Your shopping cart is empty!
Tip 1—Return Multiple Resultsets
Review your database code to see if you have request paths that go to the database more than once. Each of those round-trips decreases the number of requests per second your application can serve. By returning multiple resultsets in a single database request, you can cut the total time spent communicating with the database. You'll be making your system more scalable, too, as you'll cut down on the work the database server is doing managing requests.
While you can return multiple resultsets using dynamic SQL, I prefer to use stored procedures. It's arguable whether business logic should reside in a stored procedure, but I think that if logic in a stored procedure can constrain the data returned (reduce the size of the dataset, time spent on the network, and not having to filter the data in the logic tier), it's a good thing.
Using a SqlCommand instance and its ExecuteReader method to populate strongly typed business classes, you can move the resultset pointer forward by calling NextResult.
Tip 2—Paged Data Access
The ASP.NET DataGrid exposes a wonderful capability: data paging support. When paging is enabled in the DataGrid, a fixed number of records is shown at a time. Additionally, paging UI is also shown at the bottom of the DataGrid for navigating through the records. The paging UI allows you to navigate backwards and forwards through displayed data, displaying a fixed number of records at a time.
There's one slight wrinkle. Paging with the DataGrid requires all of the data to be bound to the grid. For example, your data layer will need to return all of the data and then the DataGrid will filter all the displayed records based on the current page. If 100,000 records are returned when you're paging through the DataGrid, 99,975 records would be discarded on each request (assuming a page size of 25). As the number of records grows, the performance of the application will suffer as more and more data must be sent on each request.
Tip 3—Connection Pooling
Setting up the TCP connection between your Web application and SQL Server™ can be an expensive operation. Developers at Microsoft have been able to take advantage of connection pooling for some time now, allowing them to reuse connections to the database. Rather than setting up a new TCP connection on each request, a new connection is set up only when one is not available in the connection pool. When the connection is closed, it is returned to the pool where it remains connected to the database, as opposed to completely tearing down that TCP connection.
Of course you need to watch out for leaking connections. Always close your connections when you're finished with them. I repeat: no matter what anyone says about garbage collection within the Microsoft® .NET Framework, always call Close or Dispose explicitly on your connection when you are finished with it. Do not trust the common language runtime (CLR) to clean up and close your connection for you at a predetermined time. The CLR will eventually destroy the class and force the connection closed, but you have no guarantee when the garbage collection on the object will actually happen.
To use connection pooling optimally, there are a couple of rules to live by. First, open the connection, do the work, and then close the connection. It's okay to open and close the connection multiple times on each request if you have to (optimally you apply Tip 1) rather than keeping the connection open and passing it around through different methods. Second, use the same connection string (and the same thread identity if you're using integrated authentication). If you don't use the same connection string, for example customizing the connection string based on the logged-in user, you won't get the same optimization value provided by connection pooling. And if you use integrated authentication while impersonating a large set of users, your pooling will also be much less effective. The .NET CLR data performance counters can be very useful when attempting to track down any performance issues that are related to connection pooling.
Whenever your application is connecting to a resource, such as a database, running in another process, you should optimize by focusing on the time spent connecting to the resource, the time spent sending or retrieving data, and the number of round-trips. Optimizing any kind of process hop in your application is the first place to start to achieve better performance.
The application tier contains the logic that connects to your data layer and transforms data into meaningful class instances and business processes. For example, in Community Server, this is where you populate a Forums or Threads collection, and apply business rules such as permissions; most importantly it is where the Caching logic is performed.
Tip 4—ASP.NET Cache API
One of the very first things you should do before writing a line of application code is architect the application tier to maximize and exploit the ASP.NET Cache feature.
If your components are running within an ASP.NET application, you simply need to include a reference to System.Web.dll in your application project. When you need access to the Cache, use the HttpRuntime.Cache property (the same object is also accessible through Page.Cache and HttpContext.Cache).
