I need to UPDATE all new inserted values of 0 with the highest value from the same column + 1. Any value with zero should be updated by the highest value +1. If the highest value is 30 below in the "Preference" column, then the next value should be 31 for Id 11 and 32 for Id 12. New values are inserted every 30 seconds, could be multiple, from the source table that I have no access to into the table below (table 1).
The UPDATE statement is executed when a user drags and drops a row in the web app.
UPDATE [DB].[dbo].[tbl1] SET
Preference = #Preference
WHERE Id = Id
I need to somehow add that logic to this statement described above. This is where I am lost.
Any ideas? Thank you for the help!!
For example:
ID
Preference
Account
3
7
22
6
8
33
7
9
44
9
0
55
11
0
66
Required results:
ID
Preference
Account
3
7
22
6
8
33
7
9
44
9
10
55
11
11
66
Gather the current maximum preference using a cross apply (or you could use a cross join) and together with row_number() ordered by ID you will increment preference as described:
with CTE as (
select id, preference, cp.maxpref, row_number() over(order by id) rn
from mytable
cross apply (select max(preference) maxpref
from mytable p
) cp
where preference = 0
)
update cte
set preference = maxpref + rn
where preference = 0
see db<>fiddle here
select *
from mytable
order by id
ID
Preference
Account
3
7
22
6
8
33
7
9
44
9
10
55
11
11
66
It's hard to formulate, so i'll just show an example and you are welcome to edit my question and title.
Suppose, i have a table
flag id value datetime
0 b 1 343 13
1 a 1 23 12
2 b 1 21 11
3 b 1 32 10
4 c 2 43 11
5 d 2 43 10
6 d 2 32 9
7 c 2 1 8
For each id i want to squeze the table by flag columns such that all duplicate flag values that follow each other collapse to one row with sum aggregation. Desired result:
flag id value
0 b 1 343
1 a 1 23
2 b 1 53
3 c 2 75
4 d 2 32
5 c 2 1
P.S: I found functions like CONDITIONAL_CHANGE_EVENT, which seem to be able to do that, but the examples of them in docs dont work for me
Use the differnece of row number approach to assign groups based on consecutive row flags being the same. Thereafter use a running sum.
select distinct id,flag,sum(value) over(partition by id,grp) as finalvalue
from (
select t.*,row_number() over(partition by id order by datetime)-row_number() over(partition by id,flag order by datetime) as grp
from tbl t
) t
Here's an approach which uses CONDITIONAL_CHANGE_EVENT:
select
flag,
id,
sum(value) value
from (
select
conditional_change_event(flag) over (order by datetime desc) part,
flag,
id,
value
from so
) t
group by part, flag, id
order by part;
The result is different from your desired result stated in the question because of order by datetime. Adding a separate column for the row number and sorting on that gives the correct result.
For SQL Server 2012, I am trying to assign given rows to sequential buckets based on the maximum size of the bucket (100 in the sample below) and running total of a column. Most of the solutions I found partition by known column changing value e.g. partition by department id etc. However, in this situation all I have is sequential id and size. The closest solution I have found is discussed in this thread for SQL Server 2008 and I tried it but the performance very slow for large row set much worse than cursor based solution. https://dba.stackexchange.com/questions/45179/how-can-i-write-windowing-query-which-sums-a-column-to-create-discrete-buckets
This table can contain up to 10 Million rows. With SQL Server 2012 supporting SUM OVER and LAG and LEAD functions, wondering if someone can suggest a solution based on 2012.
CREATE TABLE raw_data (
id INT PRIMARY KEY
, size INT NOT NULL
);
INSERT INTO raw_data
(id, size)
VALUES
( 1, 96) -- new bucket here, maximum bucket size is 100
, ( 2, 10) -- and here
, ( 3, 98) -- and here
, ( 4, 20)
, ( 5, 50)
, ( 6, 15)
, ( 7, 97)
, ( 8, 96) -- and here
;
--Expected output
--bucket_size is for illustration only, actual needed output is bucket only
id size bucket_size bucket
-----------------------------
1 100 100 1
2 10 10 2
3 98 98 3
4 20 85 4
5 50 85 4
6 15 85 4
7 97 98 5
8 1 98 5
TIA
You can achieve this quite easily in SQL Server 2012 using a window function and framing. The syntax looks quite complex, but the concept is simple - sum all the previous rows up to and including the current one. The cumulative_bucket_size column in this example is for demonstration purposes, as it is part of the equation used to derive the bucket number:
DECLARE #Bucket_Size AS INT;
SET #Bucket_Size = 100
SELECT
id,
size,
SUM(size) OVER (
PARTITION BY 1 ORDER BY id ASC
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
) AS cumulative_bucket_size,
1 + SUM(size) OVER (
PARTITION BY 1 ORDER BY id ASC
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
) / #Bucket_Size AS bucket
FROM
raw_data
The PARTITION BY clause is optional, but would be useful if you had different "bucket sets" for column groupings. I have added it here for completeness.
