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  • Applications affected by memory performance

    - by robotron
    I'm writing a paper on the topic of applications affected more by memory performance than processor performance. I've got a lot written regarding the gap between the two, however I can't seem to find anything about the applications that might be affected more by memory performance than by processor speed. I suppose these are applications that make a large amount of memory references, but I have no idea what kind of applications would make such large number of references to make it stand out? Perhaps databases? Can you please give me any pointers on how to proceed, some links to papers? I'm really stuck.

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  • IE error with jquery counter plugin

    - by Mankey
    I've implemented a jquery counter script (count up from say 50 to 100 with different increments) that I found from this question: jQuery counter to count up to a target number The scripts works great except for in Internet Explorer 8 (and possibly other IE versions?). Here's an error message from IE with the URL to the creator of the script's demo. Message: 'undefined' is null or not an object Line: 32 Char: 17 Code: 0 URI: http://www.ulmanen.fi/stuff/counter.php I'm just wondering if anyone know how this can be fixed. I'm guessing it has to do with el.html() not finding any data but I can't really figure this out. Thanks for any help ^^ I would reply to that post if I could but I can't seem to find any way of doing so (I'm new to stackoverflow, I think I lack privileges).

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  • SSAS – Synchronisation performance

    - by ACALVETT
    I’ve always thought of SSAS synchronisation as a clever file mirroring utility built into SSAS and i have never considered the technology as bringing any performance gains to the table. So, its a good job I like to revisit areas…. :) I decided to compare the performance of robocopy and SSAS Synchronisation between 2 Windows 2003 servers running SSAS 2008 SP1 CU7 with 1gb network links. For the robocopy of the data directory i used the SQLCat Robocopy Script . The results are shown below. SSAS Sync...(read more)

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  • Improving performance for web scraping code

    - by Pankaj Upadhyay
    I have a website in which the code scrapes other websites for getting the accurate data. While the code works good but there a decent lag in performance because the code firsts downloads the html stream from various sites(some times 9 websites), extracts the relative part and then renders the html page. What should I do to get an optimal performance. Should I change from shared hosting (godaddy) to my own server or it has nothing to do with my hosting and I need to make changes to my code?

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  • how do you manage application performance reviews

    - by CoolBeans
    I have been trying to figure out ways to effectively do performance reviews before an install happens for all releases done by our team. Do you usually make this a part of code review process or do you handle it as a separate review task? FYI - we do not have a dedicated performance testing team. It is up to the developers to make sure the app performs well. The apps I am referring to are web applications.

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  • Tap into MySQL's Amazing Performance Results with the Performance Tuning Course

    - by Antoinette O'Sullivan
    Want to leverage the high-speed load utilities, distinctive memory caches, full text indexes, and other performance-enhancing mechanisms that MySQL offers to fuel today's critical business systems. The authentic MySQL Performance Tuning course, in 4 days, teaches you to evaluate the MySQL architecture, learn to use the tools, configure the database for performance, tune application and SQL code, tune the server, examine the storage engines, assess the application architecture, and learn general tuning concepts. You can take this course in one the following three ways: Training-on-Demand: Access the streaming video, instructor delivery of this course from your own desk, at your own pace. Book time for hands-on practice when it suits you. Live-Virtual Class: Take this instructor-led class live from your own desk. With 700 events on the schedule you are sure to find a time and date to suit you! In-Class: Travel to a classroom to take this class. A sample of events on the schedule are as follows.  Location  Date  Delivery Language  Hamburg, Germany  22 October 2012  German  Prague, Czech Republic  1 October 2012  Czech  Warsaw, Poland  3 December 2012  Polish  London, England  19 November 2012  English  Rome, Italy  23 October 2012  Italian Lisbon, Portugal  6 November 2012  European Portugese  Aix en Provence, France  4 September 2012   French  Strasbourg, France 16 October 2012   French  Nieuwegein, Netherlands 26 November 2012   Dutch  Madrid, Spain 17 December 2012   Spanish  Mechelen, Belgium  1 October 2012  English  Riga, Latvia  10 December 2012  Latvian  Petaling Jaya, Malaysia  10 September 2012 English   Edmonton, Canada 10 December 2012   English  Vancouver, Canada 10 December 2012   English  Ottawa, Canada 26 November 2012   English  Toronto, Canada 26 November 2012   English  Montreal, Canada 26 November 2012   English  Mexico City, Mexico 10 September 2012   Spanish  Sao Paolo, Brazil 26 November 2012  Brazilian Portugese   Tokyo, Japan 19 November 2012   Japanese  Tokyo, Japan  19 November 2012  Japanese For further information on this class, or to register your interest in additional events, go to the Oracle University Portal: http://oracle.com/education/mysql

