I am trying to form a query for returning, reactivated and WAU as defined below:
Returning WAU - active last week
WAU - not active last week, but active within last 30 days
Reactivated WAU – not seen in 30+ days
I have table for past 60 days containing cust_id, login date but cant lag function to work (Teradata ODBC connection). I keep getting this error:
[3706] Syntax error: Data Type "logindate" does not match a Defined
Type name. My format is: select .... lag(logindate, 1) over (partition
by cust_id order by 1 asc) as lag_ind from ( ....
Please help for the 3 cases above.
You can aggregate to get the expected answer:
select cust_id,
case
when max(logindate) > current_date - 7 -- active last week
then 'Returning WAU'
when max(logindate) > current_date - 30 -- not active last week, but active within last 30 days
then 'WAU'
else 'Reactivated WAU' –- not seen in 30+ days
end
from tab
group by 1
Regarding the issue with LAG, this has been introduced in 16.10, before you have to rewrite:
lag(logindate, 1)
over (partition by cust_id
order by col asc) as lag_ind
max(logindate)
over (partition by cust_id
order by col asc
rows between 1 preceding and 1 preceding) as lag_ind
Hint: never use ORDER BY 1 in an OLAP function, here it's the literal value one and not the first column.
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'm trying to determine the length of time in days between using the AR_Event_Creation_Date_Time for every other row. For example, the number of days between the 1 and 2 row, 3rd and 4th, 5th and 6th etc. In other words, there will be a number of days value for every even row and NULL for every odd row. My code below works if there are only two rows per borrower number but falls down when there are more than two. In the results, notice the change in 1002092539
SELECT Borrower_Number,
Workgroup_Name,
FORMAT(AR_Event_Creation_Date_Time,'d','en-us') AS Tag_Date,
Usr_Usrnm,
DATEDIFF(day, LAG(AR_Event_Creation_Date_Time,1) OVER(PARTITION BY
Borrower_Number Order By Borrower_Number), AR_Event_Creation_Date_Time) Diff
FROM Control_Mail
You need to add in a row number. Also your partition by is non-deterministic:
SELECT Borrower_Number,
Workgroup_Name,
FORMAT(AR_Event_Creation_Date_Time,'d','en-us') AS Tag_Date,
Usr_Usrnm,
DATEDIFF(day, LAG(AR_Event_Creation_Date_Time,1) OVER(PARTITION BY Borrower_Number, (rn - 1) / 2 ORDER BY AR_Event_Creation_Date_Time),
AR_Event_Creation_Date_Time) Diff
FROM (
SELECT *,
ROW_NUMBER() OVER (PARTITION BY Borrower_Number ORDER BY AR_Event_Creation_Date_Time) AS rn
FROM Control_Mail
) C
```
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 am trying to create following logic in Alteryx and data is coming from Exasol database.
Column “Sum_Qty_28_days“ should sum up the values of “Qty ” column for same article which falls under last 28 days.
My sample data looks like:
and I want following output:
E.g. “Sum_Qty_28_days” value for “article” = ‘A’ and date = ‘’2019-10-8” is 8 because it is summing up the “Qty” values associated with dates (coming within previous 28 days) Which are:
2019-09-15
2019-10-05
2019-10-08
for “article” = ‘A’.
Is this possible using SQL window function?
I tried myself with following code:
SUM("Qty") OVER (PARTITION BY "article", date_trunc('month',"Date")
ORDER BY "Date")
But, it is far from what I need. It is summing up the Qty for dates falling in same month. However, I need to sum of Qty for last 28 days.
Thanks in advance.
Yes, this is possible using standard SQL and in many databases. However, this will not work in all databases:
select t.*,
sum(qty) over (partition by article
order by date
range between interval '27 day' preceding and current row
) as sum_qty_28_days
from t;
If your RDBMS does not support the range frame, an alternative solution is to use an inline subquery:
select
t.*,
(
select sum(t1.qty)
from mytable t1
where
t1.article = t.article
and t1.date between t.date - interval 28 days and t.date
) sum_qty_28_days
from mytable t
So I have created a table that has the following columns from a transaction table with all customer purchase records:
1. Month-Year, 2.Customer ID, 3. Number of Transactions in that month.
I'm trying to create a table that has the output of
1. Month-Year, 2. Number of active customers defined by having at least 1 purchase in the previous year.
The code that I have currently is this but the case when obviously only capturing one date and the where clause isn't dynamic. Would really appreciate your help.
select month_start_date, cust_ID,
(case when month_start_Date between date and add_months(date, -12) then count(cust_ID) else 0 end) as active
from myserver.mytable
where
month_start_Date>add_months(month_start_date,-12)
group by 1,2
EDIT: I'm just trying to put a flag next to a customer if they are active in each month defined as having at least one transaction in the last year thanks!
You might use Teradata's proprietary EXPAND ON synax for creating time series:
SELECT month_start_date, COUNT(*)
FROM
( -- create one row for every month within the next year
-- after a customer's transaction
SELECT DISTINCT
BEGIN(pd) AS month_start_date,
cust_ID
FROM myserver.mytable
EXPAND ON PERIOD(month_start_date, ADD_MONTHS(month_start_date,12)) AS pd
BY ANCHOR MONTH_BEGIN -- every 1st of month
FOR PERIOD (DATE - 500, DATE) -- use this to restrict to a specific date range
) AS dt
GROUP BY month_start_date
ORDER BY month_start_date