I need to grab the # of settled and unsettled orders by month. Here is what I have so far:
SELECT
CONCAT(MONTH(time_settle), "/", YEAR(time_settle)) as month_settled, count(*) as settled
FROM payment_order
WHERE time_settle IS NOT NULL
AND datediff(time_settle,NOW())>-90
AND datediff(time_settle,NOW())<+90
AND account_id=28 AND current_state !="deleted"
GROUP BY MONTH(time_settle);
The result is:
month_settled | settled
-------------------------
6/2014 | 1
9/2014 | 10
12/2014 | 1
And unsettled I use time_due:
SELECT
CONCAT(MONTH(time_due), "/", YEAR(time_due)) as month_due, count(*) as unsettled
FROM payment_order
WHERE time_settle IS NULL
AND datediff(time_due,NOW())>-90
AND datediff(time_due,NOW())<+90
AND account_id=28
AND current_state !="deleted"
GROUP BY MONTH(time_due);
The result is:
month_due | unsettled
-------------------------
8/2014 | 1
9/2014 | 8
10/2014 | 2
I need a result that looks something like this:
month | settled | unsettled | total
----------------------------------------------
6/2014 | 1 | 0 | 1
8/2014 | 0 | 1 | 1
9/2014 | 10 | 8 | 18
10/2014 | 0 | 2 | 2
12/2014 | 1 | 0 | 1
Any ideas? How can I do a group by months if my sum criteria are two different months? I need the settled transactions to be grouped by time_settle and the unsettled transactions to be grouped by time_due.
Ok try this
SELECT t.month,
coalesce(t1.settled, 0) as settled,
coalesce(t2.unsettled, 0) as unsettled,
coalesce(t1.settled, 0) + coalesce(t2.unsettled, 0) as total
FROM
( SELECT CONCAT(MONTH(a.t_month), "/", YEAR(a.t_month)) as month
FROM
( SELECT COALESCE(time_settle, time_due) as t_month
FROM payment_order
)a
WHERE datediff(a.t_month,NOW())>-90 AND datediff(a.t_month,NOW())<+90
GROUP BY month
)t
LEFT JOIN(SELECT CONCAT(MONTH(time_settle), "/", YEAR(time_settle)) as month_settled, count(*) as settled FROM payment_order WHERE time_settle IS NOT NULL AND datediff(time_settle,NOW())>-90 AND datediff(time_settle,NOW())<+90 AND account_id=28 AND current_state !="deleted" GROUP BY EXTRACT(YEAR_MONTH FROM time_settle)) t1
on t1.month_settled = t.month
LEFT JOIN(SELECT CONCAT(MONTH(time_due), "/", YEAR(time_due)) as month_due, count(*) as unsettled FROM payment_order WHERE time_settle IS NULL AND account_id=28 AND current_state !="deleted" GROUP BY EXTRACT(YEAR_MONTH FROM time_due)) t2
on t2.month_due = t.month;
DEMO
Related
I have a MySQL table like this;
recordID| netcall | sign | activity | netid
1 | group1 | wa1 | 1 | 20
2 | group2 | wa2 | 2 | 30
3 | group1 | wa2 | 1 | 20
4 | group2 | wa3 | 2 | 30
5 | group1 | wa1 | 1 | 40
6 | group3 | wa4 | 3 | 50
7 | group3 | wa4 | 3 | 50
8 | group1 | wa2 | 1 | 40
9 | group1 | wa1 | 1 | 40
10 | group2 | wa4 | 2 | 60
What I need from that is:
Netcall | count | activity | netid
Group1 | 3 | 1 | 40
Group2 | 2 | 2 | 30
Group3 | 2 | 3 | 50
I thought I could;
SELECT MAX(xx.mycount) AS MAXcount
FROM (SELECT COUNT(tt.sign) AS mycount ,tt.activity
FROM NetLog tt
WHERE ID <> 0
GROUP BY netcall) xx
But this only brings up the grand total not broken down by netcall. I don't see an example of this question but I'm sure there is one, I'm just asking it wrong.
Your example and desire output are too basic, you should try to expand so include more cases.
Right now you can get the desire output with:
SELECT `netcall`, COUNT(*) as `total`, MAX(`activity`) as `activity`
FROM t
GROUP BY `netcall`;
My guess is you can have different activities for group so you need multiples steps
Calculate the COUNT() for GROUP BY netcall, activity I call it q
Then see what is the MAX(total) for each netcall I call it p
Now you reuse q as o you have all the count, so just select the one with the max count.