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  • Mouse button and keypress counter for Windows XP

    - by Yuval F
    I am trying to kick the habit of using a mouse where I could use keyboard shortcuts, for ergonomic reasons. I believe that if I see some statistics of my use of both input devices, I could reduce my use of mouse clicks. Do you know of any free software I can install on my Windows XP machine that counts keypresses and mouse button presses and displays an hourly/daily report? No fancy GUI is needed - just two summary lines.

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  • Kinect Click counter function

    - by Sweta Dwivedi
    So i have the following kinect click function which will check if the hand is within the bounds then it will click with a counter . . however there is a slight problem . .the first few button clicks work fine.. but after it clicks one of the buttons it changes the game state and immediately clicks the other button without the counter reaching 200. . . Kinect click is a method in the button class. . .and each button inside a list can access the Kinect click method. . . public bool KinectClick(int x,int y) { if ((x >= position.X && x <= position.X + position.Width) && (y >= position.Y && y <= position.Y + position.Height)) { counter++; if (counter > 200) { counter = 0; return true; } } else { counter = 0; } return false; } I call to check if this property is true in the Game update method to act as a button click. . foreach(Button g_t in Game_theme) { if ((g_t.KinectClick(x_c, y_c) == true || g_t.ButtonClicked() == true) && g_t.name == "animoe") { Selected_anim = true; currentGameState = GameState.InGame; } if ((g_t.KinectClick(x_c, y_c) == true || g_t.ButtonClicked() == true) && g_t.name == "planet") { Selected_planet = true; currentGameState = GameState.InGame; }

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  • Graphics performance of 945GME

    - by l0b0
    Edit: Since setting Appearance - Visual Effects up to a stunning "Normal", I now get ~35 FPS in glxgears right after login, with nothing else running :( I'm getting terrible graphics performance in NeverWinter Nights (native with SoU+HotU+CEP2) on my Eee PC 1005HAB. Even with all graphics settings (including the "advanced" ones) at minimum I get about 2-10 FPS, depending on the scene. Firefox is really sluggish as well - Changing tabs often takes a second, scrolling is laggy, and typing this I notice the delay between pressing keys and seeing the text on screen. The rest of the OS is running OK, although general performance seems to be even worse than my old Eee PC 900. glxgears gives about 60 FPS, which is apparently as it should be (synchronized with the monitor refresh rate). Bugs like Launchpad #252094 and the instructions for Reverting the Jaunty Xorg intel driver to 2.4 are old enough that I'm afraid following the instructions would render the system unusable. Are there any tips for improving graphics performance on this system that are still relevant for 10.10? $ uname -a Linux l0b0eee 2.6.35-28-generic #49-Ubuntu SMP Tue Mar 1 14:40:58 UTC 2011 i686 GNU/Linux $ lspci -nn | grep VGA 00:02.0 VGA compatible controller [0300]: Intel Corporation Mobile 945GME Express Integrated Graphics Controller [8086:27ae] (rev 03) $ glxinfo name of display: :0.0 display: :0 screen: 0 direct rendering: Yes server glx vendor string: SGI server glx version string: 1.4 ...

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  • Bad 3D Performance in Ubuntu 12.04

    - by Pandem
    I already posted a question before but I didn't really get any advice/help. I'll be a bit more brief/general in hope it'll help. I have an MSI HD 7850 with the Catalyst 12.4 drivers installed. I've found that I'm having bad 3D performance for some reason but I'm not entirely sure what. I suspect it may just that the graphics card is new and AMD just need to work on their drivers but it would be nice to get advice and narrow the problem down so that I can be sure rather than wait for driver updates that may not even help. I ran gxlgears to give some general idea of how bad the performance is. At default size it is averaging around 2000 FPS. The command glxinfo confirms the renderer is using AMD Radeon HD 7800 Series with OpenGL version 4.2. Edits below: As asked for others: lspci -v output is here. fglrxinfo output is here xvinfo output is here glxinfo | grep rendering says yes for direct rendering. These confirmed that everything was configured correctly. Within Unity and Gnome Classic: glxgears had an FPS of around 2000 FPS fgl_glxgears had an FPS of around 544 FPS Within LDXE: glxgears had an FPS of around 4600 FPS fgl_glxgears had an FPS of around 1600 FPS In the end it was discovered that Compiz was causing a large performance decrease and solution was simply to change window manager for the time being. Thanks to TechZilla for all his help!

