Usually, data is stored in relational databases in multiple tables. There are two reasons for this: (1) data duplication is reduced and (2) complex queries can combine data from various tables in new ways that were not necessarily planned in advance. In order to build some queries, we must “join” data from multiple tables.

Join logic

Much of the SQL language is inspired by mathematical set theory. A SELECT query is how we describe the content of a set. So far, we have only described a set of results from a single table. With joins, we can describe unions and intersections of sets of results from multiple tables.

The diagram below is commonly found on the internet when searching for “sql joins” (from here). It’s a quick summary of the various kinds of joins that MySQL supports (I removed one kind of join MySQL doesn’t support: full outer joins).

SQL Joins

Joins use the following syntax:

    FROM [table1]
    (JOIN | LEFT JOIN | RIGHT JOIN) [table2]
    [ON match_condition]
    ... possibly more joins
    [WHERE where_condition]
    ... etc. just like normal SELECT

Note that the ON match_condition constrains the join and is performed before the WHERE. A temporary new table is constructed out of the data from the joined tables, and it is this temporary table that is subjected to the WHERE clause. This means that it is more efficient to put your constraints in an ON condition if possible, rather than a WHERE condition.

Inner joins

Inner joins include only those rows where the ON match_condition is met from both tables. It is the default join type, and most common, so you can specify just the word JOIN (but, if you choose, you can write INNER JOIN also).

Left joins

Left joins may return rows from the “left” (first) table even in cases where the ON match_condition is not met. In other words, only the right table will be subjected to the match condition.

Right joins

A right join is just like a left join except only the left (first) table is subjected to the match conditions. If you reverse the order that the tables are mentioned in the query, you can change a right join into an equivalent left join and vice versa.

Example: Shop

-- show product inventory counts
select title, invcount from shop_products join shop_inventory on shop_products.id = shop_inventory.product_id;

-- show ratings for products, INCLUDING products with no ratings (left join; or right join if you switch the table order)
select title, rating from shop_products left join shop_reviews on shop_reviews.product_id = shop_products.id;

-- show products in customer's shopping carts
select name, title, quantity from shop_customers join shop_shoppingcart on shop_shoppingcart.customer_id = shop_customers.id
  join shop_products on shop_products.id = shop_shoppingcart.product_id;

Example: IMDB

Here are some examples from class with the various tables in the cinf201_imdb database.

-- movie title, character, and actor name for females in lead roles
select distinct title, character_name, fname, lname
  from movies m
  join acted_in ai on m.idmovies = ai.idmovies
  join actors on actors.idactors = ai.idactors
  where billing_position = 1 and gender = 0 order by title limit 10;

-- all the unique genres Amy Schumer has worked in
select distinct genre from genres
  join movies_genres on genres.idgenres = movies_genres.idgenres
  join movies on movies_genres.idmovies = movies.idmovies
  join acted_in on movies.idmovies = acted_in.idmovies
  join actors on acted_in.idactors = actors.idactors
  where lname = 'Schumer' and fname = 'Amy' order by genre;
CINF 201 material by Joshua Eckroth is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Source code for this website available at GitHub.