--option 1 delete from jobs where exists (select 1 from calibrations c where id =c.JobId) --option 2 delete from jobs from calibrations c inner join jobs j on j.id =c.JobId --option 3 delete from jobs where id in (select Jobid from calibrations ) --This is not a good option if you use the id column from your delete table, all rows will be deleted delete from jobs where id in (select Id from calibrations )
In the US, Thanksgiving is always celebrated on the fourth Thursday of November.
For any given date, we can find out Thanksgiving day in that year with T-SQL.
declare @anydate datetime='2014-01-30' declare @dt datetime='20151101' Select @dt=dateadd(month,10,dateadd(year, datediff(year,0,@anydate),0)) ---November 1st select DateAdd(day, (7+5 -DatePart(weekday, @dt))%7, @dt) firstThuIntheMonth select DATEADD(WEEK, 3, DATEADD(d, Case when DATEPART(dw, @dt)>5 Then 7 Else 0 ENd + (5 - DATEPART(dw, @dt)), @dt)) Thanksgivingday Select DATEADD(WEEK, 3, DateAdd(day, (7+5 -DatePart(weekday, @dt))%7, @dt) ) Thanksgivingday /* Year U.S. Thanksgiving 2012 Thursday, November 22 2013 Thursday, November 28 2014 Thursday, November 27 2015 Thursday, November 26 2016 Thursday, November 24 2017 Thursday, November 23 2018 Thursday, November 22 2019 Thursday, November 28 */
--Robyn Page's NthDayOfWeekOfMonth CREATE FUNCTION NthDayOfWeekOfMonth ( @TheYear CHAR(4), --the year as four characters (e.g. '2014') @TheMonth CHAR(3), --in english (Sorry to our EU collegues) e.g. Jun, Jul, Aug @TheDayOfWeek CHAR(3), -- one of Mon, Tue, Wed, Thu, Fri, Sat, Sun @Nth INT) --1 for the first date, 2 for the second occurence, 3 for the third RETURNS DATETIME WITH EXECUTE AS CALLER AS BEGIN RETURN DATEADD(MONTH, DATEDIFF(MONTH, 0, CONVERT(date,'1 '+@TheMonth+' '+@TheYear,113)), 0)+ (7*@Nth)-1 -(DATEPART (Weekday, DATEADD(MONTH, DATEDIFF(MONTH, 0, CONVERT(date,'1 '+@TheMonth+' '+@TheYear,113)), 0)) +@@DateFirst+(CHARINDEX(@TheDayOfWeek,'FriThuWedTueMonSunSat')-1)/3)%7 END GO SELECT dbo.NthDayOfWeekOfMonth ('2019','Nov','Thu',4) --Robyn Page's SQL Server DATE/TIME Workbench
use [myDB]; declare @dt datetime=getdate() declare @dbname sysname= (select DB_NAME()) declare @server_name sysname ='DEVSQL' ;WIth mycte as (SELECT s.database_name, s.backup_start_date, s.first_lsn, s.last_lsn, s.database_backup_lsn, s.checkpoint_lsn, s.[type],-- D--FULL,I--Diff,L--LOG m.physical_device_name, s.server_name,s.recovery_model ,s.backup_finish_date ,row_number() Over(Partition by s.[type] Order by s.backup_finish_date DESC ) rn FROM msdb.dbo.backupset s INNER JOIN msdb.dbo.backupmediafamily m ON s.media_set_id = m.media_set_id WHERE s.database_name = @dbname AND server_name=@server_name AND s.backup_finish_date >=(select top 1 s.backup_finish_date from msdb.dbo.backupset s Where s.[type]='D' and s.server_name= @server_name AND s.database_name = @dbname AND s.backup_finish_date<= @dt Order by s.backup_finish_date DESC) AND s.backup_finish_date<= @dt ) Select * from mycte WHERE (rn=1 and [type]<>'L') Or (last_lsn >= (select last_lsn+1 from mycte WHERE rn=1 and [type]='I') ) ORDER BY backup_finish_date desc,backup_start_date desc
You can find the original question from MSDN and I tried to come up with a solution but with requirement changes, here is the final version. I hope this is.
