If they match, the name and population are retrieved from the city table. Each code (PK in country table) returned by the subquery is checked against Countr圜ode (FK in city table).The subquery must be in parentheses in MySQL.The subquery shown above returns a result list of all of the codes from the country table that have a region of ‘Caribbean’. A subquery in MySQL is a query, which is nested into another SQL query and embedded with SELECT, INSERT, UPDATE or DELETE statement along with the various.Filter to only rows that have a value found in the subsequent subquery.Return the name and population columns from the city table.You can use a subquery in a WHERE, HAVING, FROM and SELECT clause.A subquery can be nested within another subquery.This SQL actually completes running in seconds and is much much faster than my original query. A subquery cannot make use of the ORDER BY clause NoDisplayName got close but not all the way there.A subquery can return multiple columns.When prompted, enter the root password of your MySQL server and hit Enter to continue. This sample database is used to run the different example queries in this guide: SSH to your server and log in to MySQL as root: mysql -u root -p. A subquery can return a single value or a list of values. To understand how subqueries work, create a sample database first.A subquery is usually added within the WHERE Clause of another SQL SELECT statement. In MySQL subquery can be nested inside a SELECT, INSERT, UPDATE, DELETE, SET, or DO statement or inside another subquery. A subquery may occur in: - A SELECT clause. A subquery is a SELECT statement coded within another SELECT statement. A subquery is a SQL query nested inside a larger query.More columns also required adding to the GROUP BY portion of the query. I ran across this while trying to perform a similar task with a query containing about a dozen columns. One can make a correlated query into a non-correlated query by selecting everything from the subquery, like so: SELECT FROM ( SELECT relevantfield FROM sometable GROUP BY relevantfield HAVING COUNT () > 1 ) AS subquery. I do believe my approach is a bit easier to follow. The subquery is being run for each row because it is a correlated query. That is still significantly slower then the other two queries. Adding a key to the user_id on the posts and pages tables avoids the file sort and sped up the slow query to only take 18 seconds. Using EXPLAIN with each of the queries shows that both of your approaches involves a filesort which is avoided with my query. Your updated simpler method took over 2000 times as long (nearly 3 minutes compared to. Limited testing showed nearly identical performance with this query to your query using left join to select subqueries. To test performance differences, I loaded the tables with 16,000 posts and nearly 25,000 pages. (select count(*) from pages where er_id=er_id) as page_count (select count(*) from posts where er_id=er_id) as post_count, My solution involves the use of dependent subqueries. INSERT INTO users (name) VALUES ( 'Jen ') ĬREATE TABLE posts (post_id INT PRIMARY KEY AUTO_INCREMENT, user_id INT) ĬREATE TABLE pages (page_id INT PRIMARY KEY AUTO_INCREMENT, user_id INT) The COUNT() aggregate will be evaluated after the rows are accessed, and after the GROUP BY operation. At the time the rows are being retrieved, MySQL doesn't have any information about the value returned by aggregate functions (e.g. INSERT INTO users (name) VALUES ( 'Simon ') The predicates in the WHERE clause are evaluated when the rows are accessed. INSERT INTO users (name) VALUES ( 'Matt ') CREATE TABLE users (user_id INT PRIMARY KEY AUTO_INCREMENT, name VARCHAR( 20))
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