I have the following table (Sample):
+----+--------+-------+------+------------+
| ID | WEIGHT | MONTH | YEAR | CATEGORYID |
+----+--------+-------+------+------------+
| 1 | 0.5 | 1 | 2014 | A |
| 1 | 0.5 | 1 | 2014 | A |
| 1 | 0.5 | 2 | 2014 | A |
| 1 | 0.2 | 2 | 2014 | C |
| 1 | 0.2 | 2 | 2014 | C |
| 2 | 1.0 | 2 | 2014 | B |
| 2 | 1.0 | 2 | 2014 | B |
+----+--------+-------+------+------------+
The Output I want would be like this (Sample):
+----+--------+-------+------+------------+
| ID | WEIGHT | MONTH | YEAR | CATEGORYID |
+----+--------+-------+------+------------+
| 1 | 1.5 | 1 | 2014 | A |
| 1 | 1.5 | 2 | 2014 | A |
| 1 | 0.4 | 1 | 2014 | C |
| 1 | 0.4 | 2 | 2014 | C |
| 2 | 2.0 | 2 | 2014 | B |
| 2 | 2.0 | 3 | 2014 | B |
+----+--------+-------+------+------------+
So, when the month breaks I still want to sum the weight from previous month into the current etc. I want to sum the weight on the specific ID & CategoryID.
Hope this works.
select DISTINCT ID,sum(WEIGHT) over (partition by categoryid order by categoryid) as WEIGHT,
MONTH,YEAR, CATEGORYID
from table;
Try this
SELECT ID,
Sum(s_weight)OVER(partition BY CATEGORYID, id),
MONTH,
YEAR,
CATEGORYID
FROM (SELECT ID,
Sum(weight) AS s_weight,
MONTH,
YEAR,
CATEGORYID
FROM Yourtable
GROUP BY ID,
MONTH,
YEAR,
CATEGORYID) a
Related
I have the below table
+------+------+---+---+---+
| type | year | a | b | c |
+------+------+---+---+---+
| x | 2015 | 1 | 1 | 1 |
| x | 2015 | 2 | 2 | 2 |
| x | 2017 | 3 | 3 | 3 |
| y | 2016 | 1 | 1 | 1 |
| y | 2017 | 2 | 2 | 2 |
| z | 2015 | 1 | 1 | 1 |
| z | 2016 | 3 | 3 | 3 |
+------+------+---+---+---+
The expected result must be as follows
+------+------+---+---+---+
| type | year | x | y | z |
+------+------+---+---+---+
| a | 2015 | 3 | 0 | 1 |
| a | 2016 | 0 | 1 | 3 |
| a | 2017 | 3 | 2 | 0 |
| b | 2015 | 3 | 2 | 0 |
| b | 2016 | 0 | 1 | 3 |
| b | 2017 | 3 | 2 | 0 |
| c | 2015 | 3 | 0 | 1 |
| c | 2016 | 0 | 1 | 3 |
| c | 2017 | 3 | 2 | 0 |
+------+------+---+---+---+
So far, I could write the following query to obtain the result using simple group by in a pivot table manner, but i need to display the result in the unpivot manner as my expected result shown as above.
