Set up access to network shares from SQL Server

Using a local service account for your SQL Server service, your server won’t automatically have permissions to access to other network resources like UNC paths. Most commonly, this is needed to be able to perform backups directly to a network share.

Using a domain account as your SQL Server service account will allow the server to access a network share on the same domain, but if the network share is not on your domain, like an Azure File Share, you need a different solution.

There’s a relatively easy way to make all of this work, though.

Continue reading

Optimizing a string split and search

We’re no strangers to doing things in T-SQL that would perhaps be more efficient in a procedural language. Love it or hate it, a T-SQL solution is easier in some situations, like my sp_ctrl3 procedure that I use as a drop-in replacement for the standard sp_help procedure to display object information in a way that simplifies copying and pasting.

One of the things that sp_ctrl3 does is plaintext database search. If you pass a string to the procedure that does not match an existing object, it’ll just perform a plaintext search of all SQL modules (procedure, views, triggers, etc) for that string. The search result includes line numbers for each result, so it needs to split each module into lines.

I’ve found that this takes a very long time to run in a database with large stored procedures, so here’s how I tuned it to run faster.

Continue reading

How to add “created” and “updated” timestamps without triggers

You have a table that you want to add “created” and “updated” timestamp columns to, but you can’t update the application code to update those columns. In the bad old times, you had to write a trigger to do the hard work for you. Triggers introduce additional complexity and potentially even a performance impact.

So here’s a nicer way to do it, trigger-free.

Continue reading

A “shock absorber” pattern for high-performance data ingestion

It’s almost like a myth – one that I’ve heard people talk about, but never actually seen myself. The “shock absorber” is a pretty clever data flow design pattern to ingest data where a regular ETL process would choke on the throughput or spikes. The idea is to use a buffer table to capture incoming data, and then run an asynchronous process that loads that data in batches from the buffer into its intended target table.

While I’ve seen whitepapers and blog posts mention the concept loosely along with claims of “7x or 10x performance”, none of them go into technical detail on how it’s done, so I decided to try my hand at it.

I’ve compiled my findings, along with some pre-baked framework code if you want to try building something yourself. Professional driver on closed roads. It’s gonna get pretty technical.

Continue reading

How MERGE on two different rows can still deadlock you

I recently ran into a curious deadlock issue. I have a process that performs a lot of updates in a “state” table using multiple, concurrent connections. The business logic in the application guarantees that two connections won’t try to update the same item, so we shouldn’t ever run into any locking issues. And yet, we keep getting deadlocks.

What’s going on here? Hint: it has to do with isolation levels and range locks.

Continue reading

Is a sort faster when the data is already sorted?

Whenever SQL Server needs to sort a data stream, it will use the Sort operator to reorder the rows of the stream. Sorting data is an expensive operation because it entails loading part or all of the data into memory and shifting that data back and forth a couple of times. The only time SQL Server doesn’t sort the data is when it already knows the data to be ordered correctly, like when it has already passed a Sort operator or it’s reading from an appropriately sorted index.

But what happens if the data is ordered correctly, but SQL Server doesn’t know about it? Let’s find out.

Continue reading

How to run your CTE just once, and re-use the output

You may already know that common table expressions, like views, don’t behave like regular tables. They’re a way to make your query more readable by allowing you to write a complex SQL expression just once, rather than repeating it all over your statement or view. This makes reading, understanding and future refactoring of your code a little less painful.

But they’re no magic bullet, and you may end up with some unexpected execution plans.

Continue reading