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  • Windows Azure Evolution – Caching (Preview)

    - by Shaun
    Caching is a popular topic when we are building a high performance and high scalable system not only on top of the cloud platform but the on-premise environment as well. On March 2011 the Windows Azure AppFabric Caching had been production launched. It provides an in-memory, distributed caching service over the cloud. And now, in this June 2012 update, the cache team announce a grand new caching solution on Windows Azure, which is called Windows Azure Caching (Preview). And the original Windows Azure AppFabric Caching was renamed to Windows Azure Shared Caching.   What’s Caching (Preview) If you had been using the Shared Caching you should know that it is constructed by a bunch of cache servers. And when you want to use you should firstly create a cache account from the developer portal and specify the size you want to use, which means how much memory you can use to store your data that wanted to be cached. Then you can add, get and remove them through your code through the cache URL. The Shared Caching is a multi-tenancy system which host all cached items across all users. So you don’t know which server your data was located. This caching mode works well and can take most of the cases. But it has some problems. The first one is the performance. Since the Shared Caching is a multi-tenancy system, which means all cache operations should go through the Shared Caching gateway and then routed to the server which have the data your are looking for. Even though there are some caches in the Shared Caching system it also takes time from your cloud services to the cache service. Secondary, the Shared Caching service works as a block box to the developer. The only thing we know is my cache endpoint, and that’s all. Someone may satisfied since they don’t want to care about anything underlying. But if you need to know more and want more control that’s impossible in the Shared Caching. The last problem would be the price and cost-efficiency. You pay the bill based on how much cache you requested per month. But when we host a web role or worker role, it seldom consumes all of the memory and CPU in the virtual machine (service instance). If using Shared Caching we have to pay for the cache service while waste of some of our memory and CPU locally. Since the issues above Microsoft offered a new caching mode over to us, which is the Caching (Preview). Instead of having a separated cache service, the Caching (Preview) leverage the memory and CPU in our cloud services (web role and worker role) as the cache clusters. Hence the Caching (Preview) runs on the virtual machines which hosted or near our cloud applications. Without any gateway and routing, since it located in the same data center and same racks, it provides really high performance than the Shared Caching. The Caching (Preview) works side-by-side to our application, initialized and worked as a Windows Service running in the virtual machines invoked by the startup tasks from our roles, we could get more information and control to them. And since the Caching (Preview) utilizes the memory and CPU from our existing cloud services, so it’s free. What we need to pay is the original computing price. And the resource on each machines could be used more efficiently.   Enable Caching (Preview) It’s very simple to enable the Caching (Preview) in a cloud service. Let’s create a new windows azure cloud project from Visual Studio and added an ASP.NET Web Role. Then open the role setting and select the Caching page. This is where we enable and configure the Caching (Preview) on a role. To enable the Caching (Preview) just open the “Enable Caching (Preview Release)” check box. And then we need to specify which mode of the caching clusters we want to use. There are two kinds of caching mode, co-located and dedicate. The co-located mode means we use the memory in the instances we run our cloud services (web role or worker role). By using this mode we must specify how many percentage of the memory will be used as the cache. The default value is 30%. So make sure it will not affect the role business execution. The dedicate mode will use all memory in the virtual machine as the cache. In fact it will reserve some for operation system, azure hosting etc.. But it will try to use as much as the available memory to be the cache. As you can see, the Caching (Preview) was defined based on roles, which means all instances of this role will apply the same setting and play as a whole cache pool, and you can consume it by specifying the name of the role, which I will demonstrate later. And in a windows azure project we can have more than one role have the Caching (Preview) enabled. Then we will have more caches. For example, let’s say I have a web role and worker role. The web role I specified 30% co-located caching and the worker role I specified dedicated caching. If I have 3 instances of my web role and 2 instances of my worker role, then I will have two caches. As the figure above, cache 1 was contributed by three web role instances while cache 2 was contributed by 2 worker role instances. Then we can add items into cache 1 and retrieve it from web role code and worker role code. But the items stored in cache 1 cannot be retrieved from cache 2 since they are isolated. Back to our Visual Studio we specify 30% of co-located cache and use the local storage emulator to store the cache cluster runtime status. Then at the bottom we can specify the named caches. Now we just use the default one. Now we had enabled the Caching (Preview) in our web role settings. Next, let’s have a look on how to consume our cache.   