SQL實現佔比（時間函數升級版）

之前博文中寫過一篇

《SQL實現佔比、同比、環比指標分析》

其中列舉了mysql和oracle實現佔比的兩種方式，分別使用on1=1和cross join 實現笛卡爾積。
基本語法如下

SELECT
  `status`,
  number,
  concat(round(number / total * 100.00, 2), '%') percent
FROM
  (
    SELECT
      *
    FROM
      (
        SELECT
          `status`,
          COUNT(1) number
        FROM
          `user_tasks`
        GROUP BY
          `status`
      ) t1
      INNER JOIN(
        SELECT
          COUNT(1) total
        FROM
          `user_tasks`
      ) t2 ON 1 = 1

基本這種操作可以應對大部分的佔比求值， 但是當使用時間進行分組求佔比的時候就需要注意了

例如下面的例子

創建數據庫並插入數據

CREATE TABLE `order` (
  `order_id` int(11) NOT NULL,
  `order_time` datetime DEFAULT NULL,
  `order_num` int(11) DEFAULT NULL,
  PRIMARY KEY (`order_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

插入數據

INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (1, '2019-01-02 15:02:42', 100);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (2, '2019-01-24 15:03:18', 200);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (3, '2018-01-04 15:03:37', 50);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (4, '2018-01-26 15:12:12', 120);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (5, '2019-02-01 15:12:48', 300);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (6, '2018-02-20 15:12:58', 180);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (7, '2019-03-12 15:13:08', 260);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (8, '2018-03-22 15:13:14', 220);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (9, '2019-04-17 15:13:27', 350);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (10, '2018-04-19 15:13:59', 280);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (11, '2019-04-17 15:21:45', 260);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (12, '2019-05-21 15:21:54', 200);
INSERT INTO `order`(`order_id`, `order_time`, `order_num`) VALUES (13, '2018-05-10 15:22:03', 220);

如下圖，該表記錄了2018年1-5月和209年1-5月的訂單量

2.誤區：沒有進行對月和年分別分組

這時候我們發現，在做彙總的時候月份需要按照月份，年份需要按照年份分組，這時候我們進行笛卡爾積進行查看

3.誤區：笛卡爾積錯位

SELECT
	* 
FROM
	( SELECT DATE_FORMAT( order_time, '%Y-%m' ) AS MONTH, 
	sum( order_num ) AS number FROM `order` 
	GROUP BY MONTH ) t1
	JOIN 
	( SELECT DATE_FORMAT( order_time, '%Y' ) AS YEAR,
	sum( order_num ) AS total FROM `order` 
	GROUP BY YEAR ) t2 
	ON 1 = 1

這時候我們查看一下

total和number的彙總值是沒問題對的，一個是按照月份一個是按照年份，但是在進行笛卡爾積關聯的時候錯位了

這是因爲我們在拼接的時候少了拼接條件

4.誤區：添加條件失敗

SELECT
	* 
FROM
	( SELECT DATE_FORMAT( order_time, '%Y-%m' ) AS MONTH, sum( order_num ) AS number FROM `order` 
	GROUP BY MONTH ) t1
	JOIN 
	( SELECT DATE_FORMAT( order_time, '%Y' ) AS YEAR,sum( order_num ) AS total FROM `order` 
	GROUP BY YEAR ) t2 
	ON 1 = 1 AND date_format( t1.MONTH, '%Y' ) = t2.YEAR 

這時候我們加上條件，讓年份等於年份，結果卻爲空值，這是爲什麼呢？

不如我們看一下 date_format( t1.MONTH, ‘%Y’ )，這幾個值哪裏有問題，爲什麼不能連接

SELECT
	t1.month,date_format( t1.MONTH, '%Y' ),t2.YEAR 
FROM
	( SELECT DATE_FORMAT( order_time, '%Y-%m' ) AS MONTH, 
	sum( order_num ) AS number FROM `order` 
	GROUP BY MONTH ) t1
	JOIN 
	( SELECT DATE_FORMAT( order_time, '%Y' ) AS YEAR,
	sum( order_num ) AS total FROM `order` 
	GROUP BY YEAR ) t2 
	ON 1 = 1 

所以關鍵是 date_format( t1.MONTH, ‘%Y’ )有問題，

這是因爲在時間格式化成月份之後，再次進行格式化的時候不能識別出這是個時間格式，所以可以進行字符串拼接，根據第一次格式化出來的格式，在月份後面添加上相同格式的日期

例如 date_format( concat( t1.MONTH, ‘-01’ ), ‘%Y’ )就可以了，這樣就可以識別出時間格式了，
正確的語法應爲

SELECT 
	MONTH,
	YEAR,
	number,
	concat( round( number / total * 100.00, 2 ), '%' ) percent 
FROM
	(
SELECT
	* 
FROM
	( SELECT DATE_FORMAT( order_time, '%Y-%m' ) AS MONTH, 
	sum( order_num ) AS number FROM `order` 
	GROUP BY MONTH ) t1
	JOIN 
	( SELECT DATE_FORMAT( order_time, '%Y' ) AS YEAR,
	sum( order_num ) AS total FROM `order` 
	GROUP BY YEAR ) t2 
	ON 1 = 1
	AND date_format( concat( t1.MONTH, '-01' ), '%Y' ) = t2.YEAR 
	) t3;

執行結果如下

此時年份和月份是一一對應的。