WITH 语句
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
1
WITH 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
1
SELECT *2
FROM 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
1
total_tasks_per_project AS (2
SELECT 3
project_id,4
count(*) as task_count5
FROM tasks6
GROUP BY project_id7
),8
9
tasks_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
1
overloaded_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 project3
4
--- Initial query to grab project title and tasks per user5
WITH 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 project24
total_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 user33
tasks_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 assigned43
overloaded_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
50
SELECT 51
email,52
task_list,53
title54
FROM 55
users_tasks,56
overloaded_users57
WHERE58
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
1
WITH moved_rows AS (2
DELETE FROM products3
WHERE4
"date" >= ‘2010-10-01‘5
AND "date" < ‘2010-11-01‘6
RETURNING *7
)8
INSERT INTO products_log9
SELECT * 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。