Consume Caching (Preview) The Caching (Preview) can only be consumed by the roles in the same cloud services. As I mentioned earlier, a cache contributed by web role can be connected from a worker role if they are in the same cloud service. But you cannot consume a Caching (Preview) from other cloud services. This is different from the Shared Caching. The Shared Caching is opened to all services if it has the connection URL and authentication token. To consume the Caching (Preview) we need to add some references into our project as well as some configuration in the Web.config. NuGet makes our life easy. Right click on our web role project and select “Manage NuGet packages”, and then search the package named “WindowsAzure.Caching”. In the package list install the “Windows Azure Caching Preview”. It will download all necessary references from the NuGet repository and update our Web.config as well. Open the Web.config of our web role and find the “dataCacheClients” node. Under this node we can specify the cache clients we are going to use. For each cache client it will use the role name to identity and find the cache. Since we only have this web role with the Caching (Preview) enabled so I pasted the current role name in the configuration. Then, in the default page I will add some code to show how to use the cache. I will have a textbox on the page where user can input his or her name, then press a button to generate the email address for him/her. And in backend code I will check if this name had been added in cache. If yes I will return the email back immediately. Otherwise, I will sleep the tread for 2 seconds to simulate the latency, then add it into cache and return back to the page. 1: protected void btnGenerate_Click(object sender, EventArgs e) 2: { 3: // check if name is specified 4: var name = txtName.Text; 5: if (string.IsNullOrWhiteSpace(name)) 6: { 7: lblResult.Text = "Error. Please specify name."; 8: return; 9: } 10:  11: bool cached; 12: var sw = new Stopwatch(); 13: sw.Start(); 14:  15: // create the cache factory and cache 16: var factory = new DataCacheFactory(); 17: var cache = factory.GetDefaultCache(); 18:  19: // check if the name specified is in cache 20: var email = cache.Get(name) as string; 21: if (email != null) 22: { 23: cached = true; 24: sw.Stop(); 25: } 26: else 27: { 28: cached = false; 29: // simulate the letancy 30: Thread.Sleep(2000); 31: email = string.Format("{0}@igt.com", name); 32: // add to cache 33: cache.Add(name, email); 34: } 35:  36: sw.Stop(); 37: lblResult.Text = string.Format( 38: "Cached = {0}. Duration: {1}s. {2} => {3}", 39: cached, sw.Elapsed.TotalSeconds.ToString("0.00"), name, email); 40: } The Caching (Preview) can be used on the local emulator so we just F5. The first time I entered my name it will take about 2 seconds to get the email back to me since it was not in the cache. But if we re-enter my name it will be back at once from the cache. Since the Caching (Preview) is distributed across all instances of the role, so we can scaling-out it by scaling-out our web role. Just use 2 instances and tweak some code to show the current instance ID in the page, and have another try. Then we can see the cache can be retrieved even though it was added by another instance.   Consume Caching (Preview) Across Roles As I mentioned, the Caching (Preview) can be consumed by all other roles within the same cloud service. For example, let’s add another web role in our cloud solution and add the same code in its default page. In the Web.config we add the cache client to one enabled in the last role, by specifying its role name here. Then we start the solution locally and go to web role 1, specify the name and let it generate the email to us. Since there’s no cache for this name so it will take about 2 seconds but will save the email into cache. And then we go to web role 2 and specify the same name. Then you can see it retrieve the email saved by the web role 1 and returned back very quickly. Finally then we can upload our application to Windows Azure and test again. Make sure you had changed the cache cluster status storage account to the real azure account.   More Awesome Features As a in-memory distributed caching solution, the Caching (Preview) has some fancy features I would like to highlight here. The first one is the high availability support. This is the first time I have heard that a distributed cache support high availability. In the distributed cache world if a cache cluster was failed, the data it stored will be lost. This behavior was introduced by Memcached and is followed by almost all distributed cache productions. But Caching (Preview) provides high availability, which means you can specify if the named cache will be backup automatically. If yes then the data belongs to this named cache will be replicated on another role instance of this role. Then if one of the instance was failed the data can be retrieved from its backup instance. To enable the backup just open the Caching page in Visual Studio. In the named cache you want to enable backup, change the Backup Copies value from 0 to 1. The value of Backup Copies only for 0 and 1. “0” means no backup and no high availability while “1” means enabled high availability with backup the data into another instance. But by using the high availability feature there are something we need to make sure. Firstly the high availability does NOT means the data in cache will never be lost for any kind of failure. For example, if we have a role with cache enabled that has 10 instances, and 9 of them was failed, then most of the cached data will be lost since the primary and backup instance may failed together. But normally is will not be happened since MS guarantees that it will use the instance in the different fault domain for backup cache. Another one is that, enabling the backup means you store two copies of your data. For example if you think 100MB memory is OK for cache, but you need at least 200MB if you enabled backup. Besides the high availability, the Caching (Preview) support more features introduced in Windows Server AppFabric Caching than the Windows Azure Shared Caching. It supports local cache with notification. It also support absolute and slide window expiration types as well. And the Caching (Preview) also support the Memcached protocol as well. This means if you have an application based on Memcached, you can use Caching (Preview) without any code changes. What you need to do is to change the configuration of how you connect to the cache. Similar as the Windows Azure Shared Caching, MS also offers the out-of-box ASP.NET session provider and output cache provide on top of the Caching (Preview).   Summary Caching is very important component when we building a cloud-based application. In the June 2012 update MS provides a new cache solution named Caching (Preview). Different from the existing Windows Azure Shared Caching, Caching (Preview) runs the cache cluster within the role instances we have deployed to the cloud. It gives more control, more performance and more cost-effect. So now we have two caching solutions in Windows Azure, the Shared Caching and Caching (Preview). If you need a central cache service which can be used by many cloud services and web sites, then you have to use the Shared Caching. But if you only need a fast, near distributed cache, then you’d better use Caching (Preview).   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Data caching in ASP.Net applications

