因为UNION ALL的每个部分可能相同,但是如果每个部分都去执行一遍的话,则成本太高,所以可以使用WITH AS短语,则只要执行一遍即可。如果WITH AS短语所定义的表名被调用两次以上,则优化器会自动将WITH AS短语所获取的数据放入一个TEMP表里,如果只是被调用一次,则不会。而提示materialize则是强制将WITH AS短语里的数据放入...
WITHC(OrderYear,CustomerID)AS(SELECTYEAR(OrderDate),CustomerIDFROMdbo.Orders)SELECTOrderYear,COUNT(DISTINCTCustomerID)ASNumCustsFROMCGROUP BYOrderYear; CTE实例二(多重CTEs) WITHC1AS(SELECTYEAR(OrderDate)ASOrderYear,CustomerIDFROMdbo.Orders),C2AS(SELECTOrderYear,COUNT(DISTINCTCustomerID)ASNumCustsFROMC...
with as 在t-sql(SQL Server 2005版)中也称为公用表达试,语法如下: WITH [name of temporary resultset] (columns in result set) AS ( SQL Query Definition ) with as 作用:相当于定义一个临时名称存储一个select结果集。 with as 效率:比子查询和表变量效率要高。 examples: WITH Developers (Name,Sala...
对于完全相同的行,大都表示创建一个临时表来过渡操作。 以下使用“with 子句 和 ROW_NUMBER()函数”来实现删除完全重复的其他行 ,partition分组时可以选择一列(或所有列)进行分组排序 ;WITH TAB AS( SELECT ROW_NUMBER()over(partition by object_id order by (select 0)) id FROM [dbo].[tabName] )DELETE...
不支持吧，建议将with Data as 也写进@sql里 set @sql = ';with Data as ( ' + @sql + ' )'另动态语句不太好，尽量用变量代替 确实是不支持，因为；with cte 里面要放的是select、update等，不能是一个数据集吧。
--WITH只需要使用一次WITHTemp1AS(),Temp2AS()SELECT... 视图 视图是虚拟表,自身不包含数据,只存储了动态查询语句,多用于简化复杂查询。 视图创建后被作为数据库对象而存储到数据库中,除非显式进行删除。因此,同一个视图可以被不同的查询多次使用。
WITH <expression_name> (Column1, Column2, …) AS (CTE Definition) 表示: “<expression_name>” CTE的命名 “Column 1, Column2,…” 查询语句返回结果集的列名称 “CTE Definition” select语句返回的结果集. 定义CTE需要跟着一个INSERT, UPDATE, DELETE, 或者SELECT的语句来引用CTE。假如CTE是一个批处理...
[ FROM { } [ , ...n ] ] ::= { table_or_view_name [ FOR SYSTEM_TIME <system_time> ] [ [ AS ] table_alias ] [ <tablesample_clause> ] [ WITH ( < table_hint > [ [ , ] ...n ] ) ] | rowset_function [ [ AS ] table_alias ] [ ( bulk_column_alias [ , ......
--Create a login on the master databaseCREATELOGIN job_credentialWITHPASSWORD='<password>'; SQL --Create a user on a user database mapped to a login.CREATEUSER[job_credential]FROMLOGIN [job_credential];-- Grant permissions as necessary to execute your jobs. For example, ALTER and CREATE ...
Joins in T-SQL are clauses used to combine rows from two or more tables, based on a related column between them. Joins specify how SQL should use data from one table to select the rows in another table. Several operators -- such as =, <, >, <>, <=, >=, !=, BETWEEN, LIKE,...