Search Results

Search found 5846 results on 234 pages for 'linq to crm'.

Page 97/234 | < Previous Page | 93 94 95 96 97 98 99 100 101 102 103 104  | Next Page >

• Entity Framework and Plain Old CLR Objects in an ASP.Net application

  - by nikolaosk

  This is going to be the sixth post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here and the third one here , the fourth one here and the fifth one here . I have a post regarding ASP.Net and EntityDataSource. You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a look at them here , here and here . In this post I will be looking...(read more)

  Read the article

• Daily tech links for .net and related technologies - May 13-16, 2010

  - by SanjeevAgarwal

  Daily tech links for .net and related technologies - May 13-16, 2010 Web Development Integrating Twitter Into An ASP.NET Website Using OAuth - Scott Mitchell T4MVC Extensions for MVC Partials - Evan Building a Data Grid in ASP.NET MVC - Ali Bastani Introducing the MVC Music Store - MVC 2 Sample Application and Tutorial - Jon Galloway Announcing the RTM of MvcExtensions - kazimanzurrashid Optimizing Your Website For Speed Web Design Validation with the jQuery UI Tabs Widget - Chris Love A Brief History...(read more)

  Read the article

• Daily tech links for .net and related technologies - Apr 1-3, 2010

  - by SanjeevAgarwal

  Daily tech links for .net and related technologies - Apr 1-3, 2010 Web Development Cleaner HTML Markup with ASP.NET 4 Web Forms - Client IDs - ScottGu Using jQuery and OData to Insert a Database Record - Stephen Walter Apple vs. Microsoft – A Website Usability Study Mastering ASP.NET MVC 2.0: Preview - TekPub Web Design UX Lessons Learned From Offline Experiences - Jon Phillips 5 Steps Toward jQuery Mastery - Dave Ward 20 jQuery Cheatsheets, Docs and References for Every Occasion - Paul Andrew 11...(read more)

  Read the article

• Using TPL and PLINQ to raise performance of feed aggregator

  - by DigiMortal

  In this posting I will show you how to use Task Parallel Library (TPL) and PLINQ features to boost performance of simple RSS-feed aggregator. I will use here only very basic .NET classes that almost every developer starts from when learning parallel programming. Of course, we will also measure how every optimization affects performance of feed aggregator. Feed aggregator Our feed aggregator works as follows: Load list of blogs Download RSS-feed Parse feed XML Add new posts to database Our feed aggregator is run by task scheduler after every 15 minutes by example. We will start our journey with serial implementation of feed aggregator. Second step is to use task parallelism and parallelize feeds downloading and parsing. And our last step is to use data parallelism to parallelize database operations. We will use Stopwatch class to measure how much time it takes for aggregator to download and insert all posts from all registered blogs. After every run we empty posts table in database. Serial aggregation Before doing parallel stuff let’s take a look at serial implementation of feed aggregator. All tasks happen one after other. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();           for (var index = 0; index <blogs.Count; index++)         {              ImportFeed(blogs[index]);         }     }       private void ImportFeed(BlogDto blog)     {         if(blog == null)             return;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                 }       private void ImportRssFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = RssFeed.Create(uri);           foreach (var item in feed.Channel.Items)         {             SaveRssFeedItem(item, blog.Id, blog.CreatedById);         }     }       private void ImportAtomFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           foreach (var item in feed.Entries)         {             SaveAtomFeedEntry(item, blog.Id, blog.CreatedById);         }     } } Serial implementation of feed aggregator downloads and inserts all posts with 25.46 seconds. Task parallelism Task parallelism means that separate tasks are run in parallel. You can find out more about task parallelism from MSDN page Task Parallelism (Task Parallel Library) and Wikipedia page Task parallelism. Although finding parts of code that can run safely in parallel without synchronization issues is not easy task we are lucky this time. Feeds import and parsing is perfect candidate for parallel tasks. We can safely parallelize feeds import because importing tasks doesn’t share any resources and therefore they don’t also need any synchronization. After getting the list of blogs we iterate through the collection and start new TPL task for each blog feed aggregation. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();                var tasks = new Task[blogs.Count];           for (var index = 0; index <blogs.Count; index++)         {             tasks[index] = new Task(ImportFeed, blogs[index]);             tasks[index].Start();         }           Task.WaitAll(tasks);     }       private void ImportFeed(object blogObject)     {         if(blogObject == null)             return;         var blog = (BlogDto)blogObject;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                }       private void ImportRssFeed(BlogDto blog)     {          var uri = new Uri(blog.RssUrl);          var feed = RssFeed.Create(uri);           foreach (var item in feed.Channel.Items)          {              SaveRssFeedItem(item, blog.Id, blog.CreatedById);          }     }     private void ImportAtomFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           foreach (var item in feed.Entries)         {             SaveAtomFeedEntry(item, blog.Id, blog.CreatedById);         }     } } You should notice first signs of the power of TPL. We made only minor changes to our code to parallelize blog feeds aggregating. On my machine this modification gives some performance boost – time is now 17.57 seconds. Data parallelism There is one more way how to parallelize activities. Previous section introduced task or operation based parallelism, this section introduces data based parallelism. By MSDN page Data Parallelism (Task Parallel Library) data parallelism refers to scenario in which the same operation is performed concurrently on elements in a source collection or array. In our code we have independent collections we can process in parallel – imported feed entries. As checking for feed entry existence and inserting it if it is missing from database doesn’t affect other entries the imported feed entries collection is ideal candidate for parallelization. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();                var tasks = new Task[blogs.Count];           for (var index = 0; index <blogs.Count; index++)         {             tasks[index] = new Task(ImportFeed, blogs[index]);             tasks[index].Start();         }           Task.WaitAll(tasks);     }       private void ImportFeed(object blogObject)     {         if(blogObject == null)             return;         var blog = (BlogDto)blogObject;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                }       private void ImportRssFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = RssFeed.Create(uri);           feed.Channel.Items.AsParallel().ForAll(a =>         {             SaveRssFeedItem(a, blog.Id, blog.CreatedById);         });      }        private void ImportAtomFeed(BlogDto blog)      {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           feed.Entries.AsParallel().ForAll(a =>         {              SaveAtomFeedEntry(a, blog.Id, blog.CreatedById);         });      } } We did small change again and as the result we parallelized checking and saving of feed items. This change was data centric as we applied same operation to all elements in collection. On my machine I got better performance again. Time is now 11.22 seconds. Results Let’s visualize our measurement results (numbers are given in seconds). As we can see then with task parallelism feed aggregation takes about 25% less time than in original case. When adding data parallelism to task parallelism our aggregation takes about 2.3 times less time than in original case. More about TPL and PLINQ Adding parallelism to your application can be very challenging task. You have to carefully find out parts of your code where you can safely go to parallel processing and even then you have to measure the effects of parallel processing to find out if parallel code performs better. If you are not careful then troubles you will face later are worse than ones you have seen before (imagine error that occurs by average only once per 10000 code runs). Parallel programming is something that is hard to ignore. Effective programs are able to use multiple cores of processors. Using TPL you can also set degree of parallelism so your application doesn’t use all computing cores and leaves one or more of them free for host system and other processes. And there are many more things in TPL that make it easier for you to start and go on with parallel programming. In next major version all .NET languages will have built-in support for parallel programming. There will be also new language constructs that support parallel programming. Currently you can download Visual Studio Async to get some idea about what is coming. Conclusion Parallel programming is very challenging but good tools offered by Visual Studio and .NET Framework make it way easier for us. In this posting we started with feed aggregator that imports feed items on serial mode. With two steps we parallelized feed importing and entries inserting gaining 2.3 times raise in performance. Although this number is specific to my test environment it shows clearly that parallel programming may raise the performance of your application significantly.