    - by nikolaosk
    In this post I will continue my series of posts on caching. You can read my other post in Output caching here .You can read on how to cache a page depending on the user's browser language. Output caching has its place as a caching mechanism. But right now I will focus on data caching .The advantages of data caching are well known but I will highlight the main points. We have improvements in response times We have reduced database round trips We have different levels of caching and it is up to us...(read more)

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  • Caching in the .NET Stack: Inside-Out

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/06/28/caching-in-the-.net-stack-inside-out.aspxI'm delighted to have my first course published on Pluralsight - Caching in the .NET Stack: Inside-out.   It's a pretty comprehensive look at caching in .NET solutions. The first half covers using local, remote and persistent cache stores inside the solution, including the .NET MemoryCache, NCache Express, AppFabric Caching, memcached, Azure Table Storage and local disk stores. The second half covers caching outside the solution in HTTP clients and proxies, and how to set up ASP.NET WebForms, MVC, Web API and WCF projects to use HTTP validation and expiration caching.   The course takes a hands-on approach, starting with a distributed solution that has no caching, analysing key points which can benefit from caching, and adding different types of cache. At the end of the course I run through a set of before and after performance tests, stressing the solution under load. Without caching and with 60 concurrent users the page response time maxes out at 18 seconds - with caching that falls to 2 seconds, so it's a huge improvement from very little effort. I’d be glad to hear feedback if you watch the course, especially if it’s as positive as my editor’s.

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  • Sixeyed.Caching available now on NuGet and GitHub!

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/22/sixeyed.caching-available-now-on-nuget-and-github.aspxThe good guys at Pluralsight have okayed me to publish my caching framework (as seen in Caching in the .NET Stack: Inside-Out) as an open-source library, and it’s out now. You can get it here: Sixeyed.Caching source code on GitHub, and here: Sixeyed.Caching package v1.0.0 on NuGet. If you haven’t seen the course, there’s a preview here on YouTube: In-Process and Out-of-Process Caches, which gives a good flavour. The library is a wrapper around various cache providers, including the .NET MemoryCache, AppFabric cache, and  memcached*. All the wrappers inherit from a base class which gives you a set of common functionality against all the cache implementations: •    inherits OutputCacheProvider, so you can use your chosen cache provider as an ASP.NET output cache; •    serialization and encryption, so you can configure whether you want your cache items serialized (XML, JSON or binary) and encrypted; •    instrumentation, you can optionally use performance counters to monitor cache attempts and hits, at a low level. The framework wraps up different caches into an ICache interface, and it lets you use a provider directly like this: Cache.Memory.Get<RefData>(refDataKey); - or with configuration to use the default cache provider: Cache.Default.Get<RefData>(refDataKey); The library uses Unity’s interception framework to implement AOP caching, which you can use by flagging methods with the [Cache] attribute: [Cache] public RefData GetItem(string refDataKey) - and you can be more specific on the required cache behaviour: [Cache(CacheType=CacheType.Memory, Days=1] public RefData GetItem(string refDataKey) - or really specific: [Cache(CacheType=CacheType.Disk, SerializationFormat=SerializationFormat.Json, Hours=2, Minutes=59)] public RefData GetItem(string refDataKey) Provided you get instances of classes with cacheable methods from the container, the attributed method results will be cached, and repeated calls will be fetched from the cache. You can also set a bunch of cache defaults in application config, like whether to use encryption and instrumentation, and whether the cache system is enabled at all: <sixeyed.caching enabled="true"> <performanceCounters instrumentCacheTotalCounts="true" instrumentCacheTargetCounts="true" categoryNamePrefix ="Sixeyed.Caching.Tests"/> <encryption enabled="true" key="1234567890abcdef1234567890abcdef" iv="1234567890abcdef"/> <!-- key must be 32 characters, IV must be 16 characters--> </sixeyed.caching> For AOP and methods flagged with the cache attribute, you can override the compile-time cache settings at runtime with more config (keyed by the class and method name): <sixeyed.caching enabled="true"> <targets> <target keyPrefix="MethodLevelCachingStub.GetRandomIntCacheConfiguredInternal" enabled="false"/> <target keyPrefix="MethodLevelCachingStub.GetRandomIntCacheExpiresConfiguredInternal" seconds="1"/> </targets> It’s released under the MIT license, so you can use it freely in your own apps and modify as required. I’ll be adding more content to the GitHub wiki, which will be the main source of documentation, but for now there’s an FAQ to get you started. * - in the course the framework library also wraps NCache Express, but there's no public redistributable library that I can find, so it's not in Sixeyed.Caching.

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  • Idea to develop a caching server between IIS and SQL Server

    - by John
    I work on a few high traffic websites that all share the same database and that are all heavily database driven. Our SQL server is max-ed out and, although we have already implemented many changes that have helped but the server is still working too hard. We employ some caching in our website but the type of queries we use negate using SQL dependency caching. We tried SQL replication to try and kind of load balance but that didn't prove very successful because the replication process is quite demanding on the servers too and it needed to be done frequently as it is important that data is up to date. We do use a Varnish web caching server (Linux based) to take a bit of the load off both the web and database server but as a lot of the sites are customised based on the user we can only do so much. Anyway, the reason for this question... Varnish gave me an idea for a possible application that might help in this situation. Just like Varnish sits between a web browser and the web server and caches response from the web server, I was wondering about the possibility of creating something that sits between the web server and the database server. Imagine that all SQL queries go through this SQL caching server. If it's a first time query then it will get recorded, and the result requested from the SQL server and stored locally on the cache server. If it's a repeat request within a set time then the result gets retrieved from the local copy without the query being sent to the SQL server. The caching server could also take advantage of SQL dependency caching notifications. This seems like a good idea in theory. There's still the same amount of data moving back and forward from the web server, but the SQL server is relieved of the work of processing the repeat queries. I wonder about how difficult it would be to build a service that sort of emulates requests and responses from SQL server, whether SQL server's own caching is doing enough of this already that this wouldn't be a benefit, or even if someone has done this before and I haven't found it? I would welcome any feedback or any references to any relevant projects.

