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  • Loosely coupled .NET Cache Provider using Dependency Injection

    - by Rhames
    I have recently been reading the excellent book “Dependency Injection in .NET”, written by Mark Seemann. I do not generally buy software development related books, as I never seem to have the time to read them, but I have found the time to read Mark’s book, and it was time well spent I think. Reading the ideas around Dependency Injection made me realise that the Cache Provider code I wrote about earlier (see http://geekswithblogs.net/Rhames/archive/2011/01/10/using-the-asp.net-cache-to-cache-data-in-a-model.aspx) could be refactored to use Dependency Injection, which should produce cleaner code. The goals are to: Separate the cache provider implementation (using the ASP.NET data cache) from the consumers (loose coupling). This will also mean that the dependency on System.Web for the cache provider does not ripple down into the layers where it is being consumed (such as the domain layer). Provide a decorator pattern to allow a consumer of the cache provider to be implemented separately from the base consumer (i.e. if we have a base repository, we can decorate this with a caching version). Although I used the term repository, in reality the cache consumer could be just about anything. Use constructor injection to provide the Dependency Injection, with a suitable DI container (I use Castle Windsor). The sample code for this post is available on github, https://github.com/RobinHames/CacheProvider.git ICacheProvider In the sample code, the key interface is ICacheProvider, which is in the domain layer. 1: using System; 2: using System.Collections.Generic; 3:   4: namespace CacheDiSample.Domain 5: { 6: public interface ICacheProvider<T> 7: { 8: T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry); 9: IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry); 10: } 11: }   This interface contains two methods to retrieve data from the cache, either as a single instance or as an IEnumerable. the second paramerter is of type Func<T>. This is the method used to retrieve data if nothing is found in the cache. The ASP.NET implementation of the ICacheProvider interface needs to live in a project that has a reference to system.web, typically this will be the root UI project, or it could be a separate project. The key thing is that the domain or data access layers do not need system.web references adding to them. In my sample MVC application, the CacheProvider is implemented in the UI project, in a folder called “CacheProviders”: 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Web; 5: using System.Web.Caching; 6: using CacheDiSample.Domain; 7:   8: namespace CacheDiSample.CacheProvider 9: { 10: public class CacheProvider<T> : ICacheProvider<T> 11: { 12: public T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) 13: { 14: return FetchAndCache<T>(key, retrieveData, absoluteExpiry, relativeExpiry); 15: } 16:   17: public IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) 18: { 19: return FetchAndCache<IEnumerable<T>>(key, retrieveData, absoluteExpiry, relativeExpiry); 20: } 21:   22: #region Helper Methods 23:   24: private U FetchAndCache<U>(string key, Func<U> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) 25: { 26: U value; 27: if (!TryGetValue<U>(key, out value)) 28: { 29: value = retrieveData(); 30: if (!absoluteExpiry.HasValue) 31: absoluteExpiry = Cache.NoAbsoluteExpiration; 32:   33: if (!relativeExpiry.HasValue) 34: relativeExpiry = Cache.NoSlidingExpiration; 35:   36: HttpContext.Current.Cache.Insert(key, value, null, absoluteExpiry.Value, relativeExpiry.Value); 37: } 38: return value; 39: } 40:   41: private bool TryGetValue<U>(string key, out U value) 42: { 43: object cachedValue = HttpContext.Current.Cache.Get(key); 44: if (cachedValue == null) 45: { 46: value = default(U); 47: return false; 48: } 49: else 50: { 51: try 52: { 53: value = (U)cachedValue; 54: return true; 55: } 56: catch 57: { 58: value = default(U); 59: return false; 60: } 61: } 62: } 63:   64: #endregion 65:   66: } 67: }   The FetchAndCache helper method checks if the specified cache key exists, if it does not, the Func<U> retrieveData method is called, and the results are added to the cache. Using Castle Windsor to register the cache provider In the MVC UI project (my application root), Castle Windsor is used to register the CacheProvider implementation, using a Windsor Installer: 1: using Castle.MicroKernel.Registration; 2: using Castle.MicroKernel.SubSystems.Configuration; 3: using Castle.Windsor; 4:   5: using CacheDiSample.Domain; 6: using CacheDiSample.CacheProvider; 7:   8: namespace CacheDiSample.WindsorInstallers 9: { 10: public class CacheInstaller : IWindsorInstaller 11: { 12: public void Install(IWindsorContainer container, IConfigurationStore store) 13: { 14: container.Register( 15: Component.For(typeof(ICacheProvider<>)) 16: .ImplementedBy(typeof(CacheProvider<>)) 17: .LifestyleTransient()); 18: } 19: } 20: }   Note that the cache provider is registered as a open generic type. Consuming a Repository I have an existing couple of repository interfaces defined in my domain layer: IRepository.cs 1: using System; 2: using System.Collections.Generic; 3:   4: using CacheDiSample.Domain.Model; 5:   6: namespace CacheDiSample.Domain.Repositories 7: { 8: public interface IRepository<T> 9: where T : EntityBase 10: { 11: T GetById(int id); 12: IList<T> GetAll(); 13: } 14: }   IBlogRepository.cs 1: using System; 2: using CacheDiSample.Domain.Model; 3:   4: namespace CacheDiSample.Domain.Repositories 5: { 6: public interface IBlogRepository : IRepository<Blog> 7: { 8: Blog GetByName(string name); 9: } 10: }   These two repositories are implemented in the DataAccess layer, using Entity Framework to retrieve data (this is not important though). One important point is that in the BaseRepository implementation of IRepository, the methods are virtual. This will allow the decorator to override them. The BlogRepository is registered in a RepositoriesInstaller, again in the MVC UI project. 1: using Castle.MicroKernel.Registration; 2: using Castle.MicroKernel.SubSystems.Configuration; 3: using Castle.Windsor; 4:   5: using CacheDiSample.Domain.CacheDecorators; 6: using CacheDiSample.Domain.Repositories; 7: using CacheDiSample.DataAccess; 8:   9: namespace CacheDiSample.WindsorInstallers 10: { 11: public class RepositoriesInstaller : IWindsorInstaller 12: { 13: public void Install(IWindsorContainer container, IConfigurationStore store) 14: { 15: container.Register(Component.For<IBlogRepository>() 16: .ImplementedBy<BlogRepository>() 17: .LifestyleTransient() 18: .DependsOn(new 19: { 20: nameOrConnectionString = "BloggingContext" 21: })); 22: } 23: } 24: }   Now I can inject a dependency on the IBlogRepository into a consumer, such as a controller in my sample code: 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Web; 5: using System.Web.Mvc; 6:   7: using CacheDiSample.Domain.Repositories; 8: using CacheDiSample.Domain.Model; 9:   10: namespace CacheDiSample.Controllers 11: { 12: public class HomeController : Controller 13: { 14: private readonly IBlogRepository blogRepository; 15:   16: public HomeController(IBlogRepository blogRepository) 17: { 18: if (blogRepository == null) 19: throw new ArgumentNullException("blogRepository"); 20:   21: this.blogRepository = blogRepository; 22: } 23:   24: public ActionResult Index() 25: { 26: ViewBag.Message = "Welcome to ASP.NET MVC!"; 27:   28: var blogs = blogRepository.GetAll(); 29:   30: return View(new Models.HomeModel { Blogs = blogs }); 31: } 32:   33: public ActionResult About() 34: { 35: return View(); 36: } 37: } 38: }   Consuming the Cache Provider via a Decorator I used a Decorator pattern to consume the cache provider, this means my repositories follow the open/closed principle, as they do not require any modifications to implement the caching. It also means that my controllers do not have any knowledge of the caching taking place, as the DI container will simply inject the decorator instead of the root implementation of the repository. The first step is to implement a BlogRepository decorator, with the caching logic in it. Note that this can reside in the domain layer, as it does not require any knowledge of the data access methods. BlogRepositoryWithCaching.cs 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Text; 5:   6: using CacheDiSample.Domain.Model; 7: using CacheDiSample.Domain; 8: using CacheDiSample.Domain.Repositories; 9:   10: namespace CacheDiSample.Domain.CacheDecorators 11: { 12: public class BlogRepositoryWithCaching : IBlogRepository 13: { 14: // The generic cache provider, injected by DI 15: private ICacheProvider<Blog> cacheProvider; 16: // The decorated blog repository, injected by DI 17: private IBlogRepository parentBlogRepository; 18:   19: public BlogRepositoryWithCaching(IBlogRepository parentBlogRepository, ICacheProvider<Blog> cacheProvider) 20: { 21: if (parentBlogRepository == null) 22: throw new ArgumentNullException("parentBlogRepository"); 23:   24: this.parentBlogRepository = parentBlogRepository; 25:   26: if (cacheProvider == null) 27: throw new ArgumentNullException("cacheProvider"); 28:   29: this.cacheProvider = cacheProvider; 30: } 31:   32: public Blog GetByName(string name) 33: { 34: string key = string.Format("CacheDiSample.DataAccess.GetByName.{0}", name); 35: // hard code 5 minute expiry! 36: TimeSpan relativeCacheExpiry = new TimeSpan(0, 5, 0); 37: return cacheProvider.Fetch(key, () => 38: { 39: return parentBlogRepository.GetByName(name); 40: }, 41: null, relativeCacheExpiry); 42: } 43:   44: public Blog GetById(int id) 45: { 46: string key = string.Format("CacheDiSample.DataAccess.GetById.{0}", id); 47:   48: // hard code 5 minute expiry! 49: TimeSpan relativeCacheExpiry = new TimeSpan(0, 5, 0); 50: return cacheProvider.Fetch(key, () => 51: { 52: return parentBlogRepository.GetById(id); 53: }, 54: null, relativeCacheExpiry); 55: } 56:   57: public IList<Blog> GetAll() 58: { 59: string key = string.Format("CacheDiSample.DataAccess.GetAll"); 60:   61: // hard code 5 minute expiry! 62: TimeSpan relativeCacheExpiry = new TimeSpan(0, 5, 0); 63: return cacheProvider.Fetch(key, () => 64: { 65: return parentBlogRepository.GetAll(); 66: }, 67: null, relativeCacheExpiry) 68: .ToList(); 69: } 70: } 71: }   The key things in this caching repository are: I inject into the repository the ICacheProvider<Blog> implementation, via the constructor. This will make the cache provider functionality available to the repository. I inject the parent IBlogRepository implementation (which has the actual data access code), via the constructor. This will allow the methods implemented in the parent to be called if nothing is found in the cache. I override each of the methods implemented in the repository, including those implemented in the generic BaseRepository. Each override of these methods follows the same pattern. It makes a call to the CacheProvider.Fetch method, and passes in the parentBlogRepository implementation of the method as the retrieval method, to be used if nothing is present in the cache. Configuring the Caching Repository in the DI Container The final piece of the jigsaw is to tell Castle Windsor to use the BlogRepositoryWithCaching implementation of IBlogRepository, but to inject the actual Data Access implementation into this decorator. This is easily achieved by modifying the RepositoriesInstaller to use Windsor’s implicit decorator wiring: 1: using Castle.MicroKernel.Registration; 2: using Castle.MicroKernel.SubSystems.Configuration; 3: using Castle.Windsor; 4:   5: using CacheDiSample.Domain.CacheDecorators; 6: using CacheDiSample.Domain.Repositories; 7: using CacheDiSample.DataAccess; 8:   9: namespace CacheDiSample.WindsorInstallers 10: { 11: public class RepositoriesInstaller : IWindsorInstaller 12: { 13: public void Install(IWindsorContainer container, IConfigurationStore store) 14: { 15:   16: // Use Castle Windsor implicit wiring for the block repository decorator 17: // Register the outermost decorator first 18: container.Register(Component.For<IBlogRepository>() 19: .ImplementedBy<BlogRepositoryWithCaching>() 20: .LifestyleTransient()); 21: // Next register the IBlogRepository inmplementation to inject into the outer decorator 22: container.Register(Component.For<IBlogRepository>() 23: .ImplementedBy<BlogRepository>() 24: .LifestyleTransient() 25: .DependsOn(new 26: { 27: nameOrConnectionString = "BloggingContext" 28: })); 29: } 30: } 31: }   This is all that is needed. Now if the consumer of the repository makes a call to the repositories method, it will be routed via the caching mechanism. You can test this by stepping through the code, and seeing that the DataAccess.BlogRepository code is only called if there is no data in the cache, or this has expired. The next step is to add the SQL Cache Dependency support into this pattern, this will be a future post.