SQL DEMO
SELECT o.`netcall`, o.total, o.`activity`
FROM (
SELECT `netcall`, COUNT(*) `total`, `activity`
FROM t
GROUP BY `netcall`, `activity`
) o
JOIN (
SELECT `netcall`, MAX(`total`) as `total`
FROM (
SELECT `netcall`, COUNT(*) `total`
FROM t
GROUP BY `netcall`, `activity`
) q
GROUP BY `netcall`
) p
ON o.`netcall` = p.`netcall`
AND o.`total` = p.`total`
With MySQL v8+ you can use cte and window function to simplify a little bit
with group_count as (
SELECT `netcall`, COUNT(*) as total, `activity`
FROM t
GROUP BY `netcall`, `activity`
), group_sort as (
SELECT `netcall`, total, `activity`,
RANK() OVER (PARTITION BY `netcall`, `activity` ORDER BY total DESC) as rnk
FROM group_count
)
SELECT *
FROM group_sort
WHERE rnk = 1
This question is asked (and answered) every day on SO; it even has its own chapter in the MySQL manual, but anyway...
SELECT a.netcall
, b.total
, a.activity
FROM netlog a
JOIN
( SELECT netcall
, MAX(record_id) record_id
, COUNT(*) total
FROM netlog
GROUP
BY netcall
) b
ON b.netcall = a.netcall
AND b.record_id = a.record_id
SELECT k.netcall, k.netID, MAX(k.logins) highest,
AVG(k.logins) average, netDate, activity
FROM
(SELECT netID, netcall, COUNT(*) logins, DATE(`logdate`) as netDate, activity
FROM NetLog
WHERE netID <> 0 AND status = 1
AND netcall <> '0' AND netcall <> ''
GROUP BY netcall, netID) k
GROUP BY netcall
ORDER BY highest DESC
Resulted in:
Net Call Highest Average Net ID Sub Net Of... ICS
214 309 Map Date Activity
MESN 65 41.5294 339 214 309 MAP 2017-09-03 MESN
W0KCN 34 14.9597 1 214 309 MAP 2016-03-15 KCNARES Weekly 2m Voice Net
W0ERH 31 31.0000 883 214 309 MAP 2018-10-12 Johnson Co. Radio Amateurs Club Meeting Net
KCABARC 29 22.3333 57 214 309 MAP 2016-10-10 KCA Blind Amateurs Weekly 2m Voice Net
....
I want to calculate the division of each row per the sum of all rows that have the same Dateadded and fundid, but it seems my query is wrong due the results is not what I was expecting.
My table schema looks like this, I avoided mine because it has many more columns:
+----+--------+------------+--------+
| id | fundid | Dateadded | amount |
+====+========+============+========+
| 1 | 45 | 21-02-2018 | 5412 |
| 2 | 45 | 21-02-2018 | 5414 |
| 3 | 45 | 21-02-2018 | 1412 |
| 4 | 45 | 22-02-2018 | 5756 |
| 5 | 45 | 22-02-2018 | 4412 |
| 6 | 45 | 25-02-2018 | 2532 |
| 7 | 45 | 26-02-2018 | 7892 |
| 8 | 45 | 26-02-2018 | 8143 |
+----+-------+-------------+--------+
Rows with id's: 1,2,3 should be calculated together because they have
the same fundid and date.
Rows with id's: 4,5 same thing.
Rows with id's: 6 it is just one.
Rows with id's: 7,8 same thing.
My SQL query:
SELECT fundid
, Dateadded
, ( amount / SUM(amount) ) AS AvgRow
FROM stock2
GROUP
BY fundid
, Dateadded
ORDER
BY DateAdded ASC
Is this what you want?
select t.*, t.amount / tt.total_amount
from stock2 t join
(select fundid, dateadded, sum(amount) as total_amount
from stock2 t
group by fundid, dateadded
) tt
using (fundid, dateadded);
Or is this?
select fundid, dateadded, sum(t.amount) / tt.total_amount
from stock2 t cross join
(select sum(amount) as total_amount
from stock2 t
) tt
group by fundid, dateadded, tt.total_amount;
Check out a very well explained response to a similar issue related to usage of Group by here).