  Read the article

• Lazy Loading,Eager Loading,Explicit Loading in Entity Framework 4

  - by nikolaosk

  This is going to be the ninth post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here , the third one here , the fourth one here , the fifth one here ,the sixth one here ,the seventh one here and the eighth one here . I have a post regarding ASP.Net and EntityDataSource . You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a...(read more)

  Read the article

• DB Documentation Tool

  - by Hisham El-bereky

   Recently I have uploaded new project to codeplex site, DbDocument or DbDoc project is a helper tool used side by side with MS SQL server management studio tool, you can design your DB Tables in visualized way through Diagrams and then use “DbDoc” tool to generate design document in MS Word format, the generated file can be used in design review process or as history reference, the tool facilitate and reduce the time of writing DB structure documentthe current version is not so sophisticated which is intend to generate word document in table format with all tables in DB illustrating its structure and constraints, but for now it seems to be good.   For more details check DbDoc document or go immediately to DbDoc home page http://dbdocument.codeplex.com/

  Read the article

• Creating Property Set Expression Trees In A Developer Friendly Way

  - by Paulo Morgado

  In a previous post I showed how to create expression trees to set properties on an object. The way I did it was not very developer friendly. It involved explicitly creating the necessary expressions because the compiler won’t generate expression trees with property or field set expressions. Recently someone contacted me the help develop some kind of command pattern framework that used developer friendly lambdas to generate property set expression trees. Simply putting, given this entity class: public class Person { public string Name { get; set; } } The person in question wanted to write code like this: var et = Set((Person p) => p.Name = "me"); Where et is the expression tree that represents the property assignment. So, if we can’t do this, let’s try the next best thing that is splitting retrieving the property information from the retrieving the value to assign o the property: var et = Set((Person p) => p.Name, () => "me"); And this is something that the compiler can handle. The implementation of Set receives an expression to retrieve the property information from and another expression the retrieve the value to assign to the property: public static Expression<Action<TEntity>> Set<TEntity, TValue>( Expression<Func<TEntity, TValue>> propertyGetExpression, Expression<Func<TValue>> valueExpression) The implementation of this method gets the property information form the body of the property get expression (propertyGetExpression) and the value expression (valueExpression) to build an assign expression and builds a lambda expression using the same parameter of the property get expression as its parameter: public static Expression<Action<TEntity>> Set<TEntity, TValue>( Expression<Func<TEntity, TValue>> propertyGetExpression, Expression<Func<TValue>> valueExpression) { var entityParameterExpression = (ParameterExpression)(((MemberExpression)(propertyGetExpression.Body)).Expression); return Expression.Lambda<Action<TEntity>>( Expression.Assign(propertyGetExpression.Body, valueExpression.Body), entityParameterExpression); } And now we can use the expression to translate to another context or just compile and use it: var et = Set((Person p) => p.Name, () => name); Console.WriteLine(person.Name); // Prints: p => (p.Name = “me”) var d = et.Compile(); d(person); Console.WriteLine(person.Name); // Prints: me It can even support closures: var et = Set((Person p) => p.Name, () => name); Console.WriteLine(person.Name); // Prints: p => (p.Name = value(<>c__DisplayClass0).name) var d = et.Compile(); name = "me"; d(person); Console.WriteLine(person.Name); // Prints: me name = "you"; d(person); Console.WriteLine(person.Name); // Prints: you Not so useful in the intended scenario (but still possible) is building an expression tree that receives the value to assign to the property as a parameter: public static Expression<Action<TEntity, TValue>> Set<TEntity, TValue>(Expression<Func<TEntity, TValue>> propertyGetExpression) { var entityParameterExpression = (ParameterExpression)(((MemberExpression)(propertyGetExpression.Body)).Expression); var valueParameterExpression = Expression.Parameter(typeof(TValue)); return Expression.Lambda<Action<TEntity, TValue>>( Expression.Assign(propertyGetExpression.Body, valueParameterExpression), entityParameterExpression, valueParameterExpression); } This new expression can be used like this: var et = Set((Person p) => p.Name); Console.WriteLine(person.Name); // Prints: (p, Param_0) => (p.Name = Param_0) var d = et.Compile(); d(person, "me"); Console.WriteLine(person.Name); // Prints: me d(person, "you"); Console.WriteLine(person.Name); // Prints: you The only caveat is that we need to be able to write code to read the property in order to write to it.

  Read the article

• The WaitForAll Roadshow

  - by adweigert

  OK, so I took for granted some imaginative uses of WaitForAll but lacking that, here is how I am using. First, I have a nice little class called Parallel that allows me to spin together a list of tasks (actions) and then use WaitForAll, so here it is, WaitForAll's 15 minutes of fame ... First Parallel that allows me to spin together several Action delegates to execute, well in parallel.   public static class Parallel { public static ParallelQuery Task(Action action) { return new Action[] { action }.AsParallel(); } public static ParallelQuery> Task(Action action) { return new Action[] { action }.AsParallel(); } public static ParallelQuery Task(this ParallelQuery actions, Action action) { var list = new List(actions); list.Add(action); return list.AsParallel(); } public static ParallelQuery> Task(this ParallelQuery> actions, Action action) { var list = new List>(actions); list.Add(action); return list.AsParallel(); } }   Next, this is an example usage from an app I'm working on that just is rendering some basic computer information via WMI and performance counters. The WMI calls can be expensive given the distance and link speed of some of the computers it will be trying to communicate with. This is the actual MVC action from my controller to return the data for an individual computer.  public PartialViewResult Detail(string computerName) { var computer = this.Computers.Get(computerName); var perf = Factory.GetInstance(); var detail = new ComputerDetailViewModel() { Computer = computer }; try { var work = Parallel .Task(delegate { // Win32_ComputerSystem var key = computer.Name + "_Win32_ComputerSystem"; var system = this.Cache.Get(key); if (system == null) { using (var impersonation = computer.ImpersonateElevatedIdentity()) { system = computer.GetWmiContext().GetInstances().Single(); } this.Cache.Set(key, system); } detail.TotalMemory = system.TotalPhysicalMemory; detail.Manufacturer = system.Manufacturer; detail.Model = system.Model; detail.NumberOfProcessors = system.NumberOfProcessors; }) .Task(delegate { // Win32_OperatingSystem var key = computer.Name + "_Win32_OperatingSystem"; var os = this.Cache.Get(key); if (os == null) { using (var impersonation = computer.ImpersonateElevatedIdentity()) { os = computer.GetWmiContext().GetInstances().Single(); } this.Cache.Set(key, os); } detail.OperatingSystem = os.Caption; detail.OSVersion = os.Version; }) // Performance Counters .Task(delegate { using (var impersonation = computer.ImpersonateElevatedIdentity()) { detail.AvailableBytes = perf.GetSample(computer, "Memory", "Available Bytes"); } }) .Task(delegate { using (var impersonation = computer.ImpersonateElevatedIdentity()) { detail.TotalProcessorUtilization = perf.GetValue(computer, "Processor", "% Processor Time", "_Total"); } }).WithExecutionMode(ParallelExecutionMode.ForceParallelism); if (!work.WaitForAll(TimeSpan.FromSeconds(15), task => task())) { return PartialView("Timeout"); } } catch (Exception ex) { this.LogException(ex); return PartialView("Error.ascx"); } return PartialView(detail); }

  Read the article

• Code and Slides: Building the Account at a Glance ASP.NET MVC, EF Code First, HTML5, and jQuery Application

  - by dwahlin

  This presentation was given at the spring 2012 DevConnections conference in Las Vegas and is based on my Pluralsight course. The presentation shows how several different technologies including ASP.NET MVC, EF Code First, HTML5, jQuery, Canvas, SVG, JavaScript patterns, Ajax, and more can be integrated together to build a robust application. An example of the application in action is shown next: View more of my presentations here. The complete code (and associated SQL Server database) for the Account at a Glance application can be found here. Check out the full-length course on the topic at Pluralsight.com.