Results:
id size cumulative_bucket_size bucket
------------------------------------------
1 96 96 1
2 10 106 2
3 98 204 3
4 20 224 3
5 50 274 3
6 15 289 3
7 97 386 4
8 96 482 5
You can read more about windows framing in the following article:
https://www.simple-talk.com/sql/learn-sql-server/window-functions-in-sql-server-part-2-the-frame/
Before you can use the running total method to assign bucket numbers, you need to generate that bucket_size column, because the numbers would be produced based on that column.
Based on your expected output, the bucket ranges are
1..10
11..85
86..100
You could use a simple CASE expression like this to generate a bucket_size column like in your example:
CASE
WHEN size <= 10 THEN 10
WHEN size <= 85 THEN 85
ELSE 100
END
Then you would use LAG() to determine if a row starts a new sequence of sizes belonging to the same bucket:
CASE bucket_size
WHEN LAG(bucket_size) OVER (ORDER BY id) THEN 0
ELSE 1
END
These two calculations could be done in the same (sub)query with the help of CROSS APPLY:
SELECT
d.id,
d.size,
x.bucket_size, -- for illustration only
is_new_seq = CASE x.bucket_size
WHEN LAG(x.bucket_size) OVER (ORDER BY d.id) THEN 0
ELSE 1
END
FROM dbo.raw_data AS d
CROSS APPLY
(
SELECT
CASE
WHEN size <= 10 THEN 10
WHEN size <= 85 THEN 85
ELSE 100
END
) AS x (bucket_size)
The above query would produce this output:
id size bucket_size is_new_seq
-- ---- ----------- ----------
1 96 100 1
2 10 10 1
3 98 100 1
4 20 85 1
5 50 85 0
6 15 85 0
7 97 100 1
8 96 100 0
Now use that result as a derived table and apply SUM() OVER to is_new_seq to produce the bucket numbers, like this:
SELECT
id,
size,
bucket = SUM(is_new_seq) OVER (ORDER BY id)
FROM
(
SELECT
d.id,
d.size,
is_new_seq = CASE x.bucket_size
WHEN LAG(x.bucket_size) OVER (ORDER BY d.id) THEN 0
ELSE 1
END
FROM dbo.raw_data AS d
CROSS APPLY
(
SELECT
CASE
WHEN size <= 10 THEN 10
WHEN size <= 85 THEN 85
ELSE 100
END
) AS x (bucket_size)
) AS s
;
How can one reference a calculated value from the previous row in a SQL query? In my case each row is an event that somehow manipulates the same value from the previous row.
The raw data looks like this:
Eventno Eventtype Totalcharge
3 ACQ 32
2 OUT NULL
1 OUT NULL
Lets say each Eventtype=OUT should half the previous row totalcharge in a column called Remaincharge:
Eventno Eventtype Totalcharge Remaincharge
3 ACQ 32 32
2 OUT NULL 16
1 OUT NULL 8
I've already tried the LAG analytic function but that does not allow me to get a calculated value from the previous row. Tried something like this:
LAG(remaincharge, 1, totalcharge) OVER (PARTITION BY ...) as remaincharge
But this didn't work because remaingcharge could not be found.
Any ideas how to achieve this? Would need a analytics function that can give me the the cumulative sum but given a function instead with access to the previous value.
Thank you in advance!
Update problem description
I'm afraid my example problem was to general, here is a better problem description:
What remains of totalcharge is decided by the ratio of outqty/(previous remainqty).
