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For fast, relevance-ranked searches on Ubuntu, store the searchable columns in an InnoDB FULLTEXT index and query that index with MATCH() ... AGAINST(). Use natural-language mode when MySQL should rank results automatically; use boolean mode when your application must require, exclude, phrase-match, or prefix-match terms. If searches for two-letter codes or common words return nothing, check InnoDB’s minimum token length and stopword settings, then rebuild every affected index after changing them.
What full-text search changes
A conventional query such as LIKE '%ubuntu%' checks whether a character sequence appears in a value. It does not calculate linguistic relevance, and a leading wildcard generally prevents MySQL from using an ordinary B-tree index efficiently. MySQL full-text search builds a specialized inverted index for the words in selected columns. MATCH() identifies the indexed collection, while AGAINST() supplies the search expression and mode.
Natural-language search assigns greater weight to terms that are rarer in the indexed collection and less weight to terms that occur widely. The result is a relevance score that you can return and sort on. Boolean search skips automatic ranking in favor of operators that make application intent explicit. Both modes require a compatible FULLTEXT index on the same columns named in MATCH().
Install and verify MySQL on Ubuntu
On Ubuntu, install the distribution package from a terminal:
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sudo apt update
sudo apt install mysql-serverCanonical’s Ubuntu Server documentation gives sudo apt install mysql-server as the installation command. After installation, verify that the server is running with either service-management command:
sudo service mysql status
# or
systemctl status mysqlIf the service is inactive, start it with sudo systemctl start mysql. Keep the package-managed configuration under /etc/mysql. Before editing a setting, inspect the option-file hierarchy and active defaults; mysqld --verbose --help can show the files MySQL reads and the compiled defaults. Put site-specific server options in the included configuration file intended for local changes so a package upgrade is less likely to overwrite them.
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Choose the exact columns users will search and index them together. The column list and order in MATCH() must correspond to the indexed collection.
CREATE TABLE articles (
id BIGINT UNSIGNED PRIMARY KEY AUTO_INCREMENT,
title VARCHAR(200) NOT NULL,
body TEXT NOT NULL,
FULLTEXT KEY ft_articles_title_body (title, body)
) ENGINE=InnoDB;InnoDB is the usual choice for an application table because it provides transactional behavior alongside full-text indexing. Create the index when the table is created, or add one later:
ALTER TABLE articles
ADD FULLTEXT KEY ft_articles_title_body (title, body);Index only fields that belong in the same search experience. A title and body collection is sensible when a query should rank both together. If users need separate search semantics, create separate collections instead of placing unrelated fields in one index. The index must exist before the production query is issued; otherwise MySQL reports that no matching full-text index is available.
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Query with natural-language mode
Natural-language mode is the default mode, but stating it explicitly makes the behavior clear. The following pattern returns a score, filters out rows with no positive relevance, and orders the matches from most relevant to least relevant:
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SELECT id, title,
MATCH(title, body) AGAINST (? IN NATURAL LANGUAGE MODE) AS score
FROM articles
WHERE MATCH(title, body) AGAINST (? IN NATURAL LANGUAGE MODE) > 0
ORDER BY score DESC;Bind the same user query to both placeholders with your database driver rather than concatenating it into SQL. The first occurrence produces the displayed score; the second applies the result filter. A score is meaningful within the collection and query, not a universal quality rating that can be compared across unrelated tables or search strings.
When natural language is the right default
- Users enter ordinary words and expect the most relevant documents first.
- You want rare, descriptive terms to influence ranking more than ubiquitous terms.
- You do not need mandatory, prohibited, phrase, or prefix operators in the user-facing syntax.
- Your result page can use the returned score for ordering or diagnostics.
Natural-language parsing can omit words that are too short or listed as stopwords. That behavior is often desirable for prose, but it explains many apparently empty result sets.
Use boolean mode for explicit control
Boolean mode lets the application express inclusion and exclusion requirements directly:
SELECT id, title
FROM articles
WHERE MATCH(title, body) AGAINST (
'+ubuntu +mysql -windows "full text"*' IN BOOLEAN MODE
);In this example, +ubuntu and +mysql require those terms, -windows excludes rows containing that term, quotation marks treat full text as a phrase, and the trailing * keeps a prefix from being stripped during parsing. Design the query grammar deliberately: if users can type operators, document them and escape or validate input according to your application’s syntax rules.