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  • why my site cache 2 time par day?

    - by clarawood
    I have read the FAQs and checked for similar issues: YES My site's URL (web address) is: www.adultxdating.com Description (including timeline of any changes made): I have lost my top search listings from last 4 months. I am still working on this but not getting proper guidance. This site is caching 2 times in 24Hrs. Some times sites will back in to top 10 search listing on 100s keywords, some time its gone out 1000+. anybody can help me why its happening. I have more than 200K+ incoming links and updating the site regularly. Please help. Thanks clara wood

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  • Different cache concurrent strategies for root entity and its collection (Hibernate with EHCache)?

    - by grigory
    Given example from Hibernate docs and modifying it so that root level entity (Customer) is read-only while one of its collections (tickets) is read-write: @Entity @Cache(usage = CacheConcurrencyStrategy.READ_ONLY) public class Customer { ... @OneToMany(...) @Cache(usage = CacheConcurrencyStrategy.READ_WRITE) public SortedSet<Ticket> getTickets() { return tickets; } ... } Would collection of tickets get refreshed when accessing customer from cache?

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  • Using the ASP.NET Cache to cache data in a Model or Business Object layer, without a dependency on System.Web in the layer - Part One.

    - by Rhames
    ASP.NET applications can make use of the System.Web.Caching.Cache object to cache data and prevent repeated expensive calls to a database or other store. However, ideally an application should make use of caching at the point where data is retrieved from the database, which typically is inside a Business Objects or Model layer. One of the key features of using a UI pattern such as Model-View-Presenter (MVP) or Model-View-Controller (MVC) is that the Model and Presenter (or Controller) layers are developed without any knowledge of the UI layer. Introducing a dependency on System.Web into the Model layer would break this independence of the Model from the View. This article gives a solution to this problem, using dependency injection to inject the caching implementation into the Model layer at runtime. This allows caching to be used within the Model layer, without any knowledge of the actual caching mechanism that will be used. Create a sample application to use the caching solution Create a test SQL Server database This solution uses a SQL Server database with the same Sales data used in my previous post on calculating running totals. The advantage of using this data is that it gives nice slow queries that will exaggerate the effect of using caching! To create the data, first create a new SQL database called CacheSample. Next run the following script to create the Sale table and populate it: USE CacheSample GO   CREATE TABLE Sale(DayCount smallint, Sales money) CREATE CLUSTERED INDEX ndx_DayCount ON Sale(DayCount) go INSERT Sale VALUES (1,120) INSERT Sale VALUES (2,60) INSERT Sale VALUES (3,125) INSERT Sale VALUES (4,40)   DECLARE @DayCount smallint, @Sales money SET @DayCount = 5 SET @Sales = 10   WHILE @DayCount < 5000  BEGIN  INSERT Sale VALUES (@DayCount,@Sales)  SET @DayCount = @DayCount + 1  SET @Sales = @Sales + 15  END Next create a stored procedure to calculate the running total, and return a specified number of rows from the Sale table, using the following script: USE [CacheSample] GO   SET ANSI_NULLS ON GO   SET QUOTED_IDENTIFIER ON GO   -- ============================================= -- Author:        Robin -- Create date: -- Description:   -- ============================================= CREATE PROCEDURE [dbo].[spGetRunningTotals]       -- Add the parameters for the stored procedure here       @HighestDayCount smallint = null AS BEGIN       -- SET NOCOUNT ON added to prevent extra result sets from       -- interfering with SELECT statements.       SET NOCOUNT ON;         IF @HighestDayCount IS NULL             SELECT @HighestDayCount = MAX(DayCount) FROM dbo.Sale                   DECLARE @SaleTbl TABLE (DayCount smallint, Sales money, RunningTotal money)         DECLARE @DayCount smallint,                   @Sales money,                   @RunningTotal money         SET @RunningTotal = 0       SET @DayCount = 0         DECLARE rt_cursor CURSOR       FOR       SELECT DayCount, Sales       FROM Sale       ORDER BY DayCount         OPEN rt_cursor         FETCH NEXT FROM rt_cursor INTO @DayCount,@Sales         WHILE @@FETCH_STATUS = 0 AND @DayCount <= @HighestDayCount        BEGIN        SET @RunningTotal = @RunningTotal + @Sales        INSERT @SaleTbl VALUES (@DayCount,@Sales,@RunningTotal)        FETCH NEXT FROM rt_cursor INTO @DayCount,@Sales        END         CLOSE rt_cursor       DEALLOCATE rt_cursor         SELECT DayCount, Sales, RunningTotal       FROM @SaleTbl   END   GO   Create the Sample ASP.NET application In Visual Studio create a new solution and add a class library project called CacheSample.BusinessObjects and an ASP.NET web application called CacheSample.UI. The CacheSample.BusinessObjects project will contain a single class to represent a Sale data item, with all the code to retrieve the sales from the database included in it for simplicity (normally I would at least have a separate Repository or other object that is responsible for retrieving data, and probably a data access layer as well, but for this sample I want to keep it simple). The C# code for the Sale class is shown below: using System; using System.Collections.Generic; using System.Data; using System.Data.SqlClient;   namespace CacheSample.BusinessObjects {     public class Sale     {         public Int16 DayCount { get; set; }         public decimal Sales { get; set; }         public decimal RunningTotal { get; set; }           public static IEnumerable<Sale> GetSales(int? highestDayCount)         {             List<Sale> sales = new List<Sale>();               SqlParameter highestDayCountParameter = new SqlParameter("@HighestDayCount", SqlDbType.SmallInt);             if (highestDayCount.HasValue)                 highestDayCountParameter.Value = highestDayCount;             else                 highestDayCountParameter.Value = DBNull.Value;               string connectionStr = System.Configuration.ConfigurationManager .ConnectionStrings["CacheSample"].ConnectionString;               using(SqlConnection sqlConn = new SqlConnection(connectionStr))             using (SqlCommand sqlCmd = sqlConn.CreateCommand())             {                 sqlCmd.CommandText = "spGetRunningTotals";                 sqlCmd.CommandType = CommandType.StoredProcedure;                 sqlCmd.Parameters.Add(highestDayCountParameter);                   sqlConn.Open();                   using (SqlDataReader dr = sqlCmd.ExecuteReader())                 {                     while (dr.Read())                     {                         Sale newSale = new Sale();                         newSale.DayCount = dr.GetInt16(0);                         newSale.Sales = dr.GetDecimal(1);                         newSale.RunningTotal = dr.GetDecimal(2);                           sales.Add(newSale);                     }                 }             }               return sales;         }     } }   The static GetSale() method makes a call to the spGetRunningTotals stored procedure and then reads each row from the returned SqlDataReader into an instance of the Sale class, it then returns a List of the Sale objects, as IEnnumerable<Sale>. A reference to System.Configuration needs to be added to the CacheSample.BusinessObjects project so that the connection string can be read from the web.config file. In the CacheSample.UI ASP.NET project, create a single web page called ShowSales.aspx, and make this the default start up page. This page will contain a single button to call the GetSales() method and a label to display the results. The html mark up and the C# code behind are shown below: ShowSales.aspx <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="ShowSales.aspx.cs" Inherits="CacheSample.UI.ShowSales" %>   <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">   <html xmlns="http://www.w3.org/1999/xhtml"> <head runat="server">     <title>Cache Sample - Show All Sales</title> </head> <body>     <form id="form1" runat="server">     <div>         <asp:Button ID="btnTest1" runat="server" onclick="btnTest1_Click"             Text="Get All Sales" />         &nbsp;&nbsp;&nbsp;         <asp:Label ID="lblResults" runat="server"></asp:Label>         </div>     </form> </body> </html>   ShowSales.aspx.cs using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.Web.UI; using System.Web.UI.WebControls;   using CacheSample.BusinessObjects;   namespace CacheSample.UI {     public partial class ShowSales : System.Web.UI.Page     {         protected void Page_Load(object sender, EventArgs e)         {         }           protected void btnTest1_Click(object sender, EventArgs e)         {             System.Diagnostics.Stopwatch stopWatch = new System.Diagnostics.Stopwatch();             stopWatch.Start();               var sales = Sale.GetSales(null);               var lastSales = sales.Last();               stopWatch.Stop();               lblResults.Text = string.Format( "Count of Sales: {0}, Last DayCount: {1}, Total Sales: {2}. Query took {3} ms", sales.Count(), lastSales.DayCount, lastSales.RunningTotal, stopWatch.ElapsedMilliseconds);         }       } }   Finally we need to add a connection string to the CacheSample SQL Server database, called CacheSample, to the web.config file: <?xmlversion="1.0"?>   <configuration>    <connectionStrings>     <addname="CacheSample"          connectionString="data source=.\SQLEXPRESS;Integrated Security=SSPI;Initial Catalog=CacheSample"          providerName="System.Data.SqlClient" />  </connectionStrings>    <system.web>     <compilationdebug="true"targetFramework="4.0" />  </system.web>   </configuration>   Run the application and click the button a few times to see how long each call to the database takes. On my system, each query takes about 450ms. Next I shall look at a solution to use the ASP.NET caching to cache the data returned by the query, so that subsequent requests to the GetSales() method are much faster. Adding Data Caching Support I am going to create my caching support in a separate project called CacheSample.Caching, so the next step is to add a class library to the solution. We shall be using the application configuration to define the implementation of our caching system, so we need a reference to System.Configuration adding to the project. ICacheProvider<T> Interface The first step in adding caching to our application is to define an interface, called ICacheProvider, in the CacheSample.Caching project, with methods to retrieve any data from the cache or to retrieve the data from the data source if it is not present in the cache. Dependency Injection will then be used to inject an implementation of this interface at runtime, allowing the users of the interface (i.e. the CacheSample.BusinessObjects project) to be completely unaware of how the caching is actually implemented. As data of any type maybe retrieved from the data source, it makes sense to use generics in the interface, with a generic type parameter defining the data type associated with a particular instance of the cache interface implementation. The C# code for the ICacheProvider interface is shown below: using System; using System.Collections.Generic;   namespace CacheSample.Caching {     public interface ICacheProvider     {     }       public interface ICacheProvider<T> : ICacheProvider     {         T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry);           IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry);     } }   The empty non-generic interface will be used as a type in a Dictionary generic collection later to store instances of the ICacheProvider<T> implementation for reuse, I prefer to use a base interface when doing this, as I think the alternative of using object makes for less clear code. The ICacheProvider<T> interface defines two overloaded Fetch methods, the difference between these is that one will return a single instance of the type T and the other will return an IEnumerable<T>, providing support for easy caching of collections of data items. Both methods will take a key parameter, which will uniquely identify the cached data, a delegate of type Func<T> or Func<IEnumerable<T>> which will provide the code to retrieve the data from the store if it is not present in the cache, and absolute or relative expiry policies to define when a cached item should expire. Note that at present there is no support for cache dependencies, but I shall be showing a method of adding this in part two of this article. CacheProviderFactory Class We need a mechanism of creating instances of our ICacheProvider<T> interface, using Dependency Injection to get the implementation of the interface. To do this we shall create a CacheProviderFactory static class in the CacheSample.Caching project. This factory will provide a generic static method called GetCacheProvider<T>(), which shall return instances of ICacheProvider<T>. We can then call this factory method with the relevant data type (for example the Sale class in the CacheSample.BusinessObject project) to get a instance of ICacheProvider for that type (e.g. call CacheProviderFactory.GetCacheProvider<Sale>() to get the ICacheProvider<Sale> implementation). The C# code for the CacheProviderFactory is shown below: using System; using System.Collections.Generic;   using CacheSample.Caching.Configuration;   namespace CacheSample.Caching {     public static class CacheProviderFactory     {         private static Dictionary<Type, ICacheProvider> cacheProviders = new Dictionary<Type, ICacheProvider>();         private static object syncRoot = new object();           ///<summary>         /// Factory method to create or retrieve an implementation of the  /// ICacheProvider interface for type <typeparamref name="T"/>.         ///</summary>         ///<typeparam name="T">  /// The type that this cache provider instance will work with  ///</typeparam>         ///<returns>An instance of the implementation of ICacheProvider for type  ///<typeparamref name="T"/>, as specified by the application  /// configuration</returns>         public static ICacheProvider<T> GetCacheProvider<T>()         {             ICacheProvider<T> cacheProvider = null;             // Get the Type reference for the type parameter T             Type typeOfT = typeof(T);               // Lock the access to the cacheProviders dictionary             // so multiple threads can work with it             lock (syncRoot)             {                 // First check if an instance of the ICacheProvider implementation  // already exists in the cacheProviders dictionary for the type T                 if (cacheProviders.ContainsKey(typeOfT))                     cacheProvider = (ICacheProvider<T>)cacheProviders[typeOfT];                 else                 {                     // There is not already an instance of the ICacheProvider in       // cacheProviders for the type T                     // so we need to create one                       // Get the Type reference for the application's implementation of       // ICacheProvider from the configuration                     Type cacheProviderType = Type.GetType(CacheProviderConfigurationSection.Current. CacheProviderType);                     if (cacheProviderType != null)                     {                         // Now get a Type reference for the Cache Provider with the                         // type T generic parameter                         Type typeOfCacheProviderTypeForT = cacheProviderType.MakeGenericType(new Type[] { typeOfT });                         if (typeOfCacheProviderTypeForT != null)                         {                             // Create the instance of the Cache Provider and add it to // the cacheProviders dictionary for future use                             cacheProvider = (ICacheProvider<T>)Activator. CreateInstance(typeOfCacheProviderTypeForT);                             cacheProviders.Add(typeOfT, cacheProvider);                         }                     }                 }             }               return cacheProvider;                 }     } }   As this code uses Activator.CreateInstance() to create instances of the ICacheProvider<T> implementation, which is a slow process, the factory class maintains a Dictionary of the previously created instances so that a cache provider needs to be created only once for each type. The type of the implementation of ICacheProvider<T> is read from a custom configuration section in the application configuration file, via the CacheProviderConfigurationSection class, which is described below. CacheProviderConfigurationSection Class The implementation of ICacheProvider<T> will be specified in a custom configuration section in the application’s configuration. To handle this create a folder in the CacheSample.Caching project called Configuration, and add a class called CacheProviderConfigurationSection to this folder. This class will extend the System.Configuration.ConfigurationSection class, and will contain a single string property called CacheProviderType. The C# code for this class is shown below: using System; using System.Configuration;   namespace CacheSample.Caching.Configuration {     internal class CacheProviderConfigurationSection : ConfigurationSection     {         public static CacheProviderConfigurationSection Current         {             get             {                 return (CacheProviderConfigurationSection) ConfigurationManager.GetSection("cacheProvider");             }         }           [ConfigurationProperty("type", IsRequired=true)]         public string CacheProviderType         {             get             {                 return (string)this["type"];             }         }     } }   Adding Data Caching to the Sales Class We now have enough code in place to add caching to the GetSales() method in the CacheSample.BusinessObjects.Sale class, even though we do not yet have an implementation of the ICacheProvider<T> interface. We need to add a reference to the CacheSample.Caching project to CacheSample.BusinessObjects so that we can use the ICacheProvider<T> interface within the GetSales() method. Once the reference is added, we can first create a unique string key based on the method name and the parameter value, so that the same cache key is used for repeated calls to the method with the same parameter values. Then we get an instance of the cache provider for the Sales type, using the CacheProviderFactory, and pass the existing code to retrieve the data from the database as the retrievalMethod delegate in a call to the Cache Provider Fetch() method. The C# code for the modified GetSales() method is shown below: public static IEnumerable<Sale> GetSales(int? highestDayCount) {     string cacheKey = string.Format("CacheSample.BusinessObjects.GetSalesWithCache({0})", highestDayCount);       return CacheSample.Caching.CacheProviderFactory. GetCacheProvider<Sale>().Fetch(cacheKey,         delegate()         {             List<Sale> sales = new List<Sale>();               SqlParameter highestDayCountParameter = new SqlParameter("@HighestDayCount", SqlDbType.SmallInt);             if (highestDayCount.HasValue)                 highestDayCountParameter.Value = highestDayCount;             else                 highestDayCountParameter.Value = DBNull.Value;               string connectionStr = System.Configuration.ConfigurationManager. ConnectionStrings["CacheSample"].ConnectionString;               using (SqlConnection sqlConn = new SqlConnection(connectionStr))             using (SqlCommand sqlCmd = sqlConn.CreateCommand())             {                 sqlCmd.CommandText = "spGetRunningTotals";                 sqlCmd.CommandType = CommandType.StoredProcedure;                 sqlCmd.Parameters.Add(highestDayCountParameter);                   sqlConn.Open();                   using (SqlDataReader dr = sqlCmd.ExecuteReader())                 {                     while (dr.Read())                     {                         Sale newSale = new Sale();                         newSale.DayCount = dr.GetInt16(0);                         newSale.Sales = dr.GetDecimal(1);                         newSale.RunningTotal = dr.GetDecimal(2);                           sales.Add(newSale);                     }                 }             }               return sales;         },         null,         new TimeSpan(0, 10, 0)); }     This example passes the code to retrieve the Sales data from the database to the Cache Provider as an anonymous method, however it could also be written as a lambda. The main advantage of using an anonymous function (method or lambda) is that the code inside the anonymous function can access the parameters passed to the GetSales() method. Finally the absolute expiry is set to null, and the relative expiry set to 10 minutes, to indicate that the cache entry should be removed 10 minutes after the last request for the data. As the ICacheProvider<T> has a Fetch() method that returns IEnumerable<T>, we can simply return the results of the Fetch() method to the caller of the GetSales() method. This should be all that is needed for the GetSales() method to now retrieve data from a cache after the first time the data has be retrieved from the database. Implementing a ASP.NET Cache Provider The final step is to actually implement the ICacheProvider<T> interface, and add the implementation details to the web.config file for the dependency injection. The cache provider implementation needs to have access to System.Web. Therefore it could be placed in the CacheSample.UI project, or in its own project that has a reference to System.Web. Implementing the Cache Provider in a separate project is my favoured approach. Create a new project inside the solution called CacheSample.CacheProvider, and add references to System.Web and CacheSample.Caching to this project. Add a class to the project called AspNetCacheProvider. Make the class a generic class by adding the generic parameter <T> and indicate that the class implements ICacheProvider<T>. The C# code for the AspNetCacheProvider class is shown below: using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.Web.Caching;   using CacheSample.Caching;   namespace CacheSample.CacheProvider {     public class AspNetCacheProvider<T> : ICacheProvider<T>     {         #region ICacheProvider<T> Members           public T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry)         {             return FetchAndCache<T>(key, retrieveData, absoluteExpiry, relativeExpiry);         }           public IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry)         {             return FetchAndCache<IEnumerable<T>>(key, retrieveData, absoluteExpiry, relativeExpiry);         }           #endregion           #region Helper Methods           private U FetchAndCache<U>(string key, Func<U> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry)         {             U value;             if (!TryGetValue<U>(key, out value))             {                 value = retrieveData();                 if (!absoluteExpiry.HasValue)                     absoluteExpiry = Cache.NoAbsoluteExpiration;                   if (!relativeExpiry.HasValue)                     relativeExpiry = Cache.NoSlidingExpiration;                   HttpContext.Current.Cache.Insert(key, value, null, absoluteExpiry.Value, relativeExpiry.Value);             }             return value;         }           private bool TryGetValue<U>(string key, out U value)         {             object cachedValue = HttpContext.Current.Cache.Get(key);             if (cachedValue == null)             {                 value = default(U);                 return false;             }             else             {                 try                 {                     value = (U)cachedValue;                     return true;                 }                 catch                 {                     value = default(U);                     return false;                 }             }         }           #endregion       } }   The two interface Fetch() methods call a private method called FetchAndCache(). This method first checks for a element in the HttpContext.Current.Cache with the specified cache key, and if so tries to cast this to the specified type (either T or IEnumerable<T>). If the cached element is found, the FetchAndCache() method simply returns it. If it is not found in the cache, the method calls the retrievalMethod delegate to get the data from the data source, and then adds this to the HttpContext.Current.Cache. The final step is to add the AspNetCacheProvider class to the relevant custom configuration section in the CacheSample.UI.Web.Config file. To do this there needs to be a <configSections> element added as the first element in <configuration>. This will match a custom section called <cacheProvider> with the CacheProviderConfigurationSection. Then we add a <cacheProvider> element, with a type property set to the fully qualified assembly name of the AspNetCacheProvider class, as shown below: <?xmlversion="1.0"?>   <configuration>  <configSections>     <sectionname="cacheProvider" type="CacheSample.Base.Configuration.CacheProviderConfigurationSection, CacheSample.Base" />  </configSections>    <connectionStrings>     <addname="CacheSample"          connectionString="data source=.\SQLEXPRESS;Integrated Security=SSPI;Initial Catalog=CacheSample"          providerName="System.Data.SqlClient" />  </connectionStrings>    <cacheProvidertype="CacheSample.CacheProvider.AspNetCacheProvider`1, CacheSample.CacheProvider, Version=1.0.0.0, Culture=neutral, PublicKeyToken=null">  </cacheProvider>    <system.web>     <compilationdebug="true"targetFramework="4.0" />  </system.web>   </configuration>   One point to note is that the fully qualified assembly name of the AspNetCacheProvider class includes the notation `1 after the class name, which indicates that it is a generic class with a single generic type parameter. The CacheSample.UI project needs to have references added to CacheSample.Caching and CacheSample.CacheProvider so that the actual application is aware of the relevant cache provider implementation. Conclusion After implementing this solution, you should have a working cache provider mechanism, that will allow the middle and data access layers to implement caching support when retrieving data, without any knowledge of the actually caching implementation. If the UI is not ASP.NET based, if for example it is Winforms or WPF, the implementation of ICacheProvider<T> would be written around whatever technology is available. It could even be a standalone caching system that takes full responsibility for adding and removing items from a global store. The next part of this article will show how this caching mechanism may be extended to provide support for cache dependencies, such as the System.Web.Caching.SqlCacheDependency. Another possible extension would be to cache the cache provider implementations instead of storing them in a static Dictionary in the CacheProviderFactory. This would prevent a build up of seldom used cache providers in the application memory, as they could be removed from the cache if not used often enough, although in reality there are probably unlikely to be vast numbers of cache provider implementation instances, as most applications do not have a massive number of business object or model types.

