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  • Is there performance to be gained by moving storage allocation local to a member function to its cla

    - by neuviemeporte
    Suppose I have the following C++ class: class Foo { double bar(double sth); }; double Foo::bar(double sth) { double a,b,c,d,e,f a = b = c = d = e = f = 0; /* do stuff with a..f and sth */ } The function bar() will be called millions of times in a loop. Obviously, each time it's called, the variables a..f have to be allocated. Will I gain any performance by making the variables a..f members of the Foo class and just initializing them at the function's point of entry? On the other hand, the values of a..f will be dereferenced through this-, so I'm wondering if it isn't actually a possible performance degradation. Is there any overhead to accessing a value through a pointer? Thanks!

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  • Does it make a difference in performance if I use self.fooBar instead of fooBar?

    - by mystify
    Note: I know exactly what a property is. This question is about performance. Using self.fooBar for READ access seems a waste of time for me. Unnecessary Objective-C messaging is going on. The getters typically simply pass along the ivar, so as long as it's pretty sure there will be no reasonable getter method written, I think it's perfectly fine to bypass this heavy guy. Objective-C messaging is about 20 times slower than direct calls. So if there is some high-performance-high-frequency code with hundreds of properties in use, maybe it does help a lot to avoid unnessessary objective-c messaging? Or am I wasting my time thinking about this?

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  • How do you optimize database performance when providing results for autocomplete/iterative search?

    - by Howiecamp
    Note: In this question I'm using the term "autocomplete" (or "iterative search") to refer to returning search-as-you-type results, e.g. like Google Search gives you. Also my question is not specific to web applications vs. fat client apps. How are SQL SELECT queries normally constructed to provide decent performance for this type of query, especially over arbitrarily large data sets? In the case where the search will only query based on the first n characters (easiest case) am I still issuing a new SELECT result FROM sometable WHERE entry LIKE... on each keypress. Even with various forms of caching this seems like it might result in poor performance. In cases where you want your search string to return results with prefix matches, substring matches, etc. it's an even more difficult problem. Looking at a case of searching a list of contacts, you might return results that match FirstName + LastName, LastName + FirstName, or any other substring.

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  • Why are there performance differences when a SQL function is called from .Net app vs when the same c

    - by Dan Snell
    We are having a problem in our test and dev environments with a function that runs quite slowly at times when called from an .Net Application. When we call this function directly from management studio it works fine. Here are the differences when they are profiled: From the Application: CPU: 906 Reads: 61853 Writes: 0 Duration: 926 From SSMS: CPU: 15 Reads: 11243 Writes: 0 Duration: 31 Now we have determined that when we recompile the function the performance returns to what we are expecting and the performance profile when run from the application matches that of what we get when we run it from SSMS. It will start slowing down again at what appear to random intervals. We have not seen this in prod but they may be in part because everything is recompiled there on a weekly basis. So what might cause this sort of behavior?

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  • How to Audit Database Activity without Performance and Scalability Issues?

    - by GotoError
    I have a need to do auditing all database activity regardless of whether it came from application or someone issuing some sql via other means. So the auditing must be done at the database level. The database in question is Oracle. I looked at doing it via Triggers and also via something called Fine Grained Auditing that Oracle provides. In both cases, we turned on auditing on specific tables and specific columns. However, we found that Performance really sucks when we use either of these methods. Since auditing is an absolute must due to regulations placed around data privacy, I am wondering what is best way to do this without significant performance degradations. If someone has Oracle specific experience with this, it will be helpful but if not just general practices around database activity auditing will be okay as well.

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  • Java - Can i have a faster performance for this loop ?

    - by Brad
    I am reading a book and deleting a number of words from it. My problem is that the process takes long time, and i want to make its performance better(Less time), example : Vector<String> pages = new Vector<String>(); // Contains about 1500 page, each page has about 1000 words. Vector<String> wordsToDelete = new Vector<String>(); // Contains about 50000 words. for( String page: pages ) { String pageInLowCase = page.toLowerCase(); for( String wordToDelete: wordsToDelete ) { if( pageInLowCase.contains( wordToDelete ) ) page = page.replaceAll( "(?i)\\b" + wordToDelete + "\\b" , "" ); } // Do some staff with the final page that does not take much time. } This code takes around 3 minutes to execute. If i skipped the loop of replaceAll(...) i can save more than 2 minutes. So is there a way to do the same loop with a faster performance ?

