Search Results

Search found 14282 results on 572 pages for 'performance counter'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 108/572 | < Previous Page | 104 105 106 107 108 109 110 111 112 113 114 115  | Next Page >

  • When to use Vanilla Javascript vs. jQuery?

    - by jondavidjohn
    I have noticed while monitoring/attempting to answer common jQuery questions, that there are certain practices using javascript, instead of jQuery, that actually enable you to write less and do ... well the same amount. And may also yield performance benefits. A specific example $(this) vs this Inside a click event referencing the clicked objects id jQuery $(this).attr("id"); Javascript this.id; Are there any other common practices like this? Where certain Javascript operations could be accomplished easier, without bringing jQuery into the mix. Or is this a rare case? (of a jQuery "shortcut" actually requiring more code) EDIT : While I appreciate the answers regarding jQuery vs. plain javascript performance, I am actually looking for much more quantitative answers. While using jQuery, instances where one would actually be better off (readability/compactness) to use plain javascript instead of using $(). In addition to the example I gave in my original question.

    Read the article

  • SQL Server architecture guidance

    - by Liam
    Hi, We are designing a new version of our existing product on a new schema. Its an internal web application with possibly 100 concurrent users (max)This will run on a SQL Server 2008 database. On of the discussion items recently is whether we should have a single database of split the database for performance reasons across 2 separate databases. The database could grow anywhere from 50-100GB over 5 years. We are Developers and not DBAs so it would be nice to get some general guidance. [I know the answer is not simple as it depends on the schema, archiving policy, amount of data etc. ] Option 1 Single Main Database [This is my preferred option]. The plan would be to have all the tables in a single database and possibly to use file groups and partitioning to separate the data if required across multiple disks. [Use schema if appropriate]. This should deal with the performance concerns One of the comments wrt this was that the a single server instance would still be processing this data so there would still be a processing bottle neck. For reporting we could have a separate reporting DB but this is still being discussed. Option 2 Split the database into 2 separate databases DB1 - Customers, Accounts, Customer resources etc DB2 - This would contain the bulk of the data [i.e. Vehicle tracking data, financial transaction tables etc]. These tables would typically contain a lot of data. [It could reside on a separate server if required] This plan would involve keeping the main data in a smaller database [DB1] and retaining the [mainly] read only transaction type data in a separate DB [DB2]. The UI would mainly read from DB1 and thus be more responsive. [I'm aware that this option makes it harder for Referential Integrity to be enforced.] Points for consideration As we are at the design stage we can at least make proper use of indexes to deal performance issues so thats why option 1 to me is attractive and its more of a standard approach. For both options we are considering implementing an archiving database. Apologies for the long Question. In summary the question is 1 DB or 2? Thanks in advance, Liam

    Read the article

  • Can I use memcpy in C++ to copy classes that have no pointers or virtual functions

    - by Shane MacLaughlin
    Say I have a class, something like the following; class MyClass { public: MyClass(); int a,b,c; double x,y,z; }; #define PageSize 1000000 MyClass Array1[PageSize],Array2[PageSize]; If my class has not pointers or virtual methods, is it safe to use the following? memcpy(Array1,Array2,PageSize*sizeof(MyClass)); The reason I ask, is that I'm dealing with very large collections of paged data, as decribed here, where performance is critical, and memcpy offers significant performance advantages over iterative assignment. I suspect it should be ok, as the 'this' pointer is an implicit parameter rather than anything stored, but are there any other hidden nasties I should be aware of?

    Read the article

  • Generics vs Object performance

    - by Risho
    I'm doing practice problems from MCTS Exam 70-536 Microsft .Net Framework Application Dev Foundation, and one of the problems is to create two classes, one generic, one object type that both perform the same thing; in which a loop uses the class and iterated over thousand times. And using the timer, time the performance of both. There was another post at C# generics question that seeks the same questoion but nonone replied. Basically if in my code I run the generic class first it takes loger to process. If I run the object class first than the object class takes longer to process. The whole idea was to prove that generics perform faster. I used the original users code to save me some time. I didn't particularly see anything wrong with the code and was puzzled by the outcome. Can some one explain why the unusual results? Thanks, Risho Here is the code: class Program { class Object_Sample { public Object_Sample() { Console.WriteLine("Object_Sample Class"); } public long getTicks() { return DateTime.Now.Ticks; } public void display(Object a) { Console.WriteLine("{0}", a); } } class Generics_Samle<T> { public Generics_Samle() { Console.WriteLine("Generics_Sample Class"); } public long getTicks() { return DateTime.Now.Ticks; } public void display(T a) { Console.WriteLine("{0}", a); } } static void Main(string[] args) { long ticks_initial, ticks_final, diff_generics, diff_object; Object_Sample OS = new Object_Sample(); Generics_Samle<int> GS = new Generics_Samle<int>(); //Generic Sample ticks_initial = 0; ticks_final = 0; ticks_initial = GS.getTicks(); for (int i = 0; i < 50000; i++) { GS.display(i); } ticks_final = GS.getTicks(); diff_generics = ticks_final - ticks_initial; //Object Sample ticks_initial = 0; ticks_final = 0; ticks_initial = OS.getTicks(); for (int j = 0; j < 50000; j++) { OS.display(j); } ticks_final = OS.getTicks(); diff_object = ticks_final - ticks_initial; Console.WriteLine("\nPerformance of Generics {0}", diff_generics); Console.WriteLine("Performance of Object {0}", diff_object); Console.ReadKey(); } }

