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12.8. Full-Text Search Functions

MATCH (col1,col2,...) AGAINST (expr [search_modifier])

search_modifier: { IN BOOLEAN MODE | WITH QUERY EXPANSION }

MySQL has support for full-text indexing and searching:

Full-text searching is performed using MATCH() ... AGAINST syntax. MATCH() takes a comma-separated list that names the columns to be searched. AGAINST takes a string to search for, and an optional modifier that indicates what type of search to perform. The search string must be a literal string, not a variable or a column name. There are three types of full-text searches:

Constraints on full-text searching are listed in Section 12.8.4, “Full-Text Restrictions”.

mysql> CREATE TABLE articles (
    ->   id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
    ->   title VARCHAR(200),
    ->   body TEXT,
    ->   FULLTEXT (title,body)
    -> );
Query OK, 0 rows affected (0.00 sec)

mysql> INSERT INTO articles (title,body) VALUES
    -> ('MySQL Tutorial','DBMS stands for DataBase ...'),
    -> ('How To Use MySQL Well','After you went through a ...'),
    -> ('Optimizing MySQL','In this tutorial we will show ...'),
    -> ('1001 MySQL Tricks','1. Never run mysqld as root. 2. ...'),
    -> ('MySQL vs. YourSQL','In the following database comparison ...'),
    -> ('MySQL Security','When configured properly, MySQL ...');
Query OK, 6 rows affected (0.00 sec)
Records: 6  Duplicates: 0  Warnings: 0

mysql> SELECT * FROM articles
    -> WHERE MATCH (title,body) AGAINST ('database');
+----+-------------------+------------------------------------------+
| id | title             | body                                     |
+----+-------------------+------------------------------------------+
|  5 | MySQL vs. YourSQL | In the following database comparison ... |
|  1 | MySQL Tutorial    | DBMS stands for DataBase ...             |
+----+-------------------+------------------------------------------+
2 rows in set (0.00 sec)

The MATCH() function performs a natural language search for a string against a text collection. A collection is a set of one or more columns included in a FULLTEXT index. The search string is given as the argument to AGAINST(). For each row in the table, MATCH() returns a relevance value; that is, a similarity measure between the search string and the text in that row in the columns named in the MATCH() list.

By default, the search is performed in case-insensitive fashion. However, you can perform a case-sensitive full-text search by using a binary collation for the indexed columns. For example, a column that uses the latin1 character set of can be assigned a collation of latin1_bin to make it case sensitive for full-text searches.

When MATCH() is used in a WHERE clause, as in the example shown earlier, the rows returned are automatically sorted with the highest relevance first. Relevance values are non-negative floating-point numbers. Zero relevance means no similarity. Relevance is computed based on the number of words in the row, the number of unique words in that row, the total number of words in the collection, and the number of documents (rows) that contain a particular word.

To simply count matches, you could use a query like this:

mysql> SELECT COUNT(*) FROM articles
    -> WHERE MATCH (title,body)
    -> AGAINST ('database');
+----------+
| COUNT(*) |
+----------+
|        2 | 
+----------+
1 row in set (0.00 sec)

However, you might find it quicker to rewrite the query as follows:

mysql> SELECT
    -> COUNT(IF(MATCH (title,body) AGAINST ('database'), 1, NULL))
    -> AS count
    -> FROM articles;
+-------+
| count |
+-------+
|     2 | 
+-------+
1 row in set (0.00 sec)

The first query sorts the results by relevance whereas the second does not. However, the second query performs a full table scan and the first does not. The first may be faster if the search matches few rows; otherwise, the second may be faster because it would read many rows anyway.

For natural-language full-text searches, it is a requirement that the columns named in the MATCH() function be the same columns included in some FULLTEXT index in your table. For the preceding query, note that the columns named in the MATCH() function (title and body) are the same as those named in the definition of the article table's FULLTEXT index. If you wanted to search the title or body separately, you would need to create separate FULLTEXT indexes for each column.

It is also possible to perform a boolean search or a search with query expansion. These search types are described in Section 12.8.1, “Boolean Full-Text Searches”, and Section 12.8.2, “Full-Text Searches with Query Expansion”.

A full-text search that uses an index can name columns only from a single table in the MATCH() clause because an index cannot span multiple tables. A boolean search can be done in the absence of an index (albeit more slowly), in which case it is possible to name columns from multiple tables.

