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  • Strange response from WCF service, how to return json easily

    - by Exitos
    I want to get a service to respond with just JSON. I have written the following code: namespace BM.Security { [ServiceContract(Namespace = "")] [AspNetCompatibilityRequirements(RequirementsMode = AspNetCompatibilityRequirementsMode.Allowed)] public class AssocFileService { [OperationContract] [WebGet(ResponseFormat = WebMessageFormat.Json)] public List<Person> GetPeople(int message) { List<Person> myList = new List<Person>(); Person p = new Person() { Age = 28, Name="Name1" }; Person p2 = new Person() { Age = 26, Name = "Name2" }; myList.Add(p); myList.Add(p2); return myList; } } [DataContract] public class Person { [DataMember] public string Name { get; set; } [DataMember] public int Age { get; set; } } } But im getting the following JSON back which is really wierd... { "d" : [ { "Age" : 28, "Name" : "Name1", "__type" : "Person:#Bm.Security" }, { "Age" : 26, "Name" : "Name2", "__type" : "Person:#BM.Security" } ] } I'm totally stumped by the "d" no idea where that has come from. And also by the __type variable, no thanks don't really want that in my Json :-( How do I set the root node in my data to replace that d? Where did the d come from? So many questions... Hope someone can help....

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  • Can I use WCF in this case?

    - by BDotA
    We have a third party application that provied its web services to us by ASMX and it is created at the time of .NET 1.1 in the old days we were using VB 6.0 and connected to it by a PocketSOAP, etc... bt now we want to replace the VB 6.0 with C# 3.5 WinApps and still use that third party web services. so I wish to know what are my options for doing this? which one do you recommend and which one has a faster learning curve? Thanks All.

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  • wcf net.tcp service fails to start when extra properties are set

    - by Pharabus
    i have a current project that runs fine with a self hosted net.tcp binding if I uses the following host.AddServiceEndpoint(typeof(IMonitorService), new NetTcpBinding() {PortSharingEnabled = false }, ""); host.AddServiceEndpoint(ServiceMetadataBehavior.MexContractName, MetadataExchangeBindings.CreateMexTcpBinding(), "mex"); however if I ammend to the below it fails to run with the message that there is already an endpoint on the port, can anyone explain why adding the extra properties causes it to fail? host.AddServiceEndpoint(typeof(IMonitorService), new NetTcpBinding() {PortSharingEnabled = false,ListenBacklog=1000,ReceiveTimeout=new TimeSpan(0,3,0) }, ""); host.AddServiceEndpoint(ServiceMetadataBehavior.MexContractName, MetadataExchangeBindings.CreateMexTcpBinding(), "mex"); Edit: testing confirms that the ReceiveTimeout property works Ok, as soon as I add the MaxConnections or ListenBacklog the service fails start Edit 2: this link seems to imply i ned portsharing is i want to modify these properies, not sure I am understanding it.

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  • Java generic Interface performance

    - by halfwarp
    Simple question, but tricky answer I guess. Does using Generic Interfaces hurts performance? Example: public interface Stuff<T> { void hello(T var); } vs public interface Stuff { void hello(Integer var); <---- Integer used just as an example } My first thought is that it doesn't. Generics are just part of the language and the compiler will optimize it as though there were no generics (at least in this particular case of generic interfaces). Is this correct?

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  • AS3: Performance question calling an event function with null param

    - by adehaas
    Lately I needed to call a listener function without an actual listener like so: foo(null); private function foo(event:Event):void { //do something } So I was wondering if there is a significant difference regarding performance between this and using the following, in which I can prevent the null in calling the function without the listener, but am still able to call it with a listener as well: foo(); private function foo(event:Event = null):void { } I am not sure wether it is just a question of style, or actually bad practice and I should write two similar functions, one with and one without the event param (which seems cumbersome to me). Looking forward to your opinions, thx.

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  • error while adding WCF service reference

    - by user1561256
    There was an error downloading . Unable to connect to the remote server No connection could be made because the target machine actively refused it Metadata contains a reference that cannot be resolved.There was no endpoint listening at that could accept the message. This is often caused by an incorrect address or SOAP action. See Inner Exception, if present, for more details. Unable to connect to the remote server No connection could be made because the target machine actively refused it. If the service is defined in the current solution, try building the solution and adding the service reference again. can pls somebody solve this.

