Related
this is my starting table which provides sales information by Id.
Id
Store_Name
Market
Sales
Main_Product
1
StoreA
Rome
10
a
2
StoreB
Rome
15
b
3
StoreC
Rome
9
c
4
Mag1
Paris
10
a
5
Mag2
Paris
23
b
6
Mag3
Paris
12
c
7
Shop1
London
11
a
8
Shop2
London
31
b
9
Shop3
London
45
c
10
Shop4
London
63
d
In order to build a report and create some dynamic sentences, I will need the dataset to be "paginated" as per below table:
Id
Dimension
Dimension_Name
Sales
Main_Product
1
ShoppingCentre
StoreA
10
a
1
Market
Rome
34
a
2
ShoppingCentre
StoreB
15
b
2
Maket
Rome
34
b
3
ShoppingCentre
StoreC
9
c
3
Market
Rome
34
c
Do you have any tip about how to build the last table starting from the first one?
To sum-up:
The new table will be always by Id
Aggregation of market sales happens at row level where every single shopping centre is located
This is the query that I have built so far but wondering if there is a better and more efficient way to accomplish the same:
with store_temp_table as (
select
id
,Store_Name
,Market
, Main_Product
, sum(Sales) as Sales
from Production_Table
where 1=1
group by
1,2,3,4
)
, market_temp_table as (
select
market
, sum(Sales) as Sales
from Production_Table
where 1=1
group by
1
)
, store_temp_table_refined as(
Select
a.id
,a.Main_Product
, 'ShoppingCentre' as Dimension_Name
,SUM(a.Sales) as Sales
FROM store_temp_table a INNER JOIN
market_temp_table b on a.market = b.market
group by
1,2,3
)
, market_temp_table_refined as (
Select
a.id
,a.Main_Product
, 'Market' as DimensionName
,SUM(b.Sales) as Sales
FROM store_temp_table a INNER JOIN
market_temp_table b on a.market = b.market
group by
1,2,3
)
select * from store_temp_table_refined
union all
select * from market_temp_table_refined
Thank you
Use a CTE that returns the dimensions that you want and cross join it to a query that returns the columns of the table and an additional column with the total sales of each market:
WITH Dimensions(id, Dimension) AS (VALUES
ROW(1, 'ShoppingCentre'),
ROW(2, 'Market')
)
SELECT p.Id,
d.Dimension,
CASE d.id WHEN 1 THEN p.Store_Name ELSE p.Market END Dimension_Name,
CASE d.id WHEN 1 THEN p.Sales ELSE p.MarketSales END Sales,
p.Main_Product
FROM Dimensions d
CROSS JOIN (SELECT *, SUM(Sales) OVER (PARTITION BY Market) AS MarketSales FROM Production_Table) p
ORDER BY p.id, d.id;
Or, with UNION ALL:
SELECT Id,
'ShoppingCentre' Dimension,
Store_Name Dimension_Name,
Sales,
Main_Product
FROM Production_Table
UNION ALL
SELECT Id,
'Market',
Market,
SUM(Sales) OVER (PARTITION BY Market),
Main_Product
FROM Production_Table
ORDER BY Id,
CASE Dimension WHEN 'ShoppingCentre' THEN 1 WHEN 'Market' THEN 2 END;
See the demo.
I'm trying to get data that have the same medicine_id and unique insurance_id and last inserted row. Put Group by and Order by but in that got random data not last inserted.
I tried this code but got not last inserted data
SELECT
`m1`.`*`
FROM
(
`pricings` `m1`
LEFT JOIN `pricings` `m2` ON
(
(
(
`m1`.`medicine_id` = `m2`.`medicine_id`
)
)
)
)
WHERE m1.medicine_id = 2
group BY m1.insurance_id DESC
ORDER BY m1.created_at;
Here are the total rows.
This is a full table
id
medicine_id
insurance_id
created_at
4311
2
1
2021-04-12 16:05:07
4766
2
1
2022-01-15 11:56:06
4767
2
38
2021-05-12 08:17:11
7177
2
38
2022-03-30 10:14:11
4313
2
39
2021-04-12 16:05:46
4768
2
39
2021-05-12 08:17:30
1356
2
40
2020-11-02 11:25:43
3764
2
40
2021-03-08 15:42:16
4769
2
40
2021-05-12 08:17:44
And I want to like this
id
medicine_id
insurance_id
created_at
4766
2
1
2022-01-15 11:56:06
4768
2
39
2021-05-12 08:17:30
4769
2
40
2021-05-12 08:17:44
7177
2
38
2022-03-30 10:14:11
MySQL 5.x: Use a sub-query to find the max created_at value per group, then join that on the source table to identify the row it was from.