  Read the article

• Taming Hopping Windows

  - by Roman Schindlauer

  At first glance, hopping windows seem fairly innocuous and obvious. They organize events into windows with a simple periodic definition: the windows have some duration d (e.g. a window covers 5 second time intervals), an interval or period p (e.g. a new window starts every 2 seconds) and an alignment a (e.g. one of those windows starts at 12:00 PM on March 15, 2012 UTC). var wins = xs     .HoppingWindow(TimeSpan.FromSeconds(5),                    TimeSpan.FromSeconds(2),                    new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc)); Logically, there is a window with start time a + np and end time a + np + d for every integer n. That’s a lot of windows. So why doesn’t the following query (always) blow up? var query = wins.Select(win => win.Count()); A few users have asked why StreamInsight doesn’t produce output for empty windows. Primarily it’s because there is an infinite number of empty windows! (Actually, StreamInsight uses DateTimeOffset.MaxValue to approximate “the end of time” and DateTimeOffset.MinValue to approximate “the beginning of time”, so the number of windows is lower in practice.) That was the good news. Now the bad news. Events also have duration. Consider the following simple input: var xs = this.Application                 .DefineEnumerable(() => new[]                     { EdgeEvent.CreateStart(DateTimeOffset.UtcNow, 0) })                 .ToStreamable(AdvanceTimeSettings.IncreasingStartTime); Because the event has no explicit end edge, it lasts until the end of time. So there are lots of non-empty windows if we apply a hopping window to that single event! For this reason, we need to be careful with hopping window queries in StreamInsight. Or we can switch to a custom implementation of hopping windows that doesn’t suffer from this shortcoming. The alternate window implementation produces output only when the input changes. We start by breaking up the timeline into non-overlapping intervals assigned to each window. In figure 1, six hopping windows (“Windows”) are assigned to six intervals (“Assignments”) in the timeline. Next we take input events (“Events”) and alter their lifetimes (“Altered Events”) so that they cover the intervals of the windows they intersect. In figure 1, you can see that the first event e1 intersects windows w1 and w2 so it is adjusted to cover assignments a1 and a2. Finally, we can use snapshot windows (“Snapshots”) to produce output for the hopping windows. Notice however that instead of having six windows generating output, we have only four. The first and second snapshots correspond to the first and second hopping windows. The remaining snapshots however cover two hopping windows each! While in this example we saved only two events, the savings can be more significant when the ratio of event duration to window duration is higher. Figure 1: Timeline The implementation of this strategy is straightforward. We need to set the start times of events to the start time of the interval assigned to the earliest window including the start time. Similarly, we need to modify the end times of events to the end time of the interval assigned to the latest window including the end time. The following snap-to-boundary function that rounds a timestamp value t down to the nearest value t' <= t such that t' is a + np for some integer n will be useful. For convenience, we will represent both DateTime and TimeSpan values using long ticks: static long SnapToBoundary(long t, long a, long p) {     return t - ((t - a) % p) - (t > a ? 0L : p); } How do we find the earliest window including the start time for an event? It’s the window following the last window that does not include the start time assuming that there are no gaps in the windows (i.e. duration < interval), and limitation of this solution. To find the end time of that antecedent window, we need to know the alignment of window ends: long e = a + (d % p); Using the window end alignment, we are finally ready to describe the start time selector: static long AdjustStartTime(long t, long e, long p) {     return SnapToBoundary(t, e, p) + p; } To find the latest window including the end time for an event, we look for the last window start time (non-inclusive): public static long AdjustEndTime(long t, long a, long d, long p) {     return SnapToBoundary(t - 1, a, p) + p + d; } Bringing it together, we can define the translation from events to ‘altered events’ as in Figure 1: public static IQStreamable<T> SnapToWindowIntervals<T>(IQStreamable<T> source, TimeSpan duration, TimeSpan interval, DateTime alignment) {     if (source == null) throw new ArgumentNullException("source");     // reason about DateTime and TimeSpan in ticks     long d = Math.Min(DateTime.MaxValue.Ticks, duration.Ticks);     long p = Math.Min(DateTime.MaxValue.Ticks, Math.Abs(interval.Ticks));     // set alignment to earliest possible window     var a = alignment.ToUniversalTime().Ticks % p;     // verify constraints of this solution     if (d <= 0L) { throw new ArgumentOutOfRangeException("duration"); }     if (p == 0L || p > d) { throw new ArgumentOutOfRangeException("interval"); }     // find the alignment of window ends     long e = a + (d % p);     return source.AlterEventLifetime(         evt => ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p)),         evt => ToDateTime(AdjustEndTime(evt.EndTime.ToUniversalTime().Ticks, a, d, p)) -             ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p))); } public static DateTime ToDateTime(long ticks) {     // just snap to min or max value rather than under/overflowing     return ticks < DateTime.MinValue.Ticks         ? new DateTime(DateTime.MinValue.Ticks, DateTimeKind.Utc)         : ticks > DateTime.MaxValue.Ticks         ? new DateTime(DateTime.MaxValue.Ticks, DateTimeKind.Utc)         : new DateTime(ticks, DateTimeKind.Utc); } Finally, we can describe our custom hopping window operator: public static IQWindowedStreamable<T> HoppingWindow2<T>(     IQStreamable<T> source,     TimeSpan duration,     TimeSpan interval,     DateTime alignment) {     if (source == null) { throw new ArgumentNullException("source"); }     return SnapToWindowIntervals(source, duration, interval, alignment).SnapshotWindow(); } By switching from HoppingWindow to HoppingWindow2 in the following example, the query returns quickly rather than gobbling resources and ultimately failing! public void Main() {     var start = new DateTimeOffset(new DateTime(2012, 6, 28), TimeSpan.Zero);     var duration = TimeSpan.FromSeconds(5);     var interval = TimeSpan.FromSeconds(2);     var alignment = new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc);     var events = this.Application.DefineEnumerable(() => new[]     {         EdgeEvent.CreateStart(start.AddSeconds(0), "e0"),         EdgeEvent.CreateStart(start.AddSeconds(1), "e1"),         EdgeEvent.CreateEnd(start.AddSeconds(1), start.AddSeconds(2), "e1"),         EdgeEvent.CreateStart(start.AddSeconds(3), "e2"),         EdgeEvent.CreateStart(start.AddSeconds(9), "e3"),         EdgeEvent.CreateEnd(start.AddSeconds(3), start.AddSeconds(10), "e2"),         EdgeEvent.CreateEnd(start.AddSeconds(9), start.AddSeconds(10), "e3"),     }).ToStreamable(AdvanceTimeSettings.IncreasingStartTime);     var adjustedEvents = SnapToWindowIntervals(events, duration, interval, alignment);     var query = from win in HoppingWindow2(events, duration, interval, alignment)                 select win.Count();     DisplayResults(adjustedEvents, "Adjusted Events");     DisplayResults(query, "Query"); } As you can see, instead of producing a massive number of windows for the open start edge e0, a single window is emitted from 12:00:15 AM until the end of time: Adjusted Events StartTime EndTime Payload 6/28/2012 12:00:01 AM 12/31/9999 11:59:59 PM e0 6/28/2012 12:00:03 AM 6/28/2012 12:00:07 AM e1 6/28/2012 12:00:05 AM 6/28/2012 12:00:15 AM e2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM e3 Query StartTime EndTime Payload 6/28/2012 12:00:01 AM 6/28/2012 12:00:03 AM 1 6/28/2012 12:00:03 AM 6/28/2012 12:00:05 AM 2 6/28/2012 12:00:05 AM 6/28/2012 12:00:07 AM 3 6/28/2012 12:00:07 AM 6/28/2012 12:00:11 AM 2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM 3 6/28/2012 12:00:15 AM 12/31/9999 11:59:59 PM 1 Regards, The StreamInsight Team