    Read the article

  • Would it be simply better to use the system's functions rather than use the language?

    - by Nullw0rm
    There are many scenarios where I've questioned PHP's performance with some of its functions, and whether I should build a complex class to handle specific things using its seemingly slow tools. For example, Complex regular expressions with sed and processing with awk would seemingly be exponential in performance rather than making PHP's regular expression and seemingly excessive functions parse and in time manage to finish it. If I were to do a lot of network tasks such as MX lookups/DIGging/retrieving simultaneously I would rather pass it via system() and let the OS handle it itself. There are simply too many functions in PHP, that are inefficient and result in slow pages or can be handled easier by the OS. What are your opinions? Do you think I should do the hard work with the OS in its own/custom functions?

    Read the article

  • In what circumstances can large pages produce a speedup ?

    - by timday
    Modern x86 CPUs have the ability to support larger page sizes than the legacy 4K (ie 2MB or 4MB), and there are OS facilities (Linux, Windows) to access this functionality. The Microsoft link above states large pages "increase the efficiency of the translation buffer, which can increase performance for frequently accessed memory". Which isn't very helpful in predicting whether large pages will improve any given situation. I'm interested in concrete, preferably quantified, examples of where moving some program logic (or a whole application) to use huge pages has resulted in some performance improvement. Anyone got any success stories ? There's one particular case I know of myself: using huge pages can dramatically reduce the time needed to fork a large process (presumably as the number of TLB records needing copying is reduced by a factor on the order of 1000). I'm interested in whether huge pages can also benefit more mundane applications though.

    Read the article

  • Inserting asyncronously into Oracle, any benefits?

    - by Karl Trumstedt
    I am using ODP.NET for loading data into Oracle. I am bulking inserts into groups of a 1000 rows each call. Is there any performance benefits in calling my load method asynchronously? So say I want to insert 10000 rows, instead of making 10 calls synchronously I make 10 calls asynchronously. My database is using ASSM right now but otherwise plenty of freelists are used of course. The database server has several cores as well. My initial tests seem to point to a performance increase, but maybe there is something I cannot see? Potential deadlock or contention issues? Of course, there is added complexity in handling transactions and such doing my load this way.

    Read the article

  • VS2008 intellisense performance issue with large number of partial static classes

    - by scebula
    My question is a follow-up to the issue posted here regarding the Intellisense performance issue when building a large solution in VS2008 that has many partial static classes. Since Microsoft does not seem to be addressing the issue for VS2008, I would like to know if there are other ways around the problem? Waiting for VS2010 is not an option at this time. The proposed solution in the previous post is not practical as some of the partial classes may be regenerated and this would be a maintenance headache.

    Read the article

  • Improving Javascript Load Times - Concatenation vs Many + Cache

    - by El Yobo
    I'm wondering which of the following is going to result in better performance for a page which loads a large amount of javascript (jQuery + jQuery UI + various other javascript files). I have gone through most of the YSlow and Google Page Speed stuff, but am left wondering about a particular detail. A key thing for me here is that the site I'm working on is not on the public net; it's a business to business platform where almost all users are repeat visitors (and therefore with caches of the data, which is something that YSlow assumes will not be the case for a large number of visitors). First up, the standard approach recommended by tools such as YSlow is to concatenate it, compress it, and serve it up in a single file loaded at the end of your page. This approach sounds reasonably effective, but I think that a key part of the reasoning here is to improve performance for users without cached data. The system I currently have is something like this * All javascript files are compressed and loaded at the bottom of the page * All javascript files have far future cache expiration dates, so will remain (for most users) in the cache for a long time * Pages only load the javascript files that they require, rather than loading one monolithic file, most of which will not be required Now, my understanding is that, if the cache expiration date for a javascript file has not been reached, then the cached version is used immediately; there is no HTTP request sent at to the server at all. If this is correct, I would assume that having multiple tags is not causing any performance penalty, as I'm still not having any additional requests on most pages (recalling from above that almost all users have populated caches). In addition to this, not loading the JS means that the browser doesn't have to interpret or execute all this additional code which it isn't going to need; as a B2B application, most of our users are unfortunately stuck with IE6 and its painfully slow JS engine. Another benefit is that, when code changes, only the affected files need to be fetched again, rather than the whole set (granted, it would only need to be fetched once, so this is not so much of a benefit). I'm also looking at using LabJS to allow for parallel loading of the JS when it's not cached. So, what do people think is a better approach? In a similar vein, what do you think about a similar approach to CSS - is monolithic better?

