I have
update NewLeaderBoards set MonthlyRank=(Select RowNumber() (order by TotalPoints desc) from LeaderBoards)
I tried it this way -
(Select RowNumber() (order by TotalPoints desc) from LeaderBoards) as NewRanks
update NewLeaderBoards set MonthlyRank = NewRanks
But it doesnt work for me..Can anyone suggest me how can i perform an update in such a way..
You need to use the WITH statement and a full CTE:
;With Ranks As
(
Select PrimaryKeyColumn, Row_Number() Over( Order By TotalPoints Desc ) As Num
From LeaderBoards
)
Update NewLeaderBoards
Set MonthlyRank = T2.Num
From NewLeaderBoards As T1
Join Ranks As T2
On T2.PrimaryKeyColumn = T1.PrimaryKeyColumn
Related
Quick question, I'm trying to update a column only when there are duplicates(partition column > 1) in the table and have selected it based on partition concept, But the current query updates the whole table! please check the query below, Any leads would be greatly appreciated :)
UPDATE public.database_tag
SET deleted_at= '2022-04-25 19:33:29.087133+00'
FROM (
SELECT *,
row_number() over (partition by title order by created_at) as RN
FROM public.database_tag
ORDER BY RN DESC) X
WHERE X.RN > 1
Thanks very much!
Assuming that every row have unique ID it can be done like below.
UPDATE database_tag
SET deleted_at= '2022-04-25 19:33:29.087133+00'
WHERE <some_unique_id> in (
select <some_unique_id> from (
SELECT <some_unique_id>,
row_number() over (partition by title order by created_at) as RN
FROM public.database_tag
) X
WHERE X.RN > 1
)
Or we can reverse query to update all but set of ID's
UPDATE database_tag
SET deleted_at= '2022-04-25 19:33:29.087133+00'
WHERE <some_unique_id> not in (
select distinct on (title)
<some_unique_id> from database_tag
order by title, created_at
)
I am writing a query in Redshift to answer the question "Give the average lifetime spend of users who spent more on their first order than their second order." This is based off of an order_items table which has one row for every item ordered (so an order with 3 items would be represented in 3 rows). Here's a snapshot of the first 10 rows:
First 10 rows of order_items:
Here is my solution:
with
cte1_lifetime as (
select oi.user_id, sum(oi.sale_price) as lifetime_spend
from order_items as oi
group by oi.user_id
),
cte2_order as (
select oi.user_id, oi.order_id, sum(oi.sale_price) as order_total, rank() over(partition by oi.user_id order by oi.created_at) as order_rank
from order_items as oi
group by oi.user_id, oi.order_id, oi.created_at
order by oi.user_id, oi.order_id
),
cte3_first_order as (
select user_id, order_id, order_total
from cte2_order
where order_rank=1
order by user_id, order_id
),
cte4_second_order as (
select user_id, order_id, order_total
from cte2_order
where order_rank=2
order by user_id, order_id
)
select avg(cte1.lifetime_spend) as average_lifetime_spend
from cte1_lifetime as cte1
where exists (
select *
from cte3_first_order as cte3, cte4_second_order as cte4
where cte3.user_id=cte4.user_id
and cte1.user_id=cte3.user_id
and cte3.order_total > cte4.order_total)
And here is the answer key:
WITH
table1 AS
(SELECT user_id, order_id,
SUM(sale_price) OVER (PARTITION BY order_id ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) as order_total,
RANK() OVER (PARTITION BY user_id ORDER BY created_at) AS "sequence"
FROM order_items)
,
table2 AS
(SELECT user_id, SUM(sale_price) AS lifetime_spend
FROM order_items
WHERE EXISTS
(SELECT t1.user_id
FROM table1 t1, table1 t2
WHERE t1.user_id = t2.user_id AND t1.sequence = 1 AND t2.sequence = 2 AND t1.order_total>t2.order_total
AND t1.user_id = order_items.user_id)
GROUP BY 1
ORDER BY 1)
SELECT AVG(lifetime_spend)
FROM table2
These answers yield slightly different results on the same data- an average lifetime spend of $215 vs $220. I'd really like to understand why they are different but so far I can't figure it out. Any ideas?
