数仓｜高级数据分析师常用5大HQL分析函数

Jtao3212 05-27 98

前言：

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数据准备

CREATE TABLE `orders` (    `order_num` String COMMENT '订单号',    `order_amount` DECIMAL ( 12, 2 ) COMMENT '订单金额',    `advance_amount` DECIMAL ( 12, 2 ) COMMENT '预付款',    `order_date` string COMMENT '订单日期',    `cust_code` string COMMENT '客户',    `agent_code` string COMMENT '代理商' );INSERT INTO orders VALUES('200100', '1000.00', '600.00', '2020-08-01', 'C00013', 'A003');INSERT INTO orders VALUES('200110', '3000.00', '500.00', '2020-04-15', 'C00019', 'A010');INSERT INTO orders VALUES('200107', '4500.00', '900.00', '2020-08-30', 'C00007', 'A010');INSERT INTO orders VALUES('200112', '2000.00', '400.00', '2020-05-30', 'C00016', 'A007'); INSERT INTO orders VALUES('200113', '4000.00', '600.00', '2020-06-10', 'C00022', 'A002');INSERT INTO orders VALUES('200102', '2000.00', '300.00', '2020-05-25', 'C00012', 'A012');INSERT INTO orders VALUES('200114', '3500.00', '2000.00', '2020-08-15', 'C00002','A008');INSERT INTO orders VALUES('200122', '2500.00', '400.00', '2020-09-16', 'C00003', 'A004');INSERT INTO orders VALUES('200118', '500.00', '100.00', '2020-07-20', 'C00023', 'A006');INSERT INTO orders VALUES('200119', '4000.00', '700.00', '2020-09-16', 'C00007', 'A010');INSERT INTO orders VALUES('200121', '1500.00', '600.00', '2020-09-23', 'C00008', 'A004');INSERT INTO orders VALUES('200130', '2500.00', '400.00', '2020-07-30', 'C00025', 'A011');INSERT INTO orders VALUES('200134', '4200.00', '1800.00', '2020-09-25', 'C00004','A005');INSERT INTO orders VALUES('200108', '4000.00', '600.00', '2020-02-15', 'C00008', 'A004');INSERT INTO orders VALUES('200103', '1500.00', '700.00', '2020-05-15', 'C00021', 'A005');INSERT INTO orders VALUES('200105', '2500.00', '500.00', '2020-07-18', 'C00025', 'A011');INSERT INTO orders VALUES('200109', '3500.00', '800.00', '2020-07-30', 'C00011', 'A010');INSERT INTO orders VALUES('200101', '3000.00', '1000.00', '2020-07-15', 'C00001','A008');INSERT INTO orders VALUES('200111', '1000.00', '300.00', '2020-07-10', 'C00020', 'A008');INSERT INTO orders VALUES('200104', '1500.00', '500.00', '2020-03-13', 'C00006', 'A004');INSERT INTO orders VALUES('200106', '2500.00', '700.00', '2020-04-20', 'C00005', 'A002');INSERT INTO orders VALUES('200125', '2000.00', '600.00', '2020-10-01', 'C00018', 'A005');INSERT INTO orders VALUES('200117', '800.00', '200.00', '2020-10-20', 'C00014', 'A001');INSERT INTO orders VALUES('200123', '500.00', '100.00', '2020-09-16', 'C00022', 'A002');INSERT INTO orders VALUES('200120', '500.00', '100.00', '2020-07-20', 'C00009', 'A002');INSERT INTO orders VALUES('200116', '500.00', '100.00', '2020-07-13', 'C00010', 'A009');INSERT INTO orders VALUES('200124', '500.00', '100.00', '2020-06-20', 'C00017', 'A007'); INSERT INTO orders VALUES('200126', '500.00', '100.00', '2020-06-24', 'C00022', 'A002');INSERT INTO orders VALUES('200129', '2500.00', '500.00', '2020-07-20', 'C00024', 'A006');INSERT INTO orders VALUES('200127', '2500.00', '400.00', '2020-07-20', 'C00015', 'A003');INSERT INTO orders VALUES('200128', '3500.00', '1500.00', '2020-07-20', 'C00009','A002');INSERT INTO orders VALUES('200135', '2000.00', '800.00', '2020-09-16', 'C00007', 'A010');INSERT INTO orders VALUES('200131', '900.00', '150.00', '2020-08-26', 'C00012', 'A012');INSERT INTO orders VALUES('200133', '1200.00', '400.00', '2020-06-29', 'C00009', 'A002');

AVG() 和SUM()需求描述：

第三季度每个代理商的移动平均收入和总收入

SELECT    agent_code,    order_date,    AVG( order_amount ) OVER ( PARTITION BY agent_code ORDER BY order_date)  avg_rev,    SUM( order_amount ) OVER ( PARTITION BY agent_code ORDER BY order_date ) total_rev FROMorders WHEREorder_date >= '2020-07-01' AND order_date <= '2020-09-30';

结果输出

A002    2020-07-20      2000    4000A002    2020-07-20      2000    4000A002    2020-09-16      1500    4500A003    2020-07-20      2500    2500A003    2020-08-01      1750    3500A004    2020-09-16      2500    2500A004    2020-09-23      2000    4000A005    2020-09-25      4200    4200A006    2020-07-20      1500    3000A006    2020-07-20      1500    3000A008    2020-07-10      1000    1000A008    2020-07-15      2000    4000A008    2020-08-15      2500    7500A009    2020-07-13      500     500A010    2020-07-30      3500    3500A010    2020-08-30      4000    8000A010    2020-09-16      3500    14000A010    2020-09-16      3500    14000A011    2020-07-18      2500    2500A011    2020-07-30      2500    5000A012    2020-08-26      900     900

