T-SQL – Page 2 – sqlsunday.com

T-SQL template parser

Just for the heck of it, I scratched together a template parser for T-SQL . The usage of this function is similar to the STRING_SPLIT() function, except instead of splitting a string by a delimiter character, we want to split a string according to a defined template.

SELECT *
FROM dbo.Template_Split(
    'Wingtip Toys (Bethel Acres, OK)',
    '% (%, %)'
);

… will generate the following output:

Notice how the “%” wildcard character denotes how the string is split. Unlike the fancy stuff you can do with regular expressions, T-SQL wildcards don’t allow you to define capture groups, so this function is unfortunately constrained to just using “%”. I hope it will still come in handy to someone out there.

That’s it, that’s the post. Enjoy!

STRING_SPLIT(), but for quoted names

Can you apply gaps and islands logic on a string? Sure you can.

About wildcards and data type precedence

Implicit conversions in SQL Server follow a specific, predictable order, called data type precedence. This means that if you compare or add/concatenate two values, a and b, with different data types, you can predict which one will be implicitly converted to the data type of the other one in order to be able to complete the operation.

I stumbled on an interesting exception to this rule the other day.

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.

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.

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.

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.

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.

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.