Search Results

Search found 14719 results on 589 pages for 'optimization level'.

Page 81/589 | < Previous Page | 77 78 79 80 81 82 83 84 85 86 87 88  | Next Page >

  • Database design in blogging systems

    - by Peter
    As a learning exercise I'm trying to put myself a blogging system. The goal is to code something that will let me create multiple blogs, like blogger.com or wordpress.com, but much simplified. I would like to ask you, what do you think is best database design for this type of script. Is it better to have one big table, containing posts from all blogs of all users (like friendfeed) or would it be better to create separate table for each blog's posts? Big thanks in advance for your help, Peter.

    Read the article

  • Speed improvements for Perl's chameneos-redux in the Computer Language Benchmarks Game

    - by Robert P
    Ever looked at the Computer Language Benchmarks Game (formerly known as the Great Language Shootout)? Perl has some pretty healthy competition there at the moment. It also occurs to me that there's probably some places that Perl's scores could be improved. The biggest one is in the chameneos-redux script right now—the Perl version runs the worst out of any language: 1,626 times slower than the C baseline solution! There are some restrictions on how the programs can be made and optimized, and there is Perl's interpreted runtime penalty, but 1,626 times? There's got to be something that can get the runtime of this program way down. Taking a look at the source code and the challenge, how can the speed be improved?

    Read the article

  • Ever any performance different between Java >> and >>> right shift operators?

    - by Sean Owen
    Is there ever reason to think the (signed) and (unsigned) right bit-shift operators in Java would perform differently? I can't detect any difference on my machine. This is purely an academic question; it's never going to be the bottleneck I'm sure. I know: it's best to write what you mean foremost; use for division by 2, for example. I assume it comes down to which architectures have which operations implemented as an instruction.

    Read the article

  • How to optimize this MySQL query

    - by James Simpson
    This query was working fine when the database was small, but now that there are millions of rows in the database, I am realizing I should have looked at optimizing this earlier. It is looking at over 600,000 rows and is Using where; Using temporary; Using filesort (which leads to an execution time of 5-10 seconds). It is using an index on the field 'battle_type.' SELECT username, SUM( outcome ) AS wins, COUNT( * ) - SUM( outcome ) AS losses FROM tblBattleHistory WHERE battle_type = '0' && outcome < '2' GROUP BY username ORDER BY wins DESC , losses ASC , username ASC LIMIT 0 , 50

    Read the article

  • Fastest image iteration in Python

    - by Greg
    I am creating a simple green screen app with Python 2.7.4 but am getting quite slow results. I am currently using PIL 1.1.7 to load and iterate the images and saw huge speed-ups changing from the old getpixel() to the newer load() and pixel access object indexing. However the following loop still takes around 2.5 seconds to run for an image of around 720p resolution: def colorclose(Cb_p, Cr_p, Cb_key, Cr_key, tola, tolb): temp = math.sqrt((Cb_key-Cb_p)**2+(Cr_key-Cr_p)**2) if temp < tola: return 0.0 else: if temp < tolb: return (temp-tola)/(tolb-tola) else: return 1.0 .... for x in range(width): for y in range(height): Y, cb, cr = fg_cbcr_list[x, y] mask = colorclose(cb, cr, cb_key, cr_key, tola, tolb) mask = 1 - mask bgr, bgg, bgb = bg_list[x,y] fgr, fgg, fgb = fg_list[x,y] pixels[x,y] = ( (int)(fgr - mask*key_color[0] + mask*bgr), (int)(fgg - mask*key_color[1] + mask*bgg), (int)(fgb - mask*key_color[2] + mask*bgb)) Am I doing anything hugely inefficient here which makes it run so slow? I have seen similar, simpler examples where the loop is replaced by a boolean matrix for instance, but for this case I can't see a way to replace the loop. The pixels[x,y] assignment seems to take the most amount of time but not knowing Python very well I am unsure of a more efficient way to do this. Any help would be appreciated.

    Read the article

  • 3 dimensional bin packing algorithms

    - by BuschnicK
    I'm faced with a 3 dimensional bin packing problem and am currently conducting some preliminary research as to which algorithms/heuristics are currently yielding the best results. Since the problem is NP hard I do not expect to find the optimal solution in every case, but I was wondering: 1) what are the best exact solvers? Branch and Bound? What problem instance sizes can I expect to solve with reasonable computing resources? 2) what are the best heuristic solvers? 3) What off-the-shelf solutions exist to conduct some experiments with?

    Read the article

  • Speed up bitstring/bit operations in Python?