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  • System.Web.Caching vs. Enterprise Library Caching Block

    - by ESV
    For a .NET component that will be used in both web applications and rich client applications, there seem to be two obvious options for caching: System.Web.Caching or the Ent. Lib. Caching Block. What do you use? Why? System.Web.Caching Is this safe to use outside of web apps? I've seen mixed information, but I think the answer is maybe-kind-of-not-really. a KB article warning against 1.0 and 1.1 non web app use The 2.0 page has a comment that indicates it's OK: http://msdn.microsoft.com/en-us/library/system.web.caching.cache(VS.80).aspx Scott Hanselman is creeped out by the notion The 3.5 page includes a warning against such use Rob Howard encouraged use outside of web apps I don't expect to use one of its highlights, SqlCacheDependency, but the addition of CacheItemUpdateCallback in .NET 3.5 seems like a Really Good Thing. Enterprise Library Caching Application Block other blocks are already in use so the dependency already exists cache persistence isn't necessary; regenerating the cache on restart is OK Some cache items should always be available, but be refreshed periodically. For these items, getting a callback after an item has been removed is not very convenient. It looks like a client will have to just sleep and poll until the cache item is repopulated. Memcached for Win32 + .NET client What are the pros and cons when you don't need a distributed cache?

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  • SQL SERVER – Faster SQL Server Databases and Applications – Power and Control with SafePeak Caching Options

    - by Pinal Dave
    Update: This blog post is written based on the SafePeak, which is available for free download. Today, I’d like to examine more closely one of my preferred technologies for accelerating SQL Server databases, SafePeak. Safepeak’s software provides a variety of advanced data caching options, techniques and tools to accelerate the performance and scalability of SQL Server databases and applications. I’d like to look more closely at some of these options, as some of these capabilities could help you address lagging database and performance on your systems. To better understand the available options, it is best to start by understanding the difference between the usual “Basic Caching” vs. SafePeak’s “Dynamic Caching”. Basic Caching Basic Caching (or the stale and static cache) is an ability to put the results from a query into cache for a certain period of time. It is based on TTL, or Time-to-live, and is designed to stay in cache no matter what happens to the data. For example, although the actual data can be modified due to DML commands (update/insert/delete), the cache will still hold the same obsolete query data. Meaning that with the Basic Caching is really static / stale cache.  As you can tell, this approach has its limitations. Dynamic Caching Dynamic Caching (or the non-stale cache) is an ability to put the results from a query into cache while maintaining the cache transaction awareness looking for possible data modifications. The modifications can come as a result of: DML commands (update/insert/delete), indirect modifications due to triggers on other tables, executions of stored procedures with internal DML commands complex cases of stored procedures with multiple levels of internal stored procedures logic. When data modification commands arrive, the caching system identifies the related cache items and evicts them from cache immediately. In the dynamic caching option the TTL setting still exists, although its importance is reduced, since the main factor for cache invalidation (or cache eviction) become the actual data updates commands. Now that we have a basic understanding of the differences between “basic” and “dynamic” caching, let’s dive in deeper. SafePeak: A comprehensive and versatile caching platform SafePeak comes with a wide range of caching options. Some of SafePeak’s caching options are automated, while others require manual configuration. Together they provide a complete solution for IT and Data managers to reach excellent performance acceleration and application scalability for  a wide range of business cases and applications. Automated caching of SQL Queries: Fully/semi-automated caching of all “read” SQL queries, containing any types of data, including Blobs, XMLs, Texts as well as all other standard data types. SafePeak automatically analyzes the incoming queries, categorizes them into SQL Patterns, identifying directly and indirectly accessed tables, views, functions and stored procedures; Automated caching of Stored Procedures: Fully or semi-automated caching of all read” stored procedures, including procedures with complex sub-procedure logic as well as procedures with complex dynamic SQL code. All procedures are analyzed in advance by SafePeak’s  Metadata-Learning process, their SQL schemas are parsed – resulting with a full understanding of the underlying code, objects dependencies (tables, views, functions, sub-procedures) enabling automated or semi-automated (manually review and activate by a mouse-click) cache activation, with full understanding of the transaction logic for cache real-time invalidation; Transaction aware cache: Automated cache awareness for SQL transactions (SQL and in-procs); Dynamic SQL Caching: Procedures with dynamic SQL are pre-parsed, enabling easy cache configuration, eliminating SQL Server load for parsing time and delivering high response time value even in most complicated use-cases; Fully Automated Caching: SQL Patterns (including SQL queries and stored procedures) that are categorized by SafePeak as “read and deterministic” are automatically activated for caching; Semi-Automated Caching: SQL Patterns categorized as “Read and Non deterministic” are patterns of SQL queries and stored procedures that contain reference to non-deterministic functions, like getdate(). Such SQL Patterns are reviewed by the SafePeak administrator and in usually most of them are activated manually for caching (point and click activation); Fully Dynamic Caching: Automated detection of all dependent tables in each SQL Pattern, with automated real-time eviction of the relevant cache items in the event of “write” commands (a DML or a stored procedure) to one of relevant tables. A default setting; Semi Dynamic Caching: A manual cache configuration option enabling reducing the sensitivity of specific SQL Patterns to “write” commands to certain tables/views. An optimization technique relevant for cases when the query data is either known to be static (like archive order details), or when the application sensitivity to fresh data is not critical and can be stale for short period of time (gaining better performance and reduced load); Scheduled Cache Eviction: A manual cache configuration option enabling scheduling SQL Pattern cache eviction based on certain time(s) during a day. A very useful optimization technique when (for example) certain SQL Patterns can be cached but are time sensitive. Example: “select customers that today is their birthday”, an SQL with getdate() function, which can and should be cached, but the data stays relevant only until 00:00 (midnight); Parsing Exceptions Management: Stored procedures that were not fully parsed by SafePeak (due to too complex dynamic SQL or unfamiliar syntax), are signed as “Dynamic Objects” with highest transaction safety settings (such as: Full global cache eviction, DDL Check = lock cache and check for schema changes, and more). The SafePeak solution points the user to the Dynamic Objects that are important for cache effectiveness, provides easy configuration interface, allowing you to improve cache hits and reduce cache global evictions. Usually this is the first configuration in a deployment; Overriding Settings of Stored Procedures: Override the settings of stored procedures (or other object types) for cache optimization. For example, in case a stored procedure SP1 has an “insert” into table T1, it will not be allowed to be cached. However, it is possible that T1 is just a “logging or instrumentation” table left by developers. By overriding the settings a user can allow caching of the problematic stored procedure; Advanced Cache Warm-Up: Creating an XML-based list of queries and stored procedure (with lists of parameters) for periodically automated pre-fetching and caching. An advanced tool allowing you to handle more rare but very performance sensitive queries pre-fetch them into cache allowing high performance for users’ data access; Configuration Driven by Deep SQL Analytics: All SQL queries are continuously logged and analyzed, providing users with deep SQL Analytics and Performance Monitoring. Reduce troubleshooting from days to minutes with database objects and SQL Patterns heat-map. The performance driven configuration helps you to focus on the most important settings that bring you the highest performance gains. Use of SafePeak SQL Analytics allows continuous performance monitoring and analysis, easy identification of bottlenecks of both real-time and historical data; Cloud Ready: Available for instant deployment on Amazon Web Services (AWS). As you can see, there are many options to configure SafePeak’s SQL Server database and application acceleration caching technology to best fit a lot of situations. If you’re not familiar with their technology, they offer free-trial software you can download that comes with a free “help session” to help get you started. You can access the free trial here. Also, SafePeak is available to use on Amazon Cloud. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Scientific evidence that supports using long variable names instead of abbreviations?