  Read the article

• PLINQ Adventure Land - WaitForAll

  - by adweigert

  PLINQ is awesome for getting a lot of work done fast, but one thing I haven't figured out yet is how to start work with PLINQ but only let it execute for a maximum amount of time and react if it is taking too long. So, as I must admit I am still learning PLINQ, I created this extension in that ignorance. It behaves similar to ForAll<> but takes a timeout and returns false if the threads don't complete in the specified amount of time. Hope this helps someone else take PLINQ further, it definitely has helped for me ...  public static bool WaitForAll<T>(this ParallelQuery<T> query, TimeSpan timeout, Action<T> action) { Contract.Requires(query != null); Contract.Requires(action != null); var exception = (Exception)null; var cts = new CancellationTokenSource(); var forAllWithCancellation = new Action(delegate { try { query.WithCancellation(cts.Token).ForAll(action); } catch (OperationCanceledException) { // NOOP } catch (AggregateException ex) { exception = ex; } }); var mrs = new ManualResetEvent(false); var callback = new AsyncCallback(delegate { mrs.Set(); }); var result = forAllWithCancellation.BeginInvoke(callback, null); if (mrs.WaitOne(timeout)) { forAllWithCancellation.EndInvoke(result); if (exception != null) { throw exception; } return true; } else { cts.Cancel(); return false; } }

  Read the article

• Reinventing the Paged IEnumerable, Weigert Style!

  - by adweigert

  I am pretty sure someone else has done this, I've seen variations as PagedList<T>, but this is my style of a paged IEnumerable collection. I just store a reference to the collection and generate the paged data when the enumerator is needed, so you could technically add to a list that I'm referencing and the properties and results would be adjusted accordingly. I don't mind reinventing the wheel when I can add some of my own personal flare ... // Extension method for easy use public static PagedEnumerable AsPaged(this IEnumerable collection, int currentPage = 1, int pageSize = 0) { Contract.Requires(collection != null); Contract.Assume(currentPage >= 1); Contract.Assume(pageSize >= 0); return new PagedEnumerable(collection, currentPage, pageSize); } public class PagedEnumerable : IEnumerable { public PagedEnumerable(IEnumerable collection, int currentPage = 1, int pageSize = 0) { Contract.Requires(collection != null); Contract.Assume(currentPage >= 1); Contract.Assume(pageSize >= 0); this.collection = collection; this.PageSize = pageSize; this.CurrentPage = currentPage; } IEnumerable collection; int currentPage; public int CurrentPage { get { if (this.currentPage > this.TotalPages) { return this.TotalPages; } return this.currentPage; } set { if (value < 1) { this.currentPage = 1; } else if (value > this.TotalPages) { this.currentPage = this.TotalPages; } else { this.currentPage = value; } } } int pageSize; public int PageSize { get { if (this.pageSize == 0) { return this.collection.Count(); } return this.pageSize; } set { this.pageSize = (value < 0) ? 0 : value; } } public int TotalPages { get { return (int)Math.Ceiling(this.collection.Count() / (double)this.PageSize); } } public IEnumerator GetEnumerator() { var pageSize = this.PageSize; var currentPage = this.CurrentPage; var startCount = (currentPage - 1) * pageSize; return this.collection.Skip(startCount).Take(pageSize).GetEnumerator(); } IEnumerator IEnumerable.GetEnumerator() { return this.GetEnumerator(); } }

  Read the article

• RC of Entity Framework 4.1 (which includes EF Code First)

  - by ScottGu

  Last week the data team shipped the Release Candidate of Entity Framework 4.1.  You can learn more about it and download it here. EF 4.1 includes the new “EF Code First” option that I’ve blogged about several times in the past.  EF Code First provides a really elegant and clean way to work with data, and enables you to do so without requiring a designer or XML mapping file.  Below are links to some tutorials I’ve written in the past about it: Code First Development with Entity Framework 4.x EF Code First: Custom Database Schema Mapping Using EF Code First with an Existing Database The above tutorials were written against the CTP4 release of EF Code First (and so some APIs might be a little different) – but the concepts and scenarios outlined in them are the same as with the RC. Go Live License Last week’s EF 4.1 RC ships with a “go live” license that enables you to use it in production environments.  The final release of EF 4.1 will ship within the next 4 weeks and will be 100% API compatible with the RC release. Improvements with the RC The RC includes several improvements and enhancements.  The EF team has a good blog post summarizing the RC changes.  Scott Hanselman also has a nice video interview with the data team that talks more about the release. One of my favorite improvements introduced with last week’s RC is its support for medium trust security.  This enables you to use EF 4.1 (and code-first) within low-cost ASP.NET shared hosting web environments – without requiring a hoster to install anything to use it. EF 4.1 also now supports validation with not only code-first scenarios, but also model-first and database-first workflows.  Upgrading from previous releases The RC does include a few API tweaks and changes from the prior CTP builds.  Read the release notes that come with the release to get a more detailed listing of the changes. John Papa also has an excellent Upgrading to EF 4.1 RC blog post that describes the steps he took when upgrading a large project he wrote with the previous CTP5 release.  The work to upgrade is pretty straight forward and easy – use his write-up as a guide on how to quickly update projects of your own. NuGet Package Rename One of the changes that the data team made between the CTP5 and RC releases was to rename the NuGet package name from “EFCodeFirst” to “EntityFramework”. They decided to make this change since the EF 4.1 release now includes several additions above and beyond just code first. If you already have installed the “EFCodeFirst” NuGet package, you’ll want to uninstall it and then install the new “EntityFramework” NuGet package.  John Papa’s blog post details the exact steps on how to do this (it only takes ~20 seconds to do this). More EF Tutorials Julie Lerman has created some nice whitepapers and tutorials for MSDN that show using the new EF4 and EF 4.1 feature set. Click here to find links to read and watch them. Summary I’m really excited about the EF 4.1 release that will be shipping next month.  It significantly improves the Entity Framework, and makes it even easier and cleaner to work with data inside of .NET.  You can take advantage of it within all ASP.NET projects (including both Web Forms and MVC), within client projects using Windows Forms and WPF, and within other project types like WCF, Console and Services.  You can use NuGet to easily install it within all of them. Hope this helps, Scott P.S. I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

  Read the article

• Identity Map Pattern and the Entity Framework

  - by nikolaosk

  This is going to be the seventh post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here and the third one here , the fourth one here , the fifth one here and the sixth one here . I have a post regarding ASP.Net and EntityDataSource. You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a look at them here , here and here . In...(read more)

  Read the article

• Is it possible to implement an infinite IEnumerable without using yield with only C# code?

