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  • SQL Server 2008 Optimization

    - by hgulyan
    I've learned today, if you append to your query OPTION (MAXDOP 0) your query will run on multiple processors and if it's huge query, query will perform faster. I know general guidelines on query optimizations (using indexes, selecting only needed fields etc.), my question is about SQL Server optimization. Maybe changing some options in configurations or anything else. What guidelines are there for SQL Server Optimization? Thank you.

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  • What are some good code optimization methods?

    - by esac
    I would like to understand good code optimization methods and methodology. How do I keep from doing premature optimization if I am thinking about performance already. How do I find the bottlenecks in my code? How do I make sure that over time my program does not become any slower? What are some common performance errors to avoid (e.g.; I know it is bad in some languages to return while inside the catch portion of a try{} catch{} block

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  • Snow Leopard: Optimization

    - by Shyam
    Hi, I have bunch of questions: I have a Mac network, which has five Mac's. Right now, they are individually getting software updates. Is there a way to download the patches/security updates in a single place (repository) and point all machines to this location? Personally, I have tools like Monolingual and Onyx, but are there tools you could recommend that affect the performance of the Operating System positively? Tweaks would be nice. Links and pointers, would be really appreciated. I've read about Time machine, is there a way to backup all machines to a network drive using this tool? Thanks!

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  • Bacula optimization/profiling tools

    - by pufferfish
    I'm trying to get an idea of where the bottlenecks are in our backup system. Are there tools available for profiling this? If not, any pointers to a home grown method would also help. I guess most of the info would be in the bacula logs, but I'd also like to see things like what gets saturated during despooling: disk, CPU or network? This feels like a problem most bacula admins would have encountered.

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  • my.ini optimization on Windows 2008 R2 VPS

    - by MKphpDev
    I have a vmware VPS running Windows Server 2008 R2 Enterprise that has performance issues with MySQL. Every few minutes, MySQL stall for few seconds then responed to queries. I'm sure that my.ini need to be optimized, but unfortunately, I don't have any idea of my.ini configuration. What's running on the server: 2 small wordpress blogs, 1 vbulletin forums (approx. 1.2 GB database, and increasing), small database for some sort of plug-ins (no more than 4000 records) Server Info: Processor: Intel Xeon X5550 @ 2.67GHz, RAM: 6 GB (memory useage never exceeded 2 GB), MySQL 5.5, PHP 5.3.10, IIS 7 current my.ini: [mysqld] default-storage-engine=INNODB sql-mode="STRICT_TRANS_TABLES,NO_AUTO_CREATE _USER,NO_ENGINE_SUBSTITUTION" max_connections=250 myisam_max_sort_file_size=20G innodb_additional_mem_pool_size=256M innodb_flush_log_at_trx_commit=1 innodb_log_buffer_size=8M innodb_buffer_pool_size=512MB innodb_log_file_size=128M innodb_thread_concurrency=10 key_buffer_size = 512M myisam_sort_buffer_size = 8M join_buffer_size = 256K read_buffer_size = 256K sort_buffer_size = 256K table_cache = 4000 thread_cache_size = 200 wait_timeout = 30 connect_timeout = 10 tmp_table_size = 32M max_allowed_packet = 1M max_connect_errors = 10000 query_cache_size = 16M query_cache_limit = 2M query_cache_type = 1 query_cache_min_res_unit = 1024 query_prealloc_size = 16384 query_alloc_block_size = 16384 skip-external-locking read_rnd_buffer_size=1M max_heap_table_size=16M thread_concurrency=8 [mysqld_safe] open_files_limit = 8192 [mysqldump] quick max_allowed_packet = 16M [myisamchk] key_buffer_size = 128M sort_buffer_size = 128M read_buffer = 2M write_buffer = 2M any help with that, please?

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  • Is premature optimization really the root of all evil?

    - by Craig Day
    A colleague of mine today committed a class called ThreadLocalFormat, which basically moved instances of Java Format classes into a thread local, since they are not thread safe and "relatively expensive" to create. I wrote a quick test and calculated that I could create 200,000 instances a second, asked him was he creating that many, to which he answered "nowhere near that many". He's a great programmer and everyone on the team is highly skilled so we have no problem understanding the resulting code, but it was clearly a case of optimizing where there is no real need. He backed the code out at my request. What do you think? Is this a case of "premature optimization" and how bad is it really?