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  • WCF service code in window application

    - by Mariya
    Hello, I am using C#.net application code. I require to call service for Window Application and i am using below code to open service Host, using (ServiceHost host = new ServiceHost( typeof(class1), new Uri[] { new Uri("net.pipe://localhost") }) ) { } & Then we have clinet Console application to connect to serviceHost. Problem is, When i create service/Client application Using Conslole Application both are working fine. But if i call servide code form Window application to connect to console client it gives Error for Binding Error like("No End Point/Address found to test") Can any one help me to run service from C# window application ? Thanks

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  • c# performance- create font

    - by user85917
    I have performance issues in this code segment which I think is caused by the "new Font". Will it be faster if fonts are static/global ? if (row.StartsWith(TILD_BEGIN)) { rtbTrace.SelectionColor = Color.Maroon; rtbTrace.SelectionFont = new Font(myFont, (float)8.25, FontStyle.Regular); if (row.StartsWith(BEGIN) ) rtbTrace.AppendText(Environment.NewLine + row + Environment.NewLine); else rtbTrace.AppendText(Environment.NewLine + row.Substring(1) + Environment.NewLine); continue; } if (row.StartsWith(EXCL_BEGIN)) { -- similar block } if (row.StartsWith(DLR_BEGIN)) { -- similar block } . . .

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  • SSRS Performance Mystery

    - by user101654
    I have a stored procedure that returns about 50000 records in 10sec using at most 2 cores in SSMS. The SSRS report using the stored procedure was taking 20min and would max out the processor on an 8 core server for the entire time. The report was relatively simple (i.e. no graphs, calculations). The report did not appear to be the issue as I wrote the 50K rows to a temp table and the report could display the data in a few seconds. I tried many different ideas for testing altering the stored procedure each time, but keeping the original code in a separate window to revert back to. After one Alter of the stored procedure, going back to the original code, the report and server utilization started running fast, comparable to the performance of the stored procedure alone. Everything is fine for now, but I am would like to get to the bottom of what caused this in case it happens again. Any ideas?

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  • Dispatching generic tasks in WCF or .Net Remoting

    - by Eric
    Hello all, I've been researching for a couple days on and off, and have yet to figure out the best way to achieve the following goal. I would like to define either an interface or abstract class in C# which has an associated Run method, similar to the Java runnable interface. The goal would be to have a shared queue which contains a list of these objects. Then individual clients would be able to derive their own concrete runnable classes and add them to the queue hosted by the server. Clients would also be able to pop these runnable objects off the queue and execute them arbitrarily. This seems like it should be feasible in a VM based language without needing to place any of the concrete implementations in a shared assembly, but I have thus far had no luck finding a working example of such a system. Does anyone know how this might be achieved?

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  • C# chart control Performance with large amounts of data

    - by user3642115
    I am using a chart control with a range bar graph to basically make a gantt chart for lots of people and lots of projects, say about 1000 total series. The issue that I am running in to is that once I have all my data added to the chart, which takes some time but that is to be expected, and I go to scroll down on my graph it freezes the whole application and takes a while before it unfreezes and scrolls down. Is there any way to improve the performance of this? I tried adding the graph to a panel and growing the graph size dynamically and then scrolling down from the panel but that cause a whole plethora of other issues. Any tips for speeding this up? I don't think it is my code as it has already finished running when this issue happens. Thanks.