FIRST_VALUE()和 LAST_VALUE()first_value: 取分组内排序后，截止到当前行，第一个值last_value: 取分组内排序后，截止到当前行，最后一个值需求描述

客户首次购买后多少天才进行下一次购买

SELECT    cust_code,    order_date,    datediff(order_date,FIRST_VALUE ( order_date ) OVER ( PARTITION BY cust_code ORDER BY order_date )) next_order_gap FROMorders order by cust_code,next_order_gap

结果输出

C00001  2020-07-15      0C00002  2020-08-15      0C00003  2020-09-16      0C00004  2020-09-25      0C00005  2020-04-20      0C00006  2020-03-13      0C00007  2020-08-30      0C00007  2020-09-16      17C00007  2020-09-16      17C00008  2020-02-15      0C00008  2020-09-23      221C00009  2020-06-29      0C00009  2020-07-20      21C00009  2020-07-20      21C00010  2020-07-13      0C00011  2020-07-30      0C00012  2020-05-25      0C00012  2020-08-26      93C00013  2020-08-01      0C00014  2020-10-20      0C00015  2020-07-20      0C00016  2020-05-30      0C00017  2020-06-20      0C00018  2020-10-01      0C00019  2020-04-15      0C00020  2020-07-10      0C00021  2020-05-15      0C00022  2020-06-10      0C00022  2020-06-24      14C00022  2020-09-16      98C00023  2020-07-20      0C00024  2020-07-20      0C00025  2020-07-18      0C00025  2020-07-30      12

LEAD() 和 LAG()lead(value_expr[,offset[,default]])：用于统计窗口内往下第n行值。第一个参数为列名，第二个参数为往下第n行（可选，默认为1），第三个参数为默认值（当往下第n行为NULL时候，取默认值，如不指定，则为NULLlag(value_expr[,offset[,default]]): 与lead相反，用于统计窗口内往上第n行值。第一个参数为列名，第二个参数为往上第n行（可选，默认为1），第三个参数为默认值（当往上第n行为NULL时候，取默认值，如不指定，则为NULL）需求描述

代理商最近一次出售的最高订单金额是多少？

SELECT agent_code, order_amount, LAG ( order_amount, 1 ) OVER ( PARTITION BY agent_code ORDER BY order_amount DESC ) last_highest_amount FROM orders ORDER BY agent_code, order_amount DESC;

结果输出

A001    800     NULLA002    4000    NULLA002    3500    4000A002    2500    3500A002    1200    2500A002    500     1200A002    500     500A002    500     500A003    2500    NULLA003    1000    2500A004    4000    NULLA004    2500    4000A004    1500    2500A004    1500    1500A005    4200    NULLA005    2000    4200A005    1500    2000A006    2500    NULLA006    500     2500A007    2000    NULLA007    500     2000A008    3500    NULLA008    3000    3500A008    1000    3000A009    500     NULLA010    4500    NULLA010    4000    4500A010    3500    4000A010    3000    3500A010    2000    3000A011    2500    NULLA011    2500    2500A012    2000    NULLA012    900     2000

RANK() 和DENSE_RANK()

rank：对组中的数据进行排名，如果名次相同，则排名也相同，但是下一个名次的排名序号会出现不连续。比如查找具体条件的topN行。RANK() 排序为 (1,2,2,4)

dense_rank：dense_rank函数的功能与rank函数类似，dense_rank函数在生成序号时是连续的，而rank函数生成的序号有可能不连续。当出现名次相同时，则排名序号也相同。而下一个排名的序号与上一个排名序号是连续的。

DENSE_RANK() 排序为 (1,2,2,3)

需求描述

每月第二高的订单金额是多少？

SELECT order_num, order_date, order_amount, order_month FROM (SELECT order_num, order_date, order_amount, DATE_FORMAT( order_date, 'YYYY-MM' ) AS order_month, DENSE_RANK ( ) OVER ( PARTITION BY DATE_FORMAT( order_date, 'YYYY-MM' ) ORDER BY order_amount DESC ) order_rank FROM orders  ) t WHERE order_rank = 2 ORDER BY order_date;

结果输出

200106  2020-04-20      2500    2020-04200103  2020-05-15      1500    2020-05200133  2020-06-29      1200    2020-06200101  2020-07-15      3000    2020-07200114  2020-08-15      3500    2020-08200119  2020-09-16      4000    2020-09200117  2020-10-20      800     2020-10

CUME_DIST()

cume_dist:如果按升序排列，则统计：小于等于当前值的行数/总行数(number of rows ≤ current row)/(total number of rows）。如果是降序排列，则统计：大于等于当前值的行数/总行数。比如，统计小于等于当前工资的人数占总人数的比例，用于累计统计。

需求描述

8月和9月每个订单的收入百分比

先查看一下8月和9月的数据，按订单金额排序

SELECT order_num, order_amount, order_date, agent_code FROM orders WHERE order_date >= '2020-08-01'  AND order_date <= '2020-09-30' ORDER BY date_format( order_date, "YYYY-MM" ), order_amount;

其结果为：

SELECT

DATE_FORMAT( order_date, 'YYYY-MM' ) AS order_month,

agent_code,

order_amount,

CUME_DIST ( ) OVER ( PARTITION BY DATE_FORMAT( order_date, 'YYYY-MM' ) ORDER BY order_amount )

FROM

orders

WHERE

order_date >= '2020-08-01'

AND order_date <= '2020-09-30';

结果输出2020-08 A012 900 0.25