本文用于复习数据库窗口函数，希望能够温故知新，也希望读到这篇文章的有所收获。
本文以：MySQL为例
参考文档： https://www.begtut.com/mysql/mysql-window-functions.html
使用的样例数据：https://www.begtut.com/mysql/mysql-sample-database.html
1. 概括的说明
函数说明ROW_NUMBER为其分区中的每一行分配一个序号。RANK根据ORDER BY的字段，为每一行分配一个排名。 值相同的行分配相同的排名, 下一行排名不联系，会累加值相同的行数。DENSE_RANK与RANK（）函数类似，只是当出现值相同的行时，排名是连续的，不是累加行数。PERCENT_RANK计算分区或结果集中行的百分位数。计算公式为：(当前从小到大排序序号-1 ) / (总序号数-1) 【就是(rank - 1) / (total_rows - 1) 】FIRST_VALUE返回指定表达式相对于窗口框架中第一行的值。LAST_VALUE返回指定表达式相对于窗口框架中最后一行的值。LEAD返回分区中当前行之后的第N行的值。 如果不存在后续行，则返回NULL。LAG返回分区中当前行之前的第N行的值。 如果不存在前一行，则返回NULL。NTILE将每个窗口分区的行分配到指定数量的已排名组中。 （把结果分成n个组）CUME_DIST计算一组值中值的累积分布。NTH_VALUE返回窗口框架第N行的参数
2. 注意 rows between 的用法
rows between …… and ……unbounded preceding 前面所有行 、n preceding 前面n行unbounded following 后面所有行 、n following 后面n行current row 当前行
SELECT
orderNumber,
productCode,
quantityOrdered,
SUM(quantityOrdered) OVER(PARTITION BY orderNumber ORDER BY productcode) AS quantity_amount,
-- 前面一行和当前行的值累加
SUM(quantityOrdered) OVER(PARTITION BY orderNumber ORDER BY productcode ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) quantity_add
FROM
mysqldemo.orderdetails
WHERE
orderNumber = 10103;
3. 注意 range between的用法
range between 按照排序字段的值限制窗口大小。主要将order by后面字段排序后，然后根据排序字段的值，框定一个范围，再对这个范围内的行进行汇总。样例如下：
sum(num) over(order by dateTime
range between interval 6 day preceding and current row)
-- 必须是date类型的数据，这一天和前面6天（如果存在）的数据
sum(close) over(order by salary
range between 100 preceding and 200 following)
--通过 salary 字段差值来进行选择。如当前行的 salary 字段值是 200，那么这个窗口大小的定义就会选择分区中 salary 字段值落在 100 至 400 区间的记录（行），再求这些行的sum(close).
需要注意的点：
rows表示行，就是前n行，后n行。range表示的是具体的值，比这个值小n的行，比这个值大n的行。是以当前值为锚点进行计算。同时 range 也可以使用 between unbounded preceding and unbounded following，效果和等同于rows一样，取上下限所有行，不指定值。range 窗口仅对数字和日期起作用,因为需要计算值的范围。在range 的开窗中，order by 中只能有一列；rows 的开窗的order by 可以有多列。
SELECT
orderNumber,
productCode,
quantityOrdered,
SUM(quantityOrdered) OVER(PARTITION BY orderNumber ORDER BY quantityOrdered) AS quantity_amount,
-- quantityOrdered 的值-1 和 +2的值区间范围内的行的累加
SUM(quantityOrdered) OVER(PARTITION BY orderNumber ORDER BY quantityOrdered RANGE BETWEEN 1 PRECEDING AND 2 following) quantity_add
FROM
mysqldemo.orderdetails;
4. ROW_NUMBER & RANK & DENSE_RANK
比较常用，都很熟悉，基本用法就不用赘述了。
SELECT
orderNumber,
productCode,
quantityOrdered,
ROW_NUMBER() OVER (ORDER BY quantityOrdered) AS nb,
RANK() OVER (PARTITION BY orderNumber ORDER BY quantityOrdered) AS rank_quantity,
DENSE_RANK() OVER (PARTITION BY orderNumber ORDER BY quantityOrdered) AS dense_rank_quantity
FROM
mysqldemo.orderdetails
WHERE
orderNumber = 10103;
rank和dense_rank 的区别，就是遇到有多行值相同时，那么下一行的序号，rank会加上重复的行数，那么rank对应的序号就不连续了；dense_rank 不会加上重复的行数，保持序号任然是连续的。
需要注意的点：
ROW_NUMBER 不加partition的时候，对所有行加序号，加partition之后分组加序号。RANK 注意不加order by的时候，不排序，全是1，即使加partition也没用；一定要加order by才会排序。SUM 用法和 ROW_NUMBER 相同，汇总和分组汇总。
SELECT *,
ROW_NUMBER() OVER () row_num0,
