[2017 update: MySQL 8.0.1 now features SQL-standard CTE syntax; more information is here ; the entry below, from 2013, shows how to work around the absence of CTEs in older MySQL versions.] If you have been using certain DBMSs, or reading recent versions of the SQL standard, you are probably aware of the so-called "WITH clause" of SQL. Some call it Subquery Factoring . Others call it Common Table Expression (CTE). In its simplest form, this feature is a kind of "boosted derived table". Assume that a table T1 has three columns: CREATE TABLE T1( YEAR INT, # 2000, 2001, 2002 ... MONTH INT, # January, February, ... SALES INT # how much we sold on that month of that year ); Now I want to know the sales trend (increase/decrease), year after year: SELECT D1.YEAR, (CASE WHEN D1.S>D2.S THEN 'INCREASE' ELSE 'DECREASE' END) AS TREND FROM (SELECT YEAR, SUM(SALES) AS S FROM T1 GROUP BY YEAR) AS D1, (SELECT YEAR, SUM(SALES) AS S FROM T1 GR
In a previous post , I analyzed how a query of the famous DBT3 benchmark was optimized by MySQL. It was this query, named "Q16" in the DBT3 jargon: select p_brand, p_type, p_size, count(distinct ps_suppkey) as supplier_cnt from partsupp, part where p_partkey = ps_partkey and p_brand <> 'Brand#23' and p_type not like 'LARGE PLATED%' and p_size in (43, 1, 25, 5, 35, 12, 42, 40) and ps_suppkey not in ( select s_suppkey from supplier where s_comment like '%Customer%Complaints%' ) group by p_brand, p_type, p_size order by supplier_cnt desc, p_brand, p_type, p_size; Here is a brief recap of conclusions I had drawn: for this query, MySQL tranforms the IN condition to EXISTS and then evaluates it with the "unique_subquery" technique, which does an index lookup into the subquery's table. IN is evaluated 120,000 times (once per combined row of the outer tables). The total execution time of query Q16
Hello all. Last months have been busy for me with various tasks, and one of them is finally done and released in MySQL 8.0.14 : LATERAL derived tables. All details are in my post on mysqlserverteam . I think it is a useful addition to our SQL capabilities. Enjoy!
Commentaires
Enregistrer un commentaire