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  • Why Rails.cache is not thread safe?

    - by Freewind
    I know Rails.cache is ActiveSupport::Cache::MemoryStore, and it is not thread safe. I don't understand, why rails use a thread-unsafe cache as its default? Why not use ActiveSupport::Cache::SynchronizedMemoryStore? In my opinion, in a web site, if a cache is not thread-safe, it almost useless, because the requests are not handled in ONE thread. Do you use Rails.cache in you webapp? And how do you use it?

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  • How does one set multiple cache-control directives in ASP.NET

    - by strongopinions
    I have to have several certain cache-control directives set on an ASP.NET page in order to pass a Hailstorm security scan. For example, it wants me to have Cache-control: no-cache="set-cookie" in addition to Cache-control: no-cache I have been setting the latter with the following line in my C# codebehind: Response.CacheControl = "no-cache"; Is there a special way to indicate both directives at once? Do I just separate them with a semicolon?

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  • PHP cache header override

    - by Soyo
    I've been through over 100 answers here, lots to try, NOTHING working?? Have a PHP based site. I need caching OFF for all .php files EXCEPT A SELECT FEW. So, in .htaccess, I have the following: ExpiresActive On # Eliminate caching for certain dynamic files <FilesMatch "\.(php|cgi|pl)$"> ExpiresDefault A0 Header set Cache-Control "no-cache, no-store, must-revalidate, max-age=0, proxy-revalidate, no-transform" Header set Pragma "no-cache" </FilesMatch> Using Firebug, I see the following: Cache-Control no-cache, no-store, must-revalidate, max-age=0, proxy-revalidate, no-transform Connection Keep-Alive Content-Type text/html Date Sun, 02 Sep 2012 19:22:27 GMT Expires Sun, 02 Sep 2012 19:22:27 GMT Keep-Alive timeout=3, max=100 Pragma no-cache Server Apache Transfer-Encoding chunked X-Powered-By PHP/5.2.17 Hey, Looks great! BUT, I have a couple .php pages I need some very short caching on. I thought the simple answer was having this added to the very top of each php page in which I want caching enabled: <?php header("Cache-Control: max-age=360"); ?> Nope. Then I tried various versions of the above. Nope. Then I tried meta http-equiv variations. Nope. Then I tried variations of the .htaccess code along with the above variations, such as limiting it to: # Eliminate caching for certain dynamic files <FilesMatch "\.(php|cgi|pl)$"> Header set Cache-Control "no-cache, max-age=0" </FilesMatch> Nope. It seems nothing I do will allow a single .php to be cache enabled with the .htaccess code in place, short of removing the statements from the .htaccess file altogether. Where am I going wrong? What do I have to do to get individual php pages to be cacheable while the rest remain off?? Thank you for any thoughts.

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  • How mod_cache working with "must-revalidate" and "max-age"?

    - by Dmitriy Sosunov
    Quick question before I will explain my flow: ?an mod_cache perform revalidate with if-none-match only if max-age is expired in case if it configured in reverse proxy mode? My goal is to reduce a number of revalidation requests to our the origin server. For instance: The first request goes to the origin server and then mod_cache save a response in to the cache according to header cache-control: max-age. And only when max-age is expired then mod_cache will revalidate with if-none-match. Currently, mod_cache revalidate each request, regardless that max-age is defined or not. My configuration of Apache 2.4.3 (Windows), on linux I see the same behavior that I will show below. ServerName proxy.lo ProxyRequests Off ProxyPreserveHost Off Header set Vary "Accept, Content-Type, Content-Encoding, Accept-Language" RequestHeader set X-Forwarded-Proto "http" # modify header for user agent's Header set Cache-Control "private, no-cache, no-store, no-transform" CacheQuickHandler off CacheDefaultExpire 300 # the origin server do not provide last-modified CacheIgnoreNoLastMod On CacheIgnoreCacheControl On # the origin server define cache-control: private, no-store only for user agents # Therefore, I would like ignore those headers on the proxy server. CacheStorePrivate On CacheStoreNoStore On CacheEnable disk / CacheRoot "C:/Apache.Cache" CacheDirLevels 5 CacheDirLength 4 CacheMinExpire 15 CacheDetailHeader on CacheHeader on KeepAlive Off ProxyPass / http://origin.lo/ ProxyPassReverse / http://origin.lo/ Also, I have turned on debug log level to see how mod_cache handles a content for caching: I provided this to show that mod_proxy always decides that a content isn't fresh. Why?I provided this to show that mod_proxy always decide that a content isn't fresh. Why? max-age was provided (see below). [Sun Nov 04 11:58:42.899890 2012] [cache:debug] [pid 6492:tid 1400] cache_storage.c(624): [client 192.168.1.100:63741] AH00698: cache: Key for entity /testpage?(null) is http://proxy.lo/testpage? [Sun Nov 04 11:58:42.899890 2012] [cache_disk:debug] [pid 6492:tid 1400] mod_cache_disk.c(569): [client 192.168.1.100:63741] AH00709: Recalled cached URL info header http://proxy.lo/testpage? [Sun Nov 04 11:58:42.899890 2012] [cache_disk:debug] [pid 6492:tid 1400] mod_cache_disk.c(865): [client 192.168.1.100:63741] AH00720: Recalled headers for URL http://proxy.lo/testpage? [Sun Nov 04 11:58:42.899890 2012] [cache:debug] [pid 6492:tid 1400] cache_storage.c(320): [client 192.168.1.100:63741] AH00695: Cached response for /testpage isn't fresh. Adding/replacing conditional request headers. [Sun Nov 04 11:58:42.899890 2012] [cache:debug] [pid 6492:tid 1400] mod_cache.c(414): [client 192.168.1.100:63741] AH00757: Adding CACHE_SAVE filter for /testpage [Sun Nov 04 11:58:42.899890 2012] [cache:debug] [pid 6492:tid 1400] mod_cache.c(448): [client 192.168.1.100:63741] AH00759: Adding CACHE_REMOVE_URL filter for /testpage [Sun Nov 04 11:58:42.899890 2012] [proxy:debug] [pid 6492:tid 1400] mod_proxy.c(1068): [client 192.168.1.100:63741] AH01143: Running scheme http handler (attempt 0) [Sun Nov 04 11:58:42.899890 2012] [proxy:debug] [pid 6492:tid 1400] proxy_util.c(1976): AH00942: HTTP: has acquired connection for (origin.lo) [Sun Nov 04 11:58:42.899890 2012] [proxy:debug] [pid 6492:tid 1400] proxy_util.c(2029): [client 192.168.1.100:63741] AH00944: connecting http://origin.lo/testpage to origin.lo:80 [Sun Nov 04 11:58:42.901890 2012] [proxy:debug] [pid 6492:tid 1400] proxy_util.c(2151): [client 192.168.1.100:63741] AH00947: connected /testpage to origin.lo:80 [Sun Nov 04 11:58:42.901890 2012] [proxy:debug] [pid 6492:tid 1400] proxy_util.c(2554): AH00962: HTTP: connection complete to 192.168.1.100:80 (origin.lo) [Sun Nov 04 11:58:42.903890 2012] [proxy:debug] [pid 6492:tid 1400] proxy_util.c(1991): AH00943: http: has released connection for (origin.lo) [Sun Nov 04 11:58:42.903890 2012] [headers:debug] [pid 6492:tid 1400] mod_headers.c(800): AH01502: headers: ap_headers_output_filter() [Sun Nov 04 11:58:42.903890 2012] [cache:debug] [pid 6492:tid 1400] mod_cache.c(1190): [client 192.168.1.100:63741] AH00769: cache: Caching url: /testpage [Sun Nov 04 11:58:42.903890 2012] [cache:debug] [pid 6492:tid 1400] mod_cache.c(1196): [client 192.168.1.100:63741] AH00770: cache: Removing CACHE_REMOVE_URL filter. [Sun Nov 04 11:58:42.904890 2012] [cache_disk:debug] [pid 6492:tid 1400] mod_cache_disk.c(1318): [client 192.168.1.100:63741] AH00737: commit_entity: Headers and body for URL http://proxy.lo/testpage? cached. The first request to the origin server without mod_proxy to http://origin.lo/ GET http://origin.lo/testpage HTTP/1.1 Host: origin.lo Connection: keep-alive User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.4 (KHTML, like Gecko) Chrome/22.0.1229.94 Safari/537.4 Accept: application/json Accept-Encoding: gzip,deflate,sdch Accept-Language: en-US,en;q=0.8 Accept-Charset: ISO-8859-1,utf-8;q=0.7,*;q=0.3 The first response from the origin without mod_proxy HTTP/1.1 200 OK Cache-Control: must-revalidate, proxy-revalidate, max-age=30 Content-Type: application/json; charset=utf-8 ETag: "7cf651e2-176f-4ac1-808e-0e0c17cfd0a2" Server: Microsoft-IIS/7.5 X-AspNet-Version: 4.0.30319 X-Powered-By: ASP.NET Date: Sun, 04 Nov 2012 10:11:01 GMT Content-Length: 1877 So, I assumed that revalidation must be occur only in 30 seconds after the success response. Is't right? Let's check it:) Within 30 sec, the Google Chrome didn't perform any requests to the origin server to revalidate a request and has return the response from local cache. When max-age is expired, the Google Chrome perform a request to revalidate: GET http://origin.lo/testpage HTTP/1.1 Host: origin.lo Connection: keep-alive Cache-Control: max-age=0 User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.4 (KHTML, like Gecko) Chrome/22.0.1229.94 Safari/537.4 Accept: application/xml If-None-Match: "7cf651e2-176f-4ac1-808e-0e0c17cfd0a2" Accept-Encoding: gzip,deflate,sdch Accept-Language: en-US,en;q=0.8 Accept-Charset: ISO-8859-1,utf-8;q=0.7,*;q=0.3 and response: HTTP/1.1 304 Not Modified Cache-Control: must-revalidate, proxy-revalidate, max-age=30 ETag: "7cf651e2-176f-4ac1-808e-0e0c17cfd0a2" Server: Microsoft-IIS/7.5 X-AspNet-Version: 4.0.30319 X-Powered-By: ASP.NET Date: Sun, 04 Nov 2012 10:16:20 GMT As you can see, all works as expected. User agent revalidates request only when max-age is expired. Let's now try perform the folling flow though mod_proxy (see configuration above). The first request: GET http://proxy.lo/testpage HTTP/1.1 Host: proxy.lo Connection: keep-alive User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.4 (KHTML, like Gecko) Chrome/22.0.1229.94 Safari/537.4 Accept: application/json Accept-Encoding: gzip,deflate,sdch Accept-Language: en-US,en;q=0.8 Accept-Charset: ISO-8859-1,utf-8;q=0.7,*;q=0.3 and the response was: HTTP/1.1 200 OK Date: Sun, 04 Nov 2012 10:23:36 GMT Server: Apache Cache-Control: private, no-cache, no-store, no-transform Content-Type: application/json; charset=utf-8 ETag: "7cf651e2-176f-4ac1-808e-0e0c17cfd0a2" Content-Length: 1932 Vary: Accept,Content-Type,Content-Encoding,Accept-Language X-Cache: MISS from proxy.lo X-Cache-Detail: "cache miss: attempting entity save" from proxy.lo Connection: close Ok, let's see to the disk cache and try to see how request and response was stored. (I cut binary data) http://proxy.lo/testpage? Cache-Control: private, no-cache, no-store, no-transform Content-Type: application/json; charset=utf-8 ETag: "7cf651e2-176f-4ac1-808e-0e0c17cfd0a2" Date: Sun, 04 Nov 2012 10:27:15 GMT Content-Length: 1932 Vary: Accept, Content-Type, Content-Encoding, Accept-Language Host: proxy.lo User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.4 (KHTML, like Gecko) Chrome/22.0.1229.94 Safari/537.4 Accept: application/json Accept-Encoding: gzip,deflate,sdch Accept-Language: en-US,en;q=0.8 Accept-Charset: ISO-8859-1,utf-8;q=0.7,*;q=0.3 X-Forwarded-Proto: http Cache-Control: max-age=300, must-revalidate X-Forwarded-For: 192.168.1.100 X-Forwarded-Host: proxy.lo X-Forwarded-Server: origin.lo Ok, what we see? We see that the first request was performed with max-age=300 & must-revalidate Ok, looks good, as for me, lets perform the next call: GET http://proxy.lo/testpage HTTP/1.1 Host: proxy.lo Connection: keep-alive User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.4 (KHTML, like Gecko) Chrome/22.0.1229.94 Safari/537.4 Accept: application/json Accept-Encoding: gzip,deflate,sdch Accept-Language: en-US,en;q=0.8 Accept-Charset: ISO-8859-1,utf-8;q=0.7,*;q=0.3 and the second response from mod_proxy: HTTP/1.1 200 OK Date: Sun, 04 Nov 2012 10:31:58 GMT Server: Apache Cache-Control: private, no-cache, no-store, no-transform ETag: "7cf651e2-176f-4ac1-808e-0e0c17cfd0a2" Content-Length: 1932 Vary: Accept,Content-Type,Content-Encoding,Accept-Language X-Cache: REVALIDATE from proxy.lo X-Cache-Detail: "conditional cache hit: entity refreshed" from proxy.lo Connection: close Content-Type: application/json; charset=utf-8 SO, MY QUESTION IS: WHY mod_proxy perform revalidation on each request regardless that max-age is defined? N.B. Apache 2.4.3 Thanks, I would be grateful for any help.