    Read the article

  • Propor usage of double and single quotes?

    - by Phox
    I'm talking about the performance increase here. From all I know you can echo variables in double quotes ("), like so: <?php echo "You are $yourAge years old"; ?> But single quotes will just return You are $yourAge years old. But what about performance differences? I've always gone by the rule that single quotes are faster because the PHP interpreter doesn't have to search through the string for variables. But I'm seeing more and more blog and forum posts on the web saying differently. Does anyone actually have any information on this subject? Perhaps benchmark tests or something? Cheers.

    Read the article

  • Even lighter than SQLite

    - by Richard Fabian
    I've been looking for a C++ SQL library implementation that is simple to hook in like SQLite, but faster and smaller. My projects are in games development and there's definitely a cutoff point between needing to pass the ACID test and wanting some extreme performance. I'm willing to move away from SQL string style queries, allowing it to be code driven, but I haven't found anything out there that provides SQL like flexibility while also preferring performance over the ACID test. I don't want to go reinventing the wheel, and the idea of implementing an SQL library on my own is quite daunting, even if it's only going to be simple subset of all the calls you could make. I need the basic commands (SELECT, MODIFY, DELETE, INSERT, with JOIN, and WHERE), not data operations (like sorting, min, max, count) and don't need the database to be atomic, or even enforce consistency (I can use a real SQL service while I'm testing and debugging).

    Read the article

  • How to effectively measure difference in a run-time.

    - by Knowing me knowing you
    Guys, in one of the excersises in TC++PL B.S. asks to: "Write a function that either returns a value or that throws that value based on an argument. Measure the difference in run-time between the two ways." Great pity he never explaines how to measure such things. I'm not sure if I'm suppose to write simple "time start, time end" counter or maybe there are more effective and practical ways to do it? Thanks in advance.

    Read the article

  • Why would Linux VM in vSphere ESXi 5.5 show dramatically increased disk i/o latency?