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| Requirement | Natural-language mode | Boolean mode |
|---|---|---|
| Primary behavior | Ranks terms by their significance in the collection. | Applies operators and matching rules supplied in the search expression. |
| Required or excluded words | No operator for mandatory or prohibited terms. | + requires a term; - excludes a term. |
| Phrase matching | No explicit phrase operator. | Quotation marks form a phrase. |
| Prefix wildcard | Not the mode’s explicit control mechanism. | A trailing * preserves a prefix instead of allowing the term to be stripped. |
| Result ordering | Returns a relevance score suitable for ORDER BY. |
Use when matching rules matter more than automatic ranking; a score is not required by the query pattern. |
| Common-term behavior on MyISAM | Subject to MyISAM’s 50-percent threshold. | MySQL documents that boolean mode does not observe that MyISAM threshold. |
Boolean mode is therefore useful for filters, command-like search boxes, and advanced syntax. It does not automatically make a poorly designed query more relevant; it gives you control over the rules.
Why MATCH() ... AGAINST() returns no rows
The words are shorter than the indexed minimum
For InnoDB search indexes, the default minimum indexed word length is three characters. A query for a two-letter code such as AI, UK, or DB can return no rows because those tokens were never written to the index. MyISAM’s default minimum is four characters. These defaults are documented for MySQL 8.4 and apply to indexed tokens, not to the character length of the entire column.
The words are stopwords
MySQL omits configured stopwords from full-text indexes. Common words can consequently produce no match even when they visibly occur in a row. For InnoDB, stopword behavior is controlled by innodb_ft_enable_stopword, innodb_ft_server_stopword_table, and innodb_ft_user_stopword_table. MyISAM uses ft_stopword_file. Check the settings on the server that built the index; changing a client connection does not change what is already indexed.
The query and index collections differ
Use the same columns, in the same collection, in both places. An index on (title, body) is not interchangeable with a query that matches only (body) or adds an unindexed column. Confirm the index definition with:
SHOW CREATE TABLE articlesG
SHOW INDEX FROM articles;The query is being filtered incorrectly
A natural-language query commonly uses > 0 to discard nonmatches. If your application turns a null, empty, or whitespace-only input into a search expression, every row can be filtered out. Validate input before running the query and log the final bound value during troubleshooting. Also check that the application is connected to the server and schema where the index was created.
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The index was not rebuilt after a configuration change
Token-size and stopword options affect index construction. Existing indexes retain their old tokenization until rebuilt. Restarting MySQL alone does not retroactively add omitted words.
Index two-character terms safely
If your product must search two-letter codes, set InnoDB’s minimum token size to two before rebuilding the relevant indexes:
[mysqld]
innodb_ft_min_token_size=2The option belongs in the active MySQL server configuration under /etc/mysql. Restart when required by the option and your package configuration:
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sudo systemctl restart mysqlThen rebuild each affected index. For the example table:
ALTER TABLE articles
DROP INDEX ft_articles_title_body,
ADD FULLTEXT KEY ft_articles_title_body (title, body);Changing the variable without this rebuild leaves the old index behavior in place. Apply the change as a migration rather than an ad-hoc edit:
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- Record the current minimum-token and stopword settings, along with the MySQL version and each server role.
- Decide whether two-character terms are genuinely useful; indexing more short tokens can increase noise from abbreviations and codes.
- Set the same value on every server that creates or serves the index, including replicas used for reads.
- Schedule the restart and index rebuild during a maintenance window appropriate for the table size and workload.
- Run representative searches for expected hits, expected misses, and false-positive-prone abbreviations.
- Monitor application logs and search quality after deployment, and keep a rollback setting documented.
Do not assume that lowering the threshold improves every search. It changes what is indexed, so terms that were previously ignored can start matching documents that users did not intend to retrieve.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Configure stopwords deliberately
Stopwords are a relevance and recall decision. Leaving them enabled reduces index entries for very common words; disabling or replacing them can be necessary for domains where a normally common word is meaningful. For InnoDB, choose among the server stopword table, a user stopword table, or disabled stopword processing through the documented variables. Keep the chosen policy identical wherever the index is built.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesAfter changing any stopword variable, rebuild every affected InnoDB full-text index with an ALTER TABLE operation. Test both sides of the change: a term that should now be searchable and a common term that should remain excluded. Document the stopword table contents as part of the schema migration so a fresh Ubuntu host creates the same index semantics.
