I have a data orders that looks like this:
| Order | Step | Step Complete Date |
|:-----:|:----:|:------------------:|
| A | 1 | 11/1/2019 |
| | 2 | 11/1/2019 |
| | 3 | 11/1/2019 |
| | 4 | 11/3/2019 |
| | 5 | 11/3/2019 |
| | 6 | 11/5/2019 |
| | 7 | 11/5/2019 |
| B | 1 | 12/1/2019 |
| | 2 | 12/2/2019 |
| | 3 | |
| C | 1 | 10/21/2019 |
| | 2 | 10/23/2019 |
| | 3 | 10/25/2019 |
| | 4 | 10/25/2019 |
| | 5 | 10/25/2019 |
| | 6 | |
| | 7 | 10/27/2019 |
| | 8 | 10/28/2019 |
| | 9 | 10/29/2019 |
| | 10 | 10/30/2019 |
| D | 1 | 10/30/2019 |
| | 2 | 11/1/2019 |
| | 3 | 11/1/2019 |
| | 4 | 11/2/2019 |
| | 5 | 11/2/2019 |
What I need to accomplish is the following:
For each order, assign the 'Order_Completion_Date' field as the most recent 'Step_Complete_Date'. If ANY 'Step_Complete_Date' is NULL, then the value for 'Order_Completion_Date' should be NULL.
I set up a SQL FIDDLE with this data and my attempt, below:
SELECT
OrderNum,
MAX(Step_Complete_Date)
FROM
OrderNums
WHERE
Step_Complete_Date IS NOT NULL
GROUP BY
OrderNum
This is yielding:
ORDERNUM MAX(STEP_COMPLETE_DATE)
D 11/2/2019
A 11/5/2019
B 12/2/2019
C 10/30/2019
How can I achieve:
| OrderNum | Order_Completed_Date |
|:--------:|:--------------------:|
| A | 11/5/2019 |
| B | NULL |
| C | NULL |
| D | 11/2/2019 |
Aggregate function with KEEP can handle this
select ordernum,
max(step_complete_date)
keep (DENSE_RANK FIRST ORDER BY step_complete_date desc nulls first) res
FROM
OrderNums
GROUP BY
OrderNum
You can use a CASE expression to first count if there are any NULL values and if not then find the maximum value:
Query 1:
SELECT OrderNum,
CASE
WHEN COUNT( CASE WHEN Step_Complete_Date IS NULL THEN 1 END ) > 0
THEN NULL
ELSE MAX(Step_Complete_Date)
END AS Order_Completion_Date
FROM OrderNums
GROUP BY OrderNum
Results:
| ORDERNUM | ORDER_COMPLETION_DATE |
|----------|-----------------------|
| D | 11/2/2019 |
| A | 11/5/2019 |
| B | (null) |
| C | (null) |
First, you are representing dates as varchars in mm/dd/yyyy format (at least in fiddle). With max function it can produce incorrect result, try for example order with dates '11/10/2019' and '11/2/2019'.
Second, the most simple solution is IMHO to use fallback date for nulls and get null back when fallback date wins:
SELECT
OrderNum,
NULLIF(MAX(NVL(Step_Complete_Date,'~')),'~')
FROM
OrderNums
GROUP BY
OrderNum
(Example is still for varchars since tilde is greater than any digit. For dates, you could use 9999-12-31, for instance.)
Related
I have a table ORDERS with a column named cache_total_price, spent by each client.
+----+-----------+------------+-----------+------------------+
| id | client_id | date | reference | cache_total_price|
+----+-----------+------------+-----------+------------------+
| 1 | 20 | 2019-01-01 | 004214 | 0 |
| 2 | 3 | 2019-01-03 | 007120 | 0 |
| 3 | 11 | 2019-01-04 | 002957 | 0 |
| 4 | 6 | 2019-01-07 | 003425 | 0 |
I have another table ORDERS_REFS where there is the price total spent for each orders id
+-----+-------------+------------+----------+---------------+------------+
| id | order_id | name | quantity | unit_price | total_price|
+-----+-------------+------------+----------+---------------+------------+
| 1 | 1 | Produit 19 | 3 | 49.57 | 148.71 |
| 2 | 1 | Produit 92 | 4 | 81.24 | 324.96 |
| 3 | 1 | Produit 68 | 2 | 17.48 | 34.96 |
| 4 | 2 | Produit 53 | 4 | 83.69 | 334.76 |
| 5 | 2 | Produit 78 | 6 | 5.99 | 35.94 |
I want to had to column cache_total_price the result of my query :
select sum(total_price) from orders_refs group by order_id;
result :
+--------------------+
| sum(total_price) |
+--------------------+
| 508.6299819946289 |
| 370.700008392334 |
| 132.3699951171875 |
| 2090.1800079345703 |
I've tried some queries with Insert into select or update set, but didn't worked :(
If you're wanting to update all the orders at once, in MySQL a subquery like this should do the trick. You could always add a WHERE clause to do one at a time.
