I have a table that stores the VIN numbers and delivery dates of vehicles based on a code. I want to be able to get one row with three columns of data.
I have tried the following
SELECT DISTINCT VIN, MAX(TRANSACTION_DATE) AS DELIVERY_DATE
FROM "TABLE"
WHERE DELIVERY_TYPE ='025'
AND VIN IN ('XYZ')
GROUP BY VIN
UNION ALL
SELECT VIN, MAX(TRANSACTION_DATE) AS OTHER_DELIVERY_DATE
FROM "TABLE"
WHERE DELIVERY_TYPE !='025'
AND VIN IN ('XYZ')
GROUP BY VIN;
When I run this I get
VIN DELIVERY_DATE
XYZ 26-dec-18
XYZ 01-MAY-19
current data format in table:
VIN TRANSACTION_DATE
XYZ 26-DEC-18
XYZ 01-MAY-19
Required format:
VIN DELIVERY_DATE OTHER_DELIVERY DATE
XYZ 26-DEC-18 01-MAY-19
use conditional aggregation
SELECT VIN,
MAX (CASE WHEN DELIVERY_TYPE ='025' AND
VIN IN ('XYZ') then TRANSACTION_DATE end) AS DELIVERY_DATE
MAX(CASE WHEN DELIVERY_TYPE !='025' AND
VIN IN ('XYZ') then TRANSACTION_DATE end) AS OTHER_DELIVERY
FROM "TABLE"
GROUP BY VIN
Just use conditional aggregation:
SELECT VIN,
MAX(CASE WHEN DELIVERY_TYPE = 25 THEN TRANSACTION_DATE END) AS DELIVERY_DATE,
MAX(CASE WHEN DELIVERY_TYPE <> 25 THEN TRANSACTION_DATE END) AS TRANSACTION_DATE
FROM TABLE
WHERE VIN IN ('XYZ')
GROUP BY VIN;
Note that SELECT DISTINCT is almost never used with GROUP BY.
You can use CROSS APPLY
DECLARE #Cars TABLE (VIN VARCHAR(100), DELIVERY_TYPE VARCHAR(3), TRANSACTION_DATE DATE)
INSERT INTO #Cars
(VIN, DELIVERY_TYPE , TRANSACTION_DATE)
VALUES
('XYZ', '025', '20181226'), ('XYZ', '030', '20190319')
I needed above code to be able to run without a table and data, all you need is this:
SELECT DISTINCT C.VIN, DD.DELIVERY_DATE, TD.TRANSACTION_DATE
FROM #Cars C
CROSS APPLY (SELECT MAX(TRANSACTION_DATE) DELIVERY_DATE FROM #Cars D WHERE D.DELIVERY_TYPE = '025' AND D.VIN = C.VIN) DD
CROSS APPLY (SELECT MAX(TRANSACTION_DATE) TRANSACTION_DATE FROM #Cars D WHERE D.DELIVERY_TYPE = '025' AND D.VIN = C.VIN) TD
If you need to transpond not two but a lot more columns, I'd suggest using PIVOT TABLE as more appropriate, but for two columns either CROSS APPLY or conditional aggregation will do the trick.
Related
I have a table (vOKPI_Tickets) that has the following columns:
|CreationDate | CompletionDate|
I'd like to get a count on each of those columns, and group them by date. It should look something like this when complete:
| Date | Count-Created | Count-Completed |
I can get each of the counts individually, by doing something like this:
SELECT COUNT(TicketId)
FROM vOKPI_Tickets
GROUP BY CreationDate
and
SELECT COUNT(TicketId)
FROM vOKPI_Tickets
GROUP BY CreationDate
How can I combine the output into one table? I should also note that this will become a View.
