In the query below, I don't get the results i would expect. Any insights why? How could i reformulate such query to get the desired results?
Schema (SQLite v3.30)
WITH RECURSIVE
cnt(x,y) AS (VALUES(0,ABS(Random()%3)) UNION ALL SELECT x+1, ABS(Random()%3) FROM cnt WHERE x<10),
i_rnd as (SELECT r1.x, r1.y, (SELECT COUNT(*) FROM cnt as r2 WHERE r2.y<=r1.y) as idx FROM cnt as r1)
SELECT * FROM i_rnd ORDER BY y;
result:
| x | y | idx |
| --- | --- | --- |
| 1 | 0 | 3 |
| 5 | 0 | 6 |
| 8 | 0 | 5 |
| 9 | 0 | 4 |
| 10 | 0 | 2 |
| 3 | 1 | 4 |
| 0 | 2 | 11 |
| 2 | 2 | 11 |
| 4 | 2 | 11 |
| 6 | 2 | 11 |
| 7 | 2 | 11 |
expected result:
| x | y | idx |
| --- | --- | --- |
| 1 | 0 | 5 |
| 5 | 0 | 5 |
| 8 | 0 | 5 |
| 9 | 0 | 5 |
| 10 | 0 | 5 |
| 3 | 1 | 6 |
| 0 | 2 | 11 |
| 2 | 2 | 11 |
| 4 | 2 | 11 |
| 6 | 2 | 11 |
| 7 | 2 | 11 |
In other words, idx should indicate how many rows have y less or equal than the y of row considered.
I would just use:
select cnt.*,
count(*) over (order by y)
from cnt;
Here is a db<>fiddle.
The issue with your code is probably that the CTE is re-evaluated each time it is called, so the values are not consistent -- a problem with volatile functions in CTEs.
Related
Good day. I have a permutated table with condition and I am running redshift DB. This is a table with events log and I splitted it into session start (bool = 1) and session continue (bool = 0) like this:
=======================
| ID | BOOL |
=======================
| 1 | 0 |
| 2 | 1 |
| 3 | 0 |
| 4 | 0 |
| 5 | 0 |
| 6 | 0 |
| 7 | 0 |
| 8 | 0 |
| 9 | 0 |
| 10 | 0 |
| 11 | 1 |
| 12 | 0 |
| 13 | 0 |
| 14 | 1 |
| 15 | 0 |
| 16 | 0 |
=======================
I need to create sesssion_id column with something like dense_rank:
================================
| ID | BOOL | D_RANK |
================================
| 1 | 0 | 1 |
| 2 | 1 | 2 |
| 3 | 0 | 2 |
| 4 | 0 | 2 |
| 5 | 0 | 2 |
| 6 | 0 | 2 |
| 7 | 0 | 2 |
| 8 | 0 | 2 |
| 9 | 0 | 2 |
| 10 | 0 | 2 |
| 11 | 1 | 3 |
| 12 | 0 | 3 |
| 13 | 0 | 3 |
| 14 | 1 | 4 |
| 15 | 0 | 4 |
| 16 | 0 | 4 |
================================
Is there any option to do this? Would appreciate any help.
Use a cumulative sum. Assuming that bool is the start of a new session:
select t.*,
sum(bool) over (order by id) as session_id
from t;
Note: This will start at 0. You can add 1 if you need.
I need to increase the value of the proceeding row number by 1. When the row encounters another condition I then need to reset the counter. This is probably easiest explained with an example:
+---------+------------+------------+-----------+----------------+
| Acct_ID | Ins_Date | Acct_RowID | indicator | Desired_Output |
+---------+------------+------------+-----------+----------------+
| 5841 | 07/11/2019 | 1 | 1 | 1 |
| 5841 | 08/11/2019 | 2 | 0 | 2 |
| 5841 | 09/11/2019 | 3 | 0 | 3 |
| 5841 | 10/11/2019 | 4 | 0 | 4 |
| 5841 | 11/11/2019 | 5 | 1 | 1 |
| 5841 | 12/11/2019 | 6 | 0 | 2 |
| 5841 | 13/11/2019 | 7 | 1 | 1 |
| 5841 | 14/11/2019 | 8 | 0 | 2 |
| 5841 | 15/11/2019 | 9 | 0 | 3 |
| 5841 | 16/11/2019 | 10 | 0 | 4 |
| 5841 | 17/11/2019 | 11 | 0 | 5 |
| 5841 | 18/11/2019 | 12 | 0 | 6 |
| 5132 | 11/03/2019 | 1 | 1 | 1 |
| 5132 | 12/03/2019 | 2 | 0 | 2 |
| 5132 | 13/03/2019 | 3 | 0 | 3 |
| 5132 | 14/03/2019 | 4 | 1 | 1 |
| 5132 | 15/03/2019 | 5 | 0 | 2 |
| 5132 | 16/03/2019 | 6 | 0 | 3 |
| 5132 | 17/03/2019 | 7 | 0 | 4 |
| 5132 | 18/03/2019 | 8 | 0 | 5 |
| 5132 | 19/03/2019 | 9 | 1 | 1 |
| 5132 | 20/03/2019 | 10 | 0 | 2 |
+---------+------------+------------+-----------+----------------+
The column I want to create is 'Desired_Output'. It can be seen from this table that I need to use the column 'indicator'. I want the following row to be n+1; unless the next row is 1. The counter needs to reset when the value 1 is encountered again.
I have tried to use a loop method of some sort but this did not produce the desired results.
Is this possible in some way?
