How to get summary based on another table group summary? - sql

Business Rules: Get total cust_points for customer only if total(trans_amount) for a trans_code grouping > 0.
For customer #1, the summary at date_code level (code 10) is > 0 so cust_points total = 70.
For customer #2 only code 20 group totals > 0 so total only 75 total cust_points
Here's my query:
with customers as
(select '1' as cust_id, 10 as date_code, 30 as cust_points from dual union all
select '1' as cust_id, 10 as date_code, 40 as cust_points from dual union all
select '1' as cust_id, 20 as date_code, 22 as cust_points from dual union all --These points should not total because trans_amount sum for code 20 is less than 0
select '1' as cust_id, 40 as date_code, 33 as cust_points from dual union all -- These points should not total because there is not trans_amounts > 0 for date_code
select '2' as cust_id, 10 as date_code, 20 as cust_points from dual union all
select '2' as cust_id, 20 as date_code, 65 as cust_points from dual union all
select '2' as cust_id, 20 as date_code, 10 as cust_points from dual
),
transactions_row as
(
select '1' as cust_id, '10' as trans_code, 10.00 as trans_amount from dual union all
select '1' as cust_id, '20' as trans_code, -15.00 as trans_amount from dual union all
select '1' as cust_id, '20' as trans_code, -20.00 as trans_amount from dual union all
select '1' as cust_id, '20' as trans_code, -10.00 as trans_amount from dual union all
select '1' as cust_id, '30' as trans_code, 30.00 as trans_amount from dual union all
select '1' as cust_id, '20' as trans_code, -20.00 as trans_amount from dual union all
select '2' as cust_id, '10' as trans_code, -50.00 as trans_amount from dual union all
select '2' as cust_id, '20' as trans_code, 20.00 as trans_amount from dual
)
select cust_id,
sum(cust_points)
from customers
where cust_id in
(
select cust_id
from (
select cust_id, trans_code, sum(trans_amount)
from transactions_row
group by cust_id, trans_code
having sum(trans_amount) > 0
)
)
group by cust_id
Desired Results
CUST_ID CUST_POINTS
1 70 /* (30 because total trans_amount for tran_code(10) > 0 +
40 because total trans_amount for tran_code(10) > 0) */
2 75 /* Do not include the 20 points because total trans_amt for 10 < 0 */


Here's one way using exists:
select cust_id,
sum(cust_points)
from customers c
where exists (
select 1
from transactions_row tr
where tr.trans_code = c.date_code
and tr.cust_id = c.cust_id
group by tr.trans_code, tr.cust_id
having sum(tr.trans_amount) > 0
)
group by cust_id
SQL Fiddle Demo

Related

SQL select lapsed customers with 30 day frequency by day

The goal is to select the count of distinct customer_id's who have not made a purchase in the rolling 30 day period prior to every day in the calendar year 2016. I have created a calendar table in my database to join to.
Here is an example table for reference, let's say you have customers orders normalized as follows:
+-------------+------------+----------+
| customer_id | date | order_id |
+-------------+------------+----------+
| 123 | 01/25/2016 | 1000 |
+-------------+------------+----------+
| 123 | 04/27/2016 | 1025 |
+-------------+------------+----------+
| 444 | 02/02/2016 | 1010 |
+-------------+------------+----------+
| 521 | 01/23/2016 | 998 |
+-------------+------------+----------+
| 521 | 01/24/2016 | 999 |
+-------------+------------+----------+
The goal output is effectively a calendar with 1 row for every single day of 2016 with a count on each day of how many customers "lapsed" on that day, meaning their last purchase was 30 days or more prior from that day of the year. The final output will look like this:
+------------+--------------+
| date | lapsed_count |
+------------+--------------+
| 01/01/2016 | 0 |
+------------+--------------+
| 01/02/2016 | 0 |
+------------+--------------+
| ... | ... |
+------------+--------------+
| 03/01/2016 | 12 |
+------------+--------------+
| 03/02/2016 | 9 |
+------------+--------------+
| 03/03/2016 | 7 |
+------------+--------------+
This data does not exist in 2015, therefore it's not possible for Jan-01-2016 to have a count of lapsed customers because that is the first possible day to ever make a purchase.
So for customer_id #123, they purchased on 01/25/2016 and 04/27/2016. They should have 2 lapse counts because their purchases are more than 30 days apart. One lapse occurring on 2/24/2016 and another lapse on 05/27/2016.
Customer_id#444 only purchased once, so they should have one lapse count for 30 days after 02/02/2016 on 03/02/2016.
Customer_id#521 is tricky, since they purchased with a frequency of 1 day we will not count the first purchase on 03/02/2016, so there is only one lapse starting from their last purchase of 03/03/2016. The count for the lapse will occur on 04/02/2016 (+30 days).