    - by Sebastian Dietz
    Is there any scientific evidence that the human brain can read and understand fully written variable names better/faster than abbreviated ones? Like PersistenceManager persistenceManager; in contrast to PersistenceManager pm; I have the impression that I get a better grasp of code that does not use abbreviations, even if the abbreviations would have been commonly used throughout the codebase. Can this individual feeling be backed up by any studies?

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  • Best practices for caching search queries

    - by David Esteves
    I am trying to improve performance of my ASP.net Web Api by adding a data cache but I am not sure how exactly to go about it as it seems to be more complex than most caching scenarios. An example is I have a table of Locations and an api to retrieve locations via search, for an autocomplete. /api/location/Londo and the query would be something like SELECT * FROM Locations WHERE Name like 'Londo%' These locations change very infrequently so I would like to cache them to prevent trips to the database for no real reason and improve the response time. Looking at caching options I am using the Windows Azure Appfabric system, the problem is it's just a key/value cache. Since I can only retrieve items based on keys I couldn't actually use it for this scenario as far as Im aware. Is what I am trying to do bad use of a caching system? Should I try looking into NoSql DB which could possibly run as a cache for something like this to improve performance? Should I just cache the entire table/collection in a single key with a specific data structure which could assist with the searching and then do the search upon retrieval of the data?

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  • Caching strategies for entities and collections

    - by Rob West
    We currently have an application framework in which we automatically cache both entities and collections of entities at the business layer (using .NET cache). So the method GetWidget(int id) checks the cache using a key GetWidget_Id_{0} before hitting the database, and the method GetWidgetsByStatusId(int statusId) checks the cache using GetWidgets_Collections_ByStatusId_{0}. If the objects are not in the cache they are retrieved from the database and added to the cache. This approach is obviously quick for read scenarios, and as a blanket approach is quick for us to implement, but requires large numbers of cache keys to be purged when CRUD operations are carried out on entities. Obviously as additional methods are added this impacts performance and the benefits of caching diminish. I'm interested in alternative approaches to handling caching of collections. I know that NHibernate caches a list of the identifiers in the collection rather than the actual entities. Is this an approach other people have tried - what are the pros and cons? In particular I am looking for options that optimise performance and can be implemented automatically through boilerplate generated code (we have our own code generation tool). I know some people will say that caching needs to be done by hand each time to meet the needs of the specific situation but I am looking for something that will get us most of the way automatically.