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  • Compiler optimization causing the performance to slow down

    - by aJ
    I have one strange problem. I have following piece of code: template<clss index, class policy> inline int CBase<index,policy>::func(const A& test_in, int* srcPtr ,int* dstPtr) { int width = test_in.width(); int height = test_in.height(); double d = 0.0; //here is the problem for(int y = 0; y < height; y++) { //Pointer initializations //multiplication involving y //ex: int z = someBigNumber*y + someOtherBigNumber; for(int x = 0; x < width; x++) { //multiplication involving x //ex: int z = someBigNumber*x + someOtherBigNumber; if(soemCondition) { // floating point calculations } *dstPtr++ = array[*srcPtr++]; } } } The inner loop gets executed nearly 200,000 times and the entire function takes 100 ms for completion. ( profiled using AQTimer) I found an unused variable double d = 0.0; outside the outer loop and removed the same. After this change, suddenly the method is taking 500ms for the same number of executions. ( 5 times slower). This behavior is reproducible in different machines with different processor types. (Core2, dualcore processors). I am using VC6 compiler with optimization level O2. Follwing are the other compiler options used : -MD -O2 -Z7 -GR -GX -G5 -X -GF -EHa I suspected compiler optimizations and removed the compiler optimization /O2. After that function became normal and it is taking 100ms as old code. Could anyone throw some light on this strange behavior? Why compiler optimization should slow down performance when I remove unused variable ? Note: The assembly code (before and after the change) looked same.

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  • Database Optimization techniques for amateurs.

    - by Zombies
    Can we get a list of basic optimization techniques going (anything from modeling to querying, creating indexes, views to query optimization). It would be nice to have a list of these, one technique per answer. As a hobbyist I would find this to be very useful, thanks. And for the sake of not being too vague, let's say we are using a maintstream DB such as MySQL or Oracle, and that the DB will contain 500,000-1m or so records across ~10 tables, some with foreign key contraints, all using the most typical storage engines (eg: InnoDB for MySQL). And of course, the basics such as PKs are defined as well as FK contraints.

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  • WebSphere Application Server EJB Optimization

    - by Chris Aldrich
    We are working on developing a Java EE based application. Our application is Java 1.5 compatible and will be deployed to WAS ND 6.1.0.21 with EBJ 3.0 and Web Services feature packs. The configuration is currently one cell with two clusters. Each cluster will have two nodes. Our application, or our system, as I should rather say, comes in two or three parts. Part 1: An ear deployed to one cluster that contains 3rd party vendor code combined with customization code. Their code is EJB 2.0 compliant and has a lot of Remote Home interfaces. Part 2: An ear deployed to the same cluster as the first ear. This ear contains EBJ 3's that make calls into the EJB 2's supplied by the vendor and the custom code. These EJB 3's are used by the JSF UI also packaged with the EAR, and some of them are also exposed as web services (JAX-WS 2.0 with SOAP 1.2 compliance) for other clients. Part 3: There may be other services that do not depend on our vendor/custom code app. These services will be EJB 3.0's and web services that are deployed to the other cluster. Per a recommendation from some IBM staff on site here, communication between nodes in a cluster can be EJB RMI. But if we are going across clusters and/or other cells, then the communication should be web services. That said, some of us are wondering about performance and optimizing communication for speed of our applications that will use our web services and EJB's. Right now most EJB's are exposed as remote. (and our vendor set theirs up that way, rather than also exposing local home interfaces). We are wondering if WAS does any optimizations between apps in the same node/cluster node space. If two apps are installed in the same area and they call each other via remote home interface, is WAS smart enough to make it a local home interface call? Are their other optimization techniques? Should we consider them? Should we not? What are the costs/benefits? Here is the question from one of our team members as sent in their email: The question is: Supposing we develop our EJBs as remote EJBs, where our UI controller code is talking to our EXT java services via EJB3...what are our options for performance optimization when both the EJB server and client are running in the same container? As one point of reference, google has given me some oooooold websphere performance tuning documentation from 2000 that explains a tuning configuration you can set to enable Call By Reference for EJB communication when they're in the same application server JVM. It states the following: Because EJBs are inherently location independent, they use a remote programming model. Method parameters and return values are serialized over RMI-IIOP and returned by value. This is the intrinsic RMI "Call By Value" model. WebSphere provides the "No Local Copies" performance optimization for running EJBs and clients (typically servlets) in the same application server JVM. The "No Local Copies" option uses "Call By Reference" and does not create local proxies for called objects when both the client and the remote object are in the same process. Depending on your workload, this can result in a significant overhead savings. Configure "No Local Copies" by adding the following two command line parameters to the application server JVM: * -Djavax.rmi.CORBA.UtilClass=com.ibm.CORBA.iiop.Util * -Dcom.ibm.CORBA.iiop.noLocalCopies=true CAUTION: The "No Local Copies" configuration option improves performance by changing "Call By Value" to "Call By Reference" for clients and EJBs in the same JVM. One side effect of this is that the Java object derived (non-primitive) method parameters can actually be changed by the called enterprise bean. Consider Figure 16a: Also, we will also be using Process Server 6.2 and WESB 6.2 as well in the future. Any ideas? recommendations? Thanks

