Related
I am using EF Core 7. It looks like, since EF Core 5, there is now Single vs Split Query execution.
I see that the default configuration still uses the Single Query execution though.
I noticed in my logs it was saying:
Microsoft.EntityFrameworkCore.Query.MultipleCollectionIncludeWarning':
Compiling a query which loads related collections for more than one
collection navigation, either via 'Include' or through projection, but
no 'QuerySplittingBehavior' has been configured. By default, Entity
Framework will use 'QuerySplittingBehavior.SingleQuery', which can
potentially result in slow query performance.
Then I configured a warning on db context to get more details:
services.AddDbContextPool<TheBestDbContext>(
options => options.UseSqlServer(configuration.GetConnectionString("TheBestDbConnection"))
.ConfigureWarnings(warnings => warnings.Throw(RelationalEventId.MultipleCollectionIncludeWarning))
);
Then I was able to specifically see which call was actually causing that warning.
var user = await _userManager.Users
.Include(x => x.UserRoles)
.ThenInclude(x => x.ApplicationRole)
.ThenInclude(x => x.RoleClaims)
.SingleOrDefaultAsync(u => u.Id == userId);
So basically same code would be like:
var user = await _userManager.Users
.Include(x => x.UserRoles)
.ThenInclude(x => x.ApplicationRole)
.ThenInclude(x => x.RoleClaims)
.AsSplitQuery() // <===
.SingleOrDefaultAsync(u => u.Id == userId);
with Split query option.
I went through the documentation, but I'm still not sure how to create a pattern out of it.
I would like to set the most common one as a default value across the project, and only use the other for specific scenarios.
Based on the documentation, I have a feeling that the "Split" should be used as default in general but with caution. I also noticed on their documentation specific to pagination, that it says:
When using split queries with Skip/Take, pay special attention to making your query ordering fully unique; not doing so could cause incorrect data to be returned. For example, if results are ordered only by date, but there can be multiple results with the same date, then each one of the split queries could each get different results from the database. Ordering by both date and ID (or any other unique property or combination of properties) makes the ordering fully unique and avoids this problem. Note that relational databases do not apply any ordering by default, even on the primary key.
which completely makes sense as the query will be split.
But if we are mainly fetching from database for a single record, regardless how big or small the include list with its navigation properties, should I always go with "Split" approach?
I would love to hear if there are any best practices on that and when to use which approach.
But if we are mainly fetching from database for a single record, regardless how big or small the include list with its navigation properties, should I always go with "Split" approach?
It depends, let's examine your example in Single query approach:
var user = await _userManager.Users // 1 records based on SingleOrDefault but to server goes TAKE 2
.Include(x => x.UserRoles) // R roles
.ThenInclude(x => x.ApplicationRole) // 1 record
.ThenInclude(x => x.RoleClaims) // C claims
.SingleOrDefaultAsync(u => u.Id == userId);
As result on the client will be returned RecordCount = 1 * R * 1 * C records. Then they will be deduplicated and placed in appropriate collections.
If RecordCount is approximately small Single query can be best approach.
Also EF Core adds ORDER BY for such query which may slowdown execution. So better examine execution plan.
Side note: Better to use FirstOrDefault/Async it CAN be a lot faster than SingleOrDefault/Async, when SQL server fails to detect that there no 2 records in recordset early.
The documentation at https://learn.microsoft.com/en-us/ef/core/querying/single-split-queries outlines the considerations when Split Queries could have unintentional consequences, particularly around isolation and ordering. As mentioned when loading a single record with related details, a singlw query execution is generally perferred. The warning is appearing because you have a one-to-many, which contains a one-to-many, so it is warning that this can potentially lead to a much larger Cartesian Product in terms of a JOIN-based query. To avoid the warning as you are confident that the query is reasonable in size, you can specify .AsSingleQuery() explicitly and the warning should disappear.
When working with object graphs like this you can consider designing operations against the data state to be as atomic as possible. IF you are editing a User that has Roles & Claims, rather than loading everything for a User and attempting to edit the entire graph in memory in one go, you might structure the application to perform actions like "AddRoleToUser", "RemoveRoleFromUser", AddClaimToUserRole", etc. So instead of loading User /w Roles /w Claims, these actions just load Roles for a user, or Claims for a UserRole respectively to alter this data.
