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  • How to have a where clause on an insert or an update in Linq to Sql?

    - by Kelsey
    I am trying to convert the following stored proc to a LinqToSql call (this is a simplied version of the SQL): INSERT INTO [MyTable] ([Name], [Value]) SELECT @name, @value WHERE NOT EXISTS(SELECT [Value] FROM [MyTable] WHERE [Value] = @value) The DB does not have a constraint on the field that is getting checked for so in this specific case the check needs to be made manually. Also there are many items constantly being inserted as well so I need to make sure that when this specific insert happens there is no dupe of the value field. My first hunch is to do the following: using (TransactionScope scope = new TransactionScope()) { if (Context.MyTables.SingleOrDefault(t => t.Value == in.Value) != null) { MyLinqModels.MyTable t = new MyLinqModels.MyTable() { Name = in.Name, Value = in.Value }; // Do some stuff in the transaction scope.Complete(); } } This is the first time I have really run into this scenario so I want to make sure I am going about it the right way. Does this seem correct or can anyone suggest a better way of going about it without having two seperate calls? Edit: I am running into a similar issue with an update: UPDATE [AnotherTable] SET [Code] = @code WHERE [ID] = @id AND [Code] IS NULL How would I do the same check with Linqtosql? I assume I need to do a get and then set all the values and submit but what if someone updates [Code] to something other than null from the time I do the get to when the update executes? Same problem as the insert...

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  • Same data being returned by linq for 2 different executions of a stored procedure?

    - by Paul
    Hello I have a stored procedure that I am calling through Entity Framework. The stored procedure has 2 date parameters. I supply different argument in the 2 times I call the stored procedure. I have verified using SQL Profiler that the stored procedure is being called correctly and returning the correct results. When I call my method the second time with different arguments, even though the stored procedure is bringing back the correct results, the table created contains the same data as the first time I called it. dtStart = 01/08/2009 dtEnd = 31/08/2009 public List<dataRecord> GetData(DateTime dtStart, DateTime dtEnd) { var tbl = from t in db.SP(dtStart, dtEnd) select t; return tbl.ToList(); } GetData((new DateTime(2009, 8, 1), new DateTime(2009, 8, 31)) // tbl.field1 value = 45450 - CORRECT GetData(new DateTime(2009, 7, 1), new DateTime(2009, 7, 31)) // tbl.field1 value = 45450 - WRONG 27456 expected Is this a case of Entity Framework being clever and caching? I can't see why it would cache this though as it has executed the stored procedure twice. Do I have to do something to close tbl? using Visual Studio 2008 + Entity Framework. I also get the message "query cannot be enumerated more than once" a few times every now and then, am not sure if that is relevant? FULL CODE LISTING namespace ProfileDataService { public partial class DataService { public static List<MeterTotalConsumpRecord> GetTotalAllTimesConsumption(DateTime dtStart, DateTime dtEnd, EUtilityGroup ug, int nMeterSelectionType, int nCustomerID, int nUserID, string strSelection, bool bClosedLocations, bool bDisposedLocations) { dbChildDataContext db = DBManager.ChildDataConext(nCustomerID); var tbl = from t in db.GetTotalConsumptionByMeter(dtStart, dtEnd, (int) ug, nMeterSelectionType, nCustomerID, nUserID, strSelection, bClosedLocations, bDisposedLocations, 1) select t; return tbl.ToList(); } } } /// CALLER List<MeterTotalConsumpRecord> _P1Totals; List<MeterTotalConsumpRecord> _P2Totals; public void LoadData(int nUserID, int nCustomerID, ELocationSelectionMethod locationSelectionMethod, string strLocations, bool bIncludeClosedLocations, bool bIncludeDisposedLocations, DateTime dtStart, DateTime dtEnd, ReportsBusinessLogic.Lists.EPeriodType durMainPeriodType, ReportsBusinessLogic.Lists.EPeriodType durCompareToPeriodType, ReportsBusinessLogic.Lists.EIncreaseReportType rptType, bool bIncludeDecreases) { ///Code for setting properties using parameters.. _P2Totals = ProfileDataService.DataService.GetTotalAllTimesConsumption(_P2StartDate, _P2EndDate, EUtilityGroup.Electricity, 1, nCustomerID, nUserID, strLocations, bIncludeClosedLocations, bIncludeDisposedLocations); _P1Totals = ProfileDataService.DataService.GetTotalAllTimesConsumption(_StartDate, _EndDate, EUtilityGroup.Electricity, 1, nCustomerID, nUserID, strLocations, bIncludeClosedLocations, bIncludeDisposedLocations); PopulateLines() //This fills up a list of objects with information for my report ready for the totals to be added PopulateTotals(_P1Totals, 1); PopulateTotals(_P2Totals, 2); } void PopulateTotals(List<MeterTotalConsumpRecord> objTotals, int nPeriod) { MeterTotalConsumpRecord objMeterConsumption = null; foreach (IncreaseReportDataRecord objLine in _Lines) { objMeterConsumption = objTotals.Find(delegate(MeterTotalConsumpRecord t) { return t.MeterID == objLine.MeterID; }); if (objMeterConsumption != null) { if (nPeriod == 1) { objLine.P1Consumption = (double)objMeterConsumption.Consumption; } else { objLine.P2Consumption = (double)objMeterConsumption.Consumption; } objMeterConsumption = null; } } } }

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  • Should I invest time in learning about OR\M or LINQ?

    - by Peter Smith
    I'm a .NET web developer primarily who occasionally writes console applications to mine data, cleanup tasks, etc. Most of what I do winds up involving a database which I currently design via sql server management studio, using stored procedures, and query analyzer. I also create a lot of web services which are consumed via AJAX applications. Do these technologies really help you in speeding up development times? Do you still have to build the database or object code first?

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  • Why does LINQ-to-SQL Paging fail inside a function?

    - by ssg
    Here I have an arbitrary IEnumerable<T>. And I'd like to page it using a generic helper function instead of writing Skip/Take pairs every time. Here is my function: IEnumerable<T> GetPagedResults<T>(IEnumerable<T> query, int pageIndex, int pageSize) { return query.Skip((pageIndex - 1) * pageSize).Take(pageSize); } And my code is: result = GetPagedResults(query, 1, 10).ToList(); This produces a SELECT statement without TOP 10 keyword. But this code below produces the SELECT with it: result = query.Skip((pageIndex - 1) * pageSize).Take(pageSize).ToList(); What am I doing wrong in the function?

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  • How to join results from two different sets in LINQ?

    - by Inez
    Hi, I get some data about customers in my database with this method: public List<KlientViewModel> GetListOfKlientViewModel() { List<KlientViewModel> list = _klientRepository.List().Select(k => new KlientViewModel { Id = k.Id, Imie = k.Imie, Nazwisko = k.Nazwisko, Nazwa = k.Nazwa, SposobPlatnosci = k.SposobPlatnosci, }).ToList(); return list; } but also I have another method which counts value for extra field in KlientViewModel - field called 'Naleznosci'. I have another method which counts value for this field based on customers ids, it looks like this: public Dictionary<int, decimal> GetNaleznosc(List<int> klientIds) { return klientIds.ToDictionary(klientId => klientId, klientId => (from z in _zdarzenieRepository.List() from c in z.Klient.Cennik where z.TypZdarzenia == (int) TypyZdarzen.Sprzedaz && z.IdTowar == c.IdTowar && z.Sprzedaz.Data >= c.Od && (z.Sprzedaz.Data < c.Do || c.Do == null) && z.Klient.Id == klientId select z.Ilosc*(z.Kwota > 0 ? z.Kwota : c.Cena)).Sum() ?? 0); } So what I want to do is to join data from method GetNaleznosc with data generated in method GetListOfKlientViewModel. I call GetNaleznosc like this: GetNaleznosc(list.Select(k => k.Id).ToList()) but don't know what to do next.

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  • How can I load class's part using linq to sql without anonymous class or additional class?

    - by ais
    class Test { int Id{get;set;} string Name {get;set;} string Description {get;set;} } //1)ok context.Tests.Select(t => new {t.Id, t.Name}).ToList().Select(t => new Test{Id = t.Id, Name = t.Name}); //2)ok class TestPart{ int Id{get;set;} string Name {get;set;} } context.Tests.Select(t => new TestPart{Id = t.Id, Name = t.Name}).ToList().Select(t => new Test{Id = t.Id, Name = t.Name}); //3)error Explicit construction of entity type 'Test' in query is not allowed. context.Tests.Select(t => new Test{Id = t.Id, Name = t.Name}).ToList(); Is there any way to use third variant?

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  • How can I do more than one level of cascading deletes in Linq?