if object_id('test','U') is not null drop table test Create table test (Car int, X Char(1), [Time] int) INSERT INTO test VALUES ( 11, 'A', 5 ), ( 11, 'B', 6 ), ( 11, 'B', 7 ), ( 11, 'B', 8 ), ( 11,'C', 9 ), ( 11,'C', 10 ), ( 11,'C', 11 ), ( 11,'A', 12 ), ( 11,'B', 13 ) ; with mycte as ( Select Car, X, [Time] time1, lead( [Time],1) Over( Order by [Time]) leadTime ,row_number()Over(order by [Time]) - ROW_NUMBER() OVER (PARTITION BY X ORDER BY [Time]) delta from test ) ,mycte1 as ( Select Car, X, time1,leadTime, delta , ROW_NUMBER() OVER (PARTITION BY delta ORDER BY [Time1] DESC) rn , count(*) OVER (PARTITION BY X, delta ) cnt from mycte) Select Car, X, min(time1) minTime, max(leadTime) maxTime, 0 as moving from mycte1 WHERE rn>1 Group by Car, X, delta UNION ALL Select Car, X, min(time1) minTime, max(CASE WHEN cnt> 1 Then leadTime Else time1 END ) maxTime , 1 as Moving from mycte1 WHERE rn=1 GROUP BY Car, X, delta Order by minTime /* Car X minTime maxTime moving 11 A 5 5 1 11 B 6 8 0 11 B 8 9 1 11 C 9 11 0 11 C 11 12 1 11 A 12 12 1 11 B 13 13 1 */
--create table test (examID int, col1 int, col4 int, col3 int, col2 int) --Insert into test values (1, 1,2,3,4),(1,4,3,2,1),(1,9,9,9,9) Declare @ExamID int=1 DECLARE @colsSorted AS NVARCHAR(2000), @sql AS NVARCHAR(4000) declare @mytable varchar(50)='test', @myschema varchar(50) ='dbo' select @colsSorted = STUFF((select ', '+quotename(column_name,'[') from information_schema.columns where table_name = @mytable and TABLE_SCHEMA=@myschema AND COLUMN_NAME<>'ExamID' Order by NewID() FOR XML PATH (''),type).value('.','varchar(max)'), 1, 2, '') print @colsSorted Set @sql=N'SELECT '+ @colsSorted + ' FROM ' + @myschema+ '.'+ @mytable + ' WHERE ExamID='+ CAST(@ExamID as varchar(4)) exec sp_executesql @sql; --- drop table test
--===== Create number table on-the-fly ;WITH Num1 (n) AS ( SELECT 1 as n UNION ALL SELECT n+1 as n FROM Num1 Where n<101), Num2 (n) AS (SELECT 1 FROM Num1 AS X, Num1 AS Y), Nums (n) AS (SELECT ROW_NUMBER() OVER(ORDER BY n) FROM Num2) ,mycte as ( select strCol , Row_NUmber() Over(Order By n) rn , CAST(substring(strCol, n, charindex('/', strCol + '/', n) - n) as MONEY) splitVal from test cross apply Nums Where n <= len(strCol) AND substring('/' + strCol, n, 1) = '/' ) Select * from mycte WHERE rn=4 Drop table test
if object_id('test','U') is not null drop table test create table test (MBR_ID int, DS varchar(10)) Insert into test values (1,'2011-07-15'), (1,'2011-07-21'),(1,'2011-07-29'),(1,'2011-08-04'),(1,'2011-08-11'),(1,'2011-08-25'),(1,'2011-09-01'),(1,'2011-09-21') ,(1,'2012-01-11'),(1,'2012-03-15'),(1,'2012-06-04'),(1,'2012-10-11'),(1,'2013-02-14'),(1,'2013-06-18'),(1,'2013-07-08'),(1,'2013-07-15') ,(1,'2013-07-17'),(1,'2013-08-07'),(1,'2013-08-14'),(1,'2013-08-28'),(1,'2013-09-11'),(1,'2013-09-25'),(1,'2013-11-20') ,(1,'2013-12-04'),(1,'2013-12-17'),(1,'2014-01-14'),(1,'2014-01-29'),(1,'2014-02-25'),(1,'2014-02-26'),(1,'2014-03-12') ,(1,'2014-03-19'),(1,'2014-03-22'),(1,'2014-03-24') ;with mytest as ( --move date to the end of the month select MBR_ID, eomonth(ds) as ds from test) ,mycte as ( SELECT MBR_ID, ds, lag(ds, 1) Over(partition by MBR_ID ORDER BY ds) dslag ,Case when datediff(month,lag(ds, 1) Over(partition by MBR_ID ORDER BY ds), ds) <=2 Then 0 Else datediff(month,ds,lag(ds, 1) Over(partition by MBR_ID ORDER BY ds) ) End diff FROM mytest) ---get group grn ,mycte1 as ( Select MBR_ID, ds, SUM(diff) Over(Order by ds) grn from mycte ) --Get YYYY-MM ,mycte2 as ( select MBR_ID, Convert(varchar(7),min(ds),126) START_DT, Convert(varchar(7),max(ds),126) END_DT from mycte1 Group by MBR_ID,grn) --Sort Select MBR_ID, START_DT,END_DT from mycte2 Order by Cast(START_DT+'-01' as date) /* MBR_ID START_DT END_DT 1 2011-07 2011-09 1 2012-01 2012-03 1 2012-06 2012-06 1 2012-10 2012-10 1 2013-02 2013-02 1 2013-06 2014-03 */