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  • SQL SERVER – Server Side Paging in SQL Server 2011 – A Better Alternative

    - by pinaldave
    Ranking has improvement considerably from SQL Server 2000 to SQL Server 2005/2008 to SQL Server 2011. Here is the blog article where I wrote about SQL Server 2005/2008 paging method SQL SERVER – 2005 T-SQL Paging Query Technique Comparison (OVER and ROW_NUMBER()) – CTE vs. Derived Table. One can achieve this using OVER clause and ROW_NUMBER() function. Now SQL Server 2011 has come up with the new Syntax for paging. Here is how one can easily achieve it. USE AdventureWorks2008R2 GO DECLARE @RowsPerPage INT = 10, @PageNumber INT = 5 SELECT * FROM Sales.SalesOrderDetail ORDER BY SalesOrderDetailID OFFSET @PageNumber*@RowsPerPage ROWS FETCH NEXT 10 ROWS ONLY GO I consider it good enhancement in terms of T-SQL. I am sure many developers are waiting for this feature for long time. We will consider performance different in future posts. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Tellago is still hiring….

    - by gsusx
    Tellago 's SOA practice is rapidly growing and we are still hiring. In that sense, we are looking to for Connected Systems (WCF, BizTalk, WF) experts who are passionate about building game changing solutions with the latest Microsoft technologies. You will be working alongside technology gurus like DonXml , Pablo Cibraro or Dwight Goins . If you are interested and not afraid of working with a bunch of crazy people ;)please drop me a line at jesus dot rodriguez at tellago dot com. Hope to hear from...(read more)

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  • We are hiring (take a minute to read this, is not another BS talk ;) )

    - by gsusx
    I really wanted to wait until our new website was out to blog about this but I hope you can put up with the ugly website for a few more days J. Tellago keeps growing and, after a quick break at the beginning of the year, we are back in hiring mode J. We are currently expanding our teams in the United States and Argentina and have various positions open in the following categories. .NET developers: If you are an exceptional .NET programmer with a passion for creating great software solutions working...(read more)

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  • ADNOC talks about 50x increase in performance

    - by KLaker
    If you are still wondering about how Exadata can revolutionise your business then I would recommend watching this great video which was recorded at this year's OpenWorld. First a little background...The Abu Dhabi National Oil Company for Distribution (ADNOC) is an integrated energy company that was founded in 1973. ADNOC Distribution markets and distributes petroleum products and services within the United Arab Emirates and internationally. As one of the largest and most innovative government-owned petroleum companies in the Arab Gulf, ADNOC Distribution is renowned and respected for the exceptional quality and reliability of its products and services. Its five corporate divisions include more than 200 filling stations (a number that is growing at 8% annually), more than 150 convenience stores, 10 vehicle inspection stations, as well as wholesale and retail sales of bulk fuel, gas, oil, diesel, and lubricants. ADNOC selected Oracle Exadata Database Machine after extensive research because it provided them with a single platform that can run mixed workloads in a single unified machine: "We chose Oracle Exadata Database Machine because it.offered a fully integrated and highly engineered system that was ready to deploy. With our infrastructure running all the same technology, we can operate any type of Oracle Database without restrictions and be prepared for business growth," said Ali Abdul Aziz Al-Ali, IT division manager, ADNOC Distribution. ".....we could consolidate our transaction processing and business intelligence onto one platform. Competing solutions are just not capable of doing that." - Awad Ahmed Ali El-Sidiq, Senior Database Administrator, ADNOC Distribution In this new video Awad Ahmen Ali El Sidddig, Senior DBA at ADNOC, talks about the impact that Exadata has had on his team and the whole business. ADNOC is using our engineered systems to drive and manage all their workloads: from transaction systems to payments system to data warehouse to BI environment. A true Disk-to-Dashboard revolution using Engineered Systems. This engineered approach is delivering 50x improvement in performance with one queries running 100x faster! The IT has even revolutionised some of their data warehouse related processes with the help of Exadata and now jobs that were taking over 4 hours now run in a few minutes.  To watch the video click on the image below which will take you to our Oracle YouTube page: (if the above link does not work, click here: http://www.youtube.com/watch?v=zcRpxc6u5Ic) Now that queries are running 100x faster and jobs are completing in minutes not hours, what is next for the IT team at ADNOC? Like many of our customers ADNOC is now looking to take advantage of big data to help them better align their business operations with customer behaviour and customer insights. To help deliver this next level of insight the IT team is looking at the new features in Oracle Database 12c such as the new in-memory feature to deliver even more performance gains.  The great news is that Awad Ahmen Ali El Sidddig was awarded DBA of the Year - EMEA within our Data Warehouse Global Leaders programme and you can see the badge for this award pop-up at the start of video. Well done to everyone at ADNOC and thanks for spending the time with us at OOW to create this great video.

