please help me with getting streaks data. I have table of goal achievements
Table test
dt
2017-01-01
2017-01-02
2017-01-03. //3 days end of streak
2017-02-10 // 1 day
2017-02-15
2017-02-16
2017-02-17
2017-02-18 //4 days
I tried this in MySQL
Select dt, (select count(*) from test as t1 where t1.dt < t2.dt and datediff(t2.dt,t1.dt) =1) as str
from test as t2
And got
Dt str
2017-01-01 0
2017-01-02 1
2017-01-03 2
2017-02-10 0
2017-02-15 0
2017-02-16 1
2017-02-17 2
2017-02-18 3
Is it possible to get something like this
Dt. Str
2017-01-03 3
2017-02-10 1
2017-02-18 4
And get Max of it?
You can subtract row number (i.e the number of rows <= current row's date) from the current row's date to classify consecutive rows with one day difference into the same group. Then it is just a grouping operation to calculate the count.
select max(dt) as dt, count(*) as streak
from (select t1.dt
,date(t1.dt,-(select count(*) from t t2 where t2.dt<=t1.dt)||' day') as grp
from t t1
) t
group by grp
Run the inner query to see how groups are assigned.
Related
I have the next data: TABLE_A
RegisteredDate
Quantity
2022-03-01 13:00
100
2022-03-01 13:10
20
2022-03-01 13:20
-80
2022-03-01 13:30
-40
2022-03-02 09:00
10
2022-03-02 22:00
-5
2022-03-03 02:00
-5
2022-03-03 03:00
25
2022-03-03 03:20
-10
If I add cumulative column
select RegisteredDate, Quantity
, sum(Quantity) over ( order by RegisteredDate ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as Summary
from TABLE_A
RegisteredDate
Quantity
Summary
2022-03-01 13:00
100
100
2022-03-01 13:10
20
120
2022-03-01 13:20
-80
40
2022-03-01 13:30
-40
0
2022-03-02 09:00
10
10
2022-03-02 22:00
-5
5
2022-03-03 02:00
-5
0
2022-03-03 03:00
25
25
2022-03-03 03:20
-10
15
Is there a way to get the following result with a query?
RegisteredDate
Quantity
Summary
2022-03-03 03:00
25
25
2022-03-03 03:20
-10
15
This result is the last records after the last zero.
EDIT:
Really for the solution to this problem I need the: 2022-03-03 03:00 is the first date of the last records after the last zero.
You can try to use SUM aggregate window function to calculation grp column which part represent to last value accumulated.
Query 1:
WITH cte AS
(
SELECT RegisteredDate,
Quantity,
sum(Quantity) over (order by RegisteredDate ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as Summary
FROM TABLE_A
), cte2 AS (
SELECT *,
SUM(CASE WHEN Summary = 0 THEN 1 ELSE 0 END) OVER(order by RegisteredDate desc) grp
FROM cte
)
SELECT RegisteredDate,
Quantity
FROM cte2
WHERE grp = 0
ORDER BY RegisteredDate
Results:
| RegisteredDate | Quantity |
|----------------------|----------|
| 2022-03-03T03:00:00Z | 25 |
| 2022-03-03T03:20:00Z | -10 |
Use a CTE that returns the summary column and NOT EXISTS to filter out the rows that you don't need:
WITH cte AS (SELECT *, SUM(Quantity) OVER (ORDER BY RegisteredDate) Summary FROM TABLE_A)
SELECT c1.*
FROM cte c1
WHERE NOT EXISTS (
SELECT 1
FROM cte c2 WHERE c2.RegisteredDate >= c1.RegisteredDate AND c2.Summary = 0
)
ORDER BY c1.RegisteredDate;
There is no need for ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW in the OVER clause of the window function, because this is the default behavior.
See the demo.
Try this:
with u as
(select RegisteredDate,
Quantity,
sum(Quantity) over (order by RegisteredDate ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as Summary
from TABLE_A)
select * from u
where RegisteredDate >= all(select RegisteredDate from u where Summary = 0)
and Summary <> 0;
Fiddle
Basically what you want is for RegisteredDate to be >= all RegisteredDatess where Summary = 0, and you want Summary <> 0.
When using window functions, it is necessary to take into account that RegisteredDate column is not unique in TABLE_A, so ordering only by RegisteredDate column is not enough to get a stable result on the same dataset.