SELECT
p.`*`
FROM
`pricings` p
INNER JOIN
(
SELECT
`medicine_id`,
`insurance_id`,
MAX(created_at) AS `created_at`
FROM
`pricings`
GROUP BY
`medicine_id`,
`insurance_id`
)
p_max
ON p.`medicine_id` = p_max.`medicine_id`
AND p.`insurance_id` = p_max.`insurance_id`
AND p.`created_at` = p_max.`created_at`
WHERE
p.`medicine_id` = 2
ORDER BY
p.`created_at`;
MySQL 8: Use ROW_NUMBER() to enumerate each group, then pick the first row from each group.
SELECT
p.`*`
FROM
`pricings` p
FROM
(
SELECT
*,
ROW_NUMBER() OVER (
PARTITION BY `medicine_id`,
`insurance_id`
ORDER BY `created_at` DESC
)
AS `row_id`
FROM
`pricings`
)
p
WHERE
p.`medicine_id` = 2
AND p.`row_id` = 1
ORDER BY
p.`created_at`;
Adding it as an answer as well. I have not tested it, just fix the formating to work with whatever version of databse you are working with and let me know of the results.
SELECT m1.id , m1.Insurance_id , m1.medicine_id , max(m1,created_at)
FROM (
`pricings` `m1` LEFT JOIN `pricings` `m2` ON `m1`.`medicine_id` = `m2`.`medicine_id`
)
WHERE m1.medicine_id = 2 and m1.insurance_id in (1,39,40,38)
GROUP BY m1.insurance_id DESC
ORDER BY m1.created_at;
Edit. I also removed the 6 extra parenthesis, I don't see how they could be of any use
I have 2 queries where I group by week, by quarter and year using added_on, the problem comes in when I try to combine the queries since the first query weeks are from 1,2,3,4,5,....,25, it has transactions in every week of the year and the second query is 1,4,5,8,15,25 because it does not have transactions on some weeks and I need for both to have 1,2,3,4,5,6,7,...,25 is there any way to achieve this?
transaction table
id
value
added_on
currency_id
1
100
2020/01/20
2
320
2020/2/10
currency table
id
type
1
USD
2
EUR
My query is looking like this
SELECT
week_usd,
week_eur,
total_usd,
total_eur,
quarter_year
FROM
(SELECT
WEEK(transaction.added_on) AS week_usd,
SUM(transaction.value) AS total_usd,
CONCAT(QUARTER(transaction.added_on)," ", YEAR(transaction.added_on)) AS quarter_year
FROM transaction
JOIN currency ON transaction.currency_id = currency.id
WHERE
currency.type = 'USD'
GROUP BY 1,3
) AS table1,
(SELECT
WEEK(transaction.added_on) AS week_eur,
SUM(transaction.value) AS total_eur,
CONCAT(QUARTER(transaction.added_on)," ", YEAR(transaction.added_on)) AS quarter_year
FROM transaction
JOIN currency ON transaction.currency_id = currency.id
WHERE
currency.type = 'EUR'
GROUP BY 1,3
) AS table2
The problem with my query is that it will display like this
week_usd
week_eur
total_usd
total_eur
quarter_year
0
1
100
150
1 2020
1
1
100
150
1 2020
2
1
100
150
1 2020
3
1
100
150
1 2020
4
1
100
150
1 2020
5
1
100
150
1 2020
6
1
100
150
1 2020
7
1
100
150
1 2020
8
1
100
150
1 2020
You need first to create unique list of dates before getting joins of totals:
Select date_list.quarter_year
, date_list.week
, USD.total_usd
, EUR.total_eur
from
( select distinct CONCAT(QUARTER(transaction.added_on)," ", YEAR(transaction.added_on)) AS quarter_year
, WEEK(transaction.added_on) week
from transaction
) as date_list
Left Join (
select CONCAT(QUARTER(transaction.added_on)," ", YEAR(transaction.added_on)) AS quarter_year
, WEEK(transaction.added_on) week
, SUM(transaction.value) AS total_usd
from transaction
join currency on transaction.currency_id = currency.id
where currency.type = 'USD'
group by 1,2
) as USD on date_list.quarter_year = USD.quarter_year and date_list.week = USD.week
Left Join (
select CONCAT(QUARTER(transaction.added_on)," ", YEAR(transaction.added_on)) AS quarter_year
, WEEK(transaction.added_on) week
, SUM(transaction.value) AS total_eur
from transaction
join currency on transaction.currency_id = currency.id
where currency.type = 'EUR'
group by 1,2
) as EUR on date_list.quarter_year = EUR.quarter_year and date_list.week = EUR.week ;
I'm currently stuck on how to create a statement that shows daily overdraft statements for a particular council.
