_read_only.

Known global server variables are:

  • QUERY_LOG_FORMAT = {plain | sphinxql} Changes the current log format.
  • LOG_LEVEL = {info | debug | replication | debugv | debugvv} Changes the current log verboseness level.
  • QCACHE_MAX_BYTES = <value> Changes the query_cache RAM use limit to a given value.
  • QCACHE_THRESH_MSEC = <value> Changes the query_cache> minimum wall time threshold to a given value.
  • QCACHE_TTL_SEC = <value> Changes the query_cache TTL for a cached result to a given value.
  • MAINTENANCE = {0 | 1} When set to 1, puts the server in maintenance mode. Only clients with VIP connections can execute queries in this mode. All new non-VIP incoming connections are refused. Existing connections are left intact.
  • GROUPING_IN_UTC = {0 | 1} When set to 1, causes timed grouping functions (day(), month(), year(), yearmonth(), yearmonthday()) to be calculated in UTC. Read the doc for grouping_in_utc config params for more details.
  • QUERY_LOG_MIN_MSEC = <value> Changes the query_log_min_msec searchd settings value. In this case, it expects the value exactly in milliseconds and doesn't parse time suffixes, as in config.

    Warning: this is a very specific and 'hard' variable; filtered out messages will be just dropped and not written into the log at all. Better just filter your log with something like 'grep', in this case, you'll have at least the full original log as a backup.

  • LOG_DEBUG_FILTER = <string value> Filters out redundant log messages. If the value is set, then all logs with level > INFO (i.e., DEBUG, DEBUGV, etc.) will be compared with the string and output only in the case they start with the given value.
  • MAX_THREADS_PER_QUERY = <POSITIVE_INT_VALUE> Redefines max_threads_per_query at runtime. As global, it changes behavior for all sessions. Value 0 means 'no limit'. If both per-session and global variables are set, the per-session one has a higher priority.
  • NET_WAIT = {-1 | 0 | POSITIVE_INT_VALUE} Changes the net_wait_tm searchd settings value.
  • IOSTATS = {0 | 1} Enables or disables I/O operations (except for attributes) reporting in the query log.
  • CPUSTATS= {1|0} Turns on/off CPU time tracking.
  • COREDUMP= {1|0} Turns on/off saving a core file or a minidump of the server on crash. More details here.
  • PSEUDO_SHARDING = {1|0} Turns on/off search pseudo-sharding.
  • SECONDARY_INDEXES = {1|0} Turns on/off secondary indexes for search queries.
  • ES_COMPAT = {on/off/dashboards} When set to on (default), Elasticsearch-like write requests are supported; off disables the support; dashboards enables the support and also allows requests from Kibana (this functionality is experimental).


mysql> SET autocommit=0;
Query OK, 0 rows affected (0.00 sec)

mysql> SET GLOBAL query_log_format=sphinxql;
Query OK, 0 rows affected (0.00 sec)

mysql> SET GLOBAL @banned=(1,2,3);
Query OK, 0 rows affected (0.01 sec)

mysql> SET INDEX users GLOBAL @banned=(1,2,3);
Query OK, 0 rows affected (0.01 sec)

To make user variables persistent, make sure sphinxql_state is enabled.

⪢ Extensions


SphinxSE is a MySQL storage engine that can be compiled into MySQL/MariaDB servers using their pluggable architecture.

Despite its name, SphinxSE does not actually store any data itself. Instead, it serves as a built-in client that enables the MySQL server to communicate with searchd, execute search queries, and retrieve search results. All indexing and searching take place outside MySQL.

Some common SphinxSE applications include:

  • Simplifying the porting of MySQL Full-Text Search (FTS) applications to Manticore;
  • Enabling Manticore use with programming languages for which native APIs are not yet available;
  • Offering optimizations when additional Manticore result set processing is needed on the MySQL side (e.g., JOINs with original document tables or additional MySQL-side filtering).

Installing SphinxSE

You will need to obtain a copy of MySQL sources, prepare those, and then recompile MySQL binary. MySQL sources (mysql-5.x.yy.tar.gz) could be obtained from website.