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  • Performance analysis strategies

    - by Bernd
    I am assigned to a performance-tuning-debugging-troubleshooting task. Scenario: a multi-application environment running on several networked machines using databases. OS is Unix, DB is Oracle. Business logic is implemented across applications using synchronous/asynchronous communication. Applications are multi-user with several hundred call center users at peak time. User interfaces are web-based. Applications are third party, I can get access to developers and source code. I only have the production system and a functional test environment, no load test environment. Problem: bad performance! I need fast results. Management is going crazy. I got symptom examples like these: user interface actions taking minutes to complete. Seaching for a customer usually takes 6 seconds but an immediate subsequent search with same parameters may take 6 minutes. What would be your strategy for finding root causes?

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  • Practical Performance Monitoring and Tuning Event

    - by Andrew Kelly
      For any of you who may be interested or know of someone in the market for a performance Monitoring and Tuning class I have just the ticket for you. It’s a 3 day event that will be held in Atlanta Ga. on January 25th to the 27th 2011. For those of you that know me or have been to my sessions you realize I like to provide more than just classroom theory and like to teach real world and above all practical methodology when it comes to performance in SQL Server. This class covers all the essentials...(read more)

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  • How to achieve best performance in DirectX 9.0 while rendering on multiple monitors

    - by Vibhore Tanwer
    I am new to DirectX, and trying to learn best practice. Please suggest what are the best practices for rendering on multiple monitors different things at the same time? how can I boost performance of application? I have gone through this article http://msdn.microsoft.com/en-us/library/windows/desktop/bb147263%28v=vs.85%29.aspx . I am making use of some pixel shaders to achieve some effects. At most 4 effect(4 shader effects) can be applied at same time. What are the best practices to achieve best performance with DirectX 9.0. I read somewhere that DirectX 11 provides support for parallel rendering, but I am not able to get any working sample for DirectX 11.0. Please help me with this, Any help would be of great value. Thanks

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  • SQL SERVER – Simple Example of Incremental Statistics – Performance improvements in SQL Server 2014 – Part 2

