I have 'TABLE_A' like this:
TVA Amount InvoiceID
----------------------
22 | 10.00 | inv-12
22 |-14.00 | inv-13
25 | 24.00 | inv-14
25 |-36.00 | inv-15
25 |-25.00 | inv-16
25 | 18.50 | inv-17
24 |-16.50 | inv-18
24 | 10.00 | inv-19
The goal is to make a groupBy TABLE_A.TVA value and by SUM(TABLE_A.Amount) > 0 and SUM(TABLE_A.Amount) <0, to get finally the sum of all positive Amounts grouped by TVA value, and the sum of all negative amounts grouped by their TVA value also
my Query is like this:
SELECT TABLE_A.TVA, TABLE_A.InvoiceID,
SUM(TABLE_A.Amount) AS [PositiveTotalAMount],
SUM(TABLE_A.Amount) AS [NegativeTotalAMount]
FROM TABLE_A
GROUP BY TABLE_A.TVA
HAVING SUM(TABLE_A.TVA) > 0
MY question is how to add the second grouping by on negative values, because here i group only on SUM() > 0
You can use a CASE (Transact-SQL) expression:
SELECT
A.TVA,
A.InvoiceID,
SUM(CASE WHEN A.Amount > 0 THEN A.Amount ELSE 0 END) AS [PositiveTotalAMount],
SUM(CASE WHEN A.Amount < 0 THEN A.Amount ELSE 0 END) AS [NegativeTotalAMount]
FROM
TABLE_A A
GROUP BY
A.TVA,
A.InvoiceID
Also, you must include all columns from the select list that are not aggregated to the GROUP BY list. InvoiceID was missing.
I also use the alias A for TABLE_A to increase readability.
With conditional aggregation:
SELECT
TABLE_A.TVA,
SUM(CASE WHEN TABLE_A.Amount > 0 THEN TABLE_A.Amount ELSE 0 END) AS [PositiveTotalAMount],
SUM(CASE WHEN TABLE_A.Amount < 0 THEN TABLE_A.Amount ELSE 0 END) AS [NegativeTotalAMount]
FROM TABLE_A
GROUP BY TABLE_A.TVA
If you want to include the column TABLE_A.InvoiceID in the grouping then:
SELECT
TABLE_A.TVA,
TABLE_A.InvoiceID,
SUM(CASE WHEN TABLE_A.Amount > 0 THEN TABLE_A.Amount ELSE 0 END) AS [PositiveTotalAMount],
SUM(CASE WHEN TABLE_A.Amount < 0 THEN TABLE_A.Amount ELSE 0 END) AS [NegativeTotalAMount]
FROM TABLE_A
GROUP BY TABLE_A.TVA, TABLE_A.InvoiceID
Related
I have the following SQL query:
SELECT
modal_text,
COUNT(CASE WHEN ab_group = "control" THEN 1 ELSE 0 END)
FROM
onboarding_modals
GROUP BY
1
ORDER BY
1;
This doesn't work as expected (it will count more than expected), but when I remove the ELSE 0 in aggregate function, it works as expected:
SELECT
modal_text, COUNT(CASE WHEN ab_group = "control" THEN 1 END)
FROM
onboarding_modals
GROUP BY
1
ORDER BY
1;
Could someone explain me why having the ELSE 0 will make it count more data than it should be?
*It will also work if I use ELSE NULL
Because a COUNT(SomeColumn) doesn't count the NULL's in a column.
COUNT(1) or COUNT(*) count the rows.
And so does a COUNT(CASE WHEN x=1 THEN 1 ELSE 0 END)
This has no NULL's to ignore, because it's either 1 or 0.
But a CASE WHEN x=1 THEN 1 END
is just the implicit shorter syntax for
CASE WHEN x=1 THEN 1 ELSE NULL END
So it's normal to COUNT without the ELSE.
COUNT(DISTINCT CASE WHEN x=1 THEN t.ID END)
If you do want to use an ELSE, then do it with a SUM
SUM(CASE WHEN x=1 THEN 1 ELSE 0 END)
Use SUM() instead of COUNT(), as in:
SELECT
modal_text,
SUM(CASE WHEN ab_group = "control" THEN 1 ELSE 0 END)
FROM
onboarding_modals
GROUP BY
1
ORDER BY
1;
Could someone explain me why having the ELSE 0 will make it count more data than it should be?