The preceding example is a basic illustration that shows how to use the MATCH() function where rows are returned in order of decreasing relevance. The next example shows how to retrieve the relevance values explicitly. Returned rows are not ordered because the SELECT statement includes neither WHERE nor ORDER BY clauses:

mysql> SELECT id, MATCH (title,body) AGAINST ('Tutorial')
    -> FROM articles;
+----+-----------------------------------------+
| id | MATCH (title,body) AGAINST ('Tutorial') |
+----+-----------------------------------------+
|  1 |                        0.65545833110809 |
|  2 |                                       0 |
|  3 |                        0.66266459226608 |
|  4 |                                       0 |
|  5 |                                       0 |
|  6 |                                       0 |
+----+-----------------------------------------+
6 rows in set (0.00 sec)

The following example is more complex. The query returns the relevance values and it also sorts the rows in order of decreasing relevance. To achieve this result, you should specify MATCH() twice: once in the SELECT list and once in the WHERE clause. This causes no additional overhead, because the MySQL optimizer notices that the two MATCH() calls are identical and invokes the full-text search code only once.

mysql> SELECT id, body, MATCH (title,body) AGAINST
    -> ('Security implications of running MySQL as root') AS score
    -> FROM articles WHERE MATCH (title,body) AGAINST
    -> ('Security implications of running MySQL as root');
+----+-------------------------------------+-----------------+
| id | body                                | score           |
+----+-------------------------------------+-----------------+
|  4 | 1. Never run mysqld as root. 2. ... | 1.5219271183014 |
|  6 | When configured properly, MySQL ... | 1.3114095926285 |
+----+-------------------------------------+-----------------+
2 rows in set (0.00 sec)

The MySQL FULLTEXT implementation regards any sequence of true word characters (letters, digits, and underscores) as a word. That sequence may also contain apostrophes (‘'’), but not more than one in a row. This means that aaa'bbb is regarded as one word, but aaa''bbb is regarded as two words. Apostrophes at the beginning or the end of a word are stripped by the FULLTEXT parser; 'aaa'bbb' would be parsed as aaa'bbb.

The FULLTEXT parser determines where words start and end by looking for certain delimiter characters; for example, ‘ ’ (space), ‘,’ (comma), and ‘.’ (period). If words are not separated by delimiters (as in, for example, Chinese), the FULLTEXT parser cannot determine where a word begins or ends. To be able to add words or other indexed terms in such languages to a FULLTEXT index, you must preprocess them so that they are separated by some arbitrary delimiter such as ‘"’.

Some words are ignored in full-text searches:

The default stopword list is given in Section 12.8.3, “Full-Text Stopwords”. The default minimum word length and stopword list can be changed as described in Section 12.8.5, “Fine-Tuning MySQL Full-Text Search”.

Every correct word in the collection and in the query is weighted according to its significance in the collection or query. Consequently, a word that is present in many documents has a lower weight (and may even have a zero weight), because it has lower semantic value in this particular collection. Conversely, if the word is rare, it receives a higher weight. The weights of the words are combined to compute the relevance of the row.

Such a technique works best with large collections (in fact, it was carefully tuned this way). For very small tables, word distribution does not adequately reflect their semantic value, and this model may sometimes produce bizarre results. For example, although the word “MySQL” is present in every row of the articles table shown earlier, a search for the word produces no results:

mysql> SELECT * FROM articles
    -> WHERE MATCH (title,body) AGAINST ('MySQL');
Empty set (0.00 sec)

The search result is empty because the word “MySQL” is present in at least 50% of the rows. As such, it is effectively treated as a stopword. For large datasets, this is the most desirable behavior: A natural language query should not return every second row from a 1GB table. For small datasets, it may be less desirable.

A word that matches half of the rows in a table is less likely to locate relevant documents. In fact, it most likely finds plenty of irrelevant documents. We all know this happens far too often when we are trying to find something on the Internet with a search engine. It is with this reasoning that rows containing the word are assigned a low semantic value for the particular dataset in which they occur. A given word may exceed the 50% threshold in one dataset but not another.

The 50% threshold has a significant implication when you first try full-text searching to see how it works: If you create a table and insert only one or two rows of text into it, every word in the text occurs in at least 50% of the rows. As a result, no search returns any results. Be sure to insert at least three rows, and preferably many more. Users who need to bypass the 50% limitation can use the boolean search mode; see Section 12.8.1, “Boolean Full-Text Searches”.

