i have 1 table called order_star_member, which contain createdAt as the date of the transaction, users_id as the buyer, total_price_star_member as the amount of the transaction. on this case i want to find out buyer who had star member (transaction in a month within >= 600000) and find out where they coming from, the data(dummy) for order_star_member begin on January 2019 untill March 2019
CREATE TABLE order_star_member ( users_id INT,
createdAt DATE,
total_price_star_member DECIMAL(10,2) );
INSERT INTO order_star_member VALUES
(12,'2019-01-01',100000),
(12,'2019-01-10',100000),
(12,'2019-01-20',100000),
(12,'2019-02-10',100000),
(12,'2019-02-15',300000),
(12,'2019-02-21',500000),
(13,'2019-01-02',900000),
(13,'2019-01-11',300000),
(13,'2019-01-18',400000),
(13,'2019-02-06',100000),
(13,'2019-02-08',900000),
(13,'2019-02-14',400000),
(14,'2019-01-21',500000),
(14,'2019-01-23',200000),
(14,'2019-01-24',300000),
(14,'2019-02-08',100000),
(14,'2019-02-09',200000),
(14,'2019-02-14',100000),
(15, '2019-03-04',1000000),
(14, '2019-03-04', 300000),
(14, '2019-03-04', 350000),
(13, '2019-03-04', 400000),
(15, '2019-01-23', 620000),
(15, '2019-02-01', 650000),
(12, '2019-03-03', 750000),
(16, '2019-03-04', 650000),
(17, '2019-03-03', 670000),
(18, '2019-02-02', 450000),
(19, '2019-03-03', 750000);
SELECT * from order_star_member;
and then i summarize data per month
-- summary per-month data
SELECT users_id,
SUM( CASE WHEN MONTHNAME(createdAt) = 'January'
THEN total_price_star_member
END ) total_price_star_member_January,
SUM( CASE WHEN MONTHNAME(createdAt) = 'February'
THEN total_price_star_member
END ) total_price_star_member_February,
SUM( CASE WHEN MONTHNAME(createdAt) = 'March'
THEN total_price_star_member
END ) total_price_star_member_March
FROM order_star_member
GROUP BY users_id
ORDER BY 1;
on this case i want to find out the distribution for each star member (users_id who transaction >= 600000 in a month) in march and where the users_Id doing his transaction >= 600.000 before march (if the users_Id doing transaction on the first time in march, then the users_Id enter the march to march statistic)
expected results for star member on month march statistics
+-------------------+------+-------+
| count star_member | year | month |
+-------------------+------+-------+
| 2 | 2019 | 1 |
| 1 | 2019 | 2 |
| 3 | 2019 | 3 |
+-------------------+------+-------+
explanation : there's 2 users_Id who become star_member on march (users_Id 14,15) and become his first star_member on january 2019, there's 1 users_id who become star_member on march (users_id 12) and become his first star_member on february 2019, and there's 3 users_id who become star_member on march (users_id 16, 17, 19) and become his first star_member on march 2019
this is my progress syntax so far
select count(osm.users_id) as count_buyer, year(osm.createdAt) as year,
month(osm.createdAt) as month
from order_star_member osm
WHERE osm.createdAt >= MAKEDATE(YEAR(osm.createdAt), 1)
+ INTERVAL month(osm.createdAt) month- INTERVAL 1 month AND
osm.createdAt <= MAKEDATE(YEAR(osm.createdAt), 1)
+ INTERVAL month(osm.createdAt) month- INTERVAL 1 day group by users_Id
having sum(total_price_star_member) >= 600000
AND
NOT EXISTS (SELECT 1 from order_star_member osm2
WHERE osm2.users_id = osm.users_id
AND osm2.createdAt < MAKEDATE(YEAR(osm.createdAt), 1) +
INTERVAL month(osm.createdAt) month - INTERVAL 1 month
group by users_id
having sum(total_price_star_member) >= 600000)
AND
EXISTS (SELECT 1 from order_star_member osm3
where
osm3.users_id = osm.users_id AND
osm3.createdAt >= '2019-03-01' AND
osm3.createdAt < '2019-04-01' group by users_id
having sum(total_price_star_member) >= 600000)
group by year(osm.createdAt), month(osm.createdAt);
here's the fiddle https://dbfiddle.uk/?rdbms=mysql_5.7&fiddle=d642774357900f967d7af9659d8639d7
WITH
cte1 AS ( SELECT DISTINCT
users_id,
DATE_FORMAT(createdAt, '%Y%m') year_and_month,
SUM(total_price_star_member) OVER (PARTITION BY users_id, DATE_FORMAT(createdAt, '%Y%m')) month_price
FROM order_star_member ),
cte2 AS ( SELECT users_id, MIN(year_and_month) year_and_month
FROM cte1
WHERE month_price >= 600000
GROUP BY users_id )
SELECT COUNT(users_id) count_star_member,
year_and_month DIV 100 `year`,
year_and_month MOD 100 `month`
FROM cte2
GROUP BY year_and_month
ORDER BY `year`, `month`;
What is your MySQL server version? – Akina
it's 5.7.23-log – Fachry Dzaky Al-Qadri Sabil
SELECT COUNT(users_id) count_star_member,
year_and_month DIV 100 `year`,
year_and_month MOD 100 `month`
FROM (SELECT users_id,
MIN(year_and_month) year_and_month
FROM ( SELECT users_id,
DATE_FORMAT(createdAt, '%Y%m') year_and_month,
SUM(total_price_star_member) month_price
FROM order_star_member
GROUP BY users_id,
DATE_FORMAT(createdAt, '%Y%m')
HAVING month_price >= 600000 ) starrings
GROUP BY users_id ) first_starrings
GROUP BY year_and_month
ORDER BY `year`, `month`;
expected results for star member on month march statistics
...
Hmm... users_id=13 is NOT counted because he is NOT starred in March??? – Akina
yes, because i want to make statistic on month march, and users_id 13 not counted because they not being star member on march (transaction >= 600000) – Fachry Dzaky Al-Qadri Sabil
As I understand the user counted in this statistic MUST be starred in this month. If so
SELECT COUNT(users_id) count_star_member,
year_and_month DIV 100 `year`,
year_and_month MOD 100 `month`
FROM (SELECT users_id,
MIN(year_and_month) year_and_month
FROM ( SELECT users_id,
DATE_FORMAT(createdAt, '%Y%m') year_and_month,
SUM(total_price_star_member) month_price
FROM order_star_member
GROUP BY users_id,
DATE_FORMAT(createdAt, '%Y%m')
HAVING month_price >= 600000 ) starrings
GROUP BY users_id
HAVING SUM(year_and_month = '201903') > 0 ) first_starrings
GROUP BY year_and_month
ORDER BY `year`, `month`;