I have the following table
There are some NULL values in price column, which I want to replace with the previous date value (date is manual_date). Additionally, price column is calculated on different dates (calculation_table), so the nulls should be filled based on this group filter.
The final output should show values similar to output_price.
I found here a code that does the same thing, however, I could not figure out how to do it with my data (one of the error says I have not ts in (PARTITION BY symbol ORDER BY ts). This is true, but in the website, there is also no ts specified + I tried to replace it ts with manual_date)
I tried following code for my data
select manual_date,TS_FIRST_VALUE(price, 'const') output_price
from MYDATA
TIMESERIES manual_date AS '1 month'
OVER(PARTITION BY calculation_date ORDER BY ts) --tried also ORDER BY manual_date
Vertical supports IGNORE NULLS on last_value(). So you can use:
last_value(price ignore nulls) over (
order by manual_date
rows between unbounded preceding and current row
) as output_price
Related
I need to use the current row values in a condition used in a window function on a partition with range. See my example query I am looking for.
select
count(case when orderdate >=
(**current_row.orderdate** -30) then 1 end)
over (partition by customerid order by orderdate range between unbounded preceding and current row)
from xyz
Not getting correct syntax.
Please see below example output required. This is just an example, the 30 days and the logic is just a sample.
I want to rename a column after calculating the difference between current row and previous row by using over clause (windows function)
However, I cannot run it and it shows that I have a error in my sql syntax
select country,year,
avg(oil_consumption) OVER (partition by country
order BY year
ROWS BETWEEN 2 PRECEDING AND current row )
as 3_year_moving_average, (3_year_moving_average-lag(3_year_moving_average,1) over (partition by country) **as** difference_between_previous_current
from owid_energy_data
Error at the second as (bolded)
I have a table with equipment failure and resolved date. Until the failure is resolved, entries for each day will show as failed. Once the issue is resolved data will start from the next failure date. Below is an example
I want an output which will give me the first failure time for each resolved timestamp like
I tried to do a left join between Resolved timestamp and failure dates AND take the min but that doesn't work.
Consider below approach
select type,
max(timestamp) resolved_timestamp,
min(timestamp) first_failure_timestamp
from (
select *, countif(status='resolved') over win as grp
from your_table
window win as (partition by type order by timestamp rows between unbounded preceding and 1 preceding)
)
group by type, grp
if applied to sample data in y our question - output is
I have the following SQL statement, which I think should update 1 field, using some pretty simple standard deviation logic, and based on ID and Date. I think the ID and Date has to be included to get everything aligned right. So, here is the code that I'm testing.
UPDATE Price_Test2
SET Vol30Days = STDEV(PX_BID) OVER (ORDER BY ID_CUSIP, AsOfDate ROWS BETWEEN 30 PRECEDING AND CURRENT ROW) FROM Price_Test2
WHERE ID_CUSIP in (SELECT DISTINCT ID_CUSIP FROM Price_Test2)
It seems like it should work fine, but something is off because I'm getting an error that says: Cannot use both a From clause and a subquery in the where clause or in the data values list in an Update statement.
I am using SQL Server 2019.
You are using aggregation functions in an update. What you want is an updatable subquery (or CTE):
UPDATE p
SET Vol30Days = new_Vol30Days,
Vol60Days = new_Vol60Days,
Vol90Days = new_Vol90Days
FROM (SELECT p.*,
STDEV(PX_BID) OVER (ORDER BY Date ROWS BETWEEN 30 PRECEDING AND CURRENT ROW) as new_Vol30day,
STDEV(PX_BID) OVER (ORDER BY Date ROWS BETWEEN 60 PRECEDING AND CURRENT ROW) as new_Vol60day,
STDEV(PX_BID) OVER (ORDER BY Date ROWS BETWEEN 90 PRECEDING AND CURRENT ROW) as new_Vol60day
FROM prices p
) p;
I have an Oracle table that consist of tuples of logtime/value1, value2..., plus additional columns such as a metering point id. The values are sampled values of different counters that are each monotonically increasing, i.e. a newer value cannot be less than an older value. However, values can remain equal for several samplings, and values can miss sometimes, so the corresponding table entry is NULL while other values of the same logtime are valid. Also, the intervals between logtimes are not constant.
In the following, for simplicity I will regard only the logtime and one counter value.
I have to calculate the deltas from each logtime to the previous one. Using the method described in another question here gives two NULL deltas for each NULL value because two subtractions are invalid. A second solution fails when consecutive values are identical since the difference to the previous value is calculated twice.
Another solution is to construct a derived table/view with those NULL values replaced by the latest older valid value. My approach looks like this:
SELECT A.logtime, A.val,
(A.val - (SELECT MAX(C.val)
FROM tab C
WHERE logtime =
(SELECT MAX(B.logtime)
FROM tab B
WHERE B.logtime < A.logtime AND B.val IS NOT NULL))) AS delta
FROM tab A;
I suspect that this will result in a quite inefficient query, especially when doing this for all N counters in the table which will result in (1 + 2*N) SELECTs. It also does not take advantage from the fact that the counter is monotonically increasing.
Are there any alternative approaches? I'd think others have similar problems, too.
An obvious solution would of course be filling in those NULL values constructing a new table or modifying the existing table, but unfortunately that is not possible in this case. Avoiding/eliminating them on entry isn't possible either.
Any help would be greatly appreciated.
select
logtime,
val,
last_value(val ignore nulls) over (order by logtime)
as not_null_val,
last_value(val ignore nulls) over (order by logtime) -
last_value(val ignore nulls) over (order by logtime rows between unbounded preceding and 1 preceding)
as delta
from your_tab order by logtime;
I found a way to avoid the nested SELECT statements using Oracle SQL's build-in LAG function:
SELECT logtime, val,
NVL(val-LAG(val IGNORE NULLS) OVER (ORDER BY logtime), 0) AS delta
FROM tab;
seems to work as I intended.
(Repeated here as a separate answer)