SELECT *, ts_rank(to_tsvector('english', content), to_tsquery('english', 'quick & fox')) AS rank FROM documents WHERE to_tsvector('english', content) @@ to_tsquery('english', 'quick & fox') ORDER BY rank DESC;
Your SQL query is designed to search for documents containing the terms "quick" and "fox" using PostgreSQL's full-text search capabilities. Here's a breakdown of what each part of the query does:
to_tsvector('english', content): This function converts the content column of the documents table into a tsvector, which is a data type optimized for text search. The 'english' parameter specifies the text search configuration to use, which includes language-specific rules for tokenizing and normalizing text.
to_tsquery('english', 'quick & fox'): This function converts the search query 'quick & fox' into a tsquery, which is a data type representing a text search query. The '&' operator means that both terms must be present in the document.
ts_rank(to_tsvector('english', content), to_tsquery('english', 'quick & fox')) AS rank: This function calculates the rank of each document based on how well it matches the search query. The result is given an alias rank.
WHERE to_tsvector('english', content) @@ to_tsquery('english', 'quick & fox'): This condition filters the documents to include only those that match the search query.
ORDER BY rank DESC: This clause sorts the results by the rank in descending order, so the most relevant documents appear first.
Here is the complete query again for reference:
SELECT *, ts_rank(to_tsvector('english', content), to_tsquery('english', 'quick & fox')) AS rank
FROM documents
WHERE to_tsvector('english', content) @@ to_tsquery('english', 'quick & fox')
ORDER BY rank DESC;
This query will return all columns from the documents table along with an additional column rank that indicates the relevance of each document to the search terms "quick" and "fox". The results will be ordered by this relevance score in descending order.