select type, year, sum(a) as a, sum(b) as b, sum(c) as c from table group by type,year;
The result of the above query is a valuable result for me but in a different format
+------+------+---+---+---+
| type | year | a | b | c |
+------+------+---+---+---+
| x | 2015 | 3 | 3 | 3 |
| x | 2017 | 3 | 3 | 3 |
| y | 2016 | 1 | 1 | 1 |
| y | 2017 | 2 | 2 | 2 |
| z | 2015 | 1 | 1 | 1 |
| z | 2016 | 3 | 3 | 3 |
+------+------+---+---+---+
You can unpivot using union all and then reaggregate:
select col_type, year,
sum(case when type = 'x' then val end) as x,
sum(case when type = 'y' then val end) as y,
sum(case when type = 'z' then val end) as z
from (select type, year, 'a' as col_type, a as val from t union all
select type, year, 'b' as col_type, b as val from t union all
select type, year, 'c' as col_type, c as val from t
) x
group by col_type, year;
I want to calculate
(1) total sales amount
(2) number of distinct stores per product
in one query, if possible. Suppose we have data:
+-----------+---------+-------+--------+
| store | product | month | amount |
+-----------+---------+-------+--------+
| Anthill | A | 1 | 1 |
| Anthill | A | 2 | 1 |
| Anthill | A | 3 | 1 |
| Beetle | A | 1 | 1 |
| Beetle | A | 3 | 1 |
| Cockroach | A | 1 | 1 |
| Cockroach | A | 2 | 1 |
| Cockroach | A | 3 | 1 |
| Anthill | B | 1 | 1 |
| Beetle | B | 2 | 1 |
| Cockroach | B | 3 | 1 |
+-----------+---------+-------+--------+
I have tried this with no luck:
select
[product]
,[month]
,[amount]
,cnt_distinct_stores = count(distinct(stores))
from dbo.temp
group by
[product]
,[month]
order by 1,2
Would there be possible any combination of GROUP BY clause with window functions like SUM(amount) OVER(partition by [product],[month] ORDER BY [month] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
Try
SELECT product,
SUM(amount),
COUNT(DISTINCT store)
FROM dbo.temp
GROUP BY product
I have table like :
+-------+--------+----------+------------+-------+
| cd_hs | cd_cnt | name_cnt | dates | value |
+-------+--------+----------+------------+-------+
| 1 | 1 | aaa | 2018-06-01 | 50 |
| 1 | 2 | bbb | 2018-07-01 | 150 |
| 1 | 3 | ccc | 2018-08-01 | 20 |
| 1 | 1 | aaa | 2018-06-02 | 40 |
| 1 | 2 | bbb | 2018-07-02 | 70 |
| 1 | 3 | ccc | 2018-08-02 | 80 |
+-------+--------+----------+------------+-------+
Actually I have more data but I am just show the sample and what I want to do is
I want to group by cd_hs, name_cnt and based on year in dates column and do sum(value) but I have the 2 condition. First is to show value with condition cd_cnt with 1 and 2 and second condition cd_cnt without 1 and 2 so meaning I have much value other than 1 and 2 and do aliasing as other in one column
Expected Result :
+-------+------+----------+-------------+
| cd_hs | year | name_cnt | total_value |
+-------+------+----------+-------------+
| 1 | 2018 | aaa | 90 |
| 1 | 2018 | bbb | 220 |
| 1 | 2018 | other | 100 |
+-------+------+----------+-------------+
how can I do that? I am new in query and don't know what to do..
Your question is a bit confusing considering your spec doesn't seem to exactly line up with what you requested.
If the sample result you've provided is actually what you're looking for, a simple SUM and GROUP BY should do the trick here:
SELECT cd_hs, EXTRACT(YEAR from dates) as year, name_cnt, SUM(value_)
FROM foo
GROUP BY cd_hs, EXTRACT(YEAR from dates), name_cnt
Result:
| cd_hs | year | name_cnt | sum |
|-------|------|----------|-----|
| 1 | 2018 | aaa | 90 |
| 1 | 2018 | bbb | 220 |
| 1 | 2018 | ccc | 100 |
SQLFiddle
Since you mentioned you wanted two different totals with two separate conditions, you could use JOIN in conjunction with some well-crafted subqueries:
SELECT a.cd_hs, EXTRACT(YEAR FROM a.dates), a.name_cnt, COALESCE(b.total_a, 0) as "Total A", COALESCE(c.total_b, 0) as "Total B"
FROM foo a
LEFT JOIN (
SELECT b.cd_hs, b.name_cnt, EXTRACT(YEAR FROM b.dates), SUM(value_) as total_a
FROM foo b
WHERE b.cd_cnt NOT IN (1, 2)
GROUP BY b.cd_hs, b.name_cnt, EXTRACT(YEAR from b.dates)
) b ON a.cd_hs = b.cd_hs AND a.name_cnt = b.name_cnt
LEFT JOIN (
SELECT c.cd_hs, c.name_cnt, EXTRACT(YEAR FROM c.dates), SUM(value_) as total_b
FROM foo c
WHERE c.cd_cnt IN (1, 2)
GROUP BY c.cd_hs, c.name_cnt, EXTRACT(YEAR from c.dates)
) c ON a.cd_hs = c.cd_hs AND a.name_cnt = c.name_cnt
This particular solution is readable and will get you to the correct end result but will most likely not be scalable in its current form.