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  • OpenGL performance on rendering "virtual gallery" (textures)

    - by maticus
    I have a considerable (120-240) amount of 640x480 images that will be displayed as textured flat surfaces (4 vertex polygons) in a 3D environment. About 30-50% of them will be visible in a given frame. It is possible for them to crossover. Nothing else will be present in the environment. The question is - will the modern and/or few-years-old (lets say Radeon 9550) GPU cope with that, and what frame rate can I expect? I aim for 20FPS, but 30-40 would be nice. Would changing the resolution to 320x240 make it more probable to happen? I do not have any previous experience with performance issues of 3D graphics on modern GPUs, and unfortunately I must make a design choice. I don't want to waste time on doing something that couldn't have worked :-)

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  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

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  • Columnstore Case Study #1: MSIT SONAR Aggregations

    - by aspiringgeek
    Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

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  • Using a WCF Message Inspector to extend AppFabric Monitoring

    - by Shawn Cicoria
    I read through Ron Jacobs post on Monitoring WCF Data Services with AppFabric http://blogs.msdn.com/b/endpoint/archive/2010/06/09/tracking-wcf-data-services-with-windows-server-appfabric.aspx What is immediately striking are 2 things – it’s so easy to get monitoring data into a viewer (AppFabric Dashboard) w/ very little work.  And the 2nd thing is, why can’t this be a WCF message inspector on the dispatch side. So, I took the base class WCFUserEventProvider that’s located in the WCF/WF samples [1] in the following path, \WF_WCF_Samples\WCF\Basic\Management\AnalyticTraceExtensibility\CS\WCFAnalyticTracingExtensibility\  and then created a few classes that project the injection as a IEndPointBehavior There are just 3 classes to drive injection of the inspector at runtime via config: IDispatchMessageInspector implementation BehaviorExtensionElement implementation IEndpointBehavior implementation The full source code is below with a link to the solution file here: [Solution File] using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.ServiceModel.Dispatcher; using System.ServiceModel.Channels; using System.ServiceModel; using System.ServiceModel.Configuration; using System.ServiceModel.Description; using Microsoft.Samples.WCFAnalyticTracingExtensibility; namespace Fabrikam.Services { public class AppFabricE2EInspector : IDispatchMessageInspector { static WCFUserEventProvider evntProvider = null; static AppFabricE2EInspector() { evntProvider = new WCFUserEventProvider(); } public object AfterReceiveRequest( ref Message request, IClientChannel channel, InstanceContext instanceContext) { OperationContext ctx = OperationContext.Current; var opName = ctx.IncomingMessageHeaders.Action; evntProvider.WriteInformationEvent("start", string.Format("operation: {0} at address {1}", opName, ctx.EndpointDispatcher.EndpointAddress)); return null; } public void BeforeSendReply(ref System.ServiceModel.Channels.Message reply, object correlationState) { OperationContext ctx = OperationContext.Current; var opName = ctx.IncomingMessageHeaders.Action; evntProvider.WriteInformationEvent("end", string.Format("operation: {0} at address {1}", opName, ctx.EndpointDispatcher.EndpointAddress)); } } public class AppFabricE2EBehaviorElement : BehaviorExtensionElement { #region BehaviorExtensionElement /// <summary> /// Gets the type of behavior. /// </summary> /// <value></value> /// <returns>The type that implements the end point behavior<see cref="T:System.Type"/>.</returns> public override Type BehaviorType { get { return typeof(AppFabricE2EEndpointBehavior); } } /// <summary> /// Creates a behavior extension based on the current configuration settings. /// </summary> /// <returns>The behavior extension.</returns> protected override object CreateBehavior() { return new AppFabricE2EEndpointBehavior(); } #endregion BehaviorExtensionElement } public class AppFabricE2EEndpointBehavior : IEndpointBehavior //, IServiceBehavior { #region IEndpointBehavior public void AddBindingParameters(ServiceEndpoint endpoint, BindingParameterCollection bindingParameters) {} public void ApplyClientBehavior(ServiceEndpoint endpoint, ClientRuntime clientRuntime) { throw new NotImplementedException(); } public void ApplyDispatchBehavior(ServiceEndpoint endpoint, EndpointDispatcher endpointDispatcher) { endpointDispatcher.DispatchRuntime.MessageInspectors.Add(new AppFabricE2EInspector()); } public void Validate(ServiceEndpoint endpoint) { ; } #endregion IEndpointBehavior } }     [1] http://www.microsoft.com/downloads/details.aspx?FamilyID=35ec8682-d5fd-4bc3-a51a-d8ad115a8792&displaylang=en

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  • MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1