    - by Xavier Ho
    I wrote a prime number generator using Sieve of Eratosthenes and Python 3.1. The code runs correctly and gracefully at 0.32 seconds on ideone.com to generate prime numbers up to 1,000,000. # from bitstring import BitString def prime_numbers(limit=1000000): '''Prime number generator. Yields the series 2, 3, 5, 7, 11, 13, 17, 19, 23, 29 ... using Sieve of Eratosthenes. ''' yield 2 sub_limit = int(limit**0.5) flags = [False, False] + [True] * (limit - 2) # flags = BitString(limit) # Step through all the odd numbers for i in range(3, limit, 2): if flags[i] is False: # if flags[i] is True: continue yield i # Exclude further multiples of the current prime number if i <= sub_limit: for j in range(i*3, limit, i<<1): flags[j] = False # flags[j] = True The problem is, I run out of memory when I try to generate numbers up to 1,000,000,000. flags = [False, False] + [True] * (limit - 2) MemoryError As you can imagine, allocating 1 billion boolean values (1 byte 4 or 8 bytes (see comment) each in Python) is really not feasible, so I looked into bitstring. I figured, using 1 bit for each flag would be much more memory-efficient. However, the program's performance dropped drastically - 24 seconds runtime, for prime number up to 1,000,000. This is probably due to the internal implementation of bitstring. You can comment/uncomment the three lines to see what I changed to use BitString, as the code snippet above. My question is, is there a way to speed up my program, with or without bitstring?

    Read the article

  • C# Improvement on a Fire-and-Forget

    - by adam
    Greetings I have a program that creates multiples instances of a class, runs the same long-running Update method on all instances and waits for completion. I'm following Kev's approach from this question of adding the Update to ThreadPool.QueueUserWorkItem. In the main prog., I'm sleeping for a few minutes and checking a Boolean in the last child to see if done while(!child[child.Length-1].isFinished){ Thread.Sleep(...); } This solution is working the way I want, but is there a better way to do this? Both for the independent instances and checking if all work is done. Thanks

