Sorry for the vague title but I'm not sure how to phrase the question. What I want to do is sum a column in groups if every 4 records, but the groupings will overlap
Game Strikeouts
1. 25
2. 10
3. 10
4. 11
5. 16
Show the first group would be games 1-4 and sum would be 56, second group would be 2-5 and sun would 47, and so on all the way down to the last record.
Another option
Select Game
,Strikeouts = sum(Strikeouts) over (Order By Game ROWS BETWEEN CURRENT ROW AND 3 FOLLOWING )
From YourTable
Order By Game
Returns
Game Strikeouts
1 56
2 47
3 37
4 27
5 16
I simply added the values of the next 3 rows to the actual row:
CREATE TABLE #TEST (
Game int
,Strikeouts int
)
INSERT INTO #TEST VALUES
(1,25),(2,10),(3,10),(4,11),(5,16)
-- act. row + 3 following rows
SELECT Game, Strikeouts + LEAD(Strikeouts,1,0) OVER (ORDER BY Game) + LEAD(Strikeouts,2,0) OVER (ORDER BY Game) + LEAD(Strikeouts,3,0) OVER (ORDER BY Game) as Strikeouts
FROM #TEST
Output:
Game |Strikeouts
-----+-----------
1 | 56
2 | 47
3 | 37
4 | 27
5 | 16
Lag was introduced with SQL Server 2012
Related
I have this query that produced the table below.
select season,
guildname,
count(guildname) as mp_count,
(count(guildname)/600::float)*100 as grank
from mp_rankings
group by season, guildname
order by grank desc
season
guildname
mp_count
grank
10
LEGENDS
56
9.33333333333333
9
LEGENDS
54
9
10
EVERGLADE
50
8.33333333333333
9
Mystic
46
7.66666666666667
10
Mystic
42
7
9
EVERGLADE
39
6.5
10
100
36
6
9
PARABELLUM
33
5.5
10
PARABELLUM
29
4.83333333333333
9
100
29
4.83333333333333
I wanted to create a new column that calculates the percentage difference between the two seasons using identical guildnames. For example:
season
guildname
mp_count
grank
prev_season_percent_diff
10
LEGENDS
56
9.33333333333333
0.33%
10
EVERGLADE
50
8.33333333333333
1.83%
The resulting table will only show the current season (which is the highest season value, 10 in this case) and adds a new column prev_season_percent_diff, which is the current season's grank minus the previous season's grank.
How can I achieve this?
Use a Common Table Expression ("CTE") for the grouped result and join it to itself to calculate the difference to the previous season:
with summary as (
select
season,
guildname,
count(*) as mp_count, -- simplified equivalent expression
count(*)/6 as grank -- simplified equivalent expression
from mp_rankings
group by season, guildname
)
select
a.season,
a.guildname,
a.mp_count,
a.grank,
a.mp_count - b.mp_count as prev_season_percent_diff
from summary a
left join summary b on b.guildname = a.guildname
and b.season = a.season - 1
where a.season = (select max(season) from summary)
order by a.grank desc
If you actually want a % in the result, concatenate a % to the difference calculation.
Consider the code below:
q)tab:flip `items`sales`prices!(`nut`bolt`cam`cog;6 8 0 3;10 20 15 20)
q)tab
items sales prices
------------------
nut 6 10
bolt 8 20
cam 0 15
cog 3 20
I would like to duplicate the prices column. I can write a query like this:
q)update prices_copy: prices from tab
I also can write a query like this:
q)select items, sales, prices, prices_copy: first prices by items from tab
Both would work. I would like to know how the "by" version would work and the motivation for writing each version. I cannot help but think the "by" version is more thinking in rows.
Your initial query would be ideally what you want for your duplicate column requirement.
The by creates groups of the column items in your example and collapses every other column in the select query according to the indices calculated from grouping items. More info on by here - http://code.kx.com/wiki/Reference/select and http://code.kx.com/wiki/JB:QforMortals2/queries_q_sql#The_by_Phrase
In your example, the column items is already unique and so no collapsing into groups is actually performed, however, the by will create nested lists from the other columns (i.e. lists of lists). The use of first will just un-nest the items column, thus collapsing it to a normal (long-typed) vector.
When the grouping is finished the by columns are used as the key column[s] of the result and you will see this by the use of a vertical line to the right hand side of the key column[s]. All other columns within the select query are placed to the right hand side of the key.
The logic of the by version coincidentally creates a copy of prices. But by changes the order:
q)ungroup select sales, prices by items from tab
items sales prices
------------------
bolt 8 20
cam 0 15
cog 3 20
nut 6 10
q)tab
items sales prices
------------------
nut 6 10
bolt 8 20
cam 0 15
cog 3 20
The by version works only because items is unique. For a tab with multiple values for item eg. 8#tab, the query only produces 4 values for prices_copy.
q)select items, sales, prices, prices_copy: first prices by items from 8#tab
items| items sales prices prices_copy
-----| ----------------------------------
bolt | bolt bolt 8 8 20 20 20
cam | cam cam 0 0 15 15 15
cog | cog cog 3 3 20 20 20
nut | nut nut 6 6 10 10 10
There is a fundamental difference between a simple update and update by queries.