ROW_NUMBER() OVER (PARTITION BY productline) row_num1,
RANK() OVER() AS Rank00,
RANK() OVER(PARTITION BY productline) AS Rank01,
RANK() OVER(PARTITION BY productline,order_year) AS Rank02,
RANK() OVER(order by amount) AS Rank1,
RANK() OVER(PARTITION BY productline order by amount) AS Rank2,
SUM(amount) OVER(PARTITION BY productline,order_year ) AS amount0,
SUM(amount) OVER(PARTITION BY productline ) AS amount1,
SUM(amount) OVER() AS amount2
FROM
(SELECT productline, year(orderDate) order_year, sum(quantityOrdered) as amount
FROM orders
INNER JOIN orderdetails USING (orderNumber)
INNER JOIN products USING (productCode)
GROUP BY productline,order_year) T;
5. PERCENT_RANK()
函数返回一个从0到1的数字。 计算公式为：(rank - 1) / (total_rows - 1)。
rank是当前行的等级，total_rows是要计算的行数。 公式的意思就是计算当前行的等级减1，除以分区或结果集中的总行数减1。
PERCENT_RANK()对于分区或结果集中的第一行，函数始终返回零。重复的列值将接收相同的PERCENT_RANK()值。PERCENT_RANK()是一个顺序敏感函数，因此，您应始终使用ORDER BY子句。
CREATE TABLE productLineSales -- 我们创建了一张表，后面还会重复用到它
SELECT
productLine,
YEAR(orderDate) orderYear,
SUM(quantityOrdered * priceEach) orderValue
FROM orderDetails
INNER JOIN orders USING (orderNumber)
INNER JOIN products USING (productCode)
GROUP BY productLine , YEAR(orderDate);
WITH t AS (
SELECT productLine, SUM(orderValue) orderValue
FROM productLineSales
GROUP BY productLine
)
SELECT
productLine,
orderValue,
ROUND(PERCENT_RANK() OVER (ORDER BY orderValue),2) percentile_rank
FROM t;
在这个例子中： 首先，我们使用表达式按产品线汇总订单值。 其次，我们用它PERCENT_RANK()来计算每种产品的订单价值的百分等级。 以下是输出中的一些分析：
订单价值Trains并不比任何其他产品线更好，后者用零表示。Vintage Cars 表现优于50％的其他产品。Classic Cars 表现优于任何其他产品系列，因此其百分比等级为1或100％
6. CUME_DIST
它表示值小于或等于当前行的值除以总行数。 公式为： ROW_NUMBER() / total_rows 。注意和 PERCENT_RANK 的区别。
CUME_DIST()函数的返回值大于零且小于或等于1。重复的列值接收相同的CUME_DIST()值。
样例：计算某产品的订单订货量数量分布 （注意第7行开始有重复的值31，对应百分比也是相同的。表示数量小于等于31的一共10行，占总行数28的35.71%）
SELECT orderNumber, productCode, quantityOrdered,
ROW_NUMBER() OVER(ORDER BY quantityordered) AS nb,
CUME_DIST() OVER(ORDER BY quantityordered) AS pct,
PERCENT_RANK() OVER(ORDER BY quantityordered) AS pct_rank
FROM mysqldemo.orderdetails
WHERE productcode = 'S18_2949';
7. FIRST_VALUE
样例：获取客户首单订单金额。
SELECT customernumber,
amount,
paymentDate,
FIRST_VALUE (amount) OVER (PARTITION BY customernumber ORDER BY paymentDate) AS first_amount
FROM payments
ORDER BY customernumber;
8. Last_Value 样例：获取客户最后一笔订单金额。 注意：Last_Value 和 First_Value 不同, 他认为每一行，是当前行中的最后一行。注意对比下面两个字段的不同。
SELECT customernumber, amount, paymentDate,
last_value (amount) OVER (PARTITION BY customernumber ORDER BY paymentDate) AS last_amount,
last_value (amount) OVER (PARTITION BY customernumber ORDER BY paymentDate
RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
) AS last_amount_umbounded
FROM payments
ORDER BY customernumber;
8. Lead和Lag
函数类似，是查询某一字段的从当前行往后找到第N行的数据(Lead)和往前找到第N行的数据(Lag)。在找到某一行的偏移n行的数据非常有用。 lead/lag(expression, offffset, default) over(partion by ......order by ......)
