4/10/2023 0 Comments Postgres ilike index![]() ![]() We can run the file by running rake db:seed. We could use a Rake task to do this but this will work as a quick and dirty way to create the records. I want to meet Superman again, does anyone know where I can find him? ![]() Comment.create! name: " Lois Lane ", article: superman, content: <<-COMMENT (from Wikipedia)ĪRTICLE # Some articles and comments omitted. (later DC Comics) in 1938, the character first appeared in Action Comics #1 (June 1938) and subsequently appeared in various radio serials, television programs, films, newspaper strips, and video games. Created by American writer Jerry Siegel and Canadian-born American artist Joe Shuster in 1932 while both were living in Cleveland, Ohio, and sold to Detective Comics, Inc. Superman is a fictional comic book superhero appearing in publications by DC Comics, widely considered to be an American cultural icon. Superman = Article.create! name: " Superman ", author: clark, published_at: 3.weeks.ago, content: <<-ARTICLE First we’ll replace the texticle gem in our gemfile with pg_search and then run bundle again to install it.īruce = Author.create! name: " Bruce Wayne "Ĭlark = Author.create! name: " Clark Kent " 1000.times do We’ll use this second option in our application. The other option is called pg_search_scope and is used for searching a single model. One option called multi-search will search multiple models at once. This offers a couple of ways to do full-text searching in Postgres. Texticle is great for a simple full-text search like this but if we want a more customizable solution then another gem called PgSearch is better. This query is similar to the manual one we had, using ts_rank to generate a rank and to compare a tsvector and a tsquery. (1.2ms) SELECT COUNT(*) FROM "articles" WHERE (to_tsvector('english', "articles"."name"::text) to_tsquery('english', 'dc\ comics'::text) OR to_tsvector('english', "articles"."content"::text) to_tsquery('english', 'dc\ comics'::text)) ![]() We can use the rails db command to enter the Postgres console and we’ll use the SELECT command with some static text to experiment with various operators and functions.Īrticle Load (2.5ms) SELECT "articles".*, ts_rank(to_tsvector('english', "articles"."name"::text), to_tsquery('english', 'dc\ comics'::text)) ts_rank(to_tsvector('english', "articles"."content"::text), to_tsquery('english', 'dc\ comics'::text)) AS "rank0.9491099641574605" FROM "articles" WHERE (to_tsvector('english', "articles"."name"::text) to_tsquery('english', 'dc\ comics'::text) OR to_tsvector('english', "articles"."content"::text) to_tsquery('english', 'dc\ comics'::text)) ORDER BY "rank0.9491099641574605" DESC LIMIT 3 OFFSET 0 We’ve shown how powerful full-text searching is but what’s going on when we use it and how can we get the most from it? We’ll use the database console to show what goes on when we make a full-text search. Another good reason for using this approach is that everything stays in sync automatically: if we were to create a new article, or edit an article, that content is instantly available in the full-text search. The text_search method is still just a simple ActiveRecord scope that we can add other clauses to, such as page and per_page for pagination. For example our pagination still works without any adjustment from us. One of the best reasons for keeping full-text searching in the database is that it works seamlessly with all other SQL clauses. ![]() If we search for “superman of dc comics”, this will return the “Superman” article even though it doesn’t contain the word “of”. Stop words are also supported which means that common English words will be ignored. All we have to do is replace ilike with double at signs ( and remove the percent signs from the search term like this:īy default the full-text search uses an English dictionary with stemming so if we search for “superman characters” (note the extra “s”) we get the same set of results, even though the word “characters” isn’t in the articles. Changing from a like condition to a full-text search with Postgres is quite easy. One problem with our current approach is that we’re treating the search term as a single string so if we search for “superman character” no articles are returned even though we have articles that contain both those words but not together. This is a poor excuse for full-text searching so let’s take advantage of Postgres’s full-text search feature to improve it. We compare the articles’ name and content columns to the query, which is wrapped in percent signs so that the search term is matched anywhere in those fields. Here we check to see if the query parameter is present and if it is we find the articles that match that query using a like comparison (actually ilike so that the search is case-insensitive). Where( " name ilike :q or content ilike :q ", q: " % # % ") ![]()
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