Ayende @ Rahien

It's a girl

Goodbye, 2012: Our end of year discount starts now!

Well, as the year draws to a close, it is that time again, I got older, apparently. Yesterday marked my 31th trip around the sun.

To celebrate, I decided to give the first 31 people a 31% discount for all of our products.

This offer applies to:

This also applies to our support & consulting services.

All you have to do is to use the following coupon code: goodbye-2012

Enjoy the end of the year, and happy holidays.

Production Cloud Profiling With Uber Prof

With Uber Prof 2.0 (NHibernate Profiler, Entity Framework Profiler, Linq to SQL Profiler, LLBLGen Profiler) we are going to bring you a new era of goodness.

In 1.0, we gave you a LOT of goodness for the development stage of building your application, but now we are able to take it a few steps further. Uber Prof 2.0 supports production profiling, which means that you can run it in production and see what is going on in your application now!

To make things even more interesting, we have also done a lot of work to make sure that this works on the cloud as well. For example, go ahead and look at this site: http://efprof.cloudapp.net/

This is a live application, that doesn’t really do anything special, I’ll admit. But the kicker is when you go to this URL: http://efprof.cloudapp.net/profiler/profiler.html


This is EF Prof, running on the cloud, and giving you the results that you want, live. You can read all about this feature and how to enable it here, but I am sure that you can see the implications.

Uber Prof V2.0 is now in Public Beta

Well, we worked quite a bit on that, but the Uber Prof (NHibernate Profiler, Entity Framework Profiler, Linq to SQL Profiler, etc) version 2.0 are now out for public beta.

We made a lot of improvements. Including performance, stability and responsiveness, but probably the most important thing from the user perspective is that we now support running the profiler in production, and even on the cloud.

We will have the full listing of all the new goodies up on the company site soon, including detailed instructions on how to enable production profiling and on cloud profiling, but I just couldn’t wait to break the news to you.

In fact, along with V2.0 of the profilers, we have a brand new site for our company, which you can check here: http://hibernatingrhinos.com/.

To celebrate the fact that we are going on beta, we also offer a 20% discount for the duration of the beta.

Nitpicker corner, please remember that this is a beta, there are bound to be problems, and we will fix them as soon as we can.

What is next for the profilers?

We have been working on the profilers (NHibernate Profiler, Entity Framework Profiler, Linq to SQL Profiler, LLBLGen Profiler and Hibernate Profiler) for close to three years now. And we have been running always as 1.x, so we didn’t have a major release (although we have continual releases, we currently have close to 900 drops of the 1.x version).

The question now becomes, what is going to happen in the next version of the profiler?

  • Production Profiling, the ability to setup your application so that you can connect to your production application and see what is going on right now.
  • Error Analysis, the ability to provide you with additional insight and common solution to recurring problems.
  • Global Query Analysis, the ability to take all of your queries, look at their query plans and show your potential issues.

Those are the big ones, we have a few others, and a surprise in store Smile

What would you want to see in the next version of the profiler?

New Profiler Feature: Avoid Writes from Multiple Sessions In The Same Request

Because I keep getting asked, this feature is available for the following profilers:

This new feature detects a very interesting bad practice, write to the database from multiple session in the same web request.

For example, consider the following code:

public void SaveAccount(Account account)
    using(var session = sessionFactory.OpenSession())
public Account GetAccount(int id)
    using(var session = sessionFactory.OpenSession())
        return session.Get<Account>(id);

It is bad for several reasons, micro managing the session is just one of them, but the worst part is yet to come…

public void MakePayment(int fromAccount, int toAccount, decimal ammount)
    var from = Dao.GetAccount(fromAccount);
    var to = Dao.GetAccount(toAccount);
    from.Total -= amount;
    to.Total += amount;

Do you see the error here? There are actually several, let me count them:

  • We are using 4 different connections to the database in a single method.
  • We don’t have transactional safety!!!!

Think about it, if the server crashed between the fifth and sixth lines of this method, where would we be?

