select t1.lease_number ,t2.rec_bal, to_date(t2.date_dim_id,'YYYYMMDD') as issue_date,t2.paid_to as pay_date,
(case when pay_date <= lag(pay_date) over (order by issue_date) then null when pay_date > lag(pay_date) over (order by issue_date) then issue_date end) as payment_date,
dense_rank() over (partition by pay_date order by issue_date) as row_numbers,
(case when row_numbers = max(row_numbers) over (partition by payment_date) then payment_date else null end) as paymentmade_date,
remain_months_upd,remaining_pymt_periods, t2.dealer_dim_id, t2.lease_contract_dim_id
from dm_business_ops_tcci.v_tcci_lease_contract_dim t1
, dm_business_ops_tcci.v_tcci_lease_transaction_fact t2
where t1.lease_contract_dim_id=t2.lease_contract_dim_id
and t2.date_dim_id >=20210301 -- can be changed to latest busienss date
and lease_number in (1633014)
order by issue_date
I am trying to partition by a column I created using a window function, and I can't do it. The error is coming from the line "(case when row_numbers = max(row_numbers) over (partition by payment_date) then payment_date else null end) as paymentmade_date". Payment_date is calculating using a window function in a prior line. Is there a workaround for this?
You will need to materialize the values of your window functions before you perform any sort of filtering, partitioning, or conditional operations on that value.
There are a few ways to go about doing this, and the appropriate one for your use case will vary depending factor outside of this scope.
You may accomplish this using a view, CTE, temp table, or a table variable prior to attempting this partitioning operation. This is not an exhaustive list.
Related
I am using Spark SQL 3.2.0
Please see the DB Fiddle link for a simplified example of my dataset and desired outcome.
In abstract, I have a dataset with a series of related events that can be grouped by their time order and event number. When ordering by time and event number, every time the event number resets to 1, you're looking at a new set of events.
I understand how to use row_number() or dense_rank() to increment event_group_number where sub_event_number = 1, but I'm uncertain how to make the rows where sub_event_number > 1 take on the correct event_group_number.
I'm currently doing the following:
case
when sub_event_number = 1 and is_event_type
then row_number() over (partition by context_id, event_id, sub_event_number order by is_event_type asc, start_time asc) - 1
else null
end as event_group_number
I'd be grateful for any help, and I'm happy to answer any questions.
It seems you're looking for a cumulative conditional sum:
SELECT context_id,
event_id,
start_time,
NULLIF(
SUM(CASE WHEN sub_event_number = 1 THEN 1 ELSE 0 END) OVER(
PARTITION BY context_id, event_id
ORDER BY is_event_type, start_time) - 1,
0
) AS event_group_number
FROM foobar
ORDER BY context_id, event_id, is_event_type, start_time
db-fiddle
I want to make a calculation based on the excel file. I succeed to obtain 2 of the first records with LAG (as you can check on the 2nd screenshot). Im out of ideas how to proceed from now and need help. I just need the Calculation column take its previous data. I want to automatically calculate it over all the dates. I also tried to make a LAG for the calculation but manually and the result was +1 row more data instead of NULL. This is a headache.
LAG(Data ingested, 1) OVER ( ORDER BY DATE ASC ) AS LAG
You seem to want cumulative sums:
select t.*,
(sum(reconciliation + aves - microa) over (order by date) -
first_value(aves - microa) over (order by date)
) as calculation
from CalcTable t;
Here is a SQL Fiddle.
EDIT:
Based on your comment, you just need to define a group:
select t.*,
(sum(reconciliation + aves - microa) over (partition by grp order by date) -
first_value(aves - microa) over (partition by grp order by date)
) as calculation
from (select t.*,
count(nullif(reconciliation, 0)) over (order by date) as grp
from CalcTable t
) t
order by date;
Imo this could be solved using a "gaps and islands" approach. When Reconciliation>0 then create a gap. SUM(GAP) OVER converts the gaps into island groupings. In the outer query the 'sum_over' column (which corresponds to the 'Calculation') is a cumumlative sum partitioned by the island groupings.
with
gap_cte as (
select *, case when [Reconciliation]>0 then 1 else 0 end gap
from CalcTable),
grp_cte as (
select *, sum(gap) over (order by [Date]) grp
from gap_cte)
select *, sum([Reconciliation]+
(case when gap=1 then 0 else Aves end)-
(case when gap=1 then 0 else Microa end))
over (partition by grp order by [Date]) sum_over
from grp_cte;
[EDIT]
The CASE statement could be CROSS APPLY'ed instead
with
grp_cte as (
select c.*, v.gap, sum(v.gap) over (order by [Date]) grp
from #CalcTable c
cross apply (values (case when [Reconciliation]>0 then 1 else 0 end)) v(gap))
select *, sum([Reconciliation]+
(case when gap=1 then 0 else Aves end)-
(case when gap=1 then 0 else Microa end))
over (partition by grp order by [Date]) sum_over
from grp_cte;
Here is a fiddle
The main objective is to group the rows following Amount Column sequentially so that, if there is any different value between the 2 same values, they will be numbered separately.
