Skip to main content

SQL SERVER – @@IDENTITY vs SCOPE_IDENTITY() vs IDENT_CURRENT – Retrieve Last Inserted Identity of Record

 SELECT @@IDENTITY

It returns the last IDENTITY value produced on a connection, regardless of the table that produced the value, and regardless of the scope of the statement that produced the value.
@@IDENTITY will return the last identity value entered into a table in your current session. While @@IDENTITY is limited to the current session, it is not limited to the current scope. If you have a trigger on a table that causes an identity to be created in another table, you will get the identity that was created last, even if it was the trigger that created it.

SELECT SCOPE_IDENTITY()
It returns the last IDENTITY value produced on a connection and by a statement in the same scope, regardless of the table that produced the value.
SCOPE_IDENTITY(), like @@IDENTITY, will return the last identity value created in the current session, but it will also limit it to your current scope as well. In other words, it will return the last identity value that you explicitly created, rather than any identity that was created by a trigger or a user defined function.

SELECT IDENT_CURRENT(‘tablename’)
It returns the last IDENTITY value produced in a table, regardless of the connection that created the value, and regardless of the scope of the statement that produced the value.
IDENT_CURRENT is not limited by scope and session; it is limited to a specified table. IDENT_CURRENT returns the identity value generated for a specific table in any session and any scope.

To avoid the potential problems associated with adding a trigger later on, always use SCOPE_IDENTITY() to return the identity of the recently added row in your T SQL Statement or Stored Procedure

Comments

Post a Comment

Popular posts from this blog

SQL SERVER – Fix : Error 1702 CREATE TABLE failed because column in table exceeds the maximum of columns

  Error 1702 CREATE TABLE failed because column in table exceeds the maximum of columns SQL Server 2000 supports table with maximum 1024 columns. This errors happens when we try to create table with 1024 columns or try to add columns to table which exceeds more than 1024. Fix/Solution/WorkAround: Reduce the number of columns in the table to 1,024 or less
Post a Comment
Read more

Select Names from table which have vowels

  Problem Query the list of  CITY  names from  table  which have vowels (i.e.,  a ,  e ,  i ,  o , and  u ) as both their first  and  last characters. Your result cannot contain duplicates. Input Format The  STATION  table is described as follows: Field Type ID NUMBER CITY VARCHAR2(21) STATE VARCHAR2(2) LAT_N NUMBER LONG_W NUMBER STATION where  LAT_N  is the northern latitude and  LONG_W  is the western longitude. MYSQL select distinct city from station where (city like 'a%' or city like 'e%' or city like 'i%' or city like 'o%' or city like 'u%' ) and ( city like '%a' or city like '%e' or city like '%i' or city like '%o' or city like '%u' )
1 comment
Read more

Methods of Rank Rows in SQL Server: ROW_NUMBER(), RANK(), DENSE_RANK() and NTILE()

SQL Server provides us with a number of window functions that help us to perform calculations across a set of rows, without the need to repeat the calls to the database. Unlike the standard aggregate functions, the window functions will not group the rows into a single output row, they will return a single aggregated value for each row, keeping the separate identities for those rows. The Window term here is not related to the Microsoft Windows operating system, it describes the set of rows that the function will process. One of the most useful types of window functions is Ranking Window Functions that are used to rank specific field values and categorize them according to the rank of each row, resulting in a single aggregated value for each participated row. There are four ranking window functions supported in SQL Server;  ROW_NUMBER(),   RANK() ,  DENSE_RANK()  and  NTILE() . All these functions are used to calculate ROWID for the provided rows window in ...
Post a Comment
Read more