expression 要取的是哪一个字段offset 是从当前行前进（lead）/后退（lag）的行数。 必须是一个非负整数，为零则取当前行。default 如果没有后续行，则函数返回default。例如，如果offset是1，则lead的最后一行，lag的第一行的返回值为default。 未指定default_value，则返回 NULL 。
样例： 查询出上一个订单，下一个订单的时间
SELECT
customerName,
orderDate,
LEAD(orderDate,1) OVER (PARTITION BY customerNumber ORDER BY orderDate ) nextOrderDate,
LAG(orderDate,1) OVER (PARTITION BY customerNumber ORDER BY orderDate ) PreviousOrderDate
FROM orders
INNER JOIN customers USING (customerNumber);
样例：查询出下单时间间隔最长的用户。
SELECT customerName,
MAX(orderdate_interval) AS MAX_interval,
RANK() OVER(ORDER BY MAX(orderdate_interval) DESC) AS data_rank
FROM(
SELECT
customerName,
orderDate,
LEAD(orderDate,1) OVER (PARTITION BY customerNumber ORDER BY orderDate ) nextOrderDate,
datediff(LEAD(orderDate,1) OVER (PARTITION BY customerNumber ORDER BY orderDate), orderDate) orderdate_interval
FROM orders
INNER JOIN customers USING (customerNumber)) T1
WHERE nextOrderDate IS NOT NULL
GROUP BY customerName;
9. NTILE 平均分组
样例：将产品线按照年份，汇总订单金额，并且划分为三个组。 注意不能平均分配时，例如将9行数据分成4个组，他会把第1组分3个，剩余3个组每个组2个；
SELECT
productline,
orderYear,
orderValue,
NTILE(3) OVER (PARTITION BY orderYear ORDER BY orderValue DESC) product_line_group
FROM
productlineSales;
样例： 查询出2013支付金额排名前30%的所有用户
SELECT customerNumber, pay_amount, level
FROM
(SELECT customerNumber, SUM(amount) AS pay_amount,
NTILE(10) OVER(ORDER BY SUM(amount) DESC) AS level
FROM mysqldemo.payments
WHERE Year(paymentDate) = 2013
GROUP BY customerNumber)a
WHERE level in (1,2,3);
通过这种方法计算出来的百分比不准确，通过下面的SQL，会发现前3个组的人数超过了30%。
SELECT COUNT(customerNumber), level
FROM
(SELECT customerNumber, SUM(amount) AS pay_amount,
NTILE(10) OVER(ORDER BY SUM(amount) DESC) AS level
FROM mysqldemo.payments
WHERE Year(paymentDate) = 2013
GROUP BY customerNumber)a
GROUP BY level;
使用用 CUME_DIST 效果更好。
SELECT customerNumber, pay_amount, level, pct
FROM
(SELECT customerNumber, SUM(amount) AS pay_amount,
NTILE(10) OVER(ORDER BY SUM(amount) DESC) AS level,
CUME_DIST() over(order by SUM(amount) desc) as pct
FROM mysqldemo.payments
WHERE Year(paymentDate) = 2013
GROUP BY customerNumber)a
直接定位带排序小于等于30%的即可。从结果可以看出，和NTILE不一样，第三组的人没有全部都取。
10. NTH_VALUE
函数格式为：
NTH_VALUE(expression, N)
OVER (
partition_clause
order_clause
frame_clause)
从有序行集中的第N行获取值；如果第N行不存在，则函数返回NULL；N必须是正整数。 注意：From First（标准SQL 支持 From Last, MySQL只支持From First。如果要模拟效果From Last，则可以使用其中ORDER BY倒叙排列） 样例：2015年每月购买金额第三的人
SELECT paymentmonth,customernumber, amount,
NTH_VALUE(customernumber, 3) OVER(PARTITION BY paymentmonth ORDER BY amount DESC
RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS NTH
FROM (
SELECT MONTH(paymentDate) AS paymentmonth, customernumber, SUM(amount) amount
FROM payments
WHERE YEAR(paymentDate) = 2015
GROUP BY customernumber, paymentmonth) T1
11. 测试：查询出每年连续下单的客户和连续的年份
方法1
使用 lag 取上一年的年份，计算差值是1的，就是这两年是连续的；然后对customerName进行group by。
SELECT customerName, max(orderYear), min(previousYear), SUM(gap)+1
FROM (
SELECT customerName,
orderYear,
lag(orderYear) over(partition by customerName order by orderYear) AS previousYear,
orderYear - lag(orderYear) over(partition by customerName order by orderYear) gap
FROM (
SELECT
customerName,
YEAR(orderDate) AS orderYear
FROM orders
INNER JOIN customers USING (customerNumber)
GROUP BY customerName, orderYear
) T1
) T2
WHERE gap =1
GROUP BY customerName
方法2
用Year 减去row_number, 取得gap，gap相同的，就是年份连续的。
SELECT customerName, minYear, maxYear, max(nb)
FROM (
SELECT customerName,gap,orderYear,
min(orderYear) OVER (partition by customerName,gap ORDER BY customerName,gap) minYear,
max(orderYear)OVER (partition by customerName,gap ORDER BY customerName,gap) maxYear,
ROW_NUMBER() OVER (partition by customerName,gap ORDER BY customerName,gap) nb
FROM(
SELECT customerName, orderYear, orderYear-nbbycustomer as gap
FROM (
SELECT
customerName,
YEAR(orderDate) AS orderYear,
ROW_NUMBER() OVER (PARTITION BY customerName ORDER BY YEAR(orderDate)) nbbycustomer
FROM orders
INNER JOIN customers USING (customerNumber)
GROUP BY customerName,orderYear
)T1
) T2
) T3
WHERE minYear <> maxYear
GROUP BY customerName, minYear, maxYear;
12. 其它有趣的函数
使用rand() 获取随机10行数据。
select * from customers order by rand() limit 10;
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