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  • Where is a good place to start to learn about custom caching in .Net

    - by John
    I'm looking to make some performance enhancements to our site, but I'm not sure exactly where to begin. We have some custom object caching, but I think that we can do better. Our Business We aggregate news stories on a news type of web site. We get approximately 500-1000 new stories per week. We have index pages that show various lists of the items and details pages that show the individual stories. Our Current Use case: Getting an Individual Story User makes a request The Data Access Layer(DAL) checks to see if the item is in cache and if item is fresh (15 minutes). If the item is not in cache or is not fresh, retrieve the item from SQL Server, save to cache and return to user. Problems with this approach The pull nature of caching means that users have to pay the waiting cost every time that the cache is refreshed. Once a story is published, it changes infrequently and I think that we should replace the pull model with something better. My initial thoughts My initial thought is that stories should ALL be stored locally in some type of dictionary. (Cache or is there another, better way?). If the story is not found, then make a trip to the database, update the local dictionary and send the item back. Since there may be occasional updates to stories, this should be an entirely process from the user. I watched a video by Brent Ozar, How StackOverflow Scales SQL Server, in which Brent states "the fastest database query is the one that you don't make". Where do I start? At this point, I don't know exactly what the solution is. Is it caching? Is there a better way of using local storage? Do I use a Dictionary, OrderedDictionary, List ? It seems daunting and I'm just looking for some good starting points to learn more about how to do this type of optimization.

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  • Caching strategies - LRU, MRU, Clock-Pro

    - by golgofa
    I am going to write a bachelor's science work on caching strategies and really, can't find any links to specifications or full descriptions of some of them. Only something like summaries from wikipedia. Please, help with some links on LRU, MRU caching and new-one - Clock Pro. Thanks a lot. All links are very useful for me. The purpose of work - is to compare different cache strategies to get more effiency. It based on WebApplication with ejb 2.0, so algorithm's will be implemented there, espesially in ejbLoad() and ejbFindByPrimarKey(). Also, one of aspects of this application - it will use not common scheme of tables in database - it based on metamodel. So, if you had any experience on this topic, i would be grateful to take some of your knowledge)

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  • Enabling Http caching and compression in IIS 7 for asp.net websites

    - by anil.kasalanati
    Caching – There are 2 ways to set Http caching 1-      Use Max age property 2-      Expires header. Doing the changes via IIS Console – 1.       Select the website for which you want to enable caching and then select Http Responses in the features tab       2.       Select the Expires webcontent and on changing the After setting you can generate the max age property for the cache control    3.       Following is the screenshot of the headers   Then you can use some tool like fiddler and see 302 response coming from the server. Doing it web.config way – We can add static content section in the system.webserver section <system.webServer>   <staticContent>             <clientCache cacheControlMode="UseMaxAge" cacheControlMaxAge="365.00:00:00" />   </staticContent> Compression - By default static compression is enabled on IIS 7.0 but the only thing which falls under that category is CSS but this is not enough for most of the websites using lots of javascript.  If you just thought by enabling dynamic compression would fix this then you are wrong so please follow following steps –   In some machines the dynamic compression is not enabled and following are the steps to enable it – Open server manager Roles > Web Server (IIS) Role Services (scroll down) > Add Role Services Add desired role (Web Server > Performance > Dynamic Content Compression) Next, Install, Wait…Done!   ?  Roles > Web Server (IIS) ?  Role Services (scroll down) > Add Role Services     Add desired role (Web Server > Performance > Dynamic Content Compression)     Next, Install, Wait…Done!     Enable  - ?  Open server manager ?  Roles > Web Server (IIS) > Internet Information Services (IIS) Manager   Next pane: Sites > Default Web Site > Your Web Site Main pane: IIS > Compression         Then comes the custom configuration for encrypting javascript resources. The problem is that the compression in IIS 7 completely works on the mime types and by default there is a mismatch in the mime types Go to following location C:\Windows\System32\inetsrv\config Open applicationHost.config The mimemap is as follows  <mimeMap fileExtension=".js" mimeType="application/javascript" />   So the section in the staticTypes should be changed          <add mimeType="application/javascript" enabled="true" />     Doing the web.config way –   We can add following section in the system.webserver section <system.webServer> <urlCompression doDynamicCompression="false"  doStaticCompression="true"/> More Information/References – ·         http://weblogs.asp.net/owscott/archive/2009/02/22/iis-7-compression-good-bad-how-much.aspx ·         http://www.west-wind.com/weblog/posts/98538.aspx  

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  • Disable eclipselink caching and query caching - not working?

