I have two tables linked by an AUTO_KEY field, from one table I'm retrieving the number (id), from the other I get several statuses by number(id), each status has a date associated to it.
I need to restrict the results only to the maximum/latest date for all numbers(ids) and the corresponding status
SELECT
OPERATION.NUMBER,
STATUS.STATUS,
Max(STATUS.DATE)
FROM
STATUS,
OPERATION
WHERE
OPERATION.AUTO_KEY = STATUS.AUTO_KEY
From here
Number Status Date
-----------------------------
1 A 10/20/13
1 B 10/15/13
2 A 10/10/13
2 AX 10/05/13
2 AD 10/03/13
3 DD 10/03/13
The outcome should be
Number Status Date
-----------------------------
1 A 10/20/13
2 A 10/10/13
3 DD 10/03/13
Thanks in advance
You can use a CTE with ROW_NUMBER() function. Also Please use a Table JOIN instead FROM STATUS, OPERATION
;With CTE AS (
SELECT O.NUMBER, S.STATUS, S.DATE,
ROW_NUMBER() OVER (ORDER BY S.DATE DESC) RN
FROM STATUS S JOIN OPERATION O
ON O.AUTO_KEY = S.AUTO_KEY
)
SELECT NUMBER, STATUS, DATE
FROM CTE
WHERE RN = 1
ORDER BY NUMBER
SELECT OPERATION.CNUMBER,
STATUS.STATUS,
STATUS.CDATE
FROM STATUS,
OPERATION
WHERE OPERATION.AUTO_KEY = STATUS.AUTO_KEY
AND STATUS.CDATE = (
SELECT MAX(STATUS.CDATE) MAX_DATE
FROM STATUS,
OPERATION
WHERE OPERATION.AUTO_KEY = STATUS.AUTO_KEY
GROUP BY OPERATION.CNUMBER )
Related
I am trying to update the Contract_Start date to be the earliest date for each unique Company and Route combination. For example, the Contract_Start for the first three records should be 1/15/12 as Company = 1 and Route = 1 for all three. The Contract_Start would then change to 1/20/12 for record 4 as that is the earliest date for the combination of Company = 1 and Route = 2. Any help would be greatly appreciated.
Company Route Driver Date Contract_Start
1 1 A 1/29/12
1 1 B 2/3/12
1 1 C 1/15/12
1 2 A 1/28/12
1 2 B 1/20/12
2 1 A 1/7/12
2 1 B 1/16/12
2 2 A 2/9/12
1 2 B 1/4/12
Update query with subquery can solve your problem
UPDATE TABLE TABLE T
SET CONTRACT_START = (
SELECT MIN(DATE)
FROM TABLE TI
WHERE T.COMPANY = TI.COMPANY
AND T.ROUTE = TI.ROUTE
)
Use window function to get Contract_Start. You needn't to store it at the table.
select Company, Route, Driver, Date, min(Date) over(partition by Company, Route) as Contract_Start
from myTable;
Use an updatable CTE with window functions:
with toupdate as (
select t.*, min(date) over (partition by company, route) as min_date
from t
)
update toupdate
set contract_start = min_date;
Updatable CTE/subqueries/views are a very handy feature in SQL Server and quite powerful when combined with window functions.
I hope this approach will resolve your issue and fulfill your task requirements.