    - by Mat Keep
    0 0 1 893 5092 Homework 42 11 5974 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 to deliver over 8x higher performance than the previous MySQL Cluster 7.1 release on a recent benchmark What’s New in MySQL Cluster 7.2 MySQL Cluster 7.2 was released as GA (Generally Available) in February 2012, delivering many enhancements to performance on complex queries, new NoSQL Key / Value API, cross-data center replication and ease-of-use. These enhancements are summarized in the Figure below, and detailed in the MySQL Cluster New Features whitepaper Figure 1: Next Generation Web Services, Cross Data Center Replication and Ease-of-Use Once of the key enhancements delivered in MySQL Cluster 7.2 is extensions made to the multi-threading processes of the data nodes. Multi-Threaded Data Node Extensions The MySQL Cluster 7.2 data node is now functionally divided into seven thread types: 1) Local Data Manager threads (ldm). Note – these are sometimes also called LQH threads. 2) Transaction Coordinator threads (tc) 3) Asynchronous Replication threads (rep) 4) Schema Management threads (main) 5) Network receiver threads (recv) 6) Network send threads (send) 7) IO threads Each of these thread types are discussed in more detail below. MySQL Cluster 7.2 increases the maximum number of LDM threads from 4 to 16. The LDM contains the actual data, which means that when using 16 threads the data is more heavily partitioned (this is automatic in MySQL Cluster). Each LDM thread maintains its own set of data partitions, index partitions and REDO log. The number of LDM partitions per data node is not dynamically configurable, but it is possible, however, to map more than one partition onto each LDM thread, providing flexibility in modifying the number of LDM threads. The TC domain stores the state of in-flight transactions. This means that every new transaction can easily be assigned to a new TC thread. Testing has shown that in most cases 1 TC thread per 2 LDM threads is sufficient, and in many cases even 1 TC thread per 4 LDM threads is also acceptable. Testing also demonstrated that in some instances where the workload needed to sustain very high update loads it is necessary to configure 3 to 4 TC threads per 4 LDM threads. In the previous MySQL Cluster 7.1 release, only one TC thread was available. This limit has been increased to 16 TC threads in MySQL Cluster 7.2. The TC domain also manages the Adaptive Query Localization functionality introduced in MySQL Cluster 7.2 that significantly enhanced complex query performance by pushing JOIN operations down to the data nodes. Asynchronous Replication was separated into its own thread with the release of MySQL Cluster 7.1, and has not been modified in the latest 7.2 release. To scale the number of TC threads, it was necessary to separate the Schema Management domain from the TC domain. The schema management thread has little load, so is implemented with a single thread. The Network receiver domain was bound to 1 thread in MySQL Cluster 7.1. With the increase of threads in MySQL Cluster 7.2 it is also necessary to increase the number of recv threads to 8. This enables each receive thread to service one or more sockets used to communicate with other nodes the Cluster. The Network send thread is a new thread type introduced in MySQL Cluster 7.2. Previously other threads handled the sending operations themselves, which can provide for lower latency. To achieve highest throughput however, it has been necessary to create dedicated send threads, of which 8 can be configured. It is still possible to configure MySQL Cluster 7.2 to a legacy mode that does not use any of the send threads – useful for those workloads that are most sensitive to latency. The IO Thread is the final thread type and there have been no changes to this domain in MySQL Cluster 7.2. Multiple IO threads were already available, which could be configured to either one thread per open file, or to a fixed number of IO threads that handle the IO traffic. Except when using compression on disk, the IO threads typically have a very light load. Benchmarking the Scalability Enhancements The scalability enhancements discussed above have made it possible to scale CPU usage of each data node to more than 5x of that possible in MySQL Cluster 7.1. In addition, a number of bottlenecks have been removed, making it possible to scale data node performance by even more than 5x. Figure 2: MySQL Cluster 7.2 Delivers 8.4x Higher Performance than 7.1 The flexAsynch benchmark was used to compare MySQL Cluster 7.2 performance to 7.1 across an 8-node Intel Xeon x5670-based cluster of dual socket commodity servers (6 cores each). As the results demonstrate, MySQL Cluster 7.2 delivers over 8x higher performance per data nodes than MySQL Cluster 7.1. More details of this and other benchmarks will be published in a new whitepaper – coming soon, so stay tuned! In a following blog post, I’ll provide recommendations on optimum thread configurations for different types of server processor. You can also learn more from the Best Practices Guide to Optimizing Performance of MySQL Cluster Conclusion MySQL Cluster has achieved a range of impressive benchmark results, and set in context with the previous 7.1 release, is able to deliver over 8x higher performance per node. As a result, the multi-threaded data node extensions not only serve to increase performance of MySQL Cluster, they also enable users to achieve significantly improved levels of utilization from current and future generations of massively multi-core, multi-thread processor designs.