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  • Effective optimization strategies on modern C++ compilers

    - by user168715
    I'm working on scientific code that is very performance-critical. An initial version of the code has been written and tested, and now, with profiler in hand, it's time to start shaving cycles from the hot spots. It's well-known that some optimizations, e.g. loop unrolling, are handled these days much more effectively by the compiler than by a programmer meddling by hand. Which techniques are still worthwhile? Obviously, I'll run everything I try through a profiler, but if there's conventional wisdom as to what tends to work and what doesn't, it would save me significant time. I know that optimization is very compiler- and architecture- dependent. I'm using Intel's C++ compiler targeting the Core 2 Duo, but I'm also interested in what works well for gcc, or for "any modern compiler." Here are some concrete ideas I'm considering: Is there any benefit to replacing STL containers/algorithms with hand-rolled ones? In particular, my program includes a very large priority queue (currently a std::priority_queue) whose manipulation is taking a lot of total time. Is this something worth looking into, or is the STL implementation already likely the fastest possible? Along similar lines, for std::vectors whose needed sizes are unknown but have a reasonably small upper bound, is it profitable to replace them with statically-allocated arrays? I've found that dynamic memory allocation is often a severe bottleneck, and that eliminating it can lead to significant speedups. As a consequence I'm interesting in the performance tradeoffs of returning large temporary data structures by value vs. returning by pointer vs. passing the result in by reference. Is there a way to reliably determine whether or not the compiler will use RVO for a given method (assuming the caller doesn't need to modify the result, of course)? How cache-aware do compilers tend to be? For example, is it worth looking into reordering nested loops? Given the scientific nature of the program, floating-point numbers are used everywhere. A significant bottleneck in my code used to be conversions from floating point to integers: the compiler would emit code to save the current rounding mode, change it, perform the conversion, then restore the old rounding mode --- even though nothing in the program ever changed the rounding mode! Disabling this behavior significantly sped up my code. Are there any similar floating-point-related gotchas I should be aware of? One consequence of C++ being compiled and linked separately is that the compiler is unable to do what would seem to be very simple optimizations, such as move method calls like strlen() out of the termination conditions of loop. Are there any optimization like this one that I should look out for because they can't be done by the compiler and must be done by hand? On the flip side, are there any techniques I should avoid because they are likely to interfere with the compiler's ability to automatically optimize code? Lastly, to nip certain kinds of answers in the bud: I understand that optimization has a cost in terms of complexity, reliability, and maintainability. For this particular application, increased performance is worth these costs. I understand that the best optimizations are often to improve the high-level algorithms, and this has already been done.

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  • How to document and teach others "optimized beyond recognition" computationally intensive code?

    - by rwong
    Occasionally there is the 1% of code that is computationally intensive enough that needs the heaviest kind of low-level optimization. Examples are video processing, image processing, and all kinds of signal processing, in general. The goals are to document, and to teach the optimization techniques, so that the code does not become unmaintainable and prone to removal by newer developers. (*) (*) Notwithstanding the possibility that the particular optimization is completely useless in some unforeseeable future CPUs, such that the code will be deleted anyway. Considering that software offerings (commercial or open-source) retain their competitive advantage by having the fastest code and making use of the newest CPU architecture, software writers often need to tweak their code to make it run faster while getting the same output for a certain task, whlist tolerating a small amount of rounding errors. Typically, a software writer can keep many versions of a function as a documentation of each optimization / algorithm rewrite that takes place. How does one make these versions available for others to study their optimization techniques?