UPDATE ORDERS
SET cache_total_price = (
SELECT sum(total_price) from ORDERS_REF where order_id = ORDERS.id
)
update t
set t.cache_total_price=x.sum_total_price
from ORDERS as t
join
(
select order_id,sum(total_price)as sum_total_price
from orders_refs group by order_id
)x on t.id=x.order_id
In SQL Server you can try this one.
How can I do to check if the difference between date 1 and date 2 for every ID is more than 6 months? Let me illustrate with an example.
So I have a table like this one:
+----+---------+
| ID | Y-M |
+----+---------+
| 1 | 2017-01 |
| 1 | 2017-02 |
| 1 | 2017-10 |
| 2 | 2017-04 |
| 2 | 2017-06 |
| 3 | 2017-06 |
| 4 | 2017-07 |
+----+---------+
And I want to add a third column that says yes if the difference between the first one and the second one is more than 6months. I want to say yes only on the first one. In case there is no date to compare with, then it would be also a yes. Anyway, this would be the final result:
+----+---------+------------+
| ID | Y-M | Difference |
+----+---------+------------+
| 1 | 2017-01 | No |
| 1 | 2017-02 | Yes |
| 1 | 2017-10 | Yes |
| 2 | 2017-04 | Yes |
| 2 | 2017-11 | No |
| 2 | 2017-12 | Yes |
| 3 | 2017-06 | Yes |
| 4 | 2017-07 | Yes |
+----+---------+------------+
Thank you!
You can use lead() and some date arithmetic:
select t.*,
(case when lead(ym) over (partition by id order by ym) < dateadd(month, 6, ym)
then 'No' else 'Yes'
end) as difference
from t;
I have a base table where I need to calculate the difference between two dates based on the type of the entry.
tblA
+----------+------------+---------------+--------------+
| TypeCode | Log_Date | Complete_Date | Pending_Date |
+----------+------------+---------------+--------------+
| 1 | 18/04/2016 | 19/04/2016 | |
| 2 | 10/04/2016 | 18/04/2016 | 15/04/2016 |
| 3 | 12/04/2016 | 19/04/2016 | |
| 4 | 15/04/2016 | 17/04/2016 | 16/04/2016 |
| 5 | 16/04/2016 | 21/04/2016 | |
| 1 | 19/04/2016 | 20/04/2016 | |
| 2 | 20/03/2016 | 31/03/2015 | |
| 3 | 25/03/2016 | 28/03/2016 | |
| 4 | 26/03/2016 | 27/03/2016 | |
| 5 | 27/03/2016 | 30/03/2016 | |
+----------+------------+---------------+--------------+
I have another look up table which has the column names to be considered based on the TypeCode.
tblB
+----------+----------+---------------+
| TypeCode | DateCol1 | DateCol2 |
+----------+----------+---------------+
| 1 | Log_Date | Complete_Date |
| 2 | Log_Date | Pending_Date |
| 3 | Log_Date | Complete_Date |
| 4 | Log_Date | Pending_Date |
| 5 | Log_Date | Complete_Date |
+----------+----------+---------------+
I am doing a simple DATEDIFF between two dates for my calculation. However I want to lookup which columns to consider for this calculation from tblB and apply it on tblA based on the TypeCode.
Resulting table:
For example: When the TypeCode is 2 or 4 then the calculation should be DATEDIFF(d, Log_Date, Pending_Date), otherwise DATEDIFF(d, Log_Date, Complete_Date)
+----------+------------+---------------+--------------+----------+
| TypeCode | Log_Date | Complete_Date | Pending_Date | Cal_Days |
+----------+------------+---------------+--------------+----------+
| 1 | 18/04/2016 | 19/04/2016 | | 1 |
| 2 | 10/04/2016 | 18/04/2016 | 15/04/2016 | 5 |
| 3 | 12/04/2016 | 19/04/2016 | | 7 |
| 4 | 15/04/2016 | 17/04/2016 | 16/04/2016 | 1 |
| 5 | 16/04/2016 | 21/04/2016 | | 5 |
| 1 | 19/04/2016 | 20/04/2016 | | 1 |
| 2 | 20/03/2016 | 31/03/2015 | | |
| 3 | 25/03/2016 | 28/03/2016 | | 3 |
| 4 | 26/03/2016 | 27/03/2016 | | |
| 5 | 27/03/2016 | 30/03/2016 | | 3 |
+----------+------------+---------------+--------------+----------+
Any help would be appreciated. Thanks.