  - by sinelaw

  This isn't a practical problem, it's more of a riddle. Problem I'm curious to know if there's a way to implement something equivalent to the following, but without using yield: IEnumerable<T> Infinite<T>() { while (true) { yield return default(T); } } Rules You can't use the yield keyword Use only C# itself directly - no IL code, no constructing dynamic assemblies etc. You can only use the basic .NET lib (only mscorlib.dll, System.Core.dll? not sure what else to include). However if you find a solution with some of the other .NET assemblies (WPF?!), I'm also interested. Don't implement IEnumerable or IEnumerator. Notes The closest I've come yet: IEnumerable<int> infinite = null; infinite = new int[1].SelectMany(x => new int[1].Concat(infinite)); This is "correct" but hits a StackOverflowException after 14399 iterations through the enumerable (not quite infinite). I'm thinking there might be no way to do this due to the CLR's lack of tail recursion optimization. A proof would be nice :)

  Read the article

• Commerce Anywhere...Where the Web, Store, Mobile, Social and Call Center Come Together

  - by divya.malik

  I am pleased to introduce guest blogger, Bill Zujewski today. Bill has just joined the Oracle CRM Product Marketing team as part of our recent ATG acquisition. Based in Cambridge, MA Bill was the VP of Product Marketing for ATG and collaborated on eCommerce strategy with some of the best brands in the world. Welcome Bill!! BY BILL ZUJEWSKI "Times are a changing"...or so the song goes. Not long ago, eCommerce just meant having a cool brand and a slick website. Today, customers expect much more... what I think they really want...Commerce Anywhere...a seamless, consistent and personal way to interact or transact business with you and your products, whether they start on the web, go into a store, talk over the phone, access products via their mobile device or on their favorite social media site. They want one more thing... for you to remember them and their history with you... so they can be treated more intelligently and not have to repeat previous interactions. It makes sense to me, I want it too... it saves me time and money. I work with many companies that are trying to understand how to evolve their business structure and technology solutions to meet the challenges of Commerce Anywhere. My advice ... think differently and take a more holistic approach to the customer experience and the cross-channel selling solution. Stop integrating siloed legacy systems and start thinking about a single platform as your new foundation... the e-Commerce platform. I recently wrote a new white paper, Commerce Anywhere - A Business and Technology ! Strategy to Maximize Cross- channel Commerce Growth to help our customers better understand how to create that "Commerce Anywhere" customer experience that customers really want. The paper offers practical insights into an IT transformation that can help you leverage a commerce platform to go beyond the web store front and instead use it to enable rapid expansion into mobile apps, new in-store apps, and interact with your customers through social commerce. Let me know what you think by posting a comment on this blog.

  Read the article

• Taming Hopping Windows

  - by Roman Schindlauer

  At first glance, hopping windows seem fairly innocuous and obvious. They organize events into windows with a simple periodic definition: the windows have some duration d (e.g. a window covers 5 second time intervals), an interval or period p (e.g. a new window starts every 2 seconds) and an alignment a (e.g. one of those windows starts at 12:00 PM on March 15, 2012 UTC). var wins = xs     .HoppingWindow(TimeSpan.FromSeconds(5),                    TimeSpan.FromSeconds(2),                    new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc)); Logically, there is a window with start time a + np and end time a + np + d for every integer n. That’s a lot of windows. So why doesn’t the following query (always) blow up? var query = wins.Select(win => win.Count()); A few users have asked why StreamInsight doesn’t produce output for empty windows. Primarily it’s because there is an infinite number of empty windows! (Actually, StreamInsight uses DateTimeOffset.MaxValue to approximate “the end of time” and DateTimeOffset.MinValue to approximate “the beginning of time”, so the number of windows is lower in practice.) That was the good news. Now the bad news. Events also have duration. Consider the following simple input: var xs = this.Application                 .DefineEnumerable(() => new[]                     { EdgeEvent.CreateStart(DateTimeOffset.UtcNow, 0) })                 .ToStreamable(AdvanceTimeSettings.IncreasingStartTime); Because the event has no explicit end edge, it lasts until the end of time. So there are lots of non-empty windows if we apply a hopping window to that single event! For this reason, we need to be careful with hopping window queries in StreamInsight. Or we can switch to a custom implementation of hopping windows that doesn’t suffer from this shortcoming. The alternate window implementation produces output only when the input changes. We start by breaking up the timeline into non-overlapping intervals assigned to each window. In figure 1, six hopping windows (“Windows”) are assigned to six intervals (“Assignments”) in the timeline. Next we take input events (“Events”) and alter their lifetimes (“Altered Events”) so that they cover the intervals of the windows they intersect. In figure 1, you can see that the first event e1 intersects windows w1 and w2 so it is adjusted to cover assignments a1 and a2. Finally, we can use snapshot windows (“Snapshots”) to produce output for the hopping windows. Notice however that instead of having six windows generating output, we have only four. The first and second snapshots correspond to the first and second hopping windows. The remaining snapshots however cover two hopping windows each! While in this example we saved only two events, the savings can be more significant when the ratio of event duration to window duration is higher. Figure 1: Timeline The implementation of this strategy is straightforward. We need to set the start times of events to the start time of the interval assigned to the earliest window including the start time. Similarly, we need to modify the end times of events to the end time of the interval assigned to the latest window including the end time. The following snap-to-boundary function that rounds a timestamp value t down to the nearest value t' <= t such that t' is a + np for some integer n will be useful. For convenience, we will represent both DateTime and TimeSpan values using long ticks: static long SnapToBoundary(long t, long a, long p) {     return t - ((t - a) % p) - (t > a ? 0L : p); } How do we find the earliest window including the start time for an event? It’s the window following the last window that does not include the start time assuming that there are no gaps in the windows (i.e. duration < interval), and limitation of this solution. To find the end time of that antecedent window, we need to know the alignment of window ends: long e = a + (d % p); Using the window end alignment, we are finally ready to describe the start time selector: static long AdjustStartTime(long t, long e, long p) {     return SnapToBoundary(t, e, p) + p; } To find the latest window including the end time for an event, we look for the last window start time (non-inclusive): public static long AdjustEndTime(long t, long a, long d, long p) {     return SnapToBoundary(t - 1, a, p) + p + d; } Bringing it together, we can define the translation from events to ‘altered events’ as in Figure 1: public static IQStreamable<T> SnapToWindowIntervals<T>(IQStreamable<T> source, TimeSpan duration, TimeSpan interval, DateTime alignment) {     if (source == null) throw new ArgumentNullException("source");     // reason about DateTime and TimeSpan in ticks     long d = Math.Min(DateTime.MaxValue.Ticks, duration.Ticks);     long p = Math.Min(DateTime.MaxValue.Ticks, Math.Abs(interval.Ticks));     // set alignment to earliest possible window     var a = alignment.ToUniversalTime().Ticks % p;     // verify constraints of this solution     if (d <= 0L) { throw new ArgumentOutOfRangeException("duration"); }     if (p == 0L || p > d) { throw new ArgumentOutOfRangeException("interval"); }     // find the alignment of window ends     long e = a + (d % p);     return source.AlterEventLifetime(         evt => ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p)),         evt => ToDateTime(AdjustEndTime(evt.EndTime.ToUniversalTime().Ticks, a, d, p)) -             ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p))); } public static DateTime ToDateTime(long ticks) {     // just snap to min or max value rather than under/overflowing     return ticks < DateTime.MinValue.Ticks         ? new DateTime(DateTime.MinValue.Ticks, DateTimeKind.Utc)         : ticks > DateTime.MaxValue.Ticks         ? new DateTime(DateTime.MaxValue.Ticks, DateTimeKind.Utc)         : new DateTime(ticks, DateTimeKind.Utc); } Finally, we can describe our custom hopping window operator: public static IQWindowedStreamable<T> HoppingWindow2<T>(     IQStreamable<T> source,     TimeSpan duration,     TimeSpan interval,     DateTime alignment) {     if (source == null) { throw new ArgumentNullException("source"); }     return SnapToWindowIntervals(source, duration, interval, alignment).SnapshotWindow(); } By switching from HoppingWindow to HoppingWindow2 in the following example, the query returns quickly rather than gobbling resources and ultimately failing! public void Main() {     var start = new DateTimeOffset(new DateTime(2012, 6, 28), TimeSpan.Zero);     var duration = TimeSpan.FromSeconds(5);     var interval = TimeSpan.FromSeconds(2);     var alignment = new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc);     var events = this.Application.DefineEnumerable(() => new[]     {         EdgeEvent.CreateStart(start.AddSeconds(0), "e0"),         EdgeEvent.CreateStart(start.AddSeconds(1), "e1"),         EdgeEvent.CreateEnd(start.AddSeconds(1), start.AddSeconds(2), "e1"),         EdgeEvent.CreateStart(start.AddSeconds(3), "e2"),         EdgeEvent.CreateStart(start.AddSeconds(9), "e3"),         EdgeEvent.CreateEnd(start.AddSeconds(3), start.AddSeconds(10), "e2"),         EdgeEvent.CreateEnd(start.AddSeconds(9), start.AddSeconds(10), "e3"),     }).ToStreamable(AdvanceTimeSettings.IncreasingStartTime);     var adjustedEvents = SnapToWindowIntervals(events, duration, interval, alignment);     var query = from win in HoppingWindow2(events, duration, interval, alignment)                 select win.Count();     DisplayResults(adjustedEvents, "Adjusted Events");     DisplayResults(query, "Query"); } As you can see, instead of producing a massive number of windows for the open start edge e0, a single window is emitted from 12:00:15 AM until the end of time: Adjusted Events StartTime EndTime Payload 6/28/2012 12:00:01 AM 12/31/9999 11:59:59 PM e0 6/28/2012 12:00:03 AM 6/28/2012 12:00:07 AM e1 6/28/2012 12:00:05 AM 6/28/2012 12:00:15 AM e2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM e3 Query StartTime EndTime Payload 6/28/2012 12:00:01 AM 6/28/2012 12:00:03 AM 1 6/28/2012 12:00:03 AM 6/28/2012 12:00:05 AM 2 6/28/2012 12:00:05 AM 6/28/2012 12:00:07 AM 3 6/28/2012 12:00:07 AM 6/28/2012 12:00:11 AM 2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM 3 6/28/2012 12:00:15 AM 12/31/9999 11:59:59 PM 1 Regards, The StreamInsight Team