We would be in that wonderful land where money disappear into thin air and we stare at that lovely lawsuit folder and then jump from a high window to a stormy sea.

Or, of course, you could use the profiler, which will tell you that you are doing something which should be avoided:


Isn’t that better than swimming with the sharks?

New Uber Prof Feature: Too Many Database Calls In The Same Request

Recently, we added a way to track alerts across all the sessions the request. This alert will detect whenever you are making too many database calls in the same request.

But wait, don’t we already have that?

Yes, we do, but that was limited to the scope of one session. there is a very large set of codebases where the usage of OR/Ms is… suboptimal (in other words, they could take the most advantage of the profiler abilities to detect issues and suggest solutions to them), but because of the way they are structured, they weren’t previously detected.

What is the difference between a session and a request?

Note: I am using NHibernate terms here, but naturally this feature is shared among all profiler:

A session is the NHibernate session (or the data/object context in linq to sql / entity framework), and the request is the HTTP request or the WCF operation. If you had code such as the following:

public T GetEntity<T>(int id)
    using (var session = sessionFactory.OpenSession())
         return session.Get<T>(id);

This code is bad, it micro manages the session, it uses too many connections to the database, it … well, you get the point. The problem is that code that uses this code:

public IEnumerable<Friends> GetFriends(int[] friends)
   var results = new List<Friends>();
   foreach(var id in friends)

   return results;

The code above would look like the following in the profiler:


As you can see, each call is in a separate session, and previously, we wouldn’t have been able to detect that you have too many calls (because each call is a separate session).

Now, however, we will alert the user with a too many database calls in the same request alerts.


New Uber Prof Concept: Cross Session Alerts

We have recently been doing some work on Uber Prof, mostly in the sense of a code review, and I wanted to demonstrate how easy it was to add a new feature. The problem is that we couldn’t really think of a nice feature to add that we didn’t already have.

Then we started thinking about features that aren’t there and that there wasn’t anything in Uber Prof to enable, and we reached the conclusion that one limitation we have right now is the inability to analyze your application’s behavior beyond the session’s level. But there is actually a whole set of bad practices that are there when you are using multiple sessions.

That led to the creation of a new concept the Cross Session Alert, unlike the alerts we had so far, those alerts looks at the data stream with a much broader scope, and they can analyze and detect issues that we previously couldn’t detect.

I am going to be posting extensively on some of the new features in just a bit, but in the meantime, why don’t you tell me what sort of features do you think this new concept is enabling.

And just a reminder, my architecture is based around Concepts & Features.

Uber Prof New Features: A better query plan

Originally posted at 1/7/2011

Because I keep getting asked, this feature is available for the following profilers:

This feature is actually two separate ones. The first is the profiler detecting what is the most expensive part of the query plan and making it instantly visible. As you can see, in this fairly complex query, it is this select statement that is the hot spot.


Another interesting feature that only crops up whenever we are dealing with complex query plans is that the query plan can get big. And by that I mean really big. Too big for a single screen.

Therefore, we added zooming capabilities as well as the mini map that you see in the top right corner.

Uber Prof New Features: Go To Session from alert

Originally posted at 1/7/2011

This is another oft requested feature that we just implemented. The new feature is available for the full suite of Uber Profilers:

You can see the new feature below:


I think it is cute, and was surprisingly easy to do.

Uber Prof have recently passed the stage where it is mostly implemented using itself, so I just had to wire a few things together, and then I spent most of the time just making sure that things aligned correctly on the UI.

What is Uber Prof’s competitive advantage?

Originally posted at 11/25/2010

In a recent post, I discussed the notion of competitive advantage and how you should play around them. In this post, I am going to focus on Uber Prof. Just to clarify, when I am talking about Uber Prof, I am talking about NHibernate Profiler, Entity Framework Profiler, Linq to SQL Profiler, Hibernate Profiler and LLBLGen Profiler. Uber Prof is just a handle for me to use to talk about each of those.

