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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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  • 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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  • 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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  • Slow query with unexpected scan

    - by zerkms
    Hello I have this query: SELECT * FROM SAMPLE SAMPLE INNER JOIN TEST TEST ON SAMPLE.SAMPLE_NUMBER = TEST.SAMPLE_NUMBER INNER JOIN RESULT RESULT ON TEST.TEST_NUMBER = RESULT . TEST_NUMBER WHERE SAMPLED_DATE BETWEEN '2010-03-17 09:00' AND '2010-03-17 12:00' the biggest table here is RESULT, contains 11.1M records. The left 2 tables about 1M. this query works slowly (more than 10 minutes) and returns about 800 records. executing plan shows clustered index scan over all 11M records. RESULT.TEST_NUMBER is a clustered primary key. if I change 2010-03-17 09:00 to 2010-03-17 10:00 - i get about 40 records. it executes for 300ms. and plan shows clustered index seek if i replace * in SELECT clause to RESULT.TEST_NUMBER (covered with index) - then all become fast in first case too. this points to hdd io issues, but doesn't clarifies changing plan. so, any ideas?

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  • Fast read of certain bytes of multiple files in C/C++

    - by Alejandro Cámara
    I've been searching in the web about this question and although there are many similar questions about read/write in C/C++, I haven't found about this specific task. I want to be able to read from multiple files (256x256 files) only sizeof(double) bytes located in a certain position of each file. Right now my solution is, for each file: Open the file (read, binary mode): fstream fTest("current_file", ios_base::out | ios_base::binary); Seek the position I want to read: fTest.seekg(position*sizeof(test_value), ios_base::beg); Read the bytes: fTest.read((char *) &(output[i][j]), sizeof(test_value)); And close the file: fTest.close(); This takes about 350 ms to run inside a for{ for {} } structure with 256x256 iterations (one for each file). Q: Do you think there is a better way to implement this operation? How would you do it?

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  • Are there any tools to optimize the number of consumer and producer threads on a JMS queue?

    - by lindelof
    I'm working on an application that is distributed over two JBoss instances and that produces/consumes JMS messages on several JMS queues. When we configured the application we had to determine which threading model we would use, in particular the number of producing and consuming threads per queue. We have done this in a rather ad-hoc fashion but after reading the most recent columns by Herb Sutter in Dr Dobbs (in particular this one) I would like to size our threads in a more rigorous manner. Are there any methods/tools to measure the throughput of JMS queues (in particular JBoss Messaging queues) as a function of the number of producing/consuming threads?

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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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  • 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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  • Quickest way to compare a bunch of array or list of values.

    - by zapping
    Can you please let me know on the quickest and efficient way to compare a large set of values. Its like there are a list of parent codes(string) and each code has a series of child values(string). The child lists have to be compared with each other and find out duplicates and count how many times they repeat. code1(code1_value1, code1_value2, code3_value3, ..., code1_valueN); code2(code2_value1, code1_value2, code2_value3, ..., code2_valueN); code3(code2_value1, code3_value2, code3_value3, ..., code3_valueN); . . . codeN(codeN_value1, codeN_value2, codeN_value3, ..., codeN_valueN); The lists are huge say like there are 100 parent codes and each has about 250 values in them. There will not be duplicates within a code list. Doing it in java and the solution i could figure out is. Store the values of first set of code in as codeMap.put(codeValue, duplicateCount). The count initialized to 0. Then compare the rest of the values with this. If its in the map then increment the count otherwise append it to the map. The downfall of this is to get the duplicates. Another iteration needs to be performed on a very large list. An alternative is to maintain another hashmap for duplicates like duplicateCodeMap.put(codeValue, duplicateCount) and change the initial hashmap to codeMap.put(codeValue, codeValue). Speed is what is requirement. Hope one of you can help me with it.

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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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  • 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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  • Windows Workflow runs very slowlyh on my DEV machine

    - by Joon
    I am developing an app using WF hosted in IIS as WCF services as a business layer. This runs quickly on any machine running Windows Server 2008 R2, but very slowly on our dev machines, running Windows XP SP3. Yesterday, the workflows were as fast on my dev machine as they are on the server for the whole day. Today, they are back to running slowly again (I rebooted overnight) Has anyone else experienced this problem with workflows running slowly on IIS in XP? What did you do to fix it?