    Read the article

  • Optimizing a lot of Scanner.findWithinHorizon(pattern, 0) calls

    - by darvids0n
    I'm building a process which extracts data from 6 csv-style files and two poorly laid out .txt reports and builds output CSVs, and I'm fully aware that there's going to be some overhead searching through all that whitespace thousands of times, but I never anticipated converting about about 50,000 records would take 12 hours. Excerpt of my manual matching code (I know it's horrible that I use lists of tokens like that, but it was the best thing I could think of): public static String lookup(List<String> tokensBefore, List<String> tokensAfter) { String result = null; while(_match(tokensBefore)) { // block until all input is read if(id.hasNext()) { result = id.next(); // capture the next token that matches if(_matchImmediate(tokensAfter)) // try to match tokensAfter to this result return result; } else return null; // end of file; no match } return null; // no matches } private static boolean _match(List<String> tokens) { return _match(tokens, true); } private static boolean _match(List<String> tokens, boolean block) { if(tokens != null && !tokens.isEmpty()) { if(id.findWithinHorizon(tokens.get(0), 0) == null) return false; for(int i = 1; i <= tokens.size(); i++) { if (i == tokens.size()) { // matches all tokens return true; } else if(id.hasNext() && !id.next().matches(tokens.get(i))) { break; // break to blocking behaviour } } } else { return true; // empty list always matches } if(block) return _match(tokens); // loop until we find something or nothing else return false; // return after just one attempted match } private static boolean _matchImmediate(List<String> tokens) { if(tokens != null) { for(int i = 0; i <= tokens.size(); i++) { if (i == tokens.size()) { // matches all tokens return true; } else if(!id.hasNext() || !id.next().matches(tokens.get(i))) { return false; // doesn't match, or end of file } } return false; // we have some serious problems if this ever gets called } else { return true; // empty list always matches } } Basically wondering how I would work in an efficient string search (Boyer-Moore or similar). My Scanner id is scanning a java.util.String, figured buffering it to memory would reduce I/O since the search here is being performed thousands of times on a relatively small file. The performance increase compared to scanning a BufferedReader(FileReader(File)) was probably less than 1%, the process still looks to be taking a LONG time. I've also traced execution and the slowness of my overall conversion process is definitely between the first and last like of the lookup method. In fact, so much so that I ran a shortcut process to count the number of occurrences of various identifiers in the .csv-style files (I use 2 lookup methods, this is just one of them) and the process completed indexing approx 4 different identifiers for 50,000 records in less than a minute. Compared to 12 hours, that's instant. Some notes (updated): I don't necessarily need the pattern-matching behaviour, I only get the first field of a line of text so I need to match line breaks or use Scanner.nextLine(). All ID numbers I need start at position 0 of a line and run through til the first block of whitespace, after which is the name of the corresponding object. I would ideally want to return a String, not an int locating the line number or start position of the result, but if it's faster then it will still work just fine. If an int is being returned, however, then I would now have to seek to that line again just to get the ID; storing the ID of every line that is searched sounds like a way around that. Anything to help me out, even if it saves 1ms per search, will help, so all input is appreciated. Thankyou! Usage scenario 1: I have a list of objects in file A, who in the old-style system have an id number which is not in file A. It is, however, POSSIBLY in another csv-style file (file B) or possibly still in a .txt report (file C) which each also contain a bunch of other information which is not useful here, and so file B needs to be searched through for the object's full name (1 token since it would reside within the second column of any given line), and then the first column should be the ID number. If that doesn't work, we then have to split the search token by whitespace into separate tokens before doing a search of file C for those tokens as well. Generalised code: String field; for (/* each record in file A */) { /* construct the rest of this object from file A info */ // now to find the ID, if we can List<String> objectName = new ArrayList<String>(1); objectName.add(Pattern.quote(thisObject.fullName)); field = lookup(objectSearchToken, objectName); // search file B if(field == null) // not found in file B { lookupReset(false); // initialise scanner to check file C objectName.clear(); // not using the full name String[] tokens = thisObject.fullName.split(id.delimiter().pattern()); for(String s : tokens) objectName.add(Pattern.quote(s)); field = lookup(objectSearchToken, objectName); // search file C lookupReset(true); // back to file B } else { /* found it, file B specific processing here */ } if(field != null) // found it in B or C thisObject.ID = field; } The objectName tokens are all uppercase words with possible hyphens or apostrophes in them, separated by spaces. Much like a person's name. As per a comment, I will pre-compile the regex for my objectSearchToken, which is just [\r\n]+. What's ending up happening in file C is, every single line is being checked, even the 95% of lines which don't contain an ID number and object name at the start. Would it be quicker to use ^[\r\n]+.*(objectname) instead of two separate regexes? It may reduce the number of _match executions. The more general case of that would be, concatenate all tokensBefore with all tokensAfter, and put a .* in the middle. It would need to be matching backwards through the file though, otherwise it would match the correct line but with a huge .* block in the middle with lots of lines. The above situation could be resolved if I could get java.util.Scanner to return the token previous to the current one after a call to findWithinHorizon. I have another usage scenario. Will put it up asap.

    Read the article

  • sql: Group by x,y,z; return grouped by x,y with lowest f(z)