So, what is the major competitive advantage that I see in the Uber Prof line of products?

Put very simply, they focus very heavily on the developer’s point of view.

Other profilers will give you the SQL that is being executed, but Uber Prof will show you the SQL and:

  • Format that SQL in a way that make it easy to read.
  • Group the SQL statements into sessions. Which let the developer look at what is going on in the natural boundary.
  • Associate each query with the exact line of code that executed it.
  • Provide the developer with guidance about improving their code.

There are other stuff, of course, but those are the core features that make Uber Prof into what it is.

Profiler new features: Data binding alerts

The following features apply to NHProf, EFProf, L2SProf.

In general, it is strong discouraged to data bind directly to an IQueryable. Mostly, that is because data binding may actually iterate over the IQueryable several times, resulting in multiple queries being generated from something that can be done purely in memory. Worse, it is actually pretty common for data binding to result in lazy loading, and lazy loading from data binding almost always result in SELECT N+1. The profiler can now detect and warn you about such mistakes preemptively. More than that, the profiler can also now detect queries that are being generated from the views in an ASP.Net MVC application, another bad practice that I don’t like.

You can find more information about each warnings here:

WPF detection:




WinForms detections:



Web applications:



Profiler new features, Sept Edition

The following features apply to NHProf, EFProf, HProf, L2SProf.

The first feature is something that was frequently requested, but we kept deferring. Not because it was hard, but because it was tedious and we had cooler features to implement: Sorting.


Yep. Plain old sorting for all the grids in the application.

Not an exciting feature, I’ll admit, but an important one.

The feature that gets me exciting is the Go To Session. Let us take the Expensive Queries report as a great example for this feature:


As you can see, we have a very expensive query. Let us ignore the reason it is expensive, and assume that we aren’t sure about that.

The problem with the reports feature in the profiler is that while it exposes a lot of information (expensive queries, most common queries, etc), it also lose the context of where this query is running. That is why you can, in any of the reports, right click on a statement and go directly to the session where it originated from:



We bring the context back to the intelligence that we provide.

What happen if we have a statement that appear in several sessions?


You can select each session that this statement appears in, getting back the context of the statement and finding out a lot more about it.

I am very happy about this feature, because I think that it closes a circle with regards to the reports. The reports allows you to pull out a lot of data across you entire application, and the Go To Session feature allows you to connect the interesting pieces of the data back to originating session, giving you where and why this statement was issued.

Estimates sucks, especially when I pay for them

I recently got an estimate for a feature that I wanted to add to NH Prof. It was for two separate features, actually, but they were closely related.

That estimate was for 32 hours.

And it caused me a great deal of indigestion. The problem was, quite simply, that even granting that there is the usual padding of estimates (which I expect), that timing estimate was off, way off. I knew what would be required for this feature, and it shouldn’t be anywhere near complicated enough to require 4 days of full time work. In fact, I estimated that it would take me a maximum of 6 hours and a probable of 3 hours to get it done.

Now, to be fair, I know the codebase (well, actually that isn’t true, a lot of the code for NH Prof was written by Rob & Christopher, and after a few days of working with them, I stopped looking at the code, there wasn’t any need to do so). And I am well aware that most people consider me to be an above average developer.

I wouldn’t have batted an eye for an estimate of 8 – 14 hours, probably. Part of the reason that I have other people working on the code base is that even though I can do certain things faster, I can only do so many things, after all.

But a time estimate that was 5 – 10 times as large as what I estimated was too annoying. I decided that this feature I am going to do on my own. And I decided that I wanted to do this on the clock.

The result is here:


This is actually total time over three separate sittings, but the timing is close enough to what I though it would be.

This includes everything, implementing the feature, unit testing it, wiring it up in the UI, etc.

The only thing remaining is to add the UI works for the other profilers (Entity Framework, Linq to SQL, Hibernate and the upcoming LLBLGen Profiler) . Doing this now…


And we are done.

I have more features that I want to implement, but in general, if I pushed those changes out, they would be a new release that customers can use immediately.

