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  • Browser timing out attempting to load images

    - by notJim
    I've got a page on a webapp that has about 13 images that are generated by my application, which is written in the Kohana PHP framework. The images are actually graphs. They are cached so they are only generated once, but the first time the user visits the page, and the images all have to be generated, about half of the images don't load in the browser. Once the page has been requested once and images are cached, they all load successfully. Doing some ad-hoc testing, if I load an individual image in the browser, it takes from 450-700 ms to load with an empty cache (I checked this using Google Chrome's resource tracking feature). For reference, it takes around 90-150 ms to load a cached image. Even if the image cache is empty, I have the data and some of the application's startup tasks cached, so that after the first request, none of that data needs to be fetched. My questions are: Why are the images failing to load? It seems like the browser just decides not to download the image after a certain point, rather than waiting for them all to finish loading. What can I do to get them to load the first time, with an empty cache? Obviously one option is to decrease the load times, and I could figure out how to do that by profiling the app, but are there other options? As I mentioned, the app is in the Kohana PHP framework, and it's running on Apache. As an aside, I've solved this problem for now by fetching the page as soon as the data is available (it comes from a batch process), so that the images are always cached by the time the user sees them. That feels like a kludgey solution to me, though, and I'm curious about what's actually going on.

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  • Best memory settings for eclipse 4.2 (STS 3.1) on Windows 7 64 bit?

    - by jorrebor
    I apoligize in advance if this question is indeed too subjective as SO warns me. My workstation has 8 gb of ram and runs windows 7 64 bit. I use the Spring tool Suite (3.1) but as soon as i am starting to open and modify the spring config (.xml) files, STS becomes incredibly slow. I already tried switching off "build automatically" and to increase memory settings but no luck. How should i change my .ini ? this is what i have set now: -vm C:/Program Files/Java/jdk1.7.0_07/bin/javaw.exe -startup plugins/org.eclipse.equinox.launcher_1.3.0.v20120522-1813.jar --launcher.library plugins/org.eclipse.equinox.launcher.win32.win32.x86_64_1.1.200.v20120522-1813 -product org.springsource.sts.ide --launcher.defaultAction openFile --launcher.XXMaxPermSize 4096M -vmargs -Dosgi.requiredJavaVersion=1.5 -Xms512m -Xmx2048m -XX:MaxPermSize=512m My collageu running the same project in IntelliJ, has no problems. Thank you!

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  • Treeview Slow in IE?!?!

    - by Mike
    I have a treeview with around 200 records that needs to be fully expanded at all times (so no loading on demand). It is inside of an update panel with the updatemode set to conditional. There are other update panels on the page as well that are set to conditional. Depending on user actions the tree may need to be rebuilt by calling databind and updating the updatepanel. Everything works fine in firefox, longest postback about 2 seconds. With IE I have to wait up to 30 seconds sometimes and the action may have nothing to do with the tree just changing a dropdown in its own updatepanel takes forever. I have considered the size of viewstate and just raw HTML generated may be causing the delay but wouldn't that effect both browsers? Anyone have anyideas what is making it so slow in IE??? Thanks!

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  • Suggestion on Database structure for relational data

    - by miccet
    Hi there. I've been wrestling with this problem for quite a while now and the automatic mails with 'Slow Query' warnings are still popping in. Basically, I have Blogs with a corresponding table as well as a table that keeps track of how many times each Blog has been viewed. This last table has a huge amount of records since this page is relatively high traffic and it logs every hit as an individual row. I have tried with indexes on the fields that are included in the WHERE clause, but it doesn't seem to help. I have also tried to clean the table each week by removing old ( 1.weeks) records. SO, I'm asking you guys, how would you solve this? The query that I know is causing the slowness is generated by Rails and looks like this: SELECT count(*) AS count_all FROM blog_views WHERE (created_at >= '2010-01-01 00:00:01' AND blog_id = 1); The tables have the following structures: CREATE TABLE IF NOT EXISTS 'blogs' ( 'id' int(11) NOT NULL auto_increment, 'name' varchar(255) default NULL, 'perma_name' varchar(255) default NULL, 'author_id' int(11) default NULL, 'created_at' datetime default NULL, 'updated_at' datetime default NULL, 'blog_picture_id' int(11) default NULL, 'blog_picture2_id' int(11) default NULL, 'page_id' int(11) default NULL, 'blog_picture3_id' int(11) default NULL, 'active' tinyint(1) default '1', PRIMARY KEY ('id'), KEY 'index_blogs_on_author_id' ('author_id') ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=1 ; And CREATE TABLE IF NOT EXISTS 'blog_views' ( 'id' int(11) NOT NULL auto_increment, 'blog_id' int(11) default NULL, 'ip' varchar(255) default NULL, 'created_at' datetime default NULL, 'updated_at' datetime default NULL, PRIMARY KEY ('id'), KEY 'index_blog_views_on_blog_id' ('blog_id'), KEY 'created_at' ('created_at') ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=1 ;

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  • What is the most efficient method to find x contiguous values of y in an array?