If you have a table of dates, here is one expensive method:
select date,
sum(case when prev_date < date - 30 then 1 else 0 end) as lapsed
from (select c.date, o.customer_id, max(o.date) as prev_date
from calendar c cross join
(select distinct customer_id from orders) c left join
orders o
on o.date <= c.date and o.customer_id = c.customer_id
group by c.date, o.customer_id
) oc
group by date;
For each date/customer pair, it determines the latest purchase the customer made before the date. It then uses this information to count the lapsed.
To be honest, this will probably work well on a handful of dates, but not for a full year's worth.

Apologies, I didn't read your question properly the first time around. This query will give you all the lapses you have. It takes each order and uses an analytic function to work out the next order date - if the gap is greater than 30 days then a lapse is recorded
WITH
cust_orders (customer_id , order_date , order_id )
AS
(SELECT 1, TO_DATE('01/01/2016','DD/MM/YYYY'), 1001 FROM dual UNION ALL
SELECT 1, TO_DATE('29/01/2016','DD/MM/YYYY'), 1002 FROM dual UNION ALL
SELECT 1, TO_DATE('01/03/2016','DD/MM/YYYY'), 1003 FROM dual UNION ALL
SELECT 2, TO_DATE('01/01/2016','DD/MM/YYYY'), 1004 FROM dual UNION ALL
SELECT 2, TO_DATE('29/01/2016','DD/MM/YYYY'), 1005 FROM dual UNION ALL
SELECT 2, TO_DATE('01/04/2016','DD/MM/YYYY'), 1006 FROM dual UNION ALL
SELECT 2, TO_DATE('01/06/2016','DD/MM/YYYY'), 1007 FROM dual UNION ALL
SELECT 2, TO_DATE('01/08/2016','DD/MM/YYYY'), 1008 FROM dual UNION ALL
SELECT 3, TO_DATE('01/09/2016','DD/MM/YYYY'), 1009 FROM dual UNION ALL
SELECT 3, TO_DATE('01/12/2016','DD/MM/YYYY'), 1010 FROM dual UNION ALL
SELECT 3, TO_DATE('02/12/2016','DD/MM/YYYY'), 1011 FROM dual UNION ALL
SELECT 3, TO_DATE('03/12/2016','DD/MM/YYYY'), 1012 FROM dual UNION ALL
SELECT 3, TO_DATE('04/12/2016','DD/MM/YYYY'), 1013 FROM dual UNION ALL
SELECT 3, TO_DATE('05/12/2016','DD/MM/YYYY'), 1014 FROM dual UNION ALL
SELECT 3, TO_DATE('06/12/2016','DD/MM/YYYY'), 1015 FROM dual UNION ALL
SELECT 3, TO_DATE('07/12/2016','DD/MM/YYYY'), 1016 FROM dual
)
SELECT
customer_id
,order_date
,order_id
,next_order_date
,order_date + 30 lapse_date
FROM
(SELECT
customer_id
,order_date
,order_id
,LEAD(order_date) OVER (PARTITION BY customer_id ORDER BY order_date) next_order_date
FROM
cust_orders
)
WHERE NVL(next_order_date,sysdate) - order_date > 30
;
Now join that to a set of dates and run a COUNT function (enter the year parameter as YYYY) :
WITH
cust_orders (customer_id , order_date , order_id )
AS
(SELECT 1, TO_DATE('01/01/2016','DD/MM/YYYY'), 1001 FROM dual UNION ALL
SELECT 1, TO_DATE('29/01/2016','DD/MM/YYYY'), 1002 FROM dual UNION ALL
SELECT 1, TO_DATE('01/03/2016','DD/MM/YYYY'), 1003 FROM dual UNION ALL
SELECT 2, TO_DATE('01/01/2016','DD/MM/YYYY'), 1004 FROM dual UNION ALL
SELECT 2, TO_DATE('29/01/2016','DD/MM/YYYY'), 1005 FROM dual UNION ALL
SELECT 2, TO_DATE('01/04/2016','DD/MM/YYYY'), 1006 FROM dual UNION ALL
SELECT 2, TO_DATE('01/06/2016','DD/MM/YYYY'), 1007 FROM dual UNION ALL
SELECT 2, TO_DATE('01/08/2016','DD/MM/YYYY'), 1008 FROM dual UNION ALL