Eventno Eventtype Totalcharge Remainqty Outqty
4 ACQ 32 100 0
3 OTHER NULL 100 0
2 OUT NULL 60 40
1 OUT NULL 0 60
Eventno Eventtype Totalcharge Remainqty Outqty Remaincharge
4 ACQ 32 100 0 32
3 OTHER NULL 100 0 32 - (0/100 * 32) = 32
2 OUT NULL 60 40 32 - (40/100 * 32) = 12.8
1 OUT NULL 0 60 12.8 - (60/60 * 12.8) = 0
In your case you could work out the first value using the FIRST_VALUE() analytic function and the power of 2 that you have to divide by with RANK() in a sub-query and then use that. It's very specific to your example but should give you the general idea:
select eventno, eventtype, totalcharge
, case when eventtype <> 'OUT' then firstcharge
else firstcharge / power(2, "rank" - 1)
end as remaincharge
from ( select a.*
, first_value(totalcharge) over
( partition by 1 order by eventno desc ) as firstcharge
, rank() over ( partition by 1 order by eventno desc ) as "rank"
from the_table a
)
Here's a SQL Fiddle to demonstrate. I haven't partitioned by anything because you've got nothing in your raw data to partition by...
A variation on Ben's answer to use a windowing clause, which seems to take care of your updated requirements:
select eventno, eventtype, totalcharge, remainingqty, outqty,
initial_charge - case when running_outqty = 0 then 0
else (running_outqty / 100) * initial_charge end as remainingcharge
from (
select eventno, eventtype, totalcharge, remainingqty, outqty,
first_value(totalcharge) over (partition by null
order by eventno desc) as initial_charge,
sum(outqty) over (partition by null
order by eventno desc
rows between unbounded preceding and current row)
as running_outqty
from t42
);
Except it gives 19.2 instead of 12.8 for the third row, but that's what your formula suggests it should be:
EVENTNO EVENT TOTALCHARGE REMAININGQTY OUTQTY REMAININGCHARGE
---------- ----- ----------- ------------ ---------- ---------------
4 ACQ 32 100 0 32
3 OTHER 100 0 32
2 OUT 60 40 19.2
1 OUT 0 60 0
If I add another split so it goes from 60 to zero in two steps, with another non-OUT record in the mix too:
EVENTNO EVENT TOTALCHARGE REMAININGQTY OUTQTY REMAININGCHARGE
---------- ----- ----------- ------------ ---------- ---------------
6 ACQ 32 100 0 32
5 OTHER 100 0 32
4 OUT 60 40 19.2
3 OUT 30 30 9.6
2 OTHER 30 0 9.6
1 OUT 0 30 0
There's an assumption that the remaining quantity is consistent and you can effectively track a running total of what has gone before, but from the data you've shown that looks plausible. The inner query calculates that running total for each row, and the outer query does the calculation; that could be condensed but is hopefully clearer like this...
Ben's answer is the better one (will probably perform better) but you can also do it like this:
select t.*, (connect_by_root Totalcharge) / power (2,level-1) Remaincharge
from the_table t
start with EVENTTYPE = 'ACQ'
connect by prior eventno = eventno + 1;
I think it's easier to read
Here is a demo
I have a table called crewWork as follows :
CREATE TABLE crewWork(
FloorNumber int, AptNumber int, WorkType int, simTime int )
After the table was populated, I need to know how many times a change in apt occurred and how many times a change in floor occurred. Usually I expect to find 10 rows on each apt and 40-50 on each floor.
I could just write a scalar function for that, but I was wondering if there's any way to do that in t-SQL without having to write scalar functions.
Thanks
The data will look like this:
FloorNumber AptNumber WorkType simTime
1 1 12 10
1 1 12 25
1 1 13 35
1 1 13 47
1 2 12 52
1 2 12 59
1 2 13 68
1 1 14 75
1 4 12 79
1 4 12 89
1 4 13 92
1 4 14 105
1 3 12 115
1 3 13 129
1 3 14 138
2 1 12 142
2 1 12 150
2 1 14 168
2 1 14 171
2 3 12 180
2 3 13 190
2 3 13 200
2 3 14 205
3 3 14 216
3 4 12 228
3 4 12 231
3 4 14 249
3 4 13 260
3 1 12 280
3 1 13 295
2 1 14 315
2 2 12 328
2 2 14 346
I need the information for a report, I don't need to store it anywhere.
If you use the accepted answer as written now (1/6/2023), you get correct results with the OP dataset, but I think you can get wrong results with other data.
CONFIRMED: ACCEPTED ANSWER HAS A MISTAKE (as of 1/6/2023)
I explain the potential for wrong results in my comments on the accepted answer.