This is the raw data here:
SELECT Area, DateA, DateB, Amount
FROM (VALUES
('ABC', '2019-08-18', '2019-08-18 00:07:47.000', 3.75),
('ABC','2019-08-19', '2019-08-19 00:08:47.000', 3.75),
('ABC','2019-08-20', '2019-08-20 00:09:47.000', 3.65),
('ABC','2019-08-21', '2019-08-21 00:09:57.000', 3.75))
AS FeeCollection(Area, DateA, DateB, Amount)
I've tried this but, I don't know the real matter to number in a special way.
DENSE_RANK() OVER(ORDER BY Area, Amount)
This is the sample result I want to achieve. I'm looking for simple logic to do it. Using cursor or while looping will not be efficient for me.
I believe this is what you want. I use LAG to get the value of the prior row in a CTE, and then use a windowed COUNT to reduce the value of ROW_NUMBER by 1 for each row with the same consecutive value for amount:
WITH CTE AS(
SELECT Area,
DateA,
DateB,
Amount,
LAG(Amount) OVER (PARTITION BY Area ORDER BY DateA) AS PrevAmount
FROM (VALUES
('ABC', '2019-08-18', '2019-08-18 00:07:47.000', 3.75),
('ABC','2019-08-19', '2019-08-19 00:08:47.000', 3.75),
('ABC','2019-08-20', '2019-08-20 00:09:47.000', 3.65),
('ABC','2019-08-21', '2019-08-21 00:09:57.000', 3.75))
AS FeeCollection(Area, DateA, DateB, Amount))
SELECT Area,
DateA,
DateB,
Amount,
ROW_NUMBER() OVER (PARTITION BY Area ORDER BY DateA) -
COUNT(CASE Amount WHEN PrevAmount THEN 1 END) OVER (PARTITION BY Area ORDER BY DateA
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS Number
FROM CTE
ORDER BY DateA;
I did assume your PARTITION BY clause, which you may need to change/remove/move to the ORDER BY. As we had only one value for Area was impossible to know what the value should be when it changes.
I would do this using lag() and a cumulative sum, but looking like:
select t.*,
sum(case when prev_amount = amount then 0 else 1 end) over
(partition by area order by datea) as number
from (select t.*,
lag(amount) over (partition by area order by datea) as prev_amount
from t
) t;
I'm using T-SQL 2014
Suppose I have a stock price chart as follow
I want to write efficient code for a stored function to display the Open price at the start, Close price at the end, and the difference between Close and Open. Is it possible to do that in one query? The query seems easy but it turned out extremely difficult. My first problem is to display the first row and last row in one query.
My attempt is like this
create function GetVolatilityRank(#from date, #to date)
returns table as
return(
with Price_Selected_Time as (select * from Price where [date] between #from and #to)
select
(select top 1([Open]) from Price_Selected_Time) as 'Open',
(select top 1([Close]) from Price_Selected_Time order by date desc) as 'Close',
[Close] - [Open] as 'Difference'
);
I feel this code is very clumsy. And it also won't let me pass, because the 'Open'and 'Close' is not defined yet.
Is there anyway to query this in one select?
Thank you
We can handle this via a regular query using ROW_NUMBER:
WITH cte AS (
SELECT *, ROW_NUMBER() OVER (ORDER BY Date) rn_start,
ROW_NUMBER() OVER (ORDER BY Date DESC) rn_end
FROM Price
)
SELECT
MAX(CASE WHEN rn_start = 1 THEN [Open] END) AS OpenStart,
MAX(CASE WHEN rn_end = 1 THEN [Close] END) AS CloseEnd,
MAX(CASE WHEN rn_end = 1 THEN [Close] END) -
MAX(CASE WHEN rn_start = 1 THEN [Open] END) AS diff
FROM cte;
In Teradata, I need a query to first identify all members in the MEM TABLE that currently have a negative balance, let's call that CUR_BAL. Then, for all of those members only, sum all transactions from the TRAN TABLE in order by date until the sum of those transactions is equal to the CUR_BAL.
Editing to add a third ADJ table that contains MEM_NBR, ADJ_DT and ADJ_AMT that need to be included in the running total in order to capture all of the records.
I would like the outcome to include the MEM.MEM_NBR, MEM.CUR_BAL, TRAN.TRAN_DATE OR ADJ.ADJ_DT (date associated with the transaction that resulted in the running total to equal CUR_BAL), MEM.LST_UPD_DT. I don't need to know if the balance is negative as a result of a transaction or adjustment, just the date that it went negative.
Thank you!
select
mem_nbr,
cur_bal,
tran_date,
tran_type
from (
select
a.mem_nbr,
a.cur_bal,
b.tran_date,
b.tran_type,
a.lst_upd_dt,
sum(b.tran_amt) over (partition by b.mem_nbr order by b.tran_date rows between unbounded preceding and current row) as cumulative_bal
from mem a
inner join (
select
mem_nbr,
tran_date,
tran_amt,
'Tran' as tran_type
from tran
union all
select
mem_nbr,
adj_date,
adj_amt,
'Adj' as tran_type
from adj
) b
on a.mem_nbr = b.mem_nbr
where a.cur_bal < 0
qualify cumulative_bal < 0
) z
qualify rank() over (partition by mem_nbr order by tran_date) = 1
The subquery picks up all instances where the cumulative balance is negative, then the outer query picks up the earliest instance of it. If you want the latest, add desc after tran_date in the final qualify line.