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  • Is learning the Caché database hard coming from relational databases and object oriented programming

    - by Edelcom
    I am currently running the local version of Caché on my system in order to determine if I can (and will) take on a new possible project. The current project uses Delphi 7 as a front end calling a Caché dll where the business logic is stored in the database. I have a background of Sqlserver and Firebird (and before Access and Paradox) as databases. I use Delphi 7 for 95% of my Windows development, so I know about object programming. I would like to recieve opinions from persons having used Caché and either SqlServer, Firebird or Oracle and having developed in Delphi (or C++ or C# - an object oriented language). I have read the pro's and con's from other questions, but I am not asking for this, I need input from Caché developers. Thanks in advance.

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  • Calculating the Size (in Bytes and MB) of a Oracle Coherence Cache

    - by Ricardo Ferreira
    The concept and usage of data grids are becoming very popular in this days since this type of technology are evolving very fast with some cool lead products like Oracle Coherence. Once for a while, developers need an programmatic way to calculate the total size of a specific cache that are residing in the data grid. In this post, I will show how to accomplish this using Oracle Coherence API. This example has been tested with 3.6, 3.7 and 3.7.1 versions of Oracle Coherence. To start the development of this example, you need to create a POJO ("Plain Old Java Object") that represents a data structure that will hold user data. This data structure will also create an internal fat so I call that should increase considerably the size of each instance in the heap memory. Create a Java class named "Person" as shown in the listing below. package com.oracle.coherence.domain; import java.io.Serializable; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Random; @SuppressWarnings("serial") public class Person implements Serializable { private String firstName; private String lastName; private List<Object> fat; private String email; public Person() { generateFat(); } public Person(String firstName, String lastName, String email) { setFirstName(firstName); setLastName(lastName); setEmail(email); generateFat(); } private void generateFat() { fat = new ArrayList<Object>(); Random random = new Random(); for (int i = 0; i < random.nextInt(18000); i++) { HashMap<Long, Double> internalFat = new HashMap<Long, Double>(); for (int j = 0; j < random.nextInt(10000); j++) { internalFat.put(random.nextLong(), random.nextDouble()); } fat.add(internalFat); } } public String getFirstName() { return firstName; } public void setFirstName(String firstName) { this.firstName = firstName; } public String getLastName() { return lastName; } public void setLastName(String lastName) { this.lastName = lastName; } public String getEmail() { return email; } public void setEmail(String email) { this.email = email; } } Now let's create a Java program that will start a data grid into Coherence and will create a cache named "People", that will hold people instances with sequential integer keys. Each person created in this program will trigger the execution of a custom constructor created in the People class that instantiates an internal fat (the random amount of data generated to increase the size of the object) for each person. Create a Java class named "CreatePeopleCacheAndPopulateWithData" as shown in the listing below. package com.oracle.coherence.demo; import com.oracle.coherence.domain.Person; import com.tangosol.net.CacheFactory; import com.tangosol.net.NamedCache; public class CreatePeopleCacheAndPopulateWithData { public static void main(String[] args) { // Asks Coherence for a new cache named "People"... NamedCache people = CacheFactory.getCache("People"); // Creates three people that will be putted into the data grid. Each person // generates an internal fat that should increase its size in terms of bytes... Person pessoa1 = new Person("Ricardo", "Ferreira", "[email protected]"); Person pessoa2 = new Person("Vitor", "Ferreira", "[email protected]"); Person pessoa3 = new Person("Vivian", "Ferreira", "[email protected]"); // Insert three people at the data grid... people.put(1, pessoa1); people.put(2, pessoa2); people.put(3, pessoa3); // Waits for 5 minutes until the user runs the Java program // that calculates the total size of the people cache... try { System.out.println("---> Waiting for 5 minutes for the cache size calculation..."); Thread.sleep(300000); } catch (InterruptedException ie) { ie.printStackTrace(); } } } Finally, let's create a Java program that, using the Coherence API and JMX, will calculate the total size of each cache that the data grid is currently managing. The approach used in this example was retrieve every cache that the data grid are currently managing, but if you are interested on an specific cache, the same approach can be used, you should only filter witch cache will be looked for. Create a Java class named "CalculateTheSizeOfPeopleCache" as shown in the listing below. package com.oracle.coherence.demo; import java.text.DecimalFormat; import java.util.Map; import java.util.Set; import java.util.TreeMap; import javax.management.MBeanServer; import javax.management.MBeanServerFactory; import javax.management.ObjectName; import com.tangosol.net.CacheFactory; public class CalculateTheSizeOfPeopleCache { @SuppressWarnings({ "unchecked", "rawtypes" }) private void run() throws Exception { // Enable JMX support in this Coherence data grid session... System.setProperty("tangosol.coherence.management", "all"); // Create a sample cache just to access the data grid... CacheFactory.getCache(MBeanServerFactory.class.getName()); // Gets the JMX server from Coherence data grid... MBeanServer jmxServer = getJMXServer(); // Creates a internal data structure that would maintain // the statistics from each cache in the data grid... Map cacheList = new TreeMap(); Set jmxObjectList = jmxServer.queryNames(new ObjectName("Coherence:type=Cache,*"), null); for (Object jmxObject : jmxObjectList) { ObjectName jmxObjectName = (ObjectName) jmxObject; String cacheName = jmxObjectName.getKeyProperty("name"); if (cacheName.equals(MBeanServerFactory.class.getName())) { continue; } else { cacheList.put(cacheName, new Statistics(cacheName)); } } // Updates the internal data structure with statistic data // retrieved from caches inside the in-memory data grid... Set<String> cacheNames = cacheList.keySet(); for (String cacheName : cacheNames) { Set resultSet = jmxServer.queryNames( new ObjectName("Coherence:type=Cache,name=" + cacheName + ",*"), null); for (Object resultSetRef : resultSet) { ObjectName objectName = (ObjectName) resultSetRef; if (objectName.getKeyProperty("tier").equals("back")) { int unit = (Integer) jmxServer.getAttribute(objectName, "Units"); int size = (Integer) jmxServer.getAttribute(objectName, "Size"); Statistics statistics = (Statistics) cacheList.get(cacheName); statistics.incrementUnit(unit); statistics.incrementSize(size); cacheList.put(cacheName, statistics); } } } // Finally... print the objects from the internal data // structure that represents the statistics from caches... cacheNames = cacheList.keySet(); for (String cacheName : cacheNames) { Statistics estatisticas = (Statistics) cacheList.get(cacheName); System.out.println(estatisticas); } } public MBeanServer getJMXServer() { MBeanServer jmxServer = null; for (Object jmxServerRef : MBeanServerFactory.findMBeanServer(null)) { jmxServer = (MBeanServer) jmxServerRef; if (jmxServer.getDefaultDomain().equals(DEFAULT_DOMAIN) || DEFAULT_DOMAIN.length() == 0) { break; } jmxServer = null; } if (jmxServer == null) { jmxServer = MBeanServerFactory.createMBeanServer(DEFAULT_DOMAIN); } return jmxServer; } private class Statistics { private long unit; private long size; private String cacheName; public Statistics(String cacheName) { this.cacheName = cacheName; } public void incrementUnit(long unit) { this.unit += unit; } public void incrementSize(long size) { this.size += size; } public long getUnit() { return unit; } public long getSize() { return size; } public double getUnitInMB() { return unit / (1024.0 * 1024.0); } public double getAverageSize() { return size == 0 ? 0 : unit / size; } public String toString() { StringBuffer sb = new StringBuffer(); sb.append("\nCache Statistics of '").append(cacheName).append("':\n"); sb.append(" - Total Entries of Cache -----> " + getSize()).append("\n"); sb.append(" - Used Memory (Bytes) --------> " + getUnit()).append("\n"); sb.append(" - Used Memory (MB) -----------> " + FORMAT.format(getUnitInMB())).append("\n"); sb.append(" - Object Average Size --------> " + FORMAT.format(getAverageSize())).append("\n"); return sb.toString(); } } public static void main(String[] args) throws Exception { new CalculateTheSizeOfPeopleCache().run(); } public static final DecimalFormat FORMAT = new DecimalFormat("###.###"); public static final String DEFAULT_DOMAIN = ""; public static final String DOMAIN_NAME = "Coherence"; } I've commented the overall example so, I don't think that you should get into trouble to understand it. Basically we are dealing with JMX. The first thing to do is enable JMX support for the Coherence client (ie, an JVM that will only retrieve values from the data grid and will not integrate the cluster) application. This can be done very easily using the runtime "tangosol.coherence.management" system property. Consult the Coherence documentation for JMX to understand the possible values that could be applied. The program creates an in memory data structure that holds a custom class created called "Statistics". This class represents the information that we are interested to see, which in this case are the size in bytes and in MB of the caches. An instance of this class is created for each cache that are currently managed by the data grid. Using JMX specific methods, we retrieve the information that are relevant for calculate the total size of the caches. To test this example, you should execute first the CreatePeopleCacheAndPopulateWithData.java program and after the CreatePeopleCacheAndPopulateWithData.java program. The results in the console should be something like this: 2012-06-23 13:29:31.188/4.970 Oracle Coherence 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded operational configuration from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/tangosol-coherence.xml" 2012-06-23 13:29:31.219/5.001 Oracle Coherence 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded operational overrides from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/tangosol-coherence-override-dev.xml" 2012-06-23 13:29:31.219/5.001 Oracle Coherence 3.6.0.4 <D5> (thread=Main Thread, member=n/a): Optional configuration override "/tangosol-coherence-override.xml" is not specified 2012-06-23 13:29:31.266/5.048 Oracle Coherence 3.6.0.4 <D5> (thread=Main Thread, member=n/a): Optional configuration override "/custom-mbeans.xml" is not specified Oracle Coherence Version 3.6.0.4 Build 19111 Grid Edition: Development mode Copyright (c) 2000, 2010, Oracle and/or its affiliates. All rights reserved. 2012-06-23 13:29:33.156/6.938 Oracle Coherence GE 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded Reporter configuration from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/reports/report-group.xml" 2012-06-23 13:29:33.500/7.282 Oracle Coherence GE 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Loaded cache configuration from "jar:file:/E:/Oracle/Middleware/oepe_11gR1PS4/workspace/calcular-tamanho-cache-coherence/lib/coherence.jar!/coherence-cache-config.xml" 2012-06-23 13:29:35.391/9.173 Oracle Coherence GE 3.6.0.4 <D4> (thread=Main Thread, member=n/a): TCMP bound to /192.168.177.133:8090 using SystemSocketProvider 2012-06-23 13:29:37.062/10.844 Oracle Coherence GE 3.6.0.4 <Info> (thread=Cluster, member=n/a): This Member(Id=2, Timestamp=2012-06-23 13:29:36.899, Address=192.168.177.133:8090, MachineId=55685, Location=process:244, Role=Oracle, Edition=Grid Edition, Mode=Development, CpuCount=2, SocketCount=2) joined cluster "cluster:0xC4DB" with senior Member(Id=1, Timestamp=2012-06-23 13:29:14.031, Address=192.168.177.133:8088, MachineId=55685, Location=process:1128, Role=CreatePeopleCacheAndPopulateWith, Edition=Grid Edition, Mode=Development, CpuCount=2, SocketCount=2) 2012-06-23 13:29:37.172/10.954 Oracle Coherence GE 3.6.0.4 <D5> (thread=Cluster, member=n/a): Member 1 joined Service Cluster with senior member 1 2012-06-23 13:29:37.188/10.970 Oracle Coherence GE 3.6.0.4 <D5> (thread=Cluster, member=n/a): Member 1 joined Service Management with senior member 1 2012-06-23 13:29:37.188/10.970 Oracle Coherence GE 3.6.0.4 <D5> (thread=Cluster, member=n/a): Member 1 joined Service DistributedCache with senior member 1 2012-06-23 13:29:37.188/10.970 Oracle Coherence GE 3.6.0.4 <Info> (thread=Main Thread, member=n/a): Started cluster Name=cluster:0xC4DB Group{Address=224.3.6.0, Port=36000, TTL=4} MasterMemberSet ( ThisMember=Member(Id=2, Timestamp=2012-06-23 13:29:36.899, Address=192.168.177.133:8090, MachineId=55685, Location=process:244, Role=Oracle) OldestMember=Member(Id=1, Timestamp=2012-06-23 13:29:14.031, Address=192.168.177.133:8088, MachineId=55685, Location=process:1128, Role=CreatePeopleCacheAndPopulateWith) ActualMemberSet=MemberSet(Size=2, BitSetCount=2 Member(Id=1, Timestamp=2012-06-23 13:29:14.031, Address=192.168.177.133:8088, MachineId=55685, Location=process:1128, Role=CreatePeopleCacheAndPopulateWith) Member(Id=2, Timestamp=2012-06-23 13:29:36.899, Address=192.168.177.133:8090, MachineId=55685, Location=process:244, Role=Oracle) ) RecycleMillis=1200000 RecycleSet=MemberSet(Size=0, BitSetCount=0 ) ) TcpRing{Connections=[1]} IpMonitor{AddressListSize=0} 2012-06-23 13:29:37.891/11.673 Oracle Coherence GE 3.6.0.4 <D5> (thread=Invocation:Management, member=2): Service Management joined the cluster with senior service member 1 2012-06-23 13:29:39.203/12.985 Oracle Coherence GE 3.6.0.4 <D5> (thread=DistributedCache, member=2): Service DistributedCache joined the cluster with senior service member 1 2012-06-23 13:29:39.297/13.079 Oracle Coherence GE 3.6.0.4 <D4> (thread=DistributedCache, member=2): Asking member 1 for 128 primary partitions Cache Statistics of 'People': - Total Entries of Cache -----> 3 - Used Memory (Bytes) --------> 883920 - Used Memory (MB) -----------> 0.843 - Object Average Size --------> 294640 I hope that this post could save you some time when calculate the total size of Coherence cache became a requirement for your high scalable system using data grids. See you!

