I have a dataset with the following columns
city
user
week
month
earnings
Ideally I want to calculate a 50th % from percentile_cont(earnings,0.5) over (partition by city order by month range between 1 preceding and current row). But Big query doesn't support window framing in percentile_cont. Can anyone please help me if there is a work around this problem.
If I understand correctly, you can aggregate into an array and then unnest:
select t.*,
(select percentile_cont(earning) over ()
from unnest(ar_earnings) earning
limit 1
) as median_2months
from (select t.*,
array_agg(earnings) over (partition by city
order by month
range between 1 preceding and current month
) as ar_earnings
from t
) t;
You don't provide sample data, but this version assumes that month is an incrementing integer that represents the month. You may need to adjust the range depending on the type.
Related
This is my table:
userID
Year
Month
Day
NbOfVisits
I would like to calculate the 7 days moving average, my query is as follows:
select userID,year,month,day, sum(nbofvisits) OVER (Partition by userID order by year,month,day RANGE BETWEEN 7 PRECEDING AND CURRENT ROW) as nbVisits7days
from table
order by userID, year, month, day;
But I keep getting this error: "A range window frame with value boundaries cannot be used in a window specification with multiple order by expressions". I understand I have multiple "Order Bys", but I can't think of a straight way other than this.
Following Jon Armstrong's comment, I managed to run my intended query as follows:
select userID,year,month,day, sum(nbofvisits) OVER (Partition by userID order by TIMESTAMP(concat(annee,'-',mois,'-',jour)) RANGE BETWEEN INTERVAL '7' DAY PRECEDING AND CURRENT ROW) as nbVisits7days
from table
order by userID, year, month, day;
Thank you!
I am having trouble using window functions in SNOWFLAKE to look at historical data (from 12 months prior). When I add a dimension, this code doesn't work.
SELECT
DATE_TRUNC('MONTH',pl.DATE) AS MONTH,
COUNT(DISTINCT PL.ID) AS CURRENT,
PL.DIMENSION,
FIRST_VALUE(count(DISTINCT pl.ID)) OVER (PARTITION BY PL.DIMENSION ORDER BY MONTH ASC ROWS BETWEEN 12 PRECEDING AND 12 PRECEDING) AS 1_YEAR_AGO
from table1 pl
group by MONTH, PL.DIMENSION
ORDER BY MONTH
here are the results if i filter on the dimension:
i am wanting more rows.. for example month = 2019-10-01, CURRENT_ would be NULL and 1_YR_AGO should be 1 and so on.. what am I missing? (I put examples of this in the highlighted section of the picture. the results are unhighlighted.
NOTE: I've also tried a lag and it does the same thing here.
I have been working with window functions a fair amount but I don't think I understand enough about how they work to answer why they behave the way they do.
For the query that I was working on (below), why am I required to take my aggregated field and add it to the group by? (In the second half of my query below I am unable to produce a result if I don't include "Events" in my second group by)
With Data as (
Select
CohortDate as month
,datediff(week,CohortDate,EventDate) as EventAge
,count(distinct case when EventDate is not null then GUID end) as Events
From MyTable
where month >= [getdate():month] - interval '12 months'
group by 1, 2
order by 1, 2
)
Select
month
,EventAge
,sum(Events) over (partition by month order by SubAge asc rows between unbounded preceding and current row) as TotEvents
from data
group by 1, 2, Events
order by 1, 2
I have run into this enough that I have just taken it for granted, but would really love some more color as to why this is needed. Is there a way I should be formatting these differently in order to avoid this (somewhat non-intuitive) requirement?
Thanks a ton!
What you are looking for is presumably a cumulative sum. That would be:
select month, EventAge,
sum(sum(Events)) over (partition by month
order by SubAge asc
rows between unbounded preceding and current row
) as TotEvents
from data
group by 1, 2
order by 1, 2 ;
Why? That might be a little hard to explain. Perhaps if you see the equivalent version with a subquery it will be clearer:
select me.*
sum(sum_events) over (partition by month
order by SubAge asc
rows between unbounded preceding and current row
) as TotEvents
from (select month, EventAge, sum(events) as sum_events
from data
group by 1, 2
) me
order by 1, 2 ;
This is pretty much an exactly shorthand for the query. The window function is evaluated after aggregation. You want to sum the SUM of the events after the aggregation. Hence, you need sum(sum(events)). After the aggregation, events is no longer available.
The nesting of aggregation functions is awkward at first -- at least it was for me. When I first started using window functions, I think I first spent a few days writing aggregation queries using subqueries and then rewriting without the subqueries. Quickly, I got used to writing them without subqueries.
Hi I am a newbie when it comes to SQL and was hoping someone can help me in this matter. I've been using the lag function here and there but was wondering if there is a way to rewrite it to make it into a sum range. So instead of prior one month, i want to take the prior 12 months and sum them together for each period. I don't want to write 12 lines of lag but was wondering if there is a way to get it with less lines of code. Note there will be nulls and if one of the 12 records is null then it should be null.
I know you can write write subquery to do this, but was wondering if this is possible. Any help would be much appreciated.
You want the "window frame" part of the window function. A moving 12-month average would look like:
select t.*,
sum(balance) over (order by period rows between 11 preceding and current row) as moving_sum_12
from t;
You can review window frames in the documentation.
If you want a cumulative sum, you can leave out the window frame entirely.
I should note that you can also do this using lag(), but it is much more complicated:
select t.*,
(balance +
lag(balance, 1, 0) over (order by period) +
lag(balance, 2, 0) over (order by period) +
. . .
lag(balance, 11, 0) over (order by period) +
) as sum_1112
from t;
This uses the little known third argument to lag(), which is the default value to use if the record is not available. It replaces a coalesce().
EDIT:
If you want NULL if 12 values are not available, then use case and count() as well:
select t.*,
(case when count(*) over (order by period rows between 11 preceding and current row) = 12
then sum(balance) over (order by period rows between 11 preceding and current row)
end) as moving_sum_12
from t;
I want to incorporate two average calculations for a bunch of value columns in my select statement.
see this link for my simplified table structure including the desired output calculation: Pastebin
1) moving average:
Month1 = value of the value1-column for that month, Month2 = if sum == 0 then write 0, else avg(Month1 and Month2) and so on.
So for each product, I want the moving average for each month within one year.
I have this set up in my Excel but I can't transfer the expression to sql.
2) overall average:
for each product, calculate the average over all years and duplicate the calculated value to all rows for that product.
I hope you can help me out with this. It looks like I need a procedure but maybe it is just a simple statement.
SQL-Server 2012 supports the analytic functions required to do this:
SELECT Product,
Month,
Year,
Value,
AVG_YTD = AVG(Value) OVER(PARTITION BY Year ORDER BY Month),
AVG_Year = AVG(Value) OVER(PARTITION BY Product, Year),
AVG_Overall = AVG(Value) OVER(PARTITION BY Product)
FROM T;
Simplified Example on SQL Fiddle