With A As (
Select ROW_NUMBER() Over (Order by RegisteredDate, Quantity) As ID, RegisteredDate, Quantity
From TABLE_A),
B As (
Select A.*, SUM(Quantity) Over (Order by ID) As Summary
From A)
Select Top 1 *
From B
Where ID > (Select MAX(ID) From B Where Summary=0)
ID
RegisteredDate
Quantity
Summary
8
2022-03-03 03:00
25
25
Is it possible to group records based on a predefined date range differences (e.g. 30 days) based on the start_date of a row and the end_date of the previous row for non-consecutive dates? I want to take the min(start_date) and max(end_date) of each group. I tried the lead and lag function with partition by in Oracle but couldn't come up with a proper solution. A related but unanswered post related to my question can be found here.
E.g.
ROW_NUM PROJECT_ID START_DATE END_DATE
1 1 2016-01-14 2016-08-15
2 1 2016-08-16 2016-09-10 --- Date diff Row 1&2 = 1 Day
3 1 2016-11-15 2017-01-10 --- Date diff Row 2&3 = 66 Days
4 1 2016-01-17 2017-04-10 --- Date diff Row 3&4 = 7 Days
5 2 2018-04-28 2018-06-01 --- Other Project
6 2 2019-02-01 2019-04-05 --- Diff > 30 Days
7 2 2019-04-08 2019-07-28 --- Diff 3 Days
Expected Result:
ROW_NUM PROJECT_ID START_DATE END_DATE
1 1 2016-01-14 2016-09-10
3 1 2016-11-15 2017-04-10
5 2 2018-04-28 2018-06-01
6 2 2019-02-01 2019-07-28
Use lag() and a cumulative sum to define where the groups begin. Then aggregate:
select project_id, min(start_date), max(end_date)
from (select t.*,
sum(case when prev_end_date > start_date - interval '30' day then 0 else 1 end) over
(partition by project_id order by start_date) as grp
from (select t.*,
lag(end_date) over (partition by project_id order by start_date) as prev_end_date
from t
) t
) t
group by project_id, grp;
I am trying to calculate a moving average of several fields in a SQL Server database that involved irregularly-spaced values over time. I realized that for regularly-spaced data I can use an SELECT grp, AVG(count) FROM t ... OVER (PARTITION BY grp ... ROWS 7 PRECEDING) to create a moving average of the prior week's data. However, I have data organized as follows:
DATE GRP COUNT
2018-07-05 1 10
2018-07-08 1 4
2018-07-11 1 6
2018-07-12 1 6
2018-07-11 2 5
2018-07-15 2 10
2018-07-17 2 8
2018-07-20 2 10
...
Where for most groups there are no observations for some dates. The output I'm looking for is:
DATE GRP MOVING_AVG
2018-07-05 1 10
2018-07-08 1 7
2018-07-11 1 6.67
2018-07-13 1 5.33
2018-07-11 2 5
2018-07-15 2 7.5
2018-07-16 2 7.67
2018-07-20 2 9.33
Is there a way of specifying dates instead of rows in the PRECEDING clause, or do I have to create some sort of mask to average over?
EDITED FOR CLARIFICATION BASED ON COMMENTS
In SQL Server, I think this might be simpler achieved with a lateral join:
select
date,
grp,
(
select avg(count)
from mytable t1
where
t1.grp = t.grp
and t1.date >= dateadd(year, -1, t.date)
and t1.date <= t.date
) as cnt
from mytable
If i'm not misunderstanding. You want 7 or whatever days but rows before a date.
DATE GRP COUNT
2018-07-11 2 5
2018-07-15 2 10
2018-07-17 2 8
2018-07-20 2 10 <--- the AVG of this row must include 7 days before,so 2018-07-11 not include
In that case :
select
date,
grp,
(
select avg(count)
from t t1
where
t1.grp = t.grp
and DATEDIFF(day, t1.date, t.date) <= 7 /*7 or whatever day you want*/
and t1.date <= t.date
) as MOVING_AVG
from t
I am learning SQL and I was wondering how to select active users by month, depending on their starting and ending date (both timestamp(6)). My table looks like this:
Cust_Num | Start_Date | End_Date
1 | 2018-01-01 | 2019-01-01
2 | 2018-01-01 | NULL
3 | 2019-01-01 | 2019-06-01
4 | 2017-01-01 | 2019-03-01
So, counting the active users by month, I should have an output like:
As of. | Count
2018-06-01 | 3
...
2019-02-01 | 3
2019-07-01 | 1
So far, I do a manual operation by entering each month:
Select
201906,
count(distinct a.cust_num)
From
active_users a
Where
to_date(‘20190630’,’yyyymmdd) between a.start_date and nvl (a.end_date, ‘31-dec-9999)
union all
Select
201905,
count(distinct a.cust_num)
From
active_users a
Where
to_date(‘20190531’,’yyyymmdd) between a.start_date and nvl (a.end_date, ‘31-dec-9999)
union all
...
Not very optimized and sustainable if I want to enter 10 years ao 120 months lol.
