CTEs(Common Table Expressions),也就是通用表表达式,你有可能称做它为WITH 语句。和数据库中视图一样,它的主要好处就是,它允许你在当前事务中创建临时表。你可以大量使用它,因为它允许你思路清晰的构建模块,别人很容易就理解你在做什么。 WITH语句作为一个辅助语句依附于主语句,WITH语句和主语句都可以是SELECT,INSERT,UPDATE,DELETE中的任何一种语句。
CTEs的优势在可读性上,其性能通常不如经过精简优化过的SQL语句性能高。大多数差距小于一倍差距。
让我们select举个简单的例子
WITH users_tasks AS (
SELECT
users.email,
array_agg(tasks.name) as task_list,
projects.title
FROM
users,
tasks,
project
WHERE
users.id = tasks.user_id
projects.title = tasks.project_id
GROUP BY
users.email,
projects.title
)16 1WITH users_tasks AS (2 SELECT 3 users.email,4 array_agg(tasks.name) as task_list,5 projects.title6 FROM7 users,8 tasks,9 project10 WHERE11 users.id = tasks.user_id12 projects.title = tasks.project_id13 GROUP BY14 users.email,15 projects.title16)通过这样定义临时表users_tasks,我就可以在后面加上对users_tasks基本查询语句,像:
SELECT *
FROM users_tasks;2 1SELECT *2FROM users_tasks;有趣的是你可以将它们连在一起。当我知道分配给每个用户的任务量时,也许我想知道在一个指定的任务上,谁因为对这个任务负责超过了50%而因此造成瓶颈。为了简化,我们可以使用多种方式,先计算每个任务的总量,然后是每人针对每个任务的负责总量。
total_tasks_per_project AS (
SELECT
project_id,
count(*) as task_count
FROM tasks
GROUP BY project_id
),
tasks_per_project_per_user AS (
SELECT
user_id,
project_id,
count(*) as task_count
FROM tasks
GROUP BY user_id, project_id
),16 1total_tasks_per_project AS (2 SELECT 3 project_id,4 count(*) as task_count5 FROM tasks6 GROUP BY project_id7),8 9tasks_per_project_per_user AS (10 SELECT 11 user_id,12 project_id,13 count(*) as task_count14 FROM tasks15 GROUP BY user_id, project_id16),现在我们将组合一下然后发现超过50%的用户
overloaded_users AS (
SELECT tasks_per_project_per_user.user_id
FROM tasks_per_project_per_user,
total_tasks_per_project
WHERE tasks_per_project_per_user.task_count > (total_tasks_per_project / 2)
)6 1overloaded_users AS (2 SELECT tasks_per_project_per_user.user_id3 FROM tasks_per_project_per_user,4 total_tasks_per_project5 WHERE tasks_per_project_per_user.task_count > (total_tasks_per_project / 2)6)最终目标,我想获得超负荷工作这的用户和任务的逗号分隔列表。我们只要简单地对overloaded_users和 users_tasks的初始列表进行join操作。放在一起可能有点长,但是可读性强。作为额外帮助,我又在每一层加了注释。
--- Query highlights users that have over 50% of tasks on a given project
--- Gives comma separated list of their tasks and the project
--- Initial query to grab project title and tasks per user
WITH users_tasks AS (
SELECT
users.id as user_id,
users.email,
array_agg(tasks.name) as task_list,
projects.title
FROM
users,
tasks,
project
WHERE
users.id = tasks.user_id
projects.title = tasks.project_id
GROUP BY
users.email,
projects.title
),
--- Calculates the total tasks per each project
total_tasks_per_project AS (
SELECT
project_id,
count(*) as task_count
FROM tasks
GROUP BY project_id
),
--- Calculates the projects per each user
tasks_per_project_per_user AS (
SELECT
user_id,
project_id,
count(*) as task_count
FROM tasks
GROUP BY user_id, project_id
),