After searching through this to figure out if there is any pattern to apply this, and with all the great content provided at the bottom, I was still not sure as I was looking for "When to use split queries" and "when not to", so I tried the summarized my understanding at the bottom.
I will use the same example that Microsoft shows on Single vs Split Queries
var blogs = ctx.Blogs
.Include(b => b.Posts)
.Include(b => b.Contributors)
.ToList();
and here is the generated SQL for that:
SELECT [b].[Id], [b].[Name], [p].[Id], [p].[BlogId], [p].[Title], [c].[Id], [c].[BlogId], [c].[FirstName], [c].[LastName]
FROM [Blogs] AS [b]
LEFT JOIN [Posts] AS [p] ON [b].[Id] = [p].[BlogId]
LEFT JOIN [Contributors] AS [c] ON [b].[Id] = [c].[BlogId]
ORDER BY [b].[Id], [p].[Id]
Microsoft says:
In this example, since both Posts and Contributors are collection
navigations of Blog - they're at the same level - relational databases
return a cross product: each row from Posts is joined with each row
from Contributors. This means that if a given blog has 10 posts and 10
contributors, the database returns 100 rows for that single blog. This
phenomenon - sometimes called cartesian explosion - can cause huge
amounts of data to unintentionally get transferred to the client,
especially as more sibling JOINs are added to the query; this can be a
major performance issue in database applications.
However what it doesn't clearly mention is, other than sorting/ordering issues, this may easily mess up the performance of the queries.
First concern is, we are going to be hitting to database multiple times in that case.
Let's check this one:
using (var context = new BloggingContext())
{
var blogs = context.Blogs
.Include(blog => blog.Posts)
.AsSplitQuery()
.ToList();
}
And check out the generated SQL when .AsSplitQuery() is used.
SELECT [b].[BlogId], [b].[OwnerId], [b].[Rating], [b].[Url]
FROM [Blogs] AS [b]
ORDER BY [b].[BlogId]
SELECT [p].[PostId], [p].[AuthorId], [p].[BlogId], [p].[Content], [p].[Rating], [p].[Title], [b].[BlogId]
FROM [Blogs] AS [b]
INNER JOIN [Posts] AS [p] ON [b].[BlogId] = [p].[BlogId]
ORDER BY [b].[BlogId]
So above query was kind of surprised me. It is interesting that when it uses the split option, it still joins on the second query even though second query should only be pulling data from posts table. Pretty sure EF Core folks had some idea behind that but it just doesn't make sense to me. Then what is the point of having that foreign key over there?
Looks like Microsoft was mainly focused on a solution to avoid cartesian explosion problem but obviously it doesn't mean that "split queries" should be used as best practices by default going forward. Definitely not!
And another possible problem I can think of is data inconsistency, yet the queries are ran separate, you can't guarantee the data consistency. (unless completely locked)
I just don't want to throw away the feature of course. There are still some "good" scenarios to use Split Queries imo, (unless you are really worried about the data consistency) like if we are returning lots of columns with a relation and the size is pretty large, then this could be really performance factor. Or the parent data is not a lot, but tons of navigation sets, then there is your cartesian explosion.
PS: Note that cartesian explosion does not occur when the two JOINs aren't at the same level.
Last but not least, personally, if I am really going to be pulling some heavy amount of data with bunch of relation of relation of relation, I would still prefer those "good old" Stored Procedures. It never gets old!
I'm an EF noob (as in I just started today, I've only used other ORMs), and I'm experiencing a baptism of fire.
I've been asked to improve the performance of this query created by another dev:
var questionnaires = await _myContext.Questionnaires
.Include("Sections")
.Include(q => q.QuestionnaireCommonFields)
.Include("Sections.Questions")
.Include("Sections.Questions.Answers")
.Include("Sections.Questions.Answers.AnswerMetadatas")
.Include("Sections.Questions.Answers.SubQuestions")
.Include("Sections.Questions.Answers.SubQuestions.Answers")
.Include("Sections.Questions.Answers.SubQuestions.Answers.AnswerMetadatas")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.AnswerMetadatas")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.AnswerMetadatas")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.AnswerMetadatas")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers")
.Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.AnswerMetadatas")
.Where(q => questionnaireIds.Contains(q.Id))
.ToListAsync().ConfigureAwait(false);
A quick web-surf tells me that Include() results in a cols * rows product and poor performance if you run multiple levels deep.