Use JOIN with CASE expression:
SELECT
a.*,
Cal_Days =
DATEDIFF(
DAY,
CASE
WHEN b.DateCol1 = 'Log_Date' THEN a.Log_Date
WHEN b.DateCol1 = 'Complete_Date' THEN a.Complete_Date
ELSE a.Pending_Date
END,
CASE
WHEN b.DateCol2 = 'Log_Date' THEN a.Log_Date
WHEN b.DateCol2 = 'Complete_Date' THEN a.Complete_Date
ELSE a.Pending_Date
END
)
FROM TblA a
INNER JOIN TblB b
ON b.TypeCode = a.TypeCode
There are 3 Tables (SorMaster, SorDetail, and InvWarehouse):
SorMaster:
+------------+
| SalesOrder |
+------------+
| 100 |
| 101 |
| 102 |
+------------+
SorDetail:
+------------+------------+---------------+
| SalesOrder | MStockCode | MBackOrderQty |
+------------+------------+---------------+
| 100 | PN-1 | 4 |
| 100 | PN-2 | 9 |
| 100 | PN-3 | 1 |
| 100 | PN-4 | 6 |
| 101 | PN-1 | 6 |
| 101 | PN-3 | 2 |
| 102 | PN-2 | 19 |
| 102 | PN-3 | 14 |
| 102 | PN-4 | 6 |
| 102 | PN-5 | 4 |
+------------+------------+---------------+
InvWarehouse:
+------------+-----------+-----------+
| MStockCode | Warehouse | QtyOnHand |
+------------+-----------+-----------+
| PN-1 | A | 1 |
| PN-2 | B | 9 |
| PN-3 | A | 0 |
| PN-4 | B | 1 |
| PN-1 | A | 0 |
| PN-3 | B | 5 |
| PN-2 | A | 9 |
| PN-3 | B | 4 |
| PN-4 | A | 6 |
| PN-5 | B | 0 |
+------------+-----------+-----------+
Desired Results:
+------------+-----------------+--------------+
| MStockCode | SumBackOrderQty | SumQtyOnHand |
+------------+-----------------+--------------+
| PN-1 | 10 | 10 |
| PN-2 | 28 | 1 |
| PN-3 | 17 | 5 |
| PN-4 | 12 | 13 |
| PN-5 | 11 | 6 |
+------------+-----------------+--------------+
I have been going around in circles with no end in sight. Seems like it should be simple but just can't wrap my head around it. The SumBackOrderQty obviously getting counted twice as the SumQtyOnHand is evaluated. To this point I have been doing the calculations in the PHP instead of the select statement but would like to clean things up a bit where possible.
Current query statement is:
SELECT SorDetail.MStockCode,
SUM(SorDetail.MBackOrderQty) AS 'SumMBackOrderQty',
SUM(InvWarehouse.QtyOnHand) AS 'SumQtyOnHand'
FROM SysproCompanyJ.dbo.SorMaster SorMaster,
SysproCompanyJ.dbo.SorDetail SorDetail LEFT OUTER JOIN SysproCompanyJ.dbo.InvWarehouse InvWarehouse
ON SorDetail.MStockCode = InvWarehouse.StockCode
WHERE SorMaster.SalesOrder = SorDetail.SalesOrder
AND SorMaster.ActiveFlag != 'N'
AND SorDetail.MBackOrderQty > '0'
AND SorDetail.MPrice > '0'
GROUP BY SorDetail.MStockCode
ORDER BY SorDetail.MStockCode ASC
Without providing the complete picture, in terms of your RDBMS, database schema, a description of the problem you're trying to solve and sample data that matches the aforementioned, the following is just an illustration of what a solution based on Barmar's comment could look like:
SELECT SD.MStockCode,
SD.SumBackOrderQty,
IW.SumQtyOnHand
FROM (SELECT MStockCode,
SUM(MBackOrderQty) AS `SumBackOrderQty`
FROM SorDetail
JOIN SorMaster ON SorDetail.SalesOrder=SorMaster.SalesOrder
WHERE SorMaster.ActiveFlag != 'N'
AND SorDetail.MBackOrderQty > 0
AND SorDetail.MPrice > 0
GROUP BY MStockCode) AS SD
LEFT JOIN (SELECT MStockCode,
SUM(QtyOnHand) AS `SumQtyOnHand`
FROM InvWarehouse
GROUP BY MStockCode) AS IW ON SD.MStockCode=IW.MStockCode
ORDER BY SD.MStockCode;
Here's one approach:
select MStockCode,
(select sum(MBackOrderQty) from sorDetail as T2
where T2.MStockCode = T1.MStockCode ) as SumBackOrderQty,
(select sum(QtyOnHand) from invWarehouse as T3
where T3.MStockCode = T1.MStockCode ) as SumQtyOnHand
from
(
select mstockcode from sorDetail
union
select mstockcode from invWarehouse
) as T1
In a fiddle here: http://sqlfiddle.com/#!9/fdaca/6
Though my SumQtyOnHand values don't match yours (as #Gordon pointed out).