Result:
| cd_hs | date_part | name_cnt | Total A | Total B |
|-------|-----------|----------|---------|---------|
| 1 | 2018 | aaa | 0 | 90 |
| 1 | 2018 | bbb | 0 | 220 |
| 1 | 2018 | ccc | 100 | 0 |
| 1 | 2018 | aaa | 0 | 90 |
| 1 | 2018 | bbb | 0 | 220 |
| 1 | 2018 | ccc | 100 | 0 |
SQLFiddle
I'm trying to provide rolled up summaries of the following data including only the group in question as well as excluding the group. I think this can be done with a window function, but I'm having problems with getting the syntax down (in my case Hive SQL).
I want the following data to be aggregated
+------------+---------+--------+
| date | product | rating |
+------------+---------+--------+
| 2018-01-01 | A | 1 |
| 2018-01-02 | A | 3 |
| 2018-01-20 | A | 4 |
| 2018-01-27 | A | 5 |
| 2018-01-29 | A | 4 |
| 2018-02-01 | A | 5 |
| 2017-01-09 | B | NULL |
| 2017-01-12 | B | 3 |
| 2017-01-15 | B | 4 |
| 2017-01-28 | B | 4 |
| 2017-07-21 | B | 2 |
| 2017-09-21 | B | 5 |
| 2017-09-13 | C | 3 |
| 2017-09-14 | C | 4 |
| 2017-09-15 | C | 5 |
| 2017-09-16 | C | 5 |
| 2018-04-01 | C | 2 |
| 2018-01-13 | D | 1 |
| 2018-01-14 | D | 2 |
| 2018-01-24 | D | 3 |
| 2018-01-31 | D | 4 |
+------------+---------+--------+
Aggregated results:
+------+-------+---------+----+------------+------------------+----------+
| year | month | product | ct | avg_rating | avg_rating_other | other_ct |
+------+-------+---------+----+------------+------------------+----------+
| 2018 | 1 | A | 5 | 3.4 | 2.5 | 4 |
| 2018 | 2 | A | 1 | 5 | NULL | 0 |
| 2017 | 1 | B | 4 | 3.6666667 | NULL | 0 |
| 2017 | 7 | B | 1 | 2 | NULL | 0 |
| 2017 | 9 | B | 1 | 5 | 4.25 | 4 |
| 2017 | 9 | C | 4 | 4.25 | 5 | 1 |
| 2018 | 4 | C | 1 | 2 | NULL | 0 |
| 2018 | 1 | D | 4 | 2.5 | 3.4 | 5 |
+------+-------+---------+----+------------+------------------+----------+
I've also considered producing two aggregates, one with the product in question and one without, but having trouble with creating the appropriate joining key.
You can do:
select year(date), month(date), product,
count(*) as ct, avg(rating) as avg_rating,
sum(count(*)) over (partition by year(date), month(date)) - count(*) as ct_other,
((sum(sum(rating)) over (partition by year(date), month(date)) - sum(rating)) /
(sum(count(*)) over (partition by year(date), month(date)) - count(*))
) as avg_other
from t
group by year(date), month(date), product;
The rating for the "other" is a bit tricky. You need to add everything up and subtract out the current row -- and calculate the average by doing the sum divided by the count.
i hope my description will be enough. i tried to remove all non-significant fields.
i have 5 tables (Customer, Invoice, Items, Invoice_Item, Payment):
Customer fields and sample date are:
+----+------+
| ID | Name |
+----+------+
| 1 | John |
| 2 | Mary |
+----+------+
Invoice fields and sample date are:
+----+-----------+----------+------+
| ID | Date | Customer | Tax |
+----+-----------+----------+------+
| 1 | 1.1.2017 | 1 | 0.10 |
| 2 | 2.1.2017 | 2 | 0.10 |
| 3 | 3.1.2017 | 1 | 0.10 |
| 4 | 3.1.2017 | 2 | 0.10 |
| 5 | 8.1.2017 | 1 | 0.10 |
| 6 | 11.1.2017 | 1 | 0.10 |
| 7 | 12.1.2017 | 2 | 0.10 |
| 8 | 13.1.2017 | 1 | 0.10 |
+----+-----------+----------+------+
Item fields and sample data are:
+----+--------+
| ID | Name |
+----+--------+
| 1 | Door |
| 2 | Window |
| 3 | Table |
| 4 | Chair |
+----+--------+
Invoice_Item fields and sample data are:
+------------+---------+--------+------------+
| Invoice_ID | Item_ID | Amount | Unit_Price |
+------------+---------+--------+------------+
| 1 | 1 | 4 | 10 |
| 1 | 2 | 2 | 20 |
| 1 | 3 | 1 | 30 |
| 1 | 4 | 2 | 40 |
| 2 | 1 | 1 | 10 |
| 2 | 3 | 1 | 15 |
| 2 | 4 | 2 | 12 |
| 3 | 3 | 4 | 15 |
| 4 | 1 | 1 | 10 |
| 4 | 2 | 20 | 30 |
| 4 | 3 | 15 | 30 |
| 5 | 1 | 4 | 10 |
| 5 | 2 | 2 | 20 |
| 5 | 3 | 1 | 30 |
| 5 | 4 | 2 | 40 |
| 6 | 1 | 1 | 10 |
| 6 | 3 | 1 | 15 |
| 6 | 4 | 2 | 12 |
| 7 | 3 | 4 | 15 |
| 8 | 1 | 1 | 10 |
| 8 | 2 | 20 | 30 |
| 8 | 3 | 15 | 30 |
+------------+---------+--------+------------+
The reason the price is in this table not in the item table is because it is customer specific price.