    - by Sai Emrys
    This is for http://cssfingerprint.com I collect timing stats about how fast the different methods I use perform on different browsers, etc., so that I can optimize the scraping speed. Separately, I have a report about what each method returns for a handful of URLs with known-correct values, so that I can tell which methods are bogus on which browsers. (Each is different, alas.) The related tables look like this: CREATE TABLE `browser_tests` ( `id` int(11) NOT NULL AUTO_INCREMENT, `bogus` tinyint(1) DEFAULT NULL, `result` tinyint(1) DEFAULT NULL, `method` varchar(255) DEFAULT NULL, `url` varchar(255) DEFAULT NULL, `os` varchar(255) DEFAULT NULL, `browser` varchar(255) DEFAULT NULL, `version` varchar(255) DEFAULT NULL, `created_at` datetime DEFAULT NULL, `updated_at` datetime DEFAULT NULL, `user_agent` varchar(255) DEFAULT NULL, PRIMARY KEY (`id`) ) ENGINE=InnoDB AUTO_INCREMENT=33784 DEFAULT CHARSET=latin1 CREATE TABLE `method_timings` ( `id` int(11) NOT NULL AUTO_INCREMENT, `method` varchar(255) DEFAULT NULL, `batch_size` int(11) DEFAULT NULL, `timing` int(11) DEFAULT NULL, `os` varchar(255) DEFAULT NULL, `browser` varchar(255) DEFAULT NULL, `version` varchar(255) DEFAULT NULL, `user_agent` varchar(255) DEFAULT NULL, `created_at` datetime DEFAULT NULL, `updated_at` datetime DEFAULT NULL, PRIMARY KEY (`id`) ) ENGINE=InnoDB AUTO_INCREMENT=28849 DEFAULT CHARSET=latin1 (user_agent is broken down pre-insert into browser, version, and os from a small list of recognized values using regex; I keep the original user-agent string just in case.) I have a query like this that tells me the average timing for every non-bogus browser / version / method tuple: select c, avg(bogus) as bog, timing, method, browser, version from browser_tests as b inner join ( select count(*) as c, round(avg(timing)) as timing, method, browser, version from method_timings group by browser, version, method having c > 10 order by browser, version, timing ) as t using (browser, version, method) group by browser, version, method having bog < 1 order by browser, version, timing; Which returns something like: c bog tim method browser version 88 0.8333 184 reuse_insert Chrome 4.0.249.89 18 0.0000 238 mass_insert_width Chrome 4.0.249.89 70 0.0400 246 mass_insert Chrome 4.0.249.89 70 0.0400 327 mass_noinsert Chrome 4.0.249.89 88 0.0556 367 reuse_reinsert Chrome 4.0.249.89 88 0.0556 383 jquery Chrome 4.0.249.89 88 0.0556 863 full_reinsert Chrome 4.0.249.89 187 0.0000 105 jquery Chrome 5.0.307.11 187 0.8806 109 reuse_insert Chrome 5.0.307.11 123 0.0000 110 mass_insert_width Chrome 5.0.307.11 176 0.0000 231 mass_noinsert Chrome 5.0.307.11 176 0.0000 237 mass_insert Chrome 5.0.307.11 187 0.0000 314 reuse_reinsert Chrome 5.0.307.11 187 0.0000 372 full_reinsert Chrome 5.0.307.11 12 0.7500 82 reuse_insert Chrome 5.0.335.0 12 0.2500 102 jquery Chrome 5.0.335.0 [...] I want to modify this query to return only the browser/version/method with the lowest timing - i.e. something like: 88 0.8333 184 reuse_insert Chrome 4.0.249.89 187 0.0000 105 jquery Chrome 5.0.307.11 12 0.7500 82 reuse_insert Chrome 5.0.335.0 [...] How can I do this, while still returning the method that goes with that lowest timing? I could filter it app-side, but I'd rather do this in mysql since it'd work better with my caching.

    Read the article

  • Explanation of Pingdom Results

    - by Computer Guru
    Hi, I'm trying to optimize my page load times, and I'm using Pingdom to test the site response times. However, I'm not exactly sure what the various components of the "time bar" mean. Example link: http://tools.pingdom.com/fpt/?url=http://neosmart.net/forums//&id=2230361 According to them, the portion of the bar that is yellow is the time between "start" and "connect" and the portion of the bar that is green is the time between "connect" and "first byte" with the blue section being the actual transfer time (time between "first byte" and "last byte"). If I'm trying to the first two (which take very long in my case), what's the recommended course of action? Thanks.

    Read the article

  • iPhone - dequeueReusableCellWithIdentifier usage

    - by Jukurrpa
    Hi, I'm working on a iPhone app which has a pretty large UITableView with data taken from the web, so I'm trying to optimize its creation and usage. I found out that dequeueReusableCellWithIdentifier is pretty useful, but after seeing many source codes using this, I'm wondering if the usage I make of this function is the good one. Here is what people usually do: UITableViewCell* cell = [tableView dequeueReusableCellWithIdentifier:@"Cell"]; if (cell == nil) { cell = [[UITableViewCell alloc] initWithFrame:CGRectZero reuseIdentifier:@"Cell"]; // Add elements to the cell return cell; And here is the way I did it: NSString identifier = [NSString stringWithFormat:@"Cell @d", indexPath.row]: // The cell row UITableViewCell* cell = [tableView dequeueReusableCellWithIdentifier:identifier]; if (cell != nil) return cell; cell = [[UITableViewCell alloc] initWithFrame:CGRectZero reuseIdentifier:identifier]; // Add elements to the cell return cell; The difference is that people use the same identifier for every cell, so dequeuing one only avoids to alloc a new one. For me, the point of queuing was to give each cell a unique identifier, so when the app asks for a cell it already displayed, neither allocation nor element adding have to be done. In fine I don't know which is best, the "common" method ceils the table's memory usage to the exact number of cells it display, whislt the method I use seems to favor speed as it keeps all calculated cells, but can cause large memory consumption (unless there's an inner limit to the queue). Am I wrong to use it this way? Or is it just up to the developper, depending on his needs?