    - by Gary McGill
    If I have a Customers table linked to an Orders table, and I want to delete a customer and its corresponding orders, then I can do: dataContext.Orders.DeleteAllOnSubmit(customer.Orders); dataContext.Customers.DeleteOnSubmit(customer); ...which is great. However, what if I also have an OrderItems table, and I want to delete the order items for each of the orders deleted? I can see how I could use DeleteAllOnSubmit to cause the deletion of all the order items for a single order, but how can I do it for all the orders?

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  • I want to get 2 values returned by my query. How to do, using linq-to-entity

    - by Shantanu Gupta
    var dept_list = (from map in DtMapGuestDepartment.AsEnumerable() where map.Field<Nullable<long>>("GUEST_ID") == DRowGuestPI.Field<Nullable<long>>("PK_GUEST_ID") join dept in DtDepartment.AsEnumerable() on map.Field<Nullable<long>>("DEPARTMENT_ID") equals dept.Field<Nullable<long>>("DEPARTMENT_ID") select new { dept_id=dept.Field<long>("DEPARTMENT_ID") ,dept_name=dept.Field<long>("DEPARTMENT_NAME") }).Distinct(); DataTable dt = new DataTable(); dt.Columns.Add("DEPARTMENT_ID"); dt.Columns.Add("DEPARTMENT_NAME"); foreach (long? dept_ in dept_list) { dt.Rows.Add(dept_[0], dept_[1]); } EDIT In the previous question asked by me. I got an answer like this for single value. What is the difference between the two ? foreach (long? dept in dept_list) { dt.Rows.Add(dept); }

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  • What is the difference between these two LINQ statements?

    - by jamone
    I had the 1nd statement in my code and found it not giving an accurate count, it was returning 1 when the correct answer is 18. To try and debug the problem I broke it out creating the 2nd statement here and the count returns 18. I just don't see what the difference is between these two. It seems like the 1st is just more compact. I'm currently running these two statements back to back and I'm sure that the database isn't changing between the two. int count = (from s in surveysThisQuarter where s.FacilityID == facility.LocationID select s.Deficiencies).Count(); vs var tempSurveys = from s in surveysThisQuarter where s.FacilityID == facility.LocationID select s; int count = 0; foreach (Survey s in tempSurveys) count += s.Deficiencies.Count();

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  • is there a better way to write this frankenstein LINQ query that searches for values in a child tabl

    - by MRV
    I have a table of Users and a one to many UserSkills table. I need to be able to search for users based on skills. This query takes a list of desired skills and searches for users who have those skills. I want to sort the users based on the number of desired skills they posses. So if a users only has 1 of 3 desired skills he will be further down the list than the user who has 3 of 3 desired skills. I start with my comma separated list of skill IDs that are being searched for: List<short> searchedSkillsRaw = skills.Value.Split(',').Select(i => short.Parse(i)).ToList(); I then filter out only the types of users that are searchable: List<User> users = (from u in db.Users where u.Verified == true && u.Level > 0 && u.Type == 1 && (u.UserDetail.City == city.SelectedValue || u.UserDetail.City == null) select u).ToList(); and then comes the crazy part: var fUsers = from u in users select new { u.Id, u.FirstName, u.LastName, u.UserName, UserPhone = u.UserDetail.Phone, UserSkills = (from uskills in u.UserSkills join skillsJoin in configSkills on uskills.SkillId equals skillsJoin.ValueIdInt into tempSkills from skillsJoin in tempSkills.DefaultIfEmpty() where uskills.UserId == u.Id select new { SkillId = uskills.SkillId, SkillName = skillsJoin.Name, SkillNameFound = searchedSkillsRaw.Contains(uskills.SkillId) }), UserSkillsFound = (from uskills in u.UserSkills where uskills.UserId == u.Id && searchedSkillsRaw.Contains(uskills.SkillId) select uskills.UserId).Count() } into userResults where userResults.UserSkillsFound > 0 orderby userResults.UserSkillsFound descending select userResults; and this works! But it seems super bloated and inefficient to me. Especially the secondary part that counts the number of skills found. Thanks for any advice you can give. --r

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  • How can i have different LINQ to XML quries based on two different condition?

    - by Subhen
    Hi , We want the query result should be assigned with two results based on some condition like following: var vAudioData = (from xAudioinfo in xResponse.Descendants(ns + "DIDL-Lite").Elements(ns + "item") if((xAudioinfo.Element(upnp + "artist")!=null) { select new RMSMedia { strAudioTitle = ((string)xAudioinfo.Element(dc + "title")).Trim() }; } else select new RMSMedia { strGen = ((string)xAudioinfo.Element(dc + "Gen")).Trim() }; The VarAudioData should contain both if and else condition values. I have added the if condition just to project , what is my needs, m quite sure though that we can not use if and else. Please help if there are any other approach to accomplish this. Thanks, Subhen

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  • Is a full list returned first and then filtered when using linq to sql to filter data from a databas

    - by RJ
    This is probably a very simple question that I am working through in an MVC project. Here's an example of what I am talking about. I have an rdml file linked to a database with a table called Users that has 500,000 rows. But I only want to find the Users who were entered on 5/7/2010. So let's say I do this in my UserRepository: from u in db.GetUsers() where u.CreatedDate = "5/7/2010" select u (doing this from memory so don't kill me if my syntax is a little off, it's the concept I am looking for) Does this statement first return all 500,000 rows and then filter it or does it only bring back the filtered list?

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  • How to avoid geometric slowdown with large Linq transactions?

    - by Shaul
    I've written some really nice, funky libraries for use in LinqToSql. (Some day when I have time to think about it I might make it open source... :) ) Anyway, I'm not sure if this is related to my libraries or not, but I've discovered that when I have a large number of changed objects in one transaction, and then call DataContext.GetChangeSet(), things start getting reaalllly slooowwwww. When I break into the code, I find that my program is spinning its wheels doing an awful lot of Equals() comparisons between the objects in the change set. I can't guarantee this is true, but I suspect that if there are n objects in the change set, then the call to GetChangeSet() is causing every object to be compared to every other object for equivalence, i.e. at best (n^2-n)/2 calls to Equals()... Yes, of course I could commit each object separately, but that kinda defeats the purpose of transactions. And in the program I'm writing, I could have a batch job containing 100,000 separate items, that all need to be committed together. Around 5 billion comparisons there. So the question is: (1) is my assessment of the situation correct? Do you get this behavior in pure, textbook LinqToSql, or is this something my libraries are doing? And (2) is there a standard/reasonable workaround so that I can create my batch without making the program geometrically slower with every extra object in the change set?

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  • How to get the value of an XML element using Linq even when empty.

    - by Yeodave
    Please excuse my stupidity, I tend to find the traversing XML overly complicated. I am using ASP.NET in VB. I have an XML document which contains all the details of staff in my company... <staff> <staffName>Test Staff</staffName> <staffTitle>Slave</staffTitle> <staffDepartmentName>Finance</staffDepartmentName> <staffOffice>London</staffOffice> <staffEmail>[email protected]</staffEmail> <staffPhone>0207 123 456</staffPhone> <staffNotes>Working hours Mon to Thurs 9.15 - 5.15</staffNotes> <staffBio></staffBio> </staff> As you can see, some nodes do not always contain data for ever member of staff; only Directors have biographies. I access the values like this... For Each staff In ( _ From matches In myXMLFile.Descendants("staff").Descendants("staffName") _ Where matches.Nodes(0).ToString.ToLower.Contains(LCase(search)) _ Order By matches.Value _ Select matches) staffName = staff.Descendants("staffName").Nodes(0).ToString) staffTitle = staff.Descendants("staffTitle").Nodes(0).ToString) staffOffice = staff.Descendants("staffOffice").Nodes(0).ToString) staffEmail = staff.Descendants("staffEmail").Nodes(0).ToString) staffPhone = staff.Descendants("staffPhone").Nodes(0).ToString) staffNotes = staff.Descendants("staffNotes").Nodes(0).ToString) staffBio = staff.Descendants("staffBio").Nodes(0).ToString) ' Do something with that data... Next Once it gets to staffBio I get an error saying "Object reference not set to an instance of an object." obviously because that node does not exist. My question is how can I assign the value to a variable even when it is empty without having to do a conditional check before each assignment?

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  • Howto use predicates in LINQ to Entities for Entity Framework objects

    - by user274947
    I'm using LINQ to Entities for Entity Framework objects in my Data Access Layer. My goal is to filter as much as I can from the database, without applying filtering logic on in-memory results. For that purpose Business Logic Layer passes a predicate to Data Access Layer. I mean Func<MyEntity, bool> So, if I use this predicate directly, like public IQueryable<MyEntity> GetAllMatchedEntities(Func<MyEntity, Boolean> isMatched) { return qry = _Context.MyEntities.Where(x => isMatched(x)); } I'm getting the exception [System.NotSupportedException] --- {"The LINQ expression node type 'Invoke' is not supported in LINQ to Entities."} Solution in that question suggests to use AsExpandable() method from LINQKit library. But again, using public IQueryable<MyEntity> GetAllMatchedEntities(Func<MyEntity, Boolean> isMatched) { return qry = _Context.MyEntities.AsExpandable().Where(x => isMatched(x)); } I'm getting the exception Unable to cast object of type 'System.Linq.Expressions.FieldExpression' to type 'System.Linq.Expressions.LambdaExpression' Is there way to use predicate in LINQ to Entities query for Entity Framework objects, so that it is correctly transformed it into a SQL statement. Thank you.