Nitpicker corner: No, I am not being ripped off. And no, the people making the estimates aren't incompetent. To be perfectly honest, looking at the work that they did do and the time marked against it, they are good, and they deliver in a reasonable time frame. What I think is going on is that their estimates are highly conservative, because they don't want to get into a bind with "oh, we run into a problem with XYZ and overrun the time for the feature by 150%".

That also lead to a different problem, when you pay by the hour, you really want to have estimates that are more or less reasonably tied to your payments. But estimating with hours has too much granularity to be really effective (a single bug can easily consume hours, totally throwing off estimation, and it doesn't even have to be a complex one.)

The Profiler New Features: Starring & Renaming

An interesting thing happened recently, when I started to build the profiler, a lot of the features were what I call Core Features. Those were the things that without which, we wouldn’t have a product. Things like detecting SQL, merging it into sessions, providing reports, etc. What I find myself doing recently with the profiler is not so much building Core Features, but building UX features. In other words, now that we have this in place, let us see how we can make better use of this.

Case in point, the new features that were just released in build 713. They aren’t big, but they are there to improve how people are commonly using the products.

Renaming a session:


This is primarily useful if you are in a long profiling session and you want to mark a specific session with some notation:


Small feature, and individually not very useful. But you might have noticed that the sessions are marked with stars around them. They weren’t there is previous builds, so what are they?


They are a way to tell the profiler that you really like those sessions :-)

More to the point, such sessions will not be removed when you clear the current state. That lets you keep around the previous state of the application as a base line while you work to improve it. Beside, it makes it much easier to locate them visually.

And finally, as a quicker way to do that, you can just ask the profiler to clear all but the selected features.


Not big features, but nice ones, I think.

NHProf new feature: Expensive queries report

It has been a while since we had a new major feature for the profiler, but here it is:


The expensive queries report will look at all your queries and surface the most expensive ones across all the sessions. This can give you a good indication on where you need to optimize things.

Naturally, this feature is available across all the profiler profiles (NHibernate Profiler, Entity Framework Profiler, Linq to SQL Profiler and Hibernate Profiler).

Profiler subscriptions are now open for all profilers

After trying it out on NH Prof, profiler subscriptions are now opened for all the profilers.

A profiler subscription allows you to pay a small monthly free (~16$) and get the full profiler capabilities along with the assurance of no upgrade cost when the next major version comes out.

In addition to the monthly subscription, I got requests for a yearly subscription. I am not sure that I quite follow the logic, but I am not going to make it harder for people to give me money, so that is available as well for all profilers.

Profiler new feature: Too many joins detection

This is Josh’s feature, since we wrote most of the code for it together. Basically, it recognize a very common performance problem, queries that uses too many joins, such as this one:


Which would result in the following warning:


Queries with too many joins might be a performance problem. Each join requires the database to perform additional work, and the complexity and cost of the query grows rapidly with each additional join. While relational database are optimized for handling joins, it is often more efficient to perform several separate queries instead of a single query with several joins in it.

For OLTP systems, you should consider simplifying your queries or simplifying the data model. While I do not recommend avoiding joins completely, I strong discourage queries with large numbers of joins. Another issue to pay attention to is possible Cartesian products in queries contains joins, it is very easy to create such a thing and not notice it during development.

Profiler Speculative Feature: Query plans

This isn’t a new feature, because you can’t use it right now, but it is a really nice feature that we are working on, and I couldn’t resist showing it off hot “off the press”, so to speak.