12.8.1. Boolean Full-Text Searches

MySQL can perform boolean full-text searches using the IN BOOLEAN MODE modifier:

mysql> SELECT * FROM articles WHERE MATCH (title,body)
    -> AGAINST ('+MySQL -YourSQL' IN BOOLEAN MODE);
+----+-----------------------+-------------------------------------+
| id | title                 | body                                |
+----+-----------------------+-------------------------------------+
|  1 | MySQL Tutorial        | DBMS stands for DataBase ...        |
|  2 | How To Use MySQL Well | After you went through a ...        |
|  3 | Optimizing MySQL      | In this tutorial we will show ...   |
|  4 | 1001 MySQL Tricks     | 1. Never run mysqld as root. 2. ... |
|  6 | MySQL Security        | When configured properly, MySQL ... |
+----+-----------------------+-------------------------------------+

The + and - operators indicate that a word is required to be present or absent, respectively, for a match to occur. Thus, this query retrieves all the rows that contain the word “MySQL” but that do not contain the word “YourSQL”.

Boolean full-text searches have these characteristics:

  • They do not use the 50% threshold.

  • They do not automatically sort rows in order of decreasing relevance. You can see this from the preceding query result: The row with the highest relevance is the one that contains “MySQL” twice, but it is listed last, not first.

  • They can work even without a FULLTEXT index, although a search executed in this fashion would be quite slow.

  • The minimum and maximum word length full-text parameters apply.

  • The stopword list applies.

The boolean full-text search capability supports the following operators:

  • +

    A leading plus sign indicates that this word must be present in each row that is returned.

  • -

    A leading minus sign indicates that this word must not be present in any of the rows that are returned.

    Note: The - operator acts only to exclude rows that are otherwise matched by other search terms. Thus, a boolean-mode search that contains only terms preceded by - returns an empty result. It does not return “all rows except those containing any of the excluded terms.

  • (no operator)

    By default (when neither + nor - is specified) the word is optional, but the rows that contain it are rated higher. This mimics the behavior of MATCH() ... AGAINST() without the IN BOOLEAN MODE modifier.

  • > <

    These two operators are used to change a word's contribution to the relevance value that is assigned to a row. The > operator increases the contribution and the < operator decreases it. See the example following this list.

  • ( )

    Parentheses group words into subexpressions. Parenthesized groups can be nested.

  • ~

    A leading tilde acts as a negation operator, causing the word's contribution to the row's relevance to be negative. This is useful for marking “noise” words. A row containing such a word is rated lower than others, but is not excluded altogether, as it would be with the - operator.

  • *

    The asterisk serves as the truncation (or wildcard) operator. Unlike the other operators, it should be appended to the word to be affected. Words match if they begin with the word preceding the * operator.

    If a stopword or too-short word is specified with the truncation operator, it will not be stripped from a boolean query. For example, a search for '+word +stopword*' will likely return fewer rows than a search for '+word +stopword' because the former query remains as is and requires stopword* to be present in a document. The latter query is transformed to +word.

  • "

    A phrase that is enclosed within double quote (‘"’) characters matches only rows that contain the phrase literally, as it was typed. The full-text engine splits the phrase into words, performs a search in the FULLTEXT index for the words. Prior to MySQL 5.0.3, the engine then performed a substring search for the phrase in the records that were found, so the match must include non-word characters in the phrase. As of MySQL 5.0.3, non-word characters need not be matched exactly: Phrase searching requires only that matches contain exactly the same words as the phrase and in the same order. For example, "test phrase" matches "test, phrase" in MySQL 5.0.3, but not before.

    If the phrase contains no words that are in the index, the result is empty. For example, if all words are either stopwords or shorter than the minimum length of indexed words, the result is empty.

The following examples demonstrate some search strings that use boolean full-text operators:

  • 'apple banana'

    Find rows that contain at least one of the two words.

  • '+apple +juice'

    Find rows that contain both words.

  • '+apple macintosh'

    Find rows that contain the word “apple”, but rank rows higher if they also contain “macintosh”.

  • '+apple -macintosh'

    Find rows that contain the word “apple” but not “macintosh”.

  • '+apple ~macintosh'

    Find rows that contain the word “apple”, but if the row also contains the word “macintosh”, rate it lower than if row does not. This is “softer” than a search for '+apple -macintosh', for which the presence of “macintosh” causes the row not to be returned at all.