In this db<>fiddle, I demonstrate the wrong results. I use a slightly modified form of accepted answer (my syntax works in SQL Server and PostgreSQL). I use a slightly modified form of the OP's data (I change two rows). I demonstrate how the accepted answer can be changed slightly, to produce correct results.
The accepted answer is clever but needs a small change to produce correct results (as demonstrated in the above db<>fiddle and described here:
Instead of doing this as seen in the accepted answer COUNT(DISTINCT AptGroup)...
You should do thisCOUNT(DISTINCT CONCAT(AptGroup, '_', AptNumber))...
DDL:
SELECT * INTO crewWork FROM (VALUES
-- data from question, with a couple changes to demonstrate problems with the accepted answer
-- https://stackoverflow.com/q/8666295/1175496
--FloorNumber AptNumber WorkType simTime
(1, 1, 12, 10 ),
-- (1, 1, 12, 25 ), -- original
(2, 1, 12, 25 ), -- new, changing FloorNumber 1->2->1
(1, 1, 13, 35 ),
(1, 1, 13, 47 ),
(1, 2, 12, 52 ),
(1, 2, 12, 59 ),
(1, 2, 13, 68 ),
(1, 1, 14, 75 ),
(1, 4, 12, 79 ),
-- (1, 4, 12, 89 ), -- original
(1, 1, 12, 89 ), -- new , changing AptNumber 4->1->4 ges)
(1, 4, 13, 92 ),
(1, 4, 14, 105 ),
(1, 3, 12, 115 ),
...
DML:
;
WITH groupedWithConcats as (SELECT
*,
CONCAT(AptGroup,'_', AptNumber) as AptCombo,
CONCAT(FloorGroup,'_',FloorNumber) as FloorCombo
-- SQL SERVER doesnt have TEMPORARY keyword; Postgres doesn't understand # for temp tables
-- INTO TEMPORARY groupedWithConcats
FROM
(
SELECT
-- the columns shown in Andriy's answer:
-- https://stackoverflow.com/a/8667477/1175496
ROW_NUMBER() OVER ( ORDER BY simTime) as RN,
-- AptNumber
AptNumber,
ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime) as RN_Apt,
ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime) as AptGroup,
-- FloorNumber
FloorNumber,
ROW_NUMBER() OVER (PARTITION BY FloorNumber ORDER BY simTime) as RN_Floor,
ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY FloorNumber ORDER BY simTime) as FloorGroup
FROM crewWork
) grouped
)
-- if you want to see how the groupings work:
-- SELECT * FROM groupedWithConcats
-- otherwise just run this query to see the counts of "changes":
SELECT
COUNT(DISTINCT AptCombo)-1 as CountAptChangesWithConcat_Correct,
COUNT(DISTINCT AptGroup)-1 as CountAptChangesWithoutConcat_Wrong,
COUNT(DISTINCT FloorCombo)-1 as CountFloorChangesWithConcat_Correct,
COUNT(DISTINCT FloorGroup)-1 as CountFloorChangesWithoutConcat_Wrong
FROM groupedWithConcats;
ALTERNATIVE ANSWER
The accepted-answer may eventually get updated to remove the mistake. If that happens I can remove my warning but I still want leave you with this alternative way to produce the answer.
My approach goes like this: "check the previous row, if the value is different in previous row vs current row, then there is a change". SQL doesn't have idea or row order functions per se (at least not like in Excel for example; )
Instead, SQL has window functions. With SQL's window functions, you can use the window function RANK plus a self-JOIN technique as seen here to combine current row values and previous row values so you can compare them. Here is a db<>fiddle showing my approach, which I pasted below.
The intermediate table, showing the columns which has a value 1 if there is a change, 0 otherwise (i.e. FloorChange, AptChange), is shown at the bottom of the post...
DDL:
...same as above...
