I have the following table:
respid, uploadtime
I need a query that will show all the records that respid is duplicate and show them except the latest (by upload time)
exmple:
4 2014-01-01
4 2014-06-01
4 2015-01-01
4 2015-06-01
4 2016-01-01
In this case the query should return four records (the latest is : 4 2016-01-01 )
Thank you very much.
Use ROW_NUMBER:
WITH cte AS (
SELECT respid, uploadtime,
ROW_NUMBER() OVER (PARTITION BY respid ORDER BY uploadtime DESC) rn
FROM yourTable
)
SELECT respid, uploadtime
FROM cte
WHERE rn > 1
ORDER BY respid, uploadtime;
The logic here is to show all records except those having the first row number value, which would be the latest records for each respid group.
If I interpreted your question correctly, then you want to see all records where respid occurs multiple times, but exclude the last duplicate.
Translating this to SQL could sound like "show all records that have a later record for the same respid". That is exactly what the solution below does. It says that for every row in the result a later record with the same respid must exists.
Sample data
declare #MyTable table
(
respid int,
uploadtime date
);
insert into #MyTable (respid, uploadtime) values
(4, '2014-01-01'),
(4, '2014-06-01'),
(4, '2015-01-01'),
(4, '2015-06-01'),
(4, '2016-01-01'), --> last duplicate of respid=4, not part of result
(5, '2020-01-01'); --> has no duplicate, not part of result
Solution
select mt.respid, mt.uploadtime
from #MyTable mt
where exists ( select top 1 'x'
from #MyTable mt2
where mt2.respid = mt.respid
and mt2.uploadtime > mt.uploadtime );
Result
respid uploadtime
----------- ----------
4 2014-01-01
4 2014-06-01
4 2015-01-01
4 2015-06-01
Related
There was one other SIMILAR answer but it is 2 pages long and my requirement doesn't need that. I have 2 tables, tableA and a tableB, and I need to find the COUNTS of rows that are present in tableA but are not present in tableB OR if update_on in tableB is not today's date.
My tables:
tableA:
release_id book_name release_begin_date
----------------------------------------------------
1122 midsummer 2016-01-01
1123 fool's errand 2016-06-01
1124 midsummer 2016-04-01
1125 fool's errand 2016-08-01
tableB:
release_id book_name updated_on
-----------------------------------------
1122 midsummer 2016-08-17
1123 fool's errand 2016-08-16**
Expected result: Since each book is missing one release id, 1 is count. But in addition fool's errand's existing row in tableB has updated_on date of yesterday and not today, it needs to be counted in count_of_not_updated.
book_name count_of_missing count_of_not_updated
-------------------------------------------------------
midsummer 1 0
fool's errand 1 1
Note: Even though fool's errand is present in tableB, I need to show it in count_of_missing because it's updated_on date is yesterday and not today. I know it has to be a combination of a left join and something else, but the kicker here is not only getting the missing rows from left table but at the same time checking if the updated_on table was today's date and if not, count that row in count_of_not_updated.
select sum(case when b.release_id is null then 1 else 0 end) as noReleaseID
, sum(case when datediff(d, b.release_date, getdate()) > 0 then 1 else 0 end) as releaseDateNotToday
, a.release_id
from tableA a
left outer join tableB b on a.release_id = b.release_id
Group by a.release_id
This example uses a sum function on a case statement to add up the instances where the case statement returns true. Note that the current code assumes, as in your example, that you are looking to count all old release dates from table b - more steps would be required if each book has multiple old release dates in table b, and you only want to compare to the most recent release date.
Try this
DECLARE #tableA TABLE (release_id INT, book_name NVARCHAR(50), release_begin_date DATETIME)
DECLARE #tableB TABLE (release_id INT, book_name NVARCHAR(50), updated_on DATETIME)
INSERT INTO #tableA
VALUES
(1122, 'midsummer', '2016-01-01'),
(1123, 'fool''s errand', '2016-06-01'),
(1124, 'midsummer', '2016-04-01'),
(1125, 'fool''s errand', '2016-08-01')
INSERT INTO #tableB
VALUES
(1122, 'midsummer', '2016-08-17'),
(1123, 'fool''s errand', '2016-08-16')
;WITH TmpTableA
AS
(
SELECT
book_name,
COUNT(1) CountOfTableA
FROM
#tableA
GROUP BY
book_name
), TmpTableB
AS
(
SELECT
book_name,
COUNT(1) CountOfTableB,
SUM(CASE WHEN CONVERT(VARCHAR(11), updated_on, 112) = CONVERT(VARCHAR(11), GETDATE(), 112) THEN 0 ELSE 1 END) count_of_not_updated
FROM
#tableB
GROUP BY
book_name
)
SELECT
A.book_name ,
A.CountOfTableA - ISNULL(B.CountOfTableB, 0) AS count_of_missing,
ISNULL(B.count_of_not_updated, 0) AS count_of_not_updated
FROM
TmpTableA A LEFT JOIN
TmpTableB B ON A.book_name = B.book_name
Result:
book_name count_of_missing count_of_not_updated
-------------------- ---------------- --------------------
fool's errand 1 1
midsummer 1 1
I am facing this problem where I need to compare the most recent row with the immediate previous one based on the same criteria (it will be trader in this case).