SELECT 3, TO_DATE('01/09/2016','DD/MM/YYYY'), 1009 FROM dual UNION ALL
SELECT 3, TO_DATE('01/12/2016','DD/MM/YYYY'), 1010 FROM dual UNION ALL
SELECT 3, TO_DATE('02/12/2016','DD/MM/YYYY'), 1011 FROM dual UNION ALL
SELECT 3, TO_DATE('03/12/2016','DD/MM/YYYY'), 1012 FROM dual UNION ALL
SELECT 3, TO_DATE('04/12/2016','DD/MM/YYYY'), 1013 FROM dual UNION ALL
SELECT 3, TO_DATE('05/12/2016','DD/MM/YYYY'), 1014 FROM dual UNION ALL
SELECT 3, TO_DATE('06/12/2016','DD/MM/YYYY'), 1015 FROM dual UNION ALL
SELECT 3, TO_DATE('07/12/2016','DD/MM/YYYY'), 1016 FROM dual
)
,calendar (date_value)
AS
(SELECT TO_DATE('01/01/'||:P_year,'DD/MM/YYYY') + (rownum -1)
FROM all_tables
WHERE rownum < (TO_DATE('31/12/'||:P_year,'DD/MM/YYYY') - TO_DATE('01/01/'||:P_year,'DD/MM/YYYY')) + 2
)
SELECT
calendar.date_value
,COUNT(*)
FROM
(
SELECT
customer_id
,order_date
,order_id
,next_order_date
,order_date + 30 lapse_date
FROM
(SELECT
customer_id
,order_date
,order_id
,LEAD(order_date) OVER (PARTITION BY customer_id ORDER BY order_date) next_order_date
FROM
cust_orders
)
WHERE NVL(next_order_date,sysdate) - order_date > 30
) lapses
,calendar
WHERE 1=1
AND calendar.date_value = TRUNC(lapses.lapse_date)
GROUP BY
calendar.date_value
;
Or if you really want every date printed out then use this :
WITH
cust_orders (customer_id , order_date , order_id )
AS
(SELECT 1, TO_DATE('01/01/2016','DD/MM/YYYY'), 1001 FROM dual UNION ALL
SELECT 1, TO_DATE('29/01/2016','DD/MM/YYYY'), 1002 FROM dual UNION ALL
SELECT 1, TO_DATE('01/03/2016','DD/MM/YYYY'), 1003 FROM dual UNION ALL
SELECT 2, TO_DATE('01/01/2016','DD/MM/YYYY'), 1004 FROM dual UNION ALL
SELECT 2, TO_DATE('29/01/2016','DD/MM/YYYY'), 1005 FROM dual UNION ALL
SELECT 2, TO_DATE('01/04/2016','DD/MM/YYYY'), 1006 FROM dual UNION ALL
SELECT 2, TO_DATE('01/06/2016','DD/MM/YYYY'), 1007 FROM dual UNION ALL
SELECT 2, TO_DATE('01/08/2016','DD/MM/YYYY'), 1008 FROM dual UNION ALL
SELECT 3, TO_DATE('01/09/2016','DD/MM/YYYY'), 1009 FROM dual UNION ALL
SELECT 3, TO_DATE('01/12/2016','DD/MM/YYYY'), 1010 FROM dual UNION ALL
SELECT 3, TO_DATE('02/12/2016','DD/MM/YYYY'), 1011 FROM dual UNION ALL
SELECT 3, TO_DATE('03/12/2016','DD/MM/YYYY'), 1012 FROM dual UNION ALL
SELECT 3, TO_DATE('04/12/2016','DD/MM/YYYY'), 1013 FROM dual UNION ALL
SELECT 3, TO_DATE('05/12/2016','DD/MM/YYYY'), 1014 FROM dual UNION ALL
SELECT 3, TO_DATE('06/12/2016','DD/MM/YYYY'), 1015 FROM dual UNION ALL
SELECT 3, TO_DATE('07/12/2016','DD/MM/YYYY'), 1016 FROM dual
)
,lapses
AS
(SELECT
customer_id
,order_date
,order_id
,next_order_date
,order_date + 30 lapse_date
FROM
(SELECT
customer_id
,order_date
,order_id
,LEAD(order_date) OVER (PARTITION BY customer_id ORDER BY order_date) next_order_date
FROM
cust_orders
)
WHERE NVL(next_order_date,sysdate) - order_date > 30
)
,calendar (date_value)
AS
(SELECT TO_DATE('01/01/'||:P_year,'DD/MM/YYYY') + (rownum -1)
FROM all_tables
WHERE rownum < (TO_DATE('31/12/'||:P_year,'DD/MM/YYYY') - TO_DATE('01/01/'||:P_year,'DD/MM/YYYY')) + 2
)
SELECT
calendar.date_value
,(SELECT COUNT(*)
FROM lapses
WHERE calendar.date_value = lapses.lapse_date
)
FROM
calendar
WHERE 1=1
ORDER BY
calendar.date_value
;