    - by Alec
    Running my app through callgrind revealed that this line dwarfed everything else by a factor of about 10,000. I'm probably going to redesign around it, but it got me wondering; Is there a better way to do it? Here's what I'm doing at the moment: int i = 1; while ( ( (*(buffer++) == 0xffffffff && ++i) || (i = 1) ) && i < desiredLength + 1 && buffer < bufferEnd ); It's looking for the offset of the first chunk of desiredLength 0xffffffff values in a 32 bit unsigned int array. It's significantly faster than any implementations I could come up with involving an inner loop. But it's still too damn slow.

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  • SQL Database Schema Design For Large 3 Billion Relationship Database.

    - by K-Bell
    Get your geek on. Can you solve this? I am designing a products database for SQL Server 2008 R2 Ed. (not Enterprise Ed.) that will be used to store custom product configurations for over 30,000 distinct products. The database will have up to 500 users at a time. Here is the design problem… Each Product has a collection of Parts (up to 50 parts per product). So if I have 30,000 Products and each of them can have up to 50 Parts, that’s 1.5 million distinct Product-to-Part relationships …or as an equation… 30,000 (Products) X 50 (Parts) = 1.5 million Product-to-Parts records. …and If… Each Part can have up to 2000 finish options (A finish is a paint color). NOTE: Only one finish will be selected by a user at run-time. The 2000 finish options I need to store are the allowed options for a specific part on a specific product. So if I have 1.5 million distinct product-to-part relationships/records and each of those parts can have up to 2,000 finishes that is 3 billion allowable product-to-part-to finish relationships/records …or as an equation… 1.5 million (Parts) x 2,000 (Finishes) = 3 Billion Product-to-Part-to-Finishes records. How can I design this database so that I can execute fast and efficient queries for a specific product and return its list of Parts and all the allowable Finishes for each part without 3 Billion Product-to-Part-to-Finish records? Read time is more important then write time. Please post your thoughts/suggestions if you have experience with large databases. Thanks!

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  • What influences running time of reading a bunch of images?

    - by remi
    I have a program where I read a handful of tiny images (50000 images of size 32x32). I read them using OpenCV imread function, in a program like this: std::vector<std::string> imageList; // is initialized with full path to the 50K images for(string s : imageList) { cv::Mat m = cv::imread(s); } Sometimes, it will read the images in a few seconds. Sometimes, it takes a few minutes to do so. I run this program in GDB, with a breakpoint further away than the loop for reading images so it's not because I'm stuck in a breakpoint. The same "erratic" behaviour happens when I run the program out of GDB. The same "erratic" behaviour happens with program compiled with/without optimisation The same "erratic" behaviour happens while I have or not other programs running in background The images are always at the same place in the hard drive of my machine. I run the program on a Linux Suse distrib, compiled with gcc. So I am wondering what could affect the time of reading the images that much?

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  • Fastest way to do a weighted tag search in SQL Server

    - by Hasan Khan
    My table is as follows ObjectID bigint Tag nvarchar(50) Weight float Type tinyint I want to get search for all objects that has tags 'big' or 'large' I want the objectid in order of sum of weights (so objects having both the tags will be on top) select objectid, row_number() over (order by sum(weight) desc) as rowid from tags where tag in ('big', 'large') and type=0 group by objectid the reason for row_number() is that i want paging over results. The query in its current form is very slow, takes a minute to execute over 16 million tags. What should I do to make it faster? I have a non clustered index (objectid, tag, type) Any suggestions?

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  • Session Timeout and page response time

    - by Johnny5
    Hi, I'm load testing an asp.net app. The load test is simulating 500 user doing searchs on the site and browsing the results. I'm observing that the more I reduce the session timeout limit (in web.config) the better the page response time. For exemple, with a timeout at 10 minutes, I got an average response time of 8.35 seconds. With a timout at 3 minutes, the average response time for the same page is 3,98 seconds. The session in stored "InProc". I supposed the memory used by the "no more used but still actives" sessions may be in cause. But, even if there is more memory used when the timeout is at 10, there is still plenty of memory available (about 2.7Gb). Any ideas?

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  • Profilers for ASP.Net Web Applications?

    - by Earlz
    I was recently wanting to do some profiling on an ASP.Net project and was surprised to see that Visual Studio (at least seems to be) lacking a profiler. So my question is what profiler do you use for ASP.Net? Are there any decent ones out there that are free? I've seen a few general .Net profilers but have yet to see one that can be used with ASP.Net..

