XML documents are, by design, at best like an entire relational database, stored in a single column. Worst-case, they don’t even come with a schema. Small wonder then, that XML queries take a good deal of CPU and I/O performance to complete. The solution to this problem is to index them, pretty much like you would index regular tables.
performance
Table value functions vs Inline functions
You may not know that there are two different ways of writing user-defined functions that return a recordset: Table value functions and Inline functions, and they both come with a number of benefits and limitations with regard to performance and programmability.
Typed XML data
Did you know that you can define an XML schema for every XML column or variable that you want? Defining XML schemas is not only good practice, because it validates the data as soon as you store it in the column or variable, but it also improves XML query performance.
A prime number challenge.
I stumbled upon a challenge on a blog i follow, to find prime numbers using T-SQL. With a little bit of Wikipedia research, I’ve built a T-SQL version of the “sieve of Eratosthenes“.
How to create, find and eliminate deadlocks
Deadlocks are typically encountered in high-load scenarios or in complex concurrent transactions. And the worst part is, you probably won’t see them until you’re live in production. Luckily, finding and solving deadlock issues isn’t as complicated as it may sound. All it takes is a bit of logging and patience, along with some basic know-how of how locking mechanisms work in SQL Server.
JOIN types and performance
There are basically three main types of joins in SQL Server, each one of which has its own characteristics, advantages and drawbacks. You’ll find these three operators in query plans. Knowing how different types joins work will help you optimize your queries, indexing and how to store your data.
Working with covering indexes
As you could read in the indexing basics article, a well-defined index can boost query performance, but there are a few more basic tricks that can have a great impact on how your query is executed. One of the most important is a technique called covering indexes. A covering index is basically a non-clustered index that covers all the columns you need in a query, not just the keys.
Indexing basics
Understanding indexes in SQL Server can help you build much more efficient database solutions. Often, performance problems can be adressed with indexes, so knowing how indexes work and how to set them up for the best performance are a great asset in your optimization work.
Reading a query plan
Knowing how to read a query plan is absolutely key to optimizing SQL Server query performance. The query plan tells you how SQL Server goes about running your query, including what indexes are used (and how), what join strategies are applied and a lot of other information. If you can read the query plan, you can make the appropriate changes to indexes, query hints, join conditions, etc to tune your workload for optimum performance.
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