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  • Measuring debug vs release of ASP.NET applications

    - by Alex Angas
    A question at work came up about building ASP.NET applications in release vs debug mode. When researching further (particularly on SO), general advice is that setting <compilation debug="true"> in web.config has a much bigger impact. Has anyone done any testing to get some actual numbers about this? Here's the sort of information I'm looking for (which may give away my experience with testing such things): Execution time | Debug build | Release build -------------------+---------------+--------------- Debug web.config | average 1 | average 2 Retail web.config | average 3 | average 4 Max memory usage | Debug build | Release build -------------------+---------------+--------------- Debug web.config | average 1 | average 2 Retail web.config | average 3 | average 4 Output file size | Debug build | Release build -------------------+---------------+--------------- | size 1 | size 2

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  • .NET WebService IPC - Should it be done to minimise some expensive operations?

    - by Kyle
    I'm looking at a few different approaches to a problem: Client requests work, some stuff gets done, and a result (ok/error) is returned. A .NET web service definitely seems like the way to go, my only issue is that the "stuff" will involve building up and tearing down a session for each request. Does abstracting the "stuff" out to an app (which would keep a single session active, and process the request from the web service) seem like the right way to go? (and if so, what communication method) The work time is negligible, my concern is the hammering the transaction servers in question will probably get if I create/drop a session for each job. Is some form of IPC or socket based communication a feasible solution here? Thoughts/comments/experiences much appreciated. Edit: After a bit more research, it seems like hosting a WCF service in a Windows Service is probably a better way to go...

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  • How do I make this nested for loop, testing sums of cubes, more efficient?

    - by Brian J. Fink
    I'm trying to iterate through all the combinations of pairs of positive long integers in Java and testing the sum of their cubes to discover if it's a Fibonacci number. I'm currently doing this by using the value of the outer loop variable as the inner loop's upper limit, with the effect being that the outer loop runs a little slower each time. Initially it appeared to run very quickly--I was up to 10 digits within minutes. But now after 2 full days of continuous execution, I'm only somewhere in the middle range of 15 digits. At this rate it may end up taking a whole year just to finish running this program. The code for the program is below: import java.lang.*; import java.math.*; public class FindFib { public static void main(String args[]) { long uLimit=9223372036854775807L; //long maximum value BigDecimal PHI=new BigDecimal(1D+Math.sqrt(5D)/2D); //Golden Ratio for(long a=1;a<=uLimit;a++) //Outer Loop, 1 to maximum for(long b=1;b<=a;b++) //Inner Loop, 1 to current outer { //Cube the numbers and add BigDecimal c=BigDecimal.valueOf(a).pow(3).add(BigDecimal.valueOf(b).pow(3)); System.out.print(c+" "); //Output result //Upper and lower limits of interval for Mobius test: [c*PHI-1/c,c*PHI+1/c] BigDecimal d=c.multiply(PHI).subtract(BigDecimal.ONE.divide(c,BigDecimal.ROUND_HALF_UP)), e=c.multiply(PHI).add(BigDecimal.ONE.divide(c,BigDecimal.ROUND_HALF_UP)); //Mobius test: if integer in interval (floor values unequal) Fibonacci number! if (d.toBigInteger().compareTo(e.toBigInteger())!=0) System.out.println(); //Line feed else System.out.print("\r"); //Carriage return instead } //Display final message System.out.println("\rDone. "); } } Now the use of BigDecimal and BigInteger was delibrate; I need them to get the necessary precision. Is there anything other than my variable types that I could change to gain better efficiency?

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  • Django: Update order attribute for objects in a queryset

    - by lazerscience
    I'm having a attribute on my model to allow the user to order the objects. I have to update the element's order depending on a list, that contains the object's ids in the new order; right now I'm iterating over the whole queryset and set one objects after the other. What would be the easiest/fastest way to do the same with the whole queryset? def update_ordering(model, order): """ order is in the form [id,id,id,id] for example: [8,4,5,1,3] """ id_to_order = dict((order[i], i) for i in range(len(order))) for x in model.objects.all(): x.order = id_to_order[x.id] x.save()

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  • integer division in php

    - by oezi
    hi guys, i'm looking for the fastest way to do an integer division in php. for example, 5 / 2 schould be 4 | 6 / 2 should be 3 and so on. if i simply do this, php will return 2.5 in the first case, the only solution i could find was using intval($my_number/2) - wich isn't as fast as i want it to be (but gives the expected results). can anyone help me out with this?

