The question I have is very similar to the question here, but I am using Presto SQL (on aws athena) and couldn't find information on loops in presto.
To reiterate the issue, I want the query that:
Given table that contains: Day, Number of Items for this Day
I want: Day, Average Items for Last 7 Days before "Day"
So if I have a table that has data from Dec 25th to Jan 25th, my output table should have data from Jan 1st to Jan 25th. And for each day from Jan 1-25th, it will be the average number of items from last 7 days.
Is it possible to do this with presto?
maybe you can try this one
calendar Common Table Expression (CTE) is used to generate dates between two dates range.
with calendar as (
select date_generated
from (
values (sequence(date'2021-12-25', date'2022-01-25', interval '1' day))
) as t1(date_array)
cross join unnest(date_array) as t2(date_generated)),
temp CTE is basically used to make a date group which contains last 7 days for each date group.
temp as (select c1.date_generated as date_groups
, format_datetime(c2.date_generated, 'yyyy-MM-dd') as dates
from calendar c1, calendar c2
where c2.date_generated between c1.date_generated - interval '6' day and c1.date_generated
and c1.date_generated >= date'2021-12-25' + interval '6' day)
Output for this part:
date_groups
dates
2022-01-01
2021-12-26
2022-01-01
2021-12-27
2022-01-01
2021-12-28
2022-01-01
2021-12-29
2022-01-01
2021-12-30
2022-01-01
2021-12-31
2022-01-01
2022-01-01
last part is joining day column from your table with each date and then group it by the date group
select temp.date_groups as day
, avg(your_table.num_of_items) avg_last_7_days
from your_table
join temp on your_table.day = temp.dates
group by 1
You want a running average (AVG OVER)
select
day, amount,
avg(amount) over (order by day rows between 6 preceding and current row) as avg_amount
from mytable
order by day
offset 6;
I tried many different variations of getting the "running average" (which I now know is what I was looking for thanks to Thorsten's answer), but couldn't get the output I wanted exactly with my other columns (that weren't included in my original question) in the table, but this ended up working:
SELECT day, <other columns>, avg(amount) OVER (
PARTITION BY <other columns>
ORDER BY date(day) ASC
ROWS 6 PRECEDING) as avg_7_days_amount FROM table ORDER BY date(day) ASC
Related
For many years I've been collecting data and I'm interested in knowing the historic counts of IDs that appeared in the last 30 days. The source looks like this
id
dates
1
2002-01-01
2
2002-01-01
3
2002-01-01
...
...
3
2023-01-10
If I wanted to know the historic count of ids that appeared in the last 30 days I would do something like this
with total_counter as (
select id, count(id) counts
from source
group by id
),
unique_obs as (
select id
from source
where dates >= DATEADD(Day ,-30, current_date)
group by id
)
select count(distinct(id))
from unique_obs
left join total_counter
on total_counter.id = unique_obs.id;
The problem is that this results would return a single result for today's count as provided by current_date.
I would like to see a table with such counts as if for example I had ran this analysis yesterday, and the day before and so on. So the expected result would be something like
counts
date
1235
2023-01-10
1234
2023-01-09
1265
2023-01-08
...
...
7383
2022-12-11
so for example, let's say that if the current_date was 2023-01-10, my query would've returned 1235.
If you need a distinct count of Ids from the 30 days up to and including each date the below should work
WITH CTE_DATES
AS
(
--Create a list of anchor dates
SELECT DISTINCT
dates
FROM source
)
SELECT COUNT(DISTINCT s.id) AS "counts"
,D.dates AS "date"
FROM CTE_DATES D
LEFT JOIN source S ON S.dates BETWEEN DATEADD(DAY,-29,D.dates) AND D.dates --30 DAYS INCLUSIVE
GROUP BY D.dates
ORDER BY D.dates DESC
;
If the distinct count didnt matter you could likely simplify with a rolling sum, only hitting the source table once:
SELECT S.dates AS "date"
,COUNT(1) AS "count_daily"
,SUM("count_daily") OVER(ORDER BY S.dates DESC ROWS BETWEEN CURRENT ROW AND 29 FOLLOWING) AS "count_rolling" --assumes there is at least one row for every day.