I have one table that looks like this:
+---------------+---------------+-----------+-------+------+
| id_instrument | id_data_label | Date | Value | Note |
+---------------+---------------+-----------+-------+------+
| 1 | 57 | 1.10.2010 | 200 | NULL |
| 1 | 57 | 2.10.2010 | 190 | NULL |
| 1 | 57 | 3.10.2010 | 202 | NULL |
| | | | | |
+---------------+---------------+-----------+-------+------+
And the other that looks like this:
+----------------+---------------+---------------+--------------+-------+-----------+------+
| id_fundamental | id_instrument | id_data_label | quarter_code | value | AnnDate | Note |
+----------------+---------------+---------------+--------------+-------+-----------+------+
| 1 | 1 | 20 | 20101 | 3 | 28.2.2010 | NULL |
| 2 | 1 | 20 | 20102 | 4 | 1.8.2010 | NULL |
| 3 | 1 | 20 | 20103 | 5 | 2.11.2010 | NULL |
| | | | | | | |
+----------------+---------------+---------------+--------------+-------+-----------+------+
What I would like to do is to merge/join these two tables in one in a way that I get something like this:
+------------+--------------+--------------+----------+--------------+
| Date | Table1.Value | Table2.Value | AnnDate | quarter_code |
+------------+--------------+--------------+----------+--------------+
| 1.10.2010. | 200 | 3 | 1.8.2010 | 20102 |
| 2.10.2010. | 190 | 3 | 1.8.2010 | 20102 |
| 3.10.2010. | 202 | 3 | 1.8.2010 | 20102 |
| | | | | |
+------------+--------------+--------------+----------+--------------+
So the idea is to order them by Date from Table1 and since Table2 Values only change on the change of AnnDate we populate the Resulting table with same values from Table2.
After that I would like to go through the resulting table and create another (Final table) with the following.
On Date 1.10.2010. take last 4 AnnDates (so it would be 1.8.2010. and f.e. 20.3.2010. 30.1.2010. 15.11.2009) and Table2 values on those AnnDate. Make SUM of those 4 values and then divide the Table1 Value with that SUM.
So we would get something like:
+-----------+---------------------------------------------------------------+
| Date | FinalValue |
+-----------+---------------------------------------------------------------+
| 1.10.2010 | 200/(Table2.Value on 1.8.2010+Table2.Value on 20.3.2010 +...) |
| | |
+-----------+---------------------------------------------------------------+
Is there any way this can be done?
EDIT:
Hmm yes now I see that I really didn't do a good job explaining it.
What I wanted to say is
I try INNER JOIN like this:
SELECT TableOne.Date, TableOne.Value, TableTwo.Value, TableTwo.AnnDate, TableTwo.quarter_code
FROM TableOne
INNER JOIN TableTwo ON TableOne.id_intrument=TableTwo.id_instrument WHERE TableOne.id_data_label = somevalue AND TableTwo.id_data_label = somevalue AND date > xxx AND date < yyy
And this inner join returns 2620*40 rows which means for every AnnDate from table2 it returns all Date from table1.
What I want is to return 2620 values with Dates from Table1
Values from table1 on that date and Values from table2 that respond to that period of dates
f.e.
Table1:
+-------+-------+
| Date | Value |
+-------+-------+
| 1 | a |
| 2 | b |
| 3 | c |
| 4 | d |
+-------+-------+
Table2
+-------+---------+
| Value | AnnDate |
+-------+---------+
| x | 1 |
| y | 4 |
+-------+---------+
Resulting table:
+-------+---------+---------+
| Date | ValueT1 | ValueT2 |
+-------+---------+---------+
| 1 | a | x |
| 2 | b | x |
| 3 | c | x |
| 4 | d | y |
+-------+---------+---------+
You need a JOIN statement for your first query. Try:
SELECT TableOne.Date, TableOne.Value, TableTwo.Value, TableTwo.AnnDate, TableTwo.quarter_code FROM TableOne
INNER JOIN TableTwo
ON TableOne.id_intrument=TableTwo.id_instrument;