+----+-------+
| id | value |
+----+-------+
| 1 | A |
| 2 | B |
| 3 | C |
| 4 | D |
| 5 | D |
| 6 | D |
| 7 | N |
| 8 | P |
| 9 | P |
+----+-------+
Desired output
+----+-------+---------------------+
| id | value | calc ↓ |
+----+-------+---------------------+
| 1 | A | 1 |
| 2 | B | 2 |
| 3 | C | 3 |
| 4 | D | 6 |
| 5 | D | 6 |
| 6 | D | 6 |
| 7 | N | 7 |
| 8 | P | 9 |
| 9 | P | 9 |
| 10 | D | 11 |
| 11 | D | 11 |
| 12 | Z | 12 |
+----+-------+---------------------+
Can you help me for a solution for this ? Id is identity, id must be present in output, must have the same 9 rows in output.
New note: I added rows 10,11,12. Notice that id 10 and 11 which has letter 'D' is in a different group from id 4,5,6
thanks
If the grouping also depends on the surrounding ids then this turns into something like the gaps and islands problem https://www.red-gate.com/simple-talk/sql/t-sql-programming/the-sql-of-gaps-and-islands-in-sequences/#:~:text=The%20SQL%20of%20Gaps%20and%20Islands%20in%20Sequences,...%204%20Performance%20Comparison%20of%20Gaps%20Solutions.%20
You could use the Tabibitosan method https://rwijk.blogspot.com/2014/01/tabibitosan.html
Here you also need to group by your value column but that doesn't complicate it too much:
select id, value, max(id) over (partition by value, island) calc
from (
select id, value, id - row_number() over(partition by value order by id) island
from my_table
) as sq
order by id;
The id - row_number() over(partition by value order by id) expression gives you a number which changes each time the ID value changes by more than 1 for each value of value. This gets included in the max(id) over (partition by value, island) expression. The island number is only valid for that particular value. In your case, both values N and D have a computed island number of 6 but they need to be considered differently.
Db-fiddle https://www.db-fiddle.com/f/jahP7T6xBt3cpbLRhZZdQG/1
For this sample date you need MAX() window function:
SELECT id, value,
MAX(id) OVER (PARTITION BY value) calc
FROM tablename
SELECT id, value, (SELECT max(id) FROM TABLE inner where inner.value = outer.value)
FROM table as outer
Related
Let's say I have the following table:
| sku | id | value | count |
|-----|----|-------|-------|
| A | 1 | 1 | 2 |
| A | 1 | 2 | 2 |
| A | 3 | 3 | 3 |
I want to select rows that don't have the same count for the same id. So my desired outcome is:
| sku | id | value | count |
|-----|----|-------|-------|
| A | 3 | 3 | 3 |
I need something that works with Postgres 10
A simple method is window functions:
select t.*
from (select t.*, count(*) over (partition by sku, id) as cnt
from t
) t
where cnt = 1;
This assumes you really mean the sku/id combination.
Suppose I have a table sorted by date as so:
+-------------+--------+
| DATE | VALUE |
+-------------+--------+
| 01-09-2020 | 5 |
| 01-15-2020 | 5 |
| 01-17-2020 | 5 |
| 02-03-2020 | 8 |
| 02-13-2020 | 8 |
| 02-20-2020 | 8 |
| 02-23-2020 | 5 |
| 02-25-2020 | 5 |
| 02-28-2020 | 3 |
| 03-13-2020 | 3 |
| 03-18-2020 | 3 |
+-------------+--------+
I want to group by changes in value within that given date range, and add a value that increments each time as an added column to denote that.
I have tried a number of different things, such as using the lag function:
SELECT value, value - lag(value) over (order by date) as count
GROUP BY value
In short, I want to take the table above and have it look like:
+-------------+--------+-------+
| DATE | VALUE | COUNT |
+-------------+--------+-------+
| 01-09-2020 | 5 | 1 |
| 01-15-2020 | 5 | 1 |
| 01-17-2020 | 5 | 1 |
| 02-03-2020 | 8 | 2 |
| 02-13-2020 | 8 | 2 |
| 02-20-2020 | 8 | 2 |
| 02-23-2020 | 5 | 3 |
| 02-25-2020 | 5 | 3 |
| 02-28-2020 | 3 | 4 |
| 03-13-2020 | 3 | 4 |
| 03-18-2020 | 3 | 4 |
+-------------+--------+-------+
I want to eventually have it all in one small table with the earliest date for each.