Similarly to the situation described there, for your query is ambiguous re: what "amount" should be used for each row. I.e. if you try:
SELECT fundid, Dateadded, ( AVG(amount) / SUM(amount) ) AS AvgRow FROM stock2 GROUP BY fundid, Dateadded ORDER BY DateAdded ASC
it will work because AVG(amount) is non-ambiguous for each (fundid, Dateadded) pair that should be calculated together.
It seems you are looking for something like:
SELECT st.fundid, st.Dateadded, ( amount / st2.total) ) AS AvgRow
FROM stock2 st
inner join
(select fundid, Dateadded, sum(amount) as total
from stock2
GROUP BY fundid, Dateadded) st2
on st.fundid = st2.fundid and st.Dateadded = st2.Dateadded
order by st.Dateadded
I have a table look like below....
ID HID Date UID
1 1 2012-01-01 1002
2 1 2012-01-24 2005
3 1 2012-02-15 5152
4 2 2012-01-01 6252
5 2 2012-01-19 10356
6 3 2013-01-06 10989
7 3 2013-03-25 25001
8 3 2014-01-14 35798
How can i group by HID, Year, Month and count(UID) and add a cumulative_sum (which is count of UID). So the final result look like this...
HID Year Month Count cumulative_sum
1 2012 01 2 2
1 2012 02 1 3
2 2012 01 2 2
3 2013 01 1 1
3 2013 03 1 2
3 2014 01 1 3
What's the best way to accomplish this using query?
I made assumptions about the original data set. You should be able to adapt this to the revised dataset - although note that the solution using variables (instead of my self-join) is faster...
DROP TABLE IF EXISTS my_table;
CREATE TABLE my_table
(ID INT NOT NULL
,Date DATE NOT NULL
,UID INT NOT NULL PRIMARY KEY
);
INSERT INTO my_table VALUES
(1 ,'2012-01-01', 1002),
(1 ,'2012-01-24', 2005),
(1 ,'2012-02-15', 5152),
(2 ,'2012-01-01', 6252),
(2 ,'2012-01-19', 10356),
(3 ,'2013-01-06', 10989),
(3 ,'2013-03-25', 25001),
(3 ,'2014-01-14', 35798);
SELECT a.*
, SUM(b.count) cumulative
FROM
(
SELECT x.id,YEAR(date) year,MONTH(date) month, COUNT(0) count FROM my_table x GROUP BY id,year,month
) a
JOIN
(
SELECT x.id,YEAR(date) year,MONTH(date) month, COUNT(0) count FROM my_table x GROUP BY id,year,month
) b
ON b.id = a.id AND (b.year < a.year OR (b.year = a.year AND b.month <= a.month)
)
GROUP
BY a.id, a.year,a.month;
+----+------+-------+-------+------------+
| id | year | month | count | cumulative |
+----+------+-------+-------+------------+
| 1 | 2012 | 1 | 2 | 2 |
| 1 | 2012 | 2 | 1 | 3 |
| 2 | 2012 | 1 | 2 | 2 |
| 3 | 2013 | 1 | 1 | 1 |
| 3 | 2013 | 3 | 1 | 2 |
| 3 | 2014 | 1 | 1 | 3 |
+----+------+-------+-------+------------+
If you don't mind an extra column in the result, you can simplify (and accelerate) the above, as follows:
SELECT x.*
, #running:= IF(#previous=x.id,#running,0)+x.count cumulative
, #previous:=x.id
FROM
( SELECT x.id,YEAR(date) year,MONTH(date) month, COUNT(0) count FROM my_table x GROUP BY id,year,month ) x
,( SELECT #cumulative := 0,#running:=0) vals;
The code turns out kind of messy, and it reads as follows:
SELECT
HID,
strftime('%Y', `Date`) AS Year,
strftime('%m', `Date`) AS Month,
COUNT(UID) AS Count,
(SELECT
COUNT(UID)
FROM your_db A