I have the following, councils, users, markets, market_transactions, user_deposits.
market_transaction run daily reducing user's account balance. When the account_balance is 0 the users go into overdraft (negative). When users make a deposit their account balance increases.
I Have put the following tables to show how transactions and deposits are stored.
if I reverse today's transactions I'm able to get what account balance a user had yesterday but to formulate a query to get the daily OD amount is where the problem is.
USERS
user_id
name
account_bal
1
Wells
-5
2
James
100
3
Joy
10
4
Mumbi
-300
DEPOSITS
id
user_id
amount
date
1
1
5
2021-04-26
2
3
10
2021-04-26
3
3
5
2021-04-25
4
4
5
2021-04-25
TRANSACTIONS
id
user_id
amount_tendered
date
1
1
5
2021-04-27
2
2
10
2021-04-26
3
3
15
2021-04-26
4
4
50
2021-04-25
The Relationships are as follows,
COUNCILS
council_id
name
1
a
2
b
3
c
MARKETS
market_id
name
council_id
1
x
3
2
y
1
3
z
2
MARTKET_USER_LINK
id
market_id
user_id
1
1
3
2
2
2
3
3
1
I'm running this SQL query to get the total amount users have spent and subtracting with the current user account balance.
Don't know If I can use this to figure out the account_balance for each day.
SELECT u.user_id, total_spent, total_deposits,m.council_id
FROM users u
JOIN market_user_link ul ON ul.user_id= u.user_id
LEFT JOIN markets m ON ul.market_id =m.market_id
LEFT JOIN councils c ON m.council_id =c.council_id
LEFT JOIN (
SELECT user_id, SUM(amount_tendered) AS total_spent
FROM transactions
WHERE DATE(date) BETWEEN DATE('2021-02-01') AND DATE(NOW())
GROUP BY user_id
) t ON t.user_id= u.user_id
ORDER BY user_id, total_spent ASC
// looks like this when run
| user_id | total_spent | council_id |
|-------------|----------------|------------|
| 1 | 50.00 | 1 |
| 2 | 2.00 | 3 |
I was hoping to reverse transactions and deposits done to get the account balance for a day then get the sum of users with an account balance < 0... But this has just failed to work.
The goal is to produce a query that shows daily overdraft (Only SUM the total account balance of users with account balance below 0 ) for a particular council.
Expected Result
date
council_id
o_d_amount
2021-04-24
1
-300.00
2021-04-24
2
-60.00
2021-04-24
3
-900.00
2021-04-25
1
-600.00
2021-04-25
2
-100.00
2021-04-25
3
-1200.00
This is actually not that hard, but the way you asked makes it hard to follow.
Also, your expected result should match the data you provided.
Edited: Previous solution was wrong - It counted withdraws and deposits more than once if you have more than one event for each user/date.
Start by having the total exchanged on each day, like
select user_id, date, sum(amount) exchanged_on_day from (
select user_id, date, amount amount from deposits
union all select user_id, date, -amount_tendered amount from transactions
) d
group by user_id, date
order by user_id, date;
What follows gets the state of the account only on days that had any deposits or withdraws.
To get the results of all days (and not just those with account movement) you just have to change the cross join part to get a table with all dates you want (like Get all dates between two dates in SQL Server) but I digress...
select dates.date, c.council_id, u.name username
, u.account_bal - sum(case when e.date >= dates.date then e.exchanged_on_day else 0 end) as amount_on_start_of_day
, u.account_bal - sum(case when e.date > dates.date then e.exchanged_on_day else 0 end) as amount_on_end_of_day
from councils c
inner join markets m on c.council_id=m.council_id
inner join market_user_link mul on m.market_id=mul.market_id
inner join users u on mul.user_id=u.user_id
left join (
select user_id, date, sum(amount) exchanged_on_day from (
select user_id, date, amount amount from deposits
union all select user_id, date, -amount_tendered amount from transactions
) d group by user_id, date
) e on u.user_id=e.user_id --exchange on each Day
cross join (select distinct date from (select date from deposits union select date from transactions) datesInternal) dates --all days that had a transaction
group by dates.date, c.council_id, u.name, u.account_bal
order by dates.date desc, c.council_id, u.name;
From there you can rearrange to get the result you want.
