To illustrate, consider the following example source and target tables and data. Target(Employee ID int, Employee Name varchar(10), CONSTRAINT Target_PK PRIMARY KEY(Employee ID)); CREATE TABLE dbo.
Source(Employee ID int, Employee Name varchar(10), CONSTRAINT Source_PK PRIMARY KEY(Employee ID)); GO INSERT dbo.
Target(Employee ID, Employee Name) VALUES(100, 'Mary'); INSERT dbo.
Target(Employee ID, Employee Name) VALUES(101, 'Sara'); INSERT dbo.
Rows in the source are matched with rows in the target based on the join predicate specified in the ON clause. One insert, update, or delete operation is performed per input row.
Depending on the WHEN clauses specified in the statement, the input row might be any one of the following: The combination of WHEN clauses specified in the MERGE statement determines the join type that is implemented by the query processor and affects the resulting input stream.
TABLESAMPLE() is good from a performance standpoint, but you will get clumping of results (all rows on a page will be returned).
Two examples of how to use the DELETE FROM statement are shown below. Table Store_Information In Example 1, the criteria we use to determine which rows to delete is quite simple. Below is an example where we use a subquery as the condition.
I've thought of a complicated way, creating a temp table with a "random number" column, copying my table into that, looping through the temp table and updating each row with It's always good to keep in mind that newid() isn't a really good pseudorandom number generator, at least not nearly as good as rand().
But if you just need some vaguely randomish samples and don't care about mathematical qualities and such, it'll be good enough.
If the table has too many indices, it is better to disable them during update and enable it again after update3.
Instead of updating the table in single shot, break it into groups as shown in the above example.