I have a table like this:
OrderID | PhaseID | Timestamp
1 | 1 | 1/1
1 | 2 | 1/2
1 | 3 | 1/3
1 | 2 | 1/4
1 | 4 | 1/5
I'm trying to get a query to return the most recent timestamp for each orderphase combination without being followed by a lesser phaseid. Something like this:
OrderID | PhaseID | MaxTimestampWithoutBeingFollowedByLesserPhaseID
1 | 1 | 1/1
1 | 2 | 1/4
1 | 3 | NULL
1 | 4 | 1/5
I keep running around in circles and coming up with this problem of a conditional aggregate query.
Can anybody figure out the query or give me some pointers?
With a as (
Select OrderID, PhaseID, MaxTimestamp=max([Timestamp])
From orderphase op
Where not exists(select 1 from orderphase where PhaseID < op.PhaseID
and [Timstamp]> op.[Timestamp])
Group by OrderID, PhaseID
)
Select distinct o.Orderid, o.PhaseID, MaxTimestamp=a.MaxTimestamp
From orderphase o
Left join a on a.OrderID = o.OrderID and a.PhaseID=o.PhaseID
EDIT ref a.MaxTimestamp
Rank phases by time stamps for every order.
Join every row with its successor based on the rank.
Mark the rows where PhaseID is followed by a lesser PhaseID.
Aggregate the last result set picking max time stamps conditionally using MAX(CASE ...) to omit rows marked as ones being followed by lesser PhaseIDs.
Here's a sample implementation:
;
WITH ranked AS (
SELECT
*,
rnk = ROW_NUMBER() OVER (PARTITION BY OrderID ORDER BY [Timestamp])
FROM atable
),
marked AS (
SELECT
r1.OrderID,
r1.PhaseID,
r1.[Timestamp],
IsFollowedByLesserPhaseID = CASE WHEN r2.PhaseID IS NULL THEN 0 ELSE 1 END
FROM ranked r1
LEFT JOIN ranked r2 ON r1.OrderID = r2.OrderID
AND r1.rnk = r2.rnk - 1
AND r1.PhaseID > r2.PhaseID
)
SELECT
OrderID,
PhaseID,
MaxTimestampWithoutBeingFollowedByLesserPhaseID = MAX(
CASE IsFollowedByLesserPhaseID WHEN 0 THEN [Timestamp] END
)
FROM marked
GROUP BY
OrderID,
PhaseID
Related
I am working with data similar to below,
week | product | sale
1 | ABC | 2
1 | ABC | 1
2 | ABC | 1
3 | ABC | 5
4 | ABC | 1
2 | DEF | 5
Let us say that is my Orders table named tblOrders. Now, in each row, I want to aggregate the total sales from last week for that product - for instance, if I am on week 2 of product "ABC", I need to show the aggregated sales amount of week 1 for product ABC. so, the output should look something like below,
week | product | sale | ProductPreviousWeekSales
1 | ABC | 2 | 0
1 | ABC | 1 | 0
2 | ABC | 1 | 3
3 | ABC | 5 | 1
4 | ABC | 1 | 5
2 | DEF | 5 | 0
I was originally thinking I could solve this using Aggregates and Window Function, but doesn't look to be so. Another thought I was having is to use Conditional Aggregate - something like sum(case when x=currentRow.x then sale else 0 end), but that wouldn't work too.
Here is the SQLFiddle for above sample - http://sqlfiddle.com/#!18/890b7/2
Note: I need to calculate similar value for Last 4 weeks, so trying to avoid doing this as a sub-query or multiple joins (if possible), as the data set I am working with is very large, and don't want to add to much performance overhead trying to incorporate this change.
Here is one approach which first aggregates your table in a separate CTE and uses LAG to find the previous week's amount, for each week and product:
WITH cte AS (
SELECT week, product,
LAG(SUM(sale)) OVER (PARTITION BY product ORDER BY week) AS lag_total_sales
FROM yourTable
GROUP BY week, product
)
SELECT t1.week, t1.product, t1.sale,
COALESCE(t2.lag_total_sales, 0) AS ProductPreviousWeekSales
FROM yourTable t1
INNER JOIN cte t2
ON t2.week = t1.week AND
t2.product = t1.product
ORDER BY
t1.product,
t1.week;
Demo
DISCLAIMER
The query I am showing below doesn't work in SQL Server, unfortunately. Up to SQL Server version 2019 the DBMS lacks full support of the RANGE clause that is essential for the query to work. Running the query in SQL Server results in
Msg 4194 Level 16 State 1 Line 1 RANGE is only supported with UNBOUNDED and CURRENT ROW window frame delimiters.