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  • LINQ to SQL - Lightweight O/RM?

    - by CoffeeAddict
    I've heard from some that LINQ to SQL is good for lightweight apps. But then I see LINQ to SQL being used for Stackoverflow, and a bunch of other .coms I know (from interviewing with them). Ok, so is this true? for an e-commerce site that's bringing in millions and you're typically only doing basic CRUDs most the time with the exception of an occasional stored proc for something more complex, is LINQ to SQL complete enough and performance-wise good enough or able to be tweaked enough to run happily on an e-commerce site? I've heard that you just need to tweak performance on the DB side when using LINQ to SQL for a better approach. So there are really 2 questions here: 1) Meaning/scope/definition of a "Lightweight" O/RM solution: What the heck does "lightweight" mean when people say LINQ to SQL is a "lightweight O/RM" and is that true??? If this is so lightweight then why do I see a bunch of huge .coms using it? Is it good enough to run major .coms (obviously it looks like it is) and what determines what the context of "lightweight" is...it's such a generic statement. 2) Performance: I'm working on my own .com and researching different O/RMs. I'm not really looking at the Entity Framework (yet), just want to figure out the LINQ to SQL basics here and determine if it will be efficient enough for me. The problem I think is you can't tweak or control the SQL it generates...

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  • StreamInsight 2.1, meet LINQ

    - by Roman Schindlauer
    Someone recently called LINQ “magic” in my hearing. I leapt to LINQ’s defense immediately. Turns out some people don’t realize “magic” is can be a pejorative term. I thought LINQ needed demystification. Here’s your best demystification resource: http://blogs.msdn.com/b/mattwar/archive/2008/11/18/linq-links.aspx. I won’t repeat much of what Matt Warren says in his excellent series, but will talk about some core ideas and how they affect the 2.1 release of StreamInsight. Let’s tell the story of a LINQ query. Compile time It begins with some code: IQueryable<Product> products = ...; var query = from p in products             where p.Name == "Widget"             select p.ProductID; foreach (int id in query) {     ... When the code is compiled, the C# compiler (among other things) de-sugars the query expression (see C# spec section 7.16): ... var query = products.Where(p => p.Name == "Widget").Select(p => p.ProductID); ... Overload resolution subsequently binds the Queryable.Where<Product> and Queryable.Select<Product, int> extension methods (see C# spec sections 7.5 and 7.6.5). After overload resolution, the compiler knows something interesting about the anonymous functions (lambda syntax) in the de-sugared code: they must be converted to expression trees, i.e.,“an object structure that represents the structure of the anonymous function itself” (see C# spec section 6.5). The conversion is equivalent to the following rewrite: ... var prm1 = Expression.Parameter(typeof(Product), "p"); var prm2 = Expression.Parameter(typeof(Product), "p"); var query = Queryable.Select<Product, int>(     Queryable.Where<Product>(         products,         Expression.Lambda<Func<Product, bool>>(Expression.Property(prm1, "Name"), prm1)),         Expression.Lambda<Func<Product, int>>(Expression.Property(prm2, "ProductID"), prm2)); ... If the “products” expression had type IEnumerable<Product>, the compiler would have chosen the Enumerable.Where and Enumerable.Select extension methods instead, in which case the anonymous functions would have been converted to delegates. At this point, we’ve reduced the LINQ query to familiar code that will compile in C# 2.0. (Note that I’m using C# snippets to illustrate transformations that occur in the compiler, not to suggest a viable compiler design!) Runtime When the above program is executed, the Queryable.Where method is invoked. It takes two arguments. The first is an IQueryable<> instance that exposes an Expression property and a Provider property. The second is an expression tree. The Queryable.Where method implementation looks something like this: public static IQueryable<T> Where<T>(this IQueryable<T> source, Expression<Func<T, bool>> predicate) {     return source.Provider.CreateQuery<T>(     Expression.Call(this method, source.Expression, Expression.Quote(predicate))); } Notice that the method is really just composing a new expression tree that calls itself with arguments derived from the source and predicate arguments. Also notice that the query object returned from the method is associated with the same provider as the source query. By invoking operator methods, we’re constructing an expression tree that describes a query. Interestingly, the compiler and operator methods are colluding to construct a query expression tree. The important takeaway is that expression trees are built in one of two ways: (1) by the compiler when it sees an anonymous function that needs to be converted to an expression tree, and; (2) by a query operator method that constructs a new queryable object with an expression tree rooted in a call to the operator method (self-referential). Next we hit the foreach block. At this point, the power of LINQ queries becomes apparent. The provider is able to determine how the query expression tree is evaluated! The code that began our story was intentionally vague about the definition of the “products” collection. Maybe it is a queryable in-memory collection of products: var products = new[]     { new Product { Name = "Widget", ProductID = 1 } }.AsQueryable(); The in-memory LINQ provider works by rewriting Queryable method calls to Enumerable method calls in the query expression tree. It then compiles the expression tree and evaluates it. It should be mentioned that the provider does not blindly rewrite all Queryable calls. It only rewrites a call when its arguments have been rewritten in a way that introduces a type mismatch, e.g. the first argument to Queryable.Where<Product> being rewritten as an expression of type IEnumerable<Product> from IQueryable<Product>. The type mismatch is triggered initially by a “leaf” expression like the one associated with the AsQueryable query: when the provider recognizes one of its own leaf expressions, it replaces the expression with the original IEnumerable<> constant expression. I like to think of this rewrite process as “type irritation” because the rewritten leaf expression is like a foreign body that triggers an immune response (further rewrites) in the tree. The technique ensures that only those portions of the expression tree constructed by a particular provider are rewritten by that provider: no type irritation, no rewrite. Let’s consider the behavior of an alternative LINQ provider. If “products” is a collection created by a LINQ to SQL provider: var products = new NorthwindDataContext().Products; the provider rewrites the expression tree as a SQL query that is then evaluated by your favorite RDBMS. The predicate may ultimately be evaluated using an index! In this example, the expression associated with the Products property is the “leaf” expression. StreamInsight 2.1 For the in-memory LINQ to Objects provider, a leaf is an in-memory collection. For LINQ to SQL, a leaf is a table or view. When defining a “process” in StreamInsight 2.1, what is a leaf? To StreamInsight a leaf is logic: an adapter, a sequence, or even a query targeting an entirely different LINQ provider! How do we represent the logic? Remember that a standing query may outlive the client that provisioned it. A reference to a sequence object in the client application is therefore not terribly useful. But if we instead represent the code constructing the sequence as an expression, we can host the sequence in the server: using (var server = Server.Connect(...)) {     var app = server.Applications["my application"];     var source = app.DefineObservable(() => Observable.Range(0, 10, Scheduler.NewThread));     var query = from i in source where i % 2 == 0 select i; } Example 1: defining a source and composing a query Let’s look in more detail at what’s happening in example 1. We first connect to the remote server and retrieve an existing app. Next, we define a simple Reactive sequence using the Observable.Range method. Notice that the call to the Range method is in the body of an anonymous function. This is important because it means the source sequence definition is in the form of an expression, rather than simply an opaque reference to an IObservable<int> object. The variation in Example 2 fails. Although it looks similar, the sequence is now a reference to an in-memory observable collection: var local = Observable.Range(0, 10, Scheduler.NewThread); var source = app.DefineObservable(() => local); // can’t serialize ‘local’! Example 2: error referencing unserializable local object The Define* methods support definitions of operator tree leaves that target the StreamInsight server. These methods all have the same basic structure. The definition argument is a lambda expression taking between 0 and 16 arguments and returning a source or sink. The method returns a proxy for the source or sink that can then be used for the usual style of LINQ query composition. The “define” methods exploit the compile-time C# feature that converts anonymous functions into translatable expression trees! Query composition exploits the runtime pattern that allows expression trees to be constructed by operators taking queryable and expression (Expression<>) arguments. The practical upshot: once you’ve Defined a source, you can compose LINQ queries in the familiar way using query expressions and operator combinators. Notably, queries can be composed using pull-sequences (LINQ to Objects IQueryable<> inputs), push sequences (Reactive IQbservable<> inputs), and temporal sequences (StreamInsight IQStreamable<> inputs). You can even construct processes that span these three domains using “bridge” method overloads (ToEnumerable, ToObservable and To*Streamable). Finally, the targeted rewrite via type irritation pattern is used to ensure that StreamInsight computations can leverage other LINQ providers as well. Consider the following example (this example depends on Interactive Extensions): var source = app.DefineEnumerable((int id) =>     EnumerableEx.Using(() =>         new NorthwindDataContext(), context =>             from p in context.Products             where p.ProductID == id             select p.ProductName)); Within the definition, StreamInsight has no reason to suspect that it ‘owns’ the Queryable.Where and Queryable.Select calls, and it can therefore defer to LINQ to SQL! Let’s use this source in the context of a StreamInsight process: var sink = app.DefineObserver(() => Observer.Create<string>(Console.WriteLine)); var query = from name in source(1).ToObservable()             where name == "Widget"             select name; using (query.Bind(sink).Run("process")) {     ... } When we run the binding, the source portion which filters on product ID and projects the product name is evaluated by SQL Server. Outside of the definition, responsibility for evaluation shifts to the StreamInsight server where we create a bridge to the Reactive Framework (using ToObservable) and evaluate an additional predicate. It’s incredibly easy to define computations that span multiple domains using these new features in StreamInsight 2.1! Regards, The StreamInsight Team

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  • C#: LINQ vs foreach - Round 1.