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  • Jmeter- HTTP Cache Manager, Unable to cache everything what it is being cached by Browser

    - by chinmay brahma
    I used HTTP Chache Manager to Cache files which are being cached in browser. I am successful of doing it for some of the pages. Number of files being cached in Jmeter is equal to Number of files being cached by browser. But in some cases : I found number files being cached is lesser than the files being cached by browser. Using Jmeter I found only 5 files are being cached but in real browser 12 files are getting cached. Thanks in advance

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  • Database structure for ecommerce site

    - by imanc
    Hey Guys, I have been tasked with designing an ecommerce solution. The aspect that is causing me the most problems is the database. Currently the site consists of 10+ country based shops each with their own database (all residing on the same mysql instance). For the new site I'd rather all these shop databases be merged into one database so that all tables (products, orders, customers etc.) have a shop_id field. From a programming perspective this seems to make the most sense as we won't have to manage data across multiple databases. Currently the entire site generates about 120k orders a year, but is experiencing fairly heavy growth and we need to design a solution that will scale. In 5 years there may be more than a million orders per year and a database that contains 5 years order history (archiving maybe a solution here). The question is - do we use a single database, or do we keep the database-per-shop structure? I am currently trying to find supporting evidence for either avenue. The company I am designing the solution for prefer the per-shop database structure because they believe it will allow the sites to scale. But my argument is that the shop's database probably won't get that busy over the next few years that they exceed the capacity of a mysql database and a "no expenses spared" hardware set-up. I am wondering if anyone has any advice either way? Does anyone have experience with websites / ecommerce sites that have tables containing millions of records? I know there is probably not a clear answer here, but at what stage do we have too many records or too large table files to have a fast loading site? Also, if anyone has any advice on sources of information - books, websites, etc. where I can do further research, it would be highly appreciated! Cheers, imanc

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  • Time to start a counter on client-side.

    - by Felipe
    Hi everybody, I'm developing an web application using asp.net mvc, and i need to do a stopwatch (chronometer) (with 30 seconds preprogrammed to start in a certain moment) on client-side using the time of the server, by the way, the client's clock can't be as the server's clock. So, i'm using Jquery to call the server by JSon and get the time, but it's very stress because each one second I call the server to get time, something like this: $(function() { GetTimeByServer(); }); function GetTimeByServer() { $.getJSon('/Home/Time', null, function(result) { if (result.SecondsPending < 30) { // call another function to start an chronometer } else { window.SetTimeout(GetTimeByServer, 1000); //call again each 1 second! } }); } It works fine, but when I have more than 3 or 4 call like this, the browser slowly but works! I'd like to know, how improve more performace in client side, or if is there any way to do this... is there any way to client listen the server like a "socket" to know if the chronometer should start... PS: Sorry for my english! thanks Cheers

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  • Preventing a heavy process from sinking in the swap file

    - by eran
    Our service tends to fall asleep during the nights on our client's server, and then have a hard time waking up. What seems to happen is that the process heap, which is sometimes several hundreds of MB, is moved to the swap file. This happens at night, when our service is not used, and others are scheduled to run (DB backups, AV scans etc). When this happens, after a few hours of inactivity the first call to the service takes up to a few minutes (consequent calls take seconds). I'm quite certain it's an issue of virtual memory management, and I really hate the idea of forcing the OS to keep our service in the physical memory. I know doing that will hurt other processes on the server, and decrease the overall server throughput. Having that said, our clients just want our app to be responsive. They don't care if nightly jobs take longer. I vaguely remember there's a way to force Windows to keep pages on the physical memory, but I really hate that idea. I'm leaning more towards some internal or external watchdog that will initiate higher-level functionalities (there is already some internal scheduler that does very little, and makes no difference). If there were a 3rd party tool that provided that kind of service is would have been just as good. I'd love to hear any comments, recommendations and common solutions to this kind of problem. The service is written in VC2005 and runs on Windows servers.

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  • Effecient data structure design

    - by Sway
    Hi there, I need to match a series of user inputed words against a large dictionary of words (to ensure the entered value exists). So if the user entered: "orange" it should match an entry "orange' in the dictionary. Now the catch is that the user can also enter a wildcard or series of wildcard characters like say "or__ge" which would also match "orange" The key requirements are: * this should be as fast as possible. * use the smallest amount of memory to achieve it. If the size of the word list was small I could use a string containing all the words and use regular expressions. however given that the word list could contain potentially hundreds of thousands of enteries I'm assuming this wouldn't work. So is some sort of 'tree' be the way to go for this...? Any thoughts or suggestions on this would be totally appreciated! Thanks in advance, Matt

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  • one two-directed tcp socket OR two one-directed? (linux, high volume, low latency)

