[Note from Pinal]: This is a 49th episode of Notes from the Field series. Every day I get few emails where I am asked how to tune queries so the entire server run faster. I always end up writing long answer this question. The reason is simple – query tuning is indeed the need of hours, but it is not everything. There are many more things one should do along with tuning queries. I asked the same question to Brian Moran, who is every day dealing with consultants and various organizations who are facing issues with SQL Server.
In this episode of the Notes from the Field series database expert Brian Moran explains a how Query Tuning is sometimes a waste of time when we are facing issues with performance and scalability. Read the experience of Brian in his own words.
Tuning queries is sometimes a waste of time when you’re trying to fix performance and scalability problems. That sounds crazy but it’s true. Designing an efficient workload is almost always more important than maintaining a laser focus on query tuning and other technical tricks of the DBA trade.
Here’s an example that helps to explain what I mean.
What’s the shortest distance between two points? A straight line, of course. Everyone knows that. Imagine that you need to calculate the most efficient path from Washington DC to New York. Imagine those cities on a traditional 3D globe. The straight line is simple to figure out, right? Just head north as the crow flies.
But what if you wander about and take a curvy path as you head north? DC to New York is about 204 miles as the crow flies, but Google says the distance is 226 miles if you take I95 and the New Jersey Turnpike. Google also presents some reasonable travel options that are as far 264 miles. It’s easy to imagine you could increase the distance even more by taking scenic roads and side trips along the way. Of course, you can also draw a straight line on a globe between DC and New York that heads in a southerly direction, which is over 24,000 miles. That’s over 100 times more expensive that the straight route northwards.
Now, let me map that mapping example back to database performance tuning. Sometimes database performance tuning is an exercise in making the workload more efficient, just as you might want to make your route to New York more efficient. To make the database workload more efficient, you can tune queries, add indexes, and do all sorts of other neat tricks. Query tuning is like an exercise in flattening the northerly path from DC to New York to make as straight a line as possible. You want to tune your queries so that they’re as direct as possible and don’t veer off into unnecessary detours.
But, what if you’re talking about trying to flatten a squiggly line from DC to New York that starts out by heading south 180 degrees, the wrong way? You can make that line as straight and as efficient as you want. But heading south from DC to get to New York is never going to be efficient no matter how straight of a line you draw. A route that goes the wrong way can be optimized, but it’s still going the wrong way.
The same idea applies to queries. If you start out tuning an inefficient workload, you’ll end up with an inefficient workload that is tuned, but it is still inefficient.
This seems like a silly example. Everyone intuitively knows that the southerly route is inherently a poor choice. You can tune the route as much as you want, but in best case scenarios it’s still going to be over 100X worse than going north.
Oddly enough, 25 years of database consulting tells me many DBAs will spend most of their time tuning queries that are the database equivalent of trying to make that southerly line from DC to New York as straight as possible. They’ll spend days, weeks, or months, trying to shave that last 10%.
All too often, DBAs fail to take a moment to pause, understand the nature of the problem they are trying to solve, and try to envision a more efficient way to solve the problem. These DBAs don’t recognize that changing the workload can be vastly better than tuning the workload.
Two Classic Examples
Here are a two classic examples that most DBAs intuitively understand. Say you have a business need defined in a way that requires drop-down list box that will be populated with 100,000 rows that users will have to scroll through. You can try to tune the process to make it more efficient at loading 100,000 rows every time the screen is touched. But that tuning does not change the workload.
Rather than simply tuning the existing workload, a better investment in time would be if you helped the designers of that screen understand and accept a solution that doesn’t require loading 100,000 rows. Or perhaps you have a system that makes heavy use of database cursors in a procedural manner of some kind. Most DBA’s know that architecting with a set-based solution will almost always be better than trying to make the cursor-based approach as fast as possible.
Here’s a 15-year-old example that’s still a common design pattern mistake made today. I was working on an office supply site when e-commerce was first becoming big business. The application was built in a very object-oriented manner. Developers love object-oriented approaches, but databases aren’t always as fond of the approach. In this case this object-oriented design pattern led to 1000 and sometimes 2000 or more round trips to SQL Server when a single user searched for office chairs, and the search brought back just one screen of results.
This was a problem because the system needed to support hundreds or thousands of concurrent users. The existing workload might therefore need to handle hundreds of thousands or millions of batch requests per second. The client wanted to do this on a single SQL Server instance since that’s all their budget could afford.
I could have spent an infinite amount of time tuning the queries used in this approach, but the workload was never going to be efficient. I was never going to be able to handle hundreds of thousands of batch requests per second on a single instance of SQL Server 2000. Instead, I made some changes to the architecture. In other words, I changed the workload, and I was able to achieve the performance goals I had.
The examples I used here are pretty basic, and most DBA’s today are aware of how to deal with such situations. But I’m willing to bet that many people reading this post are struggling with a performance problem where tuning the queries is a poor use of time as compared to completely changing the essence of the workload. It’s too easy to lose sight of the forest for the trees.
Having a hard time figuring out how to tune your queries to achieve performance goals? Maybe you should take a step back and focus on changes you can make to the workload instead?
If you want to get started with performance tuning and database security with the help of experts, read more over at Fix Your SQL Server.
Reference: Pinal Dave (https://blog.sqlauthority.com)