If that is more important to you than performance you might prefer this answer, especially if your update is a one off to correct some data. So better than Robin Day's answer for this purpose. Thanks for sharing! Peter Mortensen This assumes none of the columns are nullable though.
You're right, I was typing the example by hand. I've added a third and fourth clause to the where statement to deal with that. Col1, T1. Col1, T2.
Col2 is more concise. Depends on if you want to replace nulls in the destination with nulls from the source. Frequently, I don't.
But if you do, Martin's construction of the where clause is the best thing to use. Show 1 more comment. Col2, T2. Stewart 3, 3 3 gold badges 25 25 silver badges 36 36 bronze badges.
Martin Smith Martin Smith k 81 81 gold badges silver badges bronze badges. Just an arbitrary alias in this case. Adrian Macneil Adrian Macneil Shiva Patrick Frenette Patrick Frenette 6 6 silver badges 2 2 bronze badges.
Ryan Ryan 2, 6 6 gold badges 33 33 silver badges 45 45 bronze badges. I feel this should be the accepted answer, because it keeps things simple and to the point. Simon Hughes 3, 3 3 gold badges 23 23 silver badges 44 44 bronze badges. Hentold Hentold 7 7 silver badges 11 11 bronze badges. What if we want to update Table2. BSMP 4, 8 8 gold badges 33 33 silver badges 43 43 bronze badges. Jason Clark Jason Clark 6 6 gold badges 17 17 silver badges 47 47 bronze badges. And if you wanted to join the table with itself which won't happen too often : update t1 -- just reference table alias here set t1.
Aleksandr Fedorenko Aleksandr Fedorenko Richard Richard 1, 10 10 silver badges 13 13 bronze badges. Consolidating all the different approaches here. Abdul Azeez Abdul Azeez 8 8 silver badges 18 18 bronze badges.
Yaman Yaman 16 16 silver badges 31 31 bronze badges. Bartosz X Bartosz X 2, 23 23 silver badges 32 32 bronze badges. Or even use table variable like tbl, "on PermTable. Have you tried? I am using a phone to reply this, no computer to try. After the execution of the update from a select query the output of the Persons table will be as shown below;. After the SET keyword, we specified the column names to be updated, and also, we matched them with the referenced table columns.
After the FROM clause, we retyped the table name, which will be updated. In addition to this, we can specify a WHERE clause and filter any columns of the referenced or updated table. We can also rewrite the query by using aliases for tables. Indexes are very helpful database objects to improve query performance in SQL Server.
Particularly, if we are working on the performance of the update query, we should take into account of this probability. The following execution plan illustrates an execution plan of the previous query. The only difference is that this query updated the 3.
This query was completed within 68 seconds. We added a non-clustered index on Persons table before to update and the added index involves the PersonCityName and PersonPostCode columns as the index key.
The following execution plan is demonstrating an execution plan of the same query, but this query was completed within seconds because of the added index, unlike the first one. We have seen this obvious performance difference between the same query because of index usage on the updated columns. As a result, if the updated columns are being used by the indexes, like this, for example, the query performance might be affected negatively. In particular, we should consider this problem if we will update a large number of rows.
To overcome this issue, we can disable or remove the index before executing the update query. On the other hand, a warning sign is seen on the Sort operator, and it indicates something does not go well for this operator. When we hover the mouse over this operator, we can see the warning details. During the execution of the query, the query optimizer calculates a required memory consumption for the query based on the estimated row numbers and row size.
However, this consumption estimation can be wrong for a variety of reasons, and if the query requires more memory than the estimation, it uses the tempdb data. This mechanism is called a tempdb spill and causes performance loss.
The reason for this: the memory always faster than the tempdb database because the tempdb database uses the disk resources. Now, if we go back to our position, the MERGE statement can be used as an alternative method for updating data in a table with those in another table. Discover why our customers rate Chartio 1.
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