Becasue COUNT(CASE WHEN ab_group = "control" THEN 1 ELSE 0 END) is different to COUNT(CASE WHEN ab_group = "control" THEN 1 END) let's see a sample below
we can see there will be count when we use count(1) or count(0) except count(null) count function will not be count when the value is null
Query 1:
SELECT COUNT(1)
| COUNT(1) |
|----------|
| 1 |
SELECT COUNT(0)
| COUNT(0) |
|----------|
| 1 |
SELECT COUNT(NULL)
| COUNT(NULL) |
|-------------|
| 0 |
Query 2:
SELECT SUM(1)
| SUM(1) |
|--------|
| 1 |
SELECT SUM(0)
| SUM(0) |
|--------|
| 0 |
SELECT SUM(NULL)
| SUM(NULL) |
|-----------|
| (null) |
Results:
I'm gonna to make a SUM function with these columns of Profile table when each column is greater than 1.
How can I do it?
bank docs personal
2 1 2
The following counts the rows where the values are greater than 1:
select sum(case when bank > 1 then 1 else 0 end) as bank,
sum(case when docs > 1 then 1 else 0 end) as docs,
sum(case when personal > 1 then 1 else 0 end) as personal
from Profile;
The following counts the number of columns within a row with values greater than 1:
select p.*,
(case when bank > 1 then 1 else 0 end +
case when docs > 1 then 1 else 0 end +
case when personal > 1 then 1 else 0 end
) as cnt
from Profile p;
These are the two most sensible interpretations of our question.
The sum of rows where each column value is greater than one:
select sum(bank + docs + personal)
from Profile
where bank > 1 and docs > 1 and personal > 1
;
with t as (
select 0 as v0, 1 as v1 from dual
union all select 3 as v0, 2 as v1 from dual
)
select sum(v0 + v1)
from t
where v0 > 1 and v1 > 1
;
| SUM(V0+V1) |
| ---------: |
| 5 |
db<>fiddle here
The sum of each individual column when the column is greater than 1: (untested)
select sum(case when isnull(bank,0) > 1 then bank else 0 end) banktotal
,sum(case when isnull(docs,0) > 1 then docs else 0 end) docstotal
,sum(case when isnull(personal,0) > 1 then personal else 0 end) personaltotal
from Profile
isnull() may or may not be needed based on your data and table design.
I am trying to generate a report, and so far have one completed that gives me how many orders, for each day, are in status 1-9.
TableA structure looks like this:
Sales Order | Order Status | Order Date
123456789 | 1 | 2017-02-22 00:00:00.000
123456790 | 0 | 2017-02-21 00:00:00.000
TableB structure looks like this:
Sales Order | Price
123456789 | 123.00
123456789 | 42.00
123456790 | 56.00
123456790 | 28.00
This code:
SELECT
MAX(year([OrderDate])) as Yr,
MAX(MONTH([OrderDate])) as M,
Day([OrderDate]) as Day,
sum(case when [OrderStatus]='0' THEN 1 ELSE 0 END) AS 'STATUS"0"',
sum(case when [OrderStatus]='1' THEN 1 ELSE 0 END) AS 'STATUS"1"',
sum(case when [OrderStatus]='2' THEN 1 ELSE 0 END) AS 'STATUS"2"',
sum(case when [OrderStatus]='4' THEN 1 ELSE 0 END) AS 'STATUS"4"',
sum(case when [OrderStatus]='8' THEN 1 ELSE 0 END) AS 'STATUS"8"',
sum(case when [OrderStatus]='9' THEN 1 ELSE 0 END) AS 'STATUS"9"',
sum(case when [OrderStatus]='S' THEN 1 ELSE 0 END) AS 'STATUS"S"',
sum(case when [OrderStatus]='*' THEN 1 ELSE 0 END) AS 'STATUS"*"',
sum(case when [OrderStatus]='/' THEN 1 ELSE 0 END) AS 'STATUS"/"'
FROM
SorMaster
WHERE
YEAR([OrderDate]) = YEAR(GETDATE())
GROUP BY
DATENAME(month, DateAdd(month, Month([OrderDate]) - 1, Cast('2008-01-01' AS Datetime))), Day([OrderDate])
ORDER BY
Yr DESC, M DESC, Day DESC
Returns this:
Yr | M | Day | STATUS"0" | STATUS"1" | STATUS"2" | STATUS"4" | STATUS"8" | STATUS"9" | STATUS"S" | STATUS"*" | STATUS"/"
2017 2 22 0 2 0 1 0 0 5 0 0
2017 2 21 0 0 0 7 0 0 0 0 0
This is PERFECT for my first report.
Now, comes the trouble. My Problem is that I need to nest-query Table B, so that instead of returning a count(orders), I need the sum(orders) those totals for each order are in Table B.
