Connect and share knowledge within a single location that is structured and easy to search. Now, what I want is to update the age column for certain IDs, so that the end result will be as follows.
This is just a sample table. In real case, it's a table with over data, so that it consumes a lot of time to update the rows individually. I found a solution, but I can't add it as an answer. So I decided to edit my own question and put the answer. Please refer the below url for more info:. If they gave you the list of ID to update and the age, you can easily generate the inner select union in excel with a formula and place it there.
Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. Asked 7 years, 1 month ago. Active 7 years, 1 month ago. Viewed 7k times. Improve this question. Sahan De Silva. No loops or cursors or other RBAR row-by-agonizing-row processing needed!
Add id, name, country. ConnectionStrings "constr". Using con As New SqlConnection constr. AddWithValue " tblCustomers" , dt. End Using. The following screenshot displays the Customers table containing the updated as well as the inserted records. Related Articles. Add Comments. Thank you for the feedback. The comment is now awaiting moderation.
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I agree to the above terms. Download Required. I am going to update the CustTransaction table with one command. This took around 5 minutes. A bulk update is an expensive operation in terms of query cost, because it takes more resources for the single update operation. It also takes time for the update to be logged in the transaction log. Also, long running updates can cause blocking issues for other processes. Another approach is to update the data in smaller batches.
So instead of doing row by row updates or one big update, I have divided the data into batches of 10K rows and performed the update operation as shown below. This completed in less than 2 minutes, which is much faster than the other two approaches. In addition, the transaction size is minimized and also the data logged and resources used are minimized.
I prefer to update data in batches for large volumes of data. You can set your own batch size after analyzing your data and environment to see what makes the most sense. Another option for batching updates is to use the top statement for configuring the batch size. What was the recovery model set to? I'm thinking full recovery vs simple recovery might make a big difference in performance.
I'm not certain why your 'bulk' update performed so slowly.
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