  Read the article

• What is Rainbow (not the CMS)

  - by Jeremy Thompson

  I was reading this excellent blog article regarding speeding up the badge page and in the last comment the author @waffles (a.k.a Sam Saffron) mentions these tools: dapper and a bunch of custom helpers like rainbow, sql builder etc Dapper and sql builder was easy to look up but rainbow keeps pointing me to a CMS, can someone please point me to the real source? Thanks. Obviously the architecture of these [SE] sites is uber cool and ultra fast so no comments on that thanks.

  Read the article

• Using 'new' in a projection?

  - by davenewza

  I wish to project a collection from one type (Something) to another type (SomethingElse). Yes, this is a very open-eneded question, but which of the two options below do you prefer? Creating a new instance using new: var result = query.Select(something => new SomethingElse(something)); Using a factory: var result = query.Select(something => SomethingElse.FromSomething(something)); When I think of a projection, I generally think of it as a conversion. Using new gives me this idea that I'm creating new objects during a conversion, which doesn't feel right. Semantically, SomethingElse.FromSomething() most definitely fits better. Although, the second option does require addition code to setup a factory, which could become unnecessarily compulsive.

  Read the article

• Extension methods on a null object instance – something you did not know

  - by nmarun

  Extension methods gave developers with a lot of bandwidth to do interesting (read ‘cool’) things. But there are a couple of things that we need to be aware of while using these extension methods. I have a StringUtil class that defines two extension methods: 1: public static class StringUtils 2: { 3: public static string Left( this string arg, int leftCharCount) 4: { 5: if (arg == null ) 6: { 7: throw new ArgumentNullException( "arg" ); 8: } 9: return arg.Substring(0, leftCharCount); 10...(read more)

  Read the article

• Using Subjects to Deploy Queries Dynamically

  - by Roman Schindlauer

  In the previous blog posting, we showed how to construct and deploy query fragments to a StreamInsight server, and how to re-use them later. In today’s posting we’ll integrate this pattern into a method of dynamically composing a new query with an existing one. The construct that enables this scenario in StreamInsight V2.1 is a Subject. A Subject lets me create a junction element in an existing query that I can tap into while the query is running. To set this up as an end-to-end example, let’s first define a stream simulator as our data source: var generator = myApp.DefineObservable(     (TimeSpan t) => Observable.Interval(t).Select(_ => new SourcePayload())); This ‘generator’ produces a new instance of SourcePayload with a period of t (system time) as an IObservable. SourcePayload happens to have a property of type double as its payload data. Let’s also define a sink for our example—an IObserver of double values that writes to the console: var console = myApp.DefineObserver(     (string label) => Observer.Create<double>(e => Console.WriteLine("{0}: {1}", label, e)))     .Deploy("ConsoleSink"); The observer takes a string as parameter which is used as a label on the console, so that we can distinguish the output of different sink instances. Note that we also deploy this observer, so that we can retrieve it later from the server from a different process. Remember how we defined the aggregation as an IQStreamable function in the previous article? We will use that as well: var avg = myApp     .DefineStreamable((IQStreamable<SourcePayload> s, TimeSpan w) =>         from win in s.TumblingWindow(w)         select win.Avg(e => e.Value))     .Deploy("AverageQuery"); Then we define the Subject, which acts as an observable sequence as well as an observer. Thus, we can feed a single source into the Subject and have multiple consumers—that can come and go at runtime—on the other side: var subject = myApp.CreateSubject("Subject", () => new Subject<SourcePayload>()); Subject are always deployed automatically. Their name is used to retrieve them from a (potentially) different process (see below). Note that the Subject as we defined it here doesn’t know anything about temporal streams. It is merely a sequence of SourcePayloads, without any notion of StreamInsight point events or CTIs. So in order to compose a temporal query on top of the Subject, we need to 'promote' the sequence of SourcePayloads into an IQStreamable of point events, including CTIs: var stream = subject.ToPointStreamable(     e => PointEvent.CreateInsert<SourcePayload>(e.Timestamp, e),     AdvanceTimeSettings.StrictlyIncreasingStartTime); In a later posting we will show how to use Subjects that have more awareness of time and can be used as a junction between QStreamables instead of IQbservables. Having turned the Subject into a temporal stream, we can now define the aggregate on this stream. We will use the IQStreamable entity avg that we defined above: var longAverages = avg(stream, TimeSpan.FromSeconds(5)); In order to run the query, we need to bind it to a sink, and bind the subject to the source: var standardQuery = longAverages     .Bind(console("5sec average"))     .With(generator(TimeSpan.FromMilliseconds(300)).Bind(subject)); Lastly, we start the process: standardQuery.Run("StandardProcess"); Now we have a simple query running end-to-end, producing results. What follows next is the crucial part of tapping into the Subject and adding another query that runs in parallel, using the same query definition (the “AverageQuery”) but with a different window length. We are assuming that we connected to the same StreamInsight server from a different process or even client, and thus have to retrieve the previously deployed entities through their names: // simulate the addition of a 'fast' query from a separate server connection, // by retrieving the aggregation query fragment // (instead of simply using the 'avg' object) var averageQuery = myApp     .GetStreamable<IQStreamable<SourcePayload>, TimeSpan, double>("AverageQuery"); // retrieve the input sequence as a subject var inputSequence = myApp     .GetSubject<SourcePayload, SourcePayload>("Subject"); // retrieve the registered sink var sink = myApp.GetObserver<string, double>("ConsoleSink"); // turn the sequence into a temporal stream var stream2 = inputSequence.ToPointStreamable(     e => PointEvent.CreateInsert<SourcePayload>(e.Timestamp, e),     AdvanceTimeSettings.StrictlyIncreasingStartTime); // apply the query, now with a different window length var shortAverages = averageQuery(stream2, TimeSpan.FromSeconds(1)); // bind new sink to query and run it var fastQuery = shortAverages     .Bind(sink("1sec average"))     .Run("FastProcess"); The attached solution demonstrates the sample end-to-end. Regards, The StreamInsight Team

  Read the article

• Why do I get a connection error / timeout when using python suds to connect to Microsoft CRM?