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  • How to improve WinForms MSChart performance?

    - by Marcel
    Hi all, I have created some simple charts (of type FastLine) with MSChart and update them with live data, like below: . To do so, I bind an observable collection of a custom type to the chart like so: // set chart data source this._Chart.DataSource = value; //is of type ObservableCollection<SpectrumLevels> //define x and y value members for each series this._Chart.Series[0].XValueMember = "Index"; this._Chart.Series[1].XValueMember = "Index"; this._Chart.Series[0].YValueMembers = "Channel0Level"; this._Chart.Series[1].YValueMembers = "Channel1Level"; // bind data to chart this._Chart.DataBind(); //lasts 1.5 seconds for 8000 points per series At each refresh, the dataset completely changes, it is not a scrolling update! With a profiler I have found that the DataBind() call takes about 1.5 seconds. The other calls are negligible. How can I make this faster? Should I use another type than ObservableCollection? An array probably? Should I use another form of data binding? Is there some tweak for the MSChart that I may have missed? Should I use a sparsed set of date, having one value per pixel only? Have I simply reached the performance limit of MSCharts? From the type of the application to keep it "fluent", we should have multiple refreshes per second. Thanks for any hints!

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  • Books and resources for Java Performance tuning - when working with databases, huge lists

    - by Arvind
    Hi All, I am relatively new to working on huge applications in Java. I am working on a Java web service which is pretty heavily used by various clients. The service basically queries the database (hibernate) and then works with a lot of Lists (there are adapters to convert list returned from DB to the interface which the service publishes) and I am seeing lot of issues with the service like high CPU usage or high heap space. While I can troubleshoot the performance issues using a profiler, I want to actually learn about what all I need to take care when I actually write code. Like what kind of List to use or things like using StringBuilder instead of String, etc... Is there any book or blogs which I can refer which will help me while I write new services? Also my application is multithreaded - each service call from a client is a new thread, and I want to know some best practices around that area as well. I did search the web but I found many tips which are not relevant in the latest Java 6 releases, so wanted to know what kind of resources would help a developer starting out now on Java for heavily used applications. Arvind

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  • Silverlight combobox performance issue

    - by Vinzz
    Hi, I'm facing a performance issue with a crowded combobox (5000 items). Rendering of the drop down list is really slow (as if it was computing all items before showing any). Do you have any trick to make this dropdown display lazy? Xaml code: <Grid x:Name="LayoutRoot"> <StackPanel Orientation="Horizontal" Width="200" Height="20"> <TextBlock>Test Combo </TextBlock> <ComboBox x:Name="fooCombo" Margin="5,0,0,0"></ComboBox> </StackPanel> </Grid> code behind: public MainPage() { InitializeComponent(); List<string> li = new List<string>(); int Max = 5000; for (int i = 0; i < Max; ++i) li.Add("Item - " + i); fooCombo.ItemsSource = li; }

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  • Increase performance on iphone at pdf rendering