Compiling MySQL 5.0.x with SphinxSE

  1. copy sphinx.5.0.yy.diff patch file into MySQL sources directory and run
    $ patch -p1 < sphinx.5.0.yy.diff

    If there's no .diff file exactly for the specific version you need to: build, try applying .diff with closest version numbers. It is important that the patch should apply with no rejects.

  2. in MySQL sources directory, run
    $ sh BUILD/
  3. in MySQL sources directory, create sql/sphinx directory in and copy all files in mysqlse directory from Manticore sources there. Example:
    $ cp -R /root/builds/sphinx-0.9.7/mysqlse /root/builds/mysql-5.0.24/sql/sphinx
  4. configure MySQL and enable the new engine:
    $ ./configure --with-sphinx-storage-engine
  5. build and install MySQL:
    $ make
    $ make install

Compiling MySQL 5.1.x with SphinxSE

  1. In the MySQL sources directory, create a storage/sphinx directory and copy all files from the mysqlse directory in the Manticore sources to this new location. For example:
    $ cp -R /root/builds/sphinx-0.9.7/mysqlse /root/builds/mysql-5.1.14/storage/sphinx
  2. In the MySQL source directory, run:
    $ sh BUILD/
  3. Configure MySQL and enable the Manticore engine:
    $ ./configure --with-plugins=sphinx
  4. Build and install MySQL:
    $ make
    $ make install

Checking SphinxSE installation

To verify that SphinxSE has been successfully compiled into MySQL, start the newly built server, run the MySQL client, and issue the SHOW ENGINES query. You should see a list of all available engines. Manticore should be present, and the "Support" column should display "YES":

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

Using SphinxSE

To search using SphinxSE, you'll need to create a special ENGINE=SPHINX "search table" and then use a SELECT statement with the full-text query placed in the WHERE clause for the query column.

Here's an example create statement and search query:

    weight      INTEGER NOT NULL,
    query       VARCHAR(3072) NOT NULL,
    group_id    INTEGER,
) ENGINE=SPHINX CONNECTION="sphinx://localhost:9312/test";

SELECT * FROM t1 WHERE query='test it;mode=any';

In a search table, the first three columns must have the following types: INTEGER UNSIGNED or BIGINT for the 1st column (document ID), INTEGER or BIGINT for the 2nd column (match weight), and VARCHAR or TEXT for the 3rd column (your query). This mapping is fixed; you cannot omit any of these three required columns, move them around, or change their types. Additionally, the query column must be indexed, while all others should remain unindexed. Column names are ignored, so you can use any arbitrary names.

Additional columns must be either INTEGER, TIMESTAMP, BIGINT, VARCHAR, or FLOAT. They will be bound to attributes provided in the Manticore result set by name, so their names must match the attribute names specified in sphinx.conf. If there's no matching attribute name in the Manticore search results, the column will have NULL values.

Special "virtual" attribute names can also be bound to SphinxSE columns. Use _sph_ instead of @ for that purpose. For example, to obtain the values of @groupby, @count, or @distinct virtual attributes, use _sph_groupby, _sph_count, or _sph_distinct column names, respectively.

The CONNECTION string parameter is used to specify the Manticore host, port, and table. If no connection string is specified in CREATE TABLE, the table name * (i.e., search all tables) and localhost:9312 are assumed. The connection string syntax is as follows:


You can change the default connection string later:


You can also override these parameters on a per-query basis.

As shown in the example, both the query text and search options should be placed in the WHERE clause on the search query column (i.e., the 3rd column). Options are separated by semicolons and their names from values by an equality sign. Any number of options can be specified. The available options are:

