9/18/2023 0 Comments Mysql join query![]() ![]() Always use explain to analyze query execution plans and optimize your queries for performance. By properly indexing the related columns between tables, you can significantly improve the performance of your queries. Indexing is critical when it comes to joins in MySQL. id Nested loop left join (cost=12347.65 rows=54620) -> Left hash join (film_actor.film_id = film.id) (cost=5519.98 rows=54620) -> Filter: (film.id Index range scan on film using PRIMARY (cost=3.02 rows=10) -> Hash -> Index scan on film_actor using PRIMARY (cost=54.93 rows=5462) -> Single-row index lookup on actor using PRIMARY (id=film_actor.actor_id) (cost=0.08 rows=1) Conclusion last_name FROM film LEFT JOIN film_actor ON film_actor. Next, let's turn the index off (by making it invisible) and run the same query again: ALTER TABLE film_actor ALTER INDEX idx_film_id INVISIBLE SELECT film. id Nested loop left join (cost=29.42 rows=55) -> Nested loop left join (cost=10.25 rows=55) -> Filter: (film.id Index range scan on film using PRIMARY (cost=2.82 rows=10) -> Covering index lookup on film_actor using idx_fk_film_id (film_id=film.id) (cost=1.06 rows=5) -> Single-row index lookup on actor using PRIMARY (id=film_actor.actor_id) (cost=0.84 rows=1) Query without indexes Let's say we want to get a list of the first 10 films and all the actors that were in those movies. We'll use the explain statement to see the query execution plan and the cost of each query. To illustrate the impact of indexing, let's run some queries with and without indexes. ![]() This table has a composite primary key made up of actor_id and film_id. To get a list of all the movies and the actors that were in those movies, we need to use the film_actor table as the joining table. We have a film table full of movies and an actor table full of actors. To link these two entities, you need a joining table with composite primary keys. ![]() For example, in a film database, an actor can be in many movies and a movie can have many actors. This formula can be extended to more than 3 tables to N tables, You just need to make sure that the SQL query should have N-1 join statement in order to join N. Sometimes you'll come across a many-to-many relationship between tables. The better way is to use an index on the related columns, which allows MySQL to quickly retrieve the matching rows and combine them. One way to do this is by doing a full table scan, which is slow and inefficient. When MySQL joins tables together, it needs to figure out which rows from one table match which rows from the other table. In this post, we're going to take a deeper dive into indexing joins and how it can affect the performance of your queries. In our previous video, we talked about joins and how they work in MySQL. The importance of indexing joins in MySQL ![]()
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