Thanks in advance
Simple generic approach:
select
coalesce(crte.creationdate, cmpl.CompletionDate) as theDate,
crte.cnt as created,
cmpl.cnt as completed
from
(select creationdate, count (*) as cnt from vOKPI_Tickets where creationdate is not null group by creationdate) crte
full join
(select CompletionDate, count (*) as cnt from vOKPI_Tickets where CompletionDate is not null group by CompletionDate) cmpl
on crte.creationdate = cmpl.CompletionDate
You can unpivot and aggregate. A general method is:
select dte, sum(created), sum(completed)
from ((select creationdate as dte, 1 as created, 0 as completed
from vOKPI_Tickets
) union all
(select completed as dte, 0 created, 1 as completed
from vOKPI_Tickets
)
) t
group by dte;
In SQL Server, you can use cross apply for this:
select d.dt, sum(d.is_completed) count_created, sum(d.is_completed) count_completed
from vokpi_tickets t
cross apply (values (creationdate, 1, 0), (completion_date, 0, 1)) as d(dt, is_created, is_completed)
where d.dt is not null
group by d.dt
I have a checking account table that contains columns Cust_id (customer id), Open_Date (start date), and Closed_Date (end date). There is one row for each account. A customer can open multiple accounts at any given point. I would like to know how long the person has been a customer.
eg 1:
CREATE TABLE [Cust]
(
[Cust_id] [varchar](10) NULL,
[Open_Date] [date] NULL,
[Closed_Date] [date] NULL
)
insert into [Cust] values ('a123', '10/01/2019', '10/15/2019')
insert into [Cust] values ('a123', '10/12/2019', '11/01/2019')
Ideally I would like to insert this into a table with just one row, that says this person has been a customer from 10/01/2019 to 11/01/2019. (as he opened his second account before he closed his previous one.
Similarly eg 2:
insert into [Cust] values ('b245', '07/01/2019', '09/15/2019')
insert into [Cust] values ('b245', '10/12/2019', '12/01/2019')
I would like to see 2 rows in this case- one that shows he was a customer from 07/01 to 09/15 and then again from 10/12 to 12/01.
Can you point me to the best way to get this?
I would approach this as a gaps and islands problem. You want to group together groups of adjacents rows whose periods overlap.
Here is one way to solve it using lag() and a cumulative sum(). Everytime the open date is greater than the closed date of the previous record, a new group starts.
select
cust_id,
min(open_date) open_date,
max(closed_date) closed_date
from (
select
t.*,
sum(case when not open_date <= lag_closed_date then 1 else 0 end)
over(partition by cust_id order by open_date) grp
from (
select
t.*,
lag(closed_date) over (partition by cust_id order by open_date) lag_closed_date
from cust t
) t
) t
group by cust_id, grp
In this db fiddle with your sample data, the query produces:
cust_id | open_date | closed_date
:------ | :--------- | :----------
a123 | 2019-10-01 | 2019-11-01
b245 | 2019-07-01 | 2019-09-15
b245 | 2019-10-12 | 2019-12-01
I would solve this with recursion. While this is certainly very heavy, it should accommodate even the most complex account timings (assuming your data has such). However, if the sample data provided is as complex as you need to solve for, I highly recommend sticking with the solution provided above. It is much more concise and clear.
WITH x (cust_id, open_date, closed_date, lvl, grp) AS (
SELECT cust_id, open_date, closed_date, 1, 1
FROM (
SELECT cust_id
, open_date
, closed_date
, row_number()
OVER (PARTITION BY cust_id ORDER BY closed_date DESC, open_date) AS rn
FROM cust
) AS t
WHERE rn = 1
UNION ALL
SELECT cust_id, open_date, closed_date, lvl, grp
FROM (
SELECT c.cust_id
, c.open_date
, c.closed_date
, x.lvl + 1 AS lvl
, x.grp + CASE WHEN c.closed_date < x.open_date THEN 1 ELSE 0 END AS grp
, row_number() OVER (PARTITION BY c.cust_id ORDER BY c.closed_date DESC) AS rn
FROM cust c
JOIN x
ON x.cust_id = c.cust_id
AND c.open_date < x.open_date
) AS t
WHERE t.rn = 1
)
SELECT cust_id, min(open_date) AS first_open_date, max(closed_date) AS last_closed_date
FROM x
GROUP BY cust_id, grp
ORDER BY cust_id, grp
I would also add the caveat that I don't run on SQL Server, so there could be syntax differences that I didn't account for. Hopefully they are minor, if present.