select date, council_id
, sum(case when amount_on_start_of_day<0 then amount_on_start_of_day else 0 end) o_d_amount_start
, sum(case when amount_on_end_of_day<0 then amount_on_end_of_day else 0 end) o_d_amount_end
from (
select dates.date, c.council_id, u.name username
, u.account_bal - sum(case when e.date >= dates.date then e.exchanged_on_day else 0 end) as amount_on_start_of_day
, u.account_bal - sum(case when e.date > dates.date then e.exchanged_on_day else 0 end) as amount_on_end_of_day
from councils c
inner join markets m on c.council_id=m.council_id
inner join market_user_link mul on m.market_id=mul.market_id
inner join users u on mul.user_id=u.user_id
left join (
select user_id, date, sum(amount) exchanged_on_day from (
select user_id, date, amount amount from deposits
union all select user_id, date, -amount_tendered amount from transactions
) d group by user_id, date
) e on u.user_id=e.user_id --exchange on each Day
cross join (select distinct date from (select date from deposits union select date from transactions) datesInternal) dates --all days that had a transaction
group by dates.date, c.council_id, u.name, u.account_bal
) result
group by date, council_id
order by date;
You can check it on https://www.db-fiddle.com/f/msScT6B5F7FjU2aQXVr2da/6
Basically the query maps users to councils, caculates periods of overdrafts for users, them aggregates over councils. I assume that starting balance is dated start of the month '2021-04-01' (it could be ending balance as well, see below), change it as needed. Also that negative starting balance counts as an overdraft. For simplicity and debugging the query is divided into a number of steps.
with uc as (
select distinct m.council_id, mul.user_id
from markets m
join market_user_link mul on m.market_id = mul.market_id
),
user_running_total as (
select user_id, date,
coalesce(lead(date) over(partition by user_id order by date) - interval 1 day, date) nxt,
sum(sum(s)) over(partition by user_id order by date) rt
from (
select user_id, date, -amount_tendered s
from transactions
union all
select user_id, date, amount
from deposits
union all
select user_id, se.d, se.s
from users
cross join lateral (
select date(NOW() + interval 1 day) d, 0 s
union all
select '2021-04-01' d, account_bal
) se
) t
group by user_id, date
),
user_overdraft as (
select user_id, date, nxt, least(rt, 0) ovd
from user_running_total
where date <= date(NOW())
),
dates as (
select date
from user_overdraft
union
select nxt
from user_overdraft
),
council__overdraft as (
select uc.council_id, d.date, sum(uo.ovd) total_overdraft, lag(sum(uo.ovd), 1, sum(uo.ovd) - 1) over(partition by uc.council_id order by d.date) prev_ovd
from uc
cross join dates d
join user_overdraft uo on uc.user_id = uo.user_id and d.date between uo.date and uo.nxt
group by uc.council_id, d.date
)
select council_id, date, total_overdraft
from council__overdraft
where total_overdraft <> prev_ovd
order by date, council_id
Really council__overdraft is quite usable, the last step just compacts output excluding intermidiate dates when overdraft is not changed.
With following sample data:
users
user_id name account_bal
1 Wells -5
2 James 100
3 Joy 10
4 Mumbi -300
deposits, odered by date, extra row added for the last date
id user_id amount date
3 3 5 2021-04-25
4 4 5 2021-04-25
1 1 5 2021-04-26
2 3 10 2021-04-26
5 3 73 2021-05-06
transactions, odered by date (note the added row, to illustrate running total in action)
id user_id amount_tendered date
5 4 50 2021-04-25
2 2 10 2021-04-26
3 3 15 2021-04-26
1 1 5 2021-04-27
4 3 17 2021-04-27
councils
council_id name
1 a
2 b
3 c
markets
market_id name council_id
1 x 3
2 y 1
3 z 2
market_user_link
id market_id user_id
1 1 3
2 2 2
3 3 1
4 3 4
the query ouput is
council_id
date
overdraft
1
2021-04-01
0
2
2021-04-01
-305
3
2021-04-01
0
2
2021-04-25
-350
2
2021-04-26
-345
2
2021-04-27
-350
3
2021-04-27
-7
3
2021-05-06
0
Alternatively, provided the users table is holding a closing (NOW()) balance, replace user_running_total CTE with the following code
user_running_total as (
select user_id, date,
coalesce(lead(date) over(partition by user_id order by date) - interval 1 day, date) nxt,
coalesce(sum(sum(s)) over(partition by user_id order by date desc
rows between unbounded preceding and 1 preceding), sum(s)) rt
from (
select user_id, date, amount_tendered s
from transactions
union all
select user_id, date, -amount
from deposits
union all
select user_id, se.d, se.s
from users
cross join lateral (
select date(NOW() + interval 1 day) d, account_bal s
union all
select '2021-04-01' d, 0
) se
) t
where DATE(date) between date '2021-04-01' and date(NOW() + interval 1 day)
group by user_id, date
),
This way the query starts with closing balance dated next date after now and rollouts a running total in the reverse order till '2021-04-01' as a starting date.
