Recently i needed to implement a way to allow for Table Records to be Ranked.
Initially i deployed an Update statement to seed the ranks:
;with cte as (
select
t.id,
Rank() Over (
Partition by t.field2
Order by t.id
) as [Rank],
t.index,
t.field2,
t.field3 ,
t.field4
from dbo.Table t
where t.field2 = #fldValue
) Update cte
set index = [Rank]
But now i need to be able to have the end-user re-order the ranks. Any suggestions on how to allow an end-user to take Rank value 92 to Rank value 15 and have everything be re-ranked appropriately.
I had thought about doing this via cursor but am trying to do this via Set based operation.
My first goto was to do a Procedural based operation but need to get more inline with Set based operation.
Table Schema
Table:
id bigint
field2 int
field3 int ---> This field will be the key pivoting column for ranking
field4 int
Data:
id field2 field3 field4
1 0 1 1
2 0 1 1
3 0 1 1
4 0 1 2
5 0 1 2
6 0 1 1
7 0 1 1
8 0 1 1
9 0 1 1
10 0 1 2
11 0 1 2
12 0 1 1
13 0 1 1
14 0 1 1
15 0 1 2
16 0 1 1
17 0 1 2
18 0 1 2
19 0 1 1
Related
I am trying to find the best way to accomplish the following.
Get the beginning customer count, which carries from the previous day
Get New Customer count
Get the number of Customers who have not come in since the prior month
Get the number of Customers who have come back after lapsing
Get the number of total customers
The following example
Customer ID
Store ID
Date
Amount
1
1
1/2/22
1.00
2
2
1/2/22
2.00
1
1
2/2/22
1.00
3
2
3/2/22
1.00
2
2
3/2/22
1.00
1
1
3/2/22
1.00
1
1
4/2/22
1.00
4
1
4/2/22
1.00
2
2
4/2/22
1.00
The result would be
Date
Store
Beginning
New
Dropped
Returned
Total
1/2/22
1
0
1
0
0
1
1/2/22
2
0
1
0
0
1
2/2/22
1
1
0
0
0
1
2/2/22
2
1
0
1
0
0
3/2/22
1
1
0
0
0
1
3/2/22
2
0
1
0
1
2
4/2/22
1
1
1
0
0
2
4/2/22
2
2
0
1
0
1
I kind of have a query, but it's not getting the right results
WITH customerset AS (
SELECT
location_id,
date,
array_agg(DISTINCT customer_id ORDER BY customer_id ASC) AS customer_ids
FROM customer_orders
GROUP BY
location_id,
date
)
SELECT
cset.location_id,
cset.date,
array_length(cset2.customer_ids, 1) AS beginning,
array_length((past2.customer_ids - cset.customer_ids), 1) AS dropped,
array_length((cset.customer_ids - past2.customer_ids), 1) AS returned
FROM
(
SELECT
ords.location_id,
ords.date,
array_agg(DISTINCT ords.customer_id ORDER BY ords.customer_id ASC) AS customers_id
FROM customer_orders ords
GROUP BY
ords.location_id,
ords.date
) cset
JOIN
customerset cset2 ON cset.date - '1 month'::interval = cset2.date
AND cset2.location_id = cset.location_id
GROUP BY
cset.location_id,
cset.date,
cset2.customer_ids,
cset.customer_ids
ORDER BY
cset.date ASC
I need to expand the indicator (currently on daily basis) to a larger group (groups multiple consecutive days into one grp). I have following type of data:
id date grp new_ind traditional_ind
--------------------------------------------------
1 02-01-2021 1 1 0
1 02-02-2021 1 0 1
1 02-03-2021 1 0 0
1 02-04-2021 1 null null
1 02-06-2021 2 0 1
1 02-07-2021 2 0 0
2 02-01-2021 1 null null
where new_ind and traditional_ind are mutually exclusive. With this, I am trying to create new indicator that expands the indicators that are currently on daily level to grp level, that will look like:
id date grp new_ind traditional_ind final_type
----------------------------------------------------------------
1 02-01-2021 1 1 0 new
1 02-02-2021 1 0 1 new
1 02-03-2021 1 0 0 new
1 02-04-2021 1 null null new
1 02-06-2021 2 0 1 traditional
1 02-07-2021 2 0 0 traditional
2 02-01-2021 1 null null none
basically,
if new_ind was ever 1, I want to flag entire grp as 'new'
if new_ind=0 and if traditional_ind is ever 1, flag entire grp as 'traditional'
if both indicators were null, then flag entire grp as 'none'
so that each id and grp can have single value of final_type.