Using the above example, the query would need to return something like this:
Yr | M | Day | STATUS"0" | STATUS"1" | STATUS"2" | STATUS"4" | STATUS"8" | STATUS"9" | STATUS"S" | STATUS"*" | STATUS"/"
2017 2 22 0 165 0 0 0 0 0 0 0
2017 2 21 84 0 0 0 0 0 0 0 0
Any pointers?
Just join to TableB:
SELECT MAX(year([t1.OrderDate])) AS Yr,
MAX(MONTH([t2.OrderDate])) AS M,
DAY([t1.OrderDate]) AS Day,
SUM(CASE WHEN [OrderStatus] = '0' THEN t2.Price ELSE 0 END) AS 'STATUS"0"',
SUM(CASE WHEN [OrderStatus] = '1' THEN t2.Price ELSE 0 END) AS 'STATUS"1"',
SUM(CASE WHEN [OrderStatus] = '2' THEN t2.Price ELSE 0 END) AS 'STATUS"2"',
SUM(CASE WHEN [OrderStatus] = '4' THEN t2.Price ELSE 0 END) AS 'STATUS"4"',
SUM(CASE WHEN [OrderStatus] = '8' THEN t2.Price ELSE 0 END) AS 'STATUS"8"',
SUM(CASE WHEN [OrderStatus] = '9' THEN t2.Price ELSE 0 END) AS 'STATUS"9"',
SUM(CASE WHEN [OrderStatus] = 'S' THEN t2.Price ELSE 0 END) AS 'STATUS"S"',
SUM(CASE WHEN [OrderStatus] = '*' THEN t2.Price ELSE 0 END) AS 'STATUS"*"',
SUM(CASE WHEN [OrderStatus] = '/' THEN t2.Price ELSE 0 END) AS 'STATUS"/"'
FROM SorMaster t1
LEFT JOIN TableB t2
ON t1.[Sales Order] = t2.[Sales Order]
WHERE YEAR([OrderDate]) = YEAR(GETDATE())
GROUP BY DATENAME(month,DateAdd(month,Month([OrderDate])-1,Cast('2008-01-01' AS Datetime))),
DAY([OrderDate])
ORDER BY Yr DESC, M DEACLLSC, Day DESC
That's not too difficult, just a matter of LEFT JOINing in table B and then summing the prices in that. There's a couple of small tricks here. You want to LEFT JOIN to ensure that rows in table A always show up, even if there are no corresponding rows in table B. Secondly, in your SUM() statement, you'll need to add a COALESCE(...,0.00) to ensure you're summing decimals and no NULL values creep in from the LEFT JOIN. Oddly in databases, NULL + {anything} = NULL.
For the below query, you'll need to change the name of TableB to whatever the table name is, and the JOIN predicate will need to have the column names named accurately, and delimited correctly if they contain spaces. For example, in MSSQL the delimiters are [ and ], e.g. MyTable.[My Column With Spaces]
SELECT
MAX(YEAR([OrderDate])) as Yr,
MAX(MONTH([OrderDate])) as M,
DAY([OrderDate]) as Day,
sum(case when [OrderStatus]='0' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"0"',
sum(case when [OrderStatus]='1' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"1"',
sum(case when [OrderStatus]='2' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"2"',
sum(case when [OrderStatus]='4' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"4"',
sum(case when [OrderStatus]='8' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"8"',
sum(case when [OrderStatus]='9' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"9"',
sum(case when [OrderStatus]='S' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"S"',
sum(case when [OrderStatus]='*' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"*"',
sum(case when [OrderStatus]='/' THEN COALESCE(TableB.Price, 0.00) ELSE 0.00 END) AS 'STATUS"/"'
FROM SorMaster
LEFT OUTER JOIN TableB
ON TableB.SalesOrder = SorMaster.SalesOrder
WHERE YEAR([OrderDate]) = YEAR(GETDATE())
GROUP BY
DATENAME(month,DateAdd(month,Month([OrderDate])-1,Cast('2008-01-01' AS Datetime))),
DAY([OrderDate])
ORDER BY
Yr DESC,
M DESC,
Day DESC
By (left) joining tableB and replacing your 'count' ones by tableB.price you should get the sum of all positions of orders with the according status.
I have a huge database with over 4 million rows that look like that:
Customer ID Shop
1 Asda
1 Sainsbury
1 Tesco
2 TEsco
2 Tesco
I need to count customers that within last 4 weeks had shopped in all 3 shops Tesco Sainsbury and Asda. Can you please advice if its possible to do it with subqueries?