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  • Cache-control for permanent 301 redirects nginx

    - by gansbrest
    I was wondering if there is a way to control lifetime of the redirects in Nginx? We would liek to cache 301 redirects in CDN for specific amount of time, let say 20 minutes and the CDN is controlled by the standard caching headers. By default there is no Cache-control or Expires directives with the Nginx redirect. That could cause the redirect to be cached for a really long time. By having specific redirect lifetime the system could have a chance to correct itself, knowing that even "permanent" redirect change from time to time.. The other thing is that those redirects are included from the Server block, which according the nginx specification should be evaluated before locations. I tried to add add_header Cache-Control "max-age=1200, public"; to the bottom of the redirects file, but the problem is that Cache-control gets added twice - first comes let say from the backend script and the other one added by the add_header directive.. In Apache there is the environment variable trick to control headers for rewrites: RewriteRule /taxonomy/term/(\d+)/feed /taxonomy/term/$1 [R=301,E=expire:1] Header always set Cache-Control "store, max-age=1200" env=expire But I'm not sure how to accomplish this in Nginx.

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  • Nginx Cache-Control

    - by optixx
    Iam serving my static content with ngnix. location /static { alias /opt/static/blog/; access_log off; etags on; etag_hash on; etag_hash_method md5; expires 1d; add_header Pragma "public"; add_header Cache-Control "public, must-revalidate, proxy-revalidate"; } The resulting header looks like this: Cache-Control:public, must-revalidate, proxy-revalidate Cache-Control:max-age=86400 Connection:close Content-Encoding:gzip Content-Type:application/x-javascript; charset=utf-8 Date:Tue, 11 Sep 2012 08:39:05 GMT Etag:e2266fb151337fc1996218fafcf3bcee Expires:Wed, 12 Sep 2012 08:39:05 GMT Last-Modified:Tue, 11 Sep 2012 06:22:41 GMT Pragma:public Server:nginx/1.2.2 Transfer-Encoding:chunked Vary:Accept-Encoding Why is nginx sending 2 Cache-Control entries, could this be a problem for the clients?

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  • Flush mod_pagespeed cache in Debian

    - by Ivar
    I need a way to flush the mod_pagespeed cache while developing. According to mod_pagespeed documents, I should run the following command: sudo touch /var/mod_pagespeed/cache/cache.flush In Debian it's "su" instead of "sudo". However, it doesn't work for me; there's no "touch" command, nor is there any "cache.flush" file in the defined directory. Have I missed something? You kick-ass Linux users, please be humble - I'm pretty new to these stuff. Thank you in advance!

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  • Force request to miss cache but still store the response

    - by Tom Marthenal
    I have a slow web app that I've placed Varnish in front of. All of the pages are static (they don't vary for a different user), but they need to be updated every 5 minutes so they contain recent data. I have a simple script (wget --mirror) that crawls the entire website every 15 minutes. Each crawl takes about 5 minutes. The point of the crawl is to update every page in the Varnish cache so that a user never has to wait for the page to generate (since all pages have been generated recently thanks to the spider). The timeline looks like this: 00:00:00: Cache flushed 00:00:00: Spider starts crawling to update cache with new pages 00:05:00: Spider finishes crawling, all pages are updated until 1:15 A request that comes in between 0:00:00 and 0:05:00 might hit a page that hasn't been updated yet, and will be forced to wait a few seconds for a response. This isn't acceptable. What I'd like to do is, perhaps using some VCL magic, always foward requests from the spider to the backend, but still store the response in the cache. This way, a user will never have to wait for a page to generate since there is no 5-minute window in which parts of the cache are empty (except perhaps at server startup). How can I do this?

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  • How to increase the disk cache of Windows 7

    - by Mark Christiaens
    Under Windows 7 (64 bit), I'm reading through 9000 moderately sized files. In total, there is more than 200 MB of data. Using Java (JDK 1.6.21) I'm iterating over the files. The first 1400 or so go at full speed but then speed drops off to 4ms per file. It turns out that the main cost is incurred simply by opening the files. I'm opening the files using new FileInputStream (and of course closing them in time to avoid file leaks). After some investigating, I see that Windows' disk cache is using only 100 MB or so of RAM although I have 8 GiB available. I've tried increasing the cache size using the CacheSet tool but any values I provide are considered out of range. I've also tried enabling the LargeSystemCache registry key but (after rebooting) the CacheSet tool still indicates I'm using 100 MB of cache (and doesn't increase during the test run). Does anybody have any suggestions to "encourage" Windows 7 to cache my 9000 files?

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  • SBUG Session: The Enterprise Cache

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] I did a session on "The Enterprise Cache" at the UK SOA/BPM User Group yesterday which generated some useful discussion. The proposal was for a dedicated caching layer which all app servers and service providers can hook into, sharing resources and common data. The architecture might end up like this: I'll update this post with a link to the slide deck once it's available. The next session will have Udi Dahan walking through nServiceBus, register on EventBrite if you want to come along. Synopsis Looked at the benefits and drawbacks of app-centric isolated caches, compared to an enterprise-wide shared cache running on dedicated nodes; Suggested issues and risks around caching including staleness of data, resource usage, performance and testing; Walked through a generic service cache implemented as a WCF behaviour – suitable for IIS- or BizTalk-hosted services - which I'll be releasing on CodePlex shortly; Listed common options for cache providers and their offerings. Discussion Cache usage. Different value propositions for utilising the cache: improved performance, isolation from underlying systems (e.g. service output caching can have a TTL large enough to cover downtime), reduced resource impact – CPU, memory, SQL and cost (e.g. caching results of paid-for services). Dedicated cache nodes. Preferred over in-host caching provided latency is acceptable. Depending on cache provider, can offer easy scalability and global replication so cache clients always use local nodes. Restriction of AppFabric Caching to Windows Server 2008 not viewed as a concern. Security. Limited security model in most cache providers. Options for securing cache content suggested as custom implementations. Obfuscating keys and serialized values may mean additional security is not needed. Depending on security requirements and architecture, can ensure cache servers only accessible to cache clients via IPsec. Staleness. Generally thought to be an overrated problem. Thinking in line with eventual consistency, that serving up stale data may not be a significant issue. Good technical arguments support this, although I suspect business users will be harder to persuade. Providers. Positive feedback for AppFabric Caching – speed, configurability and richness of the distributed model making it a good enterprise choice. .NET port of memcached well thought of for performance but lack of replication makes it less suitable for these shared scenarios. Replicated fork – repcached – untried and less active than memcached. NCache also well thought of, but Express version too limited for enterprise scenarios, and commercial versions look costly compared to AppFabric.