    - by Pinal Dave
    This is the second part of the series Incremental Statistics. Here is the index of the complete series. What is Incremental Statistics? – Performance improvements in SQL Server 2014 – Part 1 Simple Example of Incremental Statistics – Performance improvements in SQL Server 2014 – Part 2 DMV to Identify Incremental Statistics – Performance improvements in SQL Server 2014 – Part 3 In part 1 we have understood what is incremental statistics and now in this second part we will see a simple example of incremental statistics. This blog post is heavily inspired from my friend Balmukund’s must read blog post. If you have partitioned table and lots of data, this feature can be specifically very useful. Prerequisite Here are two things you must know before you start with the demonstrations. AdventureWorks – For the demonstration purpose I have installed AdventureWorks 2012 as an AdventureWorks 2014 in this demonstration. Partitions – You should know how partition works with databases. Setup Script Here is the setup script for creating Partition Function, Scheme, and the Table. We will populate the table based on the SalesOrderDetails table from AdventureWorks. -- Use Database USE AdventureWorks2014 GO -- Create Partition Function CREATE PARTITION FUNCTION IncrStatFn (INT) AS RANGE LEFT FOR VALUES (44000, 54000, 64000, 74000) GO -- Create Partition Scheme CREATE PARTITION SCHEME IncrStatSch AS PARTITION [IncrStatFn] TO ([PRIMARY], [PRIMARY], [PRIMARY], [PRIMARY], [PRIMARY]) GO -- Create Table Incremental_Statistics CREATE TABLE [IncrStatTab]( [SalesOrderID] [int] NOT NULL, [SalesOrderDetailID] [int] NOT NULL, [CarrierTrackingNumber] [nvarchar](25) NULL, [OrderQty] [smallint] NOT NULL, [ProductID] [int] NOT NULL, [SpecialOfferID] [int] NOT NULL, [UnitPrice] [money] NOT NULL, [UnitPriceDiscount] [money] NOT NULL, [ModifiedDate] [datetime] NOT NULL) ON IncrStatSch(SalesOrderID) GO -- Populate Table INSERT INTO [IncrStatTab]([SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate]) SELECT     [SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate] FROM       [Sales].[SalesOrderDetail] WHERE      SalesOrderID < 54000 GO Check Details Now we will check details in the partition table IncrStatSch. -- Check the partition SELECT * FROM sys.partitions WHERE OBJECT_ID = OBJECT_ID('IncrStatTab') GO You will notice that only a few of the partition are filled up with data and remaining all the partitions are empty. Now we will create statistics on the Table on the column SalesOrderID. However, here we will keep adding one more keyword which is INCREMENTAL = ON. Please note this is the new keyword and feature added in SQL Server 2014. It did not exist in earlier versions. -- Create Statistics CREATE STATISTICS IncrStat ON [IncrStatTab] (SalesOrderID) WITH FULLSCAN, INCREMENTAL = ON GO Now we have successfully created statistics let us check the statistical histogram of the table. Now let us once again populate the table with more data. This time the data are entered into a different partition than earlier populated partition. -- Populate Table INSERT INTO [IncrStatTab]([SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate]) SELECT     [SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate] FROM       [Sales].[SalesOrderDetail] WHERE      SalesOrderID > 54000 GO Let us check the status of the partition once again with following script. -- Check the partition SELECT * FROM sys.partitions WHERE OBJECT_ID = OBJECT_ID('IncrStatTab') GO Statistics Update Now here has the new feature come into action. Previously, if we have to update the statistics, we will have to FULLSCAN the entire table irrespective of which partition got the data. However, in SQL Server 2014 we can just specify which partition we want to update in terms of Statistics. Here is the script for the same. -- Update Statistics Manually UPDATE STATISTICS IncrStatTab (IncrStat) WITH RESAMPLE ON PARTITIONS(3, 4) GO Now let us check the statistics once again. -- Show Statistics DBCC SHOW_STATISTICS('IncrStatTab', IncrStat) WITH HISTOGRAM GO Upon examining statistics histogram, you will notice that now the distribution has changed and there is way more rows in the histogram. Summary The new feature of Incremental Statistics is indeed a boon for the scenario where there are partitions and statistics needs to be updated frequently on the partitions. In earlier version to update statistics one has to do FULLSCAN on the entire table which was wasting too many resources. With the new feature in SQL Server 2014, now only those partitions which are significantly changed can be specified in the script to update statistics. Cleanup You can clean up the database by executing following scripts. -- Clean up DROP TABLE [IncrStatTab] DROP PARTITION SCHEME [IncrStatSch] DROP PARTITION FUNCTION [IncrStatFn] GO 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 Tagged: SQL Statistics, Statistics

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  • SQL SERVER – BI Quiz – Troubleshooting Cube Performance

    - by pinaldave
    My friend Jacob Sebastian runs SQL BI Quiz competition. Where there are 30 different questions on each day of the month. Winners get opportunity to participate in this Quiz, learn something new and win great awards. Working with huge data is very common when it is about Data Warehousing. It is necessary to create Cubes on the data to make it meaningful and consumable. There are cases when retrieving the data from cube takes lots of the time. Let us assume that your cube is returning you data very quickly. Suddenly on one day it is returning the data very slowly. What are the three things will you in order to diagnose this. After diagnose what you will do to resolve performance issue. Participate in my question over here Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Business Intelligence, Pinal Dave, PostADay, Readers Question, SQL, SQL Authority, SQL Performance, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Will JVisualVM degrade application performance?

    - by rocky
    I have doubts in JVisual VM profiler tool related to performance. I have requirement to implement a JVM Monitoring tool for my enterpise java application. I have gone through some profiling tools in market but all them are having some kind of agent file which we need include in server startup. I have a fear that these client agent will degrade my application performance will more. So I have decided to JVisual VM because this profiler tool comes with JDK itself but before implementing JVisualVM, does anybody faces any issues with JVisualVM profiler tool? As well as, is this safe if I implement in application?