FROM source S
GROUP BY S.dates
ORDER BY S.dates DESC;
;
This wont work though if you have gaps in your list of dates as it'll just include the latest 30 days available. In which case the first example without distinct in the count will do the trick.
SELECT count(*) AS Counts
dates AS Date
FROM source
WHERE dates >= DATEADD(DAY, -30, CURRENT_DATE)
GROUP BY dates
ORDER BY dates DESC
Have a requirement where I would need to rope the calculated value of the previous row for calculation in the current row.
The following is a sample of how the data currently looks :-
ID
Date
Days
1
2022-01-15
30
2
2022-02-18
30
3
2022-03-15
90
4
2022-05-15
30
The following is the output What I am expecting :-
ID
Date
Days
CalVal
1
2022-01-15
30
2022-02-14
2
2022-02-18
30
2022-03-16
3
2022-03-15
90
2022-06-14
4
2022-05-15
30
2022-07-14
The value of CalVal for the first row is Date + Days
From the second row onwards it should take the CalVal value of the previous row and add it with the current row Days
Essentially, what I am looking for is means to access the previous rows calculated value for use in the current row.
Is there anyway we can achieve the above via Postgres SQL? I have been tinkering with window functions and even recursive CTEs but have had no luck :(
Would appreciate any direction!
Thanks in advance!
select
id,
date,
coalesce(
days - (lag(days, 1) over (order by date, days))
, days) as days,
first_date + cast(days as integer) as newdate
from
(
select
-- get a running sum of days
id,
first_date,
date,
sum(days) over (order by date, days) as days
from
(
select
-- get the first date
id,
(select min(date) from table1) as first_date,
date,
days
from
table1
) A
) B
This query get the exact output you described. I'm not at all ready to say it is the best solution but the strategy employed is to essential create a running total of the "days" ... this means that we can just add this running total to the first date and that will always be the next date in the desired sequence. One finesse: to put the "days" back into the result, we calculated the current running total less the previous running total to arrive at the original amount.
assuming that table name is table1
select
id,
date,
days,
first_value(date) over (order by id) +
(sum(days) over (order by id rows between unbounded preceding and current row))
*interval '1 day' calval
from table1;
We just add cumulative sum of days to first date in table. It's not really what you want to do (we don't need date from previous row, just cumulative days sum)
Solution with recursion
with recursive prev_row as (
select id, date, days, date+ days*interval '1 day' calval
from table1
where id = 1
union all
select t.id, t.date, t.days, p.calval + t.days*interval '1 day' calval
from prev_row p
join table1 t on t.id = p.id+ 1
)
select *
from prev_row
If you have table like this:
Name
Data type
UserID
INT
StartDate
DATETIME
EndDate
DATETIME
With data like this:
UserID
StartDate
EndDate
21
2021-01-02 00:00:00
2021-01-02 23:59:59
21
2021-01-03 00:00:00
2021-01-04 15:42:00
24
2021-01-02 00:00:00
2021-01-06 23:59:59
And you want to calculate number of users that is represented on each day in a week with a result like this:
Year
Week
NumberOfTimes
2021
1
8
2021
2
10
2021
3
4
Basically I want to to a Select like this:
SELECT YEAR(dateColumn) AS yearname, WEEK(dateColumn)as week name, COUNT(somecolumen)
GROUP BY YEAR(dateColumn) WEEK(dateColumn)
The problem I have is the start and end date if the date goes over several days I want it to counted each day. Preferably I don't want the same user counted twice each day. There are millions of rows that are constantly being deleted and added so speed is key.
The database is MS-SQL 2019
I would suggest a recursive CTE:
with cte as (
select userid, startdate, enddate
from t
union all
select userid, startdate,
enddate
from cte
where startdate < enddate and
week(startdate) <> week(enddate)
)
select year(startdate), week(startdate), count(*)
from cte
group by year(startdate), week(startdate)
option (maxrecursion 0);
The CTE expands the data by adding 7 days to each row. This should be one day per week.
There is a little logic in the second part to handle the situation where the enddate ends in the same week as the last start date. The above solution assumes that the dates are all in the same year -- which seems quite reasonable given the sample data. There are other ways to prevent this problem.
You need to cross-join each row with the relevant dates.
Create a calendar table with columns of years and weeks, include a start and end date of the week. See here for an example of how to create one, and make sure you index those columns.