  - by Chris R

  When I try to connect to an MS CRM web service using suds/python-ntlm, I am getting a timeout on requests. However, the code that I'm trying to replace -- which calls out to the cURL command line app to do the same call -- succeeds. Clearly something is different in the way that cURL is sending the command data, but I'll be damned if I know what the difference is. Below are the full details of the various calls. Anyone got any tips? Here's the code that is making the request, followed by the output. The cURL command code is below that, and its response follows. Hosts, users, and passwords have been changed to protect the innocent, of course. wsdl_url = 'https://client.service.host/MSCrmServices/2007/MetadataService.asmx?WSDL' username = r'domain\user.name' password = 'userpass' from suds.transport.https import WindowsHttpAuthenticated from suds.client import Client import logging logging.basicConfig(level=logging.INFO) logging.getLogger('suds.client').setLevel(logging.DEBUG) logging.getLogger('suds.transport').setLevel(logging.DEBUG) ntlmTransport = WindowsHttpAuthenticated(username=username, password=password) metadata_client = Client(wsdl_url, transport=ntlmTransport) request = metadata_client.factory.create('RetrieveAttributeRequest') request.MetadataId = '00000000-0000-0000-0000-000000000000' request.EntityLogicalName = 'opportunity' request.LogicalName = 'new_typeofcontact' request.RetrieveAsIfPublished = 'false' attr = metadata_client.service.Execute(request) print attr Here's the output: DEBUG:suds.client:sending to (http://client.service.host/MSCrmServices/2007/MetadataService.asmx) message: <SOAP-ENV:Envelope xmlns:ns0="http://schemas.xmlsoap.org/soap/envelope/" xmlns:ns1="http://schemas.microsoft.com/crm/2007/WebServices" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:SOAP-ENV="http://schemas.xmlsoap.org/soap/envelope/"> <SOAP-ENV:Header/> <ns0:Body> <ns1:Execute> <ns1:Request xsi:type="ns1:RetrieveAttributeRequest"> <ns1:MetadataId>00000000-0000-0000-0000-000000000000</ns1:MetadataId> <ns1:EntityLogicalName>opportunity</ns1:EntityLogicalName> <ns1:LogicalName>new_typeofcontact</ns1:LogicalName> <ns1:RetrieveAsIfPublished>false</ns1:RetrieveAsIfPublished> </ns1:Request> </ns1:Execute> </ns0:Body> </SOAP-ENV:Envelope> DEBUG:suds.client:headers = {'SOAPAction': u'"http://schemas.microsoft.com/crm/2007/WebServices/Execute"', 'Content-Type': 'text/xml'} DEBUG:suds.transport.http:sending: URL:http://client.service.host/MSCrmServices/2007/MetadataService.asmx HEADERS: {'SOAPAction': u'"http://schemas.microsoft.com/crm/2007/WebServices/Execute"', 'Content-Type': 'text/xml', 'Content-type': 'text/xml', 'Soapaction': u'"http://schemas.microsoft.com/crm/2007/WebServices/Execute"'} MESSAGE: <SOAP-ENV:Envelope xmlns:ns0="http://schemas.xmlsoap.org/soap/envelope/" xmlns:ns1="http://schemas.microsoft.com/crm/2007/WebServices" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:SOAP-ENV="http://schemas.xmlsoap.org/soap/envelope/"> <SOAP-ENV:Header/> <ns0:Body> <ns1:Execute> <ns1:Request xsi:type="ns1:RetrieveAttributeRequest"> <ns1:MetadataId>00000000-0000-0000-0000-000000000000</ns1:MetadataId> <ns1:EntityLogicalName>opportunity</ns1:EntityLogicalName> <ns1:LogicalName>new_typeofcontact</ns1:LogicalName> <ns1:RetrieveAsIfPublished>false</ns1:RetrieveAsIfPublished> </ns1:Request> </ns1:Execute> </ns0:Body> </SOAP-ENV:Envelope> ERROR: An unexpected error occurred while tokenizing input The following traceback may be corrupted or invalid The error message is: ('EOF in multi-line statement', (16, 0)) --------------------------------------------------------------------------- URLError Traceback (most recent call last) /Users/crose/projects/2366/crm/<ipython console> in <module>() /var/folders/nb/nbJAzxR1HbOppPcs6xO+dE+++TY/-Tmp-/python-67186icm.py in <module>() 19 request.LogicalName = 'new_typeofcontact' 20 request.RetrieveAsIfPublished = 'false' 21 ---> 22 attr = metadata_client.service.Execute(request) 23 print attr /Users/crose/virtualenv/advanis/lib/python2.6/site-packages/suds/client.pyc in __call__(self, *args, **kwargs) 537 return (500, e) 538 else: --> 539 return client.invoke(args, kwargs) 540 541 def faults(self): /Users/crose/virtualenv/advanis/lib/python2.6/site-packages/suds/client.pyc in invoke(self, args, kwargs) 596 self.method.name, timer) 597 timer.start() --> 598 result = self.send(msg) 599 timer.stop() 600 metrics.log.debug( /Users/crose/virtualenv/advanis/lib/python2.6/site-packages/suds/client.pyc in send(self, msg) 621 request = Request(location, str(msg)) 622 request.headers = self.headers() --> 623 reply = transport.send(request) 624 if retxml: 625 result = reply.message /Users/crose/virtualenv/advanis/lib/python2.6/site-packages/suds/transport/https.pyc in send(self, request) 62 def send(self, request): 63 self.addcredentials(request) ---> 64 return HttpTransport.send(self, request) 65 66 def addcredentials(self, request): /Users/crose/virtualenv/advanis/lib/python2.6/site-packages/suds/transport/http.pyc in send(self, request) 75 request.headers.update(u2request.headers) 76 log.debug('sending:\n%s', request) ---> 77 fp = self.u2open(u2request) 78 self.getcookies(fp, u2request) 79 result = Reply(200, fp.headers.dict, fp.read()) /Users/crose/virtualenv/advanis/lib/python2.6/site-packages/suds/transport/http.pyc in u2open(self, u2request) 116 return url.open(u2request) 117 else: --> 118 return url.open(u2request, timeout=tm) 119 120 def u2opener(self): /System/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/urllib2.pyc in open(self, fullurl, data, timeout) 381 req = meth(req) 382 --> 383 response = self._open(req, data) 384 385 # post-process response /System/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/urllib2.pyc in _open(self, req, data) 399 protocol = req.get_type() 400 result = self._call_chain(self.handle_open, protocol, protocol + --> 401 '_open', req) 402 if result: 403 return result /System/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/urllib2.pyc in _call_chain(self, chain, kind, meth_name, *args) 359 func = getattr(handler, meth_name) 360 --> 361 result = func(*args) 362 if result is not None: 363 return result /System/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/urllib2.pyc in http_open(self, req) 1128 1129 def http_open(self, req): -> 1130 return self.do_open(httplib.HTTPConnection, req) 1131 1132 http_request = AbstractHTTPHandler.do_request_ /System/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/urllib2.pyc in do_open(self, http_class, req) 1103 r = h.getresponse() 1104 except socket.error, err: # XXX what error? -> 1105 raise URLError(err) 1106 1107 # Pick apart the HTTPResponse object to get the addinfourl URLError: <urlopen error [Errno 60] Operation timed out> The cURL command is: /opt/local/bin/curl --ntlm -u "domain\user.name:userpass" -k -d @- -A "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.2; SV1; .NET CLR 1.1.4322; .NET CLR 2.0.50727; .NET CLR 3.0.04506.648; .NET CLR 3.5.21022; InfoPath.1)" -H "Connection: Keep-Alive" -H "Content-Type: text/xml; charset=utf-8" -H "SOAPAction: http://schemas.microsoft.com/crm/2007/WebServices/Execute" https://client.service.host/MSCrmServices/2007/MetadataService.asmx The data that is piped to that cURL command: <soap:Envelope xmlns:soap="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <soap:Header> <CrmAuthenticationToken xmlns="http://schemas.microsoft.com/crm/2007/WebServices"> <AuthenticationType xmlns="http://schemas.microsoft.com/crm/2007/CoreTypes">0</AuthenticationType> <CrmTicket xmlns="http://schemas.microsoft.com/crm/2007/CoreTypes"></CrmTicket> <OrganizationName xmlns="http://schemas.microsoft.com/crm/2007/CoreTypes">CMIFS</OrganizationName> <CallerId xmlns="http://schemas.microsoft.com/crm/2007/CoreTypes">00000000-0000-0000-0000-000000000000</CallerId> </CrmAuthenticationToken> </soap:Header> <soap:Body> <Execute xmlns="http://schemas.microsoft.com/crm/2007/WebServices"> <Request xsi:type="RetrieveAttributeRequest"> <MetadataId>00000000-0000-0000-0000-000000000000</MetadataId> <EntityLogicalName>opportunity</EntityLogicalName> <LogicalName>new_typeofcontact</LogicalName> <RetrieveAsIfPublished>false</RetrieveAsIfPublished> </Request> </Execute> </soap:Body> </soap:Envelope> Here's the response: <?xml version="1.0" encoding="utf-8"?> <soap:Envelope xmlns:soap="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <soap:Body> <ExecuteResponse xmlns="http://schemas.microsoft.com/crm/2007/WebServices"> <Response xsi:type="RetrieveAttributeResponse"> <AttributeMetadata xsi:type="PicklistAttributeMetadata"> <MetadataId>101346cf-a6af-4eb4-a4bf-9c3c6bbd6582</MetadataId> <SchemaName>New_TypeofContact</SchemaName> <LogicalName>new_typeofcontact</LogicalName> <EntityLogicalName>opportunity</EntityLogicalName> <AttributeType> <Value>Picklist</Value> </AttributeType> <!-- stuff here --> </AttributeMetadata> </Response> </ExecuteResponse> </soap:Body> </soap:Envelope>