you can try something like that:
select distinct
cust_id,
(select min(Open_Date)
from Cust as b
where b.cust_id = a.cust_id and
a.Open_Date <= b.Closed_Date and
a.Closed_Date >= b.Open_Date
),
(select max(Closed_Date)
from Cust as b
where b.cust_id = a.cust_id and
a.Open_Date <= b.Closed_Date and
a.Closed_Date >= b.Open_Date
)
from Cust as a
so, for every row - you're selecting minimal and maximal dates from all overlapping ranges, later distinct filters out duplicates
Table Name: TraderCapital
Columns:
Trader (varchar),
Currency(varchar),
Date(int i.e. yyyymmdd format),
Capital(int)
primary key fields: Trader, Currency
Trader, Currency, Date, Capital
A, USD, 20190605, 100
A, USD, 20190606, 100
B, INR, 20190605, 200
B, INR, 20190606, 200
C, USD, 20190606, 100
D, USD, 20190601, 100
I want to update my table after aggregating Capital of 20190606 on to Capital of 20190605. So, desired output should look like:
Trader, Currency, Date, Capital
A, USD, 20190605, 200
B, INR, 20190605, 400
C, USD, 20190606, 100
D, USD, 20190601, 100
Could you help me write sql query for same?
You can achieve it using LAG(). In the first step I created a column that checks if there is a previous day for a row. Later I used this column (previousDay) to group rows.
with previousDay as (
select
*
,LAG(date) over (partition by trader, currency order by date asc) as PreviousDay
from TraderCapital
)
select
trader
,currency
,case when PreviousDay is not null then dateadd(day, -1, date) else date end as date
,sum(Capital) as capital
from previousDay
group by case when PreviousDay is not null then dateadd(day, -1, date) else date end
,trader
,currency
Try window functions like:
select b.Trader,b.Currency, b.Date, b.running_total as Capital
from (
select a.Trader,a.Currency, a.Date, a.running_total
, row_number() over (partition by a.Trader, a.Currency order by a.running_total desc) rnk
from (
select * ,sum(capital) over (partition by Trader, Currency order by Date desc) as running_total
from TraderCapital )a )b
where b.rnk = 1
Test Result:
Dd<>Fiddle
Thanks #M. Kanarkowski and #Gen Wan for your answers. Here is what worked finally for me based on your suggestions:
with PreviousDayTable as (
select *, LAG(Date) over (partition by Trader, Currency order by Date)
as previousDay
from TraderCapital
),
TotalTable as (
select Trader, Currency,
case when previousDay is not null then previousDay else Date end as PreviousDay,
sum(Capital) as agg
from PreviousDayTable
group by Trader, Currency,
case when previousDay is not null then previousDay else Date end
)
update TraderCapital
set TraderCapital.Capital = B.agg
from TraderCapital as A JOIN TotalTable as B
ON A.Trader = B.Trader
AND A.Currency = B.Currency
AND A.Date = B.previousDay
with PreviousDayTable as (
select *, LAG(Date) over (partition by Trader, Currency order by Date)
as previousDay
from TraderCapital
)
delete A
from TraderCapital as A JOIN PreviousDayTable as B
ON A.Trader = B.Trader
AND A.Currency = B.Currency
AND A.Date = B.Date
where B.previousDay is not null
Feel free to suggest improvements.