Any help is welcome. Thanks a lot!
This query shows the active-user-count effective as-of the end of the month.
How it works:
Convert each input row (with StartDate and EndDate value) into two rows that represent a point-in-time when the active-user-count incremented (on StartDate) and decremented (on EndDate). We need to convert NULL to a far-off date value because NULL values are sorted before instead of after non-NULL values:
This makes your data look like this:
OnThisDate Change
2018-01-01 1
2019-01-01 -1
2018-01-01 1
9999-12-31 -1
2019-01-01 1
2019-06-01 -1
2017-01-01 1
2019-03-01 -1
Then we simply SUM OVER the Change values (after sorting) to get the active-user-count as of that specific date:
So first, sort by OnThisDate:
OnThisDate Change
2017-01-01 1
2018-01-01 1
2018-01-01 1
2019-01-01 1
2019-01-01 -1
2019-03-01 -1
2019-06-01 -1
9999-12-31 -1
Then SUM OVER:
OnThisDate ActiveCount
2017-01-01 1
2018-01-01 2
2018-01-01 3
2019-01-01 4
2019-01-01 3
2019-03-01 2
2019-06-01 1
9999-12-31 0
Then we PARTITION (not group!) the rows by month and sort them by their date so we can identify the last ActiveCount row for that month (this actually happens in the WHERE of the outermost query, using ROW_NUMBER() and COUNT() for each month PARTITION):
OnThisDate ActiveCount IsLastInMonth
2017-01-01 1 1
2018-01-01 2 0
2018-01-01 3 1
2019-01-01 4 0
2019-01-01 3 1
2019-03-01 2 1
2019-06-01 1 1
9999-12-31 0 1
Then filter on that where IsLastInMonth = 1 (actually, where ROW_COUNT() = COUNT(*) inside each PARTITION) to give us the final output data:
At-end-of-month Active-count
2017-01 1
2018-01 3
2019-01 3
2019-03 2
2019-06 1
9999-12 0
This does result in "gaps" in the result-set because the At-end-of-month column only shows rows where the Active-count value actually changed rather than including all possible calendar months - but that's ideal (as far as I'm concerned) because it excludes redundant data. Filling in the gaps can be done inside your application code by simply repeating output rows for each additional month until it reaches the next At-end-of-month value.
Here's the query using T-SQL on SQL Server (I don't have access to Oracle right now). And here's the SQLFiddle I used to come to a solution: http://sqlfiddle.com/#!18/ad68b7/24
SELECT
OtdYear,
OtdMonth,
ActiveCount
FROM
(
-- This query adds columns to indicate which row is the last-row-in-month ( where RowInMonth == RowsInMonth )
SELECT
OnThisDate,
OtdYear,
OtdMonth,
ROW_NUMBER() OVER ( PARTITION BY OtdYear, OtdMonth ORDER BY OnThisDate ) AS RowInMonth,
COUNT(*) OVER ( PARTITION BY OtdYear, OtdMonth ) AS RowsInMonth,
ActiveCount
FROM
(
SELECT
OnThisDate,
YEAR( OnThisDate ) AS OtdYear,
MONTH( OnThisDate ) AS OtdMonth,
SUM( [Change] ) OVER ( ORDER BY OnThisDate ASC ) AS ActiveCount
FROM
(
SELECT
StartDate AS [OnThisDate],
1 AS [Change]
FROM
tbl
UNION ALL
SELECT
ISNULL( EndDate, DATEFROMPARTS( 9999, 12, 31 ) ) AS [OnThisDate],
-1 AS [Change]
FROM
tbl
) AS sq1
) AS sq2
) AS sq3
WHERE
RowInMonth = RowsInMonth
ORDER BY
OtdYear,
OtdMonth
This query can be flattened into fewer nested queries by using aggregate and window functions directly instead of using aliases (like OtdYear, ActiveCount, etc) but that would make the query much harder to understand.
I have created the query which will give the result of all the months starting from the minimum start date in the table till maximum end date.
You can change it using adding one condition in WHERE clause.