I've tried:
max(case when new_ind = 1 then 'New'
when traditional_ind = 1 then 'Traditional'
else 'None' end) over (partition by id, grp) as final_type
but this wouldn't recognize when new_ind=1 then 'New' and flag all of new_ind = 1 as 'None' (but show traditional correctly):
id date grp new_ind traditional_ind final_type
----------------------------------------------------------------
1 02-01-2021 1 1 0 none
1 02-02-2021 1 0 1 none
1 02-03-2021 1 0 0 none
1 02-04-2021 1 null null none
1 02-06-2021 2 0 1 traditional
1 02-07-2021 2 0 0 traditional
2 02-01-2021 1 null null none
But if I remove else statement and only run:
max(case when new_ind = 1 then 'New'
when traditional_ind = 1 then 'Traditional'
end) over (partition by id, grp) as final_type
then this does accurately expand indicator as I hope, just returns null values (which I need to show as 'None' instead of nulls):
id date grp new_ind traditional_ind final_type
----------------------------------------------------------------
1 02-01-2021 1 1 0 new
1 02-02-2021 1 0 1 new
1 02-03-2021 1 0 0 new
1 02-04-2021 1 null null new
1 02-06-2021 2 0 1 traditional
1 02-07-2021 2 0 0 traditional
2 02-01-2021 1 null null null
Can anyone help identify issue with my max case when statement?
I think something like this should work:
WITH final_types AS (
SELECT
id,
grp,
( case
when bool_or(new_ind = 1) then 'New'
when bool_or(traditional_ind = 1) then 'Traditional'
else 'None'
end
) AS final_type
FROM your_table
GROUP BY id, grp
)
SELECT
t1.*,
t2.final_type
FROM your_table t1
JOIN final_types t2 ON t1.id = t2.id AND t1.grp = t2.grp
I have my data that looks like this:
user_id touchpoint_number days_difference
1 1 5
1 2 20
1 3 25
1 4 10
2 1 2
2 2 30
2 3 4
I would like to create one more column that would create a cumulative sum of the days_difference, partitioned by user_id, but would reset whenever the value reaches 30 and starts counting from 0. I have been trying to do it, but I couldn't figure it out how to do it in PostgreSQL, because it has to be recursive.
The outcome I would like to have would be something like:
user_id touchpoint_number days_difference cum_sum_upto30
1 1 5 5
1 2 20 25
1 3 25 0 --- new count all over again
1 4 10 10
2 1 2 2
2 2 30 0 --- new count all over again
2 3 4 4
Do you have any cool ideas how this could be done?
This should do what you want:
with cte as (
select t.a, t.b, t.c, t.c as sumc
from t
where b = 1
union all
select t.a, t.b, t.c,
(case when t.c + cte.sumc > 30 then 0 else t.c + cte.sumc end)
from t join
cte
on t.b = cte.b + 1 and t.a = cte.a
)
select *
from cte
order by a, b;
Here is a rextester.
I am trying to get the top n users by post using hive. The table looks like this.
Score User
10 1
20 2
50 1
20 2
0 3
3 1
40 2
...
I want to generate output which shows like
Rows Users
3 1
3 2
1 3
here is my query
SELECT * FROM (SELECT COUNT(score) as Score, UserID AS COUNT FROM A WHERE UserID IS NOT NULL GROUP BY UserID,score LIMIT 10) A;
The output I get is something like this
0 0
0 1
0 2
0 3
0 4
0 5
0 6
0 7
0 8
0 9
Can someone guide me where I am going wrong.
SELECT COUNT(score) as Score, UserID FROM A WHERE UserID IS NOT NULL GROUP BY UserID LIMIT 10
Suppose I have data in table like:
id level flag
1 1 0
1 2 0
1 3 1
1 4 0
1 5 1
1 6 0
1 7 0
1 8 1
1 9 1
1 10 0
2 1 0
2 2 0
2 3 0
2 4 0
2 5 1
2 6 1
2 7 1
......
I want to update flag to 0 after first 1 value for flag. For example, with above sample data,
for id = 1, the first flag value =1 is level=3, then all flag values for level>3 should be updated to 0.
For id = 2, should update flag = 0 for all level>5
How to implement it with sql even one sql statement?
You should be able to do this with a WHERE EXISTS on the same table:
UPDATE t1
SET flag = 0
FROM TheTable t1
WHERE EXISTS (
SELECT 1
FROM TheTable t2
WHERE t2.id = t1.id
AND t2.level < t1.level
AND t2.flag = 1
)
SQL Fiddle demo
You can do this with an exists statement:
update table t
set flag = 0
where exists (select 1
from table t2
where t2.id = t.id and
t2.level < t.level and
t2.flag = 1
);