I'm trying to make the following query work:
SELECT
DATE_FORMAT( date, '%Y %m' ) AS `Month`,
COUNT( schedule_id ) AS `Shifts`,
COUNT(user_id) AS `Users`
FROM
schedule
GROUP BY
`Month`, `Shifts`
It should give a frequency table stating how many users work a certain amount of shifts, per month (e.g. in Dec. there were 10 users working 20 shifts, 12 users working 15 shifts etc).
MySQL can't group on a COUNT() though, so the query breaks. How can I make this work?
Try this:
SELECT
`Month`, `Shifts`, COUNT(`User`) `Users`
FROM (
SELECT -- select nr of shifts per user
DATE_FORMAT( date, '%Y %m' ) AS `Month`,
user_id AS `User`,
COUNT( schedule_id ) AS `Shifts`
FROM
schedule
GROUP BY
`Month`, `User`
) s
GROUP BY `Month`, `Shifts`
Inner query returns month, user and shifts count. In outer query you can group by shifts.
Use subquery to get counts per some idetifier ( column id in example ), then join it with original query
SELECT ... FROM schedule sh JOIN ( SELECT id, COUNT( schedule_id ) AS Shifts FROM schedule ) AS cnt ON cnt.id = sh.id GROUP BY ..., cnt.Shifts
SELECT
y
, m
, Shifts
, COUNT(*) AS Users
FROM
( SELECT
YEAR(date) AS y
, MONTH(date) AS m
, user_id
, COUNT(*) AS Shifts
FROM
schedule
GROUP BY
YEAR(date), MONTH(date), user_id
) AS grp
GROUP BY
y
, m
, Shifts
Related
Could you help me to calculate percent of users, which made payments?
I've got two tables:
activity
user_id login_time
201 01.01.2017
202 01.01.2017
255 04.01.2017
255 05.01.2017
256 05.01.2017
260 15.03.2017
2
payments
user_id payment_date
200 01.01.2017
202 01.01.2017
255 05.01.2017
I try to use this query, but it calculates wrong percent:
SELECT activity.login_time, (select COUNT(distinct payments.user_id)
from payments where payments.payment_time between '2017-01-01' and
'2017-01-05') / COUNT(distinct activity.user_id) * 100
AS percent
FROM payments INNER JOIN activity ON
activity.user_id = payments.user_id and activity.login_time between
'2017-01-01' and '2017-01-05'
GROUP BY activity.login_time;
I need a result
01.01.2017 100 %
02.01.2017 0%
03.01.2017 0%
04.01.2017 0%
05.01.2017 - 50%
If you want the ratio of users who have made payments to those with activity, just summarize each table individually:
select p.cnt / a.cnt
from (select count(distinct user_id) as cnt from activity a) a cross join
(select count(distinct user_id) as cnt from payment) p;
EDIT:
You need a table with all dates in the range. That is the biggest problem.
Then I would recommend:
SELECT d.dte,
( ( SELECT COUNT(DISTINCT p.user_id)
FROM payments p
WHERE p.payment_date >= d.dte and p.payment_date < d.dte + INTERVAL 1 DAY
) /
NULLIF( (SELECT COUNT(DISTINCT a.user_id)
FROM activity a
WHERE a.login_time >= d.dte and p.login_time < d.dte + INTERVAL 1 DAY
), 0
) as ratio
FROM (SELECT date('2017-01-01') dte UNION ALL
SELECT date('2017-01-02') dte UNION ALL
SELECT date('2017-01-03') dte UNION ALL
SELECT date('2017-01-04') dte UNION ALL
SELECT date('2017-01-05') dte
) d;
Notes:
This returns NULL on days where there is no activity. That makes more sense to me than 0.
This uses logic on the dates that works for both dates and date/time values.
The logic for dates can make use of an index, which can be important for this type of query.
I don't recommend using LEFT JOINs. That will multiply the data which can make the query expensive.