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  • Tellago && Tellago Studios 2010

    - by gsusx
    With 2011 around the corner we, at Tellago and Tellago Studios , we have been spending a lot of times evaluating our successes and failures (yes those too ;)) of 2010 and delineating some of our goals and strategies for 2011. When I look at 2010 here are some of the things that quickly jump off the page: Growing Tellago by 300% Launching a brand new company: Tellago Studios Expanding our customer base Establishing our business intelligence practice http://tellago.com/what-we-say/events/business-intelligence...(read more)

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  • JIT compiler for C, C++, and the likes

    - by Ebrahim
    Is there any just-in-time compiler out there for compiled languages, such as C and C++? (The first names that come to mind are Clang and LLVM! But I don't think they currently support it.) Explanation: I think the software could benefit from runtime profiling feedback and aggressively optimized recompilation of hotspots at runtime, even for compiled-to-machine languages like C and C++. Profile-guided optimization does a similar job, but with the difference a JIT would be more flexible in different environments. In PGO you run your binary prior to releasing it. After you released it, it would use no environment/input feedbacks collected at runtime. So if the input pattern is changed, it is probe to performance penalty. But JIT works well even in that conditions. However I think it is controversial wether the JIT compiling performance benefit outweights its own overhead. Edit: Grammar

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  • Enterprise Performance Management: Driving Management Excellence

    Extending operational excellence to management excellence is the new strategic imperative for organizations large and small, all around the world. Management Excellence is a strategy for organizations to differentiate from their competition, by being smarter, more agile and more aligned. Tune into this conversation with John Kopcke, Senior Vice President of Oracle’s Enterprise Performance Management Global Business Unit to learn how leading companies are integrating their management processes and using Oracle’s EPM System to achieve management excellence.

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  • Advanced MySQL Replication - Improving Performance

    MySQL Replication can be made quite reliable and robust if the right tools are used to keep it running smoothly--but what if enormous loads on the primary server are overloading the slave server. Are there ways to speed up performance, so the slave can keep up?

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  • SQL SERVER – DMV – sys.dm_exec_query_optimizer_info – Statistics of Optimizer