Here's how I'd do it:
WITH your_table AS (SELECT 123 customer_id, to_date('24/01/2016', 'dd/mm/yyyy') order_date, 12345 order_id FROM dual UNION ALL
SELECT 123 customer_id, to_date('24/01/2016', 'dd/mm/yyyy') order_date, 12346 order_id FROM dual UNION ALL
SELECT 123 customer_id, to_date('25/01/2016', 'dd/mm/yyyy') order_date, 12347 order_id FROM dual UNION ALL
SELECT 123 customer_id, to_date('24/02/2016', 'dd/mm/yyyy') order_date, 12347 order_id FROM dual UNION ALL
SELECT 123 customer_id, to_date('16/03/2016', 'dd/mm/yyyy') order_date, 12348 order_id FROM dual UNION ALL
SELECT 123 customer_id, to_date('18/04/2016', 'dd/mm/yyyy') order_date, 12349 order_id FROM dual UNION ALL
SELECT 456 customer_id, to_date('20/02/2016', 'dd/mm/yyyy') order_date, 12350 order_id FROM dual UNION ALL
SELECT 456 customer_id, to_date('01/03/2016', 'dd/mm/yyyy') order_date, 12351 order_id FROM dual UNION ALL
SELECT 456 customer_id, to_date('03/03/2016', 'dd/mm/yyyy') order_date, 12352 order_id FROM dual UNION ALL
SELECT 456 customer_id, to_date('18/04/2016', 'dd/mm/yyyy') order_date, 12353 order_id FROM dual UNION ALL
SELECT 456 customer_id, to_date('20/05/2016', 'dd/mm/yyyy') order_date, 12354 order_id FROM dual UNION ALL
SELECT 456 customer_id, to_date('23/06/2016', 'dd/mm/yyyy') order_date, 12355 order_id FROM dual UNION ALL
SELECT 456 customer_id, to_date('19/01/2017', 'dd/mm/yyyy') order_date, 12356 order_id FROM dual),
-- end of mimicking your_table with data in it
lapsed_info AS (SELECT customer_id,
order_date,
CASE WHEN TRUNC(SYSDATE) - order_date <= 30 THEN NULL
WHEN COUNT(*) OVER (PARTITION BY customer_id ORDER BY order_date RANGE BETWEEN 1 FOLLOWING AND 30 FOLLOWING) = 0 THEN order_date+30
ELSE NULL
END lapsed_date
FROM your_table),
dates AS (SELECT to_date('01/01/2016', 'dd/mm/yyyy') + LEVEL -1 dt
FROM dual
CONNECT BY to_date('01/01/2016', 'dd/mm/yyyy') + LEVEL -1 <= TRUNC(SYSDATE))
SELECT dates.dt,
COUNT(li.lapsed_date) lapsed_count
FROM dates
LEFT OUTER JOIN lapsed_info li ON dates.dt = li.lapsed_date
GROUP BY dates.dt
ORDER BY dates.dt;
Results:
DT LAPSED_COUNT
---------- ------------
01/01/2016 0
<snip>
23/01/2016 0
24/01/2016 0
25/01/2016 0
26/01/2016 0
<snip>
19/02/2016 0
20/02/2016 0
21/02/2016 0
22/02/2016 0
23/02/2016 0
24/02/2016 1
25/02/2016 0
<snip>
29/02/2016 0
01/03/2016 0
02/03/2016 0
03/03/2016 0
04/03/2016 0
<snip>
15/03/2016 0
16/03/2016 0
17/03/2016 0
<snip>
20/03/2016 0
21/03/2016 0
22/03/2016 0
<snip>
30/03/2016 0
31/03/2016 0
01/04/2016 0
02/04/2016 1
03/04/2016 0
<snip>
14/04/2016 0
15/04/2016 1
16/04/2016 0
17/04/2016 0
18/04/2016 0
19/04/2016 0
<snip>
17/05/2016 0
18/05/2016 2
19/05/2016 0
20/05/2016 0
21/05/2016 0
<snip>
18/06/2016 0
19/06/2016 1
20/06/2016 0
21/06/2016 0
22/06/2016 0
23/06/2016 0
24/06/2016 0
<snip>
22/07/2016 0
23/07/2016 1
24/07/2016 0
<snip>
18/01/2017 0
19/01/2017 0
20/01/2017 0
<snip>
08/02/2017 0
This takes your data, and uses an the analytic count function to work out the number of rows that have a value within 30 days of (but excluding) the current row's date.
Then we apply a case expression to determine that if the row has a date within 30 days of today's date, we'll count those as not lapsed. If a count of 0 was returned, then the row is considered lapsed and we'll output the lapsed date as the order_date plus 30 days. Any other count result means the row has not lapsed.
The above is all worked out in the lapsed_info subquery.
Then all we need to do is list the dates (see the dates subquery) and outer join the lapsed_info subquery to it based on the lapsed_date and then do a count of the lapsed dates for each day.