-- table creation
CREATE TABLE ACTIVE_USERS (CUST_NUM NUMBER, START_DATE DATE, END_DATE DATE)
-- data creation
INSERT INTO ACTIVE_USERS
SELECT * FROM
(
SELECT 1, DATE '2018-01-01', DATE '2019-01-01' FROM DUAL UNION ALL
SELECT 2, DATE '2018-01-01', NULL FROM DUAL UNION ALL
SELECT 3, DATE '2019-01-01', DATE '2019-06-01' FROM DUAL UNION ALL
SELECT 4, DATE '2017-01-01', DATE '2019-03-01' FROM DUAL
)
-- data in the actual table
SELECT * FROM ACTIVE_USERS ORDER BY CUST_NUM;
CUST_NUM START_DATE END_DATE
---------- ---------- ----------
1 2018-01-01 2019-01-01
2 2018-01-01
3 2019-01-01 2019-06-01
4 2017-01-01 2019-03-01
Query to fetch desired result
WITH CTE ( START_DATE, END_DATE ) AS
(
SELECT
ADD_MONTHS( START_DATE, LEVEL - 1 ),
ADD_MONTHS( START_DATE, LEVEL ) - 1
FROM
(
SELECT
MIN( START_DATE ) AS START_DATE,
MAX( END_DATE ) AS END_DATE
FROM
ACTIVE_USERS
)
CONNECT BY LEVEL <= CEIL( MONTHS_BETWEEN( END_DATE, START_DATE ) ) + 1
)
--
--
SELECT
C.START_DATE,
COUNT(1) AS CNT
FROM
CTE C
JOIN ACTIVE_USERS D ON
(
C.END_DATE BETWEEN
D.START_DATE
AND
CASE
WHEN D.END_DATE IS NOT NULL THEN D.END_DATE
ELSE C.END_DATE
END
)
GROUP BY
C.START_DATE
ORDER BY
C.START_DATE;
-- output --
START_DATE CNT
---------- ----------
2017-01-01 1
2017-02-01 1
2017-03-01 1
2017-04-01 1
2017-05-01 1
2017-06-01 1
2017-07-01 1
2017-08-01 1
2017-09-01 1
2017-10-01 1
2017-11-01 1
START_DATE CNT
---------- ----------
2017-12-01 1
2018-01-01 3
2018-02-01 3
2018-03-01 3
2018-04-01 3
2018-05-01 3
2018-06-01 3
2018-07-01 3
2018-08-01 3
2018-09-01 3
2018-10-01 3
START_DATE CNT
---------- ----------
2018-11-01 3
2018-12-01 3
2019-01-01 3
2019-02-01 3
2019-03-01 2
2019-04-01 2
2019-05-01 2
2019-06-01 1
30 rows selected.
Cheers!!
I have the following data and I want to subtract current row from previous row based on the UserID. I tried the code below is not given me what I want
DECLARE #DATETBLE TABLE (UserID INT, Dates DATE)
INSERT INTO #DATETBLE VALUES
(1,'2018-01-01'), (1,'2018-01-02'), (1,'2018-01-03'),(1,'2018-01-13'),
(2,'2018-01-15'),(2,'2018-01-16'),(2,'2018-01-17'), (5,'2018-02-04'),
(5,'2018-02-05'),(5,'2018-02-06'),(5,'2018-02-11'), (5,'2018-02-17')
;with cte as (
select UserID,Dates, row_number() over (order by UserID) as seqnum
from #DATETBLE t
)
select t.UserID,t.Dates, datediff(day,tprev.Dates,t.Dates)as diff
from cte t left outer join
cte tprev
on t.seqnum = tprev.seqnum + 1;
Current Output
UserID Dates diff
1 2018-01-01 NULL
1 2018-01-02 1
1 2018-01-03 1
1 2018-01-13 10
2 2018-01-15 2
2 2018-01-16 1
2 2018-01-17 1
5 2018-02-04 18
5 2018-02-05 1
5 2018-02-06 1
5 2018-02-11 5
5 2018-02-17 6
My Expected Output
UserID Dates diff
1 2018-01-01 NULL
1 2018-01-02 1
1 2018-01-03 1
1 2018-01-13 10
2 2018-01-15 NULL
2 2018-01-16 1
2 2018-01-17 1
5 2018-02-04 NULL
5 2018-02-05 1
5 2018-02-06 1
5 2018-02-11 5
5 2018-02-17 6
Your tag (sql-server-2008) suggests me to use APPLY :
select t.userid, t.dates, datediff(day, t1.dates, t.dates) as diff
from #DATETBLE t outer apply
( select top (1) t1.*
from #DATETBLE t1
where t1.userid = t.userid and
t1.dates < t.dates
order by t1.dates desc
) t1;
If you have SQL Server version 2012 or higher, you could use LAG() with a partition by UserID:
SELECT UserID
, DATEDIFF(dd,COALESCE(LAG_DATES, Dates), Dates) as diff
FROM
(
SELECT UserID
, Dates
, LAG(Dates) OVER (PARTITION BY UserID ORDER BY Dates) as LAG_DATES
FROM #DATETBLE
) exp
This will give you a 0 value instead of a NULL value for the first date in the sequence though.
Since you tagged the post with SQL Server 2008, however, you may need to use a method that doesn't rely on this windowed function.