    - by James
    I am using eclipselink JPA with a database which is also being updated externally to my application. For that reason there are tables I want to query every few seconds. I can't get this to work even when I try to disable the cache and query cache. For example: EntityManagerFactory entityManagerFactory = Persistence.createEntityManagerFactory("default"); EntityManager em = entityManagerFactory.createEntityManager(); MyLocation one = em.createNamedQuery("MyLocation.findMyLoc").getResultList().get(0); Thread.sleep(10000); MyLocation two = em.createNamedQuery("MyLocation.findMyLoc").getResultList().get(0); System.out.println(one.getCapacity() + " - " + two.getCapacity()); Even though the capacity changes while my application is sleeping the println always prints the same value for one and two. I have added the following to the persistence.xml <property name="eclipselink.cache.shared.default" value="false"/> <property name="eclipselink.query-results-cache" value="false"/> I must be missing something but am running out of ideas. James

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  • ASP:NET :Problem in DoNut Caching

    - by Shyju
    I have an ASP.NET page where i am trying to do some output caching.But ran into a problem. My ASPX page has <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="Default.aspx.cs" Inherits="MYProject._Default" %> <%@ OutputCache Duration="600" VaryByParam="None" %> <%@ Register TagPrefix="MYProjectUC" TagName="PageHeader" Src="~/Lib/UserControls/PageHeader.ascx" %> <%@ Register TagPrefix="MYProjectUC" TagName="PageFooter" Src="~/Lib/UserControls/PageFooter.ascx" %> and i have used the User control called "PageHeader" in the aspx page. In PageHeader.ascx, i have an asp.net substitution control, where i want to show some links based on the logged in user. <%@ Control Language="C#" AutoEventWireup="true" CodeBehind="PageHeader.ascx.cs" Inherits="MyProject.Lib.UserControls.PageHeader1" %> <div class="headerRow"> <div class="headerLogo"> <a href="Default.aspx"><img src="Lib/Images/header.gif" alt=""></a> </div> <div id="divHeaderMenu" runat="server"> <asp:Substitution ID="subLinks" runat="server" MethodName="GetUserProfileHeaderLinks" /> </div> </div><!--headerRow--> In my ascx.cs file,i have a static method which will return a string based on whether the used logged in or not using session public static string GetUserProfileHeaderLinks(HttpContext context) { string strHeaderLinks = string.Empty; // check session and return string return strHeaderLinks; } But Still the page shows the same content for both logged in user and Guest user. My objective is to to have the Page being cached except the content inside the substitution control. Any idea how to achieve this ? Thanks in advance

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  • Class scope variable vs method scope variable

    - by Masud
    I know that variable scope is enclosed by a start of block { and an end of block }. If the same variable is declared within the block, then the compile error Variable already defined occurs. But take a look at following example. public class Test{ int x=0;// Class scope variable public void m(){ int x=9; //redeclaration of x is valid within the scope of same x. if(true){ int x=7; // but this redeclaration generates a compile time error. } } Here, x can be redeclared in a method, although it's already declared in the class. But in the if block, x can't be redeclared. Why is it that redeclaration of a class scope variable doesn't generate an error, but a method scope variable redeclaration generates an error?

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  • Caching large amount of ajax returned objects

    - by ofcapl
    I'm building an application which fetches large amount of items with ajax requests via other application API. It returns me 6k - 30k js objects which are used multiple times across various application views (sorting, filtering etc.). I would like to avoid querying API every time for such big list so I decided to cache this data somehow. I was thinking about various solutions: saving it to localstorage, using some caching library (e.g. locachejs), storing in js var. I'm not an expert so I would like to hear Your suggestions about each (or one of these) solution, about its pros and cons. Every help will be very appreciated.

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  • Syncing objects to a remote server, and caching on local storage

    - by Harry
    What's the best method of sycing objects (as JSON) to a remote server, with local caching? I have some objects that will pretty much just be plain-text with some extra meta-data. I was thinking of perhaps including a "last modified date" for both Local storage and Remote storage. This could then be used to determine which object is the most recent. For example, even though objects will be saved to both local and remote when they are saved, sometimes the user may not have internet access, or the server may be down, or any other number of things. In this case, the last modified date for remote storage would be reverted to its previous date. Local storage would remain as it is. At this point, the user could exit the application, and when they reload the application would then look at the last modified dates of the local and remote storages, and decide. Is there anything I'm missing with this? Is there a better method that I could use?

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  • Memcached and Rails Fragment Caching Issue

    - by Michael Waxman
    When I have 2 views that fragment cache the same query BUT display them differently, there is only one fragment and they both display it the same way. Is there any way around this? For example... #views/posts/list - cache(@posts) do - for p in @posts = p.title #views/posts/list_with_images - cache(@posts) do - for p in @posts = p.title = p.content = image_tag(p.image_url) #controllers/posts_controller def list ... @posts = Post.all end def list_with_images ... @posts = Post.all end

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  • IE7 not Caching CSS Image over SSL

    - by Alex
    Hello, I'm using the WebDevHelper toolbar for Internet Explorer to troubleshoot HTTP requests/roundtrips on my SSL site and noticed that IE re-downloads my CSS :hover images every time they are triggered. This causes a huge amount of roundtrips. How can I prevent this from happening? Edit: All static content is served with cache-control: public, so images, javascript etc. are cached in Firefox and Chrome. This problem is IE specific.

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  • Rails page caching and flash messages

    - by KJF
    I'm pretty sure I can page cache the vast majority of my site but the one thing preventing me from doing so is that my flash messages will not show, or they'll show at the wrong time. One thing I'm considering is writing the flash message to a cookie, reading it and displaying it via javascript and clearing the cookie once the message has been displayed. Has anyone had any success doing this or are there better methods? Thanks.