How to identify positive minimum or negative maximum in a column for a key?

I have the following columns - Person_ID Days. For one person id, multiple days are possible. Something like this:
Person_Id Days
1000 100
1000 200
1000 -50
1000 -10
1001 100
1001 200
1001 50
1001 10
1002 -50
1002 -10
I need to address the following scenarios:
If all values for days column are positive, I need minimum of the days for a person_id. If the days column has both positive and negative, I need minimum of positive. If all negatives, I need maximum of negative.
The output like:
Person_id Days
1000 100
1001 10
1002 -10
I tried using case statement, but I am unable to use a same column in the condition as well as grouping.

Try this (Postgres 9.4+):
select person_id, coalesce(min(days) filter (where days > 0), max(days))
from a_table
group by 1
order by 1;

Oracle Setup:
CREATE TABLE table_name ( Person_Id, Days ) AS
SELECT 1000, 100 FROM DUAL UNION ALL
SELECT 1000, 200 FROM DUAL UNION ALL
SELECT 1000, -50 FROM DUAL UNION ALL
SELECT 1000, -10 FROM DUAL UNION ALL
SELECT 1001, 100 FROM DUAL UNION ALL
SELECT 1001, 200 FROM DUAL UNION ALL
SELECT 1001, 50 FROM DUAL UNION ALL
SELECT 1001, 10 FROM DUAL UNION ALL
SELECT 1002, -50 FROM DUAL UNION ALL
SELECT 1002, -10 FROM DUAL;
Query:
SELECT person_id, days
FROM (
SELECT t.*,
ROW_NUMBER() OVER ( PARTITION BY person_id
ORDER BY SIGN( ABS( days ) ),
SIGN( DAYS ) DESC,
ABS( DAYS )
) AS rn
FROM table_name t
)
WHERE rn = 1;
Output:
PERSON_ID DAYS
---------- ----------
1000 100
1001 10
1002 -10

Oracle solution:
with
input_data ( person_id, days) as (
select 1000, 100 from dual union all
select 1000, 200 from dual union all
select 1000, -50 from dual union all
select 1000, -10 from dual union all
select 1001, 100 from dual union all
select 1001, 200 from dual union all
select 1001, 50 from dual union all
select 1001, 10 from dual union all
select 1002, -50 from dual union all
select 1002, -10 from dual
)
select person_id,
NVL(min(case when days > 0 then days end), max(days)) as days
from input_data
group by person_id;
PERSON_ID DAYS
---------- ----------
1000 100
1001 10
1002 -10
For each person_id, if there is at least one days value that is strictly positive, then the min will be taken over positive days only and will be returned by NVL(). Otherwise the min() will return null, and NVL() will return max() over all days (all of which are, in this case, negative or 0).

select Person_id, min(abs(days)) * days/abs(days) from table_name
group by Person_id
-- + handle zero_divide .. SORRY.. the above works only in MySQL .
Something like this will work anywhere which is equivalent of above query:
select t.Person_id , min(t.days) from table_name t,
(select Person_id, min(abs(days)) as days from table_name group by Person_id) v
where t.Person_id = v.Person_id
and abs(t days) = v.days
group by Person_id;
OR
select id, min(Days) from (
select Person_id, min(abs(Days)) as Days from temp group by Person_id
union
select Person_id, max(Days) as Days from temp group by Person_id
) temp
group by Person_id;

You can do this by using GroupBy clause in sql server. Take a look into below query:-
CREATE TABLE #test(Person_Id INT, [Days] INT)
DECLARE #LargestNumberFromTable INT;
INSERT INTO #test
SELECT 1000 , 100 UNION
SELECT 1000 , 200 UNION
SELECT 1000 , -50 UNION
SELECT 1000 , -10 UNION
SELECT 1001 , 100 UNION
SELECT 1001 , 200 UNION
SELECT 1001 , 50 UNION
SELECT 1001 , 10 UNION
SELECT 1002 , -50 UNION
SELECT 1002 , -10
SELECT #LargestNumberFromTable = ISNULL(MAX([Days]), 0)
FROM #test
SELECT Person_Id
,CASE WHEN SUM(IIF([Days] > 0,[Days] , 0)) = 0 THEN MAX([Days]) -- All Negative
WHEN SUM([Days]) = SUM(IIF([Days] > 0, [Days], 0)) THEN MIN ([Days]) -- ALL Positive
WHEN SUM([Days]) <> SUM(IIF([Days] > 0, [Days], 0)) THEN MIN(IIF([Days] > 0, [Days], #LargestNumberFromTable)) --Mix (Negative And positive)
END AS [Days]
FROM #test
GROUP BY Person_Id
DROP TABLE #test

How to get correct summaries with analytics?

I want to get summary numbers from the cust_detail table if a specific invoice_code appears in invoice_detail.
In this example, I'd like to report cust_detail summaries only for batches 10 and 20 because they are the ones with invoice_code='9999'. But the duplication in the invoice_detail table is skewing my numbers.
with
invoice_detail as
(
select '10' as invoice_batch, '9999' as invoice_code from dual union all
select '10' as invoice_batch, '9999' as invoice_code from dual union all
select '20' as invoice_batch, '1111' as invoice_code from dual union all
select '30' as invoice_batch, '9999' as invoice_code from dual
),
cust_detail as
(
select '1' as cust_id, '10' as invoice_batch, 40 as points_paid, 30 as points_earned, 30 as points_delivered from dual union all
select '1' as cust_id, '20' as invoice_batch, 10 as points_paid, 10 as points_earned, 10 as points_delivered from dual union all
select '1' as cust_id, '30' as invoice_batch, 20 as points_paid, 15 as points_earned, 5 as points_delivered from dual
)
select cust_id,
sum(points_paid) over (partition by c.invoice_batch
order by cust_id) batch_total
from cust_detail c
inner join invoice_detail i on c.invoice_batch=i.invoice_batch
where i.invoice_code = '9999';
Desired results:
CUST_ID PAID EARNED DELIVERED TOT_PAID TOT_EARNED TOT_DELIVERED
--------- ------ -------- ----------- ---------- ------------ ---------------
1 40 30 30 60 45 40
1 20 15 5 60 45 40