    - by pinaldave
    Incredibly, SQL Server has so much information to share with us. Every single day, I am amazed with this SQL Server technology. Sometimes I find several interesting information by just querying few of the DMV. And when I present this info in front of my client during performance tuning consultancy, they are surprised with my findings. Today, I am going to share one of the hidden gems of DMV with you, the one which I frequently use to understand what’s going on under the hood of SQL Server. SQL Server keeps the record of most of the operations of the Query Optimizer. We can learn many interesting details about the optimizer which can be utilized to improve the performance of server. SELECT * FROM sys.dm_exec_query_optimizer_info WHERE counter IN ('optimizations', 'elapsed time','final cost', 'insert stmt','delete stmt','update stmt', 'merge stmt','contains subquery','tables', 'hints','order hint','join hint', 'view reference','remote query','maximum DOP', 'maximum recursion level','indexed views loaded', 'indexed views matched','indexed views used', 'indexed views updated','dynamic cursor request', 'fast forward cursor request') All occurrence values are cumulative and are set to 0 at system restart. All values for value fields are set to NULL at system restart. I have removed a few of the internal counters from the script above, and kept only documented details. Let us check the result of the above query. As you can see, there is so much vital information that is revealed in above query. I can easily say so many things about how many times Optimizer was triggered and what the average time taken by it to optimize my queries was. Additionally, I can also determine how many times update, insert or delete statements were optimized. I was able to quickly figure out that my client was overusing the Query Hints using this dynamic management view. If you have been reading my blog, I am sure you are aware of my series related to SQL Server Views SQL SERVER – The Limitations of the Views – Eleven and more…. With this, I can take a quick look and figure out how many times Views were used in various solutions within the query. Moreover, you can easily know what fraction of the optimizations has been involved in tuning server. For example, the following query would tell me, in total optimizations, what the fraction of time View was “reference“. As this View also includes system Views and DMVs, the number is a bit higher on my machine. SELECT (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'view reference') / (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'optimizations') AS ViewReferencedFraction Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Performance Tuning Tips for Apache

    Apache is one of the most successful open source projects of our times. A big advantage of this popularity is that over the years people have spent a great deal of time fine tuning the software for better performance. Read on to learn more.

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  • I Start!

    - by andyleonard
    I originally titled this post "I Quit!" but decided that doesn't set the proper tone and definitely does not match my feelings about the upcoming transitions in my life. "I Start!" is much more appropriate! Introduction I've tendered my resignation from the position of Manager, ETL Team, Data Management Group, Molina Medicaid Solutions effective Friday 14 Jan 2011. "There I Was..." In 2008 my consultant billable-days - the metric I use to determine how business is going - dropped from 20 / month...(read more)

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  • Windows Azure Use Case: High-Performance Computing (HPC)

    - by BuckWoody
    This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: High-Performance Computing (also called Technical Computing) at its most simplistic is a layout of computer workloads where a “head node” accepts work requests, and parses them out to “worker nodes'”. This is useful in cases such as scientific simulations, drug research, MatLab work and where other large compute loads are required. It’s not the immediate-result type computing many are used to; instead, a “job” or group of work requests is sent to a cluster of computers and the worker nodes work on individual parts of the calculations and return the work to the scheduler or head node for the requestor in a batch-request fashion. This is typical to the way that many mainframe computing use-cases work. You can use commodity-based computers to create an HPC Cluster, such as the Linux application called Beowulf, and Microsoft has a server product for HPC using standard computers, called the Windows Compute Cluster that you can read more about here. The issue with HPC (from any vendor) that some organization have is the amount of compute nodes they need. Having too many results in excess infrastructure, including computers, buildings, storage, heat and so on. Having too few means that the work is slower, and takes longer to return a result to the calling application. Unless there is a consistent level of work requested, predicting the number of nodes is problematic. Implementation: Recently, Microsoft announced an internal partnership between the HPC group (Now called the Technical Computing Group) and Windows Azure. You now have two options for implementing an HPC environment using Windows. You can extend the current infrastructure you have for HPC by adding in Compute Nodes in Windows Azure, using a “Broker Node”.  You can then purchase time for adding machines, and then stop paying for them when the work is completed. This is a common pattern in groups that have a constant need for HPC, but need to “burst” that load count under certain conditions. The second option is to install only a Head Node and a Broker Node onsite, and host all Compute Nodes in Windows Azure. This is often the pattern for organizations that need HPC on a scheduled and periodic basis, such as financial analysis or actuarial table calculations. References: Blog entry on Hybrid HPC with Windows Azure: http://blogs.msdn.com/b/ignitionshowcase/archive/2010/12/13/high-performance-computing-on-premise-and-in-the-windows-azure-cloud.aspx  Links for further research on HPC, includes Windows Azure information: http://blogs.msdn.com/b/ncdevguy/archive/2011/02/16/handy-links-for-hpc-and-azure.aspx 

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  • SQL SERVER – Public Training and Private Training – Differences and Similarities