Given the following query:

SELECT this_.id             AS id7_1_,
       this_.title          AS title7_1_,
       this_.subtitle       AS subtitle7_1_,
       this_.allowscomments AS allowsco4_7_1_,
       this_.createdat      AS createdat7_1_,
       posts2_.blogid       AS blogid3_,
       posts2_.id           AS id3_,
       posts2_.id           AS id0_0_,
       posts2_.title        AS title0_0_,
       posts2_.TEXT         AS text0_0_,
       posts2_.postedat     AS postedat0_0_,
       posts2_.blogid       AS blogid0_0_,
       posts2_.userid       AS userid0_0_
FROM   blogs this_
       LEFT OUTER JOIN posts posts2_
         ON this_.id = posts2_.blogid
WHERE  this_.id = 1 /* @p0 */

SELECT this_.id            AS id0_1_,
       this_.title         AS title0_1_,
       this_.TEXT          AS text0_1_,
       this_.postedat      AS postedat0_1_,
       this_.blogid        AS blogid0_1_,
       this_.userid        AS userid0_1_,
       comments2_.postid   AS postid3_,
       comments2_.id       AS id3_,
       comments2_.id       AS id2_0_,
       comments2_.name     AS name2_0_,
       comments2_.email    AS email2_0_,
       comments2_.homepage AS homepage2_0_,
       comments2_.ip       AS ip2_0_,
       comments2_.TEXT     AS text2_0_,
       comments2_.postid   AS postid2_0_
FROM   posts this_
       LEFT OUTER JOIN comments comments2_
         ON this_.id = comments2_.postid
WHERE  this_.blogid = 1 /* @p1 */

The profiler can show you the query plan using this UI:


And here is how the same query looks like using the query plan feature in Management Studio:


So, why implement it?

  • This isn’t limited to SQL Server, the profiler can display query plans for: SQL Server, Oracle, PostgreSQL and MySQL
  • This let you keep yourself in the flow, just hit a button to see the query plan, instead of copying the SQL, opening SSMS, displaying the query plan, etc.

Don’t discount the last one, making it easy is one of the core values of the profiler.

The idea is that if you make it easy enough, the barriers for using it goes away. If you can instantly see the query plan for a query, you are far more likely to look at it than if it takes 30 seconds to get that. At that point, you would only do it when you already have a performance problem.

Linq to SQL Profiler 1.0 Released!


Well, I planned to do it last week, but it got delay for personal reasons.

But here it is, Linq to SQL Profiler is now out of beta, and I personally think it is awesome. Using the profiler, you gain valuable insight about the actual data access pattern of your application (which is usually abstracted away by the Linq to SQL framework). But the profiler goes beyond just dumping a heap of data on you, it takes it several steps further by:

  • Tying together queries and code, you can go directly from any query to the line of code that generated it, no more scratching about “what caused this query”.
  • Analyzing your data access patterns and alerting your about bad practices and suggesting how to fix them.
  • Provide detailed reports on your application’s database usage, perfect for sending to the DBA for optimization.

I got some really nice feedback from people with it:



Happy linqing

Profiler new feature: Integrating with application frameworks

One of the things that makes working with the profiler easier is the fact that it gives you not just information, but information in context.

I was working with an app using Rhino Service Bus, and it really bothered me that I couldn’t immediately figure out what was the trigger for a session. When using ASP.Net or WCF, the profiler can show the URL that triggered the request, but when we are not using a url based mechanism, that turns out to be much harder.

So I set out to fix that, you can see the results below:


This session was generated by a message batch containing messages for MyBooks, MyQueue, etc.

The integration is composed of two parts, first, from the profiler perspective, you now have the ProfilerIntegration.CurrentSessionContext property, which allows you to customize how the profiler detects the current context.

The second part is the integration from the application framework itself, you can see how I did that for Rhino Service Bus, which will dynamically detect the presence of the profiler and fill the appropriate values. The result makes it a lot easier to track down what is going on.

Say hello to Uber Prof

I got several requests for this, so I am making Uber Prof itself available for purchasing.

What is Uber Prof?

It is a short hand way of saying: All the OR/M profilers that we make.

An Uber Prof license gives you the ability to use:

And it will automatically give you the ability to use any additional profilers that we will create. And yes, there is an upgrade path if you already purchased a single profiler license and would like to upgrade to Uber Prof.