    - by James Michael Hare
    So I was reading Peter Kellner's blog entry on Resharper 5.0 and its LINQ refactoring and thought that was very cool.  But that raised a point I had always been curious about in my head -- which is a better choice: manual foreach loops or LINQ?    The answer is not really clear-cut.  There are two sides to any code cost arguments: performance and maintainability.  The first of these is obvious and quantifiable.  Given any two pieces of code that perform the same function, you can run them side-by-side and see which piece of code performs better.   Unfortunately, this is not always a good measure.  Well written assembly language outperforms well written C++ code, but you lose a lot in maintainability which creates a big techncial debt load that is hard to offset as the application ages.  In contrast, higher level constructs make the code more brief and easier to understand, hence reducing technical cost.   Now, obviously in this case we're not talking two separate languages, we're comparing doing something manually in the language versus using a higher-order set of IEnumerable extensions that are in the System.Linq library.   Well, before we discuss any further, let's look at some sample code and the numbers.  First, let's take a look at the for loop and the LINQ expression.  This is just a simple find comparison:       // find implemented via LINQ     public static bool FindViaLinq(IEnumerable<int> list, int target)     {         return list.Any(item => item == target);     }         // find implemented via standard iteration     public static bool FindViaIteration(IEnumerable<int> list, int target)     {         foreach (var i in list)         {             if (i == target)             {                 return true;             }         }           return false;     }   Okay, looking at this from a maintainability point of view, the Linq expression is definitely more concise (8 lines down to 1) and is very readable in intention.  You don't have to actually analyze the behavior of the loop to determine what it's doing.   So let's take a look at performance metrics from 100,000 iterations of these methods on a List<int> of varying sizes filled with random data.  For this test, we fill a target array with 100,000 random integers and then run the exact same pseudo-random targets through both searches.                       List<T> On 100,000 Iterations     Method      Size     Total (ms)  Per Iteration (ms)  % Slower     Any         10       26          0.00046             30.00%     Iteration   10       20          0.00023             -     Any         100      116         0.00201             18.37%     Iteration   100      98          0.00118             -     Any         1000     1058        0.01853             16.78%     Iteration   1000     906         0.01155             -     Any         10,000   10,383      0.18189             17.41%     Iteration   10,000   8843        0.11362             -     Any         100,000  104,004     1.8297              18.27%     Iteration   100,000  87,941      1.13163             -   The LINQ expression is running about 17% slower for average size collections and worse for smaller collections.  Presumably, this is due to the overhead of the state machine used to track the iterators for the yield returns in the LINQ expressions, which seems about right in a tight loop such as this.   So what about other LINQ expressions?  After all, Any() is one of the more trivial ones.  I decided to try the TakeWhile() algorithm using a Count() to get the position stopped like the sample Pete was using in his blog that Resharper refactored for him into LINQ:       // Linq form     public static int GetTargetPosition1(IEnumerable<int> list, int target)     {         return list.TakeWhile(item => item != target).Count();     }       // traditionally iterative form     public static int GetTargetPosition2(IEnumerable<int> list, int target)     {         int count = 0;           foreach (var i in list)         {             if(i == target)             {                 break;             }               ++count;         }           return count;     }   Once again, the LINQ expression is much shorter, easier to read, and should be easier to maintain over time, reducing the cost of technical debt.  So I ran these through the same test data:                       List<T> On 100,000 Iterations     Method      Size     Total (ms)  Per Iteration (ms)  % Slower     TakeWhile   10       41          0.00041             128%     Iteration   10       18          0.00018             -     TakeWhile   100      171         0.00171             88%     Iteration   100      91          0.00091             -     TakeWhile   1000     1604        0.01604             94%     Iteration   1000     825         0.00825             -     TakeWhile   10,000   15765       0.15765             92%     Iteration   10,000   8204        0.08204             -     TakeWhile   100,000  156950      1.5695              92%     Iteration   100,000  81635       0.81635             -     Wow!  I expected some overhead due to the state machines iterators produce, but 90% slower?  That seems a little heavy to me.  So then I thought, well, what if TakeWhile() is not the right tool for the job?  The problem is TakeWhile returns each item for processing using yield return, whereas our for-loop really doesn't care about the item beyond using it as a stop condition to evaluate. So what if that back and forth with the iterator state machine is the problem?  Well, we can quickly create an (albeit ugly) lambda that uses the Any() along with a count in a closure (if a LINQ guru knows a better way PLEASE let me know!), after all , this is more consistent with what we're trying to do, we're trying to find the first occurence of an item and halt once we find it, we just happen to be counting on the way.  This mostly matches Any().       // a new method that uses linq but evaluates the count in a closure.     public static int TakeWhileViaLinq2(IEnumerable<int> list, int target)     {         int count = 0;         list.Any(item =>             {                 if(item == target)                 {                     return true;                 }                   ++count;                 return false;             });         return count;     }     Now how does this one compare?                         List<T> On 100,000 Iterations     Method         Size     Total (ms)  Per Iteration (ms)  % Slower     TakeWhile      10       41          0.00041             128%     Any w/Closure  10       23          0.00023             28%     Iteration      10       18          0.00018             -     TakeWhile      100      171         0.00171             88%     Any w/Closure  100      116         0.00116             27%     Iteration      100      91          0.00091             -     TakeWhile      1000     1604        0.01604             94%     Any w/Closure  1000     1101        0.01101             33%     Iteration      1000     825         0.00825             -     TakeWhile      10,000   15765       0.15765             92%     Any w/Closure  10,000   10802       0.10802             32%     Iteration      10,000   8204        0.08204             -     TakeWhile      100,000  156950      1.5695              92%     Any w/Closure  100,000  108378      1.08378             33%     Iteration      100,000  81635       0.81635             -     Much better!  It seems that the overhead of TakeAny() returning each item and updating the state in the state machine is drastically reduced by using Any() since Any() iterates forward until it finds the value we're looking for -- for the task we're attempting to do.   So the lesson there is, make sure when you use a LINQ expression you're choosing the best expression for the job, because if you're doing more work than you really need, you'll have a slower algorithm.  But this is true of any choice of algorithm or collection in general.     Even with the Any() with the count in the closure it is still about 30% slower, but let's consider that angle carefully.  For a list of 100,000 items, it was the difference between 1.01 ms and 0.82 ms roughly in a List<T>.  That's really not that bad at all in the grand scheme of things.  Even running at 90% slower with TakeWhile(), for the vast majority of my projects, an extra millisecond to save potential errors in the long term and improve maintainability is a small price to pay.  And if your typical list is 1000 items or less we're talking only microseconds worth of difference.   It's like they say: 90% of your performance bottlenecks are in 2% of your code, so over-optimizing almost never pays off.  So personally, I'll take the LINQ expression wherever I can because they will be easier to read and maintain (thus reducing technical debt) and I can rely on Microsoft's development to have coded and unit tested those algorithm fully for me instead of relying on a developer to code the loop logic correctly.   If something's 90% slower, yes, it's worth keeping in mind, but it's really not until you start get magnitudes-of-order slower (10x, 100x, 1000x) that alarm bells should really go off.  And if I ever do need that last millisecond of performance?  Well then I'll optimize JUST THAT problem spot.  To me it's worth it for the readability, speed-to-market, and maintainability.