+-------------+--------+-------+
| DATE | VALUE | COUNT |
+-------------+--------+-------+
| 01-09-2020 | 5 | 1 |
| 02-03-2020 | 8 | 2 |
| 02-23-2020 | 5 | 3 |
| 02-28-2020 | 3 | 4 |
+-------------+--------+-------+
Any help would be very appreciated
you can use a combination of Row_number and Dense_rank functions to get the required results like below:
;with cte
as
(
select t.DATE,t.VALUE
,Dense_rank() over(partition by t.VALUE order by t.DATE) as d_rank
,Row_number() over(partition by t.VALUE order by t.DATE) as r_num
from table t
)
Select t.Date,t.Value,d_rank as count
from cte
where r_num = 1
You can use a lag and cumulative sum and a subquery:
SELECT value,
SUM(CASE WHEN prev_value = value THEN 0 ELSE 1 END) OVER (ORDER BY date)
FROM (SELECT t.*, LAG(value) OVER (ORDER BY date) as prev_value
FROM t
) t
Here is a db<>fiddle.
You can recursively use lag() and then row_number() analytic functions :
WITH t2 AS
(
SELECT LAG(value,1,value-1) OVER (ORDER BY date) as lg,
t.*
FROM t
)
SELECT t2.date,t2.value, ROW_NUMBER() OVER (ORDER BY t2.date) as count
FROM t2
WHERE value - lg != 0
Demo
and filter through inequalities among the returned values from those functions.
I have a table which has multiple records for the same id. Looks like this, and the rows are sorted by sequence number.
+----+--------+----------+----------+
| id | result | duration | sequence |
+----+--------+----------+----------+
| 1 | 12 | 7254 | 1 |
+----+--------+----------+----------+
| 1 | 12 | 2333 | 2 |
+----+--------+----------+----------+
| 1 | 11 | 1000 | 3 |
+----+--------+----------+----------+
| 1 | 6 | 5 | 4 |
+----+--------+----------+----------+
| 1 | 3 | 20 | 5 |
+----+--------+----------+----------+
| 2 | 1 | 230 | 1 |
+----+--------+----------+----------+
| 2 | 9 | 10 | 2 |
+----+--------+----------+----------+
| 2 | 6 | 0 | 3 |
+----+--------+----------+----------+
| 2 | 1 | 5 | 4 |
+----+--------+----------+----------+
| 2 | 12 | 3 | 5 |
+----+--------+----------+----------+
E.g. for id=1, i would like to sum the duration for all the rows before and include result=6, which is 7254+2333+1000+5. Same for id =2, it would be 230+10+0. Anything after the row where result=6 will be left out.
My expected output:
+----+----------+
| id | duration |
+----+----------+
| 1 | 10592 |
+----+----------+
| 2 | 240 |
+----+----------+
The sequence has to be in ascending order.
I'm not sure how I can do this in sql.
Thank you in advance!
I think you want:
select t2.id, sum(t2.duration)
from t
where t.sequence <= (select t2.sequence
from t t2
where t2.id = t.id and t2.result = 6
);
In PrestoDB, I would recommend window functions:
select id, sum(duration)
from (select t.*,
min(case when result = 6 then sequence end) over (partition by id) as sequence_6
from t
) t
where sequence <= sequence_6;
You can use a simple aggregate query with a condition that uses a subquery to recover the sequence corresponding to the record whose sequence is 6 :
SELECT t.id, SUM(t.duration) total_duration
FROM mytable t
WHERE t.sequence <= (
SELECT sequence
FROM mytable
WHERE id = t.id AND result = 6
)
GROUP BY t.id
This demo on DB Fiddle with your test data returns :
| id | total_duration |
| --- | -------------- |
| 1 | 10592 |
| 2 | 240 |
Basic group by query should solve your issue
select
id,
sum(duration) duration
from t
group by id
for the certain rows:
select
id,
sum(duration) duration
from t
where id = 1
group by id
if you want to include it in your result set
select id, duration, sequence from t
union all
select
id,
sum(duration) duration
null sequence
from t
group by id
I am trying to do a row calculation whereby the larger value will carry forward to the subsequent rows until a larger value is being compared. It is done by comparing the current value to the previous row using the lag() function.