WHERE
A.HID=B.HID
AND
(strftime('%Y', A.`Date`) < strftime('%Y', B.`Date`)
OR
(strftime('%Y', A.`Date`) = strftime('%Y', B.`Date`)
AND
strftime('%m', A.`Date`) <= strftime('%m', B.`Date`)))) AS cumulative_count
FROM your_db B
GROUP BY HID, YEAR, MONTH
Though by using views, it should become much clearer:
CREATE VIEW temp_data AS SELECT
HID,
strftime('%Y', `Date`) as Year,
strftime('%m', `Date`) as Month,
COUNT(UID) as Count
FROM your_db GROUP BY HID, YEAR, MONTH;
Then your statement will read as follows:
SELECT
HID,
Year,
Month,
`Count`,
(SELECT SUM(`Count`)
FROM temp_data A
WHERE
A.HID = B.HID
AND
(A.Year < B.Year
OR
(A.Year = B.Year
AND
A.Month <= B.Month))) AS cumulative_sum
FROM temp_data B;
I have such query that gives me results about bestseller items from shops, at the moment it works fine, but now I want to get only one product from each shop so to have a distinct si.shop_id only one bestseller product from a shop
SELECT `si`.`id`, si.shop_id,
(SELECT COUNT(*)
FROM `transaction_item` AS `tis`
JOIN `transaction` as `t`
ON `t`.`id` = `tis`.`transaction_id`
WHERE `tis`.`shop_item_id` = `si`.`id`
AND `t`.`added_date` >= '2014-02-26 00:00:00')
AS `count`
FROM `shop_item` AS `si`
INNER JOIN `transaction_item` AS `ti`
ON ti.shop_item_id = si.id
GROUP BY `si`.`id`
ORDER BY `count` DESC LIMIT 7
and that gives mu a result like:
+--------+---------+-------+
| id | shop_id | count |
+--------+---------+-------+
| 425030 | 38027 | 111 |
| 291974 | 5368 | 20 |
| 425033 | 38027 | 18 |
| 291975 | 5368 | 12 |
| 142776 | 5368 | 10 |
| 397016 | 38027 | 9 |
| 291881 | 5368 | 8 |
+--------+---------+-------+
any ideas?
EDIT
so I created a fiddle for it
http://sqlfiddle.com/#!2/cfc4c/1
Now the query returns best selling products I want it to return only one product from shopso the result of fiddle should be
+----+---------+-------+
| ID | SHOP_ID | COUNT |
+----+---------+-------+
| 1 | 222 | 3 |
| 4 | 333 | 2 |
| 8 | 555 | 1 |
| 9 | 777 | 1 |
+----+---------+-------+
Possibly something like this:-
SELECT si.shop_id,
SUBSTRING_INDEX(GROUP_CONCAT(CONCAT_WS(':', si.id, sub1.item_count) ORDER BY sub1.item_count DESC), ',', 1) AS `count`
FROM shop_item AS si
INNER JOIN
(
SELECT tis.shop_item_id, COUNT(*) AS item_count
FROM transaction_item AS tis
JOIN `transaction` as t
ON t.id = tis.transaction_id
AND t.added_date >= '2014-02-26 00:00:00'
GROUP BY tis.shop_item_id
) sub1
ON sub1.shop_item_id = si.id
GROUP BY si.shop_id
ORDER BY `count` DESC LIMIT 7
The sub query gets the count of items for each shop. Then the main query concatenates the item id and the item count together, group concatenates all those for a single shop together (ordered by the count descending) and then uses SUBSTRING_INDEX to grab the first one (ie, everything before the first comma).
You will have to split up the count field to get the item id and count separately (the separator is a : ).
This is taking a few guesses about what you really want, and with no table declares or data it isn't tested.
