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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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  • Python Speeding Up Retrieving data from extremely large string

    - by Burninghelix123
    I have a list I converted to a very very long string as I am trying to edit it, as you can gather it's called tempString. It works as of now it just takes way to long to operate, probably because it is several different regex subs. They are as follow: tempString = ','.join(str(n) for n in coords) tempString = re.sub(',{2,6}', '_', tempString) tempString = re.sub("[^0-9\-\.\_]", ",", tempString) tempString = re.sub(',+', ',', tempString) clean1 = re.findall(('[-+]?[0-9]*\.?[0-9]+,[-+]?[0-9]*\.?[0-9]+,' '[-+]?[0-9]*\.?[0-9]+'), tempString) tempString = '_'.join(str(n) for n in clean1) tempString = re.sub(',', ' ', tempString) Basically it's a long string containing commas and about 1-5 million sets of 4 floats/ints (mixture of both possible),: -5.65500020981,6.88999986649,-0.454999923706,1,,,-5.65500020981,6.95499992371,-0.454999923706,1,,, The 4th number in each set I don't need/want, i'm essentially just trying to split the string into a list with 3 floats in each separated by a space. The above code works flawlessly but as you can imagine is quite time consuming on large strings. I have done a lot of research on here for a solution but they all seem geared towards words, i.e. swapping out one word for another. EDIT: Ok so this is the solution i'm currently using: def getValues(s): output = [] while s: # get the three values you want, discard the 3 commas, and the # remainder of the string v1, v2, v3, _, _, _, s = s.split(',', 6) output.append("%s %s %s" % (v1.strip(), v2.strip(), v3.strip())) return output coords = getValues(tempString) Anyone have any advice to speed this up even farther? After running some tests It still takes much longer than i'm hoping for. I've been glancing at numPy, but I honestly have absolutely no idea how to the above with it, I understand that after the above has been done and the values are cleaned up i could use them more efficiently with numPy, but not sure how NumPy could apply to the above. The above to clean through 50k sets takes around 20 minutes, I cant imagine how long it would be on my full string of 1 million sets. I'ts just surprising that the program that originally exported the data took only around 30 secs for the 1 million sets

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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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  • .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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  • 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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  • How to not over-use jQuery?

    - by Fedyashev Nikita
    Typical jQuery over-use: $('button').click(function() { alert('Button clicked: ' + $(this).attr('id')); }); Which can be simplified to: $('button').click(function() { alert('Button clicked: ' + this.id); }); Which is way faster. Can you give me any more examples of similar jQuery over-use?

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  • What's a better choice for SQL-backed number crunching - Ruby 1.9, Python 2, Python 3, or PHP 5.3?

    - by Ivan
    Crterias of 'better': fast im math and simple (little of fields, many records) db transactions, convenient to develop/read/extend, flexible, connectible. The task is to use a common web development scripting language to process and calculate long time series and multidimensional surfaces (mostly selectint/inserting sets of floats and dong maths with rhem). The choice is Ruby 1.9, Python 2, Python 3, PHP 5.3, Perl 5.12, JavaScript (node.js). All the data is to be stored in a relational database (due to its heavily multidimensional nature), all the communication with outer world is to be done by means of web services.

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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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  • mysql_connect "bool $new_link = true" is very slow

    - by Mikk
    Hi, I'm using latest version of Xampp on 64bit Win7. The problem is that, when I use mysql_connect with "bool $new_link" set to true like so: mysql_connect('localhost', 'root', 'my_password', TRUE); script execution time increases dramatically (about 0,5 seconds per connection, and when I have 4 diffirent objects using different connections, it takes ~2 seconds). Is setting "bool $new_link" to true, generally a bad idea or could it just be some problem with my software configuration. Thank you.