  • query - query text;
  • mode - matching mode. Must be one of "all", "any", "phrase", "boolean", or "extended". Default is "all";
  • sort - match sorting mode. Must be one of "relevance", "attr_desc", "attr_asc", "time_segments", or "extended". In all modes besides "relevance", the attribute name (or sorting clause for "extended") is also required after a colon:
    ... WHERE query='test;sort=attr_asc:group_id';
    ... WHERE query='test;sort=extended:@weight desc, group_id asc';
  • offset - offset into the result set; default is 0;
  • limit - number of matches to retrieve from the result set; default is 20;
  • index - names of the tables to search:
    ... WHERE query='test;index=test1;';
    ... WHERE query='test;index=test1,test2,test3;';
  • minid, maxid - min and max document ID to match;
  • weights - comma-separated list of weights to be assigned to Manticore full-text fields:
    ... WHERE query='test;weights=1,2,3;';
  • filter, !filter - comma-separated attribute name and a set of values to match:
    # only include groups 1, 5 and 19
    ... WHERE query='test;filter=group_id,1,5,19;';
    # exclude groups 3 and 11
    ... WHERE query='test;!filter=group_id,3,11;';
  • range, !range - comma-separated (integer or bigint) Manticore attribute name, and min and max values to match:
    # include groups from 3 to 7, inclusive
    ... WHERE query='test;range=group_id,3,7;';
    # exclude groups from 5 to 25
    ... WHERE query='test;!range=group_id,5,25;';
  • floatrange, !floatrange - comma-separated (floating point) Manticore attribute name, and min and max values to match:
    # filter by a float size
    ... WHERE query='test;floatrange=size,2,3;';
    # pick all results within 1000 meter from geoanchor
    ... WHERE query='test;floatrange=@geodist,0,1000;';
  • maxmatches - maxmatches - per-query max matches value, as in max_matches search option:
    ... WHERE query='test;maxmatches=2000;';
  • cutoff - maximum allowed matches, as in cutoff search option:
    ... WHERE query='test;cutoff=10000;';
  • maxquerytime - maximum allowed query time (in milliseconds), as in max_query_time search option:
    ... WHERE query='test;maxquerytime=1000;';
  • groupby - group-by function and attribute. Read this about grouping search results:
    ... WHERE query='test;groupby=day:published_ts;';
    ... WHERE query='test;groupby=attr:group_id;';
  • groupsort - group-by sorting clause:
    ... WHERE query='test;groupsort=@count desc;';
  • distinct - an attribute to compute COUNT(DISTINCT) for when doing group-by:
    ... WHERE query='test;groupby=attr:country_id;distinct=site_id';
  • indexweights - comma-separated list of table names and weights to use when searching through several tables:
    ... WHERE query='test;indexweights=tbl_exact,2,tbl_stemmed,1;';
  • fieldweights - comma-separated list of per-field weights that can be used by the ranker:
    ... WHERE query='test;fieldweights=title,10,abstract,3,content,1;';
  • comment - a string to mark this query in query log, as in comment search option:
    ... WHERE query='test;comment=marker001;';
  • select - a string with expressions to compute:
    ... WHERE query='test;select=2*a+3*** as myexpr;';
  • host, port - remote searchd host name and TCP port, respectively:
    ... WHERE query='test;host=sphinx-test.loc;port=7312;';
  • ranker - a ranking function to use with "extended" matching mode, as in ranker. Known values are "proximity_bm25", "bm25", "none", "wordcount", "proximity", "matchany", "fieldmask", "sph04", "expr:EXPRESSION" syntax to support expression-based ranker (where EXPRESSION should be replaced with your specific ranking formula), and "export:EXPRESSION":
    ... WHERE query='test;mode=extended;ranker=bm25;';
    ... WHERE query='test;mode=extended;ranker=expr:sum(lcs);';

    The "export" ranker functions similarly to ranker=expr, but it retains the per-document factor values, while ranker=expr discards them after computing the final WEIGHT() value. Keep in mind that ranker=export is intended for occasional use, such as training a machine learning (ML) function or manually defining your own ranking function, and should not be used in actual production. When utilizing this ranker, you'll likely want to examine the output of the RANKFACTORS() function, which generates a string containing all the field-level factors for each document.