    Read the article

  • Jetty 6 - QueuedThreadPool versus ThreadPool

    - by Walter White
    Hi all, I am using Jetty 6 and was wondering when the QueuedThreadPool should be used over the ThreadPool? By default, Jetty 6 comes configured with the QueuedThreadPool. My server has Java 6 installed so I was thinking that I should use the ThreadPool: <New class="org.mortbay.thread.QueuedThreadPool"> <Set name="minThreads">10</Set> <Set name="maxThreads">200</Set> <Set name="lowThreads">20</Set> <Set name="SpawnOrShrinkAt">2</Set> </New> <New class="org.mortbay.thread.concurrent.ThreadPool"> <Set name="corePoolSize">50</Set> <Set name="maximumPoolSize">50</Set> </New> Thanks, Walter

    Read the article

  • Query Optimizing Request

    - by mithilatw
    I am very sorry if this question is structured in not a very helpful manner or the question itself is not a very good one! I need to update a MSSQL table call component every 10 minutes based on information from another table call materials_progress I have nearly 60000 records in component and more than 10000 records in materials_progress I wrote an update query to do the job, but it takes longer than 4 minutes to complete execution! Here is the query : UPDATE component SET stage_id = CASE WHEN t.required_quantity <= t.total_received THEN 27 WHEN t.total_ordered < t.total_received THEN 18 ELSE 18 END FROM ( SELECT mp.job_id, mp.line_no, mp.component, l.quantity AS line_quantity, CASE WHEN mp.component_name_id = 2 THEN l.quantity*2 ELSE l.quantity END AS required_quantity, SUM(ordered) AS total_ordered, SUM(received) AS total_received , c.component_id FROM line l LEFT JOIN component c ON c.line_id = l.line_id LEFT JOIN materials_progress mp ON l.job_id = mp.job_id AND l.line_no = mp.line_no AND c.component_name_id = mp.component_name_id WHERE mp.job_id IS NOT NULL AND (mp.cancelled IS NULL OR mp.cancelled = 0) AND (mp.manual_override IS NULL OR mp.manual_override = 0) AND c.stage_id = 18 GROUP BY mp.job_id, mp.line_no, mp.component, l.quantity, mp.component_name_id, component_id ) AS t WHERE component.component_id = t.component_id I am not going to explain the scenario as it too complex.. could somebody please please tell me what makes this query this much expensive and a way to get around it? Thank you very very much in advance!!!

    Read the article

  • Two strange efficiency problems in Mathematica

    - by Jess Riedel
    FIRST PROBLEM I have timed how long it takes to compute the following statements (where V[x] is a time-intensive function call): Alice = Table[V[i],{i,1,300},{1000}]; Bob = Table[Table[V[i],{i,1,300}],{1000}]^tr; Chris_pre = Table[V[i],{i,1,300}]; Chris = Table[Chris_pre,{1000}]^tr; Alice, Bob, and Chris are identical matricies computed 3 slightly different ways. I find that Chris is computed 1000 times faster than Alice and Bob. It is not surprising that Alice is computed 1000 times slower because, naively, the function V must be called 1000 more times than when Chris is computed. But it is very surprising that Bob is so slow, since he is computed identically to Chris except that Chris stores the intermediate step Chris_pre. Why does Bob evaluate so slowly? SECOND PROBLEM Suppose I want to compile a function in Mathematica of the form f(x)=x+y where "y" is a constant fixed at compile time (but which I prefer not to directly replace in the code with its numerical because I want to be able to easily change it). If y's actual value is y=7.3, and I define f1=Compile[{x},x+y] f2=Compile[{x},x+7.3] then f1 runs 50% slower than f2. How do I make Mathematica replace "y" with "7.3" when f1 is compiled, so that f1 runs as fast as f2? Many thanks!

    Read the article

  • How to optimize this algorithm?

