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  • Can I improve performance by refactoring SQL commands into classes?

    - by Matthew Jones
    Currently, my entire website does updating from SQL parameterized queries. It works, we've had no problems with it, but it can occasionally be very slow. I was wondering if it makes sense to refactor some of these SQL commands into classes so that we would not have to hit the database so often. I understand hitting the database is generally the slowest part of any web application For example, say we have a class structure like this: Project (comprised of) Tasks (comprised of) Assignments Where Project, Task, and Assignment are classes. At certain points in the site you are only working on one project at a time, and so creating a Project class and passing it among pages (using Session, Profile, something else) might make sense. I imagine this class would have a Save() method to save value changes. Does it make sense to invest the time into doing this? Under what conditions might it be worth it?

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  • Can I improve performance by refactoring SQL commands into C# classes?

    - by Matthew Jones
    Currently, my entire website does updating from SQL parameterized queries. It works, we've had no problems with it, but it can occasionally be very slow. I was wondering if it makes sense to refactor some of these SQL commands into classes so that we would not have to hit the database so often. I understand hitting the database is generally the slowest part of any web application For example, say we have a class structure like this: Project (comprised of) Tasks (comprised of) Assignments Where Project, Task, and Assignment are classes. At certain points in the site you are only working on one project at a time, and so creating a Project class and passing it among pages (using Session, Profile, something else) might make sense. I imagine this class would have a Save() method to save value changes. Does it make sense to invest the time into doing this? Under what conditions might it be worth it?

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  • Is there a performance gain from defining routes in app.yaml versus one large mapping in a WSGIAppli

    - by jgeewax
    Scenario 1 This involves using one "gateway" route in app.yaml and then choosing the RequestHandler in the WSGIApplication. app.yaml - url: /.* script: main.py main.py from google.appengine.ext import webapp class Page1(webapp.RequestHandler): def get(self): self.response.out.write("Page 1") class Page2(webapp.RequestHandler): def get(self): self.response.out.write("Page 2") application = webapp.WSGIApplication([ ('/page1/', Page1), ('/page2/', Page2), ], debug=True) def main(): wsgiref.handlers.CGIHandler().run(application) if __name__ == '__main__': main() Scenario 2: This involves defining two routes in app.yaml and then two separate scripts for each (page1.py and page2.py). app.yaml - url: /page1/ script: page1.py - url: /page2/ script: page2.py page1.py from google.appengine.ext import webapp class Page1(webapp.RequestHandler): def get(self): self.response.out.write("Page 1") application = webapp.WSGIApplication([ ('/page1/', Page1), ], debug=True) def main(): wsgiref.handlers.CGIHandler().run(application) if __name__ == '__main__': main() page2.py from google.appengine.ext import webapp class Page2(webapp.RequestHandler): def get(self): self.response.out.write("Page 2") application = webapp.WSGIApplication([ ('/page2/', Page2), ], debug=True) def main(): wsgiref.handlers.CGIHandler().run(application) if __name__ == '__main__': main() Question What are the benefits and drawbacks of each pattern? Is one much faster than the other?

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  • Tips for improving performance of DB that is above size 40 GB (Sql Server 2005) and growing monthly

    - by HotTester
    The current DB or our project has crossed over 40 GB this month and on an average it is growing monthly by around 3 GB. Now all the tables are best normalized and proper indexing has been used. But still as the size is growing it is taking more time to fire even basic queries like 'select count(1) from table'. So can u share some more points that will help in this front. Database is Sql Server 2005. Further if we implement Partitioning wouldn't it create a overhead ? Thanks in advance.

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  • Drawing performance in Java 6 updates 19,20 versus Java 6 update 3 ?

    - by Pesho
    I'm getting twice the frame rate with the earlier Java 6 u 3, than with the new ones. Very weird. Can anyone give some explanation? On Core 2 Duo 1.83ghz, integrated video (only one core is used) - 1500 (older java) vs 700 fps On Athlon 64 3500+, discrete video - 120 (older java) vs 55 fps The app is a simple game with a moving rectangle. I'm using Graphics2D to draw from a loop.

