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Summary: Ref T9979. This uses ngrams (specifically, trigrams) to build a reasonably efficient index for substring matching. Specifically, for a package like "Example", with ID 123, we store rows like this: ``` < ex, 123> <exa, 123> <xam, 123> <amp, 123> <mpl, 123> <ple, 123> <le , 123> ``` When the user searches for `exam`, we join this table for packages with tokens `exa` and `xam`. MySQL can do this a lot more efficiently than it can process a `LIKE "%exam%"` query against a huge table. When the user searches for a one-letter or two-letter string, we only search the beginnings of words. This is probably what they want, the only thing we can do quickly, and a reasonable/expected behavior for typeaheads. Test Plan: - Ran storage upgrades and search indexer. - Searched for stuff with "name contains". - Used typehaead and got sensible results. - Searched for `aabbccddeeffgghhiijjkkllmmnnooppqqrrssttuuvvwwxxyyzz` and saw only 16 joins. Reviewers: chad Reviewed By: chad Maniphest Tasks: T9979 Differential Revision: https://secure.phabricator.com/D14846
7 lines
302 B
SQL
7 lines
302 B
SQL
CREATE TABLE {$NAMESPACE}_owners.owners_name_ngrams (
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id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
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objectID INT UNSIGNED NOT NULL,
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ngram CHAR(3) NOT NULL COLLATE {$COLLATE_TEXT},
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KEY `key_object` (objectID),
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KEY `key_ngram` (ngram, objectID)
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) ENGINE=InnoDB, COLLATE {$COLLATE_TEXT};
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