Concurrency Week: How Entity Framework and NHibernate Can Cause Poison RESOURCE_SEMAPHORE Waits

Development, Memory Grants

I’ve already blogged about my dislike for ORMs from a production DBA performance tuning standpoint only. I get that they’re useful to developers. I get it. But I’m focused on performance.

A quick recap of what I don’t like about ORMs from that other blog post:

  • Implicit conversions due to nvarchar variables vs varchar columns
  • Queries grab every single column, regardless if they are needed or not
    • Expensive key lookups
    • Very wide missing index recommendations
  • The resulting query is hard to read

Though I did mention that they grab every single column, I didn’t mention that this can cause large memory grants which can lead to RESOURCE_SEMAPHORE waits.

RESOURCE_SEMAPHORE waits occur when SQL Server runs out of available memory to run queries.

ORM-style query: Selecting all the columns

Let’s look at an example.

This query grabs all columns from Posts, PostLinks, Users and Comments. In the normal Stack Overflow database without any nonclustered indexes, this query wants an almost 10GB memory grant just to run.

That’s not fair, though – your database indexes are surely very finely tuned – so we’ll give SQL Server a fighting chance with a few helpful indexes to reduce its workload.

However, even with supporting indexes, the query still gets a 325MB memory grant on my server. I’ve certainly seen worse, but it’s enough to simulate the issue. (Brent says: note that the query doesn’t even have an ORDER BY in it, which is my favorite way to get giant memory grants – it would be even worse!)

Nobody notices a 325MB memory grant when it runs by itself – so to show concurrency, I ran the query through SQLQueryStress using 10 iterations and 50 threads.

After it had been running for a few seconds, I checked sp_BlitzFirst.

Look at all those RESOURCE_SEMAPHORE waits.

Some queries are able to run, but many are waiting on memory to become available so that they can START.

This was a 30-second sample, but it too was struggling to run so we got a smaller sample in the Wait Stats section of the sp_BlitzFirst output.

Notice that the average waiting time on RESOURCE_SEMAPHORE is 8784.2 milliseconds. That’s 8.7 seconds. That’s a long time to wait to even start running the query.

Minus the Posts.Body column

Let’s look at the same query but without the Posts.Body column, which is nvarchar(max).

This one gets a 234MB memory grant. That’s 91MB less than the query that includes Posts.Body.

Repeat the test minus the Posts.Body column.

Still seeing RESOURCE_SEMAPHORE waits, but the average waiting time has dropped to 4.5 seconds. Queries don’t have to wait as long in order to get the memory they need to run.

Minus all big columns

Now let’s take a look at the query without the big columns: Posts.Body, Users.AboutMe and Comments.Text columns. Posts.Body and Users.AboutMe are nvarchar(max); Comments.Text is nvarchar(700).

This one gets just a 36MB memory grant.

Repeat the test minus the Posts.Body, Users.AboutMe and Comments.Text columns.

No more RESOURCE_SEMAPHORE waits! Queries no longer have to wait to get the memory they need to run – which also means more memory available for caching data pages and execution plans.

It’s not all good news though. Notice that it says 88 for “Seconds Sample”. I specified 30 seconds for sp_BlitzFirst. I now had a CPU bottleneck. Even sp_BlitzFirst was suffering.

Sometimes when we resolve a bottleneck, it moves the bottleneck to another area. If this were a real-world scenario, I would figure out if there were any other columns that weren’t needed to be returned and then add covering indexes as there are expensive key lookups in the execution plan.

What if I need to return big columns?

Sometimes you need to return really big columns. That’s okay. Return those columns ONLY when you need to. Don’t let your ORM return every single column in each of the tables in the query. Spend the time to return only the columns that are needed for the specific query. Richie shows how to do this in Entity Framework.