EDIT - now tested with the SQL fiddle example:-
SELECT SUBSTRING_INDEX(`count`, ':', 1) AS ID,
shop_id,
SUBSTRING_INDEX(`count`, ':', -1) AS `count`
FROM
(
SELECT si.shop_id,
SUBSTRING_INDEX(GROUP_CONCAT(CONCAT_WS(':', si.id, sub1.item_count) ORDER BY sub1.item_count DESC), ',', 1) AS `count`
FROM shop_item AS si
INNER JOIN transaction_item AS ti
ON ti.shop_item_id = si.id
INNER JOIN
(
SELECT tis.shop_item_id, COUNT(*) AS item_count
FROM transaction_item AS tis
JOIN `transaction` as t
ON t.id = tis.transaction_id
AND t.added_date >= '2014-02-26 00:00:00'
GROUP BY tis.shop_item_id
) sub1
ON sub1.shop_item_id = si.id
GROUP BY si.shop_id
) sub2
ORDER BY `count` DESC LIMIT 7;
I have two tables
user_raters:
| id(int) | to_id(int) | value(int) | created_at(datetime)
|1 | 2 | 1 | 2009-03-01 00:00:00
EDIT: I changed the user_rater_id. history_user_raters.user_rater_id is related to user_raters.id
history_user_raters:
| id(int) | user_rater_id(int) | value(int) | created_at(datetime)
| 1 | 1 | 1 | 2009-03-02 00:00:00
| 2 | 1 | 1 | 2009-03-02 00:00:00
| 3 | 1 | -1 | 2009-03-02 00:00:00
| 4 | 1 | 1 | 2009-03-03 00:00:00
| 5 | 1 | -1 | 2009-03-03 00:00:00
| 6 | 1 | -1 | 2009-03-03 00:00:00
| 7 | 1 | -1 | 2009-03-03 00:00:00
I want to count the sum of the values from history_user_raters as it relates to the to_id from user_raters. The result from the query should be:
| year | month | day | total | down | up
| 2009 | 3 | 2 | 1 | 1 | 2
| 2009 | 3 | 3 | -2 | 3 | 1
I have a query that is close, but it is not counting the up and down correctly. The total is right. Can some one help me write the query or new query that calculates correct up and down?
My current query:
SELECT
YEAR(history.created_at) AS `year`,
MONTH(history.created_at) AS `month`,
DAY(history.created_at) AS `day`,
SUM(history.value) as `total`,
(SELECT
abs(SUM(historydown.value))
FROM `user_raters` as raterdown
INNER JOIN `history_user_raters` AS historydown
WHERE raterdown.to_id = 2
AND historydown.value = -1
AND date(historydown.created_at)
GROUP BY history.created_at) as down,
(SELECT SUM(historyup.value)
FROM `user_raters` as raterup
INNER JOIN `history_user_raters` AS historyup
WHERE raterup.to_id = 2
AND historyup.value = 1
AND date(history.created_at)
GROUP BY raterup.to_id) as up
FROM `user_raters`
INNER JOIN history_user_raters AS history ON user_raters.id = history.user_rater_id
WHERE (user_raters.to_id = 2)
GROUP BY DATE(history.created_at)
I might see it too simply (and sorry I can't test with data at the moment), but I'm guessing the following trick with two CASE statements would do just what is needed
SELECT
YEAR(history.created_at) AS year,
MONTH(history.created_at) AS month,
DAY(history.created_at) AS day,
SUM(history.value) as total,
SUM(CASE WHEN history.value < 0 THEN history.value ELSE 0 END) as down,
SUM(CASE WHEN history.value > 0 THEN history.value ELSE 0 END) as up
FROM `user_raters`
INNER JOIN `history_user_raters` AS history
ON user_raters.id = history.user_rater_id
WHERE (user_raters.to_id = 1) -- or some other condition...
GROUP BY DATE(history.created_at)
EDIT: #OMG Ponies deleted his answer. This response make no sense now, but I am not going to delete my answer, because I think it is silly.
#OMG ponies
Your query runs, but it returns no results. I had to adjust it a bit to add the to_id in the main queries where clause
SELECT
YEAR( t.created_at ) AS `year` ,
MONTH( t.created_at ) AS `month` ,
DAY( t.created_at ) AS `day` ,
SUM( t.value ) AS `total` ,
MAX( COALESCE( x.sum_down, 0 ) ) AS down,
MAX( COALESCE( y.sum_up, 0 ) ) AS up
FROM history_user_raters AS t
JOIN user_raters AS ur ON ur.to_id = t.user_rater_id
LEFT JOIN (
SELECT hur.user_rater_id,
SUM( hur.value ) AS sum_down
FROM history_user_raters AS hur
WHERE hur.value = -1
GROUP BY hur.user_rater_id
) AS x ON x.user_rater_id = t.user_rater_id
LEFT JOIN (
SELECT hur.user_rater_id,
SUM( hur.value ) AS sum_up
FROM history_user_raters AS hur
WHERE hur.value =1
GROUP BY hur.user_rater_id
) AS y ON y.user_rater_id = t.user_rater_id
WHERE ur.to_id =1
GROUP BY YEAR( t.created_at ) , MONTH( t.created_at ) , DAY( t.created_at )