    - by pinaldave
    Earlier this year, I was on Road SQL Server Seminars. I did many SQL Server Performance Trainings and SQL Server Performance Consultations throughout the year but I feel the most rewarding exercise is always the one when instructor learns something from students, too. I was just talking to my wife, Nupur – she manages my logistics and administration related activities – and she pointed out that this year I have done 62% consultations and 38% trainings. I was bit surprised as I thought the numbers would be reversed. Every time I review the year, I think of training done at organizations. Well, I cannot argue with reality, I have done more consultations (some would call them projects) than training. I told my wife that I enjoy consultations more than training. She promptly asked me a question which was not directly related but made me think for long time, and in the end resulted in this blog post. Nupur asked me: what do I enjoy the most, public training or private training? I had a long conversation with her on this subject. I am not going to write long blog post which can change your life here. This is rather a small post condensing my one hour discussion into 200 words. Public Training is fun because… There are lots of different kinds of attendees There are always vivid questions Lots of questions on questions Less interest in theory and more interest in demos Good opportunity of future business Private Training is fun because… There is a focused interest One question is discussed deeply because of existing company issues More interest in “how it happened” concepts – under the hood operations Good connection with attendees This is also a good opportunity of future business Here I will stop my monologue and I want to open up this question to all of you: Question to Attendees - Which one do you enjoy the most – Public Training or Private Training? Question to Trainers - What do you enjoy the most – Public Training or Private Training? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, SQLAuthority News, T SQL, Technology

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  • World Record Performance on PeopleSoft Enterprise Financials Benchmark on SPARC T4-2

    - by Brian
    Oracle's SPARC T4-2 server achieved World Record performance on Oracle's PeopleSoft Enterprise Financials 9.1 executing 20 Million Journals lines in 8.92 minutes on Oracle Database 11g Release 2 running on Oracle Solaris 11. This is the first result published on this version of the benchmark. The SPARC T4-2 server was able to process 20 million general ledger journal edit and post batch jobs in 8.92 minutes on this benchmark that reflects a large customer environment that utilizes a back-end database of nearly 500 GB. This benchmark demonstrates that the SPARC T4-2 server with PeopleSoft Financials 9.1 can easily process 100 million journal lines in less than 1 hour. The SPARC T4-2 server delivered more than 146 MB/sec of IO throughput with Oracle Database 11g running on Oracle Solaris 11. Performance Landscape Results are presented for PeopleSoft Financials Benchmark 9.1. Results obtained with PeopleSoft Financials Benchmark 9.1 are not comparable to the the previous version of the benchmark, PeopleSoft Financials Benchmark 9.0, due to significant change in data model and supports only batch. PeopleSoft Financials Benchmark, Version 9.1 Solution Under Test Batch (min) SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 8.92 Results from PeopleSoft Financials Benchmark 9.0. PeopleSoft Financials Benchmark, Version 9.0 Solution Under Test Batch (min) Batch with Online (min) SPARC Enterprise M4000 (Web/App) SPARC Enterprise M5000 (DB) 33.09 34.72 SPARC T3-1 (Web/App) SPARC Enterprise M5000 (DB) 35.82 37.01 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 128 GB memory Storage Configuration: 1 x Sun Storage F5100 Flash Array (for database and redo logs) 2 x Sun Storage 2540-M2 arrays and 2 x Sun Storage 2501-M2 arrays (for backup) Software Configuration: Oracle Solaris 11 11/11 SRU 7.5 Oracle Database 11g Release 2 (11.2.0.3) PeopleSoft Financials 9.1 Feature Pack 2 PeopleSoft Supply Chain Management 9.1 Feature Pack 2 PeopleSoft PeopleTools 8.52 latest patch - 8.52.03 Oracle WebLogic Server 10.3.5 Java Platform, Standard Edition Development Kit 6 Update 32 Benchmark Description The PeopleSoft Enterprise Financials 9.1 benchmark emulates a large enterprise that processes and validates a large number of financial journal transactions before posting the journal entry to the ledger. The validation process certifies that the journal entries are accurate, ensuring that ChartFields values are valid, debits and credits equal out, and inter/intra-units are balanced. Once validated, the entries are processed, ensuring that each journal line posts to the correct target ledger, and then changes the journal status to posted. In this benchmark, the Journal Edit & Post is set up to edit and post both Inter-Unit and Regular multi-currency journals. The benchmark processes 20 million journal lines using AppEngine for edits and Cobol for post processes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN PeopleSoft Financial Management oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