First you need a table with all days in the range. Since the range is small you can build an ad hoc derived table using UNION ALL. Then left join the payments and activities. Group by the day and calculate the percentage using the count()s.
SELECT x.day,
concat(CASE count(DISTINCT a.user_id)
WHEN 0 THEN
1
ELSE
count(DISTINCT p.user_id)
/
count(DISTINCT a.user_id)
END
*
100,
'%')
FROM (SELECT cast('2017-01-01' AS date) day
UNION ALL
SELECT cast('2017-01-02' AS date) day
UNION ALL
SELECT cast('2017-01-03' AS date) day
UNION ALL
SELECT cast('2017-01-04' AS date) day
UNION ALL
SELECT cast('2017-01-05' AS date) day) x
LEFT JOIN payments p
ON p.payment_date = x.day
LEFT JOIN activity a
ON a.login_time = x.day
GROUP BY x.day;
I have a food selling website in which there is order table which record the order of every user.It column for user id ,user name,orderid ,timestamp of order.I want to know the maximum number of order that has been made in any one hour span through out the day.Give me any formula for this,or any algorithm or any sql queries for these.
SQL server:
with CTE as
(
select cast(t1.timestamp as date) as o_date, datepart(hh, t1.timestamp) as o_hour, count(*) as orders
from MyTable t1
group by cast(t1.timestamp as date), datepart(hh, t1.timestamp)
)
select o_date, o_hour, orders
from CTE
where orders = (select max(orders) from CTE)
Oracle
with CTE as
(
select to_char(t1.timestamp, 'YYYYMMDD') as o_date, to_char(t1.timestamp, 'HH24') as o_hour, count(*)
from MyTable t1
group by to_char(t1.timestamp, 'YYYYMMDD'), to_char(t1.timestamp, 'HH24')
)
select o_date, o_hour, orders
from CTE
where orders = (select max(orders) from CTE)
You can get count by day and hour like this
For SQL
SELECT TOP 1
COUNT(*)
FROM myTable
GROUP BY DATEPART(day, [column_date]), DATEPART(hour, [column_date])
ORDER BY COUNT(*) DESC;
For MySQL
SELECT
COUNT(*)
FROM myTable
GROUP BY HOUR(column_date), DAY(column_date)
ORDER BY COUNT(*) DESC
LIMIT 1;
Consider this sql:
SELECT DATE_FORMAT( Orders.Timestamp, '%Y%m' ) AS Period,
SUM(Price) AS 'Ordersum per month and organisation', Orders.Organisation,
(
SELECT SUM(Amount) AS Returns
FROM Returns
WHERE DATE_FORMAT( Returns.Timestamp, '%Y%m' ) = Period
AND Returns.Organisation = Orders.Organisation
) Returns
FROM Orders
GROUP BY Period, Organisation
Whenever there are rows in the subquery that doesn't have an equivalent period in the main query, the row isn't displayed. The reason is that the query takes its period from the orders table, and when the period of the subquery doesn't match a period in the orders table, it simply doesn't match the query.
Is there a way to reformat this query to achieve what I want?
Sqlfiddle here http://sqlfiddle.com/#!9/ace715/1
You can use left and right join with UNION like this:
SELECT
ifnull(DATE_FORMAT( Orders.Timestamp,'%Y%m' ),DATE_FORMAT(Returns.Timestamp,'%Y%m' )) AS Period,
SUM(Price) AS 'Ordersum per month and organisation',
ifnull(Orders.Organisation,Returns.Organisation) as 'Organisation',
SUM(Amount) AS 'Returns'
FROM Orders
left JOIN Returns
on DATE_FORMAT( Orders.Timestamp,'%Y%m' ) = DATE_FORMAT(Returns.Timestamp, '%Y%m' )
and Returns.Organisation = Orders.Organisation
GROUP BY Period, Returns.Organisation, Orders.Organisation
union
select ifnull(DATE_FORMAT( Orders.Timestamp, '%Y%m' ),DATE_FORMAT(Returns.Timestamp,'%Y%m' )) AS Period,
SUM(Price) AS 'Ordersum per month and organisation',
ifnull(Orders.Organisation,Returns.Organisation),
SUM(Amount) AS 'Returns'
FROM Orders
right JOIN Returns
on DATE_FORMAT( Orders.Timestamp, '%Y%m' ) = DATE_FORMAT(Returns.Timestamp, '%Y%m' )
and Returns.Organisation = Orders.Organisation
GROUP BY Period, Returns.Organisation, Orders.Organisation
I need to get a table that contains the most popular product sold per day. All data is stored in Magento, and I use MySQL to write the query. The only table I need is Sales_flat_order_item table.