  • '+apple +(>turnover <strudel)'

    Find rows that contain the words “apple” and “turnover”, or “apple” and “strudel” (in any order), but rank “apple turnover” higher than “apple strudel”.

  • 'apple*'

    Find rows that contain words such as “apple”, “apples”, “applesauce”, or “applet”.

  • '"some words"'

    Find rows that contain the exact phrase “some words” (for example, rows that contain “some words of wisdom” but not “some noise words”). Note that the ‘"’ characters that enclose the phrase are operator characters that delimit the phrase. They are not the quotes that enclose the search string itself.

12.8.2. Full-Text Searches with Query Expansion

Full-text search supports query expansion (and in particular, its variant “blind query expansion”). This is generally useful when a search phrase is too short, which often means that the user is relying on implied knowledge that the full-text search engine lacks. For example, a user searching for “database” may really mean that “MySQL”, “Oracle”, “DB2”, and “RDBMS” all are phrases that should match “databases” and should be returned, too. This is implied knowledge.

Blind query expansion (also known as automatic relevance feedback) is enabled by adding WITH QUERY EXPANSION following the search phrase. It works by performing the search twice, where the search phrase for the second search is the original search phrase concatenated with the few most highly relevant documents from the first search. Thus, if one of these documents contains the word “databases” and the word “MySQL”, the second search finds the documents that contain the word “MySQL” even if they do not contain the word “database”. The following example shows this difference:

mysql> SELECT * FROM articles
    -> WHERE MATCH (title,body) AGAINST ('database');
+----+-------------------+------------------------------------------+
| id | title             | body                                     |
+----+-------------------+------------------------------------------+
|  5 | MySQL vs. YourSQL | In the following database comparison ... |
|  1 | MySQL Tutorial    | DBMS stands for DataBase ...             |
+----+-------------------+------------------------------------------+
2 rows in set (0.00 sec)

mysql> SELECT * FROM articles
    -> WHERE MATCH (title,body)
    -> AGAINST ('database' WITH QUERY EXPANSION);
+----+-------------------+------------------------------------------+
| id | title             | body                                     |
+----+-------------------+------------------------------------------+
|  1 | MySQL Tutorial    | DBMS stands for DataBase ...             |
|  5 | MySQL vs. YourSQL | In the following database comparison ... |
|  3 | Optimizing MySQL  | In this tutorial we will show ...        |
+----+-------------------+------------------------------------------+
3 rows in set (0.00 sec)

Another example could be searching for books by Georges Simenon about Maigret, when a user is not sure how to spell “Maigret”. A search for “Megre and the reluctant witnesses” finds only “Maigret and the Reluctant Witnesses” without query expansion. A search with query expansion finds all books with the word “Maigret” on the second pass.

Note: Because blind query expansion tends to increase noise significantly by returning non-relevant documents, it is meaningful to use only when a search phrase is rather short.

12.8.3. Full-Text Stopwords

The following table shows the default list of full-text stopwords.