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  • Convert IEnumerable to EntitySet

    - by Gregorius
    Hey all, Hoping somebody can shed some light, and perhaps a possible solution to this issue I'm having... I have used LINQ to SQL to pull some data from a database into local entities. They are products from a shopping cart system. A product can contain a collection of KitGroups (which are stored in an EntitySet (System.Data.Linq.EntitySet). KitGroups contain collections of KitItems, and KitItems can contain Nested Products (which link back up to the original Product type - so its recursive). From these entities I'm building XML using LINQ to XML - all good here - my XML looks beautiful, calling a "GenerateProductElement" function, which calls itself recursively to generate the nested products. Wonderful stuff. However, here's where i'm stuck.. i'm now trying to deserialize that XML back to the original objects (all autogenerated by Linq to SQL)... and herein lies the problem. Linq tO Sql expects my collections to be EntitySet collections, however Linq to Xml (which i'm tyring to use to deserailise) is returning IEnumerable. I've experimented with a few ways of casting between the 2, but nothing seems to work... I'm starting to think that I should just deserialise manually (with some funky loops and conditionals to determine which KitGroup KitItems belong to, etc)... however its really quite tricky and that code is likely to be quite ugly, so I'd love to find a more elegant solution to this problem. Any suggestions? Here's a code snippet: private Product GenerateProductFromXML(XDocument inDoc) { var prod = from p in inDoc.Descendants("Product") select new Product { ProductID = (int)p.Attribute("ID"), ProductGUID = (Guid)p.Attribute("GUID"), Name = (string)p.Element("Name"), Summary = (string)p.Element("Summary"), Description = (string)p.Element("Description"), SEName = (string)p.Element("SEName"), SETitle = (string)p.Element("SETitle"), XmlPackage = (string)p.Element("XmlPackage"), IsAKit = (byte)(int)p.Element("IsAKit"), ExtensionData = (string)p.Element("ExtensionData"), }; //TODO: UUGGGGGGG Converting b/w IEnumerable & EntitySet var kitGroups = (from kg in inDoc.Descendants("KitGroups").Elements("KitGroup") select new KitGroup { KitGroupID = (int) kg.Attribute("ID"), KitGroupGUID = (Guid) kg.Attribute("GUID"), Name = (string) kg.Element("Name"), KitItems = // THIS IS WHERE IT FAILS - "Cannot convert source type IEnumerable to target type EntitySet..." (from ki in kg.Descendants("KitItems").Elements("KitItem") select new KitItem { KitItemID = (int) ki.Attribute("ID"), KitItemGUID = (Guid) ki.Attribute("GUID") }); }); Product ImportedProduct = prod.First(); ImportedProduct.KitGroups = new EntitySet<KitGroup>(); ImportedProduct.KitGroups.AddRange(kitGroups); return ImportedProduct; }

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  • How can I debug or set a break statement inside an expression tree?

    - by Abel
    When an external library contains a LINQ provider, and it throws an exception when executing a dynamic expression tree, how can I break when that expression is thrown? For example, I use a third party LINQ2CRM provider, which allows me to call the Max<TSource, TResult>() method of IQueryable, but when it throws an InvalidCastException, I fail to break on the spot when the exception is thrown, making it hard to review the stack-trace because it's already unwinded when the debugger breaks it in my code. I've set "break on throw" for the mentioned exception. My debug settings are: Clarification on where exactly I'd want to break. I do not want to break in side the LINQ Expression, but instead, I want to break when the expression tree is executed, or, put in other words, when the IQueryable extension method Max() calls the override provided by the LINQ provider. The top of the stacktrace looks like this, which is where I would like to break inside (or step through, or whatever): at XrmLinq.QueryProviderBase.Execute[T](Expression expression) at System.Linq.Queryable.Max[TSource,TResult](IQueryable`1 source, Expression`1 selector)

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  • Parallelism in .NET – Part 7, Some Differences between PLINQ and LINQ to Objects

    - by Reed
    In my previous post on Declarative Data Parallelism, I mentioned that PLINQ extends LINQ to Objects to support parallel operations.  Although nearly all of the same operations are supported, there are some differences between PLINQ and LINQ to Objects.  By introducing Parallelism to our declarative model, we add some extra complexity.  This, in turn, adds some extra requirements that must be addressed. In order to illustrate the main differences, and why they exist, let’s begin by discussing some differences in how the two technologies operate, and look at the underlying types involved in LINQ to Objects and PLINQ . LINQ to Objects is mainly built upon a single class: Enumerable.  The Enumerable class is a static class that defines a large set of extension methods, nearly all of which work upon an IEnumerable<T>.  Many of these methods return a new IEnumerable<T>, allowing the methods to be chained together into a fluent style interface.  This is what allows us to write statements that chain together, and lead to the nice declarative programming model of LINQ: double min = collection .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Other LINQ variants work in a similar fashion.  For example, most data-oriented LINQ providers are built upon an implementation of IQueryable<T>, which allows the database provider to turn a LINQ statement into an underlying SQL query, to be performed directly on the remote database. PLINQ is similar, but instead of being built upon the Enumerable class, most of PLINQ is built upon a new static class: ParallelEnumerable.  When using PLINQ, you typically begin with any collection which implements IEnumerable<T>, and convert it to a new type using an extension method defined on ParallelEnumerable: AsParallel().  This method takes any IEnumerable<T>, and converts it into a ParallelQuery<T>, the core class for PLINQ.  There is a similar ParallelQuery class for working with non-generic IEnumerable implementations. This brings us to our first subtle, but important difference between PLINQ and LINQ – PLINQ always works upon specific types, which must be explicitly created. Typically, the type you’ll use with PLINQ is ParallelQuery<T>, but it can sometimes be a ParallelQuery or an OrderedParallelQuery<T>.  Instead of dealing with an interface, implemented by an unknown class, we’re dealing with a specific class type.  This works seamlessly from a usage standpoint – ParallelQuery<T> implements IEnumerable<T>, so you can always “switch back” to an IEnumerable<T>.  The difference only arises at the beginning of our parallelization.  When we’re using LINQ, and we want to process a normal collection via PLINQ, we need to explicitly convert the collection into a ParallelQuery<T> by calling AsParallel().  There is an important consideration here – AsParallel() does not need to be called on your specific collection, but rather any IEnumerable<T>.  This allows you to place it anywhere in the chain of methods involved in a LINQ statement, not just at the beginning.  This can be useful if you have an operation which will not parallelize well or is not thread safe.  For example, the following is perfectly valid, and similar to our previous examples: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); However, if SomeOperation() is not thread safe, we could just as easily do: double min = collection .Select(item => item.SomeOperation()) .AsParallel() .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); In this case, we’re using standard LINQ to Objects for the Select(…) method, then converting the results of that map routine to a ParallelQuery<T>, and processing our filter (the Where method) and our aggregation (the Min method) in parallel. PLINQ also provides us with a way to convert a ParallelQuery<T> back into a standard IEnumerable<T>, forcing sequential processing via standard LINQ to Objects.  If SomeOperation() was thread-safe, but PerformComputation() was not thread-safe, we would need to handle this by using the AsEnumerable() method: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .AsEnumerable() .Min(item => item.PerformComputation()); Here, we’re converting our collection into a ParallelQuery<T>, doing our map operation (the Select(…) method) and our filtering in parallel, then converting the collection back into a standard IEnumerable<T>, which causes our aggregation via Min() to be performed sequentially. This could also be written as two statements, as well, which would allow us to use the language integrated syntax for the first portion: var tempCollection = from item in collection.AsParallel() let e = item.SomeOperation() where (e.SomeProperty > 6 && e.SomeProperty < 24) select e; double min = tempCollection.AsEnumerable().Min(item => item.PerformComputation()); This allows us to use the standard LINQ style language integrated query syntax, but control whether it’s performed in parallel or serial by adding AsParallel() and AsEnumerable() appropriately. The second important difference between PLINQ and LINQ deals with order preservation.  PLINQ, by default, does not preserve the order of of source collection. This is by design.  In order to process a collection in parallel, the system needs to naturally deal with multiple elements at the same time.  Maintaining the original ordering of the sequence adds overhead, which is, in many cases, unnecessary.  Therefore, by default, the system is allowed to completely change the order of your sequence during processing.  If you are doing a standard query operation, this is usually not an issue.  However, there are times when keeping a specific ordering in place is important.  If this is required, you can explicitly request the ordering be preserved throughout all operations done on a ParallelQuery<T> by using the AsOrdered() extension method.  This will cause our sequence ordering to be preserved. For example, suppose we wanted to take a collection, perform an expensive operation which converts it to a new type, and display the first 100 elements.  In LINQ to Objects, our code might look something like: // Using IEnumerable<SourceClass> collection IEnumerable<ResultClass> results = collection .Select(e => e.CreateResult()) .Take(100); If we just converted this to a parallel query naively, like so: IEnumerable<ResultClass> results = collection .AsParallel() .Select(e => e.CreateResult()) .Take(100); We could very easily get a very different, and non-reproducable, set of results, since the ordering of elements in the input collection is not preserved.  To get the same results as our original query, we need to use: IEnumerable<ResultClass> results = collection .AsParallel() .AsOrdered() .Select(e => e.CreateResult()) .Take(100); This requests that PLINQ process our sequence in a way that verifies that our resulting collection is ordered as if it were processed serially.  This will cause our query to run slower, since there is overhead involved in maintaining the ordering.  However, in this case, it is required, since the ordering is required for correctness. PLINQ is incredibly useful.  It allows us to easily take nearly any LINQ to Objects query and run it in parallel, using the same methods and syntax we’ve used previously.  There are some important differences in operation that must be considered, however – it is not a free pass to parallelize everything.  When using PLINQ in order to parallelize your routines declaratively, the same guideline I mentioned before still applies: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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  • Imperative vs. LINQ Performance on WP7