    - by burki
    Hi! I have a UITableView, and in every cell there's displayed a UIImage created from a pdf. But now the performance is very bad. Here's my code I use to generate the UIImage from the PDF. Creating CGPDFDocumentRef and UIImageView (in cellForRowAtIndexPath method): ... CFURLRef pdfURL = CFBundleCopyResourceURL(CFBundleGetMainBundle(), (CFStringRef)formula.icon, NULL, NULL); CGPDFDocumentRef documentRef = CGPDFDocumentCreateWithURL((CFURLRef)pdfURL); CFRelease(pdfURL); UIImageView *imageView = [[UIImageView alloc] initWithImage:[self imageFromPDFWithDocumentRef:documentRef]]; ... Generate UIImage: - (UIImage *)imageFromPDFWithDocumentRef:(CGPDFDocumentRef)documentRef { CGPDFPageRef pageRef = CGPDFDocumentGetPage(documentRef, 1); CGRect pageRect = CGPDFPageGetBoxRect(pageRef, kCGPDFCropBox); UIGraphicsBeginImageContext(pageRect.size); CGContextRef context = UIGraphicsGetCurrentContext(); CGContextTranslateCTM(context, CGRectGetMinX(pageRect),CGRectGetMaxY(pageRect)); CGContextScaleCTM(context, 1, -1); CGContextTranslateCTM(context, -(pageRect.origin.x), -(pageRect.origin.y)); CGContextDrawPDFPage(context, pageRef); UIImage *finalImage = UIGraphicsGetImageFromCurrentImageContext(); UIGraphicsEndImageContext(); return finalImage; } What can I do to increas the speed and keep the memory low?

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  • Iterator performance contract (and use on non-collections)

    - by polygenelubricants
    If all that you're doing is a simple one-pass iteration (i.e. only hasNext() and next(), no remove()), are you guaranteed linear time performance and/or amortized constant cost per operation? Is this specified in the Iterator contract anywhere? Are there data structures/Java Collection which cannot be iterated in linear time? java.util.Scanner implements Iterator<String>. A Scanner is hardly a data structure (e.g. remove() makes absolutely no sense). Is this considered a design blunder? Is something like PrimeGenerator implements Iterator<Integer> considered bad design, or is this exactly what Iterator is for? (hasNext() always returns true, next() computes the next number on demand, remove() makes no sense). Similarly, would it have made sense for java.util.Random implements Iterator<Double>? Should a type really implement Iterator if it's effectively only using one-third of its API? (i.e. no remove(), always hasNext())

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  • MySQL MyISAM table performance... painfully, painfully slow

    - by Salman A
    I've got a table structure that can be summarized as follows: pagegroup * pagegroupid * name has 3600 rows page * pageid * pagegroupid * data references pagegroup; has 10000 rows; can have anything between 1-700 rows per pagegroup; the data column is of type mediumtext and the column contains 100k - 200kbytes data per row userdata * userdataid * pageid * column1 * column2 * column9 references page; has about 300,000 rows; can have about 1-50 rows per page The above structure is pretty straight forwad, the problem is that that a join from userdata to page group is terribly, terribly slow even though I have indexed all columns that should be indexed. The time needed to run a query for such a join (userdata inner_join page inner_join pagegroup) exceeds 3 minutes. This is terribly slow considering the fact that I am not selecting the data column at all. Example of the query that takes too long: SELECT userdata.column1, pagegroup.name FROM userdata INNER JOIN page USING( pageid ) INNER JOIN pagegroup USING( pagegroupid ) Please help by explaining why does it take so long and what can i do to make it faster. Edit #1 Explain returns following gibberish: id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE userdata ALL pageid 372420 1 SIMPLE page eq_ref PRIMARY,pagegroupid PRIMARY 4 topsecret.userdata.pageid 1 1 SIMPLE pagegroup eq_ref PRIMARY PRIMARY 4 topsecret.page.pagegroupid 1 Edit #2 SELECT u.field2, p.pageid FROM userdata u INNER JOIN page p ON u.pageid = p.pageid; /* 0.07 sec execution, 6.05 sec fecth */ id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE u ALL pageid 372420 1 SIMPLE p eq_ref PRIMARY PRIMARY 4 topsecret.u.pageid 1 Using index SELECT p.pageid, g.pagegroupid FROM page p INNER JOIN pagegroup g ON p.pagegroupid = g.pagegroupid; /* 9.37 sec execution, 60.0 sec fetch */ id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE g index PRIMARY PRIMARY 4 3646 Using index 1 SIMPLE p ref pagegroupid pagegroupid 5 topsecret.g.pagegroupid 3 Using where Moral of the story Keep medium/long text columns in a separate table if you run into performance problems such as this one.