a'sableaboutaboveaccording
accordinglyacrossactuallyafterafterwards
againagainstain'tallallow
allowsalmostalonealongalready
alsoalthoughalwaysamamong
amongstanandanotherany
anybodyanyhowanyoneanythinganyway
anywaysanywhereapartappearappreciate
appropriatearearen'taroundas
asideaskaskingassociatedat
availableawayawfullybebecame
becausebecomebecomesbecomingbeen
beforebeforehandbehindbeingbelieve
belowbesidebesidesbestbetter
betweenbeyondbothbriefbut
byc'monc'scamecan
can'tcannotcantcausecauses
certaincertainlychangesclearlyco
comcomecomesconcerningconsequently
considerconsideringcontaincontainingcontains
correspondingcouldcouldn'tcoursecurrently
definitelydescribeddespitediddidn't
differentdodoesdoesn'tdoing
don'tdonedowndownwardsduring
eacheduegeighteither
elseelsewhereenoughentirelyespecially
etetceveneverevery
everybodyeveryoneeverythingeverywhereex
exactlyexampleexceptfarfew
fifthfirstfivefollowedfollowing
followsforformerformerlyforth
fourfromfurtherfurthermoreget
getsgettinggivengivesgo
goesgoinggonegotgotten
greetingshadhadn'thappenshardly
hashasn'thavehaven'thaving
hehe'shellohelphence
herherehere'shereafterhereby
hereinhereuponhersherselfhi
himhimselfhishitherhopefully
howhowbeithoweveri'di'll
i'mi'veieifignored
immediateininasmuchincindeed
indicateindicatedindicatesinnerinsofar
insteadintoinwardisisn't
itit'dit'llit'sits
itselfjustkeepkeepskept
knowknowsknownlastlately
laterlatterlatterlyleastless
lestletlet'slikeliked
likelylittlelooklookinglooks
ltdmainlymanymaymaybe
memeanmeanwhilemerelymight
moremoreovermostmostlymuch
mustmymyselfnamenamely
ndnearnearlynecessaryneed
needsneitherneverneverthelessnew
nextninenonobodynon
nonenoonenornormallynot
nothingnovelnownowhereobviously
ofoffoftenohok
okayoldononceone
onesonlyontoorother
othersotherwiseoughtourours
ourselvesoutoutsideoveroverall
ownparticularparticularlyperperhaps
placedpleasepluspossiblepresumably
probablyprovidesquequiteqv
ratherrdrereallyreasonably
regardingregardlessregardsrelativelyrespectively
rightsaidsamesawsay
sayingsayssecondsecondlysee
seeingseemseemedseemingseems
seenselfselvessensiblesent
seriousseriouslysevenseveralshall
sheshouldshouldn'tsincesix
sosomesomebodysomehowsomeone
somethingsometimesometimessomewhatsomewhere
soonsorryspecifiedspecifyspecifying
stillsubsuchsupsure
t'staketakentelltends
ththanthankthanksthanx
thatthat'sthatsthetheir
theirsthemthemselvesthenthence
therethere'sthereaftertherebytherefore
thereintheresthereuponthesethey
they'dthey'llthey'rethey'vethink
thirdthisthoroughthoroughlythose
thoughthreethroughthroughoutthru
thustotogethertootook
towardtowardstriedtriestruly
trytryingtwicetwoun
underunfortunatelyunlessunlikelyuntil
untoupuponususe
usedusefulusesusingusually
valuevariousveryviaviz
vswantwantswaswasn't
waywewe'dwe'llwe're
we'vewelcomewellwentwere
weren'twhatwhat'swhateverwhen
whencewheneverwherewhere'swhereafter
whereaswherebywhereinwhereuponwherever
whetherwhichwhilewhitherwho
who'swhoeverwholewhomwhose
whywillwillingwishwith
withinwithoutwon'twonderwould
wouldwouldn'tyesyetyou
you'dyou'llyou'reyou'veyour
yoursyourselfyourselveszero 

12.8.4. Full-Text Restrictions

  • Full-text searches are supported for MyISAM tables only.

  • Full-text searches can be used with most multi-byte character sets. The exception is that for Unicode, the utf8 character set can be used, but not the ucs2 character set.

  • Ideographic languages such as Chinese and Japanese do not have word delimiters. Therefore, the FULLTEXT parser cannot determine where words begin and end in these and other such languages. The implications of this and some workarounds for the problem are described in Section 12.8, “Full-Text Search Functions”.

  • Although the use of multiple character sets within a single table is supported, all columns in a FULLTEXT index must use the same character set and collation.

  • The MATCH() column list must match exactly the column list in some FULLTEXT index definition for the table, unless this MATCH() is IN BOOLEAN MODE. Boolean-mode searches can be done on non-indexed columns, although they are likely to be slow.

  • The argument to AGAINST() must be a constant string.

12.8.5. Fine-Tuning MySQL Full-Text Search

MySQL's full-text search capability has few user-tunable parameters. You can exert more control over full-text searching behavior if you have a MySQL source distribution because some changes require source code modifications. See Section 2.4.14, “MySQL Installation Using a Source Distribution”.

Note that full-text search is carefully tuned for the most effectiveness. Modifying the default behavior in most cases can actually decrease effectiveness. Do not alter the MySQL sources unless you know what you are doing.

Most full-text variables described in this section must be set at server startup time. A server restart is required to change them; they cannot be modified while the server is running.

Some variable changes require that you rebuild the FULLTEXT indexes in your tables. Instructions for doing this are given at the end of this section.