I am not deleting this answer, because this is standard SQL and the approach may help future readers. It runs fine in a lot of DBMS, and maybe a future version of SQL Server will be able to deal with this, too. I've added demos to show that it runs in PostgreSQL, MySQL and Oracle, but fails in SQL Server 2019.
ORIGINAL ANSWER
Your query shown in the fiddle (select a.*, sum(sale) over(partition by product) ProductPreviousWeekSales from tblOrder a) is merely lacking the appropriate windowing clause. As you are dealing with ties here (more than one row per product and week) this needs to be a RANGE clause:
select a.*,
sum(sale) over(partition by product
order by week range between 1 preceding and 1 preceding
) as ProductPreviousWeekSales
from tblOrder a
order by product, week;
(Use COALESCE if you want to see a zero instead of NULL.)
Demos:
https://dbfiddle.uk/?rdbms=postgres_13&fiddle=149eddbff82500d539b2c615f4167cff
https://dbfiddle.uk/?rdbms=mysql_8.0&fiddle=a8453970efac08ad69275914910bb13e
https://dbfiddle.uk/?rdbms=oracle_18&fiddle=64ed21150142caa0acb7f8c7ca7d9022
https://dbfiddle.uk/?rdbms=sqlserver_2019&fiddle=149eddbff82500d539b2c615f4167cff
You can do from following
; WITH cteorder AS
(
SELECT DISTINCT product, week FROM dbo.tblOrder
)
SELECT
cte.*,
SUM(ISNULL(b.sale,0)) ProductPreviousWeekSales
from tblOrder a
INNER JOIN cteorder cte ON cte.product = a.product AND cte.week = a.week
LEFT JOIN dbo.tblOrder b ON b.product = cte.product AND b.week = (a.week-1)
GROUP BY cte.product,
cte.week
You can run from : Fiddle
You need to select from TblOrders twice. Once, grouping by week and product and summing the sales, and the second time, a row-by-row scan against TblOrders, left-joining it with the grouping query on same product and week offset by 1:
If the join fails , the sales value of the joined grouping query returns NULL. You can put in 0 instead of NULL using COALESCE(), but ISNULL() has all chances of being faster, as it has a fixed number of parameters, while COALESCE() has a variable argument list, which comes at a certain cost.
WITH
tblorders(wk,product,sales) AS (
SELECT 1,'ABC',2
UNION ALL SELECT 1,'ABC',1
UNION ALL SELECT 2,'ABC',1
UNION ALL SELECT 3,'ABC',5
UNION ALL SELECT 4,'ABC',1
UNION ALL SELECT 2,'DEF',5
)
,
grp AS (
SELECT
wk
, product
, SUM(sales) AS sales
FROM tblorders
GROUP BY
wk
, product
)
SELECT
o.wk
, o.product
, o.sales
, ISNULL(g.sales,0) AS productpreviousweeksales
FROM tblorders o
LEFT
JOIN grp g
ON o.wk - 1 = g.wk
AND o.product= g.product
ORDER BY 2,1
;
wk | product | sales | productpreviousweeksales
----+---------+-------+--------------------------
1 | ABC | 2 | 0
1 | ABC | 1 | 0
2 | ABC | 1 | 3
3 | ABC | 5 | 1
4 | ABC | 1 | 5
2 | DEF | 5 | 0
I have a table with user retail transactions. It includes sales and cancels. If Qty is positive - it sells, if negative - cancels. I want to attach cancels to the most appropriate sell. So, I have tables likes that:
| CustomerId | StockId | Qty | Date |
|--------------+-----------+-------+------------|
| 1 | 100 | 50 | 2020-01-01 |
| 1 | 100 | -10 | 2020-01-10 |
| 1 | 100 | 60 | 2020-02-10 |
| 1 | 100 | -20 | 2020-02-10 |
| 1 | 100 | 200 | 2020-03-01 |
| 1 | 100 | 10 | 2020-03-05 |
| 1 | 100 | -90 | 2020-03-10 |
User with ID 1 has the following actions: buy 50 -> return 10 -> buy 60 -> return 20 -> buy 200 -> buy 10 - return 90. For each cancel row (with negative Qty) I find the previous row (by Date) with positive Qty and greater than cancel Qty.