--- Gets user ids that have over 50% of tasks assigned
overloaded_users AS (
SELECT tasks_per_project_per_user.user_id
FROM tasks_per_project_per_user,
total_tasks_per_project
WHERE tasks_per_project_per_user.task_count > (total_tasks_per_project / 2)
)
SELECT
email,
task_list,
title
FROM
users_tasks,
overloaded_users
WHERE
users_tasks.user_id = overloaded_users.user_id58 1--- Query highlights users that have over 50% of tasks on a given project2--- Gives comma separated list of their tasks and the project34--- Initial query to grab project title and tasks per user5WITH users_tasks AS (6 SELECT 7 users.id as user_id,8 users.email,9 array_agg(tasks.name) as task_list,10 projects.title11 FROM12 users,13 tasks,14 project15 WHERE16 users.id = tasks.user_id17 projects.title = tasks.project_id18 GROUP BY19 users.email,20 projects.title21),22 23--- Calculates the total tasks per each project24total_tasks_per_project AS (25 SELECT 26 project_id,27 count(*) as task_count28 FROM tasks29 GROUP BY project_id30),31 32--- Calculates the projects per each user33tasks_per_project_per_user AS (34 SELECT 35 user_id,36 project_id,37 count(*) as task_count38 FROM tasks39 GROUP BY user_id, project_id40),41 42--- Gets user ids that have over 50% of tasks assigned43overloaded_users AS (44 SELECT tasks_per_project_per_user.user_id45 FROM tasks_per_project_per_user,46 total_tasks_per_project47 WHERE tasks_per_project_per_user.task_count > (total_tasks_per_project / 2)48)49 50SELECT 51 email,52 task_list,53 title54FROM 55 users_tasks,56 overloaded_users57WHERE58 users_tasks.user_id = overloaded_users.user_id来个delete的例子:
本例通过WITH中的DELETE语句从products表中删除了一个月的数据,并通过RETURNING子句将删除的数据集赋给moved_rows这一CTE,最后在主语句中通过INSERT将删除的商品插入products_log中。
WITH moved_rows AS (
DELETE FROM products
WHERE
"date" >= ‘2010-10-01‘
AND "date" < ‘2010-11-01‘
RETURNING *
)
INSERT INTO products_log
SELECT * FROM moved_rows;9 1WITH moved_rows AS (2 DELETE FROM products3 WHERE4 "date" >= ‘2010-10-01‘5 AND "date" < ‘2010-11-01‘6 RETURNING *7)8INSERT INTO products_log9SELECT * FROM moved_rows;如果WITH里面使用的不是SELECT语句,并且没有通过RETURNING子句返回结果集,则主查询中不可以引用该CTE,但主查询和WITH语句仍然可以继续执行。这种情况可以实现将多个不相关的语句放在一个SQL语句里,实现了在不显式使用事务的情况下保证WITH语句和主语句的事务性。
WITH使用注意事项【个人感觉有点类似线程不安全】
WITH中的数据修改语句会被执行一次,并且肯定会完全执行,无论主语句是否读取或者是否读取所有其输出。而WITH中的SELECT语句则只输出主语句中所需要记录数。 WITH中使用多个子句时,这些子句和主语句会并行执行,所以当存在多个修改子语句修改相同的记录时,它们的结果不可预测。 所有的子句所能“看”到的数据集是一样的,所以它们看不到其它语句对目标数据集的影响。这也缓解了多子句执行顺序的不可预测性造成的影响。 如果在一条SQL语句中,更新同一记录多次,只有其中一条会生效,并且很难预测哪一个会生效。 如果在一条SQL语句中,同时更新和删除某条记录,则只有更新会生效。 目前,任何一个被数据修改CTE的表,不允许使用条件规则,和ALSO规则以及INSTEAD规则。WITH RECURSIVE
WITH语句还可以通过增加RECURSIVE修饰符来引入它自己,从而实现递归。 WITH RECURSIVE一般用于处理逻辑上层次化或树状结构的数据,典型的使用场景是寻找直接及间接子结点。Postgresql 特性 CTEs (with)
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