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  • Of C# Iterators and Performance

    - by James Michael Hare
    Some of you reading this will be wondering, "what is an iterator" and think I'm locked in the world of C++.  Nope, I'm talking C# iterators.  No, not enumerators, iterators.   So, for those of you who do not know what iterators are in C#, I will explain it in summary, and for those of you who know what iterators are but are curious of the performance impacts, I will explore that as well.   Iterators have been around for a bit now, and there are still a bunch of people who don't know what they are or what they do.  I don't know how many times at work I've had a code review on my code and have someone ask me, "what's that yield word do?"   Basically, this post came to me as I was writing some extension methods to extend IEnumerable<T> -- I'll post some of the fun ones in a later post.  Since I was filtering the resulting list down, I was using the standard C# iterator concept; but that got me wondering: what are the performance implications of using an iterator versus returning a new enumeration?   So, to begin, let's look at a couple of methods.  This is a new (albeit contrived) method called Every(...).  The goal of this method is to access and enumeration and return every nth item in the enumeration (including the first).  So Every(2) would return items 0, 2, 4, 6, etc.   Now, if you wanted to write this in the traditional way, you may come up with something like this:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         List<T> newList = new List<T>();         int count = 0;           foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 newList.Add(i);             }         }           return newList;     }     So basically this method takes any IEnumerable<T> and returns a new IEnumerable<T> that contains every nth item.  Pretty straight forward.   The problem?  Well, Every<T>(...) will construct a list containing every nth item whether or not you care.  What happens if you were searching this result for a certain item and find that item after five tries?  You would have generated the rest of the list for nothing.   Enter iterators.  This C# construct uses the yield keyword to effectively defer evaluation of the next item until it is asked for.  This can be very handy if the evaluation itself is expensive or if there's a fair chance you'll never want to fully evaluate a list.   We see this all the time in Linq, where many expressions are chained together to do complex processing on a list.  This would be very expensive if each of these expressions evaluated their entire possible result set on call.    Let's look at the same example function, this time using an iterator:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         int count = 0;         foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 yield return i;             }         }     }   Notice it does not create a new return value explicitly, the only evidence of a return is the "yield return" statement.  What this means is that when an item is requested from the enumeration, it will enter this method and evaluate until it either hits a yield return (in which case that item is returned) or until it exits the method or hits a yield break (in which case the iteration ends.   Behind the scenes, this is all done with a class that the CLR creates behind the scenes that keeps track of the state of the iteration, so that every time the next item is asked for, it finds that item and then updates the current position so it knows where to start at next time.   It doesn't seem like a big deal, does it?  But keep in mind the key point here: it only returns items as they are requested. Thus if there's a good chance you will only process a portion of the return list and/or if the evaluation of each item is expensive, an iterator may be of benefit.   This is especially true if you intend your methods to be chainable similar to the way Linq methods can be chained.    For example, perhaps you have a List<int> and you want to take every tenth one until you find one greater than 10.  We could write that as:       List<int> someList = new List<int>();         // fill list here         someList.Every(10).TakeWhile(i => i <= 10);     Now is the difference more apparent?  If we use the first form of Every that makes a copy of the list.  It's going to copy the entire list whether we will need those items or not, that can be costly!    With the iterator version, however, it will only take items from the list until it finds one that is > 10, at which point no further items in the list are evaluated.   So, sounds neat eh?  But what's the cost is what you're probably wondering.  So I ran some tests using the two forms of Every above on lists varying from 5 to 500,000 integers and tried various things.    Now, iteration isn't free.  If you are more likely than not to iterate the entire collection every time, iterator has some very slight overhead:   Copy vs Iterator on 100% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 5 Copy 5 5 5 Iterator 5 50 50 Copy 28 50 50 Iterator 27 500 500 Copy 227 500 500 Iterator 247 5000 5000 Copy 2266 5000 5000 Iterator 2444 50,000 50,000 Copy 24,443 50,000 50,000 Iterator 24,719 500,000 500,000 Copy 250,024 500,000 500,000 Iterator 251,521   Notice that when iterating over the entire produced list, the times for the iterator are a little better for smaller lists, then getting just a slight bit worse for larger lists.  In reality, given the number of items and iterations, the result is near negligible, but just to show that iterators come at a price.  However, it should also be noted that the form of Every that returns a copy will have a left-over collection to garbage collect.   However, if we only partially evaluate less and less through the list, the savings start to show and make it well worth the overhead.  Let's look at what happens if you stop looking after 80% of the list:   Copy vs Iterator on 80% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 4 Copy 5 5 4 Iterator 5 50 40 Copy 27 50 40 Iterator 23 500 400 Copy 215 500 400 Iterator 200 5000 4000 Copy 2099 5000 4000 Iterator 1962 50,000 40,000 Copy 22,385 50,000 40,000 Iterator 19,599 500,000 400,000 Copy 236,427 500,000 400,000 Iterator 196,010       Notice that the iterator form is now operating quite a bit faster.  But the savings really add up if you stop on average at 50% (which most searches would typically do):     Copy vs Iterator on 50% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 2 Copy 5 5 2 Iterator 4 50 25 Copy 25 50 25 Iterator 16 500 250 Copy 188 500 250 Iterator 126 5000 2500 Copy 1854 5000 2500 Iterator 1226 50,000 25,000 Copy 19,839 50,000 25,000 Iterator 12,233 500,000 250,000 Copy 208,667 500,000 250,000 Iterator 122,336   Now we see that if we only expect to go on average 50% into the results, we tend to shave off around 40% of the time.  And this is only for one level deep.  If we are using this in a chain of query expressions it only adds to the savings.   So my recommendation?  If you have a resonable expectation that someone may only want to partially consume your enumerable result, I would always tend to favor an iterator.  The cost if they iterate the whole thing does not add much at all -- and if they consume only partially, you reap some really good performance gains.   Next time I'll discuss some of my favorite extensions I've created to make development life a little easier and maintainability a little better.