    - by Bil Simser
    Jesse Liberty had a nice post presenting the concepts around imperative, LINQ and fluent programming to populate a listbox. Check out the post as it’s a great example of some foundational things every .NET programmer should know. I was more interested in what the IL code that would be generated from imperative vs. LINQ was like and what the performance numbers are and how they differ. The code at the instruction level is interesting but not surprising. The imperative example with it’s creating lists and loops weighs in at about 60 instructions. .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } 1: .method private hidebysig instance void ImperativeMethod() cil managed 2: { 3: .maxstack 3 4: .locals init ( 5: [0] class [mscorlib]System.Collections.Generic.IEnumerable`1<int32> someData, 6: [1] class [mscorlib]System.Collections.Generic.List`1<int32> inLoop, 7: [2] int32 n, 8: [3] class [mscorlib]System.Collections.Generic.IEnumerator`1<int32> CS$5$0000, 9: [4] bool CS$4$0001) 10: L_0000: nop 11: L_0001: ldc.i4.1 12: L_0002: ldc.i4.s 50 13: L_0004: call class [mscorlib]System.Collections.Generic.IEnumerable`1<int32> [System.Core]System.Linq.Enumerable::Range(int32, int32) 14: L_0009: stloc.0 15: L_000a: newobj instance void [mscorlib]System.Collections.Generic.List`1<int32>::.ctor() 16: L_000f: stloc.1 17: L_0010: nop 18: L_0011: ldloc.0 19: L_0012: callvirt instance class [mscorlib]System.Collections.Generic.IEnumerator`1<!0> [mscorlib]System.Collections.Generic.IEnumerable`1<int32>::GetEnumerator() 20: L_0017: stloc.3 21: L_0018: br.s L_003a 22: L_001a: ldloc.3 23: L_001b: callvirt instance !0 [mscorlib]System.Collections.Generic.IEnumerator`1<int32>::get_Current() 24: L_0020: stloc.2 25: L_0021: nop 26: L_0022: ldloc.2 27: L_0023: ldc.i4.5 28: L_0024: cgt 29: L_0026: ldc.i4.0 30: L_0027: ceq 31: L_0029: stloc.s CS$4$0001 32: L_002b: ldloc.s CS$4$0001 33: L_002d: brtrue.s L_0039 34: L_002f: ldloc.1 35: L_0030: ldloc.2 36: L_0031: ldloc.2 37: L_0032: mul 38: L_0033: callvirt instance void [mscorlib]System.Collections.Generic.List`1<int32>::Add(!0) 39: L_0038: nop 40: L_0039: nop 41: L_003a: ldloc.3 42: L_003b: callvirt instance bool [mscorlib]System.Collections.IEnumerator::MoveNext() 43: L_0040: stloc.s CS$4$0001 44: L_0042: ldloc.s CS$4$0001 45: L_0044: brtrue.s L_001a 46: L_0046: leave.s L_005a 47: L_0048: ldloc.3 48: L_0049: ldnull 49: L_004a: ceq 50: L_004c: stloc.s CS$4$0001 51: L_004e: ldloc.s CS$4$0001 52: L_0050: brtrue.s L_0059 53: L_0052: ldloc.3 54: L_0053: callvirt instance void [mscorlib]System.IDisposable::Dispose() 55: L_0058: nop 56: L_0059: endfinally 57: L_005a: nop 58: L_005b: ldarg.0 59: L_005c: ldfld class [System.Windows]System.Windows.Controls.ListBox PerfTest.MainPage::LB1 60: L_0061: ldloc.1 61: L_0062: callvirt instance void [System.Windows]System.Windows.Controls.ItemsControl::set_ItemsSource(class [mscorlib]System.Collections.IEnumerable) 62: L_0067: nop 63: L_0068: ret 64: .try L_0018 to L_0048 finally handler L_0048 to L_005a 65: } 66:   67: Compare that to the IL generated for the LINQ version which has about half of the instructions and just gets the job done, no fluff. .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } 1: .method private hidebysig instance void LINQMethod() cil managed 2: { 3: .maxstack 4 4: .locals init ( 5: [0] class [mscorlib]System.Collections.Generic.IEnumerable`1<int32> someData, 6: [1] class [mscorlib]System.Collections.Generic.IEnumerable`1<int32> queryResult) 7: L_0000: nop 8: L_0001: ldc.i4.1 9: L_0002: ldc.i4.s 50 10: L_0004: call class [mscorlib]System.Collections.Generic.IEnumerable`1<int32> [System.Core]System.Linq.Enumerable::Range(int32, int32) 11: L_0009: stloc.0 12: L_000a: ldloc.0 13: L_000b: ldsfld class [System.Core]System.Func`2<int32, bool> PerfTest.MainPage::CS$<>9__CachedAnonymousMethodDelegate6 14: L_0010: brtrue.s L_0025 15: L_0012: ldnull 16: L_0013: ldftn bool PerfTest.MainPage::<LINQProgramming>b__4(int32) 17: L_0019: newobj instance void [System.Core]System.Func`2<int32, bool>::.ctor(object, native int) 18: L_001e: stsfld class [System.Core]System.Func`2<int32, bool> PerfTest.MainPage::CS$<>9__CachedAnonymousMethodDelegate6 19: L_0023: br.s L_0025 20: L_0025: ldsfld class [System.Core]System.Func`2<int32, bool> PerfTest.MainPage::CS$<>9__CachedAnonymousMethodDelegate6 21: L_002a: call class [mscorlib]System.Collections.Generic.IEnumerable`1<!!0> [System.Core]System.Linq.Enumerable::Where<int32>(class [mscorlib]System.Collections.Generic.IEnumerable`1<!!0>, class [System.Core]System.Func`2<!!0, bool>) 22: L_002f: ldsfld class [System.Core]System.Func`2<int32, int32> PerfTest.MainPage::CS$<>9__CachedAnonymousMethodDelegate7 23: L_0034: brtrue.s L_0049 24: L_0036: ldnull 25: L_0037: ldftn int32 PerfTest.MainPage::<LINQProgramming>b__5(int32) 26: L_003d: newobj instance void [System.Core]System.Func`2<int32, int32>::.ctor(object, native int) 27: L_0042: stsfld class [System.Core]System.Func`2<int32, int32> PerfTest.MainPage::CS$<>9__CachedAnonymousMethodDelegate7 28: L_0047: br.s L_0049 29: L_0049: ldsfld class [System.Core]System.Func`2<int32, int32> PerfTest.MainPage::CS$<>9__CachedAnonymousMethodDelegate7 30: L_004e: call class [mscorlib]System.Collections.Generic.IEnumerable`1<!!1> [System.Core]System.Linq.Enumerable::Select<int32, int32>(class [mscorlib]System.Collections.Generic.IEnumerable`1<!!0>, class [System.Core]System.Func`2<!!0, !!1>) 31: L_0053: stloc.1 32: L_0054: ldarg.0 33: L_0055: ldfld class [System.Windows]System.Windows.Controls.ListBox PerfTest.MainPage::LB2 34: L_005a: ldloc.1 35: L_005b: callvirt instance void [System.Windows]System.Windows.Controls.ItemsControl::set_ItemsSource(class [mscorlib]System.Collections.IEnumerable) 36: L_0060: nop 37: L_0061: ret 38: } Again, not surprising here but a good indicator that you should consider using LINQ where possible. In fact if you have ReSharper installed you’ll see a squiggly (technical term) in the imperative code that says “Hey Dude, I can convert this to LINQ if you want to be c00L!” (or something like that, it’s the 2010 geek version of Clippy). What about the fluent version? As Jon correctly pointed out in the comments, when you compare the IL for the LINQ code and the IL for the fluent code it’s the same. LINQ and the fluent interface are just syntactical sugar so you decide what you’re most comfortable with. At the end of the day they’re both the same. Now onto the numbers. Again I expected the imperative version to be better performing than the LINQ version (before I saw the IL that was generated). Call it womanly instinct. A gut feel. Whatever. Some of the numbers are interesting though. For Jesse’s example of 50 items, the numbers were interesting. The imperative sample clocked in at 7ms while the LINQ version completed in 4. As the number of items went up, the elapsed time didn’t necessarily climb exponentially. At 500 items they were pretty much the same and the results were similar up to about 50,000 items. After that I tried 500,000 items where the gap widened but not by much (2.2 seconds for imperative, 2.3 for LINQ). It wasn’t until I tried 5,000,000 items where things were noticeable. Imperative filled the list in 20 seconds while LINQ took 8 seconds longer (although personally I wouldn’t suggest you put 5 million items in a list unless you want your users showing up at your door with torches and pitchforks). Here’s the table with the full results. Method/Items 50 500 5,000 50,000 500,000 5,000,000 Imperative 7ms 7ms 38ms 223ms 2230ms 20974ms LINQ/Fluent 4ms 6ms 41ms 240ms 2310ms 28731ms Like I said, at the end of the day it’s not a huge difference and you really don’t want your users waiting around for 30 seconds on a mobile device filling lists. In fact if Windows Phone 7 detects you’re taking more than 10 seconds to do any one thing, it considers the app hung and shuts it down. The results here are for Windows Phone 7 but frankly they're the same for desktop and web apps so feel free to apply it generally. From a programming perspective, choose what you like. Some LINQ statements can get pretty hairy so I usually fall back with my simple mind and write it imperatively. If you really want to impress your friends, write it old school then let ReSharper do the hard work for! Happy programming!