You can remove duplications from invoice_detail with distinct before join:
with invoice_detail as
(
select '10' as invoice_batch, '9999' as invoice_code from dual union all
select '10' as invoice_batch, '9999' as invoice_code from dual union all
select '20' as invoice_batch, '1111' as invoice_code from dual union all
select '30' as invoice_batch, '9999' as invoice_code from dual
),
cust_detail as
(
select '1' as cust_id, '10' as invoice_batch, 40 as points_paid, 30 as points_earned, 30 as points_delivered from dual union all
select '1' as cust_id, '20' as invoice_batch, 10 as points_paid, 10 as points_earned, 10 as points_delivered from dual union all
select '1' as cust_id, '30' as invoice_batch, 20 as points_paid, 15 as points_earned, 5 as points_delivered from dual
)
select cust_id
,points_paid
,points_earned
,points_delivered
,sum(points_paid) over (partition by c.cust_id) as tot_paid
,sum(points_earned) over (partition by c.cust_id) as tot_earned
,sum(points_delivered) over (partition by c.cust_id) as tot_delivered
from cust_detail c
join (select distinct * from invoice_detail) i
on c.invoice_batch=i.invoice_batch
where i.invoice_code = '9999';
Note that summaries include batches 10 and 30 because batch 20 with invoice_code='1111'.
SQL Fiddle

I am not sure what your desired results have to do with your query. But, I would expect your query to look more like this:
select cust_id,
sum(points_paid) over (partition by cust_id) as batch_total
from cust_detail c inner join
invoice_detail i
on c.invoice_batch=i.invoice_batch
where i.invoice_code = '9999' ;