Payment fields are:
+----------+--------+-----------+
| Customer | Amount | Date |
+----------+--------+-----------+
| 1 | 40 | 3.1.2017 |
| 2 | 10 | 7.1.2017 |
| 1 | 60 | 10.1.2017 |
+----------+--------+-----------+
so my report should be combine all tables and sort by DATE (either from Invoice or Payment) for a certain customer.
so for e.g. for customer John (1) it should be like:
+------------+----------------+---------+-----------+
| Invoice_ID | Invoice_Amount | Payment | Date |
+------------+----------------+---------+-----------+
| 1 | 171 | - | 1.1.2017 |
| 3 | 54 | - | 3.1.2017 |
| - | - | 40 | 3.1.2017 |
| 5 | 171 | - | 8.1.2017 |
| - | 10 | 60 | 10.1.2017 |
| 6 | 44.1 | - | 11.1.2017 |
| 8 | 954 | - | 13.1.2017 |
+------------+----------------+---------+-----------+
it is sorted by date, Invoice amount is (sum of (Amount* unit price)) * (1-tax)
i started with union but then got lost.
here is my try:
SELECT Inv_ID as Num, SUM(Invoice_Items.II_Price*Invoice_Items.II_Amount) AS Amount, Inv_Date as Created
FROM Invoice INNER JOIN Invoice_Items ON Invoice.Inv_ID = Invoice_Items.II_Inv_ID
UNION ALL
SELECT Null as Num, P_Value as Amount, P_Date as Created
FROM Payments
ORDER BY created ASC
Your help is appreciated!
Thanks
You can generate the report you requested using the following SQL script:
SELECT CustomerID,Invoice_ID,Invoice_Amount,Payment,Date
FROM (
SELECT c.ID AS CustomerID, i.ID AS Invoice_ID, SUM((t.Amount * t.UnitPrice)*(1-i.tax)) AS Invoice_Amount, NULL AS Payment,i.Date
FROM (Customer c
LEFT JOIN Invoice i
ON c.ID = i.Customer)
LEFT JOIN Invoice_Item t
ON i.ID = t.Invoice_ID
GROUP BY c.ID, i.ID,i.Date
UNION
SELECT c.ID AS CustomerID,NULL AS Invoice_ID, NULL AS Invoice_Amount, p.Amount AS Payment, p.Date
FROM Customer c
INNER JOIN Payment p
ON c.ID = p.Customer ) a
ORDER BY CustomerID, Date, Payment ASC
Note: I've added CustomerID to the output so you know what customer the data corresponds to.
here is the Answer which worked for me, a bit corrected from #Catzeye Answer , which didnt show the second part of the Union.
SELECT c.ID AS CustomerID,NULL AS Invoice_ID, NULL AS Invoice_Amount, p.Amount AS Payment, p.Date
FROM Customer c
INNER JOIN Payment p
ON c.ID = p.Customer
UNION ALL
SELECT c.ID AS CustomerID, i.ID AS Invoice_ID, SUM((t.Amount * t.Unit_Price)*(1-i.tax)) AS Invoice_Amount, NULL AS Payment,i.Date
FROM (Customer c
INNER JOIN Invoice i
ON c.ID = i.Customer)
INNER JOIN Invoice_Item t
ON i.ID = t.Invoice_ID
GROUP BY c.ID, i.ID,i.Date
ORDER BY CustomerID, Date, Payment;