I've seen some helpful answers on SO, but they have limited less complex examples, and I can't figure out the best approach for a rewrite of the above.
The multiple repeat of the part -"Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers..." looks suspicious to me like it could be done separately and then another query issued, but I don't know how to build this up or whether such an approach would even improve performance.
Questions:
How do I rewrite this query to something more sensible to improve performance, while ensuring that the eventual result set is the same?
Given the last line: .Include("Sections.Questions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.SubQuestions.Answers.AnswerMetadatas")
Why do I need all the intermediate lines? (I guess it's because some of the joins may not be left joins?)
EF Version info: package id="EntityFramework" version="6.2.0" targetFramework="net452"
I realise this question is a bit rubbish, but I'm trying to resolve as fast as I can from a point of no knowledge.
Edit
After mulling over this for half a day and thanks to StuartLC's suggestions I came up with some options:
Poor - split the query so that it performs multiple round-trips to fetch the data. This is likely to provide a slightly slower experience for the user, but will stop the SQL timing out. (This is not much better than just increasing the EF command timeout).
Good - change the clustered indexing on child tables to be clustered by their parent's foreign key (assuming you don't have a lot of insert operations).
Good - change the code to only query the first few levels and lazy-load (separate db hit) anything below this, i.e. remove all but the top few Includes, then change the ICollections - Answers.SubQuestions, Answers.AnswerMetadatas, and Question.Answers to all be virtual. Presumably the downside to making these virtual is that if any (other) existing code in the app expects those ICollection properties to be eager-loaded, you may have to update that code (i.e. if you want/need them to load immediately within that code). I will be investigating this option further. Further edit - unfortunately this won't work if you need to serialize the response due to self-referencing loop.
Non-trivial - Write a sql stored proc/view manually and build a new EF object pointed at it.
Longer term
The obvious, best, but most time-consuming option - rewrite the app design, so it doesn't need the whole data tree in a single api call, or go with the option below:
Rewrite the app to store the data in a NoSQL fashion (e.g. store the object tree as json so there are no joins). As Stuart mentioned this is not a good option if you need to filter the data in other ways (via something other than the questionnaireId), which you might need to do. Another alternative is to partially store NoSQL-style and partially relational as required.
First up, it must be said that this isn't a trivial query. Seemingly we have:
6 levels of recursion through a nested question-answer tree
A total of 20 tables are joined in this way via eager loaded .Include
I would first take the time to determine where this query is used in your app, and how often it is needed, with particular attention to where it is used most frequently.
YAGNI optimizations
The obvious place to start is to see where the query is used in your app, and if you don't need the whole tree all the time, then suggest you don't join in the nested question and answer tables if they are not needed in all usages of the query.
Also, it is possible to compose on IQueryable dynamically, so if there are multiple use cases for your query (e.g. from a "Summary" screen which doesn't need the question + answers, and a details tree which does need them), then you can do something like:
var questionnaireQuery = _myContext.Questionnaires
.Include(q => q.Sections)
.Include(q => q.QuestionnaireCommonFields);
// Conditionally extend the joins
if (mustIncludeQandA)
{
questionnaireQuery = questionnaireQuery
.Include(q => q.Sections.Select(s => s.Questions.Select(q => q.Answers..... etc);
}
// Execute + materialize the query
var questionnaires = await questionnaireQuery
.Where(q => questionnaireIds.Contains(q.Id))
.ToListAsync()
.ConfigureAwait(false);
SQL Optimizations
If you really have to fetch the whole tree all the time, then look at your SQL table design and indexing.
1) Filters
.Where(q => questionnaireIds.Contains(q.Id))
(I'm assuming SQL Server terminology here, but the concepts are applicable in most other RDBMs as well.)