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  • Using LINQ to Twitter OAuth with Windows 8

    - by Joe Mayo
    In previous posts, I explained how to use LINQ to Twitter with Windows 8, but the example was a Twitter Search, which didn’t require authentication. Much of the Twitter API requires authentication, so this post will explain how you can perform OAuth authentication with LINQ to Twitter in a Windows 8 Metro-style application. Getting Started I have earlier posts on how to create a Windows 8 app and add pages, so I’ll assume it isn’t necessary to repeat here. One difference is that I’m using Visual Studio 2012 RC and some of the terminology and/or library code might be slightly different.  Here are steps to get started: Create a new Windows metro style app, selecting the Blank App project template. Create a new Basic Page and name it OAuth.xaml.  Note: You’ll receive a prompt window for adding files and you should click Yes because those files are necessary for this demo. Add a new Basic Page named TweetPage.xaml. Open App.xaml.cs and change !rootFrame.Navigate(typeof(MainPage)) to !rootFrame.Navigate(typeof(TweetPage)). Now that the project is set up you’ll see the reason why authentication is required by setting up the TweetPage. Setting Up to Tweet a Status In this section, I’ll show you how to set up the XAML and code-behind for a tweet.  The tweet logic will check to see if the user is authenticated before performing the tweet. To tweet, I put a TextBox and Button on the XAML page. The following code omits most of the page, concentrating primarily on the elements of interest in this post: <StackPanel Grid.Row="1"> <TextBox Name="TweetTextBox" Margin="15" /> <Button Name="TweetButton" Content="Tweet" Click="TweetButton_Click" Margin="15,0" /> </StackPanel> Given the UI above, the user types the message they want to tweet, and taps Tweet. This invokes TweetButton_Click, which checks to see if the user is authenticated.  If the user is not authenticated, the app navigates to the OAuth page.  If they are authenticated, LINQ to Twitter does an UpdateStatus to post the user’s tweet.  Here’s the TweetButton_Click implementation: void TweetButton_Click(object sender, RoutedEventArgs e) { PinAuthorizer auth = null; if (SuspensionManager.SessionState.ContainsKey("Authorizer")) { auth = SuspensionManager.SessionState["Authorizer"] as PinAuthorizer; } if (auth == null || !auth.IsAuthorized) { Frame.Navigate(typeof(OAuthPage)); return; } var twitterCtx = new TwitterContext(auth); Status tweet = twitterCtx.UpdateStatus(TweetTextBox.Text); new MessageDialog(tweet.Text, "Successful Tweet").ShowAsync(); } For authentication, this app uses PinAuthorizer, one of several authorizers available in the LINQ to Twitter library. I’ll explain how PinAuthorizer works in the next section. What’s important here is that LINQ to Twitter needs an authorizer to post a Tweet. The code above checks to see if a valid authorizer is available. To do this, it uses the SuspensionManager class, which is part of the code generated earlier when creating OAuthPage.xaml. The SessionState property is a Dictionary<string, object> and I’m using the Authorizer key to store the PinAuthorizer.  If the user previously authorized during this session, the code reads the PinAuthorizer instance from SessionState and assigns it to the auth variable. If the user is authorized, auth would not be null and IsAuthorized would be true. Otherwise, the app navigates the user to OAuthPage.xaml, which I’ll discuss in more depth in the next section. When the user is authorized, the code passes the authorizer, auth, to the TwitterContext constructor. LINQ to Twitter uses the auth instance to build OAuth signatures for each interaction with Twitter.  You no longer need to write any more code to make this happen. The code above accepts the tweet just posted in the Status instance, tweet, and displays a message with the text to confirm success to the user. You can pull the PinAuthorizer instance from SessionState, instantiate your TwitterContext, and use it as you need. Just remember to make sure you have a valid authorizer, like the code above. As shown earlier, the code navigates to OAuthPage.xaml when a valid authorizer isn’t available. The next section shows how to perform the authorization upon arrival at OAuthPage.xaml. Doing the OAuth Dance This section shows how to authenticate with LINQ to Twitter’s built-in OAuth support. From the user perspective, they must be navigated to the Twitter authentication page, add credentials, be navigated to a Pin number page, and then enter that Pin in the Windows 8 application. The following XAML shows the relevant elements that the user will interact with during this process. <StackPanel Grid.Row="2"> <WebView x:Name="OAuthWebBrowser" HorizontalAlignment="Left" Height="400" Margin="15" VerticalAlignment="Top" Width="700" /> <TextBlock Text="Please perform OAuth process (above), enter Pin (below) when ready, and tap Authenticate:" Margin="15,15,15,5" /> <TextBox Name="PinTextBox" Margin="15,0,15,15" Width="432" HorizontalAlignment="Left" IsEnabled="False" /> <Button Name="AuthenticatePinButton" Content="Authenticate" Margin="15" IsEnabled="False" Click="AuthenticatePinButton_Click" /> </StackPanel> The WebView in the code above is what allows the user to see the Twitter authentication page. The TextBox is for entering the Pin, and the Button invokes code that will take the Pin and allow LINQ to Twitter to complete the authentication process. As you can see, there are several steps to OAuth authentication, but LINQ to Twitter tries to minimize the amount of code you have to write. The two important parts of the code to make this happen are the part that starts the authentication process and the part that completes the authentication process. The following code, from OAuthPage.xaml.cs, shows a couple events that are instrumental in making this process happen: public OAuthPage() { this.InitializeComponent(); this.Loaded += OAuthPage_Loaded; OAuthWebBrowser.LoadCompleted += OAuthWebBrowser_LoadCompleted; } The OAuthWebBrowser_LoadCompleted event handler enables UI controls when the browser is done loading – notice that the TextBox and Button in the previous XAML have their IsEnabled attributes set to False. When the Page.Loaded event is invoked, the OAuthPage_Loaded handler starts the OAuth process, shown here: void OAuthPage_Loaded(object sender, RoutedEventArgs e) { auth = new PinAuthorizer { Credentials = new InMemoryCredentials { ConsumerKey = "", ConsumerSecret = "" }, UseCompression = true, GoToTwitterAuthorization = pageLink => Dispatcher.RunAsync(CoreDispatcherPriority.Normal, () => OAuthWebBrowser.Navigate(new Uri(pageLink, UriKind.Absolute))) }; auth.BeginAuthorize(resp => Dispatcher.RunAsync(CoreDispatcherPriority.Normal, () => { switch (resp.Status) { case TwitterErrorStatus.Success: break; case TwitterErrorStatus.RequestProcessingException: case TwitterErrorStatus.TwitterApiError: new MessageDialog(resp.Error.ToString(), resp.Message).ShowAsync(); break; } })); } The PinAuthorizer, auth, a field of this class instantiated in the code above, assigns keys to the Credentials property. These are credentials that come from registering an application with Twitter, explained in the LINQ to Twitter documentation, Securing Your Applications. Notice how I use Dispatcher.RunAsync to marshal the web browser navigation back onto the UI thread. Internally, LINQ to Twitter invokes the lambda expression assigned to GoToTwitterAuthorization when starting the OAuth process.  In this case, we want the WebView control to navigate to the Twitter authentication page, which is defined with a default URL in LINQ to Twitter and passed to the GoToTwitterAuthorization lambda as pageLink. Then you need to start the authorization process by calling BeginAuthorize. This starts the OAuth dance, running asynchronously.  LINQ to Twitter invokes the callback assigned to the BeginAuthorize parameter, allowing you to take whatever action you need, based on the Status of the response, resp. As mentioned earlier, this is where the user performs the authentication process, enters the Pin, and clicks authenticate. The handler for authenticate completes the process and saves the authorizer for subsequent use by the application, as shown below: void AuthenticatePinButton_Click(object sender, RoutedEventArgs e) { auth.CompleteAuthorize( PinTextBox.Text, completeResp => Dispatcher.RunAsync(CoreDispatcherPriority.Normal, () => { switch (completeResp.Status) { case TwitterErrorStatus.Success: SuspensionManager.SessionState["Authorizer"] = auth; Frame.Navigate(typeof(TweetPage)); break; case TwitterErrorStatus.RequestProcessingException: case TwitterErrorStatus.TwitterApiError: new MessageDialog(completeResp.Error.ToString(), completeResp.Message).ShowAsync(); break; } })); } The PinAuthorizer CompleteAuthorize method takes two parameters: Pin and callback. The Pin is from what the user entered in the TextBox prior to clicking the Authenticate button that invoked this method. The callback handles the response from completing the OAuth process. The completeResp holds information about the results of the operation, indicated by a Status property of type TwitterErrorStatus. On success, the code assigns auth to SessionState. You might remember SessionState from the previous description of TweetPage – this is where the valid authorizer comes from. After saving the authorizer, the code navigates the user back to TweetPage, where they can type in a message, click the Tweet button, and observe that they have successfully tweeted. Summary You’ve seen how to get started with using LINQ to Twitter in a Metro-style application. The generated code contained a SuspensionManager class with way to manage information across multiple pages via its SessionState property. You also saw how LINQ to Twitter performs authorization in two steps of starting the process and completing the process when the user provides a Pin number. Remember to marshal callback thread back onto the UI – you saw earlier how to use Dispatcher.RunAsync to accomplish this. There were a few steps in the process, but LINQ to Twitter did minimize the amount of code you needed to write to make it happen. You can download the MetroOAuthDemo.zip sample on the LINQ to Twitter Samples Page.   @JoeMayo