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  • In Java, is there a performance gain in using interfaces for complex models?

    - by Gnoupi
    The title is hardly understandable, but I'm not sure how to summarize that another way. Any edit to clarify is welcome. I have been told, and recommended to use interfaces to improve performances, even in a case which doesn't especially call for the regular "interface" role. In this case, the objects are big models (in a MVC meaning), with many methods and fields. The "good use" that has been recommended to me is to create an interface, with its unique implementation. There won't be any other class implementing this interface, for sure. I have been told that this is better to do so, because it "exposes less" (or something close) to the other classes which will use methods from this class, as these objects are referring to the object from its interface (all public methods from the implementation being reproduced in the interface). This seems quite strange to me, as it seems like a C++ use to me (with header files). There I see the point, but in Java? Is there really a point in making an interface for such unique implementation? I would really appreciate some clarifications on the topic, so I could justify not following such kind of behavior, and the hassle it creates from duplicating all declarations. Edit: Plenty of valid points in most answers, I'm wondering if I won't switch this question for a community wiki, so we can regroup these points in more structured answers.

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  • What is the most idiomatic way to emulating Perl's Test::More::done_testing?

    - by DVK
    I have to build unit tests for in environment with a very old version of Test::More (perl5.8 with $Test::More::VERSION being '0.80') which predates the addition of done_testing(). Upgrading to newer Test::More is out of the question for practical reasons. And I am trying to avoid using no_tests - it's generally a bad idea not catching when your unit test exits prematurely - say due to some logic not executing when you expected it to. What is the most idiomatic way of running a configurable amount of tests, assuming no no_tests or done_testing() is used? Details: My unit tests usually take the form of: use Test::More; my @test_set = ( [ "Test #1", $param1, $param2, ... ] ,[ "Test #1", $param1, $param2, ... ] # ,... ); foreach my $test (@test_set) { run_test($test); } sub run_test { # $expected_tests += count_tests($test); ok(test1($test)) || diag("Test1 failed"); # ... } The standard approach of use Test::More tests => 23; or BEGIN {plan tests => 23} does not work since both are obviously executed before @tests is known. My current approach involves making @tests global and defining it in the BEGIN {} block as follows: use Test::More; BEGIN { our @test_set = (); # Same set of tests as above my $expected_tests = 0; foreach my $test (@tests) { my $expected_tests += count_tests($test); } plan tests = $expected_tests; } our @test_set; # Must do!!! Since first "our" was in BEGIN's scope :( foreach my $test (@test_set) { run_test($test); } # Same sub run_test {} # Same I feel this can be done more idiomatically but not certain how to improve. Chief among the smells is the duplicate our @test_test declarations - in BEGIN{} and after it. Another approach is to emulate done_testing() by calling Test::More->builder->plan(tests=>$total_tests_calculated). I'm not sure if it's any better idiomatically-wise.

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  • C# why unit test has this strange behaviour?

    - by 5YrsLaterDBA
    I have a class to encrypt the connectionString. public class SKM { private string connStrName = "AndeDBEntities"; internal void encryptConnStr() { if(isConnStrEncrypted()) return; ... } private bool isConnStrEncrypted() { bool status = false; // Open app.config of executable. System.Configuration.Configuration config = ConfigurationManager.OpenExeConfiguration(ConfigurationUserLevel.None); // Get the connection string from the app.config file. string connStr = config.ConnectionStrings.ConnectionStrings[connStrName].ConnectionString; status = !(connStr.Contains("provider")); Log.logItem(LogType.DebugDevelopment, "isConnStrEncrypted", "SKM::isConnStrEncrypted()", "isConnStrEncrypted=" + status); return status; } } Above code works fine in my application. But not in my unit test project. In my unit test project, I test the encryptConnStr() method. it will call isConnStrEncrypted() method. Then exception (null pointer) will be thrown at this line: string connStr = config.ConnectionStrings.ConnectionStrings[connStrName].ConnectionString; I have to use index like this to pass the unit test: string connStr = config.ConnectionStrings.ConnectionStrings[0].ConnectionString; I remember it worked several days ago at the time I added above unit test. But now it give me an error. The unit test is not integrated with our daily auto build yet. We only have ONE connectionStr. It works with product but not in unit test. Don't know why. Anybody can explain to me?