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  • Sql Server 2000 Stored Procedure Prevent Parallelism or something?

    - by user187305
    I have a huge disgusting stored procedure that wasn't slow a couple months ago, but now is. I barely know what this thing does and I am in no way interested in rewriting it. I do know that if I take the body of the stored procedure and then declare/set the values of the parameters and run it in query analyzer that it runs more than 20x faster. From the internet, I've read that this is probably due to a bad cached query plan. So, I've tried running the sp with "WITH RECOMPILE" after the EXEC and I've also tried putting the "WITH RECOMPLE" inside the sp, but neither of those helped even a little bit. When I look at the execution plan of the sp vs the query, the biggest difference is that the sp has "Parallelism" operations all over the place and the query doesn't have any. Can this be the cause of the difference in speeds? Thank you, any ideas would be great... I'm stuck.

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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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  • Have parameters in Dao methods to get entities the most efficient way for read-only access

    - by Blankman
    Allot of my use of hibernate, at least for that data that is presented on many parts of the web application, is for read-only purposes. I want to add some parameters to my Dao methods so I can modify the way hibernate pulls the data and how it handles transactions etc. Example usage: Data on the front page of my website is displayed to the users, it is read-only, so I want to avoid any session/entity tracking that hibernate usually does. This is data that is read-only, will not be changed in this transaction, etc. What would be the most performant way to pull the data? (the code below is c#/nhibernate, I'm implementing this in java as I learn it) public IList<Article> GetArticles() { return Session.CreateCriteria(typeof(Article)) // some where cluase }

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  • Why does Go compile quickly?

    - by Evan Kroske
    I've Googled and poked around the Go website, but I can't seem to find an explanation for Go's extraordinary build times. Are they products of the language features (or lack thereof), a highly optimized compiler, or something else? I'm not trying to promote Go; I'm just curious.

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  • Should I aim for fewer HTTP requests or more cacheable CSS files?

    - by Jonathan Hanson
    We're being told that fewer HTTP requests per page load is a Good Thing. The extreme form of that for CSS would be to have a single, unique CSS file per page, with any shared site-wide styles duplicated in each file. But there's a trade off there. If you have separate shared global CSS files, they can be cached once when the front page is loaded and then re-used on multiple pages, thereby reducing the necessary size of the page-specific CSS files. So which is better in real-world practice? Shorter CSS files through multiple discrete CSS files that are cacheable, or fewer HTTP requests through fewer-but-larger CSS files?

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  • Decent profiler for Windows?

    - by olliej
    Does windows have any decent sampling (eg. non-instrumenting) profilers available? Preferably something akin to Shark on MacOS, although i am willing to accept that i am going to have to pay for such a profiler on windows. I've tried the profiler in VS Team Suite and was not overly impressed, and was wondering if there were any other good ones. [Edit: Erk, i forgot to say this is for C/C++, rather than .NET -- sorry for any confusion]

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  • how to optimize an oracle query that has to_char in where clause for date

    - by panorama12
    I have a table that contains about 49403459 records. I want to query the table on a date range. say 04/10/2010 to 04/10/2010. However, the dates are stored in the table as format 10-APR-10 10.15.06.000000 AM (time stamp). As a result. When I do: SELECT bunch,of,stuff,create_date FROM myTable WHERE TO_CHAR (create_date,'MM/DD/YYYY)' >= '04/10/2010' AND TO_CHAR (create_date, 'MM/DD/YYYY' <= '04/10/2010' I get 529 rows but in 255.59 seconds! which is because I guess I am doing to_char on EACH record. However, When I do SELECT bunch,of,stuff,create_date FROM myTable WHERE create_date >= to_date('04/10/2010','MM/DD/YYYY') AND create_date <= to_date('04/10/2010','MM/DD/YYYY') then I get 0 results in 0.14 seconds. How can I make this query fast and still get valid (529) results?? At this point I can not change indexes. Right now I think index is created on create_date column

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  • Can this loop be sped up in pure Python?