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  • Google I/O 2012 - Building High Performance Mobile Web Applications

    Google I/O 2012 - Building High Performance Mobile Web Applications Ryan Fioravanti Learn what it takes to build an HTML5 mobile app that will wow your users. This session will focus on speed, offline support, UI layouts, and the tools necessary to set up a productive development environment. Come to this session if you're looking to make a killer mobile web app that stands out amongst the competition. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 33 0 ratings Time: 49:43 More in Science & Technology

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  • DTLoggedExec 1.0 Stable Released!

    - by Davide Mauri
    After serveral years of development I’ve finally released the first non-beta version of DTLoggedExec! I’m now very confident that the product is stable and solid and has all the feature that are important to have (at least for me). DTLoggedExec 1.0 http://dtloggedexec.codeplex.com/releases/view/44689 Here’s the release notes: FIRST NON-BETA RELEASE! :) Code cleaned up Added SetPackageInfo method to ILogProvider interface to make easier future improvements Deprecated the arguments 'ProfileDataFlow', 'ProfilePath', 'ProfileFileName' Added the new argument 'ProfileDataFlowFileName' that replaces the old 'ProfileDataFlow', 'ProfilePath', 'ProfileFileName' arguments Updated database scripts to support new reports Split releases in three different packages for easier maintenance and updates: DTLoggedExec Executable, Samples & Reports Fixed Issue #25738 (http://dtloggedexec.codeplex.com/WorkItem/View.aspx?WorkItemId=25738) Fixed Issue #26479 (http://dtloggedexec.codeplex.com/WorkItem/View.aspx?WorkItemId=26479) To make things easier to maintain I’ve divided the original package in three different releases. One is the DTLoggedExec executable; samples and reports are now available in separate packages so that I can update them more frequently without having to touch the engine. Source code of everything is available through Source Code Control: http://dtloggedexec.codeplex.com/SourceControl/list/changesets As usual, comments and feebacks are more than welcome! (Just use Codeplex, please, so it will be easier for me to keep track of requests and issues) Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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