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  • Using TPL and PLINQ to raise performance of feed aggregator

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

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  • Programmer performance

    - by RSK
    I am a PHP programmer with 1 year of experience. As I am just starting my career, I am learning a lot of things now. I can say I am a little bit of a perfectionist. When I am assigned a problem I start off by Googling. Then, even when I find a solution, I keep trying for a better one until I find 2-3 options. Then I start learning it and choose the best performing solution. Even though I am learning a lot, this process gets me labeled as a low performer. My questions: As a novice, should I continue to use this learning process and not worry about my performance? Should I focus more on my performance and less on how the code performs?

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  • SQL SERVER – NTFS File System Performance for SQL Server

    - by pinaldave
    Note: Before practicing any of the suggestion of this article, consult your IT Infrastructural Admin, applying the suggestion without proper testing can only damage your system. Question: “Pinal, we have 80 GB of data including all the database files, we have our data in NTFS file system. We have proper backups are set up. Any suggestion for our NTFS file system performance improvement. Our SQL Server box is running only SQL Server and nothing else. Please advise.” When I receive questions which I have just listed above, it often sends me deep thought. Honestly, I know a lot but there are plenty of things, I believe can be built with community knowledge base. Today I need you to help me to complete this list. I will start the list and you help me complete it. NTFS File System Performance Best Practices for SQL Server Disable Indexing on disk volumes Disable generation of 8.3 names (command: FSUTIL BEHAVIOR SET DISABLE8DOT3 1) Disable last file access time tracking (command: FSUTIL BEHAVIOR SET DISABLELASTACCESS 1) Keep some space empty (let us say 15% for reference) on drive is possible (Only on Filestream Data storage volume) Defragement the volume Add your suggestions here… The one which I often get a pretty big debate is NTFS allocation size. I have seen that on the disk volume which stores filestream data, when increased allocation to 64K from 4K, it reduces the fragmentation. Again, I suggest you attempt this after proper testing on your server. Every system is different and the file stored is different. Here is when I would like to request you to share your experience with related to NTFS allocation size. If you do not agree with any of the above suggestions, leave a comment with reference and I will modify it. Please note that above list prepared assuming the SQL Server application is only running on the computer system. The next question does all these still relevant for SSD – I personally have no experience with SSD with large database so I will refrain from comment. 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, Technology

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  • OpenGL Performance Questions

    - by Daniel
    This subject, as with any optimisation problem, gets hit on a lot, but I just couldn't find what I (think) I want. A lot of tutorials, and even SO questions have similar tips; generally covering: Use GL face culling (the OpenGL function, not the scene logic) Only send 1 matrix to the GPU (projectionModelView combination), therefore decreasing the MVP calculations from per vertex to once per model (as it should be). Use interleaved Vertices Minimize as many GL calls as possible, batch where appropriate And possibly a few/many others. I am (for curiosity reasons) rendering 28 million triangles in my application using several vertex buffers. I have tried all the above techniques (to the best of my knowledge), and received almost no performance change. Whilst I am receiving around 40FPS in my implementation, which is by no means problematic, I am still curious as to where these optimisation 'tips' actually come into use? My CPU is idling around 20-50% during rendering, therefore I assume I am GPU bound for increasing performance. Note: I am looking into gDEBugger at the moment Cross posted at StackOverflow

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  • Service and/or tool to monitor performance?

    - by chris
    I am seeing wildly different performance from a clients web site, and would like to set up some sort of monitoring. What I'm looking for is a service that will issue requests to a couple of URLs, and report on the time it took to process the page - TTFB and time to download the entire page - that means I need something that will process javascript & css. Are there services like this? I've seen a few that monitor uptime, but they don't seem to report on the overall page performance.

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  • Ios Game with many animated Nodes,performance issues

    - by user31929
    I'm working in a large map upside-down game(not tiled map),the map i use is a city. I have to insert many node to create the "life of the city",something like people that cross the streets,cars,etc... Some of this characters are involved in physics and game logic but others are only graphic characters. For what i know the only way i can achive this result is to create each character node with or without physic body and animate each character with a texture atlas. In this way i think that i'll have many performance problems, (the characters will be something like 100/150) even if i'll apply all the performance tips that i know... My question is: with large numbers of characters there another programming pattern that i must follow ? What is the approch of game like simcity,simpsons tapped out for ios,etc... that have so many animation at the same time?