I'm guessing Questionnaires.Id is a clustered primary key, so will be indexed, but just check for sanity (it will look something PK_Questionnaires CLUSTERED UNIQUE PRIMARY KEY in SSMS)
2) Ensure all child tables have indexes on their foreign keys back to the parent.
e.g. q => q.Sections means that table Sections has a foreign key back to Questionnaires.Id - make sure this has at least a non-clustered index on it - EF Code First should do this automagically, but again, check to be sure.
This would look like IX_QuestionairreId NONCLUSTERED on column Sections(QuestionairreId)
3) Consider changing the clustered indexing on child tables to be clustered by their parent's foreign key, e.g. Cluster Section by Questions.SectionId. This will keep all child rows related to the same parent together, and reduce the number of pages of data that SQL needs to fetch. It isn't trivial to achieve in EF code first, but your DBA can assist you in doing this, perhaps as a custom step.
Other comments
If this query is only used to query data, not to update or delete, then adding .AsNoTracking() will marginally reduce the memory consumption and in-memory performance of EF.
Unrelated to performance, but you've mixed the weakly typed ("Sections") and strongly typed .Include statements (q => q.QuestionnaireCommonFields). I would suggest moving to the strongly typed includes for the additional compile time safety.
Note that you only need to specify the include path for the longest chain(s) which are eager loaded - this will obviously force EF to include all higher levels too. i.e. You can reduce the 20 .Include statements to just 2. This will do the same job more efficiently:
.Include(q => q.QuestionnaireCommonFields)
.Include(q => q.Sections.Select(s => s.Questions.Select(q => q.Answers .... etc))
You'll need .Select any time there is a 1:Many relationship, but if the navigation is 1:1 (or N:1) then you don't need the .Select, e.g. City c => c.Country
Redesign
Last but not least, if data is only ever filtered from the top level (i.e. Questionnaires), and if the whole questionairre 'tree' (Aggregate Root) is typically always added or updated all at once, then you might try and approach the data modelling of the question and answer tree in a NoSQL way, e.g. by simply modelling the whole tree as XML or JSON, and then treat the whole tree as a long string. This will avoid all the nasty joins altogether. You would need a custom deserialization step in your data tier. This latter approach won't be very useful if you need to filter from nodes in the tree (i.e. a Query like find me all questionairre's where the SubAnswer to Question 5 is "Foo" won't be a good fit)
I have often found that if I have too many joins in a Linq query (whether using Entity Framework or NHibernate) and/or the shape of the resulting anonymous class is too complex, Linq takes a very long time to materialize the result set into objects.
This is a generic question, but here's a specific example using NHibernate:
var libraryBookIdsWithShelfAndBookTagQuery = (from shelf in session.Query<Shelf>()
join sbttref in session.Query<ShelfBookTagTypeCrossReference>() on
shelf.ShelfId equals sbttref.ShelfId
join bookTag in session.Query<BookTag>() on
sbttref.BookTagTypeId equals (byte)bookTag.BookTagType
join btbref in session.Query<BookTagBookCrossReference>() on
bookTag.BookTagId equals btbref.BookTagId
join book in session.Query<Book>() on
btbref.BookId equals book.BookId
join libraryBook in session.Query<LibraryBook>() on
book.BookId equals libraryBook.BookId
join library in session.Query<LibraryCredential>() on
libraryBook.LibraryCredentialId equals library.LibraryCredentialId
join lcsg in session
.Query<LibraryCredentialSalesforceGroupCrossReference>()
on library.LibraryCredentialId equals lcsg.LibraryCredentialId
join userGroup in session.Query<UserGroup>() on
lcsg.UserGroupOrganizationId equals userGroup.UserGroupOrganizationId
where
shelf.ShelfId == shelfId &&
userGroup.UserGroupId == userGroupId &&
!book.IsDeleted &&
book.IsDrm != null &&
book.BookFormatTypeId != null
select new
{
Book = book,
LibraryBook = libraryBook,
BookTag = bookTag
});
// add a couple of where clauses, then...
var result = libraryBookIdsWithShelfAndBookTagQuery.ToList();
I know it's not the query execution, because I put a sniffer on the database and I can see that the query is taking 0ms, yet the code is taking about a second to execute that query and bring back all of 11 records.
So yeah, this is an overly complex query, having 8 joins between 9 tables, and I could probably restructure it into several smaller queries. Or I could turn it into a stored procedure - but would that help?