  • The minimum and maximum lengths of words to be indexed are defined by the ft_min_word_len and ft_max_word_len system variables. (See Section 5.2.3, “System Variables”.) The default minimum value is four characters; the default maximum is version dependent. If you change either value, you must rebuild your FULLTEXT indexes. For example, if you want three-character words to be searchable, you can set the ft_min_word_len variable by putting the following lines in an option file:

    [mysqld]
    ft_min_word_len=3

    Then you must restart the server and rebuild your FULLTEXT indexes. Note particularly the remarks regarding myisamchk in the instructions following this list.

  • To override the default stopword list, set the ft_stopword_file system variable. (See Section 5.2.3, “System Variables”.) The variable value should be the pathname of the file containing the stopword list, or the empty string to disable stopword filtering. After changing the value of this variable or the contents of the stopword file, restart the server and rebuild your FULLTEXT indexes.

    The stopword list is free-form. That is, you may use any non-alphanumeric character such as newline, space, or comma to separate stopwords. Exceptions are the underscore character (‘_’) and a single apostrophe (‘'’) which are treated as part of a word. The character set of the stopword list is the server's default character set; see Section 10.3.1, “Server Character Set and Collation”.

  • The 50% threshold for natural language searches is determined by the particular weighting scheme chosen. To disable it, look for the following line in myisam/ftdefs.h:

    #define GWS_IN_USE GWS_PROB

    Change that line to this:

    #define GWS_IN_USE GWS_FREQ

    Then recompile MySQL. There is no need to rebuild the indexes in this case. Note: By making this change, you severely decrease MySQL's ability to provide adequate relevance values for the MATCH() function. If you really need to search for such common words, it would be better to search using IN BOOLEAN MODE instead, which does not observe the 50% threshold.

  • To change the operators used for boolean full-text searches, set the ft_boolean_syntax system variable. This variable can be changed while the server is running, but you must have the SUPER privilege to do so. No rebuilding of indexes is necessary in this case. See Section 5.2.3, “System Variables”, which describes the rules governing how to set this variable.

  • If you want to change the set of characters that are considered word characters, you can do so in two ways. Suppose that you want to treat the hyphen character ('-') as a word character. Use either of these methods:

    • Modify the MySQL source: In myisam/ftdefs.h, see the true_word_char() and misc_word_char() macros. Add '-' to one of those macros and recompile MySQL.

    • Modify a character set file: This requires no recompilation. The true_word_char() macro uses a “character type” table to distinguish letters and numbers from other characters. . You can edit the <ctype><map> contents in one of the character set XML files to specify that '-' is a “letter.” Then use the given character set for your FULLTEXT indexes.

    After making the modification, you must rebuild the indexes for each table that contains any FULLTEXT indexes.

If you modify full-text variables that affect indexing (ft_min_word_len, ft_max_word_len, or ft_stopword_file), or if you change the stopword file itself, you must rebuild your FULLTEXT indexes after making the changes and restarting the server. To rebuild the indexes in this case, it is sufficient to do a QUICK repair operation:

mysql> REPAIR TABLE tbl_name QUICK;

Each table that contains any FULLTEXT index must be repaired as just shown. Otherwise, queries for the table may yield incorrect results, and modifications to the table will cause the server to see the table as corrupt and in need of repair.

Note that if you use myisamchk to perform an operation that modifies table indexes (such as repair or analyze), the FULLTEXT indexes are rebuilt using the default full-text parameter values for minimum word length, maximum word length, and stopword file unless you specify otherwise. This can result in queries failing.

The problem occurs because these parameters are known only by the server. They are not stored in MyISAM index files. To avoid the problem if you have modified the minimum or maximum word length or stopword file values used by the server, specify the same ft_min_word_len, ft_max_word_len, and ft_stopword_file values to myisamchk that you use for mysqld. For example, if you have set the minimum word length to 3, you can repair a table with myisamchk like this:

shell> myisamchk --recover --ft_min_word_len=3 tbl_name.MYI

To ensure that myisamchk and the server use the same values for full-text parameters, place each one in both the [mysqld] and [myisamchk] sections of an option file:

[mysqld]
ft_min_word_len=3

[myisamchk]
ft_min_word_len=3

An alternative to using myisamchk is to use the REPAIR TABLE, ANALYZE TABLE, OPTIMIZE TABLE, or ALTER TABLE statements. These statements are performed by the server, which knows the proper full-text parameter values to use.

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