    - by Noctis Skytower
    I was trying out an experiment with Python, trying to find out how many times it could add one to an integer in one minute's time. Assuming two computers are the same except for the speed of the CPUs, this should give an estimate of how fast some CPU operations may take for the computer in question. The code below is an example of a test designed to fulfill the requirements given above. This version is about 20% faster than the first attempt and 150% faster than the third attempt. Can anyone make any suggestions as to how to get the most additions in a minute's time span? Higher numbers are desireable. EDIT: This experiment is being written in Python 3.1 and is 15% faster than the fourth speed-up attempt. def start(seconds): import time, _thread def stop(seconds, signal): time.sleep(seconds) signal.pop() total, signal = 0, [None] _thread.start_new_thread(stop, (seconds, signal)) while signal: total += 1 return total if __name__ == '__main__': print('Testing the CPU speed ...') print('Relative speed:', start(60))

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  • Why are difference lists more efficient than regular concatenation?

    - by Craig Innes
    I am currently working my way through the Learn you a haskell book online, and have come to a chapter where the author is explaining that some list concatenations can be ineffiecient: For example ((((a ++ b) ++ c) ++ d) ++ e) ++ f Is supposedly inefficient. The solution the author comes up with is to use 'difference lists' defined as newtype DiffList a = DiffList {getDiffList :: [a] -> [a] } instance Monoid (DiffList a) where mempty = DiffList (\xs -> [] ++ xs) (DiffList f) `mappend` (DiffList g) = DiffList (\xs -> f (g xs)) I am struggling to understand why DiffList is more computationally efficient than a simple concatenation in some cases. Could someone explain to me in simple terms why the above example is so inefficient, and in what way the DiffList solves this problem?

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  • Definition of Connect, Processing, Waiting in apache bench.

    - by rpatel
    When I run apache bench I get results like: Command: abs.exe -v 3 -n 10 -c 1 https://mysite Connection Times (ms) min mean[+/-sd] median max Connect: 203 213 8.1 219 219 Processing: 78 177 88.1 172 359 Waiting: 78 169 84.6 156 344 Total: 281 389 86.7 391 563 I can't seem to find the definition of Connect, Processing and Waiting. What do those numbers mean?

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  • Time complexity O() of isPalindrome()

    - by Aran
    I have this method, isPalindrome(), and I am trying to find the time complexity of it, and also rewrite the code more efficiently. boolean isPalindrome(String s) { boolean bP = true; for(int i=0; i<s.length(); i++) { if(s.charAt(i) != s.charAt(s.length()-i-1)) { bP = false; } } return bP; } Now I know this code checks the string's characters to see whether it is the same as the one before it and if it is then it doesn't change bP. And I think I know that the operations are s.length(), s.charAt(i) and s.charAt(s.length()-i-!)). Making the time-complexity O(N + 3), I think? This correct, if not what is it and how is that figured out. Also to make this more efficient, would it be good to store the character in temporary strings?

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  • XSLT 1.0: restrict entries in a nodeset

    - by Mike
    Hi, Being relatively new to XSLT I have what I hope is a simple question. I have some flat XML files, which can be pretty big (eg. 7MB) that I need to make 'more hierarchical'. For example, the flat XML might look like this: <D0011> .... .... and it should end up looking like this: <D0011> .... .... I have a working XSLT for this, and it essentially gets a nodeset of all the b elements and then uses the 'following-sibling' axis to get a nodeset of the nodes following the current b node (ie. following-sibling::*[position() =$nodePos]). Then recursion is used to add the siblings into the result tree until another b element is found (I have parameterised it of course, to make it more generic). I also have a solution that just sends the position in the XML of the next b node and selects the nodes after that one after the other (using recursion) via a *[position() = $nodePos] selection. The problem is that the time to execute the transformation increases unacceptably with the size of the XML file. Looking into it with XML Spy it seems that it is the 'following-sibling' and 'position()=' that take the time in the two respective methods. What I really need is a way of restricting the number of nodes in the above selections, so fewer comparisons are performed: every time the position is tested, every node in the nodeset is tested to see if its position is the right one. Is there a way to do that ? Any other suggestions ? Thanks, Mike

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