My objective is produce a dataset that shows a boatload of data from, in total, just shy of 50 tables, all in the same Oracle SQL database schema. Each table except the first consists of, as far as the report I'm building cares, two elements:
A foreign-key identifier that matches a row on the first table
A date
There may be many rows on one of these tables corresponding to one case, and it will NOT be the same number of rows from table to table.
My objective is to have each row in the first table show up as many times as needed to display all the results from the other tables once. So, something like this (except on a lot more tables):
CASE_FILE_ID INITIATED_DATE INSPECTION_DATE PAYMENT_DATE ACTION_DATE
------------ -------------- --------------- ------------ -----------
1000 10-JUL-1986 14-JUL-1987 10-JUL-1986
1000 14-JUL-1988 10-JUL-1987
1000 14-JUL-1989 10-JUL-1988
1000 10-JUL-1989
My current SQL code (shrunk down to five tables, but the rest all follow the same format as T1-T4):
SELECT DISTINCT
A.CASE_FILE_ID,
T1.DATE AS INITIATED_DATE,
T2.DATE AS INSPECTION_DATE,
T3.DATE AS PAYMENT_DATE,
T4.DATE AS ACTION_DATE
FROM
RECORDS.CASE_FILE A
LEFT OUTER JOIN RECORDS.INITIATE T1 ON A.CASE_FILE_ID = T1.CASE_FILE_ID
LEFT OUTER JOIN RECORDS.INSPECTION T2 ON A.CASE_FILE_ID = T2.CASE_FILE_ID
LEFT OUTER JOIN RECORDS.PAYMENT T3 ON A.CASE_FILE_ID = T3.CASE_FILE_ID
LEFT OUTER JOIN RECORDS.ACTION T4 ON A.CASE_FILE_ID = T4.CASE_FILE_ID
ORDER BY
A.CASE_FILE_ID
The problem is, the output this produces results in distinct combinations; so in the above example (where I added a 'WHERE' clause of A.CASE_FILE_ID = '1000'), instead of four rows for case 1000, it'd show twelve (1 Initiated Date * 3 Inspection Dates * 4 Payment Dates = 12 rows). Suffice it to say, as the number of tables increases, this would get very prohibitive in both display and runtime, very quickly.
What is the best way to get an output loosely akin to the ideal above, where any one date is only shown once? Failing that, is there a way to get it to only show as many lines for one CASE_FILE as it needs to show all the dates, even if some dates repeat within that?
There isn't a good way, but there are two ways. One method involves subqueries for each table and complex outer joins. The second involves subqueries and union all. Let's go with that one:
SELECT CASE_FILE_ID,
MAX(INITIATED_DATE) as INITIATED_DATE,
MAX(INSPECTION_DATE) as INSPECTION_DATE,
MAX(PAYMENT_DATE) as PAYMENT_DATE,
MAX(ACTION) as ACTION
FROM ((SELECT A.CASE_FILE_ID, NULL as INITIATED_DATE, NULL as INSPECTION_DATE,
NULL as PAYMENT_DATE, NULL as ACTION_DATE,
1 as seqnum
FROM RECORDS.CASE_FILE A
) UNION ALL
(SELECT T1.CASE_FILE_ID, DATE as INITIATED_DATE, NULL as INSPECTION_DATE,
NULL as PAYMENT_DATE, NULL as ACTION_DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.INITIATE
) UNION ALL
(SELECT T1.CASE_FILE_ID, NULL as INITIATED_DATE, DATE as INSPECTION_DATE,
NULL as PAYMENT_DATE, NULL as ACTION_DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.INSPECTION
) UNION ALL
(SELECT T1.CASE_FILE_ID, NULL as INITIATED_DATE, NULL as INSPECTION_DATE,
DATE as PAYMENT_DATE, NULL as ACTION_DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.PAYMENT
) UNION ALL
