Commerce,  Episerver,  Performance,  Uncategorized

Fixing ASP.NET Membership performance – part 1

Even though it is not the best identity management system in the .NET world, ASP.NET Membership provider is still fairly widely used, especially for systems that have been running for quite long time with a significant amount of users: migrating to a better system like AspNetIdentity does not comes cheap. However, built from early days of ASP.NET mean Membership provider has numerous significant limitations: beside the “architecture” problems, it also has limited performance. Depends on who you ask, the ultimate “maximum” number of customers that ASP.NET membership provider can handle ranges from 30.000 to 750.000. That does not sound great. Today if you start a new project, you should be probably better off with AspNetIdentity or some other solutions, but if your website is using ASP.NET membership provider and there is currently no plan to migrate, then read on.

The one I will be used for this blog post has around 950.000 registered users, and the site is doing great – but that was achieved by some very fine grained performance tuning, and a very high end Azure subscription.

A performance overview 

I have been using ASP.NET membership provider for years, but I have never looked into it from performance aspects. (Even though I have done some very nasty digging to their table structure). And now I have the chance, I realize how bad it is.

It’s a fairly common seen in the aspnet_* tables that the indexes have ApplicationId as the first column. It does not take a database master to know it is a very ineffective way to create an index – in most of the cases, you only have on ApplicationId in your website, making those indexes useless when you want to, for example, query by UserId. This is a rookie mistake – a newbie tends to make order of columns in the index as same as they appear in the table, thinking, that that SQL Server will just do magic to exchange the order for the best performance. It’s not how SQL Server – or in general – RDBMS systems work.

It is OK to be a newbie or to misunderstand some concepts. I had the very same misconception once, and learned my lessons. However, it should not be OK for a framework to make that mistake, and never correct it.

That is the beginning of much bigger problems. Because of the ineffective order of columns, the builtin indexes are as almost useless. That makes the queries, which should be very fast, become unnecessarily slow, wasting resources and increasing your site average response time. This is of course bad news. But good news is it’s in database level, so we can change it for the better. It if were in the application level then our chance of doing that is close to none.

Missing indexes

If you use Membership.GetUserNameByEmail on your website a lot, you might notice that it is … slow. It leads to this query:

Let’s just ignore the style for now (INNER JOIN would be a much more popular choice), and look into the what is actually done here. So it joins 3 tables by their keys. The join with aspnet_Applications would be fairly simple, because you usually have just one application. The join between aspnet_Users and aspnet_Membership is also simple, because both of them have index on UserId – clustered on aspnet_Users and non-clustered on aspnet_Membership

The last one is actually problematic. The clustered index on aspnet_Membership actually looks like this

Uh oh. Even if this contains LoweredEmail, it’s the worst possible kind of index. By using the least distinctive column in the first, it defeats the purpose of the index completely. Every request to get user name by email address will need to perform a full table scan (oops!)

This is a the last thing you want to see in a execution plan, especially with a fairly big table. 

It should have been just

which helps SQL Server to use the optimal execution plan

If you look into Azure SQL Database recommendation, it suggest you to create a non clustered index on LoweredEmail. That is not technically incorrect, and it still helps. However, keep in mind that each non clustered index will have to “duplicate” the clustered index, for the purpose of identify the rows, so keeping the useless clustered index actually increases wastes and slows down performance (even just a little, because you have to perform more reads to get the same data). However, if your database is currently performing badly, adding a non clustered index is a much quicker and safer option. The change to clustered index should be done with caution at low traffic time.

Tested the stored procedure on database above, without any additional index

With new non clustered index

With new clustered index:

Don’t we have a clear winner?

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