DML:
;
WITH rowNumbered AS (
SELECT
*,
ROW_NUMBER() OVER ( ORDER BY simTime) as RN
FROM crewWork
)
,joinedOnItself AS (
SELECT
rowNumbered.*,
rowNumberedRowShift.FloorNumber as FloorShift,
rowNumberedRowShift.AptNumber as AptShift,
CASE WHEN rowNumbered.FloorNumber <> rowNumberedRowShift.FloorNumber THEN 1 ELSE 0 END as FloorChange,
CASE WHEN rowNumbered.AptNumber <> rowNumberedRowShift.AptNumber THEN 1 ELSE 0 END as AptChange
FROM rowNumbered
LEFT OUTER JOIN rowNumbered as rowNumberedRowShift
ON rowNumbered.RN = (rowNumberedRowShift.RN+1)
)
-- if you want to see:
-- SELECT * FROM joinedOnItself;
SELECT
SUM(FloorChange) as FloorChanges,
SUM(AptChange) as AptChanges
FROM joinedOnItself;
Below see the first few rows of the intermediate table (joinedOnItself). This shows how my approach works. Note the last two columns, which have a value of 1 when there is a change in FloorNumber compared to FloorShift (noted in FloorChange), or a change in AptNumber compared to AptShift (noted in AptChange).
floornumber
aptnumber
worktype
simtime
rn
floorshift
aptshift
floorchange
aptchange
1
1
12
10
1
0
0
2
1
12
25
2
1
1
1
0
1
1
13
35
3
2
1
1
0
1
1
13
47
4
1
1
0
0
1
2
12
52
5
1
1
0
1
1
2
12
59
6
1
2
0
0
1
2
13
68
7
1
2
0
0
Note instead of using the window function RANK and JOIN, you could use the window function LAG to compare values in the current row to the previous row directly (no need to JOIN). I don't have that solution here, but it is described in the Wikipedia article example:
Window functions allow access to data in the records right before and after the current record.
If I am not missing anything, you could use the following method to find the number of changes:
determine groups of sequential rows with identical values;
count those groups;
subtract 1.
Apply the method individually for AptNumber and for FloorNumber.
The groups could be determined like in this answer, only there's isn't a Seq column in your case. Instead, another ROW_NUMBER() expression could be used. Here's an approximate solution:
;
WITH marked AS (
SELECT
FloorGroup = ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY FloorNumber ORDER BY simTime),
AptGroup = ROW_NUMBER() OVER ( ORDER BY simTime)
- ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime)
FROM crewWork
)
SELECT
FloorChanges = COUNT(DISTINCT FloorGroup) - 1,
AptChanges = COUNT(DISTINCT AptGroup) - 1
FROM marked
(I'm assuming here that the simTime column defines the timeline of changes.)
UPDATE
Below is a table that shows how the distinct groups are obtained for AptNumber.
AptNumber RN RN_Apt AptGroup (= RN - RN_Apt)
--------- -- ------ ---------
1 1 1 0
1 2 2 0
1 3 3 0
1 4 4 0
2 5 1 4
2 6 2 4
2 7 3 4
1 8 5 => 3
4 9 1 8
4 10 2 8
4 11 3 8
4 12 4 8
3 13 1 12
3 14 2 12
3 15 3 12
1 16 6 10
… … … …
Here RN is a pseudo-column that stands for ROW_NUMBER() OVER (ORDER BY simTime). You can see that this is just a sequence of rankings starting from 1.
Another pseudo-column, RN_Apt contains values produces by the other ROW_NUMBER, namely ROW_NUMBER() OVER (PARTITION BY AptNumber ORDER BY simTime). It contains rankings within individual groups of identical AptNumber values. You can see that, for a newly encountered value, the sequence starts over, and for a recurring one, it continues where it stopped last time.
You can also see from the table that if we subtract RN from RN_Apt (could be the other way round, doesn't matter in this situation), we get the value that uniquely identifies every distinct group of same AptNumber values. You might as well call that value a group ID.
So, now that we've got these IDs, it only remains for us to count them (count distinct values, of course). That will be the number of groups, and the number of changes is one less (assuming the first group is not counted as a change).
add an extra column changecount
CREATE TABLE crewWork(
FloorNumber int, AptNumber int, WorkType int, simTime int ,changecount int)
increment changecount value for each updation
if want to know count for each field then add columns corresponding to it for changecount
Assuming that each record represents a different change, you can find changes per floor by:
select FloorNumber, count(*)
from crewWork
group by FloorNumber
And changes per apartment (assuming AptNumber uniquely identifies apartment) by:
select AptNumber, count(*)
from crewWork
group by AptNumber
Or (assuming AptNumber and FloorNumber together uniquely identifies apartment) by:
select FloorNumber, AptNumber, count(*)
from crewWork
group by FloorNumber, AptNumber