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  • How should I force-enable BIND's persistent cache, or Unbound's persistent cache

    - by Jacob Rabinsun
    I am trying to run a local DNS server on my home computer so that I can both increase DNS lookups speed and reduce bandwidth use, so that both my laptop and my PC can do lookups faster. I have got BIND 9 running very smoothly, there is only one simple problem, and that being the fact that BIND is not a persistent DNS cache, and if I restart its service, the whole cash would be wiped out. So, is there a way that I could make BIND9 keep its cache after system restart? Also, which one is better Unbound or BIND? Which one would you suggest? Does Unbound DNS have a persistent cache or can it be enabled?

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  • I am trying to figure out the best way to understand how to cache domain objects

    - by Brett Ryan
    I've always done this wrong, I'm sure a lot of others have too, hold a reference via a map and write through to DB etc.. I need to do this right, and I just don't know how to go about it. I know how I want my objects to be cached but not sure on how to achieve it. What complicates things is that I need to do this for a legacy system where the DB can change without notice to my application. So in the context of a web application, let's say I have a WidgetService which has several methods: Widget getWidget(); Collection<Widget> getAllWidgets(); Collection<Widget> getWidgetsByCategory(String categoryCode); Collection<Widget> getWidgetsByContainer(Integer parentContainer); Collection<Widget> getWidgetsByStatus(String status); Given this, I could decide to cache by method signature, i.e. getWidgetsByCategory("AA") would have a single cache entry, or I could cache widgets individually, which would be difficult I believe; OR, a call to any method would then first cache ALL widgets with a call to getAllWidgets() but getAllWidgets() would produce caches that match all the keys for the other method invocations. For example, take the following untested theoretical code. Collection<Widget> getAllWidgets() { Entity entity = cache.get("ALL_WIDGETS"); Collection<Widget> res; if (entity == null) { res = loadCache(); } else { res = (Collection<Widget>) entity.getValue(); } return res } Collection<Widget> loadCache() { // Get widgets from underlying DB Collection<Widget> res = db.getAllWidgets(); cache.put("ALL_WIDGETS", res); Map<String, List<Widget>> byCat = new HashMap<>(); for (Widget w : res) { // cache by different types of method calls, i.e. by category if (!byCat.containsKey(widget.getCategory()) { byCat.put(widget.getCategory(), new ArrayList<Widget>); } byCat.get(widget.getCatgory(), widget); } cacheCategories(byCat); return res; } Collection<Widget> getWidgetsByCategory(String categoryCode) { CategoryCacheKey key = new CategoryCacheKey(categoryCode); Entity ent = cache.get(key); if (entity == null) { loadCache(); } ent = cache.get(key); return ent == null ? Collections.emptyList() : (Collection<Widget>)ent.getValue(); } NOTE: I have not worked with a cache manager, the above code illustrates cache as some object that may hold caches by key/value pairs, though it's not modelled on any specific implementation. Using this I have the benefit of being able to cache all objects in the different ways they will be called with only single objects on the heap, whereas if I were to cache the method call invocation via say Spring It would (I believe) cache multiple copies of the objects. I really wish to try and understand the best ways to cache domain objects before I go down the wrong path and make it harder for myself later. I have read the documentation on the Ehcache website and found various articles of interest, but nothing to give a good solid technique. Since I'm working with an ERP system, some DB calls are very complicated, not that the DB is slow, but the business representation of the domain objects makes it very clumsy, coupled with the fact that there are actually 11 different DB's where information can be contained that this application is consolidating in a single view, this makes caching quite important.

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  • Cache efficient code

    - by goldenmean
    This could sound a subjective question, but what i am looking for is specific instances which you would have encountered related to this. 1) How to make a code, cache effective-cache friendly? (More cache hits, as less cahce misses as possible). from both perspectives, data cache & program cache(instruction cache). i.e. What all things in one's code, related to data structures, code constructs one should take care of to make it cache effective. 2) Are there any particular data structures one must use, must avoid,or particular way of accessing the memers of that structure etc.. to make code cache effective. 3) Are there any program constructs(if, for, switch, break, goto,...), code-flow(for inside a if, if inside a for, etc...) one should follow/avoid in this matter? I am looking forward to hear individual experiences related to making a cache efficient code in general. It can be any programming language(C,C++,ASsembly,...), any hardware target(ARM,Intel,PowerPC,...), any OS(Windows,Linux,Symbian,...) etc.. More the variety, it will help better to understand it deeply.

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  • Too many Bind query (cache) denied, DNS attack?

    - by Jake
    Once Bind crashed and I did: tail -f /var/log/messages I see a massive number of logs every second. Is this a DNS attack? or is there something wrong? Sometimes I see a domain in logs like this: dOmAin.com (upper and lower). As you see there is only one single domain in the logs with different IPs Oct 10 02:21:26 mail named[20831]: client 74.125.189.18#38921: query (cache) 'ns1.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.144.171#38833: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.17#42428: query (cache) 'ns2.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.146.27#37899: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 193.203.82.66#39263: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 8.0.16.170#59723: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 80.169.197.66#32903: query (cache) 'dOmAin.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 134.58.60.1#47558: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.146.34#47387: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 8.0.16.8#59392: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.19#64395: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 217.72.163.3#42190: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 83.146.21.252#22020: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.146.116#57342: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 193.203.82.66#52020: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 8.0.16.72#64317: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 80.169.197.66#31989: query (cache) 'dOmAin.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.18#47436: query (cache) 'ns2.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.16#44005: query (cache) 'ns1.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 85.132.31.10#50379: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 94.241.128.3#60106: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 85.132.31.10#59118: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 212.95.135.78#27811: query (cache) 'domain.com/A/IN' denied /etc/resolv.conf ; generated by /sbin/dhclient-script nameserver 4.2.2.4 nameserver 8.8.4.4 Bind config: // generated by named-bootconf.pl options { directory "/var/named"; /* * If there is a firewall between you and nameservers you want * to talk to, you might need to uncomment the query-source * directive below. Previous versions of BIND always asked * questions using port 53, but BIND 8.1 uses an unprivileged * port by default. */ // query-source address * port 53; allow-transfer { none; }; allow-recursion { localnets; }; //listen-on-v6 { any; }; notify no; }; // // a caching only nameserver config // controls { inet 127.0.0.1 allow { localhost; } keys { rndckey; }; }; zone "." IN { type hint; file "named.ca"; }; zone "localhost" IN { type master; file "localhost.zone"; allow-update { none; }; }; zone "0.0.127.in-addr.arpa" IN { type master; file "named.local"; allow-update { none; }; };

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  • Datanucleus/JDO Level 2 Cache on Google App Engine

    - by Thilo
    Is it possible (and does it make sense) to use the JDO Level 2 Cache for the Google App Engine Datastore? First of all, why is there no documentation about this on Google's pages? Are there some problems with it? Do we need to set up limits to protect our memcache quota? According to DataNucleus on Stackoverflow, you can set the following persistence properties: datanucleus.cache.level2.type=javax.cache datanucleus.cache.level2.cacheName={cache name} Is that all? Can we choose any cache name? Other sources on the Internet report using different settings. Also, it seems we need to download the DataNucleus Cache support plugin. Which version would be appropriate? And do we just place it in WEB-INF/lib or does it need more setup to activate it?

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  • Collections not read from hibernate/ehcache second-level-cache

    - by Mark van Venrooij
    I'm trying to cache lazy loaded collections with ehcache/hibernate in a Spring project. When I execute a session.get(Parent.class, 123) and browse through the children multiple times a query is executed every time to fetch the children. The parent is only queried the first time and then resolved from the cache. Probably I'm missing something, but I can't find the solution. Please see the relevant code below. I'm using Spring (3.2.4.RELEASE) Hibernate(4.2.1.Final) and ehcache(2.6.6) The parent class: @Entity @Table(name = "PARENT") @Cacheable @Cache(usage = CacheConcurrencyStrategy.READ_WRITE, include = "all") public class ServiceSubscriptionGroup implements Serializable { /** The Id. */ @Id @Column(name = "ID") private int id; @OneToMany(fetch = FetchType.LAZY, mappedBy = "parent") @Cache(usage = CacheConcurrencyStrategy.READ_WRITE) private List<Child> children; public List<Child> getChildren() { return children; } public void setChildren(List<Child> children) { this.children = children; } @Override public boolean equals(Object o) { if (this == o) return true; if (o == null || getClass() != o.getClass()) return false; Parent that = (Parent) o; if (id != that.id) return false; return true; } @Override public int hashCode() { return id; } } The child class: @Entity @Table(name = "CHILD") @Cacheable @Cache(usage = CacheConcurrencyStrategy.READ_WRITE, include = "all") public class Child { @Id @Column(name = "ID") private int id; @ManyToOne(fetch = FetchType.LAZY, cascade = CascadeType.ALL) @JoinColumn(name = "PARENT_ID") @Cache(usage = CacheConcurrencyStrategy.READ_WRITE) private Parent parent; public int getId() { return id; } public void setId(final int id) { this.id = id; } private Parent getParent(){ return parent; } private void setParent(Parent parent) { this.parent = parent; } @Override public boolean equals(final Object o) { if (this == o) { return true; } if (o == null || getClass() != o.getClass()) { return false; } final Child that = (Child) o; return id == that.id; } @Override public int hashCode() { return id; } } The application context: <bean id="sessionFactory" class="org.springframework.orm.hibernate4.LocalSessionFactoryBean"> <property name="dataSource" ref="dataSource" /> <property name="annotatedClasses"> <list> <value>Parent</value> <value>Child</value> </list> </property> <property name="hibernateProperties"> <props> <prop key="hibernate.dialect">org.hibernate.dialect.SQLServer2008Dialect</prop> <prop key="hibernate.hbm2ddl.auto">validate</prop> <prop key="hibernate.ejb.naming_strategy">org.hibernate.cfg.ImprovedNamingStrategy</prop> <prop key="hibernate.connection.charSet">UTF-8</prop> <prop key="hibernate.show_sql">true</prop> <prop key="hibernate.format_sql">true</prop> <prop key="hibernate.use_sql_comments">true</prop> <!-- cache settings ehcache--> <prop key="hibernate.cache.use_second_level_cache">true</prop> <prop key="hibernate.cache.use_query_cache">true</prop> <prop key="hibernate.cache.region.factory_class"> org.hibernate.cache.ehcache.SingletonEhCacheRegionFactory</prop> <prop key="hibernate.generate_statistics">true</prop> <prop key="hibernate.cache.use_structured_entries">true</prop> <prop key="hibernate.cache.use_query_cache">true</prop> <prop key="hibernate.transaction.factory_class"> org.hibernate.engine.transaction.internal.jta.JtaTransactionFactory</prop> <prop key="hibernate.transaction.jta.platform"> org.hibernate.service.jta.platform.internal.JBossStandAloneJtaPlatform</prop> </props> </property> </bean> The testcase I'm running: @Test public void testGetParentFromCache() { for (int i = 0; i <3 ; i++ ) { getEntity(); } } private void getEntity() { Session sess = sessionFactory.openSession() sess.setCacheMode(CacheMode.NORMAL); Transaction t = sess.beginTransaction(); Parent p = (Parent) s.get(Parent.class, 123); Assert.assertNotNull(p); Assert.assertNotNull(p.getChildren().size()); t.commit(); sess.flush(); sess.clear(); sess.close(); } In the logging I can see that the first time 2 queries are executed getting the parent and getting the children. Furthermore the logging shows that the child entities as well as the collection are stored in the 2nd level cache. However when reading the collection a query is executed to fetch the children on second and third attempt.