Output
council_id
date
overdraft
1
2021-04-01
0
2
2021-04-01
-260
3
2021-04-01
-46
2
2021-04-25
-305
3
2021-04-25
-41
2
2021-04-26
-300
3
2021-04-26
-46
2
2021-04-27
-305
3
2021-04-27
-63
3
2021-05-06
0
db-fiddle both versions
I have tables:
orders:
id_order id_customer
1 1
2 2
3 1
orders_history
id_history id_order id_order_state date_add
1 1 1 2010-01-01 00:00:00
2 1 2 2010-01-02 00:00:00
3 1 3 2010-01-03 00:00:00
4 2 2 2010-05-01 00:00:00
5 2 3 2011-05-02 00:00:00
6 3 1 2011-05-03 00:00:00
7 3 2 2011-06-01 00:00:00
order_state
id_order_state name
1 New
2 Sent
3 Rejected
4 ...
How to get all order_id's where last id_order_state of that order (by last I mean this with MAX(id_history) or MAX(date_add)) is not equal 1 or 3?
select oh.id_history, oh.id_order, oh.id_order_state, oh.date_add
from (
select id_order, max(date_add) as MaxDate
from orders_history
where id_order_state not in (1, 3)
group by id_order
) ohm
inner join orders_history oh on ohm.id_order = oh.id_order
and ohm.MaxDate = oh.date_add
I think what he's after is what orders are complete... ie their final status, not those that are exclusive of the 1 and 3 specifically. The first pre-query should be the max ID regardless of the status code
select
orders.*
from
( select oh.id_order,
max( oh.id_history ) LastID_HistoryPerOrder
from
orders_history oh
group by
oh.id_order ) PreQuery
join orders_history oh2
on PreQuery.ID_Order = oh2.id_order
AND PreQuery.LastID_HistoryPerOrder = oh2.id_history
AND NOT OH2.id_order_state IN (1, 3) <<== THIS ELIMINATES 1's & 3's from result set
join Orders <<= NOW, anything left after above ^ is joined to orders
on PreQuery.ID_Order = Orders.ID_Order
Just to re-show YOUR data... I've marked the last SEQUENCE (ID_History) per ORDER... This is what the PREQUERY is going to return...
id_history id_order id_order_state date_add
1 1 1 2010-01-01 00:00:00
2 1 2 2010-01-02 00:00:00
**3 1 3 2010-01-03 00:00:00
4 2 2 2010-05-01 00:00:00
**5 2 3 2011-05-02 00:00:00
6 3 1 2011-05-03 00:00:00
**7 3 2 2011-06-01 00:00:00
The "PreQuery" will result with the following subset
ID_Order LastID_HistoryPerOrder (ID_History)
1 3 (state=3) THIS ONE WILL BE SKIPPED IN FINAL RESULT
2 5 (state=3) THIS ONE WILL BE SKIPPED IN FINAL RESULT
3 7 (state=2)
Now, the result of this is then re-joined back to order history on just these two elements... yet adds the criteria to EXCLUDE the 1,3 entries for "order state".
In this case,
1 would be rejected as its state = 3 (sequence #3),
2 would be rejected since its last history is state = 3 (sequence #5).
3 would be INCLUDED since its state = 2 (sequence #7)
Finally, all that joined to the orders will result with ONE ID, and nicely match up with the orders table on the Order_ID alone and get the desired results.