How to calculate price change over 3 years in SQL query

I need to calculate the price change of an item (both in cost and % change) over the last three years.
The table has four fields:
SKU_no, Date_updated, Price, Active_flag
When the Active_flag field is A, the item is active, when I it is inactive. Some items haven't changed prices in years so they won't have three years of entries with an inactive flag.
Sample table
SKU_NO Update_date Price Active_flag
30 1/1/1999 40.8 I
33 1/1/2014 70.59 A
33 1/1/2013 67.23 I
33 1/1/2012 60.03 I
33 1/1/2011 55.08 I
33 1/1/2010 55.08 I
34 1/1/2009 51 A
36 1/1/2014 70.59 A
36 1/1/2013 67.23 I
36 1/1/2012 60.03 I
38 1/1/2002 43.32 A
38 1/1/2001 43.32 I
38 4/8/2000 43.32 I
38 1/1/1999 43.32 I
39 1/1/2014 73.08 A
39 1/1/2013 69.6 I
39 1/1/2012 62.13 I
39 1/1/2011 57 I
39 1/1/2010 57 I
39 1/1/2009 52.8 I
This is the first query I wrote. I'm not too familiar with complex calculations
select
s.VENDOR,
s.FISCAL_YEAR,
s.FISCAL_MONTH_NO,
s.FISCAL_YEAR||'_'||FISCAL_MONTH_NO as PERIOD,
CASE WHEN S.COST_USED_FLAG IN ('CONTRACT') THEN 'CONTRACT' ELSE 'NON-CONTRACT' END AS CONTRACT_TYPE,
CASE WHEN ((s.FISCAL_YEAR = 2014 AND FISCAL_MONTH_NO <=9) OR (FISCAL_YEAR = 2013 AND FISCAL_MONTH_NO >=10)) THEN 'CP_1'
WHEN ((s.FISCAL_YEAR = 2013 AND FISCAL_MONTH_NO <= 9) OR (FISCAL_YEAR = 2012 AND FISCAL_MONTH_NO >=10)) THEN 'CP_2'
WHEN ((s.FISCAL_YEAR = 2012 AND FISCAL_MONTH_NO <= 9) OR (FISCAL_YEAR = 2011 AND FISCAL_MONTH_NO >=10)) THEN 'CP_3'
ELSE 'NULL' END CAGR_PERIODS,
CASE WHEN s.MARKET IN ('PO', 'SC', 'OC') THEN 'PC' ELSE 'EC' END AS MARKET_TYPE,
s.MARKET,
s.COST_PLUS_FLAG,
s.COST_USED_FLAG,
LPAD(S.PC_ITEM_NO,6,'0') AS NEW_ITEM_NO,
s.PC_ITEM_NO,
i.ITEM_NO,
i.VEND_CAT_NUM,
i.DESCRIPTION,
s.PC_PROD_CAT,
s.PC_PROD_SUBCAT,
i.SELL_UOM,
i.QTY_PER_SELL_UOM,
i.PRIMARY_UOM,
i.HEAD_CONV_FACT,
SUM(s.QTY_EACH) AS QUANTITY_SOLD,
SUM(s.EXT_GROSS_COGS) AS TOTAL_COGS,
SUM(s.EXT_GROSS_COGS)/ SUM(s.QTY_EACH) as NET_SALES,
SUM(s.EXT_SALES)/ SUM(s.QTY_EACH) as ASP,
SUM(s.EXT_SALES) AS TOTAL_SALES,
SUM(S.EXT_SALES) - SUM(S.EXT_GROSS_COGS) as GROSS_PROFIT
from SIXSIGMA.CIA_ALL_SALES_TREND_DATA s
INNER JOIN MGMSH.ITEM i
ON S.PC_ITEM_NO = I.ITEM_NO
WHERE S.VENDOR = 'BD' AND
(S.EXT_SALES IS NOT NULL AND S.FISCAL_YEAR IN ('2013','2012','2011'))
GROUP BY
s.VENDOR,
s.FISCAL_YEAR,
s.FISCAL_MONTH_NO,
s.FISCAL_YEAR||'_'||FISCAL_MONTH_NO,
CASE WHEN s.MARKET IN ('PO', 'SC', 'OC') THEN 'PC' ELSE 'EC' END,
CASE WHEN S.COST_USED_FLAG IN ('CONTRACT') THEN 'CONTRACT' ELSE 'NON-CONTRACT' END,
CASE WHEN ((s.FISCAL_YEAR = 2014 AND FISCAL_MONTH_NO <=9) OR (FISCAL_YEAR = 2013 AND FISCAL_MONTH_NO >=10)) THEN 'CP_1'
WHEN ((s.FISCAL_YEAR = 2013 AND FISCAL_MONTH_NO <= 9) OR (FISCAL_YEAR = 2012 AND FISCAL_MONTH_NO >=10)) THEN 'CP_2'
WHEN ((s.FISCAL_YEAR = 2012 AND FISCAL_MONTH_NO <= 9) OR (FISCAL_YEAR = 2011 AND FISCAL_MONTH_NO >=10)) THEN 'CP_3'
ELSE 'NULL' END,
s.MARKET,
s.COST_USED_FLAG,
s.COST_PLUS_FLAG,
s.PC_ITEM_NO,
s.PC_PROD_CAT,
i.SELL_UOM,
i.QTY_PER_SELL_UOM,
i.PRIMARY_UOM,
i.HEAD_CONV_FACT,
i.DESCRIPTION,
i.VEND_CAT_NUM,
s.PC_PROD_SUBCAT,
i.ITEM_NO
ORDER BY s.PC_ITEM_NO,s.FISCAL_YEAR, s.FISCAL_MONTH_NO

There are several ways to approach this, but I would recommend a windowing function such as LAG or LEAD. With these functions, you can reference neighboring rows. For example:
lead(column, offset, default) over (partition by some_column order by column)
And in the example below:
lead(price, 1, price) over (partition by sku_no order by update_date desc)
Here is a working example with sample data:
with sample_data as (
select '30' sku_no, to_date('1/1/1999','DD/MM/YYYY') update_date, 40.8 price, 'I' active_flag from dual union all
select '33', to_date('1/1/2014','DD/MM/YYYY'), 70.59, 'A' from dual union all
select '33', to_date('1/1/2013','DD/MM/YYYY'), 67.23, 'I' from dual union all
select '33', to_date('1/1/2012','DD/MM/YYYY'), 60.03, 'I' from dual union all
select '33', to_date('1/1/2011','DD/MM/YYYY'), 55.08, 'I' from dual union all
select '33', to_date('1/1/2010','DD/MM/YYYY'), 55.08, 'I' from dual union all
select '34', to_date('1/1/2009','DD/MM/YYYY'), 51 , 'A' from dual union all
select '36', to_date('1/1/2014','DD/MM/YYYY'), 70.59, 'A' from dual union all
select '36', to_date('1/1/2013','DD/MM/YYYY'), 67.23, 'I' from dual union all
select '36', to_date('1/1/2012','DD/MM/YYYY'), 60.03, 'I' from dual union all
select '38', to_date('1/1/2002','DD/MM/YYYY'), 43.32, 'A' from dual union all
select '38', to_date('1/1/2001','DD/MM/YYYY'), 43.32, 'I' from dual union all
select '38', to_date('4/8/2000','DD/MM/YYYY'), 43.32, 'I' from dual union all
select '38', to_date('1/1/1999','DD/MM/YYYY'), 43.32, 'I' from dual union all
select '39', to_date('1/1/2014','DD/MM/YYYY'), 73.08, 'A' from dual union all
select '39', to_date('1/1/2013','DD/MM/YYYY'), 69.6 , 'I' from dual union all
select '39', to_date('1/1/2012','DD/MM/YYYY'), 62.13, 'I' from dual union all
select '39', to_date('1/1/2011','DD/MM/YYYY'), 57 , 'I' from dual union all
select '39', to_date('1/1/2010','DD/MM/YYYY'), 57 , 'I' from dual union all
select '39', to_date('1/1/2009','DD/MM/YYYY'), 52.8 , 'I' from dual)
select
sku_no,
update_date,
price,
lead(price,1, price) over (partition by sku_no order by update_date desc) prior_price, -- Showing the offset
price - lead(price,1, price) over (partition by sku_no order by update_date desc) price_difference, -- Calculate the difference
round((price - lead(price,1, price) over (partition by sku_no order by update_date desc)) * 100 /price, 2) percent_change -- Calculate the percentage
from sample_data
where update_date >= add_months(trunc(sysdate,'YYYY'),-36); -- You said in the last three years
You can also use LAG with a different order by sort. If you want to calculate the difference from three years prior, I would suggest using the KEEP function.