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  • Will Algorithm written in OCaml compiled from C be Faster than Algorithm written in Pure C code?

    - by Ole Jak
    So I have some cool Image Processing algorithm. I have written it in OCaml. It performs well. I now I can compile it as C code with such command ocamlc -output-obj -o foo.c foo.ml (I have a situation where I am not alowed to use OCaml compiler to bild my programm for my arcetecture, I can use only specialy modified gcc. so I will compile that programm with sometyhing like gcc -L/usr/lib/ocaml foo.c -lcamlrun -lm -lncurses and Itll run on my archetecture.) I want to know in general case will my OCaml code compiled into C run faster than algorithm implemented in pure C?

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  • Java program runs smoothly in Netbeans but slowly in Eclipse and as an executed jar. WTF?

    - by comp sci balla
    A java program that does frequent swing/awt painting animation (but nothing more advanced than g.fillOval(...)) runs at a consistent 60fps in Netbeans, and at about 6fps when ran in Eclipse or executed as a jar file from a unix terminal. The program was developed in Netbeans and is run-of-the-mill desktop application (not webstart or japplet or ...). This is occurring in Ubuntu 10 with java 1.6. How is this possible? The universe no longer makes sense to me.

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  • Is it better to use GL_FIXED or GL_FLOAT on Android.

    - by Timmmm
    I would have assumed that GL_FIXED was faster, but the iPhone docs actually say to use GL_FLOAT because GL_FIXED has to be converted to GL_FLOAT. Is it the same on Android? I suppose it varies by phone, but what about recent popular ones (Nexus One, Droid/Milestone, etc.)? Bonus points: This appears to be completely undocumented (e.g. search google for GL_FIXED!) but where is the 'point' in GL_FIXED? I.e. how much is (GL_FIXED)1 worth?

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  • apache alias and .htacess willing to understand configuration?

    - by sushil bharwani
    On our local dev enviornment we had just one server and to add far future expires and cache control header to static images we kept a .htaccess file in the root of the application things worked fine. But on our prod we have multiple apache servers having aliases to a code base on a different server. Here in this case i am not sure where to keep .htacess file on. Should i be keeping it on code base or on the individual apache servers. How can i write the same stuff that i have written in .htaccess file to httpd.conf file.

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  • Why PHP (script) serves more requests than CGI (compiled)?

    - by Lucas Batistussi
    I developed the following CGI script and run on Apache 2 (http://localhost/test.chtml). I did same script in PHP (http://localhost/verifica.php). Later I performed Apache benchmark using Apache Benchmark tool. The results are showed in images. include #include <stdlib.h> int main(void) { printf("%s%c%c\n", "Content-Type:text/html;charset=iso-8859-1",13,10); printf("<TITLE>Multiplication results</TITLE>\n"); printf("<H3>Multiplication results</H3>\n"); return 0; } Someone can explain me why PHP serves more requests than CGI script?

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  • Project Euler #119 Make Faster

    - by gangqinlaohu
    Trying to solve Project Euler problem 119: The number 512 is interesting because it is equal to the sum of its digits raised to some power: 5 + 1 + 2 = 8, and 8^3 = 512. Another example of a number with this property is 614656 = 28^4. We shall define an to be the nth term of this sequence and insist that a number must contain at least two digits to have a sum. You are given that a2 = 512 and a10 = 614656. Find a30. Question: Is there a more efficient way to find the answer than just checking every number until a30 is found? My Code int currentNum = 0; long value = 0; for (long a = 11; currentNum != 30; a++){ //maybe a++ is inefficient int test = Util.sumDigits(a); if (isPower(a, test)) { currentNum++; value = a; System.out.println(value + ":" + currentNum); } } System.out.println(value); isPower checks if a is a power of test. Util.sumDigits: public static int sumDigits(long n){ int sum = 0; String s = "" + n; while (!s.equals("")){ sum += Integer.parseInt("" + s.charAt(0)); s = s.substring(1); } return sum; } program has been running for about 30 minutes (might be overflow on the long). Output (so far): 81:1 512:2 2401:3 4913:4 5832:5 17576:6 19683:7 234256:8 390625:9 614656:10 1679616:11 17210368:12 34012224:13 52521875:14 60466176:15 205962976:16 612220032:17

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  • Python : How do you find the CPU consumption for a piece of code?

