Batch update sql server

So for alphanumeric or GUID keys, this approach won't work, but you can implement some other type of custom batch processing with some additional coding. So, with the batch size and the key control variable, we validate the rows in the table are within the range. Important Note: Your process will need to always operate on at least some rows in each batch. If a batch does not operate on any rows, the process will end as row count will be 0.

Another approach for these cases is to use a temporary table to filter the rows to be processed and then use this temp table in the loop to control the process. Note, I enabled statistics IO and cleared the data cache first so we have better results for comparison.

If we multiply it for 60 batches performed it should be around 65, logical reads approximately the same as before, this makes sense since is the same data we are accessing. But if we look at the overall execution time, it improves by around 10 seconds, with the same number of rows:. We will do an UPDATE on a varchar field with random data so our test is more real , after clearing the cache, we will execute the code.

Checking the log size again, we can see it grew to 1. I also shrunk the transaction log to its original size and perform a cache cleanup before executing. As we can see there was an improvement with the log spaced used. This time the log grew to 0.

The last thing to verify is the number of rows affected. As you can see, for very large DML processes, running in smaller batches can help on execution time and transaction log use.

The only drawback of this method is that your key must be a sequential number and there must ne at least one row in each batch, so the process does not end before being applied to all data. For example MyTestTable does not contain any records with ID 1 - , but the ID starts from , there will be no updates performed. There are several ways to obtain the row count for a table, you can check this article that explains them very well:. Informative article.

Could you have performed a count on the number of records in the table and then used a partitioning variable to determine your block sizes or does the math get messy? I will work on another tip to show you an example of those cases even if the table does not have primary key defined. Table 'MyTestTable'. Scan count 1, logical reads , physical reads 2, read-ahead reads , lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. I am also considering performance aspects.

You can update from the temporary table and then delete or invalidate rows in that table. Something like this:. Do this. This will delete records every milliseconds. But the good thing what I do here, is that I release the transaction, and allow another transaction to complete. Because there could be another CRUD statement. It does take longer. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams?

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