UPDATE TABLE SET Contract_Start = CE.Date1
FROM Table_Name TB JOIN (
SELECT Company,Route,date1, Count(*) AS Countnum,
Row_Number() OVER(PARTITION BY Company, Route ORDER BY date1 ASC) AS Rownumber
FROM Table_Name GROUP BY Company,Route,date1) as CE ON TB.Company = CE.Company AND TB.Route = CE.Route
WHERE Rownumber = 1;
I have a table like this,
Date User
15-06-2018 A
16-06-2018 A
15-06-2018 B
14-06-2018 C
16-06-2018 C
I want to get the output like this,
Date User
16-06-2018 A
15-06-2018 B
16-06-2018 C
I tried Select Max(date),User from Table group by User
Based on your comment, I assume you have duplicated results in those 80 columns when you group by them. Assuming so, here's one option using row_number to always return 1 row per user:
select *
from (
select *, row_number() over (partition by user order by date desc) rn
from yourtable
) t
where rn = 1
You can use correlation subquery :
select t.*
from table t
where date = (select max(t1.date)
from table t1
where t1.user = t.user
);
However, i would also recommend row_number() :
select top (1) with ties *
from table t
order by row_number() over (partition by user order by date desc);
You can also use a ranking function
SELECT User, Date
FROM
(
SELECT User, Date
, Row_id = Row_Number() OVER (Partition by User, ORDER BY User, Date desc)
FROM table
)q
WHERE Row_Id = 1
I would suggest you this
Select * from table t where exist
(Select 1 from
(Select user, max(date) as date from table) A
Where A.user = t.user and A.date = t.date )
I want to retrieve TOPIC 1 SCORES with the most recent score (excluding null) (sorted by date) for each detailsID, (there are only detailsID 2 and 3 here, therefore only two results should return)
What about getting rid of Topic 1 Scores in GROUP BYdetailsID,Topic 1 Scores ?
Use a subquery to get the max and then join to it.
SELECT a.detailsID,`Topic 1 Scores`, a.Date
FROM Information.scores AS a
JOIN (SELECT detailsID, MAX(Date) "MaxDate"
FROM Information.scores
WHERE `Topic 1 Scores` IS NOT NULL
GROUP BY detailsID) Maxes
ON a.detailsID = Maxes.detailsID
AND a.Date = Maxes.MaxDate
WHERE `Topic 1 Scores` IS NOT NULL
Assuming SQL Server:
SELECT
ROW_NUMBER() OVER (PARTITION BY detailsID ORDER BY Date DESC) AS RowNumber,
detailsID, Date, Topic 1 Scores
FROM
Information.scores
Try doing
SELECT detailsID,`Topic 1 Scores`, MAX(Date) as "Date" GROUP BY "Date"
We have a table say 'timekeeper' like
id | entry_date
------------------
1 | 1406864087263
1 | 1406864087268
Assume the entry_date column represents in and out time. Instead of put two columns for in and out we used one column. This is wrong design. I accept.
But my requirement is i want select query to produce output like,
id | in_time | out_time
1 | 1406864087263 | 1406864087268
i.e., show same column as two columns in select stmt.
Is it possible to achieve?
Assumes you always enter before you exit and there is only one enter and exit per id.
SELECT id,
Min(entry_time) [in_time],
Max(entry_time) [out_time]
FROM timekeeper
GROUP BY id
Link to a sqlfiddle: http://sqlfiddle.com/#!6/a93f5/2
You can create a rownumber with 1 for in_rows and 2 for out_rows and self join the in and out rows
with table_with_rows as
(
select *, ROW_NUMBER() OVER ( PARTITION BY id ORDER BY entry_date )
as in_out from timekeeper
)
select in_table.id, in_table.entry_date as in_time, out_table.entry_date
as out_time from
table_with_rows in_table
inner join
table_with_rows out_table
on in_table.in_out = 1 and out_table.in_out = 2 and in_table.id = out_table.id
Link to SqlFiddle
;WITH CTE
AS
(
SELECT ROW_NUMBER() OVER (PARTITION BY ID ORDER BY LOGINOUT)RNO,ID,LOGINOUT FROM #TEMP
)
SELECT C1.LOGINOUT AS INTIME,C2.LOGINOUT AS OUTTIME FROM CTE C1
LEFT OUTER JOIN CTE AS C2
ON C1.ID = C2.ID+1
I want to retrieve elapsed days since the last time the data of the specific column was changed, for example :
TABLE_X contains
ID PDATE DATA1 DATA2
A 10-Jan-2013 5 10
A 9-Jan-2013 5 10
A 8-Jan-2013 5 11
A 7-Jan-2013 5 11
A 6-Jan-2013 14 12
A 5-Jan-2013 14 12
B 10-Jan-2013 3 15
B 9-Jan-2013 3 15
B 8-Jan-2013 9 15
B 7-Jan-2013 9 15
B 6-Jan-2013 14 15
B 5-Jan-2013 14 8
I simplify the table for example purpose.