    - by Yugal Jindle
    Background: I have a django application, it works and responds pretty well on low load, but on high load like 100 users/sec, it consumes 100% CPU and then due to lack of CPU slows down. Problem : Profiling the application gives me time taken by functions. This time increases on high load. Time consumed may be due to complex calculation or for waiting for CPU. so, how to find the CPU cycles consumed by a piece of code ? Since, reducing the CPU consumption will increase the response time. I might have written extremely efficient code and need to add more CPU power OR I might have some stupid code taking the CPU and causing the slow down ? Any help is appreciated ! Update: I am using Jmeter to profile my webapp, it gives me a throughput of 2 requests/sec. [ 100 users] I get a average time of 36 seconds on 100 request vs 1.25 sec time on 1 request. More Info Configuration Nginx + Uwsgi with 4 workers No database used, using a responses from a REST API On 1st hit the response of REST API gets cached, therefore doesn't makes a difference. Using ujson for json parsing. Curious to Know: Python-Django is used by so many orgs for so many big sites, then there must be some high end Debug / Memory-CPU analysis tools. All those I found were casual snippets of code that perform profiling.

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  • Is there a better way to count the messages in an Message Queue (MSMQ)?

    - by Damovisa
    I'm currently doing it like this: MessageQueue queue = new MessageQueue(".\Private$\myqueue"); MessageEnumerator messageEnumerator = queue.GetMessageEnumerator2(); int i = 0; while (messageEnumerator.MoveNext()) { i++; } return i; But for obvious reasons, it just feels wrong - I shouldn't have to iterate through every message just to get a count, should I? Is there a better way?

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  • Faster code with another compiler

    - by Andrei
    I'm using the standard gcc compiler in math software development with C-language. I don't know that much about compilers or compiler options, and I was just wondering, is it possible to make faster executables using another compiler or choosing better options? The default Makefile sets options -ffast-math and -O3 and I think both of them have some impact in the overall calculation time. My software is using memory quite extensively, so I imagine some options related to memory management might do the trick? Any ideas?

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  • Very simple python functions takes spends long time in function and not subfunctions

    - by John Salvatier
    I have spent many hours trying to figure what is going on here. The function 'grad_logp' in the code below is called many times in my program, and cProfile and runsnakerun the visualize the results reveals that the function grad_logp spends about .00004s 'locally' every call not in any functions it calls and the function 'n' spends about .00006s locally every call. Together these two times make up about 30% of program time that I care about. It doesn't seem like this is function overhead as other python functions spend far less time 'locally' and merging 'grad_logp' and 'n' does not make my program faster, but the operations that these two functions do seem rather trivial. Does anyone have any suggestions on what might be happening? Have I done something obviously inefficient? Am I misunderstanding how cProfile works? def grad_logp(self, variable, calculation_set ): p = params(self.p,self.parents) return self.n(variable, self.p) def n (self, variable, p ): gradient = self.gg(variable, p) return np.reshape(gradient, np.shape(variable.value)) def gg(self, variable, p): if variable is self: gradient = self._grad_logps['x']( x = self.value, **p) else: gradient = __builtin__.sum([self._pgradient(variable, parameter, value, p) for parameter, value in self.parents.iteritems()]) return gradient

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  • Is putting the javascript before the closing body tag okay on an asp.net website?

    - by Jason Weber
    I pretty much stated what I have to ask. But is taking all of your external .js files and putting them before the closing body tag on your master pages okay on an asp.net website? I'm just going off of what yslow and google speed have been showing. I can't combine these javascripts, so I'm trying to load them "after page load", but doing so makes them useless; some of my jquery things don't work. I moved my .js files above the opening body tag, and they work. What am I doing wrong? And what could I do to load my .js files after page load? Thanks for any advice anybody can offer!

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  • JavaScript: Is there a better way to retain your array but efficiently concat or replace items?

    - by Michael Mikowski
    I am looking for the best way to replace or add to elements of an array without deleting the original reference. Here is the set up: var a = [], b = [], c, i, obj; for ( i = 0; i < 100000; i++ ) { a[ i ] = i; b[ i ] = 10000 - i; } obj.data_list = a; Now we want to concatenate b INTO a without changing the reference to a, since it is used in obj.data_list. Here is one method: for ( i = 0; i < b.length; i++ ) { a.push( b[ i ] ); } This seems to be a somewhat terser and 8x (on V8) faster method: a.splice.apply( a, [ a.length, 0 ].concat( b ) ); I have found this useful when iterating over an "in-place" array and don't want to touch the elements as I go (a good practice). I start a new array (let's call it keep_list) with the initial arguments and then add the elements I wish to retain. Finally I use this apply method to quickly replace the truncated array: var keep_list = [ 0, 0 ]; for ( i = 0; i < a.length; i++ ){ if ( some_condition ){ keep_list.push( a[ i ] ); } // truncate array a.length = 0; // And replace contents a.splice.apply( a, keep_list ); There are a few problems with this solution: there is a max call stack size limit of around 50k on V8 I have not tested on other JS engines yet. This solution is a bit cryptic Has anyone found a better way?

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