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  • Which one has a faster runtime performance: WPF or Winforms?

    - by Joan Venge
    I know WPF is more complex an flexible so could be thought to do more calculations. But since the rendering is done on the GPU, wouldn't it be faster than Winforms for the same application (functionally and visually)? I mean when you are not running any games or heavy 3d rendering, the GPU isn't doing heavy work, right? Whereas the CPU is always busy. Is this a valid assumption or is the GPU utilization of WPF a very minor operation in its pipeline?

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  • What are various methods for discovering test cases

    - by NativeByte
    All, I am a developer but like to know more about testing process and methods. I believe this helps me write more solid code as it improves the cases I can test using my unit tests before delivering product to the test team. I have recently started looking at Test Driven Development and Exploratory testing approach to software projects. Now it's easier for me to find test cases for the code that I have written. But I am curios to know how to discover test cases when I am not the developer for the functionality under test. Say for e.g. let's have a basic user registration form that we see on various websites. Assuming the person testing it is not the developer of the form, how should one go about testing the input fields on the form, what would be your strategy? How would you discover test cases? I believe this kind of testing benefits from exploratory testing approach, i may be wrong here though. I would appreciate your views on this. Thanks, Byte

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  • When does code bloat start having a noticeable effect on performance?

    - by Kyle
    I am looking to make a hefty shift towards templates in one of my OpenGL projects, mainly for fun and the learning experience. I plan on watching the size of the executable carefully as I do this, to see just how much of the notorious bloat happens. Currently, the size of my Release build is around 580 KB when I favor speed and 440 KB when I favor size. Yes, it's a tiny project, and in fact even if my executable bloats 10 x its size, it's still going to be 5 MB or so, which hardly seems large by today's standards... or is it? This brings me to my question. Is speed proportional to size, or are there leaps and plateaus at certain thresholds, thresholds which I should be aiming to stay below? (And if so, what are the thresholds specifically?)

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  • How can i test my TSQL syntax?

    - by acidzombie24
    Quick question: How do i get some kind of database to use to test my sql syntax and create basic data. I have Sqlite Code which i'll soon put on a server. I have sql server 2008 installed with visual studio 2010. I tried connecting to the database and had no luck. I also tried using a .mdf file instead thinking its a file and i wont have connectivity issues. Wrong, i still couldnt connect and i used this site to help me (i'm aware its 2005) In that case i used var conn = new SqlConnection(@"Server=.\SQLExpress;AttachDbFilename=C:\dev\src\test\SQL_DB_VS_Test\test.mdf;Database=dbo;Trusted_Connection=Yes;"); exception Unable to open the physical file "C:\dev\src\test\SQL_DB_VS_Test\test.mdf". Operating system error 5: "5(Access is denied.)". Cannot attach the file 'C:\dev\src\test\SQL_DB_VS_Test\test.mdf' as database 'dbo'. with trusted = no i get Login failed for user ''. (What user am i suppose to set...). I created the .mdf with visual studio somehow.

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  • How can I compare the performance of log() and fp division in C++?