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 4

    - by MarkPearl
    Learning Outcomes Explain the characteristics of memory systems Describe the memory hierarchy Discuss cache memory principles Discuss issues relevant to cache design Describe the cache organization of the Pentium Computer Memory Systems There are key characteristics of memory… Location – internal or external Capacity – expressed in terms of bytes Unit of Transfer – the number of bits read out of or written into memory at a time Access Method – sequential, direct, random or associative From a users perspective the two most important characteristics of memory are… Capacity Performance – access time, memory cycle time, transfer rate The trade off for memory happens along three axis… Faster access time, greater cost per bit Greater capacity, smaller cost per bit Greater capacity, slower access time This leads to people using a tiered approach in their use of memory   As one goes down the hierarchy, the following occurs… Decreasing cost per bit Increasing capacity Increasing access time Decreasing frequency of access of the memory by the processor The use of two levels of memory to reduce average access time works in principle, but only if conditions 1 to 4 apply. A variety of technologies exist that allow us to accomplish this. Thus it is possible to organize data across the hierarchy such that the percentage of accesses to each successively lower level is substantially less than that of the level above. A portion of main memory can be used as a buffer to hold data temporarily that is to be read out to disk. This is sometimes referred to as a disk cache and improves performance in two ways… Disk writes are clustered. Instead of many small transfers of data, we have a few large transfers of data. This improves disk performance and minimizes processor involvement. Some data designed for write-out may be referenced by a program before the next dump to disk. In that case the data is retrieved rapidly from the software cache rather than slowly from disk. Cache Memory Principles Cache memory is substantially faster than main memory. A caching system works as follows.. When a processor attempts to read a word of memory, a check is made to see if this in in cache memory… If it is, the data is supplied, If it is not in the cache, a block of main memory, consisting of a fixed number of words is loaded to the cache. Because of the phenomenon of locality of references, when a block of data is fetched into the cache, it is likely that there will be future references to that same memory location or to other words in the block. Elements of Cache Design While there are a large number of cache implementations, there are a few basic design elements that serve to classify and differentiate cache architectures… Cache Addresses Cache Size Mapping Function Replacement Algorithm Write Policy Line Size Number of Caches Cache Addresses Almost all non-embedded processors support virtual memory. Virtual memory in essence allows a program to address memory from a logical point of view without needing to worry about the amount of physical memory available. When virtual addresses are used the designer may choose to place the cache between the MMU (memory management unit) and the processor or between the MMU and main memory. The disadvantage of virtual memory is that most virtual memory systems supply each application with the same virtual memory address space (each application sees virtual memory starting at memory address 0), which means the cache memory must be completely flushed with each application context switch or extra bits must be added to each line of the cache to identify which virtual address space the address refers to. Cache Size We would like the size of the cache to be small enough so that the overall average cost per bit is close to that of main memory alone and large enough so that the overall average access time is close to that of the cache alone. Also, larger caches are slightly slower than smaller ones. Mapping Function Because there are fewer cache lines than main memory blocks, an algorithm is needed for mapping main memory blocks into cache lines. The choice of mapping function dictates how the cache is organized. Three techniques can be used… Direct – simplest technique, maps each block of main memory into only one possible cache line Associative – Each main memory block to be loaded into any line of the cache Set Associative – exhibits the strengths of both the direct and associative approaches while reducing their disadvantages For detailed explanations of each approach – read the text book (page 148 – 154) Replacement Algorithm For associative and set associating mapping a replacement algorithm is needed to determine which of the existing blocks in the cache must be replaced by a new block. There are four common approaches… LRU (Least recently used) FIFO (First in first out) LFU (Least frequently used) Random selection Write Policy When a block resident in the cache is to be replaced, there are two cases to consider If no writes to that block have happened in the cache – discard it If a write has occurred, a process needs to be initiated where the changes in the cache are propagated back to the main memory. There are several approaches to achieve this including… Write Through – all writes to the cache are done to the main memory as well at the point of the change Write Back – when a block is replaced, all dirty bits are written back to main memory The problem is complicated when we have multiple caches, there are techniques to accommodate for this but I have not summarized them. Line Size When a block of data is retrieved and placed in the cache, not only the desired word but also some number of adjacent words are retrieved. As the block size increases from very small to larger sizes, the hit ratio will at first increase because of the principle of locality, which states that the data in the vicinity of a referenced word are likely to be referenced in the near future. As the block size increases, more useful data are brought into cache. The hit ratio will begin to decrease as the block becomes even bigger and the probability of using the newly fetched information becomes less than the probability of using the newly fetched information that has to be replaced. Two specific effects come into play… Larger blocks reduce the number of blocks that fit into a cache. Because each block fetch overwrites older cache contents, a small number of blocks results in data being overwritten shortly after they are fetched. As a block becomes larger, each additional word is farther from the requested word and therefore less likely to be needed in the near future. The relationship between block size and hit ratio is complex, and no set approach is judged to be the best in all circumstances.   Pentium 4 and ARM cache organizations The processor core consists of four major components: Fetch/decode unit – fetches program instruction in order from the L2 cache, decodes these into a series of micro-operations, and stores the results in the L2 instruction cache Out-of-order execution logic – Schedules execution of the micro-operations subject to data dependencies and resource availability – thus micro-operations may be scheduled for execution in a different order than they were fetched from the instruction stream. As time permits, this unit schedules speculative execution of micro-operations that may be required in the future Execution units – These units execute micro-operations, fetching the required data from the L1 data cache and temporarily storing results in registers Memory subsystem – This unit includes the L2 and L3 caches and the system bus, which is used to access main memory when the L1 and L2 caches have a cache miss and to access the system I/O resources

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  • Is it OK to set "Cache-Control: public" when sending “304 Not Modified” for images stored in the dat

    - by Emilien
    After asking a question about sending “304 Not Modified” for images stored in the in the Google App Engine datastore, I now have a question about Cache-Control. My app now sends Last-Modified and Etag, but by default GAE alsto sends Cache-Control: no-cache. According to this page: The “no-cache” directive, according to the RFC, tells the browser that it should revalidate with the server before serving the page from the cache. [...] In practice, IE and Firefox have started treating the no-cache directive as if it instructs the browser not to even cache the page. As I DO want browsers to cache the image, I've added the following line to my code: self.response.headers['Cache-Control'] = "public" According to the same page as before: The “cache-control: public” directive [...] tells the browser and proxies [...] that the page may be cached. This is good for non-sensitive pages, as caching improves performance. The question is if this could be harmful to the application in some way? Would it be best to send Cache-Control: must-revalidate to "force" the browser to revalidate (I suppose that is the behavior that was originally the reason behind sending Cache-Control: no-cache) This directive insists that the browser must revalidate the page against the server before serving it from cache. Note that it implicitly lets the browser cache the page.

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  • Squid refresh_pattern won't cache "Expires: ..."

    - by Marcelo Cantos
    Background I frequent the OpenGL ES documentation site at http://www.khronos.org/opengles/sdk/1.1/docs/man/. Even though the content is completely static, it seems to force a reload on every single page I visit, which is very annoying. I have a squid 3.0 proxy set up (apt-get install squid3 on Ubuntu 10.04), and I added a refresh_pattern to force the pages to cache: refresh_pattern ^http://www.khronos.org/opengles/sdk/1\.1/docs/man/ … 1440 20% 10080 … override-expire ignore-reload ignore-no-cache ignore-private ignore-no-store This is all on one line, of course. While this appears to work for the XHTML documents (e.g., glBindTexture), it fails to cache the linked content, such as the DTD, some .ent files (?) and some XSL files. The delay in fetching these extra files delays rendering of the main document, so my principal annoyance isn't fixed. The only difference I can glean with these ancillary files is that they come with an Expires: header set to the current time, whereas the XHTML document has none. But I would have expected the override-expire option to fix this. I have confirmed that documents have the same base URL. I have also truncated the pattern to varying degrees, with no effect. My questions Why does the override-expire option not seem to work? Is there a simple way to tell squid to unconditionally cache a document, no matter what it finds in the response headers? (Hopefully) relevant output cache.log Jan 01 10:33:30 1970/06/25 21:18:27| Processing Configuration File: /etc/squid3/squid.conf (depth 0) Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'override-expire' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-reload' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-no-cache' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-no-store' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-private' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| DNS Socket created at 0.0.0.0, port 37082, FD 10 Jan 01 10:33:30 1970/06/25 21:18:27| Adding nameserver 192.168.1.1 from /etc/resolv.conf Jan 01 10:33:30 1970/06/25 21:18:27| Accepting HTTP connections at 0.0.0.0, port 3128, FD 11. Jan 01 10:33:30 1970/06/25 21:18:27| Accepting ICP messages at 0.0.0.0, port 3130, FD 13. Jan 01 10:33:30 1970/06/25 21:18:27| HTCP Disabled. Jan 01 10:33:30 1970/06/25 21:18:27| Loaded Icons. Jan 01 10:33:30 1970/06/25 21:18:27| Ready to serve requests. access.log Jun 25 21:19:35 2010.710 0 192.168.1.50 TCP_MEM_HIT/200 2452 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/glBindTexture.xml - NONE/- text/xml Jun 25 21:19:36 2010.263 543 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml1-transitional.dtd - DIRECT/74.54.224.215 - Jun 25 21:19:36 2010.276 556 192.168.1.50 TCP_MISS/304 370 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/mathml.xsl - DIRECT/74.54.224.215 - Jun 25 21:19:36 2010.666 278 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-lat1.ent - DIRECT/74.54.224.215 - Jun 25 21:19:36 2010.958 279 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-symbol.ent - DIRECT/74.54.224.215 - Jun 25 21:19:37 2010.251 276 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-special.ent - DIRECT/74.54.224.215 - Jun 25 21:19:37 2010.332 0 192.168.1.50 TCP_IMS_HIT/304 316 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/ctop.xsl - NONE/- text/xml Jun 25 21:19:37 2010.332 0 192.168.1.50 TCP_IMS_HIT/304 316 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/pmathml.xsl - NONE/- text/xml store.log Jun 25 21:19:36 2010.263 RELEASE -1 FFFFFFFF D3056C09B42659631A65A08F97794E45 304 1277464776 -1 1277464776 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml1-transitional.dtd Jun 25 21:19:36 2010.276 RELEASE -1 FFFFFFFF 9BF7F37442FD84DD0AC0479E38329E3C 304 1277464776 -1 1277464776 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/mathml.xsl Jun 25 21:19:36 2010.666 RELEASE -1 FFFFFFFF 7BCFCE88EC91578C8E2589CB6310B3A1 304 1277464776 -1 1277464776 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-lat1.ent Jun 25 21:19:36 2010.958 RELEASE -1 FFFFFFFF ECF1B24E437CFAA08A2785AA31A042A0 304 1277464777 -1 1277464777 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-symbol.ent Jun 25 21:19:37 2010.251 RELEASE -1 FFFFFFFF 36FE3D76C80F0106E6E9F3B7DCE924FA 304 1277464777 -1 1277464777 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-special.ent Jun 25 21:19:37 2010.332 RELEASE -1 FFFFFFFF A33E5A5CCA2BFA059C0FA25163485192 304 1277462871 1221139523 1277462871 text/xml -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/ctop.xsl Jun 25 21:19:37 2010.332 RELEASE -1 FFFFFFFF E2CF8854443275755915346052ACE14E 304 1277462872 1221139523 1277462872 text/xml -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/pmathml.xsl

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