    - by mhucka
    I'm stumped and I hope someone else will recognize the symptoms of this problem. Hardware: new Dell T110 II, dual-core Pentium G860 2.9 GHz, onboard SATA controller, one new 500 GB 7200 RPM cabled hard drive inside the box, other drives inside but not mounted yet. No RAID. Software: fresh CentOS 6.5 virtual machine under VMware ESXi 5.5.0 (build 174 + vSphere Client). 2.5 GB RAM allocated. The disk is how CentOS offered to set it up, namely as a volume inside an LVM Volume Group, except that I skipped having a separate /home and simply have / and /boot. CentOS is patched up, ESXi patched up, latest VMware tools installed in the VM. No users on the system, no services running, no files on the disk but the OS installation. I'm interacting with the VM via the VM virtual console in vSphere Client. Before going further, I wanted to check that I configured things more or less reasonably. I ran the following command as root in a shell on the VM: for i in 1 2 3 4 5 6 7 8 9 10; do dd if=/dev/zero of=/test.img bs=8k count=256k conv=fdatasync done I.e., just repeat the dd command 10 times, which results in printing the transfer rate each time. The results are disturbing. It starts off well: 262144+0 records in 262144+0 records out 2147483648 bytes (2.1 GB) copied, 20.451 s, 105 MB/s 262144+0 records in 262144+0 records out 2147483648 bytes (2.1 GB) copied, 20.4202 s, 105 MB/s ... but after 7-8 of these, it then prints 262144+0 records in 262144+0 records out 2147483648 bytes (2.1 GG) copied, 82.9779 s, 25.9 MB/s 262144+0 records in 262144+0 records out 2147483648 bytes (2.1 GB) copied, 84.0396 s, 25.6 MB/s 262144+0 records in 262144+0 records out 2147483648 bytes (2.1 GB) copied, 103.42 s, 20.8 MB/s If I wait a significant amount of time, say 30-45 minutes, and run it again, it again goes back to 105 MB/s, and after several rounds (sometimes a few, sometimes 10+), it drops to ~20-25 MB/s again. Plotting the disk latency in vSphere's interface, it shows periods of high disk latency hitting 1.2-1.5 seconds during the times that dd reports the low throughput. (And yes, things get pretty unresponsive while that's happening.) What could be causing this? I'm comfortable that it is not due to the disk failing, because I also had configured two other disks as an additional volume in the same system. At first I thought I did something wrong with that volume, but after commenting the volume out from /etc/fstab and rebooting, and trying the tests on / as shown above, it became clear that the problem is elsewhere. It is probably an ESXi configuration problem, but I'm not very experienced with ESXi. It's probably something stupid, but after trying to figure this out for many hours over multiple days, I can't find the problem, so I hope someone can point me in the right direction. (P.S.: yes, I know this hardware combo won't win any speed awards as a server, and I have reasons for using this low-end hardware and running a single VM, but I think that's besides the point for this question [unless it's actually a hardware problem].) ADDENDUM #1: Reading other answers such as this one made me try adding oflag=direct to dd. However, it makes no difference in the pattern of results: initially the numbers are higher for many rounds, then they drop to 20-25 MB/s. (The initial absolute numbers are in the 50 MB/s range.) ADDENDUM #2: Adding sync ; echo 3 > /proc/sys/vm/drop_caches into the loop does not make a difference at all. ADDENDUM #3: To take out further variables, I now run dd such that the file it creates is larger than the amount of RAM on the system. The new command is dd if=/dev/zero of=/test.img bs=16k count=256k conv=fdatasync oflag=direct. Initial throughput numbers with this version of the command are ~50 MB/s. They drop to 20-25 MB/s when things go south. ADDENDUM #4: Here is the output of iostat -d -m -x 1 running in another terminal window while performance is "good" and then again when it's "bad". (While this is going on, I'm running dd if=/dev/zero of=/test.img bs=16k count=256k conv=fdatasync oflag=direct.) First, when things are "good", it shows this: When things go "bad", iostat -d -m -x 1 shows this:

    Read the article

  • What is the easiest straightforward way of telling which version performs better?

    - by Peter Perhác
    I have an application, which I have re-factored so that I believe it is now faster. One can't possibly feel the difference, but in theory, the application should run faster. Normally I would not care, but as this is part of my project for my master's degree, I would like to support my claim that the re-factoring did not only lead to improved design and 'higher quality', but also an increase in performance of the application (a small toy-thing - a train set simulation). I have toyed with the latest VisualVM thing today for about four hours but I couldn't get anything helpful out of it. There isn't (or I haven't found it) a way to simply compare the profiling results taken from the two versions (pre- and post- refactoring). What would be the easiest, the most straightforward way of simply telling the slower from the faster version of the application. The difference of the two must have had an impact on the performance. Thank you.

    Read the article

  • Does allocation speed depend on the garbage collector being used?

    - by jkff
    My app is allocating a ton of objects (1mln per second; most objects are byte arrays of size ~80-100 and strings of the same size) and I think it might be the source of its poor performance. The app's working set is only tens of megabytes. Profiling the app shows that GC time is negligibly small. However, I suspect that perhaps the allocation procedure depends on which GC is being used, and some settings might make allocation faster or perhaps make a positive influence on cache hit rate, etc. Is that so? Or is allocation performance independent on GC settings under the assumption that garbage collection itself takes little time?

    Read the article

  • Proper usage of double and single quotes?

    - by Phox
    I'm talking about the performance increase here. From all I know you can echo variables in double quotes ("), like so: <?php echo "You are $yourAge years old"; ?> But single quotes will just return You are $yourAge years old. But what about performance differences? I've always gone by the rule that single quotes are faster because the PHP interpreter doesn't have to search through the string for variables. But I'm seeing more and more blog and forum posts on the web saying differently. Does anyone actually have any information on this subject? Perhaps benchmark tests or something?

    Read the article

  • List comprehension, map, and numpy.vectorize performance

    - by mcstrother
    I have a function foo(i) that takes an integer and takes a significant amount of time to execute. Will there be a significant performance difference between any of the following ways of initializing a: a = [foo(i) for i in xrange(100)] a = map(foo, range(100)) vfoo = numpy.vectorize(foo) a = vfoo(range(100)) (I don't care whether the output is a list or a numpy array.) Is there a better way?

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 104 105 106 107 108 109 110 111 112 113 114 115  | Next Page >