    - by Ventzi Zhechev
    Hi, I’m using a log-based class in C++ to store very small floating-point values (as the values otherwise go beyond the scope of double). As I’m performing a large number of multiplications, this has the added benefit of converting the multiplications to sums. However, at a certain point in my algorithm, I need to divide a standard double value by an integer value and than do a *= to a log-based value. I have overloaded the *= operator for my log-based class and the right-hand side value is first converted to a log-based value by running log() and than added to the left-hand side value. Thus the operations actually performed are floating-point division, log() and floating-point summation. My question whether it would be faster to first convert the denominator to a log-based value, which would replace the floating-point division with floating-point subtraction, yielding the following chain of operations: twice log(), floating-point subtraction, floating-point summation. In the end, this boils down to whether floating-point division is faster or slower than log(). I suspect that a common answer would be that this is compiler and architecture dependent, so I’ll say that I use gcc 4.2 from Apple on darwin 10.3.0. Still, I hope to get an answer with a general remark on the speed of these two operators and/or an idea on how to measure the difference myself, as there might be more going on here, e.g. executing the constructors that do the type conversion etc. Cheers!

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  • What's best performance way to constantly change image on WP7?

    - by AlRodriguez
    I'm trying to make my own type of remote desktop for WP7. I have a WCF service that returns an image on what's on the target machine's screen. Here's the WCF Server Code: // Method to load desktop image Bitmap image = new Bitmap( ViewSize.Width, ViewSize.Height ); Graphics g = Graphics.FromImage( image ); g.CopyFromScreen( Position.X, Position.Y, 0, 0, ViewSize ); g.Dispose( ); return image; // Convert image to byte[] which is returned to client using ( MemoryStream ms = new MemoryStream( ) ) { Bitmap image = screenGrabber.LoadScreenImage( ); image.Save( ms, ImageFormat.Jpeg ); imageArray = ms.ToArray( ); } Here's the code for the WP7 client: MemoryStream stream = new MemoryStream( data ); BitmapImage image = new BitmapImage( ); image.SetSource( stream ); BackgroundImage.Source = image; The BackgroundImage variable is an Image control. I'm noticing this freeze on the emulator after a short while, and will eventually crash from an OutOfMemoryException. This is already pretty slow ( images show up a good half second later than what's on the screen ), and I'm wondering if there's a better/faster way of doing this? Any help would be great. Thanks in advance.

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  • Why do dicts of defaultdict(int)'s use so much memory? (and other simple python performance question

    - by dukhat
    import numpy as num from collections import defaultdict topKeys = range(16384) keys = range(8192) table = dict((k,defaultdict(int)) for k in topKeys) dat = num.zeros((16384,8192), dtype="int32") print "looping begins" #how much memory should this use? I think it shouldn't use more that a few #times the memory required to hold (16384*8192) int32's (512 mb), but #it uses 11 GB! for k in topKeys: for j in keys: dat[k,j] = table[k][j] print "done" What is going on here? Furthermore, this similar script takes eons to run compared to the first one, and also uses an absurd quantity of memory. topKeys = range(16384) keys = range(8192) table = [(j,0) for k in topKeys for j in keys] I guess python ints might be 64 bit ints, which would account for some of this, but do these relatively natural and simple constructions really produce such a massive overhead? I guess these scripts show that they do, so my question is: what exactly is causing the high memory usage in the first script and the long runtime and high memory usage of the second script and is there any way to avoid these costs?

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  • Basics of Join Factorization