    - by Bakhtiyor
    I have two sets of arrays like this for example. $Arr1['uid'][]='user 1'; $Arr1['weight'][]=1; $Arr1['uid'][]='user 2'; $Arr1['weight'][]=10; $Arr1['uid'][]='user 3'; $Arr1['weight'][]=5; $Arr2['uid'][]='user 1'; $Arr2['weight'][]=3; $Arr2['uid'][]='user 4'; $Arr2['weight'][]=20; $Arr2['uid'][]='user 5'; $Arr2['weight'][]=15; $Arr2['uid'][]='user 2'; $Arr2['weight'][]=2; The size of two arrays could be different of course. $Arr1 has coefficient of 0.7 and $Arr2 has coefficient of 0.3. I need to calculate following formula $result=$Arr1['weight'][$index]*$Arr1Coeff+$Arr2['weight'][$index]*$Arr2Coeff; where $Arr1['uid']=$Arr2['uid']. So when $Arr1['uid'] doesn't exists in $Arr2 then we need to omit $Arr2 and vice versa. And, here is an algorithm I am using now. foreach($Arr1['uid'] as $index=>$arr1_uid){ $pos=array_search($arr1_uid, $Arr2['uid']); if ($pos===false){ $result=$Arr1['weight'][$index]*$Arr1Coeff; echo "<br>$arr1_uid has not found and RES=".$result; }else{ $result=$Arr1['weight'][$index]*$Arr1Coeff+$Arr2['weight'][$pos]*$Arr2Coeff; echo "<br>$arr1_uid has found on $pos and RES=".$result; } } foreach($Arr2['uid'] as $index=>$arr2_uid){ if (!in_array($arr2_uid, $Arr1['uid'])){ $result=$Arr2['weight'][$index]*$Arr2Coeff; echo "<br>$arr2_uid has not found and RES=".$result; }else{ echo "<br>$arr2_uid has found somewhere"; } } The question is how can I optimize this algorithm? Can you offer other better solution for this problem? Thank you.

    Read the article

  • Iteration speed of int vs long

    - by jqno
    I have the following two programs: long startTime = System.currentTimeMillis(); for (int i = 0; i < N; i++); long endTime = System.currentTimeMillis(); System.out.println("Elapsed time: " + (endTime - startTime) + " msecs"); and long startTime = System.currentTimeMillis(); for (long i = 0; i < N; i++); long endTime = System.currentTimeMillis(); System.out.println("Elapsed time: " + (endTime - startTime) + " msecs"); Note: the only difference is the type of the loop variable (int and long). When I run this, the first program consistently prints between 0 and 16 msecs, regardless of the value of N. The second takes a lot longer. For N == Integer.MAX_VALUE, it runs in about 1800 msecs on my machine. The run time appears to be more or less linear in N. So why is this? I suppose the JIT-compiler optimizes the int loop to death. And for good reason, because obviously it doesn't do anything. But why doesn't it do so for the long loop as well? A colleague thought we might be measuring the JIT compiler doing its work in the long loop, but since the run time seems to be linear in N, this probably isn't the case.

    Read the article

  • Linux PDF/Postscript Optimizing

    - by Sheldon Ross
    So I have a report system built using Java and iText. PDF templates are created using Scribus. The Java code merges the data into the document using iText. The files are then copied over to a NFS share, and a BASH script prints them. I use acroread to convert them to PS, then lpr the PS. The FOSS application pdftops is horribly inefficient. My main problem is that the PDF's generated using iText/Scribus are very large. And I've recently run into the problem where acroread pukes because it hits 4gb of mem usage on large (300+ pages) documents. (Adobe is painfully slow at updating stuff to 64 bit). Now I can use Adobe reader on Windows, and use the Create Print PDF option or whatever its called, and it greatly( 10x) reduces the size of the PDF(it removes alot of metadata about form fields and such it appears) and produces a PDF that is basically a Print image. My question is does anyone know of a good solution/program for doing something similiar on Linux. Ideally, it would optimize the PDF, reduce size, and reduce PS complexity so the printer could print faster as it takes about 15-20 seconds a page to print right now.

    Read the article

  • YUI Compressor and .NET Apps

    - by objektivs
    I want to use YUI Compressor (the original) and use it as part of typical MS build processes (Visual Studio 2008, MSBuild). Does anyone have any guidance or thoughts on this? For example, good ways for incorporating into project, what to do with existing CSS and JS references, and the like. I am happy to hear on the benefits of YUI Compressor .NET and alternatives but I'm mor einterested in use of the original. Thanks Scott

    Read the article

  • text indexes vs integer indexes in mysql

    - by imanc
    Hey, I have always tried to have an integer primary key on a table no matter what. But now I am questioning if this is always necessary. Let's say I have a product table and each product has a globally unique SKU number - that would be a string of say 8-16 characters. Why not make this the PK? Typically I would make this field a unique index but then have an auto incrementing int field as the PK, as I assumed it would be faster, easier to maintain, and would allow me to do things like get the last 5 records added with ease. But in terms of optimisation, assuming I'd only ever be matching the full text field and next doing text matching queries (e.g. like %%) can you guys think of any reasons not to use a text based primary key, most likely of type varchar()? Cheers, imanc

    Read the article

  • What is the most platform- and Python-version-independent way to make a fast loop for use in Python?