    - by osgx
    Hello I need to send (interchange) a high volume of data periodically with the lowest possible latency between 2 machines. The network is rather fast (e.g. 1Gbit or even 2G+). Os is linux. Is it be faster with using 1 tcp socket (for send and recv) or with using 2 uni-directed tcp sockets? The test for this task is very like NetPIPE network benchmark - measure latency and bandwidth for sizes from 2^1 up to 2^13 bytes, each size sent and received 3 times at least (in teal task the number of sends is greater. both processes will be sending and receiving, like ping-pong maybe). The benefit of 2 uni-directed connections come from linux: http://lxr.linux.no/linux+v2.6.18/net/ipv4/tcp_input.c#L3847 3847/* 3848 * TCP receive function for the ESTABLISHED state. 3849 * 3850 * It is split into a fast path and a slow path. The fast path is 3851 * disabled when: ... 3859 * - Data is sent in both directions. Fast path only supports pure senders 3860 * or pure receivers (this means either the sequence number or the ack 3861 * value must stay constant) ... 3863 * 3864 * When these conditions are not satisfied it drops into a standard 3865 * receive procedure patterned after RFC793 to handle all cases. 3866 * The first three cases are guaranteed by proper pred_flags setting, 3867 * the rest is checked inline. Fast processing is turned on in 3868 * tcp_data_queue when everything is OK. All other conditions for disabling fast path is false. And only not-unidirected socket stops kernel from fastpath in receive

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  • one two-directed tcp socket of two one-directed? (linux, high volume, low latency)

    - by osgx
    Hello I need to send (interchange) a high volume of data periodically with the lowest possible latency between 2 machines. The network is rather fast (e.g. 1Gbit or even 2G+). Os is linux. Is it be faster with using 1 tcp socket (for send and recv) or with using 2 uni-directed tcp sockets? The test for this task is very like NetPIPE network benchmark - measure latency and bandwidth for sizes from 2^1 up to 2^13 bytes, each size sent and received 3 times at least (in teal task the number of sends is greater. both processes will be sending and receiving, like ping-pong maybe). The benefit of 2 uni-directed connections come from linux: http://lxr.linux.no/linux+v2.6.18/net/ipv4/tcp_input.c#L3847 3847/* 3848 * TCP receive function for the ESTABLISHED state. 3849 * 3850 * It is split into a fast path and a slow path. The fast path is 3851 * disabled when: ... 3859 * - Data is sent in both directions. Fast path only supports pure senders 3860 * or pure receivers (this means either the sequence number or the ack 3861 * value must stay constant) ... 3863 * 3864 * When these conditions are not satisfied it drops into a standard 3865 * receive procedure patterned after RFC793 to handle all cases. 3866 * The first three cases are guaranteed by proper pred_flags setting, 3867 * the rest is checked inline. Fast processing is turned on in 3868 * tcp_data_queue when everything is OK. All other conditions for disabling fast path is false. And only not-unidirected socket stops kernel from fastpath in receive

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  • Are closures in javascript recompiled

    - by Discodancer
    Let's say we have this code (forget about prototypes for a moment): function A(){ var foo = 1; this.method = function(){ return foo; } } var a = new A(); is the inner function recompiled each time the function A is run? Or is it better (and why) to do it like this: function method = function(){ return this.foo; } function A(){ this.foo = 1; this.method = method; } var a = new A(); Or are the javascript engines smart enough not to create a new 'method' function every time? Specifically Google's v8 and node.js. Also, any general recommendations on when to use which technique are welcome. In my specific example, it really suits me to use the first example, but I know thath the outer function will be instantiated many times.

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  • How to get the size of a binary tree ?

    - by Andrei Ciobanu
    I have a very simple binary tree structure, something like: struct nmbintree_s { unsigned int size; int (*cmp)(const void *e1, const void *e2); void (*destructor)(void *data); nmbintree_node *root; }; struct nmbintree_node_s { void *data; struct nmbintree_node_s *right; struct nmbintree_node_s *left; }; Sometimes i need to extract a 'tree' from another and i need to get the size to the 'extracted tree' in order to update the size of the initial 'tree' . I was thinking on two approaches: 1) Using a recursive function, something like: unsigned int nmbintree_size(struct nmbintree_node* node) { if (node==NULL) { return(0); } return( nmbintree_size(node->left) + nmbintree_size(node->right) + 1 ); } 2) A preorder / inorder / postorder traversal done in an iterative way (using stack / queue) + counting the nodes. What approach do you think is more 'memory failure proof' / performant ? Any other suggestions / tips ? NOTE: I am probably going to use this implementation in the future for small projects of mine. So I don't want to unexpectedly fail :).

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  • Fastest XML parser for small, simple documents in Java

    - by Varkhan
    I have to objectify very simple and small XML documents (less than 1k, and it's almost SGML: no namespaces, plain UTF-8, you name it...), read from a stream, in Java. I am using JAXP to process the data from my stream into a Document object. I have tried Xerces, it's way too big and slow... I am using Dom4j, but I am still spending way too much time in org.dom4j.io.SAXReader. Does anybody out there have any suggestion on a faster, more efficient implementation, keeping in mind I have very tough CPU and memory constraints? [Edit 1] Keep in mind that my documents are very small, so the overhead of staring the parser can be important. For instance I am spending as much time in org.xml.sax.helpers.XMLReaderFactory.createXMLReader as in org.dom4j.io.SAXReader.read [Edit 2] The result has to be in Dom format, as I pass the document to decision tools that do arbitrary processing on it, like switching code based on the value of arbitrary XPaths, but also extracting lists of values packed as children of a predefined node. [Edit 3] In any case I eventually need to load/parse the complete document, since all the information it contains is going to be used at some point. (This question is related to, but different from, http://stackoverflow.com/questions/373833/best-xml-parser-for-java )

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  • Creating C++ client app for some abstract windows server - how to manage TCP connection to server speed?

