In May of 2009 I discovered some significant performance problems that I blogged about.  In summary, I had tracked it down to the issue of LINQ2SQ having to create a full expression tree on every instantiation of a LINQ2SQL query.  I’m not a compiler write kind of guy but do respect the complexity of that and doing things like building expression trees, but still this really sucked.  Using the compile syntax in LINQ2SQL is very awkward, and IMHO takes all the fun out of using LINQ2SQL.  If you don’t remember my post, here is the graph showing the evil happening.

So, what is a Microsoft MVP to do?  I complained to everyone at Microsoft I knew.  I made this my mission for about a year.  I was told time after time that the problem was hugely complicated and no one was working on making it any faster.  I just could not believe it because I felt this was such a barrier to success to LINQ2SQL type technology (now Entity Framework really) that Microsoft just could not ignore my findings.  I was actually surprised that I was the only one screaming about this.

Well, quietly, Microsoft has announced that in .Net Framework 4.5, Entity Framework will include “Auto-Compiled LINQ Queries”.  This is awesome!   When it comes out, I’ll be testing and it giving feedback.

For now, I’m a very happy camper.

Well, my fears are put aside.  Though LINQ is somewhat slower, for 100,000 iterations, .052 seconds is pretty good.  (compared with processing a single not to complicated LINQ2SQL statement for 100,000 iterations would take about 20,000 seconds or 333 hours.  Quite a difference to .052 seconds!

Here is the code I ran for my test.  Hope this help!

using System;

using System.Collections.Generic;

using System.Diagnostics;

using System.Linq;

using System.Text;

namespace LINQTimingInMemory

{

     class Program

     {

         static void Main(string[] args)

         {

             for (int i=0;i<2;i++)

             {

                 List<int> myList = new List<int>() {1,2,3,4,5,6,7,8,9,6,5,5,5,5,5,5};

                 Stopwatch stopWatch = new Stopwatch();

                 stopWatch.Start();

                 int iterations = 100000;

                 for (int t = 0; t < iterations; t++)

                 {

                     if (i == 0)

                     {

                         var ids = myList.Where(a => a > 5).ToList();

                     }

                     else

                     {

                         var ids = new List<int>();

                         foreach (var v in myList)

                         {

                             if (v > 5)

                             {

                                 ids.Add(v);

                             }

                         }

                     }

                 }

                 stopWatch.Stop();

                 int ti = Convert.ToInt32(stopWatch.ElapsedMilliseconds);

                 Console.WriteLine("time for " + i.ToString() + " " + ti/iterations + " " + ti);

                 stopWatch.Reset();

             }

         }

     }

 }

And the Power Point Presentation:

Any Questions, feel free to contact me at http://peterkellner.net/contact/

June Meeting – Wednesday, June 25, 2008

Remember Our New Location:  835 Market Street, Suite 700.

Building High performance ASP.NET web applications – In this meeting, Peter Kellner will present on and discuss techniques and methodologies for developing highly performant and scalable web sites.

Topics will  include appropriate use of Cache and Session State, as well as how and when to use them.  Viewstate management and methods to minimize its use will be discussed.  Code to pop up a warning when a threshold is met in development will be shown.  When and how to take advantage of Server Farms will be discussed, as well as trouble shooting techniques to find problems. The evils of Server Affinity,  as well as a common pattern for caching database queries will be shown to be wrong.  Time permitting, we will talk about using Microsoft’s Ajax.asp.net with UpdatePanel and webservices and how these affect performance and scalability.