PG Search Sequelize - Example

Demonstration of how to use the pg-search-sequelize package to search a database of films and actors.

Demo

Try out this example's demo here.

Run it locally

Prerequisites: Docker. If you don't want to use Docker, you'll need to have Postgres and Node.js 6.0.0 or above installed.

To start the server and database with docker, run:

./init.sh

That's it. Now you can open your browser and navigate to http://localhost:3000/.

Test searching by navigating to http://localhost:3000/film/x-men. To filter your results by release year, modify your query to http://localhost:3000/film/x-men releaseYear:2003. Note that we did not hard code the release year filter; it is automatically provided by the pg-search-sequelize package.

How It Works

Our database is very simple; we only have 3 tables: film, actor, and film_actor. Using pg-search-sequelize, we create a materialized view from the film and actor data. We give the film names the highest weight, details and cast get a lower weight, and the rest of the details follow in order. The weighting system allows our search results to be sorted by relevance depending on how we set it up. Because we gave movie names a higher order than cast names, a search query of "Washington" would yield a result of the movie "Washington Heights" before "Man on Fire," since the first has the search query in the movie name while the second has it in the movie's cast.

We then define our materialized view model in /models and register it with pg-search-sequelize so that we get the search functionality.

Finally, we expose two API /film/:query and we start the express server on port 3000.

Next Steps

If you are interested in using this package in your projects, head on over to pg-search-sequelize.

If there's anything you didn't like, or if you have any comments or suggestions, please do submit them in the issues section of pg-search-sequelize