    - by Kabumbus
    So we have some server with some address port and ip. we are developing that server so we can implement on it what ever we need for help. What are standard/best practices for data transfer speed management between C++ windows client app and server (C++)? My main point is in how to get how much data can be uploaded/downloaded from/to client via his low speed network to my relatively super fast server. (I need it for set up of his live stream Audio/Video bit rate) My try on explaining number 3. We do not care how fast is our server. It is always faster than needed. We care about client tyring to stream out to our server his media. he streams encoded (via ffmpeg) live video data to our server. But he has say ADSL with 500kb/s of outgoing traffic. Also he uses some ICQ or what so ever so he has less than 500 kb/s per second. And he wants to stream live video! So we need to set up our ffmpeg to encode video with respect to the bit rate user can provide. We develop server side and client side. We need a way of finding out how much user can upload per second currently (so value can change dynamically over time)

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  • List of divisors of an integer n (Haskell)

    - by Code-Guru
    I currently have the following function to get the divisors of an integer: -- All divisors of a number divisors :: Integer -> [Integer] divisors 1 = [1] divisors n = firstHalf ++ secondHalf where firstHalf = filter (divides n) (candidates n) secondHalf = filter (\d -> n `div` d /= d) (map (n `div`) (reverse firstHalf)) candidates n = takeWhile (\d -> d * d <= n) [1..n] I ended up adding the filter to secondHalf because a divisor was repeating when n is a square of a prime number. This seems like a very inefficient way to solve this problem. So I have two questions: How do I measure if this really is a bottle neck in my algorithm? And if it is, how do I go about finding a better way to avoid repetitions when n is a square of a prime?

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  • C#/WPF FileSystemWatcher on every extension on every path

    - by BlueMan
    I need FileSystemWatcher, that can observing same specific paths, and specific extensions. But the paths could by dozens, hundreds or maybe thousand (hope not :P), the same with extensions. The paths and ext are added by user. Creating hundreds of FileSystemWatcher it's not good idea, isn't it? So - how to do it? Is it possible to watch/observing every device (HDDs, SD flash, pendrives, etc.)? Will it be efficient? I don't think so... . Every changing Windows log file, scanning file by antyvirus program - it could realy slow down my program with SystemWatcher :(

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  • oprofile unable to produce call graph

    - by aaa
    hello I am trying to use oprofile to generate call graph. Compiler is g++, platform is linux x86-64, linker is gfortran C++ code is compiled with -fno- omit-frame-pointer. oprofile is started with --callgraph=25. report I run with --callgraph. the call graph is produced but it's only includes self time, which is not much use what am I missing?

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  • How to find the worst performing queries in MS SQL Server 2008?

    - by Thomas Bratt
    How to find the worst performing queries in MS SQL Server 2008? I found the following example but it does not seem to work: SELECT TOP 5 obj.name, max_logical_reads, max_elapsed_time FROM sys.dm_exec_query_stats a CROSS APPLY sys.dm_exec_sql_text(sql_handle) hnd INNER JOIN sys.sysobjects obj on hnd.objectid = obj.id ORDER BY max_logical_reads DESC Taken from: http://www.sqlservercurry.com/2010/03/top-5-costly-stored-procedures-in-sql.html

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  • Reasonably faster way to traverse a directory tree in Python?

    - by Sridhar Ratnakumar
    Assuming that the given directory tree is of reasonable size: say an open source project like Twisted or Python, what is the fastest way to traverse and iterate over the absolute path of all files/directories inside that directory? I want to do this from within Python (subprocess is allowed). os.path.walk is slow. So I tried ls -lR and tree -fi. For a project with about 8337 files (including tmp, pyc, test, .svn files): $ time tree -fi > /dev/null real 0m0.170s user 0m0.044s sys 0m0.123s $ time ls -lR > /dev/null real 0m0.292s user 0m0.138s sys 0m0.152s $ time find . > /dev/null real 0m0.074s user 0m0.017s sys 0m0.056s $ tree appears to be faster than ls -lR (though ls -R is faster than tree, but it does not give full paths). find is the fastest. Can anyone think of a faster and/or better approach? On Windows, I may simply ship a 32-bit binary tree.exe or ls.exe if necessary. Update 1: Added find

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