SELECT name, salary FROM People WHERE NAME IN ( SELECT DISTINCT NAME FROM population WHERE country = "Canada" AND city = "Toronto" ) AND salary >= ( SELECT AVG( salary ) FROM salaries WHERE gender = "Female")这似乎似乎难以理解,但如果在查询中有许多子查询,那么怎么样?这就是CTEs发挥作用的地方。
with toronto_ppl as ( SELECT DISTINCT name FROM population WHERE country = "Canada" AND city = "Toronto" ) , avg_female_salary as ( SELECT AVG(salary) as avgSalary FROM salaries WHERE gender = "Female" ) SELECT name , salary FROM People WHERE name in (SELECT DISTINCT FROM toronto_ppl) AND salary >= (SELECT avgSalary FROM avg_female_salary)现在很清楚,Where子句是在多伦多的名称中过滤。如果您注意到,CTE很有用,因为您可以将代码分解为较小的块,但它们也很有用,因为它允许您为每个CTE分配变量名称(即toronto_ppl和avg_female_salary)。同样,CTEs允许您完成更高级的技术,如创建递归表。
# 堆代码 duidaima.com with org_structure as ( SELECT id , manager_id FROM staff_members WHERE manager_id IS NULL UNION ALL SELECT sm.id , sm.manager_id FROM staff_members sm INNER JOIN org_structure os ON os.id = sm.manager_id3.临时函数
SELECT name , CASE WHEN tenure < 1 THEN "analyst" WHEN tenure BETWEEN 1 and 3 THEN "associate" WHEN tenure BETWEEN 3 and 5 THEN "senior" WHEN tenure > 5 THEN "vp" ELSE "n/a" END AS seniority FROM employees相反,您可以利用临时函数来捕获案例子句。
CREATE TEMPORARY FUNCTION get_seniority(tenure INT64) AS ( CASE WHEN tenure < 1 THEN "analyst" WHEN tenure BETWEEN 1 and 3 THEN "associate" WHEN tenure BETWEEN 3 and 5 THEN "senior" WHEN tenure > 5 THEN "vp" ELSE "n/a" END ); SELECT name , get_seniority(tenure) as seniority FROM employees通过临时函数,查询本身更简单,更可读,您可以重复使用资历函数!
Initial table: +------+---------+-------+ | id | revenue | month | +------+---------+-------+ | 1 | 8000 | Jan | | 2 | 9000 | Jan | | 3 | 10000 | Feb | | 1 | 7000 | Feb | | 1 | 6000 | Mar | +------+---------+-------+ Result table: +------+-------------+-------------+-------------+-----+-----------+ | id | Jan_Revenue | Feb_Revenue | Mar_Revenue | ... | Dec_Revenue | +------+-------------+-------------+-------------+-----+-----------+ | 1 | 8000 | 7000 | 6000 | ... | null | | 2 | 9000 | null | null | ... | null | | 3 | null | 10000 | null | ... | null | +------+-------------+-------------+-------------+-----+-----------+5.EXCEPT vs NOT IN
+----+-------+--------+-----------+ | Id | Name | Salary | ManagerId | +----+-------+--------+-----------+ | 1 | Joe | 70000 | 3 | | 2 | Henry | 80000 | 4 | | 3 | Sam | 60000 | NULL | | 4 | Max | 90000 | NULL | +----+-------+--------+-----------+Answer: SELECT a.Name as Employee FROM Employee as a JOIN Employee as b on a.ManagerID = b.Id WHERE a.Salary > b.Salary7.Rank vs Dense Rank vs Row Number
.排名在观看的分钟数,不同观众的数量等观看的顶级视频。
SELECT Name , GPA , ROW_NUMBER() OVER (ORDER BY GPA desc) , RANK() OVER (ORDER BY GPA desc) , DENSE_RANK() OVER (ORDER BY GPA desc) FROM student_grades
# Comparing each month's sales to last month SELECT month , sales , sales - LAG(sales, 1) OVER (ORDER BY month) FROM monthly_sales # Comparing each month's sales to the same month last year SELECT month , sales , sales - LAG(sales, 12) OVER (ORDER BY month) FROM monthly_sales9.计算运行总数
SELECT Month , Revenue , SUM(Revenue) OVER (ORDER BY Month) AS Cumulative FROM monthly_revenue
+---------+------------------+------------------+ | Id(INT) | RecordDate(DATE) | Temperature(INT) | +---------+------------------+------------------+ | 1 | 2015-01-01 | 10 | | 2 | 2015-01-02 | 25 | | 3 | 2015-01-03 | 20 | | 4 | 2015-01-04 | 30 | +---------+------------------+------------------+Answer: SELECT a.Id FROM Weather a, Weather b WHERE a.Temperature > b.Temperature AND DATEDIFF(a.RecordDate, b.RecordDate) = 1谢谢阅读!