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Serializing complex EF model over JSON

I have done a lot of searching and experimenting and have been unable to find a workable resolution to this problem.
Environment/Tools
Visual Studio 2013
C#
Three tier web application:
Database tier: SQL Server 2012
Middle tier: Entity Framework 6.* using Database First, Web API 2.*
Presentation tier: MVC 5 w/Razor, Bootstrap, jQuery, etc.
Background
I am building a web application for a client that requires a strict three-tier architecture. Specifically, the presentation layer must perform all data access through a web service. The presentation layer cannot access a database directly. The application allows a small group of paid staff members to manage people, waiting lists, and the resources they are waiting for. Based on the requirements the data model/database design is entirely centered around the people (User table).
Problem
When the presentation layer requests something, say a Resource, it is related to at least one User, which in turn is related to some other table, say Roles, which are related to many more Users, which are related to many more Roles and other things. The point being that, when I query for just about anything EF wants to bring in almost the entire database.
Normally this would be okay because of EF's default lazy-load behavior, but when serializing just about any object to JSON for returning to the presentation layer, the Newtonsoft.Json serializer hangs for a long time then blows a stack error.
What I Have Tried
Here is what I have attempted so far:
Set Newtonsoft's JSON serialier ReferenceLoopHandling setting to Ignore. No luck. This is not cyclic graph issue, it is just the sheer volume of data that gets brought in (there are over 20,000 Users).
Clear/reset unneeded collections and set reference properties to null. This showed some promise, but I could not get around Entity Framework's desire to track everything.
Just setting nav properties to null/clear causes those changes to be saved back to the database on the next .SaveChanges() (NOTE: This is an assumption here, but seemed pretty sound. If anyone knows different, please speak up).
Detaching the entities causes EF to automatically clear ALL collections and set ALL reference properties to null, whether I wanted it to or not.
Using .AsNotTracking() on everything threw some exception about not allowing non-tracked entities to have navigation properties (I don't recall the exact details).
Use AutoMapper to make copies of the object graph, only including related objects I specify. This approach is basically working, but in the process of (I believe) performing the auto-mapping, all of the navigation properties are accessed, causing EF to query and resolve them. In one case this leads to almost 300,000 database calls during a single request to the web service.
What I am Looking For
In short, has anyone had to tackle this problem before and come up with a working and performant solution?
Lacking that, any pointers for at least where to look for how to handle this would be greatly appreciated.
Additional Note: It occurred to me as I wrote this that I could possibly combine the second and third items above. In other words, set/clear nav properties, then automap the graph to new objects, then detach everything so it won't get saved (or perhaps wrap it in a transaction and roll it back at the end). However, if there is a more elegant solution I would rather use that.
Thanks,
Dave

It is true that doing what you are asking for is very difficult and it's an architectural trap I see a lot of projects get stuck in.
Even if this problem were solveable, you'd basically end up just having a data layer which just wraps the database and destroys performance because you can't leverage SQL properly.
Instead, consider building your data access service in such a way that it returns meaningful objects containing meaningful data; that is, only the data required to perform a specific task outlined in the requirements documentation. It is true that an post is related to an account, which has many achievements, etc, etc. But usually all I want is the text and the name of the poster. And I don't want it for one post. I want it for each post in a page. Instead, write data services and methods which do things which are relevant to your application.
To clarify, it's the difference between returning a Page object containing a list of Posts which contain only a poster name and message and returning entire EF objects containing large amounts of irrelevant data such as IDs, auditing data such as creation time.
Consider the Twitter API. If it were implemented as above, performance would be abysmal with the amount of traffic Twitter gets. And most of the information returned (costing CPU time, disk activity, DB connections as they're held open longer, network bandwidth) would be completely irrelevant to what developers want to do.
Instead, the API exposes what would be useful to a developer looking to make a Twitter app. Get me the posts by this user. Get me the bio for this user. This is probably implemented as very nicely tuned SQL queries for someone as big as Twitter, but for a smaller client, EF is great as long as you don't attempt to defeat its performance features.
This additionally makes testing much easier as the smaller, more relevant data objects are far easier to mock.