  • sql
    FROM myindex
    WHERE MATCH('dog')
    OPTION ranker=export('100*bm25');
*************************** 1\. row ***************************
           id: 555617
    published: 1110067331
   channel_id: 1059819
        title: 7
      content: 428
     weight(): 69900
rankfactors(): bm25=699, bm25a=0.666478, field_mask=2,
doc_word_count=1, field1=(lcs=1, hit_count=4, word_count=1,
tf_idf=1.038127, min_idf=0.259532, max_idf=0.259532, sum_idf=0.259532,
min_hit_pos=120, min_best_span_pos=120, exact_hit=0,
max_window_hits=1), word1=(tf=4, idf=0.259532)
*************************** 2\. row ***************************
           id: 555313
    published: 1108438365
   channel_id: 1058561
        title: 8
      content: 249
     weight(): 68500
rankfactors(): bm25=685, bm25a=0.675213, field_mask=3,
doc_word_count=1, field0=(lcs=1, hit_count=1, word_count=1,
tf_idf=0.259532, min_idf=0.259532, max_idf=0.259532, sum_idf=0.259532,
min_hit_pos=8, min_best_span_pos=8, exact_hit=0, max_window_hits=1),
field1=(lcs=1, hit_count=2, word_count=1, tf_idf=0.519063,
min_idf=0.259532, max_idf=0.259532, sum_idf=0.259532, min_hit_pos=36,
min_best_span_pos=36, exact_hit=0, max_window_hits=1), word1=(tf=3,
  • geoanchor - geodistance anchor. Learn more about Geo-search in this section. Takes 4 parameters, which are the latitude and longitude attribute names, and anchor point coordinates, respectively:
    ... WHERE query='test;geoanchor=latattr,lonattr,0.123,0.456';

One very important note is that it is much more efficient to let Manticore handle sorting, filtering, and slicing the result set, rather than increasing the max matches count and using WHERE, ORDER BY, and LIMIT clauses on the MySQL side. This is due to two reasons. First, Manticore employs a variety of optimizations and performs these tasks better than MySQL. Second, less data would need to be packed by searchd, transferred, and unpacked by SphinxSE.

You can obtain additional information related to the query results using the SHOW ENGINE SPHINX STATUS statement:

  • sql
| Type   | Name  | Status                                          |
| SPHINX | stats | total: 25, total found: 25, time: 126, words: 2 |
| SPHINX | words | sphinx:591:1256 soft:11076:15945                |
2 rows in set (0.00 sec)

You can also access this information through status variables. Keep in mind that using this method does not require super-user privileges.

  • sql
mysql> SHOW STATUS LIKE 'sphinx_%';
| Variable_name      | Value                            |
| sphinx_total       | 25                               |
| sphinx_total_found | 25                               |
| sphinx_time        | 126                              |
| sphinx_word_count  | 2                                |
| sphinx_words       | sphinx:591:1256 soft:11076:15945 |
5 rows in set (0.00 sec)

SphinxSE search tables can be joined with tables using other engines. Here's an example using the "documents" table from example.sql:

  • sql
mysql> SELECT content, date_added FROM test.documents docs
-> JOIN t1 ON (
-> WHERE query="one document;mode=any";

| content                             | docdate             |
| this is my test document number two | 2006-06-17 14:04:28 |
| this is my test document number one | 2006-06-17 14:04:28 |
2 rows in set (0.00 sec)

| Type   | Name  | Status                                      |
| SPHINX | stats | total: 2, total found: 2, time: 0, words: 2 |
| SPHINX | words | one:1:2 document:2:2                        |
2 rows in set (0.00 sec)

Building snippets via MySQL

SphinxSE also features a UDF function that allows you to create snippets using MySQL. This functionality is similar to HIGHLIGHT(), but can be accessed through MySQL+SphinxSE.

The binary providing the UDF is called and should be automatically built and installed in the appropriate location along with SphinxSE. If it doesn't install automatically for some reason, locate in the build directory and copy it to your MySQL instance's plugins directory. Once done, register the UDF with the following statement:


The function name must be sphinx_snippets; you cannot use an arbitrary name. The function arguments are as follows:

Prototype: function sphinx_snippets ( document, table, words [, options] );

The document and words arguments can be either strings or table columns. Options must be specified like this: 'value' AS option_name. For a list of supported options, refer to the Highlighting section. The only UDF-specific additional option is called sphinx and allows you to specify the searchd location (host and port).

Usage examples:

SELECT sphinx_snippets('hello world doc', 'main', 'world',
    'sphinx://' AS sphinx, true AS exact_phrase,
    '[**]' AS before_match, '[/**]' AS after_match)
FROM documents;

SELECT title, sphinx_snippets(text, 'index', 'mysql php') AS text
    FROM sphinx, documents
    WHERE query='mysql php' AND;