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  • Extending ASP.NET Output Caching

    One of the most sure-fire ways to improve a web application's performance is to employ caching. Caching takes some expensive operation and stores its results in a quickly accessible location. Since it's inception, ASP.NET has offered two flavors of caching: Output Caching - caches the entire rendered markup of an ASP.NET page or User Control for a specified duration.Data Caching - a API for caching objects. Using the data cache you can write code to add, remove, and retrieve items from the cache.Until recently, the underlying functionality of these two caching mechanisms was fixed - both cached data in the web server's memory. This has its drawbacks. In some cases, developers may want to save output cache content to disk. When using the data cache you may want to cache items to the cloud or to a distributed caching architecture like memcached. The good news is that with ASP.NET 4 and the .NET Framework 4, the output caching and data caching options are now much more extensible. Both caching features are now based upon the provider model, meaning that you can create your own output cache and data cache providers (or download and use a third-party or open source provider) and plug them into a new or existing ASP.NET 4 application. This article focuses on extending the output caching feature. We'll walk through how to create a custom output cache provider that caches a page or User Control's rendered output to disk (as opposed to memory) and then see how to plug the provider into an ASP.NET application. A complete working example, available in both VB and C#, is available for download at the end of this article. Read on to learn more! Read More >

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  • Extending ASP.NET Output Caching

    One of the most sure-fire ways to improve a web application's performance is to employ caching. Caching takes some expensive operation and stores its results in a quickly accessible location. Since it's inception, ASP.NET has offered two flavors of caching: Output Caching - caches the entire rendered markup of an ASP.NET page or User Control for a specified duration.Data Caching - a API for caching objects. Using the data cache you can write code to add, remove, and retrieve items from the cache.Until recently, the underlying functionality of these two caching mechanisms was fixed - both cached data in the web server's memory. This has its drawbacks. In some cases, developers may want to save output cache content to disk. When using the data cache you may want to cache items to the cloud or to a distributed caching architecture like memcached. The good news is that with ASP.NET 4 and the .NET Framework 4, the output caching and data caching options are now much more extensible. Both caching features are now based upon the provider model, meaning that you can create your own output cache and data cache providers (or download and use a third-party or open source provider) and plug them into a new or existing ASP.NET 4 application. This article focuses on extending the output caching feature. We'll walk through how to create a custom output cache provider that caches a page or User Control's rendered output to disk (as opposed to memory) and then see how to plug the provider into an ASP.NET application. A complete working example, available in both VB and C#, is available for download at the end of this article. Read on to learn more! Read More >Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Caching factory design

    - by max
    I have a factory class XFactory that creates objects of class X. Instances of X are very large, so the main purpose of the factory is to cache them, as transparently to the client code as possible. Objects of class X are immutable, so the following code seems reasonable: # module xfactory.py import x class XFactory: _registry = {} def get_x(self, arg1, arg2, use_cache = True): if use_cache: hash_id = hash((arg1, arg2)) if hash_id in _registry: return _registry[hash_id] obj = x.X(arg1, arg2) _registry[hash_id] = obj return obj # module x.py class X: # ... Is it a good pattern? (I know it's not the actual Factory Pattern.) Is there anything I should change? Now, I find that sometimes I want to cache X objects to disk. I'll use pickle for that purpose, and store as values in the _registry the filenames of the pickled objects instead of references to the objects. Of course, _registry itself would have to be stored persistently (perhaps in a pickle file of its own, in a text file, in a database, or simply by giving pickle files the filenames that contain hash_id). Except now the validity of the cached object depends not only on the parameters passed to get_x(), but also on the version of the code that created these objects. Strictly speaking, even a memory-cached object could become invalid if someone modifies x.py or any of its dependencies, and reloads it while the program is running. So far I ignored this danger since it seems unlikely for my application. But I certainly cannot ignore it when my objects are cached to persistent storage. What can I do? I suppose I could make the hash_id more robust by calculating hash of a tuple that contains arguments arg1 and arg2, as well as the filename and last modified date for x.py and every module and data file that it (recursively) depends on. To help delete cache files that won't ever be useful again, I'd add to the _registry the unhashed representation of the modified dates for each record. But even this solution isn't 100% safe since theoretically someone might load a module dynamically, and I wouldn't know about it from statically analyzing the source code. If I go all out and assume every file in the project is a dependency, the mechanism will still break if some module grabs data from an external website, etc.). In addition, the frequency of changes in x.py and its dependencies is quite high, leading to heavy cache invalidation. Thus, I figured I might as well give up some safety, and only invalidate the cache only when there is an obvious mismatch. This means that class X would have a class-level cache validation identifier that should be changed whenever the developer believes a change happened that should invalidate the cache. (With multiple developers, a separate invalidation identifier is required for each.) This identifier is hashed along with arg1 and arg2 and becomes part of the hash keys stored in _registry. Since developers may forget to update the validation identifier or not realize that they invalidated existing cache, it would seem better to add another validation mechanism: class X can have a method that returns all the known "traits" of X. For instance, if X is a table, I might add the names of all the columns. The hash calculation will include the traits as well. I can write this code, but I am afraid that I'm missing something important; and I'm also wondering if perhaps there's a framework or package that can do all of this stuff already. Ideally, I'd like to combine in-memory and disk-based caching.

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