For three tier applications, especially if you are going to expose your entities "raw" in services, I would recommend that you disable Lazy Load and Proxy generation in EF. Your alternative would be to use DTO's instead of entities, so that the web services are returning a model object tailored to the service instead of the entity (as suggested by jameswilddev)
Either way will work, and has a variety of trade-offs.
If you are using EF in a multi-tier environment, I would highly recommend Julia Lerman's DbContext book (I have no affiliation): http://www.amazon.com/Programming-Entity-Framework-Julia-Lerman-ebook/dp/B007ECU7IC
There is a chapter in the book dedicated to working with DbContext in multi-tier environments (you will see the same recommendations about Lazy Load and Proxy). It also talks about how to manage inserts and updates in a multi-tier environment.

i had such a project which was the stressful one .... and also i needed to load large amount of data and process them from different angles and pass it to complex dashboard for charts and tables.
my optimization was :
1-instead of using ef to load data i called old-school stored procedure (and for more optimization grouping stuff to reduce table as much as possible for charts. eg query returns a table that multiple charts datasets can be extracted from it)
2-more important ,instead of Newtonsoft's JSON i used fastJSON which performance was mentionable( it is really fast but not compatible with complex object. simple example may be view models that have list of models inside and may so on and on or )
better to read pros and cons of fastJSON before
https://www.codeproject.com/Articles/159450/fastJSON
3-in relational database design who is The prime suspect of this problem it might be good to create those tables which have raw data to process in (most probably for analytics) denormalized schema which save performance on querying data.
also be ware of using model class from EF designer from database for reading or selecting data especially when u want serialize it(some times i think separating same schema model to two section of identical classes/models for writing and reading data in such a way that the write models has benefit of virtual collections came from foreign key and read models ignore it...i am not sure for this).
NOTE: in case of very very huge data its better go deeper and set up in-memory table OLTP for the certain table contains facts or raw data how ever in that case your table acts as none relational table like noSQL.
NOTE: for example in mssql you can use benefits of sqlCLR which let you write scripts in c#,vb..etc and call them by t-sql in other words handle data processing from database level.
4-for interactive view which needs load data i think its better to consider which information might be processed in server side and which ones can be handled by client side(some times its better to query data from client-side ... how ever you should consider that those data in client side can be accessed by user) how ever it is situation-wise.
5-in case of large raw data table in view using datatables.min.js is a good idea and also every one suggest using serverside-paging on tables.
6- in case of importing and exporting data from big files oledb is a best choice i think.
how ever still i doubt them to be exact solutions. if any body have practical solutions please mention it ;) .

I have fiddled with a similar problem using EF model first, and found the following solution satisfying for "One to Many" relations:
Include "Foreign key properties" in the sub-entities and use this for later look-up.
Define the get/set modifiers of any "Navigation Properties" (sub-collections) in your EF entity to private.
This will give you an object not exposing the sub-collections, and you will only get the main properties serialized. This workaround will require some restructuring of your LINQ queries, asking directly from your table of SubItems with the foreign key property as your filtering option like this:
var myFitnessClubs = context.FitnessClubs
?.Where(f => f.FitnessClubChainID == myFitnessClubChain.ID);
Note 1:
You may off-cause choose to implement this solution partly, hence only affecting the sub-collections that you strongly do not want to serialize.
Note 2:
For "Many to Many" relations, at least one of the entities needs to have a public representation of the collection. Since the relation cannot be retrieved using a single ID property.

How entity framework works for large number of records? [closed]

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I see already a un-answered question here on.
My question is -
Is EF really production ready for large application?
The question originated from these underlying questions -
EF pulls all the records into memory then performs the query
operation. How EF would behave when table has around ~1000 records?
For simple edit I have to pull the record edit it and
then push to db using SaveChanges()