    - by Hong Su
    We continue our series on optimizer transformations with a post that describes the Join Factorization transformation. The Join Factorization transformation was introduced in Oracle 11g Release 2 and applies to UNION ALL queries. Union all queries are commonly used in database applications, especially in data integration applications. In many scenarios the branches in a UNION All query share a common processing, i.e, refer to the same tables. In the current Oracle execution strategy, each branch of a UNION ALL query is evaluated independently, which leads to repetitive processing, including data access and join. The join factorization transformation offers an opportunity to share the common computations across the UNION ALL branches. Currently, join factorization only factorizes common references to base tables only, i.e, not views. Consider a simple example of query Q1. Q1:    select t1.c1, t2.c2    from t1, t2, t3    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2   union all    select t1.c1, t2.c2    from t1, t2, t4    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3; Table t1 appears in both the branches. As does the filter predicates on t1 (t1.c1 > 1) and the join predicates involving t1 (t1.c1 = t2.c1). Nevertheless, without any transformation, the scan (and the filtering) on t1 has to be done twice, once per branch. Such a query may benefit from join factorization which can transform Q1 into Q2 as follows: Q2:    select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                   from t2, t3                    where t2.c2 = t3.c2 and t2.c2 = 2                                  union all                   select t2.c1 item_1, t2.c2 item_2                   from t2, t4                    where t2.c3 = t4.c3) VW_JF_1    where t1.c1 = VW_JF_1.item_1 and t1.c1 > 1; In Q2, t1 is "factorized" and thus the table scan and the filtering on t1 is done only once (it's shared). If t1 is large, then avoiding one extra scan of t1 can lead to a huge performance improvement. Another benefit of join factorization is that it can open up more join orders. Let's look at query Q3. Q3:    select *    from t5, (select t1.c1, t2.c2                  from t1, t2, t3                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2                 union all                  select t1.c1, t2.c2                  from t1, t2, t4                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3) V;   where t5.c1 = V.c1 In Q3, view V is same as Q1. Before join factorization, t1, t2 and t3 must be joined first before they can be joined with t5. But if join factorization factorizes t1 from view V, t1 can then be joined with t5. This opens up new join orders. That being said, join factorization imposes certain join orders. For example, in Q2, t2 and t3 appear in the first branch of the UNION ALL query in view VW_JF_1. T2 must be joined with t3 before it can be joined with t1 which is outside of the VW_JF_1 view. The imposed join order may not necessarily be the best join order. For this reason, join factorization is performed under cost-based transformation framework; this means that we cost the plans with and without join factorization and choose the cheapest plan. Note that if the branches in UNION ALL have DISTINCT clauses, join factorization is not valid. For example, Q4 is NOT semantically equivalent to Q5.   Q4:     select distinct t1.*      from t1, t2      where t1.c1 = t2.c1  union all      select distinct t1.*      from t1, t2      where t1.c1 = t2.c1 Q5:    select distinct t1.*     from t1, (select t2.c1 item_1                   from t2                union all                   select t2.c1 item_1                  from t2) VW_JF_1     where t1.c1 = VW_JF_1.item_1 Q4 might return more rows than Q5. Q5's results are guaranteed to be duplicate free because of the DISTINCT key word at the top level while Q4's results might contain duplicates.   The examples given so far involve inner joins only. Join factorization is also supported in outer join, anti join and semi join. But only the right tables of outer join, anti join and semi joins can be factorized. It is not semantically correct to factorize the left table of outer join, anti join or semi join. For example, Q6 is NOT semantically equivalent to Q7. Q6:     select t1.c1, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t2.c2 (+) = 2  union all    select t1.c1, t2.c2    from t1, t2      where t1.c1 = t2.c1(+) and t2.c2 (+) = 3 Q7:     select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                  from t2                  where t2.c2 = 2                union all                  select t2.c1 item_1, t2.c2 item_2                  from t2                                                                                                    where t2.c2 = 3) VW_JF_1       where t1.c1 = VW_JF_1.item_1(+)                                                                  However, the right side of an outer join can be factorized. For example, join factorization can transform Q8 to Q9 by factorizing t2, which is the right table of an outer join. Q8:    select t1.c2, t2.c2    from t1, t2      where t1.c1 = t2.c1 (+) and t1.c1 = 1 union all    select t1.c2, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t1.c1 = 2 Q9:   select VW_JF_1.item_2, t2.c2   from t2,             (select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 1           union all            select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 2) VW_JF_1   where VW_JF_1.item_1 = t2.c1(+) All of the examples in this blog show factorizing a single table from two branches. This is just for ease of illustration. Join factorization can factorize multiple tables and from more than two UNION ALL branches.  SummaryJoin factorization is a cost-based transformation. It can factorize common computations from branches in a UNION ALL query which can lead to huge performance improvement. 

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