Then you can cross-join like this
SELECT
YEAR(dateColumn) AS yearname,
WEEK(dateColumn)as weekname,
COUNT(somecolumen)
FROM Table t
JOIN CalendarWeek c ON c.StartDate >= t.StartDate AND c.EndDate <= t.EndDate
GROUP BY YEAR(dateColumn), WEEK(dateColumn)
I want to know the trick to find the list of customers who are transacting for consecutive 3 months ,that could be any 3 consecutive months with any number of occurrence.
example: suppose there is customer who transact in January then keep transacting till march then he stopped transacting.I want the list of these customer from my database .
I am working on AWS Athena.
One method uses aggregation and window functions:
select customer_id, yyyymm_2
from (select date_trunc(month, transactdate) as yyyymm, customer_id,
lag(date_trunc(month, transactdate), 2) over (partition by customer_id order by date_trunc(month, transactdate)) as prev_yyyymm_2
from t
where transactdate >= '2017-01-01' and
transactadte < '2019-01-01'
)
where prev_dt_2 = yyyymm - interval '2' month;
This aggregates transactions by month and looks at the transaction date two rows earlier. The outer filter checks that that date is exactly 2 months earlier.
I have a table of 'semesters' of variable lengths with variable breaks in between them with a constraint such that a 'start_date' is always greater than the previous 'end_date':
id start_date end_date
-----------------------------
1 2012-10-01 2012-12-20
2 2013-01-05 2013-03-28
3 2013-04-05 2013-06-29
4 2013-07-10 2013-09-20
And a table of students as follows, where a start date may occur at any time within a given semester:
id start_date n_weeks
-------------------------
1 2012-11-15 25
2 2013-02-12 8
3 2013-03-02 12
I am attempting to compute an 'end_date' by joining the 'students' on 'semesters' which takes into account the variable-length breaks in-between semesters.
I can draw in the previous semester's end date (ie from the previous row's end_date) and by subtraction find the number of days in-between semesters using the following:
SELECT start_date
, end_date
, lag(end_date) OVER () AS prev_end_date
, start_date - lag(end_date) OVER () AS days_break
FROM terms
ORDER BY start_date;
Clearly, if there were to be only two terms, it would simply be a matter of adding the 'break' in days (perhaps, cast to 'weeks') -- and thereby extend the 'end_date' by that same period of time.
But should 'n_weeks' for a given student span more than one term, how could such a query be structured ?
Been banging my head against a wall for the last couple of days and I'd be immensely grateful for any help anyone would be able to offer....
Many thanks.
Rather than just looking at the lengths of semesters or the gaps between them, you could generate a list of all the dates that are within a semester using generate_series(), like this:
SELECT
row_number() OVER () as day_number,
day
FROM
(
SELECT
generate_series(start_date, end_date, '1 day') as day
FROM
semesters
) as day_series
ORDER BY
day
(SQLFiddle demo)
This assigns each day that is during a semester an arbitrary but sequential "day number", skipping out all the gaps between semesters.
You can then use this as a sub-query/CTE JOINed to your table of students: first find the "day number" of their start date, then add 7 * n_weeks to find the "day number" of their end date, and finally join back to find the actual date for that "day number".
This assumes that there is no special handling needed for partial weeks - i.e. if n_weeks is 4, the student must be enrolled for 28 days which are within the duration of a semeseter. The approach could be adapted to measure weeks (pass 1 week as the last argument to generate_series()), with the additional step of finding which week the student's start_date falls into.
Here's a complete query (SQLFiddle demo here):
WITH semester_days AS
(
SELECT
semester_id,
row_number() OVER () as day_number,
day_date::date
FROM
(
SELECT
id as semester_id,
generate_series(start_date, end_date, '1 day') as day_date
FROM
semesters
) as day_series
ORDER BY
day_date
)
SELECT
S.id as student_id,
S.start_date,
SD_start.semester_id as start_semester_id,
S.n_weeks,
SD_end.day_date as end_date,
SD_end.semester_id as end_semester_id
FROM
students as S
JOIN
semester_days as SD_start
On SD_start.day_date = S.start_date
JOIN
semester_days as SD_end
On SD_end.day_number = SD_start.day_number + (7 * S.n_weeks)
ORDER BY
S.start_date