    - by Statto
    I'm writing a scientific application in Python with a very processor-intensive loop at its core. I would like to optimise this as far as possible, at minimum inconvenience to end users, who will probably use it as an uncompiled collection of Python scripts, and will be using Windows, Mac, and (mainly Ubuntu) Linux. It is currently written in Python with a dash of NumPy, and I've included the code below. Is there a solution which would be reasonably fast which would not require compilation? This would seem to be the easiest way to maintain platform-independence. If using something like Pyrex, which does require compilation, is there an easy way to bundle many modules and have Python choose between them depending on detected OS and Python version? Is there an easy way to build the collection of modules without needing access to every system with every version of Python? Does one method lend itself particularly to multi-processor optimisation? (If you're interested, the loop is to calculate the magnetic field at a given point inside a crystal by adding together the contributions of a large number of nearby magnetic ions, treated as tiny bar magnets. Basically, a massive sum of these.) # calculate_dipole # ------------------------- # calculate_dipole works out the dipole field at a given point within the crystal unit cell # --- # INPUT # mu = position at which to calculate the dipole field # r_i = array of atomic positions # mom_i = corresponding array of magnetic moments # --- # OUTPUT # B = the B-field at this point def calculate_dipole(mu, r_i, mom_i): relative = mu - r_i r_unit = unit_vectors(relative) #4pi / mu0 (at the front of the dipole eqn) A = 1e-7 #initalise dipole field B = zeros(3,float) for i in range(len(relative)): #work out the dipole field and add it to the estimate so far B += A*(3*dot(mom_i[i],r_unit[i])*r_unit[i] - mom_i[i]) / sqrt(dot(relative[i],relative[i]))**3 return B