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  • Issues in Convergence of Sequential minimal optimization for SVM

    - by Amol Joshi
    I have been working on Support Vector Machine for about 2 months now. I have coded SVM myself and for the optimization problem of SVM, I have used Sequential Minimal Optimization(SMO) by Mr. John Platt. Right now I am in the phase where I am going to grid search to find optimal C value for my dataset. ( Please find details of my project application and dataset details here http://stackoverflow.com/questions/2284059/svm-classification-minimum-number-of-input-sets-for-each-class) I have successfully checked my custom implemented SVM`s accuracy for C values ranging from 2^0 to 2^6. But now I am having some issues regarding the convergence of the SMO for C 128. Like I have tried to find the alpha values for C=128 and it is taking long time before it actually converges and successfully gives alpha values. Time taken for the SMO to converge is about 5 hours for C=100. This huge I think ( because SMO is supposed to be fast. ) though I`m getting good accuracy? I am screwed right not because I can not test the accuracy for higher values of C. I am actually displaying number of alphas changed in every pass of SMO and getting 10, 13, 8... alphas changing continuously. The KKT conditions assures convergence so what is so weird happening here? Please note that my implementation is working fine for C<=100 with good accuracy though the execution time is long. Please give me inputs on this issue. Thank You and Cheers.

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  • Am I understanding premature optimization correctly?

    - by Ed Mazur
    I've been struggling with an application I'm writing and I think I'm beginning to see that my problem is premature optimization. The perfectionist side of me wants to make everything optimal and perfect the first time through, but I'm finding this is complicating the design quite a bit. Instead of writing small, testable functions that do one simple thing well, I'm leaning towards cramming in as much functionality as possible in order to be more efficient. For example, I'm avoiding multiple trips to the database for the same piece of information at the cost of my code becoming more complex. One part of me wants to just not worry about redundant database calls. It would make it easier to write correct code and the amount of data being fetched is small anyway. The other part of me feels very dirty and unclean doing this. :-) I'm leaning towards just going to the database multiple times, which I think is the right move here. It's more important that I finish the project and I feel like I'm getting hung up because of optimizations like this. My question is: is this the right strategy to be using when avoiding premature optimization?

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  • ASP.NET Web Optimization - confusion about loading order

    - by Ciel
    Using the ASP.NET Web Optimization Framework, I am attempting to load some javascript files up. It works fine, except I am running into a peculiar situation with either the loading order, the loading speed, or its execution. I cannot figure out which. Basically, I am using ace code editor for javascript, and I also want to include its autocompletion package. This requires two files. /ace.js /ext-language_tools.js This isn't an issue, if I load both of these files the normal way (with <script> tags) it works fine. But when I try to use the web optimization bundles, it seems as if something goes wrong. Trying this out... bundles.Add(new ScriptBundle("~/bundles/js") { .Include("~/js/ace.js") .Include("~/js/ext-language_tools.js") }); and then in the view .. @Scripts.Render("~/bundles/js") I get the error ace is not defined This means that the ace.js file hasn't run, or hasn't loaded. Because if I break it apart into two bundles, it starts working. bundles.Add(new ScriptBundle("~/bundles/js") { .Include("~/js/ace.js") }); bundles.Add(new ScriptBundle("~/bundles/js/language_tools") { .Include("~/js/ext-language_tools.js") }); Can anyone explain why this would behave in this fashion?

