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Improved attribution and formatting
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Paul White ♦
Paul White ♦
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FULLTEXT

performs better when your text has low redundancy FULLTEXT performance differs by a factor of 78 between a vocabulary of 1,000 words and 100,000 words. I guess that larger vocabularies result in a very wide but shallow inverted index that can quickly determine if a query has matches or not. An educated person has a passive vocabulary of 15,000 to 20,000 words, so FULLTEXT should work well for natural language texts.

From Detailed Information HerePerformance analysis of MySQL's FULLTEXT indexes and LIKE queries for full text search by Henning Koch:

FULLTEXT performs better when your text has low redundancy
FULLTEXT performance differs by a factor of 78 between a vocabulary of 1,000 words and 100,000 words. I guess that larger vocabularies result in a very wide but shallow inverted index that can quickly determine if a query has matches or not. An educated person has a passive vocabulary of 15,000 to 20,000 words, so FULLTEXT should work well for natural language texts.

FULLTEXT

performs better when your text has low redundancy FULLTEXT performance differs by a factor of 78 between a vocabulary of 1,000 words and 100,000 words. I guess that larger vocabularies result in a very wide but shallow inverted index that can quickly determine if a query has matches or not. An educated person has a passive vocabulary of 15,000 to 20,000 words, so FULLTEXT should work well for natural language texts.

Detailed Information Here

From Performance analysis of MySQL's FULLTEXT indexes and LIKE queries for full text search by Henning Koch:

FULLTEXT performs better when your text has low redundancy
FULLTEXT performance differs by a factor of 78 between a vocabulary of 1,000 words and 100,000 words. I guess that larger vocabularies result in a very wide but shallow inverted index that can quickly determine if a query has matches or not. An educated person has a passive vocabulary of 15,000 to 20,000 words, so FULLTEXT should work well for natural language texts.

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l.lijith
l.lijith
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FULLTEXT

performs better when your text has low redundancy FULLTEXT performance differs by a factor of 78 between a vocabulary of 1,000 words and 100,000 words. I guess that larger vocabularies result in a very wide but shallow inverted index that can quickly determine if a query has matches or not. An educated person has a passive vocabulary of 15,000 to 20,000 words, so FULLTEXT should work well for natural language texts.

Detailed Information Here