So I need to create BigQuery queries to create table likes this:
| CustomerId | StockId | Qty | Date | CancelQty |
|--------------+-----------+-------+------------+-------------|
| 1 | 100 | 50 | 2020-01-01 | -10 |
| 1 | 100 | 60 | 2020-02-10 | -20 |
| 1 | 100 | 200 | 2020-03-01 | -90 |
| 1 | 100 | 10 | 2020-03-05 | 0 |
Does anybody help me with these queries? I have created one candidate query (split cancel and sales, join them, and do some staff for removing), but it works incorrectly in the above case.
I use BigQuery, so any BQ SQL features could be applied.
Any ideas will be helpful.
You can use the following query.
;WITH result AS (
select t1.*,t2.Qty as cQty,t2.Date as Date_t2 from
(select *,ROW_NUMBER() OVER (ORDER BY qty DESC) AS [ROW NUMBER] from Test) t1
join
(select *,ROW_NUMBER() OVER (ORDER BY qty) AS [ROW NUMBER] from Test) t2
on t1.[ROW NUMBER] = t2.[ROW NUMBER]
)
select CustomerId,StockId,Qty,Date,ISNULL(cQty, 0) As CancelQty,Date_t2
from (select CustomerId,StockId,Qty,Date,case
when cQty < 0 then cQty
else NULL
end AS cQty,
case
when cQty < 0 then Date_t2
else NULL
end AS Date_t2 from result) t
where qty > 0
order by cQty desc
result: https://dbfiddle.uk
You can do this as a gaps-and-islands problem. Basically, add a grouping column to the rows based on a cumulative reverse count of negative values. Then within each group, choose the first row where the sum is positive. So:
select t.* (except cancelqty, grp),
(case when min(case when cancelqty + qty >= 0 then date end) over (partition by customerid grp) = date
then cancelqty
else 0
end) as cancelqty
from (select t.*,
min(cancelqty) over (partition by customerid, grp) as cancelqty
from (select t.*,
countif(qty < 0) over (partition by customerid order by date desc) as grp
from transactions t
) t
from t
) t;
Note: This works for the data you have provided. However, there may be complicated scenarios where this does not work. In fact, I don't think there is a simple optimal solution assuming that the returns are not connected to the original sales. I would suggest that you fix the data model so you record where the returns come from.
The below query seems to satisfy the conditions and the output mentioned.The solution is based on mapping the base table (t) and having the corresponding canceled qty row alongside from same table(t1)
First, a self join based on the customer and StockId is done since they need to correspond to the same customer and product.
Additionally, we are bringing in the canceled transactions t1 that happened after the base row in table t t.Dt<=t1.Dt and to ensure this is a negative qty t1.Qty<0 clause is added
Further we cannot attribute the canceled qty if they are less than the Original Qty. Therefore I am checking if the positive is greater than the canceled qty. This is done by adding a '-' sign to the cancel qty so that they can be compared easily. -(t1.Qty)<=t.Qty
After the Join, we are interested only in the positive qty, so adding a where clause to filter the other rows from the base table t with canceled quantities t.Qty>0.
Now we have the table joined to every other canceled qty row which is less than the transaction date. For example, the Qty 50 can have all the canceled qty mapped to it but we are interested only in the immediate one came after. So we first group all the base quantity values and then choose the date of the canceled Qty that came in first in the Having clause condition HAVING IFNULL(t1.dt, '0')=MIN(IFNULL(t1.dt, '0'))
Finally we get the rows we need and we can exclude the last column if required using an outer select query
SELECT t.CustomerId,t.StockId,t.Qty,t.Dt,IFNULL(t1.Qty, 0) CancelQty
,t1.dt dt_t1
FROM tbl t
LEFT JOIN tbl t1 ON t.CustomerId=t1.CustomerId AND
t.StockId=t1.StockId
AND t.Dt<=t1.Dt AND t1.Qty<0 AND -(t1.Qty)<=t.Qty
WHERE t.Qty>0
GROUP BY 1,2,3,4
HAVING IFNULL(t1.dt, '0')=MIN(IFNULL(t1.dt, '0'))
ORDER BY 1,2,4,3
fiddle
Consider below approach
with sales as (
select * from `project.dataset.table` where Qty > 0
), cancels as (
select * from `project.dataset.table` where Qty < 0
)
select any_value(s).*,
ifnull(array_agg(c.Qty order by c.Date limit 1)[offset(0)], 0) as CancelQty
from sales s
left join cancels c
on s.CustomerId = c.CustomerId
and s.StockId = c.StockId
and s.Date <= c.Date
and s.Qty > abs(c.Qty)
group by format('%t', s)
if applied to sample data in your question - output is
I have created a table from multiple tables like this:
Week | Cid | CustId | L1
10 | 1 | 1 | 2
10 | 2 | 1 | 2
10 | 5 | 1 | 2
10 | 4 | 1 | 1
10 | 3 | 2 | 1
4 | 6 | 1 | 2
4 | 7 | 1 | 2
I want the output as:
Repeat
0
1
1
0
0
0
1
So, basically what I want is for each week, if a person (custid) comes in again with the same L1, then the value in the column Repeat should become 1, otherwise 0 ( so like, here, in row 2 & 3, custid 1, came with L1=2 again, so it will get 1 in column "Repeat", however in row 4, custid 1 came with L1=1, so it will get value as ).