    Read the article

  • Mysql - Help me change this single complex query to use temporary tables

    - by sandeepan-nath
    About the system: - There are tutors who create classes and packs - A tags based search approach is being followed.Tag relations are created when new tutors register and when tutors create packs (this makes tutors and packs searcheable). For details please check the section How tags work in this system? below. Following is the concerned query Can anybody help me suggest an approach using temporary tables. We have indexed all the relevant fields and it looks like this is the least time possible with this approach:- SELECT SUM(DISTINCT( t.tag LIKE "%Dictatorship%" OR tt.tag LIKE "%Dictatorship%" OR ttt.tag LIKE "%Dictatorship%" )) AS key_1_total_matches , SUM(DISTINCT( t.tag LIKE "%democracy%" OR tt.tag LIKE "%democracy%" OR ttt.tag LIKE "%democracy%" )) AS key_2_total_matches , COUNT(DISTINCT( od.id_od )) AS tutor_popularity, CASE WHEN ( IF(( wc.id_wc > 0 ), ( wc.wc_api_status = 1 AND wc.wc_type = 0 AND wc.class_date > '2010-06-01 22:00:56' AND wccp.status = 1 AND ( wccp.country_code = 'IE' OR wccp.country_code IN ( 'INT' ) ) ), 0) ) THEN 1 ELSE 0 END AS 'classes_published' , CASE WHEN ( IF(( lp.id_lp > 0 ), ( lp.id_status = 1 AND lp.published = 1 AND lpcp.status = 1 AND ( lpcp.country_code = 'IE' OR lpcp.country_code IN ( 'INT' ) ) ), 0) ) THEN 1 ELSE 0 END AS 'packs_published', td . *, u . * FROM tutor_details AS td JOIN users AS u ON u.id_user = td.id_user LEFT JOIN learning_packs_tag_relations AS lptagrels ON td.id_tutor = lptagrels.id_tutor LEFT JOIN learning_packs AS lp ON lptagrels.id_lp = lp.id_lp LEFT JOIN learning_packs_categories AS lpc ON lpc.id_lp_cat = lp.id_lp_cat LEFT JOIN learning_packs_categories AS lpcp ON lpcp.id_lp_cat = lpc.id_parent LEFT JOIN learning_pack_content AS lpct ON ( lp.id_lp = lpct.id_lp ) LEFT JOIN webclasses_tag_relations AS wtagrels ON td.id_tutor = wtagrels.id_tutor LEFT JOIN webclasses AS wc ON wtagrels.id_wc = wc.id_wc LEFT JOIN learning_packs_categories AS wcc ON wcc.id_lp_cat = wc.id_wp_cat LEFT JOIN learning_packs_categories AS wccp ON wccp.id_lp_cat = wcc.id_parent LEFT JOIN order_details AS od ON td.id_tutor = od.id_author LEFT JOIN orders AS o ON od.id_order = o.id_order LEFT JOIN tutors_tag_relations AS ttagrels ON td.id_tutor = ttagrels.id_tutor LEFT JOIN tags AS t ON t.id_tag = ttagrels.id_tag LEFT JOIN tags AS tt ON tt.id_tag = lptagrels.id_tag LEFT JOIN tags AS ttt ON ttt.id_tag = wtagrels.id_tag WHERE ( u.country = 'IE' OR u.country IN ( 'INT' ) ) AND CASE WHEN ( ( tt.id_tag = lptagrels.id_tag ) AND ( lp.id_lp > 0 ) ) THEN lp.id_status = 1 AND lp.published = 1 AND lpcp.status = 1 AND ( lpcp.country_code = 'IE' OR lpcp.country_code IN ( 'INT' ) ) ELSE 1 END AND CASE WHEN ( ( ttt.id_tag = wtagrels.id_tag ) AND ( wc.id_wc > 0 ) ) THEN wc.wc_api_status = 1 AND wc.wc_type = 0 AND wc.class_date > '2010-06-01 22:00:56' AND wccp.status = 1 AND ( wccp.country_code = 'IE' OR wccp.country_code IN ( 'INT' ) ) ELSE 1 END AND CASE WHEN ( od.id_od > 0 ) THEN od.id_author = td.id_tutor AND o.order_status = 'paid' AND CASE WHEN ( od.id_wc > 0 ) THEN od.can_attend_class = 1 ELSE 1 END ELSE 1 END AND ( t.tag LIKE "%Dictatorship%" OR t.tag LIKE "%democracy%" OR tt.tag LIKE "%Dictatorship%" OR tt.tag LIKE "%democracy%" OR ttt.tag LIKE "%Dictatorship%" OR ttt.tag LIKE "%democracy%" ) GROUP BY td.id_tutor HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 ORDER BY tutor_popularity DESC, u.surname ASC, u.name ASC LIMIT 0, 20 The problem The results returned by the above query are correct (AND logic working as per expectation), but the time taken by the query rises alarmingly for heavier data and for the current data I have it is like 10 seconds as against normal query timings of the order of 0.005 - 0.0002 seconds, which makes it totally unusable. Somebody suggested in my previous question to do the following:- create a temporary table and insert here all relevant data that might end up in the final result set run several updates on this table, joining the required tables one at a time instead of all of them at the same time finally perform a query on this temporary table to extract the end result All this was done in a stored procedure, the end result has passed unit tests, and is blazing fast. I have never worked with temporary tables till now. Only if I could get some hints, kind of schematic representations so that I can start with... Is there something faulty with the query? What can be the reason behind 10+ seconds of execution time? How tags work in this system? When a tutor registers, tags are entered and tag relations are created with respect to tutor's details like name, surname etc. When a Tutors create packs, again tags are entered and tag relations are created with respect to pack's details like pack name, description etc. tag relations for tutors stored in tutors_tag_relations and those for packs stored in learning_packs_tag_relations. All individual tags are stored in tags table. The explain query output:- Please see this screenshot - http://www.test.examvillage.com/Explain_query_improved.jpg

    Read the article

  • Speed improvements for Perl's chameneos-redux script in the Computer Language Benchmarks Game

    - by Robert P
    Ever looked at the Computer Language Benchmarks Game, (formerly known as the Great Language Shootout)? Perl has some pretty healthy competition there at the moment. It also occurs to me that there's probably some places that Perl's scores could be improved. The biggest one is in the chameneos-redux script right now - the Perl version runs the worst out of any language : 1,626 times slower than the C baseline solution! There are some restrictions on how the programs can be made and optimized, and there is Perl's interpreted runtime penalty, but 1,626 times? There's got to be something that can get the runtime of this program way down. Taking a look at the source code and the challenge, what do you think could be done to reduce this runtime speed?

    Read the article

  • Java Integer: what is faster comparison or subtraction?

    - by Vladimir
    I've found that java.lang.Integer implementation of compareTo method looks as follows: public int compareTo(Integer anotherInteger) { int thisVal = this.value; int anotherVal = anotherInteger.value; return (thisVal<anotherVal ? -1 : (thisVal==anotherVal ? 0 : 1)); } The question is why use comparison instead of subtraction: return thisVal - anotherVal;

    Read the article

< Previous Page | 77 78 79 80 81 82 83 84 85 86 87 88  | Next Page >