Code
DECLARE #TAB TABLE (id varchar(1),d1 INT , d2 INT)
INSERT INTO #TAB (id,d1,d2)
VALUES ('A',0,5)
,('A',1,2)
,('A',2,4)
,('A',3,6)
,('B',0,4)
,('B',2,3)
,('B',3,2)
,('B',4,5)
SELECT id
,d1
,d2 = CASE WHEN id <> (LAG(id,1,0) OVER (ORDER BY id,d1)) THEN d2
WHEN d2 < (LAG(d2,1,0) OVER (ORDER BY id,d1)) THEN (LAG(d2,1,0) OVER (ORDER BY id,d1))
ELSE d2 END
Output (Added row od2 for clarity)
+----+----+----+ +----+
| id | d1 | d2 | | od2|
+----+----+----+ +----+
| A | 0 | 5 | | 5 |
| A | 1 | 5 | | 2 |
| A | 2 | 4 | | 4 |
| A | 3 | 6 | | 6 |
| B | 0 | 4 | | 4 |
| B | 2 | 4 | | 3 |
| B | 3 | 3 | | 2 |
| B | 4 | 5 | | 5 |
+----+----+----+ +----+
As you can see from the output it lag function is referencing the original value of the previous row rather than the new value. Is there anyway to achieve this?
Desired Output
+----+----+----+ +----+
| id | d1 | d2 | | od2|
+----+----+----+ +----+
| A | 0 | 5 | | 5 |
| A | 1 | 5 | | 2 |
| A | 2 | 5 | | 4 |
| A | 3 | 6 | | 6 |
| B | 0 | 4 | | 4 |
| B | 2 | 4 | | 3 |
| B | 3 | 4 | | 2 |
| B | 4 | 5 | | 5 |
+----+----+----+ +----+
Try this:
SELECT id
,d1
,d2
,MAX(d2) OVER (PARTITION BY ID ORDER BY d1)
FROM #TAB
The idea is to use the MAX to get the max value from the beginning to the current row for each partition.
Thanks for providing the DDL scripts and the DML.
One way of doing it would be using recursive cte as follows.
1. First rank all the records according to id, d1 and d2. -> cte block
2. Use recursive cte and get the first elements using rnk=1
3. the field "compared_val" will check against the values from the previous rnk to see if the value is > than the existing and if so it would swap
DECLARE #TAB TABLE (id varchar(1),d1 INT , d2 INT)
INSERT INTO #TAB (id,d1,d2)
VALUES ('A',0,5)
,('A',1,2)
,('A',2,4)
,('A',3,6)
,('B',0,4)
,('B',2,3)
,('B',3,2)
,('B',4,5)
;with cte
as (select row_number() over(partition by id order by d1,d2) as rnk
,id,d1,d2
from #TAB
)
,data(rnk,id,d1,d2,compared_val)
as (select rnk,id,d1,d2,d2 as compared_val
from cte
where rnk=1
union all
select a.rnk,a.id,a.d1,a.d2,case when b.compared_val > a.d2 then
b.compared_val
else a.d2
end
from cte a
join data b
on a.id=b.id
and a.rnk=b.rnk+1
)
select * from data order by id,d1,d2
I have been trying to get this to work with some row_number, group by, top, sort of things, but I am missing some fundamental concept. I have a table like so:
+-------+-------+-------+
| name | ord | f_id |
+-------+-------+-------+
| a | 1 | 2 |
| b | 5 | 2 |
| c | 6 | 2 |
| d | 2 | 1 |
| e | 4 | 1 |
| a | 2 | 3 |
| c | 50 | 4 |
+-------+-------+-------+
And my desired output would be:
+-------+---------+--------+-------+
| f_id | ord_n | ord | name |
+-------+---------+--------+-------+
| 2 | 1 | 1 | a |
| 2 | 2 | 5 | b |
| 1 | 1 | 2 | d |
| 1 | 2 | 4 | e |
| 3 | 1 | 2 | a |
| 4 | 1 | 50 | c |
+-------+---------+--------+-------+
Where data is ordered by the ord value, and only up to two results per f_id. Should I be working on a Stored Procedure for this or can I just do it with SQL? I have experimented with some select TOP subqueries, but nothing has even come close..
Here are some statements to create the test table:
create table help(name varchar(255),ord tinyint,f_id tinyint);
insert into help values
('a',1,2),
('b',5,2),
('c',6,2),
('d',2,1),
('e',4,1),
('a',2,3),
('c',50,4);
You may use Rank or DENSE_RANK functions.
select A.name, A.ord_n, A.ord , A.f_id from
(
select
RANK() OVER (partition by f_id ORDER BY ord asc) AS "Rank",
ROW_NUMBER() OVER (partition by f_id ORDER BY ord asc) AS "ord_n",
help.*
from help
) A where A.rank <= 2
Sqlfiddle demo