Here is my table:
ID Trader Price
-----------------
1 abc 5
2 xyz 5.2
3 abc 5.7
4 xyz 5
5 abc 5.2
6 abc 6
Here is the script
CREATE TABLE Sale
(
ID int not null PRIMARY KEY ,
trader varchar(10) NOT NULL,
price decimal(2,1),
)
INSERT INTO Sale (ID,trader, price)
VALUES (1, 'abc', 5), (2, 'xyz', 5.2),
(3, 'abc', 5.7), (4, 'xyz', 5),
(5, 'abc', 5.2), (6, 'abc', 6);
So far I am working with this solution that is not perfect yet
select
a.trader,
(a.price - b.price ) New_price
from
sale a
join
sale b on a.trader = b.trader and a.id > b.ID
left outer join
sale c on a.trader = c.trader and a.id > c.ID and b.id < c.ID
where
c.ID is null
Above is not perfect because I want to compare only the most recent with the immediate previous on... In this sample for example
Trader abc : I will compare only id = 6 and id = 5
Trader xyz : id = 4 and id = 2
Thanks for any help!
If you are using SQL Server 2012 or later, you can use functions LEAD and LAG to join previous and next data. Unfortunately these function can only be used in SELECT or ORDER BY clause, so you will need to use subquery to get the data you need:
SELECT t.trader, t.current_price - t.previous_price as difference
FROM (
SELECT
a.trader,
a.price as current_price,
LAG(a.price) OVER(PARTITION BY a.trader ORDER BY a.ID) as previous_price,
LEAD(a.price) OVER(PARTITION BY a.trader ORDER BY a.ID) as next_price
FROM sale a
) t
WHERE t.next_price IS NULL
Here in your subquery you create additional columns for previous and next value. Then in your main query you filter only these rows where next price is NULL - that indicates this is the last row for the specific trader.
I'm working with SQL Server 2005 and looking to export some data off of a table I have. However, prior to do that I need to update a status column based upon a field called "VisitNumber", which can contain multiple entries same value entries. I have a table set up in the following manner. There are more columns to it, but I am just putting in what's relevant to my issue
ID Name MyReport VisitNumber DateTimeStamp Status
-- --------- -------- ----------- ----------------------- ------
1 Test John Test123 123 2014-01-01 05.00.00.000
2 Test John Test456 123 2014-01-01 07.00.00.000
3 Test Sue Test123 555 2014-01-02 08.00.00.000
4 Test Ann Test123 888 2014-01-02 09.00.00.000
5 Test Ann Test456 888 2014-01-02 10.00.00.000
6 Test Ann Test789 888 2014-01-02 11.00.00.000
Field Notes
ID column is a unique ID in incremental numbers
MyReport is a text value and can actually be thousands of characters. Shortened for simplicity. In my scenario the text would be completely different
Rest of fields are varchar
My Goal
I need to address putting in a status of "F" for two conditions:
* If there is only one VisitNumber, update the status column of "F"
* If there is more than one visit number, only put "F" for the one based upon the earliest timestamp. For the other ones, put in a status of "A"
So going back to my table, here is the expectation
ID Name MyReport VisitNumber DateTimeStamp Status
-- --------- -------- ----------- ----------------------- ------
1 Test John Test123 123 2014-01-01 05.00.00.000 F
2 Test John Test456 123 2014-01-01 07.00.00.000 A
3 Test Sue Test123 555 2014-01-02 08.00.00.000 F
4 Test Ann Test123 888 2014-01-02 09.00.00.000 F
5 Test Ann Test456 888 2014-01-02 10.00.00.000 A
6 Test Ann Test789 888 2014-01-02 11.00.00.000 A
I was thinking I could handle this by splitting each types of duplicates/triplicates+ (2,3,4,5). Then updating every other (or every 3,4,5 rows). Then delete those from the original table and combine them together to export the data in SSIS. But I am thinking there is a much more efficient way of handling it.
Any thoughts? I can accomplish this by updating the table directly in SQL for this status column and then export normally through SSIS. Or if there is some way I can manipulate the column for the exact conditions I need, I can do it all in SSIS. I am just not sure how to proceed with this.