Another possible solution:
SELECT DISTINCT
id_order
FROM
Orders_History OH1
LEFT OUTER JOIN Orders_History OH2 ON
OH2.id_order = OH1.id_order AND
OH2.is_order_state IN (1, 3) AND
OH2.date_add >= OH1.date_add
WHERE
OH2.id_order IS NULL
I'm using "answer for my question" because I need to post results of your queries. So.
Unfortunately not all of your answers guys works. Let's prepare test environment:
CREATE TABLE `order_history` (
`id_order_history` int(11) NOT NULL AUTO_INCREMENT,
`id_order` int(11) NOT NULL,
`id_order_state` int(11) NOT NULL,
`date_add` datetime NOT NULL,
PRIMARY KEY (`id_order_history`)
) ENGINE=MyISAM AUTO_INCREMENT=11 DEFAULT CHARSET=latin2;
CREATE TABLE `orders` (
`id_order` int(11) NOT NULL AUTO_INCREMENT,
`id_customer` int(11) DEFAULT NULL,
PRIMARY KEY (`id_order`)
) ENGINE=MyISAM AUTO_INCREMENT=8 DEFAULT CHARSET=latin2;
INSERT INTO `order_history`
(`id_order_history`, `id_order`, `id_order_state`, `date_add`) VALUES
(1,1,1,'2011-01-01 00:00:00'),
(2,1,2,'2011-01-01 00:10:00'),
(3,1,3,'2011-01-01 00:20:00'),
(4,2,1,'2011-02-01 00:00:00'),
(5,2,2,'2011-02-01 00:25:01'),
(6,2,3,'2011-02-01 00:25:59'),
(7,3,1,'2011-03-01 00:00:01'),
(8,3,2,'2011-03-01 00:00:02'),
(9,3,3,'2011-03-01 00:01:00'),
(10,3,2,'2011-03-02 00:00:01');
COMMIT;
INSERT INTO `orders` (`id_order`, `id_customer`) VALUES
(1,1),
(2,2),
(3,3),
(4,4),
(5,5),
(6,6),
(7,7);
COMMIT;
Now, lets select Last/Max State for each Order, so let's run simple query:
select id_order, max(date_add) as MaxDate
from `order_history`
group by id_order
this gives us PROPER results, no rocket science right now:
id_order MaxDate
---------+-------------------
1 2011-01-01 00:20:00 //last order_state=3
2 2011-02-01 00:25:59 //last order_state=3
3 2011-03-02 00:00:01 //last order_state=2
Now for simplicity, lest change our queries to get Orders where Last State is not equal 3.
We're expecting to get one row result with id_order = 3.
So let's test our queries:
QUERY 1 made by RedFilter:
select oh.id_order, oh.id_order_state, oh.date_add
from (
select id_order, max(date_add) as MaxDate
from `order_history`
where id_order_state not in (3)
group by id_order
) ohm
inner join `order_history` oh on ohm.id_order = oh.id_order
and ohm.MaxDate = oh.date_add
Result:
id_order id_order_state date_add
-------------------------------------------------
1 2 2011-01-01 00:10:00
2 2 2011-02-01 00:25:01
3 2 2011-03-02 00:00:01
So it's not true
QUERY 2 made by Tom H.:
SELECT DISTINCT OH1.id_order
FROM order_history OH1
LEFT OUTER JOIN order_history OH2 ON
OH2.id_order = OH1.id_order AND
OH2.id_order_state NOT IN (3) AND
OH2.`id_order_history` >= OH1.`id_order_history`
WHERE
OH2.id_order IS NULL
Result:
id_order
--------
1
2
So it's not true
Any suggestions appreciated.
EDIT
Thanks to Andriy M. comment we have proper solution. It's a modification of Tom H. query all should looks as follow:
SELECT DISTINCT
OH1.id_order
FROM
order_history OH1
LEFT OUTER JOIN order_history OH2 ON
OH2.id_order = OH1.id_order
AND OH2.date_add > OH1.date_add
WHERE OH1.id_order_state NOT IN (3) AND OH2.id_order IS NULL
EDIT 2:
QUERY 3 made by DRapp:
select
distinct orders.`id_order`
from
( select oh.id_order,
max( oh.id_order_history ) LastID_HistoryPerOrder
from
order_history oh
group by
oh.id_order ) PreQuery
join order_history oh2
on PreQuery.id_order = oh2.id_order
AND PreQuery.LastID_HistoryPerOrder = oh2.id_order_history
AND NOT oh2.id_order_state IN (1,3)
join orders
on PreQuery.id_order = orders.id_order
Result:
id_order
--------
3
So it's finally true