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  • Memory optimization while downloading

    - by lboregard
    hello all i have the following piece of code, that im looking forward to optimize, since i'm consuming gobs of memory this routine is heavily used first optimization would be to move the stringbuilder construction out of the download routine and make it a field of the class, then i would clear it inside the routine can you please suggest any other optimization or point me in the direction of some resources that could help me with this (web articles, books, etc). i'm thinking about replacing the stringbuilder by a fixed (much larger) size buffer ... or perhaps create a larger sized stringbuilder thanks in advance. StreamWriter _writer; StreamReader _reader; public string Download(string msgId) { _writer.WriteLine("BODY <" + msgId + ">"); string response = _reader.ReadLine(); if (!response.StartsWith("222")) return null; bool done = false; StringBuilder body = new StringBuilder(256* 1024); do { response = _reader.ReadLine(); if (OnProgress != null) OnProgress(response.Length); if (response == ".") { done = true; } else { if (response.StartsWith("..")) response = response.Remove(0, 1); body.Append(response); body.Append("\r\n"); } } while (!done); return body.ToString(); }

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  • optimization math computation (multiplication and summing)

    - by wiso
    Suppose you want to compute the sum of the square of the differences of items: $\sum_{i=1}^{N-1} (x_i - x_{i+1})^2$, the simplest code (the input is std::vector<double> xs, the ouput sum2) is: double sum2 = 0.; double prev = xs[0]; for (vector::const_iterator i = xs.begin() + 1; i != xs.end(); ++i) { sum2 += (prev - (*i)) * (prev - (*i)); // only 1 - with compiler optimization prev = (*i); } I hope that the compiler do the optimization in the comment above. If N is the length of xs you have N-1 multiplications and 2N-3 sums (sums means + or -). Now suppose you know this variable: sum = $x_1^2 + x_N^2 + 2 sum_{i=2}^{N-1} x_i^2$ Expanding the binomial square: $sum_i^{N-1} (x_i-x_{i+1})^2 = sum - 2\sum_{i=1}^{N-1} x_i x_{i+1}$ so the code becomes: double sum2 = 0.; double prev = xs[0]; for (vector::const_iterator i = xs.begin() + 1; i != xs.end(); ++i) { sum2 += (*i) * prev; prev = (*i); } sum2 = -sum2 * 2. + sum; Here I have N multiplications and N-1 additions. In my case N is about 100. Well, compiling with g++ -O2 I got no speed up (I try calling the inlined function 2M times), why?

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  • Search Engine Optimization Tutorial

    A search engine optimization tutorial is nothing but a manual that educates you on how to go about the processes of search engine optimization. Though it sounds complicated, search engine optimization is not so difficult to carry out and with proper training you can do it too.

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  • 10 SEO Optimization Tips You Would Pay Money to Know

    "SEO", also known as search engine optimization is one of the many ways to build traffic to your website. While many internet marketers believe the best way to build massive traffic is to focus your efforts on one type of traffic generation method, whether PPC, SEO Optimization or viral traffic, it is always good to tap into other sources of traffic. This article will give you 10 SEO optimization tips that you can start implementing in your websites or blogs immediately.

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  • Search Engine Optimization Techniques - Just Try and See

    Using these outstanding search engine optimization techniques will really get you the high search engine ranking you want so bad. I would like to introduce you to the hottest search engine optimization tools that are available for the optimization of your online business. It is not important if is expensive, or cheap, or even if is free, and by the way all of them are FREE; is the fact that it is really effective and that has to be correctly used what matter most.

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  • Search Engine Optimization - The Best Way to Market Your Online Based Business

    There are many things to consider, when you start your own online marketing campaign via search engine optimization services. If you're an entrepreneur, you won't have time for all this, meaning you would need to hire someone to do all the work related to the optimization and the functioning of the website. The lucky fact is that most of the companies, which offer search engine optimization (SEO) services, also provide web design, content writing, web development, social bookmarking, and other related services.

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  • Google Optimization - Your Key For Online Success

    The online market is a highly attractive and lucrative one, in case you need to succeed on the internet there are a lot of different avenues however the one that stands way above all other options is Google. Website business owners can make the most of their online ventures with Google Optimization. A form of SEO or search engine optimization that primarily concentrates on the world's most popular search engine, Google optimization can offer a lot of benefits to your business.

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  • Search Engine Optimization Strategies 101

    I have learned over the last ten years of internet experience that Search Engine Optimization (SEO) can be an elusive and often overcharged service by "SEO experts." So in this article I will lay out in a simple, step by step fashion how to do search engine optimization that will get your website noticed in the search engine general results. Here are some fundamental search engine optimization strategies to get you started.

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