Sql server updating large databases

In the case of Postgre SQL, it can be done using a FROM clause with UPDATE, like this: This does an INNER JOIN between the tables “staff” and “updates” where the column “name” matches.

The SET clause then takes the “salary” field from the “updates” table and uses it to update the “salary” field of the “staff” table.

Now the query will run using the old statistics which is probably OK in this case as they were ok 2 seconds earlier so if they are used for a few more seconds it probably isn’t all that big of a deal.

Now I don’t recommend turning this setting on for every database on the server.

So, given a list of updates to apply we could effect them using the following steps: So in the example above we can reduce five statements to four. But now the number of statements is no longer directly dependent on the number of rows requiring updates.

This feature is only available by turning on trace flag 2371 so it won’t be turned on by default for you.Let us start with a simple table: UPDATE staff SET salary = 1200 WHERE name = ' Bob'; UPDATE staff SET salary = 1200 WHERE name = ' Jane'; UPDATE staff SET salary = 1200 WHERE name = ' Frank'; UPDATE staff SET salary = 1200 WHERE name = ' Susan'; UPDATE staff SET salary = 1200 WHERE name = ' John'; UPDATE staff SET salary = 1200 WHERE name = ' Bob'; UPDATE staff SET salary = 1250 WHERE name = ' Jane'; UPDATE staff SET salary = 1200 WHERE name = ' Frank'; UPDATE staff SET salary = 1250 WHERE name = ' Susan'; UPDATE staff SET salary = 1200 WHERE name = ' John'; We are no longer setting all the salary fields to the same value, so we can’t collapse it into a single statement.But we can group the updates according to the value being set, and then do one UPDATE statement per distinct value.A requirement arises in many systems to update multiple SQL database rows.For small numbers of rows requiring updates, it can be adequate to use an UPDATE statement for each row that requires an update.

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