I ran into a text file (generated from informix(?) ) with an extral pipe (|) appended at the row end. We need to manipulate the importing procees from import/export wizard to skip the last pipe.
You can play with the an extra column from the source and ingnore it from target to do it.
However, I found an easy way :
You can add a pipe (|) directly to Row delimiter (both header and regular Columns) and it should work.
If you are using bcp or bulk insert, you can define both column and row delimiter to import the data to skip the list pipe.
Here is the sample code for bco and bulk insert.
--- Bulk Insert BULK INSERT [TestFullMode].[dbo].[InfoData2] FROM 'C:\temp\myDataPipetail.txt' WITH ( FIELDTERMINATOR ='|', ROWTERMINATOR ='|\n', FirstRow=2 ); --bcp DECLARE @cmd NVARCHAR(4000) set @cmd = 'BCP [TestFullMode].[dbo].[InfoData2] IN C:\temp\myDataPipetail.txt -c -T -t\^| -F 2 -r ^|\n -S'+ @@servername exec master..xp_cmdshell @cmd
We can take advantage of the the wildcard match  with LIKE in TSQL for single letter search.
Here is a code snippet:
CREATE TABLE Testa ( id INT, col1 VARCHAR(100)) INSERT INTO Testa VALUES (1,'a,b,c,d') ,(2,'d,e,f,g') , (3,'a,s,k') , (4,'t') declare @s varchar (20)='a,z,t' select * from testa where ','+col1+',' like '%,'+quotename(@s)+',%' --drop table testa
As a last resort, you may be able to recover your deleted data or truncated data from intact log file.
It is very unlikely for someone who knows how to recover data without a backup in their own work.
But the point is that SQL Server tracking all operations in its log file and as long as the log file is intact,
the real thing is to have the knowledge to get the data back.
The techniques are using undocumented functions: fn_dblog and DBCC PAGE to get access to the raw data inside the log file.
It takes extra efforts to retrieve the raw data back.
If you have full backup and log backups, the process can be a little simpler.
This blog by itself may not help you directly but it points to a few resources to get your hand dirty.
If you really want to do it now, download Mr. Imran’s scripts and give them a try.
I have listed a few pointers incase you are interested in this process.
1. Paul Randal has posted detailed techniques and inside knowledge about the internals of log file.
2. Mladen Prajdić has a good write up in this topic with code samples:
3. Muhammad Imran posted two stored procedures to recover these lost data.
To get truncated data back in SQL Server 2014, you need to modify the code a little since the underneath data format changes.
In order to make these operations work, the codition is to be able to read intact log file.
In Full recover mode, most likely you have all your log chains since you don’t have a log backup. You can go ahead to try these two stored procedures posted by Mr. Imran.
If your database is in Simple Recover Mode, you may or may not be successful. If your log file is big enough and ther is no checkpoints run (before log clear),
you may be able to get your data back and you are lucky.
This excercise helps to get a peek inside SQL Server log file and to get a better understanding related to SQL Server log file management.
The normal route to make sure we can safeguard our data is to implement a robust disaster recovery solution with good backups in a non-broken chain.
It should be handy to get lost data back more efficiently.