The result should be :
ID DATA1_LASTUPDATE DATA2_LASTUPDATE
A 4 2
B 2 5
which says,
- data1 of A last update is 4 days ago,
- data2 of A last update is 2 days ago,
- data1 of B last update is 2 days ago,
- data2 of B last update is 5 days ago.
Using query below is OK but it takes too long to complete if I apply it to the real table which have lots of records and add 2 more data columns to find their latest update days.
I use LEAD function for this purposes.
Any other alternatives to speed up the query?
with qdata1 as
(
select ID, pdate from
(
select a.*, row_number() over (partition by ID order by pdate desc) rnum from
(
select a.*,
lead(data1,1,0) over (partition by ID order by pdate desc) - data1 as data1_diff
from table_x a
) a
where data1_diff <> 0
)
where rnum=1
),
qdata2 as
(
select ID, pdate from
(
select a.*, row_number() over (partition by ID order by pdate desc) rnum from
(
select a.*,
lead(data2,1,0) over (partition by ID order by pdate desc) - data2 as data2_diff
from table_x a
) a
where data2_diff <> 0
)
where rnum=1
)
select a.ID,
trunc(sysdate) - b.pdate data1_lastupdate,
trunc(sysdate) - c.pdate data2_lastupdate,
from table_master a, qdata1 b, qdata2 c
where a.ID=b.ID(+) and a.ID=b.ID(+)
and a.ID=c.ID(+) and a.ID=c.ID(+)
Thanks a lot.
You can avoid the multiple hits on the table and the joins by doing both lag (or lead) calculations together:
with t as (
select id, pdate, data1, data2,
lag(data1) over (partition by id order by pdate) as lag_data1,
lag(data2) over (partition by id order by pdate) as lag_data2
from table_x
),
u as (
select t.*,
case when lag_data1 is null or lag_data1 != data1 then pdate end as pdate1,
case when lag_data2 is null or lag_data2 != data2 then pdate end as pdate2
from t
),
v as (
select u.*,
rank() over (partition by id order by pdate1 desc nulls last) as rn1,
rank() over (partition by id order by pdate2 desc nulls last) as rn2
from u
)
select v.id,
max(trunc(sysdate) - (case when rn1 = 1 then pdate1 end))
as data1_last_update,
max(trunc(sysdate) - (case when rn2 = 1 then pdate2 end))
as data2_last_update
from v
group by v.id
order by v.id;
I'm assuming that you meant your data to be for Jun-2014, not Jan-2013; and that you're comparing the most recent change dates with the current date. With the data adjusted to use 10-Jun-2014 etc., this gives:
ID DATA1_LAST_UPDATE DATA2_LAST_UPDATE
-- ----------------- -----------------
A 4 2
B 2 5
The first CTE (t) gets the actual table data and adds two extra columns, one for each of the data columns, using lag (whic his the the same as lead ordered by descending dates).
The second CTE (u) adds two date columns that are only set when the data columns are changed (or when they are first set, just in case they have never changed). So if a row has data1 the same as the previous row, its pdate1 will be blank. You could combine the first two by repeating the lag calculation but I've left it split out to make it a bit clearer.
The third CTE (v) assigns a ranking to those pdate columns such that the most recent is ranked first.
And the final query works out the difference from the current date to the highest-ranked (i.e. most recent) change for each of the data columns.
SQL Fiddle, including all the CTEs run individually so you can see what they are doing.
Your query wasn't returning the right results for me, maybe I missed something, but I got the correct results also with the below query (you can check this SQLFiddle demo):
with ranked as (
select ID,
data1,
data2,
rank() over(partition by id order by pdate desc) r
from table_x
)
select id,
sum(DATA1_LASTUPDATE) DATA1_LASTUPDATE,
sum(DATA2_LASTUPDATE) DATA2_LASTUPDATE
from (
-- here I get when data1 was updated
select id,
count(1) DATA1_LASTUPDATE,
0 DATA2_LASTUPDATE
from ranked
start with r = 1
CONNECT BY (PRIOR data1 = data1)
and PRIOR r = r - 1
group by id
union
-- here I get when data2 was updated
select id,
0 DATA1_LASTUPDATE,
count(1) DATA0_LASTUPDATE
from ranked
start with r = 1
CONNECT BY (PRIOR data2 = data2)
and PRIOR r = r - 1
group by id
)
group by id