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  • How to write Asynchronous LINQ query?

    - by Morgan Cheng
    After I read a bunch of LINQ related stuff, I suddenly realized that no articles introduce how to write asynchronous LINQ query. Suppose we use LINQ to SQL, below statement is clear. However, if the SQL database responds slowly, then the thread using this block of code would be hindered. var result = from item in Products where item.Price > 3 select item.Name; foreach (var name in result) { Console.WriteLine(name); } Seems that current LINQ query spec doesn't provide support to this. Is there any way to do asynchronous programming LINQ? It works like there is a callback notification when results are ready to use without any blocking delay on I/O.

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  • Separating merged array of arithmetic and geometric series

    - by user1814037
    Given an array of positive integers in increasing order. Separate them in two series, an arithmetic sequence and geometric sequence. The given array is such that a solution do exist. The union of numbers of the two sequence must be the given array. Both series can have common elements i.e. series need not to be disjoint. The ratio of the geometric series can be fractional. Example: Given series : 2,4,6,8,10,12,25 AP: 2,4,6,8,10,12 GP: 4,10,25 I tried taking few examples but could not reach a general way. Even tried some graph implementation by introducing edges if they follow a particular sequence but could not reach solution.

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  • Linq-to-sql Compiled Query returns object NOT belonging to submitted DataContext ?

    - by Vladimir Kojic
    Compiled query: public static class Machines { public static readonly Func<OperationalDataContext, short, Machine> QueryMachineById = CompiledQuery.Compile((OperationalDataContext db, short machineID) => db.Machines.Where(m => m.MachineID == machineID).SingleOrDefault() ); public static Machine GetMachineById(IUnitOfWork unitOfWork, short id) { Machine machine; // Old code (working) //var machineRepository = unitOfWork.GetRepository<Machine>(); //machine = machineRepository.Find(m => m.MachineID == id).SingleOrDefault(); // New code (making problems) machine = QueryMachineById(unitOfWork.DataContext, id); return machine; } It looks like compiled query is returning result from another data context [TestMethod] public void GetMachinesTest() { using (var unitOfWork = IoC.Get<IUnitOfWork>()) { // Compile Query var machine = Machines.GetMachineById(unitOfWork, 3); } using (var unitOfWork = IoC.Get<IUnitOfWork>()) { var machineRepository = unitOfWork.GetRepository<Machine>(); // Get From Repository var machineFromRepository = machineRepository.Find(m => m.MachineID == 2).SingleOrDefault(); var machine = Machines.GetMachineById(unitOfWork, 2); VerifyHuskyHostMachine(machineFromRepository, 2, "Machine 2", "222222", "H400RS", "MachineIconB.xaml", false, true, LicenseType.Licensed, InterfaceType.HuskyHostV2, "10.0.97.2:8080", "10.0.97.2", 8080, "4.0"); VerifyHuskyHostMachine(machine, 2, "Machine 2", "222222", "H400RS", "MachineIconB.xaml", false, true, LicenseType.Licensed, InterfaceType.HuskyHostV2, "10.0.97.2:8080", "10.0.97.2", 8080, "4.0"); Assert.AreSame(machineFromRepository, machine); // FAIL } } If I run other (complex) unit tests I'm getting as expected: An attempt has been made to Attach or Add an entity that is not new, perhaps having been loaded from another DataContext. Another Important information is that this test is under TransactionScope! UPDATE: It looks like next link is describing similar problem (is this bug solved ?): http://social.msdn.microsoft.com/Forums/en-US/linqprojectgeneral/thread/9bcffc2d-794e-4c4a-9e3e-cdc89dad0e38

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  • What join in Linq i have to use to do what i want?

    - by Garcia Julien
    Hi, I have two dataset from different server. I have result like that (if image doesn't work my data) The problem is at last, i've got only the result from the first table like that And i would like to have all the result for different job type like that asset job jan feb mar ... 5000 acc 10 11 12 5000 over 10 11 12 The problem is not solve with a right join because it's the same problem Could you help me? Thank Ju

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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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  • 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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  • Time series in R

    - by Christian Stade-Schuldt
    Hi, I am tracking my body weight in a spread sheet but I want to improve the experience by using R. I was trying to find some information about time series analysis in R but I was not succesful. The data I have here is in the following format: date - weight - body-fat-percentage - water-percentage e.g. 10/08/09 - 84.30 - 18.20 - 55.3 What I want to do plot weight and exponential moving average against time How can I achieve that?

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