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  • iPhone and Vertex Buffer Objects

    - by dancer
    I've just started playing around with opengl es on the iphone the past couple of weeks and i'm looking at refactoring some of my code to use Vertex Buffer Objects(VBO). Before I do though I would like to make sure it'll be worth it. The problem is that afaik the only reason you create VBO's is to shift a chunk of data onto the graphics card so that it doesn't need to be retrieved from system ram when it's used. The iPhone however does not have any dedicated ram that I'm aware of so i'm struggling to see why I would benefit at all from using VBO's. I have seen talk around the internet with conflicting opinions and apple certainly want dev's to use it so there's probably still a reason to use them but just wanted to see if anyone on SO had an opinion to add.

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  • JVM tuning on Amazon EC2

    - by Shadowman
    We will be deploying a production application to Amazon EC2 very shortly. Initially, we'll just be using a "small" instance, but have plans to scale up not long afterwards. My question is, has any investigation been done on JVM tuning for the EC2 environment? Are there any specific changes that we should make to our JVM parameters to compensate for quirks/characteristics of Amazon EC2? Or, do the normal tuning methodologies apply here as they would in a physical environment? Our application will be deployed on Tomcat 6.x. It is built using JBoss Seam 2.2.x, and uses PostgreSQL 8.x as the backend database. Any advice you can give is greatly appreciated!

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  • PHP fastest method of reading server response

    - by Peter John
    Hi there, im having some real problems with the lag produced by using fgets to grab the server's response to some batch database calls im making. Im sending through a batch of say, 10,000 calls and ive tracked the lag down to fgets causing the hold up in the speed of my application as the response for each call needs to be grabbed. I have found this thread http://bugs.php.net/bug.php?id=32806 which explains the problem quite well, but hes reading a file, not a server response so fread could be a bit tricky as i could get part of the next line, and extra stuff which i dont want. Any help much appreciated!

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  • Node & Redis: Crucial Design Issues in Production Mode

    - by Ali
    This question is a hybrid one, being both technical and system design related. I'm developing the backend of an application that will handle approx. 4K request per second. We are using Node.js being super fast and in terms of our database struction we are using MongoDB, with Redis being a layer between Node and MongoDB handling volatile operations. I'm quite stressed because we are expecting concurrent requests that we need to handle carefully and we are quite close to launch. However I do not believe I've applied the correct approach on redis. I have a class Student, and they constantly change stages(such as 'active', 'doing homework','in lesson' etc. Thus I created a Redis DB for each state. (1 for being 'active', 2 for being 'doing homework'). Above I have the structure of the 'active' students table; xa5p - JSON stringified object #1 pQrW - JSON stringified object #2 active_student_table - {{studentId:'xa5p'}, {studentId:'pQrW'}} Since there is no 'select all keys method' in Redis, I've been suggested to use a set such that when I run command 'smembers' I receive the keys and later on do 'get' for each id in order to find a specific user (lets say that age older than 15). I've been also suggested that in fact I used never use keys in production mode. My question is, no matter how 'conceptual' it is, what specific things I should avoid doing in Node & Redis in production stage?. Are they any issues related to my design? Students must be objects and I sure can list them in a list but I haven't done yet. Is it that crucial in production stage?

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  • PHP Object References in Frameworks

    - by bigstylee
    Before I dive into the disscusion part a quick question; Is there a method to determine if a variable is a reference to another variable/object? For example $foo = 'Hello World'; $bar = &$foo; echo (is_reference($bar) ? 'Is reference' : 'Is orginal'; I have been using PHP5 for a few years now (personal use only) and I would say I am moderately reversed on the topic of Object Orientated implementation. However the concept of Model View Controller Framework is fairly new to me. I have looked a number of tutorials and looked at some of the open source frameworks (mainly CodeIgnitor) to get a better understanding how everything fits together. I am starting to appreciate the real benefits of using this type of structure. I am used to implementing object referencing in the following technique. class Foo{ public $var = 'Hello World!'; } class Bar{ public function __construct(){ global $Foo; echo $Foo->var; } } $Foo = new Foo; $Bar = new Bar; I was surprised to see that CodeIgnitor and Yii pass referencs of objects and can be accessed via the following method: $this->load->view('argument') The immediate advantage I can see is a lot less code and more user friendly. But I do wonder if it is more efficient as these frameworks are presumably optimised? Or simply to make the code more user friendly? This was an interesting article Do not use PHP references.

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  • Python faster way to read fixed length fields form a file into dictionary

    - by Martlark
    I have a file of names and addresses as follows (example line) OSCAR ,CANNONS ,8 ,STIEGLITZ CIRCUIT And I want to read it into a dictionary of name and value. Here self.field_list is a list of the name, length and start point of the fixed fields in the file. What ways are there to speed up this method? (python 2.6) def line_to_dictionary(self, file_line,rec_num): file_line = file_line.lower() # Make it all lowercase return_rec = {} # Return record as a dictionary for (field_start, field_length, field_name) in self.field_list: field_data = file_line[field_start:field_start+field_length] if (self.strip_fields == True): # Strip off white spaces first field_data = field_data.strip() if (field_data != ''): # Only add non-empty fields to dictionary return_rec[field_name] = field_data # Set hidden fields # return_rec['_rec_num_'] = rec_num return_rec['_dataset_name_'] = self.name return return_rec

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  • SQL Server 2008 BULK INSERT causes more reads than writes. Why?