Let’s add RESOURCE_SEMAPHORE waits to the list of why I don’t like ORMs from a production DBA performance tuning standpoint:

  • Implicit conversions due to nvarchar variables vs varchar columns
  • Queries grab every single column, regardless if they are needed or not
    • Expensive key lookups
    • Very wide missing index recommendations
    • Leads to RESOURCE_SEMAPHORE waits
  • The resulting query is hard to read

In the wild

Have you seen RESOURCE_SEMAPHORE waits in the wild? Were they due to big columns or something else? How did you resolve it?

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6 Comments. Leave new

  • Gábor Nagypál
    April 25, 2018 1:17 pm

    Table splitting in Entity Framework also can help to return big columns only when explicitly needed:

  • I have talked to so many Application developers about this. They do the .NET code-first because they have no database skills. Then they write all the code in Linq and don’t even bother to create non-clustered indexes on anything! I feel sorry for the DBA trying to explain that someone used an ORM the wrong way, especially after moving to production sized data.

  • Concerning the Point “Queries grab every single column, regardless if they are needed or not”. You can tune the queries on the application side while still using NHibernate. You can reduce the selected columns with the help of JoinAlias, SelectList and the Transformers class.
    Example (not tested but I think you get the concept). The resulting data class must have a parameterless constructor. I am using such Code for readonly operations.

    public IEnumerable TestForSemaphores(DateTime startDate, DateTime endDate, int reputationLevel)
    PostUserCommentDto resultAlias = null;
    PostEntity postAlias = null;
    PostLinkEntity postLinkAlias = null;
    UserEntity userAlias = null;
    CommentEntity commentAlias = null;

    return Session.QueryOver(() => postAlias)
    .JoinAlias(() => postAlias.PostLinks, () => postLinkAlias)
    .JoinAlias(() => postAlias.OwnerUser, () => userAlias)
    .Left.JoinAlias(() => postAlias.Comments, () => commentAlias)
    .WhereRestrictionOn(() => postAlias.CreationDate).IsBetween(startDate).And(endDate)
    .And(() => userAlias.Reputation >= reputationLevel)
    .SelectList(list => list
    .Select(() => postAlias.ID).WithAlias(() => resultAlias.FertigungsauftragID)
    .Select(() => postAlias.AcceptedAnserId).WithAlias(() => resultAlias.AuftragID)
    .Select(() => postAlias.AnswerCount).WithAlias(() => resultAlias.AuftragPK)
    .Select(() => postAlias.CreationDate).WithAlias(() => resultAlias.ProduktionsDatum)
    .Select(() => postAlias.FavoriteCount).WithAlias(() => resultAlias.BinderAnzahl)
    .Select(() => userAlias.DisplayName).WithAlias(() => resultAlias.ShowID)
    .Select(() => userAlias.Location).WithAlias(() => resultAlias.UserLocation)
    .Select(() => commentAlias.Id).WithAlias(() => resultAlias.CommentId)
    .Select(() => commentAlias.CreationDate).WithAlias(() => resultAlias.CommentCreationDate)
    .Select(() => commentAlias.Score).WithAlias(() => resultAlias.CommentScore)

  • When you write a query in EF you don’t need to return all the columns. Just select the ones you want. Its also important to check the SQL it generates. As I tell all our developers EF does not excuse you from the SQL. Always check the SQL generated and check the execution plans! Its not a problem with EF its a problem with some devs.

  • This is not “usage of an ORM”, it is BAD usage of an ORM. One should use the right tool for the right job. The query is unbounded, potentially returning thousands of records. This query would not be issued in a “business transaction” scenario, not even in a UI scenario (where paging usually limits the query with a TOP X) but rather in a “reporting” scenario. In this case, one shouldn’t use an ORM. Plain-old-queries (select, views, SPs if you like) are a much better fit. Massive update processes (bulk processes, night jobs, …) can also issue queries like this one. Again, not a good fit for an ORM.
    The problem with ORMs is not that they “grab every single column”; the problem is that they abstract the DB away from developers (good thing), leading them into thinking they are excused from understanding the instrinsics of the DB that supports their operations (bad thing). But the blame is on the (bad) developer, not on the ORM.

  • […] on April 29, 2018by admin submitted by /u/grauenwolf [link] [comments] No comments […]


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