  Read the article

• Dynamic Data with Subsonic 3

  - by Ezequiel Bertti

  i want to make a webproject with Subsonic and Dynamic Data... But when i go register the ContextData a don't have it in subsonic with LINQ... in Global.asax.cs a have to do something like this model.RegisterContext(SubSonicRepo, new ContextConfiguration() { ScaffoldAllTables = true }); how can i make it work? have some way to make it work? using entities or LINQ everything work... but using Subsonic with linq it not work...

  Read the article

• Passing integer lists in a sql query, best practices

  - by Artiom Chilaru

  I'm currently looking at ways to pass lists of integers in a SQL query, and try to decide which of them is best in which situation, what are the benefots of each, and what are the pitfalls, what should be avoided :) Right now I know of 3 ways that we currently use in our application. 1) Table valued parameter: Create a new Table Valued Parameter in sql server: CREATE TYPE [dbo].[TVP_INT] AS TABLE( [ID] [int] NOT NULL ) Then run the query against it: using (var conn = new SqlConnection(DataContext.GetDefaultConnectionString)) { var comm = conn.CreateCommand(); comm.CommandType = CommandType.Text; comm.CommandText = @" UPDATE DA SET [tsLastImportAttempt] = CURRENT_TIMESTAMP FROM [Account] DA JOIN @values IDs ON DA.ID = IDs.ID"; comm.Parameters.Add(new SqlParameter("values", downloadResults.Select(d => d.ID).ToDataTable()) { TypeName = "TVP_INT" }); conn.Open(); comm.ExecuteScalar(); } The major disadvantages of this method is the fact that Linq doesn't support table valued params (if you create an SP with a TVP param, linq won't be able to run it) :( 2) Convert the list to Binary and use it in Linq! This is a bit better.. Create an SP, and you can run it within linq :) To do this, the SP will have an IMAGE parameter, and we'll be using a user defined function (udf) to convert this to a table.. We currently have implementations of this function written in C++ and in assembly, both have pretty much the same performance :) Basically, each integer is represented by 4 bytes, and passed to the SP. In .NET we have an extension method that convers an IEnumerable to a byte array The extension method: public static Byte[] ToBinary(this IEnumerable intList) { return ToBinaryEnum(intList).ToArray(); } private static IEnumerable<Byte> ToBinaryEnum(IEnumerable<Int32> intList) { IEnumerator<Int32> marker = intList.GetEnumerator(); while (marker.MoveNext()) { Byte[] result = BitConverter.GetBytes(marker.Current); Array.Reverse(result); foreach (byte b in result) yield return b; } } The SP: CREATE PROCEDURE [Accounts-UpdateImportAttempts] @values IMAGE AS BEGIN UPDATE DA SET [tsLastImportAttempt] = CURRENT_TIMESTAMP FROM [Account] DA JOIN dbo.udfIntegerArray(@values, 4) IDs ON DA.ID = IDs.Value4 END And we can use it by running the SP directly, or in any linq query we need using (var db = new DataContext()) { db.Accounts_UpdateImportAttempts(downloadResults.Select(d => d.ID).ToBinary()); // or var accounts = db.Accounts .Where(a => db.udfIntegerArray(downloadResults.Select(d => d.ID).ToBinary(), 4) .Select(i => i.Value4) .Contains(a.ID)); } This method has the benefit of using compiled queries in linq (which will have the same sql definition, and query plan, so will also be cached), and can be used in SPs as well. Both these methods are theoretically unlimited, so you can pass millions of ints at a time :) 3) The simple linq .Contains() It's a more simple approach, and is perfect in simple scenarios. But is of course limited by this. using (var db = new DataContext()) { var accounts = db.Accounts .Where(a => downloadResults.Select(d => d.ID).Contains(a.ID)); } The biggest drawback of this method is that each integer in the downloadResults variable will be passed as a separate int.. In this case, the query is limited by sql (max allowed parameters in a sql query, which is a couple of thousand, if I remember right). So I'd like to ask.. What do you think is the best of these, and what other methods and approaches have I missed?

  Read the article

• Import Namespace System.Query

  - by GateKiller

  I am trying to load Linq on my .Net 3.5 enabled web server by adding the following to my .aspx page: <%@ Import Namespace="System.Query" %> However, this fails and tells me it cannot find the namespace. The type or namespace name 'Query' does not exist in the namespace 'System' I have also tried with no luck: System.Data.Linq System.Linq System.Xml.Linq I believe that .Net 3.5 is working because var hello = "Hello World" seems to work. Can anyone help please? Cheers, Stephen PS: I just want to clarify that I don't use Visual Studio, I simple have a Text Editor and write my code directly into .aspx files.

  Read the article

< Previous Page | 93 94 95 96 97 98 99 100 101 102 103 104  | Next Page >