What happens behind the scenes: NHibernate, Linq to SQL, Entity Framework scenario analysis

One of the things that I began doing since starting to work on multiple OR/M Profilers is to compare how all of them are handling a particular task. This is by no means a comparative analysis, but it is an interesting data point.

The scenario in question is loading a blog with all its posts and comments.

Let us start with NHibernate:

var blogs = s.CreateQuery(
    @"from Blog b 
        left join fetch b.Posts p 
        left join fetch p.Comments 
    where b.Id = :id")
    .SetParameter("id", 1)

Will generate the following SQL 

select blog0_.Id             as Id7_0_,
       posts1_.Id            as Id0_1_,
       comments2_.Id         as Id2_2_,
       blog0_.Title          as Title7_0_,
       blog0_.Subtitle       as Subtitle7_0_,
       blog0_.AllowsComments as AllowsCo4_7_0_,
       blog0_.CreatedAt      as CreatedAt7_0_,
       posts1_.Title         as Title0_1_,
       posts1_.Text          as Text0_1_,
       posts1_.PostedAt      as PostedAt0_1_,
       posts1_.BlogId        as BlogId0_1_,
       posts1_.UserId        as UserId0_1_,
       posts1_.BlogId        as BlogId0__,
       posts1_.Id            as Id0__,
       comments2_.Name       as Name2_2_,
       comments2_.Email      as Email2_2_,
       comments2_.HomePage   as HomePage2_2_,
       comments2_.Ip         as Ip2_2_,
       comments2_.Text       as Text2_2_,
       comments2_.PostId     as PostId2_2_,
       comments2_.PostId     as PostId1__,
       comments2_.Id         as Id1__
from   Blogs blog0_
       left outer join Posts posts1_
         on blog0_.Id = posts1_.BlogId
       left outer join Comments comments2_
         on posts1_.Id = comments2_.PostId
where  blog0_.Id = 1 /* @p0 */

This result in a fairly simple query plan:


However, you should note that this also result in a Cartesian product, which may not be what you wanted.

Linq to SQL doesn’t really provide a good way to express what I wanted, but it does get the job done:

var dataLoadOptions = new DataLoadOptions();
dataLoadOptions.LoadWith<Blog>(x => x.Posts);
dataLoadOptions.LoadWith<Post>(x => x.Comments);
using (var db = new BlogModelDataContext(conStr)
    LoadOptions =  dataLoadOptions
    db.Blogs.Where(x => x.Id == 1).ToList();

Interestingly enough, this does not generate a single query, but two queries:

-- statement #1
SELECT [t0].[Id],
FROM   [dbo].[Blogs] AS [t0]
WHERE  [t0].[Id] = 1 /* @p0 */

-- statement #2
SELECT   [t0].[Id],
         [t1].[Id]       AS [Id2],
         [t1].[Text]     AS [Text2],
         (SELECT COUNT(* )
          FROM   [dbo].[Comments] AS [t2]
          WHERE  [t2].[PostId] = [t0].[Id]) AS [value]
FROM     [dbo].[Posts] AS [t0]
         LEFT OUTER JOIN [dbo].[Comments] AS [t1]
           ON [t1].[PostId] = [t0].[Id]
WHERE    [t0].[BlogId] = 1 /* @x1 */
ORDER BY [t0].[Id],

The interesting bit is that while there are two queries here, this method does not generate a Cartesian product, so I have to consider this a plus. What I would like to know is whatever this is intentionally so or just a result of the way Linq to SQL eager loading is structured.