How do I write an SQL to get a cumulative value and a monthly total in one row?

Say, I have the following data:
select 1 id, date '2007-01-16' date_created, 5 sales, 'Bob' name from dual union all
select 2 id, date '2007-04-16' date_created, 2 sales, 'Bob' name from dual union all
select 3 id, date '2007-05-16' date_created, 6 sales, 'Bob' name from dual union all
select 4 id, date '2007-05-21' date_created, 4 sales, 'Bob' name from dual union all
select 5 id, date '2013-07-16' date_created, 24 sales, 'Bob' name from dual union all
select 6 id, date '2007-01-17' date_created, 15 sales, 'Ann' name from dual union all
select 7 id, date '2007-04-17' date_created, 12 sales, 'Ann' name from dual union all
select 8 id, date '2007-05-17' date_created, 16 sales, 'Ann' name from dual union all
select 9 id, date '2007-05-22' date_created, 14 sales, 'Ann' name from dual union all
select 10 id, date '2013-07-17' date_created, 34 sales, 'Ann' name from dual
I want to get results like the following:
Name Total_cumulative_sales Total_sales_current_month
Bob 41 24
Ann 91 34
In this table, for Bob, his total sales is 41 starting from the beginning. And for this month which is July, his sales for this entire month is 24. Same goes for Ann.
How do I write an SQL to get this result?

Try this way:
select name, sum(sales) as Total_cumulative_sales ,
sum(
case trunc(to_date(date_created), 'MM')
when trunc(sysdate, 'MM') then sales
else 0
end
) as Total_sales_current_month
from tab
group by name
SQL Fiddle Demo
More information
Trunc
Case Statement

SELECT Name,
SUM(Sales) Total_sales,
SUM(CASE WHEN MONTH(date_created) = MONTH(GetDate()) AND YEAR(date_created) = YEAR(GetDate()) THEN Sales END) Total_sales_current_month
GROUP BY Name
Should work, but there's probably a more elegant way to specify "in the current month".

This should work for sales over a number of years. It will get the cumulative sales over any number of years. It won't produce a record if there are no sales in the latest month.
WITH sales AS
(select 1 id, date '2007-01-16' date_created, 5 sales, 'Bob' sales_name from dual union all
select 2 id, date '2007-04-16' date_created, 2 sales, 'Bob' sales_name from dual union all
select 3 id, date '2007-05-16' date_created, 6 sales, 'Bob' sales_name from dual union all
select 4 id, date '2007-05-21' date_created, 4 sales, 'Bob' sales_name from dual union all
select 5 id, date '2013-07-16' date_created, 24 sales, 'Bob' sales_name from dual union all
select 6 id, date '2007-01-17' date_created, 15 sales, 'Ann' sales_name from dual union all
select 7 id, date '2007-04-17' date_created, 12 sales, 'Ann' sales_name from dual union all
select 8 id, date '2007-05-17' date_created, 16 sales, 'Ann' sales_name from dual union all
select 9 id, date '2007-05-22' date_created, 14 sales, 'Ann' sales_name from dual union all
select 10 id, date '2013-07-17' date_created, 34 sales, 'Ann' sales_name from dual)
SELECT sales_name
,total_sales
,monthly_sales
,mon
FROM (SELECT sales_name
,SUM(sales) OVER (PARTITION BY sales_name ORDER BY mon) total_sales
,SUM(sales) OVER (PARTITION BY sales_name,mon ORDER BY mon) monthly_sales
,mon
,max_mon
FROM ( SELECT sales_name
,sum(sales) sales
,mon
,max_mon
FROM (SELECT sales_name
,to_number(to_char(date_created,'YYYYMM')) mon
,sales
,MAX(to_number(to_char(date_created,'YYYYMM'))) OVER (PARTITION BY sales_name) max_mon
FROM sales
ORDER BY 2)
GROUP BY sales_name
,max_mon
,mon
)
)
WHERE max_mon = mon
;