I faced a similar situation where we had a large database with many tables 7- 10 million records each. we used Entity framework to display the data. To get nice performance here's what I learned; My 10 Golden rules for Entity Framework:
Understand that call to database made only when the actual records are required. all the operations are just used to make the query (SQL) so try to fetch only a piece of data rather then requesting a large number of records. Trim the fetch size as much as possible
Yes, (In some cases stored procedures are a better choice, they are not that evil as some make you believe), you should use stored procedures where necessary. Import them into your model and have function imports for them. You can also call them directly ExecuteStoreCommand(), ExecuteStoreQuery<>(). Same goes for functions and views but EF has a really odd way of calling functions "SELECT dbo.blah(#id)".
EF performs slower when it has to populate an Entity with deep hierarchy. be extremely careful with entities with deep hierarchy
Sometimes when you are requesting records and you are not required to modify them you should tell EF not to watch the property changes (AutoDetectChanges). that way record retrieval is much faster
Indexing of database is good but in case of EF it becomes very important. The columns you use for retrieval and sorting should be properly indexed.
When you model is large, VS2010/VS2012 Model designer gets real crazy. so break your model into medium sized models. There is a limitation that the Entities from different models cannot be shared even though they may be pointing to the same table in the database.
When you have to make changes in the same entity at different places, use the same entity, make changes and save it only once. The point is to AVOID retrieving the same record, make changes & save it multiple times. (Real performance gain tip).
When you need the info in only one or two columns try not to fetch the full entity. you can either execute your sql directly or have a mini entity something. You may need to cache some frequently used data in your application also.
Transactions are slow. be careful with them.
SQL Profiler or any query profiler is your friend. Run it when developing your application to see what does EF sends to database. When you perform a join using LINQ or Lambda expression in ur application, EF usually generates a Select-Where-In-Select style query which may not always perform well. If u find any such case, roll up ur sleeves, perform the join on DB and have EF retrieve results. (I forgot this one, the most important one!)
if you keep these things in mind EF should give almost similar performance as plain ADO.NET if not the same.

1. EF pulls all the records into memory then performs the query operation. How EF would behave when table has around ~1000 records?
That's not true! EF fetches only necessary records and queries are transformed into proper SQL statements. EF can cache objects locally within DataContext (and track all changes made to entities), but as long as you follow the rule to keep context open only when needed, it won't be a problem.
2. For simple edit I have to pull the record edit it and then push to db using SaveChanges()
It's true, but I would not bother in doing that unless you really see the performance problems. Because 1. is not true, you'll only get one record from DB fetched before it's saved. You can bypass that, by creating the SQL query as a string and sending it as a plain string.

EF translates your LINQ query into an SQL query, so it doesn't pull all records into memory. The generated SQL might not always be the most efficient, but a thousand records won't be a problem at all.
Yes, that's one way of doing it (assuming you only want to edit one record). If you are changing several records, you can get them all using one query and SaveChanges() will persist all of those changes.

EF is not a bad ORM framework. It is a different one with its own characteristics. Compare Microsoft Entity Framework 6, against say NetTiers which is powered by Microsoft Enterprise Library 6.
These are two entirely different beasts. The accepted answer is really good because it goes through the nuances of EF6. Whats key to understand is that each ORM has its own strengths and weaknesses. Compare the project requirements and its data access patterns against the ORM's behavior patterns.
For Example: NetTiers will always give you higher raw performance than EF6. However that is primarily because it is not a point and click ORM and as part and parcel of generating the ORM you will be optimizing your data model, adding custom stored procedures where relevant, etc... if you engineered your data model with the same effort for EF6 you could probably get close to the same performance.
Also consider can you modify the ORM? for example with NetTiers you can add extensions to the codesmith templates to include your own design patterns over and above what is generated by the base ORM library.
Also consider EF6 makes significant use of reflection whereas NetTiers or any library powered by Microsoft Enterprise Library will make heavy use of Generics instead. These are two entirely different approaches. Why so? Because EF6 is based on dynamic reflection whereas NetTiers is based on static reflection. Which is faster and which is better entirely depends on the usage patterns that will be required of the ORM.
Sometimes a hybrid approach works better: Consider for example EF6 for Web API OData endpoints, A few large tables wrapped with NetTiers & Microsoft Enterprise Library with custom stored procedures, and a few large masterdata tables wrapped with a custom built write through object cache where on initial load the record set is streamed into the memory cache using an ADO data reader.
These are all different and they all have their best fit scenarios: EF6, NetTiers, NHibernate, Wilson OR Mapper, XPO from Dev Express, etc...

There is no simple answer for your question. The main thing is about what you want to do with your data? And do you need so much data at one time?
EF translated your Queries to SQL so at this time there is no Object in Memory. When you get the data, then the selected records are in memory. If you are selecting a large amount of large objects then it can be a performance killer if you need to manipulate them all.
If you don't need to manipulate them all you can disable change tracking and enable it later for single objects you need to manipulate.
So you see it depends on your type of application.
If you need to manipulate a mass of data efficient, then don't use a OR-Mapper!
Otherwise EF is fine, but consider how many objects you really need at one time and what you want to do with them.