The query plan for this is simple as well:


Finally, Entity Framework (both 3.5 and 4.0), using this code:

    .Where(x => x.Id == 1)

This code will generate:

SELECT   [Project2].[Id]             AS [Id],
         [Project2].[Title]          AS [Title],
         [Project2].[Subtitle]       AS [Subtitle],
         [Project2].[AllowsComments] AS [AllowsComments],
         [Project2].[CreatedAt]      AS [CreatedAt],
         [Project2].[C1]             AS [C1],
         [Project2].[C4]             AS [C2],
         [Project2].[Id1]            AS [Id1],
         [Project2].[Title1]         AS [Title1],
         [Project2].[Text]           AS [Text],
         [Project2].[PostedAt]       AS [PostedAt],
         [Project2].[BlogId]         AS [BlogId],
         [Project2].[UserId]         AS [UserId],
         [Project2].[C3]             AS [C3],
         [Project2].[C2]             AS [C4],
         [Project2].[Id2]            AS [Id2],
         [Project2].[Name]           AS [Name],
         [Project2].[Email]          AS [Email],
         [Project2].[HomePage]       AS [HomePage],
         [Project2].[Ip]             AS [Ip],
         [Project2].[Text1]          AS [Text1],
         [Project2].[PostId]         AS [PostId]
FROM     (SELECT [Extent1].[Id]             AS [Id],
                 [Extent1].[Title]          AS [Title],
                 [Extent1].[Subtitle]       AS [Subtitle],
                 [Extent1].[AllowsComments] AS [AllowsComments],
                 [Extent1].[CreatedAt]      AS [CreatedAt],
                 1                          AS [C1],
                 [Project1].[Id]            AS [Id1],
                 [Project1].[Title]         AS [Title1],
                 [Project1].[Text]          AS [Text],
                 [Project1].[PostedAt]      AS [PostedAt],
                 [Project1].[BlogId]        AS [BlogId],
                 [Project1].[UserId]        AS [UserId],
                 [Project1].[Id1]           AS [Id2],
                 [Project1].[Name]          AS [Name],
                 [Project1].[Email]         AS [Email],
                 [Project1].[HomePage]      AS [HomePage],
                 [Project1].[Ip]            AS [Ip],
                 [Project1].[Text1]         AS [Text1],
                 [Project1].[PostId]        AS [PostId],
                   WHEN ([Project1].[C1] IS NULL) THEN CAST(NULL AS int)
                   ELSE CASE 
                          WHEN ([Project1].[Id1] IS NULL) THEN CAST(NULL AS int)
                          ELSE 1
                 END AS [C2],
                   WHEN ([Project1].[C1] IS NULL) THEN CAST(NULL AS int)
                   ELSE CASE 
                          WHEN ([Project1].[Id1] IS NULL) THEN CAST(NULL AS int)
                          ELSE 1
                 END AS [C3],
                 [Project1].[C1]            AS [C4]
          FROM   [dbo].[Blogs] AS [Extent1]
                 LEFT OUTER JOIN (SELECT [Extent2].[Id]       AS [Id],
                                         [Extent2].[Title]    AS [Title],
                                         [Extent2].[Text]     AS [Text],
                                         [Extent2].[PostedAt] AS [PostedAt],
                                         [Extent2].[BlogId]   AS [BlogId],
                                         [Extent2].[UserId]   AS [UserId],
                                         [Extent3].[Id]       AS [Id1],
                                         [Extent3].[Name]     AS [Name],
                                         [Extent3].[Email]    AS [Email],
                                         [Extent3].[HomePage] AS [HomePage],
                                         [Extent3].[Ip]       AS [Ip],
                                         [Extent3].[Text]     AS [Text1],
                                         [Extent3].[PostId]   AS [PostId],
                                         1                    AS [C1]
                                  FROM   [dbo].[Posts] AS [Extent2]
                                         LEFT OUTER JOIN [dbo].[Comments] AS [Extent3]
                                           ON [Extent2].[Id] = [Extent3].[PostId]) AS [Project1]
                   ON [Extent1].[Id] = [Project1].[BlogId]
          WHERE  1 = [Extent1].[Id]) AS [Project2]
ORDER BY [Project2].[Id] ASC,
         [Project2].[C4] ASC,
         [Project2].[Id1] ASC,
         [Project2].[C3] ASC

The query plan for this seems overly complicated:



If you’ll look closely, you’ll see that it generate a join between Blogs, Posts and Comments, essentially creating a Cartesian product between all three.

I am not going to offer commentary on the results, but open a discussion on them.