Let's explore it by adding an extra column brand to the table
tab2:flip `items`sales`prices`brand!(`nut`bolt`cam`cog`nut`bolt`cam`cog;6 8 0 3 1 2 3 4;10 20 15 20 30 40 50 60;`b1`b1`b1`b1`b2`b2`b2`b2)
The following will now simply copy the column :
asc update prices_copy: prices from tab2
However, the following query is copying the first item price regardless of the brand and updating it for all other brands of same item.
asc ungroup select sales, prices,brand, prices_copy: first prices by items from tab2
items sales prices brand prices_copy
------------------------------------
bolt 2 40 b2 20
bolt 8 20 b1 20 //b2 price
cam 0 15 b1 15 //b2 price
cam 3 50 b2 15
cog 3 20 b1 20
cog 4 60 b2 20 //b2 price
nut 1 30 b2 10 //b2 price
nut 6 10 b1 10
update by might be useful in the case where you want to copy the max price of the items regardless of the brand or some other aggregation query.
asc ungroup select sales, prices,brand, prices_copy: max prices by items from tab2
items sales prices brand prices_copy
------------------------------------
bolt 2 40 b2 40
bolt 8 20 b1 40 //max price in bolts regardless of the brand
cam 0 15 b1 50
cam 3 50 b2 50
cog 3 20 b1 60
cog 4 60 b2 60
nut 1 30 b2 30
nut 6 10 b1 30
Currently i have a requirement which needs a table to look like this:
Instrument Long Short 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 ....
Fixed 41 41 35 35 35 35 35 35 35 53 25 25
Index 16 16 22 22 22 32 12 12 12 12 12 12
Credits 29 29 41 16 16 16 16 16 16 16 16 16
Short term 12 12 5 5 5 5 5 5 5 5 5 17
My worktable looks like the following:
Instrument Long Short Annual Coupon Maturity Date Instrument ID
Fixed 10 10 10 01/01/2025 1
Index 5 5 10 10/05/2016 2
Credits 15 15 16 25/06/2020 3
Short term 12 12 5 31/10/2022 4
Fixed 13 13 15 31/03/2030 5
Fixed 18 18 10 31/01/2019 6
Credits 14 14 11 31/12/2013 7
Index 11 11 12 31/10/2040 8
..... etc
So basically the long and the short in the pivot should be the sum of each distinct instrument ID. And then for each year i need to take the sum of each Annual Coupon until the maturity date year where the long and the coupon rate are added together.
My thinking was that i had to create a while loop which would populate a table with a record for each year for each instrument until the maturity date, so that i could then pivot using an sql pivot some how. Does this seem feasible? Any other ideas on the best way of doing this, particularly i might need help on the while loop?
The following solution uses a numbers table to unfold ranges in your table, performs some special processing on some of the data columns in the unfolded set, and finally pivots the results:
WITH unfolded AS (
SELECT
t.Instrument,
Long = SUM(z.Long ) OVER (PARTITION BY Instrument),
Short = SUM(z.Short) OVER (PARTITION BY Instrument),
Year = y.Number,
YearValue = t.AnnualCoupon + z.Long + z.Short
FROM YourTable t
CROSS APPLY (SELECT YEAR(t.MaturityDate)) x (Year)
INNER JOIN numbers y ON y.Number BETWEEN YEAR(GETDATE()) AND x.Year
CROSS APPLY (
SELECT
Long = CASE y.Number WHEN x.Year THEN t.Long ELSE 0 END,
Short = CASE y.Number WHEN x.Year THEN t.Short ELSE 0 END
) z (Long, Short)
),
pivoted AS (
SELECT *
FROM unfolded
PIVOT (
SUM(YearValue) FOR Year IN ([2013], [2014], [2015], [2016], [2017], [2018], [2019], [2020],
[2021], [2022], [2023], [2024], [2025], [2026], [2027], [2028], [2029], [2030],
[2031], [2032], [2033], [2034], [2035], [2036], [2037], [2038], [2039], [2040])
) p
)
SELECT *
FROM pivoted
;
It returns results for a static range years. To use it for a dynamically calculated year range, you'll first need to prepare the list of years as a CSV string, something like this:
SET #columnlist = STUFF(
(
SELECT ', [' + CAST(Number) + ']'
FROM numbers
WHERE Number BETWEEN YEAR(GETDATE())
AND (SELECT YEAR(MAX(MaturityDate)) FROM YourTable)
ORDER BY Number
FOR XML PATH ('')
),
1, 2, ''
);
then put it into the dynamic SQL version of the query:
SET #sql = N'
WITH unfolded AS (
...
PIVOT (
SUM(YearValue) FOR Year IN (' + #columnlist + ')
) p
)
SELECT *
FROM pivoted;
';
and execute the result:
EXECUTE(#sql);
You can try this solution at SQL Fiddle.
I want to insert a row number in a records like counting rows in a specific number of range. example output:
RowNumber ID Name
1 20 a
2 21 b
3 22 c
1 23 d
2 24 e
3 25 f
1 26 g
2 27 h
3 28 i
1 29 j
2 30 k
I rather to try using the rownumber() over (partition by order by column name) but my real records are not containing columns that will count into 1-3 rownumber.