There are several rules for caching data. First, if data can be used more than once it's a good candidate for caching. Second, if data is general rather than specific to a given request or user, it's a great candidate for the cache. If the data is user- or request-specific, but is long lived, it can still be cached, but may not be used as frequently. Third, an often overlooked rule is that sometimes you can cache too much. Generally on an x86 machine, you want to run a process with no higher than 800MB of private bytes in order to reduce the chance of an out-of-memory error. Therefore, caching should be bounded. In other words, you may be able to reuse a result of a computation, but if that computation takes 10 parameters, you might attempt to cache on 10 permutations, which will likely get you into trouble. One of the most common support calls for ASP.NET is out-of-memory errors caused by overcaching, especially of large datasets.Common Performance Myths
One of the most common myths is that C# code is faster than Visual Basic code. There is a grain of truth in this, as it is possible to take several performance-hindering actions in Visual Basic that are not possible to accomplish in C#, such as not explicitly declaring types. But if good programming practices are followed, there is no reason why Visual Basic and C# code cannot execute with nearly identical performance. To put it more succinctly, similar code produces similar results.
Another myth is that codebehind is faster than inline, which is absolutely false. It doesn't matter where your code for your ASP.NET application lives, whether in a codebehind file or inline with the ASP.NET page. Sometimes I prefer to use inline code as changes don't incur the same update costs as codebehind. For example, with codebehind you have to update the entire codebehind DLL, which can be a scary proposition.
Tip 5—Per-Request Caching
Earlier in the article, I mentioned that small improvements to frequently traversed code paths can lead to big, overall performance gains. One of my absolute favorites of these is something I've termed per-request caching.
Whereas the Cache API is designed to cache data for a long period or until some condition is met, per-request caching simply means caching the data for the duration of the request. A particular code path is accessed frequently on each request but the data only needs to be fetched, applied, modified, or updated once. This sounds fairly theoretical, so let's consider a concrete example.
In the Forums application of Community Server, each server control used on a page requires personalization data to determine which skin to use, the style sheet to use, as well as other personalization data. Some of this data can be cached for a long period of time, but some data, such as the skin to use for the controls, is fetched once on each request and reused multiple times during the execution of the request.
To accomplish per-request caching, use the ASP.NET HttpContext. An instance of HttpContext is created with every request and is accessible anywhere during that request from the HttpContext.Current property. The HttpContext class has a special Items collection property; objects and data added to this Items collection are cached only for the duration of the request. Just as you can use the Cache to store frequently accessed data, you can use HttpContext.Items to store data that you'll use only on a per-request basis. The logic behind this is simple: data is added to the HttpContext.Items collection when it doesn't exist, and on subsequent lookups the data found in HttpContext.Items is simply returned.
Tip 6—Background Processing
The path through your code should be as fast as possible, right? There may be times when you find yourself performing expensive tasks on each request or once every n requests. Sending out e-mails or parsing and validation of incoming data are just a few examples.
When tearing apart ASP.NET Forums 1.0 and rebuilding what became Community Server, we found that the code path for adding a new post was pretty slow. Each time a post was added, the application first needed to ensure that there were no duplicate posts, then it had to parse the post using a "badword" filter, parse the post for emoticons, tokenize and index the post, add the post to the moderation queue when required, validate attachments, and finally, once posted, send e-mail notifications out to any subscribers. Clearly, that's a lot of work.
It turns out that most of the time was spent in the indexing logic and sending e-mails. Indexing a post was a time-consuming operation, and it turned out that the built-in System.Web.Mail functionality would connect to an SMTP server and send the e-mails serially. As the number of subscribers to a particular post or topic area increased, it would take longer and longer to perform the AddPost function.
Indexing e-mail didn't need to happen on each request. Ideally, we wanted to batch this work together and index 25 posts at a time or send all the e-mails every five minutes. We decided to use the same code I had used to prototype database cache invalidation for what eventually got baked into Visual Studio® 2005.
The Timer class, found in the System.Threading namespace, is a wonderfully useful, but less well-known class in the .NET Framework, at least for Web developers. Once created, the Timer will invoke the specified callback on a thread from the ThreadPool at a configurable interval. This means you can set up code to execute without an incoming request to your ASP.NET application, an ideal situation for background processing. You can do work such as indexing or sending e-mail in this background process too.