By the way, the table isn't ordered (as I've shown).
I'm trying to do it as follows:
select t.*,
lag(0, 1, 0) over (partition by week, custid, L1 order by cid) as repeat
from
table;
But this is not giving the output and is giving empty result.
I think you need a case, but I would use row_number() for this:
select t.*,
(case when row_number() over (partition by week, custid, l1 order by cid) = 1
then 0 else 1
end) as repeat
from table;
This can also be computed without Window functions but by a self-join in the following way:
SELECT a.week, a.cid, a.custid, a.l1,
CASE WHEN b IS NULL THEN 1 ELSE 0 END AS repeat
FROM mytable a NATURAL LEFT JOIN
(SELECT week, min(cid) AS cid, custid, l1 FROM mytable
GROUP BY week,custid,l1) b
ORDER BY week DESC, custid, l1 DESC, cid;
It can be done simply by using an count(*) as analytic function. No case expression or self join needed. The query is even portable across databases that support analytic functions:
SELECT cust.*, least(count(*)
OVER (PARTITION BY Week, CustId, L1 ORDER BY Cid
ROWS UNBOUNDED PRECEDING) - 1, 1) repeat
FROM cust ORDER BY Week DESC, custId, L1 DESC;
Executing the query on your data results in the following output (last row is the repeat row):
Week | Cid | CustId | L1 | repeat
10 1 1 2 0
10 2 1 2 1
10 5 1 2 1
10 4 1 1 0
10 3 2 1 0
4 6 1 2 0
4 7 1 2 1
Tested on Oracle 11g and PostgreSQL 9.4. Note that the second ORDER BY is optional. See Oracle Language Reference, Analytic Functions for more details.
I have table with data something like this:
ID | RowNumber | Data
------------------------------
1 | 1 | Data
2 | 2 | Data
3 | 3 | Data
4 | 1 | Data
5 | 2 | Data
6 | 1 | Data
7 | 2 | Data
8 | 3 | Data
9 | 4 | Data
I want to group each set of RowNumbers So that my result is something like this:
ID | RowNumber | Group | Data
--------------------------------------
1 | 1 | a | Data
2 | 2 | a | Data
3 | 3 | a | Data
4 | 1 | b | Data
5 | 2 | b | Data
6 | 1 | c | Data
7 | 2 | c | Data
8 | 3 | c | Data
9 | 4 | c | Data
The only way I know where each group starts and stops is when the RowNumber starts over. How can I accomplish this? It also needs to be fairly efficient since the table I need to do this on has 52 Million Rows.
Additional Info
ID is truly sequential, but RowNumber may not be. I think RowNumber will always begin with 1 but for example the RowNumbers for group1 could be "1,1,2,2,3,4" and for group2 they could be "1,2,4,6", etc.
For the clarified requirements in the comments
The rownumbers for group1 could be "1,1,2,2,3,4" and for group2 they
could be "1,2,4,6" ... a higher number followed by a lower would be a
new group.
A SQL Server 2012 solution could be as follows.
Use LAG to access the previous row and set a flag to 1 if that row is the start of a new group or 0 otherwise.
Calculate a running sum of these flags to use as the grouping value.
Code
WITH T1 AS
(
SELECT *,
LAG(RowNumber) OVER (ORDER BY ID) AS PrevRowNumber
FROM YourTable
), T2 AS
(
SELECT *,
IIF(PrevRowNumber IS NULL OR PrevRowNumber > RowNumber, 1, 0) AS NewGroup
FROM T1
)
SELECT ID,
RowNumber,
Data,
SUM(NewGroup) OVER (ORDER BY ID
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS Grp
FROM T2
SQL Fiddle
Assuming ID is the clustered index the plan for this has one scan against YourTable and avoids any sort operations.