What I'm trying to understand is, where is that red line crossed between a query that is performant and one that starts to struggle with materialization? What's going on under the hood? And would it help if this were a SP whose flat results I subsequently manipulate in memory into the right shape?
EDIT: in response to a request in the comments, here's the SQL emitted:
SELECT DISTINCT book4_.bookid AS BookId12_0_,
libraryboo5_.librarybookid AS LibraryB1_35_1_,
booktag2_.booktagid AS BookTagId15_2_,
book4_.title AS Title12_0_,
book4_.isbn AS ISBN12_0_,
book4_.publicationdate AS Publicat4_12_0_,
book4_.classificationtypeid AS Classifi5_12_0_,
book4_.synopsis AS Synopsis12_0_,
book4_.thumbnailurl AS Thumbnai7_12_0_,
book4_.retinathumbnailurl AS RetinaTh8_12_0_,
book4_.totalpages AS TotalPages12_0_,
book4_.lastpage AS LastPage12_0_,
book4_.lastpagelocation AS LastPag11_12_0_,
book4_.lexilerating AS LexileR12_12_0_,
book4_.lastpageposition AS LastPag13_12_0_,
book4_.hidden AS Hidden12_0_,
book4_.teacherhidden AS Teacher15_12_0_,
book4_.modifieddatetime AS Modifie16_12_0_,
book4_.isdeleted AS IsDeleted12_0_,
book4_.importedwithlexile AS Importe18_12_0_,
book4_.bookformattypeid AS BookFor19_12_0_,
book4_.isdrm AS IsDrm12_0_,
book4_.lightsailready AS LightSa21_12_0_,
libraryboo5_.bookid AS BookId35_1_,
libraryboo5_.libraryid AS LibraryId35_1_,
libraryboo5_.externalid AS ExternalId35_1_,
libraryboo5_.totalcopies AS TotalCop5_35_1_,
libraryboo5_.availablecopies AS Availabl6_35_1_,
libraryboo5_.statuschangedate AS StatusCh7_35_1_,
booktag2_.booktagtypeid AS BookTagT2_15_2_,
booktag2_.booktagvalue AS BookTagV3_15_2_
FROM shelf shelf0_,
shelfbooktagtypecrossreference shelfbookt1_,
booktag booktag2_,
booktagbookcrossreference booktagboo3_,
book book4_,
librarybook libraryboo5_,
library librarycre6_,
librarycredentialsalesforcegroupcrossreference librarycre7_,
usergroup usergroup8_
WHERE shelfbookt1_.shelfid = shelf0_.shelfid
AND booktag2_.booktagtypeid = shelfbookt1_.booktagtypeid
AND booktagboo3_.booktagid = booktag2_.booktagid
AND book4_.bookid = booktagboo3_.bookid
AND libraryboo5_.bookid = book4_.bookid
AND librarycre6_.libraryid = libraryboo5_.libraryid
AND librarycre7_.librarycredentialid = librarycre6_.libraryid
AND usergroup8_.usergrouporganizationid =
librarycre7_.usergrouporganizationid
AND shelf0_.shelfid = #p0
AND usergroup8_.usergroupid = #p1
AND NOT ( book4_.isdeleted = 1 )
AND ( book4_.isdrm IS NOT NULL )
AND ( book4_.bookformattypeid IS NOT NULL )
AND book4_.lightsailready = 1
EDIT 2: Here's the performance analysis from ANTS Performance Profiler:
It is often database "good" practice to place lots of joins or super common joins into views. ORMs don't let you ignore these facts nor do they supplement the decades of time spent fine tuning databases to do these kinds of things efficiently. Refactor those joins into a singular view or a couple views if that'd make more sense in the greater perspective of your application.
NHibernate should be optimizing the query down and reducing the data so that .Net only has to mess with the important parts. However, if those domain objects are just naturally large, that's still a lot of data. Also, if it's a really large result set in terms of rows returned, that's a lot of objects getting instantiated even if the DB is able to return the set quickly. Refactoring this query into a view that only returns the data you actually need would also reduce object instantiation overhead.
Another thought would be to not do a .ToList(). Return the enumerable and let your code lazily consume the data.