The final table should have 3 columns: Date, Product SKU, and number of units sold of the most popular product that day - MaxQty.
I came up with the query that works for me, but I would like to know how it can be improved since I use the same subquery twice in my code:
1 Select Date, Product Id, Sku, and Quantity from sales_flat_order_item - Subquery1
2 Select Date and Maximum Quantity from Subquery1 - Subquery2
3 Join them together knowing that dates should be the same, and Quantity from Subquery1 should be equal to Maximum Quantity from Subquery2
SELECT DATE( sq2.created_at ) AS CreatedAt, sq0.sku AS SKU, sq2.MaxQty
FROM (
SELECT created_at, product_id, sku, SUM( qty_ordered ) AS qty
FROM `sales_flat_order_item`
GROUP BY DATE( created_at ) , product_id
) AS sq0
JOIN (
SELECT sq.created_at, MAX( sq.qty ) AS MaxQty
FROM (
SELECT created_at, product_id, SUM( qty_ordered ) AS qty
FROM `sales_flat_order_item`
GROUP BY DATE( created_at ) , product_id
) AS sq
GROUP BY DATE( sq.created_at )
) AS sq2 ON DATE( sq2.created_at ) = DATE( sq0.created_at )
AND sq2.MaxQty = sq0.qty
GROUP BY DATE( CreatedAt )
I believe this should do what you want.
I added a WHERE clause to run it only for this month, in case you have a huge database so it should not take much time.
SELECT day, sku, MAX(qty_total) AS qty FROM (
SELECT DATE(created_at) AS day, sku, SUM(qty_ordered) AS qty_total
FROM `sales_flat_order_item`
WHERE created_at > '2015-07%'
GROUP BY sku, day
ORDER BY qty_total DESC
) AS item_count
GROUP BY day
I have such a schema and queries:
http://sqlfiddle.com/#!2/7b032/3
Seperately I have these queries:
SELECT COUNT(*) AS 'times', userid, name
FROM main
WHERE comedate <= DATE_SUB(CURDATE(),
INTERVAL 5 DAY)
GROUP BY userid ORDER BY times DESC LIMIT 0,2;
SELECT * FROM details WHERE 1;
By comparing userid columns of both table I need to join them.
I need an output having these columns:
"times, userid, name, age, location"
Also order, group and limits should be considered.
I would be happy if you can write one query with JOIN and one query with subquery.
I have a 60k table and I will compare the performances.
How about this:
select x.times,
x.userid,
x.name,
d.age,
d.location
from
(
SELECT COUNT(*) AS 'times', userid, name
FROM main
WHERE comedate <= DATE_SUB(CURDATE(),
INTERVAL 5 DAY)
GROUP BY userid
) x
left join details d
on x.userid = d.userid
see SQL Fiddle with Demo
edit:
select x.times,
x.userid,
x.name,
d.age,
d.location
from
(
SELECT COUNT(*) AS 'times', userid, name
FROM main
WHERE comedate <= DATE_SUB(CURDATE(),
INTERVAL 5 DAY)
GROUP BY userid
ORDER BY times DESC
LIMIT 0,2
) x
left join details d
on x.userid = d.userid
see SQL Fiddle with demo