(SELECT T1.CASE_FILE_ID, NULL as INITIATED_DATE, NULL as INSPECTION_DATE,
NULL as PAYMENT_DATE, ACTION as ACTION_DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.ACTION
)
) a
GROUP BY CASE_FILE_ID, seqnum;
Hmmm, a closely related solution is easier to maintain:
SELECT CASE_FILE_ID,
MAX(CASE WHEN type = 'INITIATED' THEN DATE END) as INITIATED_DATE,
MAX(CASE WHEN type = 'INSPECTION' THEN DATE END) as INSPECTION_DATE,
MAX(CASE WHEN type = 'PAYMENT' THEN DATE END) as PAYMENT_DATE,
MAX(CASE WHEN type = 'ACTION' THEN DATE END) as ACTION
FROM ((SELECT A.CASE_FILE_ID, NULL as TYPE, NULL as DATE,
1 as seqnum
FROM RECORDS.CASE_FILE A
) UNION ALL
(SELECT T1.CASE_FILE_ID, 'INSPECTION', DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.INITIATE
) UNION ALL
(SELECT T1.CASE_FILE_ID, 'INSPECTION', DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.INSPECTION
) UNION ALL
(SELECT T1.CASE_FILE_ID, 'PAYMENT', DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.PAYMENT
) UNION ALL
(SELECT T1.CASE_FILE_ID, 'ACTION', DATE,
ROW_NUMBER() OVER (PARTITION BY CASE_FILE_ID ORDER BY DATE) as seqnum
FROM RECORDS.ACTION
)
) a
GROUP BY CASE_FILE_ID, seqnum;
I have a table Supplier with two columns, TotalStock and Date. I'm trying to write a single query that will give me stock totals by week / month / year for a list of suppliers.
So results will look like this..
SUPPLIER WEEK MONTH YEAR
SupplierA 50 100 2000
SupplierB 60 150 2500
SupplierC 15 25 200
So far I've been playing around with multiple selects but I can't get any further than this:
SELECT Supplier,
(
SELECT Sum(TotalStock)
FROM StockBreakdown
WHERE Date >= '2014-5-12'
GROUP BY Supplier
) AS StockThisWeek,
(
SELECT Sum(TotalStock)
FROM StockBreakdown
WHERE Date >= '2014-5-1'
GROUP BY Supplier
) AS StockThisMonth,
(
SELECT Sum(TotalStock)
FROM StockBreakdown
WHERE Date >= '2014-1-1'
GROUP BY Supplier
) AS StockThisYear
This query throws an error as each individual grouping returns multiple results. I feel that I'm close to the solution but can't work out where to go
You don't have to use subqueries to achieve what you want :
SELECT Supplier
, SUM(CASE WHEN Date >= CAST('2014-05-12' as DATE) THEN TotalStock END) AS StockThisWeek
, SUM(CASE WHEN Date >= CAST('2014-05-01' as DATE) THEN TotalStock END) AS StockThisMonth
, SUM(CASE WHEN Date >= CAST('2014-01-01' as DATE) THEN TotalStock END) AS StockThisYear
FROM StockBreakdown
GROUP BY Supplier
You may need to make the selects for the columns return only a single result. You could try this (not tested currently):
SELECT Supplier,
(
SELECT TOP 1 StockThisWeek FROM
(
SELECT Supplier, Sum(TotalStock) AS StockThisWeek
FROM StockBreakdown
WHERE Date >= '2014-5-12'
GROUP BY Supplier
) tmp1
WHERE tmp1.Supplier = Supplier
) AS StockThisWeek,
(
SELECT TOP 1 StockThisMonth FROM
(
SELECT Supplier, Sum(TotalStock) AS StockThisMonth
FROM StockBreakdown
WHERE Date >= '2014-5-1'
GROUP BY Supplier
) tmp2
WHERE tmp2.Supplier = Supplier
) AS StockThisMonth,
...
This selects the supplier and then tries to create two columns StockThisWeek and StockThisMonth by selecting the first entry from the select you created before. As through the GROUP BY there should only be one entry per supplier, so you don't lose and data.