Choose the parser for the language
The built-in parser separates words using delimiters such as whitespace. That is appropriate for languages whose text normally has visible word boundaries. Chinese, Japanese, and Korean text often does not separate words with spaces, so use MySQL’s built-in ngram parser:
CREATE FULLTEXT INDEX ft_cjk
ON documents (content)
WITH PARSER ngram;The ngram parser’s default token size is two, a bigram. MySQL documents a configurable range from one through ten. The parser ignores the ordinary InnoDB and MyISAM minimum-word-length variables, so tune ngram_token_size instead:
[mysqld]
ngram_token_size=2Changing parser settings also requires rebuilding the affected full-text index. Select the token size based on the language and query behavior you need. Smaller ngrams can represent shorter fragments but create more index tokens; larger ngrams require longer contiguous sequences. Validate phrase and prefix expectations with real text from your application because ngram matching is based on generated token sequences, not the same whitespace-word model used by the built-in parser.
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|---|---|---|---|
| Built-in parser | Uses delimiters such as whitespace to identify words. | InnoDB minimum token size (three by default); MyISAM minimum (four by default), plus stopword settings. | Languages with clear word boundaries. |
| ngram parser | Generates fixed-length character ngrams, useful when words are not separated by spaces. | ngram_token_size, default two and configurable from one through ten. |
Chinese, Japanese, Korean, and other text requiring ngram segmentation. |
InnoDB and MyISAM differences that affect search
| Area | InnoDB | MyISAM |
|---|---|---|
| Default minimum token length | Three characters. | Four characters. |
| Stopword controls | innodb_ft_enable_stopword, innodb_ft_server_stopword_table, and innodb_ft_user_stopword_table. |
ft_stopword_file. |
| Common-term threshold | Does not use the MyISAM 50-percent rule. | Natural-language searches can suppress a term appearing in at least half of the rows; boolean mode does not observe that threshold. |
| Application fit | Transactional table engine suitable for typical write-heavy applications. | Legacy nontransactional engine; choose it only when its operational characteristics are intentional. |
| CJK tokenization | Can use WITH PARSER ngram; tune ngram_token_size. |
Parser and option behavior must be checked against the engine and MySQL version in use. |
For a new Ubuntu application, start with InnoDB unless a specific compatibility requirement dictates otherwise. If migrating an existing MyISAM table, retest minimum lengths, stopwords, common-term behavior, and index rebuild procedures rather than assuming the two engines produce identical results.
A production checklist for Ubuntu full-text search
- Install MySQL with APT and verify the
mysqlservice is active. - Confirm the server version and inspect option-file includes under
/etc/mysql. - Use an InnoDB table with a
FULLTEXTindex covering every column named inMATCH(). - Use natural-language mode for automatic relevance ranking and return the score when the UI needs ordering.
- Use boolean mode for required, excluded, phrase, and trailing-prefix controls.
- Check the three-character InnoDB and four-character MyISAM defaults before promising two-letter search.
- Review stopword variables and tables for the language and vocabulary of your application.
- Use the ngram parser for CJK text that lacks whitespace boundaries, and tune
ngram_token_size. - Rebuild every affected index after changing token-size, parser, or stopword settings.
- Test expected matches, expected nonmatches, phrases, prefixes, short codes, and common words on every server that serves search traffic.
Diagnose a failing search in a repeatable order
- Run
SHOW CREATE TABLEand confirm aFULLTEXTindex exists on the exactMATCH()columns. - Execute the query directly with a known three-or-more-character, non-stopword term to separate connection problems from tokenization problems.
- Check the active engine and parser. A CJK collection using the built-in parser may not produce the segmentation you expect.
- Inspect
innodb_ft_min_token_size,ngram_token_size, and the applicable stopword variables on the server that built the index. - If settings changed, verify that MySQL was restarted where necessary and that the index was dropped and recreated afterward.
- Compare natural-language and boolean results. A boolean query can reveal whether a common term is being suppressed by MyISAM’s threshold or whether the expression needs an explicit operator.
- Test the application’s bound parameter and input normalization. Empty strings, punctuation-only input, and accidental leading operators can all change the parsed query.
This sequence avoids the common mistake of changing SQL syntax when the real issue is that the desired token was never indexed.
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