WITH cte AS
(
SELECT *, ROW_NUMBER() OVER (PARTITION BY VisitNumber ORDER BY DateTimeStamp) rn from MyTable
)
UPDATE cte
SET [status] = (CASE WHEN rn = 1 THEN 'F' ELSE 'A' END)
I put together a test script to check the results. For your purposes, use the update statements and replace the temp table with your table name.
create table #temp1 (id int, [name] varchar(50), myreport varchar(50), visitnumber varchar(50), dts datetime, [status] varchar(1))
insert into #temp1 (id,[name],myreport,visitnumber, dts) values (1,'Test John','Test123','123','2014-01-01 05:00')
insert into #temp1 (id,[name],myreport,visitnumber, dts) values (2,'Test John','Test456','123','2014-01-01 07:00')
insert into #temp1 (id,[name],myreport,visitnumber, dts) values (3,'Test Sue','Test123','555','2014-01-01 08:00')
insert into #temp1 (id,[name],myreport,visitnumber, dts) values (4,'Test Ann','Test123','888','2014-01-01 09:00')
insert into #temp1 (id,[name],myreport,visitnumber, dts) values (5,'Test Ann','Test456','888','2014-01-01 10:00')
insert into #temp1 (id,[name],myreport,visitnumber, dts) values (6,'Test Ann','Test789','888','2014-01-01 11:00')
select * from #temp1;
update #temp1 set status = 'F'
where id in (
select id from #temp1 t1
join (select min(dts) as mindts, visitnumber
from #temp1
group by visitNumber) t2
on t1.visitnumber = t2.visitnumber
and t1.dts = t2.mindts)
update #temp1 set status = 'A'
where id not in (
select id from #temp1 t1
join (select min(dts) as mindts, visitnumber
from #temp1
group by visitNumber) t2
on t1.visitnumber = t2.visitnumber
and t1.dts = t2.mindts)
select * from #temp1;
drop table #temp1
Hope this helps
I'm using Microsoft SQL. I have a table that contains information stored by two different categories and a date. For example:
ID Cat1 Cat2 Date/Time Data
1 1 A 11:00 456
2 1 B 11:01 789
3 1 A 11:01 123
4 2 A 11:05 987
5 2 B 11:06 654
6 1 A 11:06 321
I want to extract one line for each unique combination of Cat1 and Cat2 and I need the line with the oldest date. In the above I want ID = 1, 2, 4, and 5.
Thanks
Have a look at row_number() on MSDN.
SELECT *
FROM (
SELECT *,
ROW_NUMBER() OVER (PARTITION BY col1, col2 ORDER BY date_time, id) rn
FROM mytable
) q
WHERE rn = 1
(run the code on SQL Fiddle)
Quassnoi's answer is fine, but I'm a bit uncomfortable with how it handles dups. It seems to return based on insertion order, but I'm not sure if even that can be guaranteed? (see these two fiddles for an example where the result changes based on insertion order: dup at the end, dup at the beginning)
Plus, I kinda like staying with old-school SQL when I can, so I would do it this way (see this fiddle for how it handles dups):
select *
from my_table t1
left join my_table t2
on t1.cat1 = t2.cat1
and t1.cat2 = t2.cat2
and t1.datetime > t2.datetime
where t2.datetime is null
I have a problem with a query.
This is the data (order by Timestamp):
Data
ID Value Timestamp
1 0 2001-1-1
2 0 2002-1-1
3 1 2003-1-1
4 1 2004-1-1
5 0 2005-1-1
6 2 2006-1-1
7 2 2007-1-1
8 2 2008-1-1
I need to extract distinct values and the first occurance of the date. The exception here is that I need to group them only if not interrupted with a new value in that timeframe.
So the data I need is:
ID Value Timestamp
1 0 2001-1-1
3 1 2003-1-1
5 0 2005-1-1
6 2 2006-1-1
I've made this work by a complicated query, but am sure there is an easier way to do it, just cant think of it. Could anyone help?
This is what I started with - probably could work with that. This is a query that should locate when a value is changed.
> SELECT * FROM Data d1 join Data d2 ON d1.Timestamp < d2.Timestamp and
> d1.Value <> d2.Value
It probably could be done with a good use of row_number clause but cant manage it.
Sample data:
declare #T table (ID int, Value int, Timestamp date)
insert into #T(ID, Value, Timestamp) values
(1, 0, '20010101'),
(2, 0, '20020101'),
(3, 1, '20030101'),
(4, 1, '20040101'),
(5, 0, '20050101'),
(6, 2, '20060101'),
(7, 2, '20070101'),
(8, 2, '20080101')
Query:
;With OrderedValues as (
select *,ROW_NUMBER() OVER (ORDER By TimeStamp) as rn --TODO - specific columns better than *
from #T
), Firsts as (
select
ov1.* --TODO - specific columns better than *
from
OrderedValues ov1
left join
OrderedValues ov2
on
ov1.Value = ov2.Value and
ov1.rn = ov2.rn + 1
where
ov2.ID is null
)
select * --TODO - specific columns better than *
from Firsts
I didn't rely on the ID values being sequential and without gaps. If that's the situation, you can omit OrderedValues (using the table and ID in place of OrderedValues and rn). The second query simply finds rows where there isn't an immediate preceding row with the same Value.
Result:
ID Value Timestamp rn
----------- ----------- ---------- --------------------
1 0 2001-01-01 1
3 1 2003-01-01 3
5 0 2005-01-01 5
6 2 2006-01-01 6
You can order by rn if you need the results in this specific order.