According to profiling information, the CreateQuery takes 45% of the total execution time. However as you mentioned the query took 0ms when you executed directly. But this alone is not enough to say there is a performance problem because,
You are running the query with the profiler which has significant impact on execution time.
When you use a profiler, it will affect every code is being profiled but not the sql execution time (because it happens in the SQL server), so you can see everything else is slower compared to SQL statement.
so ideal scenario is to measure how long it takes to execute entire code block, measure time for SQL query and calculate times, and if you do that you will probably end up with different values.
However, I'm not saying that the the NH Linq to SQL implementation is optimized for any query you come up with, but there are other ways in NHibernate to deal with those situations such as QueryOverAPI, CriteriaQueries, HQL and finally SQL.
Where is that red line crossed between a query that is performant and
one that starts to struggle with materialization. What's going on under the hood?
This one is pretty hard question and without having detail knowledge of NHibernate Linq to SQL provider it's hard to provide a accurate answer. You can always try different mechanisms provided and see which one is the best for given scenario.
And would it help if this were a SP whose flat results I subsequently
manipulate in memory into the right shape?
Yes, using a SP would help things to work pretty fast, but using SP would add more maintenance problems to your code base.
You have generic question, I'll tell you generic answer :)
If you query data for reading (not for update) try to use anonymous classes. The reason is - they are lighter to create, they have no navigatoin properties. And you select only data you need! It's very important rule. So, try to replace your select with smth like this:
select new
{
Book = new { book.Id, book.Name},
LibraryBook = new { libraryBook.Id, libraryBook.AnotherProperty},
BookTag = new { bookTag.Name}
}
Stored procedures are good, when query is complex and linq-provider generates not effective code, so, you can replace it with plain SQL or stored procedure. It's not offten case and, I think, it's not your situation
Run your sql-query. How many rows it returns? Is it the same value as result? Sometimes linq provider generates code, that select much more rows to select one entity. It happens, when entity has one to many relationship with another selecting entity. For example:
class Book
{
int Id {get;set;}
string Name {get;set;}
ICollection<Tag> Tags {get;set;}
}
class Tag
{
string Name {get;set;}
Book Book {get;set;}
}
...
dbContext.Books.Where(o => o.Id == 1).Select(o=>new {Book = o, Tags = o.Tags}).Single();
I Select only one book with Id = 1, but provider will generate code, that returns rows amount equals to Tags amount (entity framework does this).
Split complex query to set of simple and join in client side. Sometimes, you have complex query with many conditionals and resulting sql become terrible. So, you split you big query to more simple, get results of each and join/filter on client side.
At the end, I advice you to use anonymous class as result of select.
Don’t use Linq’s Join. Navigate!
in that post you can see:
As long as there are proper foreign key constraints in the database, the navigation properties will be created automatically. It is also possible to manually add them in the ORM designer. As with all LINQ to SQL usage I think that it is best to focus on getting the database right and have the code exactly reflect the database structure. With the relations properly specified as foreign keys the code can safely make assumptions about referential integrity between the tables.
I agree 100% with the sentiments expressed by everyone else (with regards to their being two parts to the optimisation here and the SQL execution being a big unknown, and likely cause of poor performance).
Another part of the solution that might help you get some speed is to pre-compile your LINQ statements. I remember this being a huge optimisation on a tiny project (high traffic) I worked on ages and ages ago... seems like it would contribute to the client side slowness you're seeing. Having said all that though I've not found a need to use them since... so heed everyone else's warnings first! :)
https://msdn.microsoft.com/en-us/library/vstudio/bb896297(v=vs.100).aspx
I have executed a linq query by using Entityframework like below
GroupMaster getGroup = null;
getGroup = DataContext.Groups.FirstOrDefault(item => keyword.IndexOf(item.Keywords,StringComparison.OrdinalIgnoreCase)>=0 && item.IsEnabled)
when executing this method I got exception like below
LINQ to Entities does not recognize the method 'Int32 IndexOf(System.String, System.StringComparison)' method, and this
method cannot be translated into a store expression.
Contains() method by default case sensitive so again I need to convert to lower.Is there any method for checking a string match other than the contains method and is there any method to solve the indexOf method issue?