If the ids are truly sequential, you can do:
select t.*,
(id - rowNumber) as grp
from t
Also you can use recursive CTE
;WITH cte AS
(
SELECT ID, RowNumber, Data, 1 AS [Group]
FROM dbo.test1
WHERE ID = 1
UNION ALL
SELECT t.ID, t.RowNumber, t.Data,
CASE WHEN t.RowNumber != 1 THEN c.[Group] ELSE c.[Group] + 1 END
FROM dbo.test1 t JOIN cte c ON t.ID = c.ID + 1
)
SELECT *
FROM cte
Demo on SQLFiddle
How about:
select ID, RowNumber, Data, dense_rank() over (order by grp) as Grp
from (
select *, (select min(ID) from [Your Table] where ID > t.ID and RowNumber = 1) as grp
from [Your Table] t
) t
order by ID
This should work on SQL 2005. You could also use rank() instead if you don't care about consecutive numbers.
I have a table that I want to find for each row id the amount remaining from the total. However, the order of amounts is in an ascending order.
id amount
1 3
2 2
3 1
4 5
The results should look like this:
id remainder
1 10
2 8
3 5
4 0
Any thoughts on how to accomplish this? I'm guessing that the over clause is the way to go, but I can't quite piece it together.Thanks.
Since you didn't specify your RDBMS, I will just assume it's Postgresql ;-)
select *, sum(amount) over() - sum(amount) over(order by amount) as remainder
from tbl;
Output:
| ID | AMOUNT | REMAINDER |
---------------------------
| 3 | 1 | 10 |
| 2 | 2 | 8 |
| 1 | 3 | 5 |
| 4 | 5 | 0 |
How it works: http://www.sqlfiddle.com/#!1/c446a/5
It works in SQL Server 2012 too: http://www.sqlfiddle.com/#!6/c446a/1
Thinking of solution for SQL Server 2008...
Btw, is your ID just a mere row number? If it is, just do this:
select
row_number() over(order by amount) as rn
, sum(amount) over() - sum(amount) over(order by amount) as remainder
from tbl
order by rn;
Output:
| RN | REMAINDER |
------------------
| 1 | 10 |
| 2 | 8 |
| 3 | 5 |
| 4 | 0 |
But if you really need the ID intact and move the smallest amount on top, do this:
with a as
(
select *, sum(amount) over() - sum(amount) over(order by amount) as remainder,
row_number() over(order by id) as id_sort,
row_number() over(order by amount) as amount_sort
from tbl
)
select a.id, sort.remainder
from a
join a sort on sort.amount_sort = a.id_sort
order by a.id_sort;
Output:
| ID | REMAINDER |
------------------
| 1 | 10 |
| 2 | 8 |
| 3 | 5 |
| 4 | 0 |
See query progression here: http://www.sqlfiddle.com/#!6/c446a/11
I just want to offer a simpler way to do this in descending order:
select id, sum(amount) over (order by id desc) as Remainder
from t
This will work in Oracle, SQL Server 2012, and Postgres.
The general solution requres a self join:
select t.id, coalesce(sum(tafter.amount), 0) as Remainder
from t left outer join
t tafter
on t.id < tafter.id
group by t.id
SQL Server 2008 answer, I can't provide an SQL Fiddle, it seems it strips the begin keyword, resulting to syntax errors. I tested this on my machine though:
create function RunningTotalGuarded()
returns #ReturnTable table(
Id int,
Amount int not null,
RunningTotal int not null,
RN int identity(1,1) not null primary key clustered
)
as
begin
insert into #ReturnTable(id, amount, RunningTotal)
select id, amount, 0 from tbl order by amount;
declare #RunningTotal numeric(16,4) = 0;
declare #rn_check int = 0;
update #ReturnTable
set
#rn_check = #rn_check + 1
,#RunningTotal =
case when rn = #rn_check then
#RunningTotal + Amount
else
1 / 0
end
,RunningTotal = #RunningTotal;
return;
end;
To achieve your desired output:
with a as
(
select *, sum(amount) over() - RunningTotal as remainder
, row_number() over(order by id) as id_order
from RunningTotalGuarded()
)
select a.id, amount_order.remainder
from a
inner join a amount_order on amount_order.rn = a.id_order;
Rationale for guarded running total: http://www.ienablemuch.com/2012/05/recursive-cte-is-evil-and-cursor-is.html
Choose the lesser evil ;-)