The trick is to identify the group of consecutive rows starts from indicator 1 to the next 1. This is achieve by using the cross apply finding the Acct_RowID with indicator = 1 and use that as a Grp_RowID to use as partition by in the row_number() window function
select *,
Desired_Output = row_number() over (partition by t.Acct_ID, Grp_RowID
order by Acct_RowID)
from your_table t
cross apply
(
select Grp_RowID = max(Acct_RowID)
from your_table x
where x.Acct_ID = t.Acct_ID
and x.Acct_RowID <= t.Acct_RowID
and x.indicator = 1
) g
My table returns results as following (skips row if HourOfDay does not have data for particular ID)
ID HourOfDay Counts
--------------------------
1 5 5
1 13 10
1 23 3
..........................HourOfDay up till 23
2 9 1
and so on.
What I am trying to achieve is to force showing rows displaying 0 for HoursOfDay, which don't have data, like following:
ID HourOfDay Counts
--------------------------
1 0 0
1 1 0
1 2 0
1......................
1 5 5
1 6 0
1......................
1 23 3
2 0 0
2 1 0
etc.
I have researched around about it. It looks like I can achieve this result if I create an extra table and outer join it. So I have created table variable in SP (as a temp workaround)
DECLARE #Hours TABLE
(
[Hour] INT NULL
);
INSERT INTO #Hours VALUES (0),(1),(2),(3),(4),(5),(6),(7),(8),(9),(10),(11),(12)
,(13),(14),(15),(16),(17),(18),(19),(20),(21),(22),(23);
However, no matter how I join it, it does not achieve desired result.
How do I proceed? Do I add extra columns to join on? Completely different approach? Any hint in the right direction is appreciated!
Using a derived table for the distinct Ids cross joined to #Hours, left joined to your table:
select
i.Id
, h.Hour
, coalesce(t.Counts,0) as Counts
from (select distinct Id from t) as i
cross join #Hours as h
left join t
on i.Id = t.Id
and h.Hour = t.HourOfDay
rextester demo: http://rextester.com/XFZYX88502
returns:
+----+------+--------+
| Id | Hour | Counts |
+----+------+--------+
| 1 | 0 | 0 |
| 1 | 1 | 0 |
| 1 | 2 | 0 |
| 1 | 3 | 0 |
| 1 | 4 | 0 |
| 1 | 5 | 5 |
| 1 | 6 | 0 |
| 1 | 7 | 0 |
| 1 | 8 | 0 |
| 1 | 9 | 0 |
| 1 | 10 | 0 |
| 1 | 11 | 0 |
| 1 | 12 | 0 |
| 1 | 13 | 10 |
| 1 | 14 | 0 |
| 1 | 15 | 0 |
| 1 | 16 | 0 |
| 1 | 17 | 0 |
| 1 | 18 | 0 |
| 1 | 19 | 0 |
| 1 | 20 | 0 |
| 1 | 21 | 0 |
| 1 | 22 | 0 |
| 1 | 23 | 3 |
| 2 | 0 | 0 |
| 2 | 1 | 0 |
| 2 | 2 | 0 |
| 2 | 3 | 0 |
| 2 | 4 | 0 |
| 2 | 5 | 0 |
| 2 | 6 | 0 |
| 2 | 7 | 0 |
| 2 | 8 | 0 |
| 2 | 9 | 1 |
| 2 | 10 | 0 |
| 2 | 11 | 0 |
| 2 | 12 | 0 |
| 2 | 13 | 0 |
| 2 | 14 | 0 |
| 2 | 15 | 0 |
| 2 | 16 | 0 |
| 2 | 17 | 0 |
| 2 | 18 | 0 |
| 2 | 19 | 0 |
| 2 | 20 | 0 |
| 2 | 21 | 0 |
| 2 | 22 | 0 |
| 2 | 23 | 0 |
+----+------+--------+
I have this table
+----+--------+------------+-----------+
| Id | day_id | subject_id | period_Id |
+----+--------+------------+-----------+
| 1 | 1 | 1 | 1 |
| 2 | 1 | 2 | 2 |
| 8 | 2 | 6 | 1 |
| 9 | 2 | 7 | 2 |
| 15 | 3 | 3 | 1 |
| 16 | 3 | 4 | 2 |
| 22 | 4 | 5 | 1 |
| 23 | 4 | 5 | 2 |
| 24 | 4 | 6 | 3 |
| 29 | 5 | 8 | 1 |
| 30 | 5 | 1 | 2 |
to something like this
| Id | day_id | subject_id | period_Id |
| 1 | 1 | 1 | 1 |
| 8 | 2 | 6 | 1 |
| 15 | 3 | 3 | 1 |
| 22 | 4 | 5 | 1 |
| 29 | 5 | 8 | 1 |
| 2 | 1 | 2 | 2 |
| 2 | 1 | 2 | 2 |
| 16 | 3 | 4 | 2 |
| 23 | 4 | 5 | 2 |
| 30 | 5 | 1 | 2 |
+----+--------+------------+-----------+
SO, I want to choose one period with a different subject each day and doing this for number of weeks. so first subject dose not come until all subject have been chosen.
You can ORDER BY period_id first and then by day_id:
SELECT *
FROM your_table
ORDER BY period_Id, day_Id
LiveDemo
i have table like this:
| ID | id_number | a | b |
| 1 | 1 | 0 | 215 |
| 2 | 2 | 28 | 8952 |
| 3 | 3 | 10 | 2000 |
| 4 | 1 | 0 | 215 |
| 5 | 1 | 0 |10000 |
| 6 | 3 | 10 | 5000 |
| 7 | 2 | 3 |90933 |
I want to sum a*b where id_number is same, what the query to get all value for every id_number? for example the result is like this :
| ID | id_number | result |
| 1 | 1 | 0 |
| 2 | 2 | 523455 |
| 3 | 3 | 70000 |
This is a simple aggregation query:
select id_number, sum(a*b)
from t
group by id_number
I'm not sure what the first column is for.