I already try to loop each of record to insert a row count 1-3 but this loop affects the performance of the query. The query will use for the RDL report, that is why as much as possible the performance of the query must be good.
any suggestions are welcome. Thanks
have you tried modulo-ing rownumber()?
SELECT
((row_number() over (order by ID)-1) % 3) +1 as RowNumber
FROM table
I use Oracle 10g and I have a table that stores a snapshot of data on a person for a given day. Every night an outside process adds new rows to the table for any person whose had any changes to their core data (stored elsewhere). This allows a query to be written using a date to find out what a person 'looked' like on some past day. A new row is added to the table even if only a single aspect of the person has changed--the implication being that many columns have duplicate values from slice to slice since not every detail changed in each snapshot.
Below is a data sample:
SliceID PersonID StartDt Detail1 Detail2 Detail3 Detail4 ...
1 101 08/20/09 Red Vanilla N 23
2 101 08/31/09 Orange Chocolate N 23
3 101 09/15/09 Yellow Chocolate Y 24
4 101 09/16/09 Green Chocolate N 24
5 102 01/10/09 Blue Lemon N 36
6 102 01/11/09 Indigo Lemon N 36
7 102 02/02/09 Violet Lemon Y 36
8 103 07/07/09 Red Orange N 12
9 104 01/31/09 Orange Orange N 12
10 104 10/20/09 Yellow Orange N 13
I need to write a query that pulls out time slices records where some pertinent bits, not the whole record, have changed. So, referring to the above, if I only want to know the slices in which Detail3 has changed from its previous value, then I would expect to only get rows having SliceID 1, 3 and 4 for PersonID 101 and SliceID 5 and 7 for PersonID 102 and SliceID 8 for PersonID 103 and SliceID 9 for PersonID 104.
I'm thinking I should be able to use some sort of Oracle Hierarchical Query (using CONNECT BY [PRIOR]) to get what I want, but I have not figured out how to write it yet. Perhaps YOU can help.
Thanks you for your time and consideration.
Here is my take on the LAG() solution, which is basically the same as that of egorius, but I show my workings ;)
SQL> select * from
2 (
3 select sliceid
4 , personid
5 , startdt
6 , detail3 as new_detail3
7 , lag(detail3) over (partition by personid
8 order by startdt) prev_detail3
9 from some_table
10 )
11 where prev_detail3 is null
12 or ( prev_detail3 != new_detail3 )
13 /
SLICEID PERSONID STARTDT N P
---------- ---------- --------- - -
1 101 20-AUG-09 N
3 101 15-SEP-09 Y N
4 101 16-SEP-09 N Y
5 102 10-JAN-09 N
7 102 02-FEB-09 Y N
8 103 07-JUL-09 N
9 104 31-JAN-09 N
7 rows selected.
SQL>
The point about this solution is that it hauls in results for 103 and 104, who don't have slice records where detail3 has changed. If that is a problem we can apply an additional filtration, to return only rows with changes:
SQL> with subq as (
2 select t.*
3 , row_number () over (partition by personid
4 order by sliceid ) rn
5 from
6 (
7 select sliceid
8 , personid
9 , startdt
10 , detail3 as new_detail3
11 , lag(detail3) over (partition by personid
12 order by startdt) prev_detail3
13 from some_table
14 ) t
15 where t.prev_detail3 is null
16 or ( t.prev_detail3 != t.new_detail3 )
17 )
18 select sliceid
19 , personid
20 , startdt
21 , new_detail3
22 , prev_detail3
23 from subq sq
24 where exists ( select null from subq x
25 where x.personid = sq.personid
26 and x.rn > 1 )
27 order by sliceid
28 /
SLICEID PERSONID STARTDT N P
---------- ---------- --------- - -
1 101 20-AUG-09 N
3 101 15-SEP-09 Y N
4 101 16-SEP-09 N Y
5 102 10-JAN-09 N
7 102 02-FEB-09 Y N
SQL>
edit
As egorius points out in the comments, the OP does want hits for all users, even if they haven't changed, so the first version of the query is the correct solution.
In addition to OMG Ponies' answer: if you need to query slices for all persons, you'll need partition by:
SELECT s.sliceid
, s.personid
FROM (SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (
PARTITION BY t.personid ORDER BY t.startdt
) prev_val
FROM t) s
WHERE (s.prev_val IS NULL OR s.prev_val != s.detail3)
I think you'll have better luck with the LAG function:
SELECT s.sliceid
FROM (SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (PARTITION BY t.personid ORDER BY t.startdt) 'prev_val'
FROM TABLE t) s
WHERE s.personid = 101
AND (s.prev_val IS NULL OR s.prev_val != s.detail3)
Subquery Factoring alternative:
WITH slices AS (
SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (PARTITION BY t.personid ORDER BY t.startdt) 'prev_val'
FROM TABLE t)
SELECT s.sliceid
FROM slices s
WHERE s.personid = 101
AND (s.prev_val IS NULL OR s.prev_val != s.detail3)