![]() ¹ (in the example, second to last and third to last characters are determined) Strings that have a specific substring at a specific position from the beginning² Strings that have a specific substring at a specific position from the end¹ Strings that have a specific substring anywhere in the string Strings that end with a specific substring Strings that begin with a specific substring You can use these characters in a wide variety of use-cases. The operators are used like this: column_name LIKE pattern. SQL patterns use the LIKE and NOT LIKE operators and the metacharacters (characters that stand for something other than themselves) % and _. They have a more limited syntax than RegEx, but they're more universal through the various SQL versions. ![]() SQL patterns are useful for pattern matching, instead of using literal comparisons. In this article, we'll look at how you can use the Contains String query. PostgreSQL has several text parsers and dictionaries, depending on the kind of text to be searched and what to be searching for including ones based on the Snowball stemmer for the languages that project currently has support for.Being able to do complex queries can be really useful in SQL. Other languages would have different collections of such "stopwords".įurther, a fulltext search for "dedicate" ought to find a hit on "dedicated". Words like "are" and "and" and "to" would be discarded from fulltext searching because those are so common in English text that using them as a filter would be comparatively useless. I don't know if it's because you only posted part of the dump, but the bit you've shown doesn't have "英語", meaning "English Language". ![]() So, entire sentence fragments, rather than words – probably because the fulltext indexer doesn't understand Japanese as well as it understands English (fulltext searching is language-sensitive). "Not only copyrighted works created by Americans " ![]() "With copyrighted works such as software " "It is a law of the United States that protects the rights of its authors, etc. Those five blocks of Japanese text in the dump translate according to Google (which in this instance turns out to be fairly good, since the writing is more formal and less idiomatic) as: I don't speak Japanese - and don't know if they use spaces like we do or whether those clusters are meaningful like words are or if the fulltext search would be useless for your typical japanese search - but I thought this might provide meaningful detail here. The index appears to work by splitting up a data field along the whitespace and punctuation characters, indexing the non-whitespace characters: # myisam_ftdump -d foo 1īc 0.9157509 その著作者などの権利を保護するアメリカ合衆国の法律である MODIFY `id` int NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=3 (1, ' Four score and seven years ago our fathers brought forth on this continent, a new nation, conceived in Liberty, and dedicated to the proposition that all men are created equal.'), I did a quick experiment, creating this SQL table: CREATE TABLE `foo` ( I stumbled across myisam_ftdump, a command which allows you to get a look inside a MyISAM fulltext index. I am still trying to absorb it but haven't had much time. I do recall there's a NATURAL LANGUAGE MODE syntax for MySQL, but that hasn't yet clarified much for me. I was trying to understand Weedpacket's thinking, and couldn't really understand how fulltext would have any language-specific aspects. Build some queries and see if the index is invoked. But it would be something to experiment with. Apparently MySQL's query planner is smart enough to recognise cases when such an index would be useful even when the generated column isn't selected (it's looked at if the real column it's generated from is used), but I don't know if it's smart enough in the general case to recognise that, say, an index on the length-three prefixes of column "col" is useful when trying to match something 'col LIKE "foo%"'. I wonder if a more specific index would be more useful: in particular, you can have a generated column that captures hints about what the real search is supposed to match but is much easier to match tentatively (the first three characters the leading digits), and then put an index on that column. Two reasons for thinking that: (1) LIKE is language-agnostic, but fulltext matching expects the text to be in an actual language and (2) If there was some aspect of FULLTEXT search that sped up LIKE, that part would end up being factored out and applied to the implementation of LIKE to begin with, and FULLTEXT would then be taking advantage of that. I'm no MySQL expert, but I kinda doubt that a fulltext index would speed up a LIKE condition (I'm not in the mood for a dive into the source code).
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