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  • Varying performance of MSVC release exe

    - by Andrew
    Hello everyone, I am curious what could be the reason for highly varying performance of the same executable. Sometimes, I run it and it takes 20 seconds and sometimes it is 110. Source is compiled with MSVC in Release mode with standard options. The code is here: vector<double> Un; vector<double> Ucur; double *pUn, *pUcur; ... // time marching for (old_time=time-logfreq, time+=dt; time <= end_time; time+=dt) { for (i=1, j=Un.size()-1, pUn=&Un[1], pUcur=&Ucur[1]; i < j; ++i, ++pUn, ++pUcur) { *pUcur = (*pUn)*(1.0-0.5*alpha*( *(pUn+1) - *(pUn-1) )); } Ucur[0] = (Un[0])*(1.0-0.5*alpha*( Un[1] - Un[j] )); Ucur[j] = (Un[j])*(1.0-0.5*alpha*( Un[0] - Un[j-1] )); Un = Ucur; }

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  • Python performance improvement request for winkler

    - by Martlark
    I'm a python n00b and I'd like some suggestions on how to improve the algorithm to improve the performance of this method to compute the Jaro-Winkler distance of two names. def winklerCompareP(str1, str2): """Return approximate string comparator measure (between 0.0 and 1.0) USAGE: score = winkler(str1, str2) ARGUMENTS: str1 The first string str2 The second string DESCRIPTION: As described in 'An Application of the Fellegi-Sunter Model of Record Linkage to the 1990 U.S. Decennial Census' by William E. Winkler and Yves Thibaudeau. Based on the 'jaro' string comparator, but modifies it according to whether the first few characters are the same or not. """ # Quick check if the strings are the same - - - - - - - - - - - - - - - - - - # jaro_winkler_marker_char = chr(1) if (str1 == str2): return 1.0 len1 = len(str1) len2 = len(str2) halflen = max(len1,len2) / 2 - 1 ass1 = '' # Characters assigned in str1 ass2 = '' # Characters assigned in str2 #ass1 = '' #ass2 = '' workstr1 = str1 workstr2 = str2 common1 = 0 # Number of common characters common2 = 0 #print "'len1', str1[i], start, end, index, ass1, workstr2, common1" # Analyse the first string - - - - - - - - - - - - - - - - - - - - - - - - - # for i in range(len1): start = max(0,i-halflen) end = min(i+halflen+1,len2) index = workstr2.find(str1[i],start,end) #print 'len1', str1[i], start, end, index, ass1, workstr2, common1 if (index > -1): # Found common character common1 += 1 #ass1 += str1[i] ass1 = ass1 + str1[i] workstr2 = workstr2[:index]+jaro_winkler_marker_char+workstr2[index+1:] #print "str1 analyse result", ass1, common1 #print "str1 analyse result", ass1, common1 # Analyse the second string - - - - - - - - - - - - - - - - - - - - - - - - - # for i in range(len2): start = max(0,i-halflen) end = min(i+halflen+1,len1) index = workstr1.find(str2[i],start,end) #print 'len2', str2[i], start, end, index, ass1, workstr1, common2 if (index > -1): # Found common character common2 += 1 #ass2 += str2[i] ass2 = ass2 + str2[i] workstr1 = workstr1[:index]+jaro_winkler_marker_char+workstr1[index+1:] if (common1 != common2): print('Winkler: Wrong common values for strings "%s" and "%s"' % \ (str1, str2) + ', common1: %i, common2: %i' % (common1, common2) + \ ', common should be the same.') common1 = float(common1+common2) / 2.0 ##### This is just a fix ##### if (common1 == 0): return 0.0 # Compute number of transpositions - - - - - - - - - - - - - - - - - - - - - # transposition = 0 for i in range(len(ass1)): if (ass1[i] != ass2[i]): transposition += 1 transposition = transposition / 2.0 # Now compute how many characters are common at beginning - - - - - - - - - - # minlen = min(len1,len2) for same in range(minlen+1): if (str1[:same] != str2[:same]): break same -= 1 if (same > 4): same = 4 common1 = float(common1) w = 1./3.*(common1 / float(len1) + common1 / float(len2) + (common1-transposition) / common1) wn = w + same*0.1 * (1.0 - w) return wn

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