![]() ![]() ( CASE when pu.point >= 10000 then 'Over 10,000' when pu. Same way by using WITH with table1 as ( ( CASE when pu.point >= 10000 then 'Over 10,000' when pu.point >= 5000 then 'Over 5,000' else 'Under 5,000' END) as level from point_users pu Practical Use of CASE, using a subquery select pu.point_user_id, pu.point, ( CASE when pu.point > 10000 then 'Great!' else 'Keep up!' END) as msg SUBSTRING(string, start_pos, num_of_str): printing substring select SUBSTRING(created_at, 1, 10) as date, count(*) as num_ordersĬase Statement select pu.point_user_id, pu.point, SQL Grammar String Type Data SUBSTRING_INDEX(string, 'key', index): splitting string select user_id, email, SUBSTRING_INDEX(email, -1) from users ![]() Inner join courses c on a.course_id = c.course_id Inner join courses c on c.course_id = a.course_idįrom table1 a inner join table2 b on a.course_id = b.course_id Select course_id, count( distinct(user_id)) as cnt_checkins from checkins Select course_id, count(*) as cnt_total from orders Round(b.cnt_checkins/a.cnt_total, 4) as ratio Execution Order: - inner select as a table -> outer select WITH select Select user_id, round( avg(likes), 1) as avg_like from checkins Execution Order: - outer select executed as reading data one by one -> inner select executed while outer select reading one data -> print at the same time Subquery in FROM (most common) select pu.user_id, t1.avg_like, pu.point from point_users pu Where c2.user_id = c.user_id) as avg_like_user in -> print Subquery in SELECT select c.checkin_id, c.user_id, c.likes, Execution Order: - from -> subquery -> where. Where o.payment_method = 'kakaopay' - Subquery select u.user_id, u.name, u.email from users u Inner join orders o on u.user_id = o.user_id : query inside the query, in order to make the queries look simple select u.user_id, u.name, u.email from users u Where o.created_at '' group by c2.course_id, c2.week Inner join orders o on o.user_id = c2.user_id Inner join courses c on c2.course_id = c.course_id Select 'July' as month, c.title, c2.week, count(*) as cnt from checkins c2 (it seems to contain a false assumption that there's only one edition).: to combine tables by key value (the common information between two tables) ![]() That might be the wrong answer, since the original The difference is between these two SQL statements is, if there are twoĮditions of Das Kapital (with different page counts), then the self-joinĮxample will return the books which are longer than the shortest edition Instead we can use the sub-query as the second table to the inner join clause.page_count > ( SELECT DISTINCT page_count FROM Books AS Bookcolumn_2 WHERE title = 'Das Kapital' ) * FROM Books AS Bookcolumn_1 WHERE Bookcolumn_1. * FROM Books AS Bookcolumn_1 JOIN Books AS Bookcolumn_2 USING ( page_count ) WHERE title = 'Das Kapital' SELECT DISTINCT Bookcolumn_1. What books are longer than Das Kapital? These two queries are effectively which still involves a parenthesized query, so nothing is gained from the.* FROM Table_1, ( SELECT MAX ( column_1 ) AS max_column_1 FROM Table_2 ) AS Table_2 WHERE Table_1. SELECT * FROM Table_1 WHERE column_1 + 5 = ( SELECT MAX ( column_1 ) FROM Table_2 ) can't be expressed using a join unless some rare SQ元 features are used.UPDATE Table_1 SET column_1 = ( SELECT column_1 FROM Table_2 ) When the outermost statement is not a query.The removal of the duplicated 1 is an error too. When you want duplicates, but not false duplicates.There are some scenarios, though, which call for subqueries rather than joins: Subqueries that can be rewritten as a LEFT JOIN are sometimes more efficient. * FROM table1 LEFT JOIN table2 ON table1. col1 ) Īnd both can be rewritten as: SELECT table1. For example, these two queries returns the same result: SELECT * FROM table1 WHERE col1 NOT IN ( SELECT col1 FROM table2 ) SELECT * FROM table1 WHERE NOT EXISTS ( SELECT col1 FROM table2 WHERE table1. If you want to INNER JOIN tables table2 and table3 and then LEFT JOIN to table1 then do this: SELECT t1.name, t.typedesc AS Type Description FROM Table1 AS t1 LEFT JOIN ( SELECT t2.id, t3.typedesc FROM table2 AS t2 INNER JOIN table3 AS t3 ON t2.table3fk t3.id ) AS t ON t1.table2fk t2.id. NOT IN or NOT EXISTS queries can also be rewritten. MySQL Server supports multiple-table DELETE statements that can be used to efficiently delete rows based on information from one table or even from many tables. A subquery using IN can be rewritten with the DISTINCT keyword, for example: SELECT * FROM table1 WHERE col1 IN ( SELECT col1 FROM table2 ) Ĭan be rewritten as: SELECT DISTINCT table1.
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