Have a table with 3 columns: ID, Signature, and Datetime, and it's grouped by Signature Having Count(*) > 9.
select * from (
select s.Signature
from #Sigs s
group by s.Signature
having count(*) > 9
) b
join #Sigs o
on o.Signature = b.Signature
order by o.Signature desc, o.DateTime
I now want to select the 1st and 10th records only, per Signature. What determines rank is the Datetime descending. Thus, I would expect every Signature to have 2 rows.
Thanks,
I would go with a couple of common table expressions.
The first will select all records from the table as well as a count of records per signature, and the second one will select from the first where the record count > 9 and add row_number partitioned by signature - and then just select from that where the row_number is either 1 or 10:
With cte1 AS
(
SELECT ID, Signature, Datetime, COUNT(*) OVER(PARTITION BY Signature) As NumberOfRows
FROM #Sigs
), cte2 AS
(
SELECT ID, Signature, Datetime, ROW_NUMBER() OVER(PARTITION BY Signature ORDER BY DateTime DESC) As Rn
FROM cte1
WHERE NumberOfRows > 9
)
SELECT ID, Signature, Datetime
FROM cte2
WHERE Rn IN (1, 10)
ORDER BY Signature desc
Because I don't know what your data looks like, this might need some adjustment.
The simplest way here, since you already know your sort order (DateTime DESC) and partitioning (Signature), is probably to assign row numbers and then select the rows you want.
SELECT *
FROM
(
select o.Signature
,o.DateTime
,ROW_NUMBER() OVER (PARTITION BY o.Signature ORDER BY o.DateTime DESC) [Row]
from (
select s.Signature
from #Sigs s
group by s.Signature
having count(*) > 9
) b
join #Sigs o
on o.Signature = b.Signature
order by o.Signature desc, o.DateTime
)
WHERE [Row] IN (1,10)
I'm trying to update a column (pop_1_rank) in a postgresql table with the results from a rank() like so:
UPDATE database_final_form_merge
SET
pop_1_rank = r.rnk
FROM (
SELECT pop_1, RANK() OVER ( ORDER BY pop_1 DESC) FROM database_final_form_merge WHERE territory_name != 'north' AS rnk)r
The SELECT query by itself works fine, but I just can't get it to update correctly. What am I doing wrong here?
I rather use the CTE notation.
WITH cte as (
SELECT pop_1,
RANK() OVER ( ORDER BY pop_1 DESC) AS rnk
FROM database_final_form_merge
WHERE territory_name <> 'north'
)
UPDATE database_final_form_merge
SET pop_1_rank = cte.rnk
FROM cte
WHERE database_final_form_merge.pop_1 = cte.pop_1
As far as I know, Postgres updates tables not subqueries. So, you can join back to the table:
UPDATE database_final_form_merge
SET pop_1_rank = r.rnk
FROM (SELECT pop_1, RANK() OVER ( ORDER BY pop_1 DESC) as rnk
FROM database_final_form_merge
WHERE territory_name <> 'north'
) r
WHERE database_final_form_merge.pop_1 = r.pop_1;
In addition:
The column alias goes by the column name.
This assumes that pop_1 is the id connecting the two tables.
You're missing WHERE on UPDATE query, because when doing UPDATE ... FROM you're basically doing joins.
So you need to select primary key and then match on primary key to update just the columns are computing rank over.
Can you let me know how to select only two employees from every department? The table has deptname, ssn, name . I am doing a sampling and I need only two ssns for every department name. Can someone help?
You can accomplish this with an "OLAP expression" row_number()
with e as
( select deptname, ssn, empname,
row_number() over (partition by dptname order by empname) as pick
from employees
)
select deptname, ssn, empname
from e
where pick < 3
order by deptname, ssn
This example will give you the two employees with the lowest order names, because that is what is specified in the row_number() (order by) expression.
Try this:
select *
from t t1
where (
select count(*)
from t t2
where
t2.deptname = t1.deptname
and
t2.ssn <= t1.ssn) <= 2
order by deptname, ssn,name;
The above will give "smallest" two ssn.
If you want top 2, change to t2.ssn >= t1.ssn
sqlfiddle
The data:
The result from query:
select * from
( select rank() over (partition by dptname order by empname) as count , *
from employees
)
where count<=2
order by deptname, ssn,name;