What's the purpose of Datasets?

I want to understand the purpose of datasets when we can directly communicate with the database using simple SQL statements.
Also, which way is better? Updating the data in dataset and then transfering them to the database at once or updating the database directly?

I want to understand the purpose of datasets when we can directly communicate with the database using simple SQL statements.
Why do you have food in your fridge, when you can just go directly to the grocery store every time you want to eat something? Because going to the grocery store every time you want a snack is extremely inconvenient.
The purpose of DataSets is to avoid directly communicating with the database using simple SQL statements. The purpose of a DataSet is to act as a cheap local copy of the data you care about so that you do not have to keep on making expensive high-latency calls to the database. They let you drive to the data store once, pick up everything you're going to need for the next week, and stuff it in the fridge in the kitchen so that its there when you need it.
Also, which way is better? Updating the data in dataset and then transfering them to the database at once or updating the database directly?
You order a dozen different products from a web site. Which way is better: delivering the items one at a time as soon as they become available from their manufacturers, or waiting until they are all available and shipping them all at once? The first way, you get each item as soon as possible; the second way has lower delivery costs. Which way is better? How the heck should we know? That's up to you to decide!
The data update strategy that is better is the one that does the thing in a way that better meets your customer's wants and needs. You haven't told us what your customer's metric for "better" is, so the question cannot be answered. What does your customer want -- the latest stuff as soon as it is available, or a low delivery fee?

Datasets support disconnected architecture. You can add local data, delete from it and then using SqlAdapter you can commit everything to the database. You can even load xml file directly into dataset. It really depends upon what your requirements are. You can even set in memory relations between tables in DataSet.
And btw, using direct sql queries embedded in your application is a really really bad and poor way of designing application. Your application will be prone to "Sql Injection". Secondly if you write queries like that embedded in application, Sql Server has to do it's execution plan everytime whereas Stored Procedures are compiled and it's execution is already decided when it is compiled. Also Sql server can change it's plan as the data gets large. You will get performance improvement by this. Atleast use stored procedures and validate junk input in that. They are inherently resistant to Sql Injection.
Stored Procedures and Dataset are the way to go.
See this diagram:
Edit: If you are into .Net framework 3.5, 4.0 you can use number of ORMs like Entity Framework, NHibernate, Subsonic. ORMs represent your business model more realistically. You can always use stored procedures with ORMs if some of the features are not supported into ORMs.
For Eg: If you are writing a recursive CTE (Common Table Expression) Stored procedures are very helpful. You will run into too much problems if you use Entity Framework for that.

This page explains in detail in which cases you should use a Dataset and in which cases you use direct access to the databases

I usually like to practice that, if I need to perform a bunch of analytical proccesses on a large set of data I will fill a dataset (or a datatable depending on the structure). That way it is a disconnected model from the database.
But for DML queries I prefer the quick hits directly to the database (preferably through stored procs). I have found this is the most efficient, and with well tuned queries it is not bad at all on the db.

What should I use for performance sensitive data access?

So I have an application which requires very fast access to large volumes of data and we're at the stage where we're undergoing a large re-design of the database, which gives a good opertunity to re-write the data access layer if nessersary!
Currently in our data access layer we use manually created entities along with plain SQL to fill them. This is pretty fast, but this technology is really getting old, and I'm concerned we're missing out on a newer framework or data access method which could be better in terms of neatness and maintainability.
We've seen the Entity Framework, but after some research it just seems that the benefit of the ORM it gives is not enough to justify the lower performance and as some of our queries are getting complex I'm sure performance with the EF would become more of an issue.
So it is a case of sticking with our current methods of data access, or is there something a bit neater than manually creating and maintaining entities?
I guess the thing that's bugging me is just opening our data layer solution and seeing lots of entities, all of which need to be maintained exactly in line with the database, which sometimes can be a lot of work, but then maybe this is the price we pay for performance?
Any ideas, comments and suggestions are very appreciated! :)
Thanks,
Andy.
** Update **
Forgot to mention that we really need to be able to handle using Azure (client requirements), which currently stops us from using stored procedures. ** Update 2 ** Actually we have an interface layer for our DAL which means we can created an Azure implementation which just override data access methods from the Local implementation which aren't suitable for Azure, so I guess we could just use stored procedures for performance sensitive local databases with EF for the cloud.