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  • Buzzword for "performance-aware" software development

    - by errantlinguist
    There seems to be an overabundance of buzzwords for software development styles and methodologies: Agile development, extreme programming, test-driven development, etc... well, is there any sort of buzzword for "performance-aware" development? By "performance awareness", I don't necessarily mean low-latency or low-level programming, although the former would logically fall under the blanket term I'm looking for. I mean development in which resources are recognised to be finite and so there is a general emphasis on low computational complexity, good resource management, etc. If I was to be snarky, I would say "good programming", but that doesn't seem to get the message across so well...

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  • Performance Tuning and Query Optimisation–SQLBits Training Day

    - by simonsabin
    I will be doing a training day at SQLbits in April on Performance Tuning and Query Optimisation. This is the outline for the day. Its going to be an intense day, I look forward to seeing you there. To register go to http://www. sqlbits .com/information/registration.aspx . Places are limited so make sure you register soon. Outline of the day. Most database performance issues are due to a combination of bad queries, bad database design or poor indexing. All of them are related to each other. In this...(read more)

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  • SQL SERVER – Shrinking Database is Bad – Increases Fragmentation – Reduces Performance

    - by pinaldave
    Earlier, I had written two articles related to Shrinking Database. I wrote about why Shrinking Database is not good. SQL SERVER – SHRINKDATABASE For Every Database in the SQL Server SQL SERVER – What the Business Says Is Not What the Business Wants I received many comments on Why Database Shrinking is bad. Today we will go over a very interesting example that I have created for the same. Here are the quick steps of the example. Create a test database Create two tables and populate with data Check the size of both the tables Size of database is very low Check the Fragmentation of one table Fragmentation will be very low Truncate another table Check the size of the table Check the fragmentation of the one table Fragmentation will be very low SHRINK Database Check the size of the table Check the fragmentation of the one table Fragmentation will be very HIGH REBUILD index on one table Check the size of the table Size of database is very HIGH Check the fragmentation of the one table Fragmentation will be very low Here is the script for the same. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO Let us check the table size and fragmentation. Now let us TRUNCATE the table and check the size and Fragmentation. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can clearly see that after TRUNCATE, the size of the database is not reduced and it is still the same as before TRUNCATE operation. After the Shrinking database operation, we were able to reduce the size of the database. If you notice the fragmentation, it is considerably high. The major problem with the Shrink operation is that it increases fragmentation of the database to very high value. Higher fragmentation reduces the performance of the database as reading from that particular table becomes very expensive. One of the ways to reduce the fragmentation is to rebuild index on the database. Let us rebuild the index and observe fragmentation and database size. -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REBUILD GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can notice that after rebuilding, Fragmentation reduces to a very low value (almost same to original value); however the database size increases way higher than the original. Before rebuilding, the size of the database was 5 MB, and after rebuilding, it is around 20 MB. Regular rebuilding the index is rebuild in the same user database where the index is placed. This usually increases the size of the database. Look at irony of the Shrinking database. One person shrinks the database to gain space (thinking it will help performance), which leads to increase in fragmentation (reducing performance). To reduce the fragmentation, one rebuilds index, which leads to size of the database to increase way more than the original size of the database (before shrinking). Well, by Shrinking, one did not gain what he was looking for usually. Rebuild indexing is not the best suggestion as that will create database grow again. I have always remembered the excellent post from Paul Randal regarding Shrinking the database is bad. I suggest every one to read that for accuracy and interesting conversation. Let us run following script where we Shrink the database and REORGANIZE. -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Shrink the Database DBCC SHRINKDATABASE (ShrinkIsBed); GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REORGANIZE GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can see that REORGANIZE does not increase the size of the database or remove the fragmentation. Again, I no way suggest that REORGANIZE is the solution over here. This is purely observation using demo. Read the blog post of Paul Randal. Following script will clean up the database -- Clean up USE MASTER GO ALTER DATABASE ShrinkIsBed SET SINGLE_USER WITH ROLLBACK IMMEDIATE GO DROP DATABASE ShrinkIsBed GO There are few valid cases of the Shrinking database as well, but that is not covered in this blog post. We will cover that area some other time in future. Additionally, one can rebuild index in the tempdb as well, and we will also talk about the same in future. Brent has written a good summary blog post as well. Are you Shrinking your database? Well, when are you going to stop Shrinking it? Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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