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  • LINQ to Twitter Maintenance Feedback

    - by Joe Mayo
    Originally posted on: http://geekswithblogs.net/WinAZ/archive/2013/06/16/linq-to-twitter-maintenance-feedback.aspxIt’s always fun to receive positive feedback on your work. If you receive a sufficient amount of positive feedback, you know you’re doing something right. Sometimes, people provide negative feedback too. There are a couple ways to handle it: come back fighting or engage for clarification. The way you handle the negative feedback depends on what your goals are. Feedback Approaches If you know the feedback is incorrect and you need to promote your idea or product, you might want to come back fighting. The feedback might just be comments by a troll or competitor wanting to spread FUD. However, this could be the totally wrong approach if you misjudge the source and intentions of the feedback. In a lot of cases, feedback is a golden opportunity. Sometimes, a problem exists that you either don’t know about or don’t realize the true impact of the problem. If you decide to come back fighting, you might loose the opportunity to learn something new. However, if you engage the person providing the feedback, looking for clarification, you might learn something very important. Negative feedback and it’s clarification can lead to the collection of useful and actionable data. In my case, something that prompted this blog post, I noticed someone who tweeted a negative comment about LINQ to Twitter. Normally, any less than stellar comments are usually from folks that need help – so I help if I can. This was different. I was like “Don’t use LINQ to Twitter”. This is an open source project, the comment didn’t come from a competing project, and  sounded more like an expression of frustration. So I engaged. Not only did the person respond, but I got some decent quality feedback. What’s also interesting is a couple other side conversations sprouted on the subject, which gave me more useful data. LINQ to Twitter Thread Actions Essentially, this particular issue centered around maintenance. There are actually several sub-issues at play here: dependencies, error handling, debugging, and visibility. I’ll describe each one and my interpretation. Dependencies Dependencies are where a library has references to other libraries. This means that when you build your application, you need DLLs for the entire dependency graph for your application. There are several potential problems with this that include more libraries for configuration management, potential versioning mismatches, and lack of cross-platform support. In the early days of LINQ to Twitter, I allowed developers to contribute and add dependencies, but it became very problematic (for reasons stated). It was like a ball and chain that kept me from moving forward. So, I refactored and pulled other open-source into my project to eliminate external dependencies. This lets me fix the code in my project without relying on someone else to upgrade or fix their DLL. The motivation for this was from early negative feedback that translated as important data and acted on it. Today, LINQ to Twitter has zero dependencies. Note: Rejecting good code from community members who worked hard to make your project better is a painful experience in itself. I have to point out that any contribution was not in vain because they had a positive influence on my subsequent refactoring that resulted in a better developer experience. Error Handling Error handling has been a problem in the past. I have this combination of supporting both synchronous and asynchronous (APM) processing that can be complex at times. Within the last 6 months, I did a fair amount of refactoring to detect errors and process them properly. I also refactored TwitterQueryException so it includes important data from Twitter. During this refactoring, I’ve made breaking changes that I felt would improve the development experience (small things like renaming a callback property to Exception, rather than Error). I think the async error handling is much better than it was a year ago. For all the work I’ve done, there is more to do. I think that a combination of more error handling support, e.g. improving semantics, and education through documentation and samples will improve the error handling story. Because of what I’ve done so far, it isn’t bad, but I see opportunities for improvement. Debugging Debugging can be painful. Here’s why: you have multiple layers of technology to navigate and figure out where the real problem is – Twitter API, Security, HTTP, LINQ to Twitter, and application. You can probably add your own nuances to that list, but the point is that debugging in this environment can be complex. I think that my plans for error handling will contribute to making the debugging process easier. However, there’s more I can do in the way of documentation and guidance. Some of the questions to be answered revolve around when something goes wrong, how does the developer figure out that there is a problem, what the problem is, and what to do about it. One example that has gone a long way to helping LINQ to Twitter developers is the 401 FAQ. A 401 Unauthorized is the error that the Twitter API returns when a use isn’t able to authenticate and is one of the most difficult problems faced by LINQ to Twitter developers. What I did was read guidance from Twitter and collect techniques from my own development and actions helping other developers to compile an extensive list of reasons for the 401 and ways to fix the problem. At one time, over half of the questions I answered in the forums were to help solve 401 issues. After publishing the 401 FAQ, I rarely get a 401 question and it’s because the person didn’t know about the FAQ. If the person is too lazy to read the FAQ, that’s not my issue, but the results in support issues have been dramatic. I think debugging can benefit from the education and documentation approach, but I’m always open to suggestions on whatever else I can do. Visibility Visibility is a nuance of the error handling/debugging discussion but is deeply rooted in comfort and control. The questions to ask in this area are what is happening as my code runs and how testable is the code. In support of these areas, LINQ to Twitter does have logging and TwitterContext properties that help see what’s happening on requests. The logging functionality allows any developer to connect a TextWriter to the Log property of TwitterContext to see what’s happening. Further, TwitterContext has a Headers property to see the headers Twitter returns and a RawResults property to show the Json string Twitter returns. From a testing perspective, I’ve been able to write hundreds of unit tests, over 600 when this post is published, and growing. If you write your own library, you have full control over all of these aspects. The tradeoff here is that while you have access to the LINQ to Twitter source code and modify it for all the visibility, LINQ to Twitter *will* change (which is good) and you will have to figure out how to merge that with your changes (which is hard). The fact is that this is a limitation of any 3rd party library, not just LINQ to Twitter. So, it’s a design decision where the tradeoff is between control and productivity. That said, there are things I can do with LINQ to Twitter to make the visibility story more compelling. I think there are opportunities to improve diagnostics. This would be a ton of work because it would need to provide multi-level logging that can be tuned for production and support any logging provider you want to attach. I’ve considered approaches such as how the new Semantic Logging application block connects to Windows Error Reporting as a potential target. Whatever I do would need to be extensible without creating native external dependencies. e.g. how many 3rd party libraries force a dependency on a logging framework that you don’t use. So, this won’t be an easy feat, but I believe it can be part of the roadmap. I think that a lot of developers are unaware of existing visibility features, so the first step would be to provide more documentation and guidance. My thought are that this would lead to more feedback that will help improve this area. Summary Recent feedback highlights some of items that are important to LINQ to Twitter developers, such as dependencies, error handling, debugging, and visibility. I know that there are maintenance issues that have been problems for LINQ to Twitter developers in the past. I’ve done a lot of work in this area, such as improving error handling, adding visibility features, and providing extensive API documentation. That said, there is more to be done to make LINQ to Twitter the best Twitter API experience available for .NET developers and I welcome anyone’s thoughts on what I’ve written here or new improvements. @JoeMayo

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