This is an example of a "set-within-sets" subquery. You can solve it with aggregation:
select customer_id
from Yourtable t
where <shopping date within last four weeks>
group by customer_id
having sum(case when shop = 'Asda' then 1 else 0 end) > 0 and
sum(case when shop = 'Sainsbury' then 1 else 0 end) > 0 and
sum(case when shop = 'Tesco' then 1 else 0 end) > 0;
This structure is quite flexible. So if you wanted Asda and Tesco but not Sainsbury, then you would do:
select customer_id
from Yourtable t
where <shopping date within last four weeks>
group by customer_id
having sum(case when shop = 'Asda' then 1 else 0 end) > 0 and
sum(case when shop = 'Sainsbury' then 1 else 0 end) = 0 and
sum(case when shop = 'Tesco' then 1 else 0 end) > 0;
EDIT:
If you want a count, then use this as a subquery and count the results:
select count(*)
from (select customer_id
from Yourtable t
where <shopping date within last four weeks>
group by customer_id
having sum(case when shop = 'Asda' then 1 else 0 end) > 0 and
sum(case when shop = 'Sainsbury' then 1 else 0 end) > 0 and
sum(case when shop = 'Tesco' then 1 else 0 end) > 0
) t
I am finding difficulty to frame a select query.
PFB, for the table and corresponding data:
ID DLS MATCH_STATUS LAST_UPDATE_TIME BO CH FT
1 0 0 09-07-2013 00:00:00 IT TE NA
1 1 1 09-07-2013 00:01:01 IT TE NA
2 0 0 09-07-2013 10:00:00 IP TE NA
3 0 0 09-07-2013 11:00:00 IT YT NA
3 2 2 09-07-2013 11:01:00 IT YT NA
Here
Match_Status 0-->Initial Record
1-->Singel Match
2-->Multi Match
For every record there will be a initial entry with match_status 0 and subsequent matching process end other number such as 1,2 will be update.
I am trying to retrieve records such as total record , waiting match ,single match and multi match group by BO, CH and FT
Below is the expected out put:
BO CH FT TOTAL_RECORD AWAITNG_MATCH SINGLE_MATCH MULTI_MATCH
IT TE NA 1 0 1 0
IP TE NA 1 1 0 0
IT YT NA 1 0 0 2
I have tried below query :
select BO,CH,FT,sum(case when match_status=0 then 1 else 0 end) as TOTAL_RECORD,
sum(case when match_status = 0 then 1 else 0 end) as AWAITING_MATCH,
sum(case when match_status = 1 then 1 else 0 end) as SINGLE_MATCH,
sum(case when match_status = 2 then 1 else 0 end) as MULTI_MATCH from
table1 where last_update_time >= current_timestamp-1
group by BO,CH,FT;
problem with the above query is, awaiting_match is getting populated same as total record as I understand because of match_status=0
Similarly I tried with
select BO,CH,FT,sum(case when match_status=0 then 1 else 0 end) as TOTAL_RECORD,
select (sum(case when t1.ms=0 then 1 else 0 end) from
(select max(match_status) as ms from table1 where last_update_time >= current_timestamp-1 group by id)t1) )awaiting_match,
sum(case when match_status = 1 then 1 else 0 end) as SINGLE_MATCH,
sum(case when match_status = 2 then 1 else 0 end) as MULTI_MATCH from
table1 where last_update_time >= current_timestamp-1
group by BO,CH,FT;
problem with the approach is awaiting_match is getting populated with the same value for subsequent row entry.
Please help me with a suitable query for the desired format.
Thanks a lot in advance.
It seems that you want the last match status. I am guessing that this is actually the maximum of the statuses. If so, the following solves the problem by first grouping on id and then doing the grouping to summarize:
select BO, CH, FT,
count(*) as TOTAL_RECORD,
sum(case when lastms = 0 then 1 else 0 end) as AWAITING_MATCH,
sum(case when lastms = 1 then 1 else 0 end) as SINGLE_MATCH,
sum(case when lastms = 2 then 1 else 0 end) as MULTI_MATCH
from (select id, bo, ch, ft, MAX(match_status) as lastms
from table1
where last_update_time >= current_timestamp-1
group by id, bo, ch, ft
) t
group by BO, CH, FT;
If you actually want the last update to provide the status for the id, then you can use row_number() to enumerate the rows for each id, order by update time descending, and choose the first one:
select BO, CH, FT,
count(*) as TOTAL_RECORD,
sum(case when lastms = 0 then 1 else 0 end) as AWAITING_MATCH,
sum(case when lastms = 1 then 1 else 0 end) as SINGLE_MATCH,
sum(case when lastms = 2 then 1 else 0 end) as MULTI_MATCH
from (select id, bo, ch, ft, match_status,
ROW_NUMBER() over (partition by id order by last_update_time desc) as seqnum
from table1
where last_update_time >= current_timestamp-1
) t
where seqnum = 1
group by BO, CH, FT;