I would use an ORM layer (Entity Framework, NHibernate etc) for management of individual entities. For example, I would use the ORM / entities layers to allow users to make edits to entities. This is because thinking of your data as entities is conceptually simpler and the ORMs make it pretty easy to code this stuff without ever having to program any SQL.
For the bulk reporting side of things, I would definitely not use an ORM layer. I would probably create a separate class library specifically for standard reports, which creates SQL statements itself or calls sprocs. ORMs are not really for bulk reporting and you'll never get the same flexibility of querying through the ORM as through hand-coded SQL.

Stored procedures for performance. ORMs for ease of development
Do you feel up to troubleshooting some opaque generated SQL when it runs badly...? That generates several round trips where one would do? Or insists on using wrong datatypes?

You could try using mybatis (previously known as ibatis). It allows you to map sql statements to domain objects. This way you keep full control over SQL being executed and get cleanly defined domain model at the same time.

Don't rule out plain old ADO.NET. It may not be as hip as EF4, but it just works.
With ADO.NET you know what your SQL queries are going to look like because you get 100% control over them. ADO.NET forces developers to think about SQL instead of falling back on the ORM to do the magic.
If performance is high on your list, I'd be reluctant to take a dependency on any ORM especially EF which is new on the scene and highly complex. ORM's speed up development (a little) but are going to make your SQL query performance hard to predict, and in most cases slower than hand rolled SQL/Stored Procs.
You can also unit test SQL/Stored Procs independently of the application and therefore isolate performance issues as either DB/query related or application related.
I guess you are using ADO.NET in your DAL already, so I'd suggest investing the time and effort in refactoring it rather than throwing it out.

pluggable data store architectures

I have a pluggable system management tool. The architecture of this kind of thing is well understood (interfaces, publish/ subscribe, ....). How about the data store though. What do people do?
I need plugins to be able to add new entities, extend existing entities, establish new relationships, etc.
My thoughts (SQL), not necessarily well thought out
each plugin simply extends the schema when they are installed. In the old days changing the schema was a big no-no; now databases are very relaxed about this
plugins have their own tables. If 2 of them have an entity (say) person, then there are 2 tables p1_person and p2_person
plugins have their own database
invent some sort of flexible scheme where the tables are softly typed. Maybe many attributes packed into a single attribute. The ultimate is to have one big table called data, with key of table name & column name and a single data value.
Not SQL
object DB. I have no experience with these. Anybody care to pass on experience. db4o for example. Can I change the 'schema' of objects as the app evolves
NO-SQL
this is 'where its at' at the moment. Most of these seem to be aimed slightly differently than my needs. Anybody want to pass on experience with these
Apologies for the open ended question

My suggestion is go read about the entity framework
a lot of the situations you are describing can be solved (very elegantly) using table inheritance.
Your idea of one big table called data makes the hamsters in my computer cry ;)
The general trend is away from weakly typed schemas because they cannot be debugged at compile time. What you get from something like entity framework is a strongly typed extenislbe schema that you can code against using linq.
Object databases:
like you i havent played with them massivley - however the time when i was considering them was a time when there was no good ORM for .net and writing ado.net code was slowly killing me.
as for NO-SQL these are databases that meet a performance need. SQL performs badly in situations here there are lots of small writes occuring. I say badly tounge in cheek - it performs very well but when you scale to millions of concurrent users everything changes. My understanding of no sql is that it is a non rationalised format designed for lots of small fast writes and reads. The scale of sites that use these is usually very large.
OK - in response
I am currently lucky enough to be on a green field project so i am using EF to generate my schema.
On non greenfield projects I use sql scripts to update my table structures. As for implementing table inheritance in sql its very easy once you know the concept, its essentially a one to many relationship with a constraint that it will only ever be 0-1.
I wouldn't write .net code that updates the database structure ... that sounds like a disaster waiting to happen to me.
Beginning to think i have misunderstood what you are looking for. I find databases to be second nature as I have spent so long with them.
I haven't found a replacement for being meticulous about script management.