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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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  • 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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  • 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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  • 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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  • 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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  • 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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  • Tuning JVM (GC) for high responsive server application

    - by elgcom
    I am running an application server on Linux 64bit with 8 core CPUs and 6 GB memory. The server must be highly responsive. After some inspection I found that the application running on the server creates rather a huge amount of short-lived objects, and has only about 200~400 MB long-lived objects(as long as there is no memory leak) After reading http://java.sun.com/javase/technologies/hotspot/gc/gc_tuning_6.html I use these JVM options -Xms2g -Xmx2g -XX:MaxPermSize=256m -XX:NewRatio=1 -XX:+UseConcMarkSweepGC Result: the minor GC takes 0.01 ~ 0.02 sec, the major GC takes 1 ~ 3 sec the minor GC happens constantly. How can I further improve or tune the JVM? larger heap size? but will it take more time for GC? larger NewSize and MaxNewSize (for young generation)? other collector? parallel GC? is it a good idea to let major GC take place more often? and how?

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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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  • Is GAE Really GZipping My Content? Slow Response Times with GAE as CDN

    - by viatropos
    I am testing out Google App Engine as a free Content Delivery Network and it feels like it's taking a long time to serve up my content. Why does this gae page take a say a half a second to download, while your typical stack overflow page downloads much faster even with a ton more content? What am I missing here? All I have done is create an app and uploaded an image according to that tutorial, but content is being served very slowly it seems. Any suggestions? (Not considering Amazon or other CDNs right now, just looking for help with GAE). Note: I am using Safari when I visit those links, maybe safari is causing problems?

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  • Approach for altering Primary Key from GUID to BigInt in SQL Server related tables

    - by Tom
    I have two tables with 10-20 million rows that have GUID primary keys and at leat 12 tables related via foreign key. The base tables have 10-20 indexes each. We are moving from GUID to BigInt primary keys. I'm wondering if anyone has any suggestions on an approach. Right now this is the approach I'm pondering: Drop all indexes and fkeys on all the tables involved. Add 'NewPrimaryKey' column to each table Make the key identity on the two base tables Script the data change "update table x, set NewPrimaryKey = y where OldPrimaryKey = z Rename the original primarykey to 'oldprimarykey' Rename the 'NewPrimaryKey' column 'PrimaryKey' Script back all the indexes and fkeys Does this seem like a good approach? Does anyone know of a tool or script that would help with this? TD: Edited per additional information. See this blog post that addresses an approach when the GUID is the Primary: http://www.sqlmag.com/blogs/sql-server-questions-answered/sql-server-questions-answered/tabid/1977/entryid/12749/Default.aspx

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  • How to increase query speed without using full-text search?

    - by andre matos
    This is my simple query; By searching selectnothing I'm sure I'll have no hits. SELECT nome_t FROM myTable WHERE nome_t ILIKE '%selectnothing%'; This is the EXPLAIN ANALYZE VERBOSE Seq Scan on myTable (cost=0.00..15259.04 rows=37 width=29) (actual time=2153.061..2153.061 rows=0 loops=1) Output: nome_t Filter: (nome_t ~~* '%selectnothing%'::text) Total runtime: 2153.116 ms myTable has around 350k rows and the table definition is something like: CREATE TABLE myTable ( nome_t text NOT NULL, ) I have an index on nome_t as stated below: CREATE INDEX idx_m_nome_t ON myTable USING btree (nome_t); Although this is clearly a good candidate for Fulltext search I would like to rule that option out for now. This query is meant to be run from a web application and currently it's taking around 2 seconds which is obviously too much; Is there anything I can do, like using other index methods, to improve the speed of this query?

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  • Should I go with Varnish instead of nginx?

    - by gotts
    I really like nginx. But recently I've found that varnish gives you an opportunity to implement smart caching revers proxy layer(with URL purging). I have a cluster of mongrels which are pretty resource-intensive so if this caching layer can remove some load from mongrels this can be a great thing. I didn't find a way to implement the caching layer(with for application pages; static content is cacheable of course) same with nginx.. Should I use Varnish instead? What would you recommend?

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  • Reusing of a PreparedStatement between methods?

    - by MRalwasser
    We all know that we should rather reuse a JDBC PreparedStatement than creating a new instance within a loop. But how to deal with PreparedStatement reuse between different method invocations? Does the reuse-"rule" still count? Should I really consider using a field for the PreparedStatement or should I close and re-create the prepared statement in every invocation? (Of course an instance of such a class would be bound to a Connection which might be a disadvantage) I am aware that the ideal answer might be "it depends". But I am looking for a best practice for less experienced developers that they will do the right choice in most of the cases.

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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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