The IndexOf method Of string class will not recognized by Entity Framework, Please replace this function with SQLfunction or Canonical functions
You can also take help from here or maybe here
You can use below code sample:
DataContext.Groups.FirstOrDefault(item =>
System.Data.Objects.SqlClient.SqlFunctions.CharIndex(item.Keywords, keyword).Value >=0 && item.IsEnabled)
You really only have four options here.
Change the collation of the database globally. This can be done in several ways, a simple google search should reveal them.
Change the collation of individual tables or columns.
Use a stored procedure and specify the COLATE statement on your query
perform a query and return a large set of results, then filter in memory using Linq to Objects.
number 4 is not a good option unless your result set is pretty small. #3 is good if you can't change the database (but you can't use Linq with it).
numbers 1 and 2 are choices you need to make about your data model as a whole, or if you only want to do it on specific fields.
Changing the Servers collation:
http://technet.microsoft.com/en-us/library/ms179254.aspx
Changing the Database Collation:
http://technet.microsoft.com/en-us/library/ms179254.aspx
Changing the Columns Collation:
http://technet.microsoft.com/en-us/library/ms190920(v=sql.105).aspx
Using the Collate statement in a stored proc:
http://technet.microsoft.com/en-us/library/ms184391.aspx
Instead you can use this method below for lowering the cases:
var lowerCaseItem = item.ToLower();
If your item is of type string. Then this might get you through that exception.
Erik Funkenbush' answer is perfectly valid when looking at it like a database problem. But I get the feeling that you need a better structure for keeping data regarding keywords if you want to traverse them efficiently.
Note that this answer isn't intended to be better, it is intended to fix the problem in your data model rather than making the environment adapt to the current (apparently flawed, since there is an issue) data model you have.
My main suggestion, regardless of time constraint (I realize this isn't the easiest fix) would be to add a separate table for the keywords (with a many-to-many relationship with its related classes).
[GROUPS] * ------- * [KEYWORD]
This should allow for you to search for the keyword, and only then retrieve the items that have that keyword related to it (based on ID rather than a compound string).
int? keywordID = DataContext.Keywords.Where(x => x.Name == keywordFilter).Select(x => x.Id).FirstOrDefault();
if(keywordID != null)
{
getGroup = DataContext.Groups.FirstOrDefault(group => group.Keywords.Any(kw => kw.Id == keywordID));
}
But I can understand completely if this type of fix is not possible anymore in the current project. I wanted to mention it though, in case anyone in the future stumbles on this question and still has the option for improving the data structure.
Using the Entity Framework, when one executes a query on lets say 2000 records requiring a groupby and some other calculations, does the query get executed on the server and only the results sent over to the client or is it all sent over to the client and then executed?
This using SQL Server.
I'm looking into this, as I'm going to be starting a project where there will be loads of queries required on a huge database and want to know if this will produce a significant load on the network, if using the Entity Framework.
I would think all database querying is done on the server side (where the database is!) and the results are passed over. However, in Linq you have what's known as Delayed Execution (lazily loaded) so your information isn't actually retrieved until you try to access it e.g. calling ToList() or accessing a property (related table).
You have the option to use the LoadWith to do eager loading if you require it.
So in terms of performance if you only really want to make 1 trip to the Database for your query (which has related tables) I would advise using the LoadWith options. However, it does really depend on the particular situation.
It's always executed on SQL Server. This also means sometimes you have to change this:
from q in ctx.Bar
where q.Id == new Guid(someString)
select q
to
Guid g = new Guid(someString);
from q in ctx.Bar
where q.Id == g
select q
This is because the constructor call cannot be translated to SQL.
Sql's groupby and linq's groupby return differently shaped results.
Sql's groupby returns keys and aggregates (no group members)
Linq's groupby returns keys and group members.
If you use those group members, they must be (re-)fetched by the grouping key. This can result in +1 database roundtrip per group.
well, i had the same question some time ago.
basically: your linq-statement is converted to a sql-statement. however: some groups will get translated, others not - depending on how you write your statement.
so yes - both is possible
example:
var a = (from entity in myTable where entity.Property == 1 select entity).ToList();
versus
var a = (from entity in myTable.ToList() where entity.Property == 1 select entity).ToList();