    - by sh1ng
    I've huge a table (a few billion rows) with a clustered index and two non-clustered indices. A BULK INSERT operation produces 112000 reads and only 383 writes (duration 19948ms). It's very confusing to me. Why do reads exceed writes? How can I reduce it? update query insert bulk DenormalizedPrice4 ([DP_ID] BigInt, [DP_CountryID] Int, [DP_OperatorID] SmallInt, [DP_OperatorPriceID] BigInt, [DP_SpoID] Int, [DP_TourTypeID] Int, [DP_CheckinDate] Date, [DP_CurrencyID] SmallInt, [DP_Cost] Decimal(9,2), [DP_FirstCityID] Int, [DP_FirstHotelID] Int, [DP_FirstBuildingID] Int, [DP_FirstHotelGlobalStarID] Int, [DP_FirstHotelGlobalMealID] Int, [DP_FirstHotelAccommodationTypeID] Int, [DP_FirstHotelRoomCategoryID] Int, [DP_FirstHotelRoomTypeID] Int, [DP_Days] TinyInt, [DP_Nights] TinyInt, [DP_ChildrenCount] TinyInt, [DP_AdultsCount] TinyInt, [DP_TariffID] Int, [DP_DepartureCityID] Int, [DP_DateCreated] SmallDateTime, [DP_DateDenormalized] SmallDateTime, [DP_IsHide] Bit, [DP_FirstHotelAccommodationID] Int) with (CHECK_CONSTRAINTS) No triggers & foreign keys Cluster Index by DP_ID and two non-unique indexes(with fillfactor=90%) And one more thing DB stored on RAID50 with stripe size 256K

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  • Hanging Forms When I Drag And Move My Forms

    - by hosseinsinohe
    I Write a Windows Application By C Sharp. I Use a Picture in Background of my Form (MainForm) And I Use Many Picture in Buttons in This Form,And also I Use Some Panel And Label with Transparent Background Color. My Forms,Panels And Buttons has flicker. I solve this problem by a method in this thread. But Still when other Forms Start over this Form,my Forms hangs when I Drag and Move my Forms over this Form.How can I Solve this Problem to Move And Drags my Forms easily And Speed? Edit:: My Forms Load Data From Access 2007 DataBase file.I Use Datasets,DataGridViews And Other Components to Load And show Data in My Forms.

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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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  • Code runs 6 times slower with 2 threads than with 1

    - by Edward Bird
    So I have written some code to experiment with threads and do some testing. The code should create some numbers and then find the mean of those numbers. I think it is just easier to show you what I have so far. I was expecting with two threads that the code would run about 2 times as fast. Measuring it with a stopwatch I think it runs about 6 times slower! void findmean(std::vector<double>*, std::size_t, std::size_t, double*); int main(int argn, char** argv) { // Program entry point std::cout << "Generating data..." << std::endl; // Create a vector containing many variables std::vector<double> data; for(uint32_t i = 1; i <= 1024 * 1024 * 128; i ++) data.push_back(i); // Calculate mean using 1 core double mean = 0; std::cout << "Calculating mean, 1 Thread..." << std::endl; findmean(&data, 0, data.size(), &mean); mean /= (double)data.size(); // Print result std::cout << " Mean=" << mean << std::endl; // Repeat, using two threads std::vector<std::thread> thread; std::vector<double> result; result.push_back(0.0); result.push_back(0.0); std::cout << "Calculating mean, 2 Threads..." << std::endl; // Run threads uint32_t halfsize = data.size() / 2; uint32_t A = 0; uint32_t B, C, D; // Split the data into two blocks if(data.size() % 2 == 0) { B = C = D = halfsize; } else if(data.size() % 2 == 1) { B = C = halfsize; D = hsz + 1; } // Run with two threads thread.push_back(std::thread(findmean, &data, A, B, &(result[0]))); thread.push_back(std::thread(findmean, &data, C, D , &(result[1]))); // Join threads thread[0].join(); thread[1].join(); // Calculate result mean = result[0] + result[1]; mean /= (double)data.size(); // Print result std::cout << " Mean=" << mean << std::endl; // Return return EXIT_SUCCESS; } void findmean(std::vector<double>* datavec, std::size_t start, std::size_t length, double* result) { for(uint32_t i = 0; i < length; i ++) { *result += (*datavec).at(start + i); } } I don't think this code is exactly wonderful, if you could suggest ways of improving it then I would be grateful for that also.

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  • Speeding up PostgreSQL query where data is between two dates

    - by Roger
    I have a large table ( 50m rows) which has some data with an ID and timestamp. I need to query the table to select all rows with a certain ID where the timestamp is between two dates, but it currently takes over 2 minutes on a high end machine. I'd really like to speed it up. I have found this tip which recommends using a spatial index, but the example it gives is for IP addresses. However, the speed increase (436s to 3s) is impressive. How can I use this with timestamps?

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  • Sql server query using function and view is slower

    - by Lieven Cardoen
    I have a table with a xml column named Data: CREATE TABLE [dbo].[Users]( [UserId] [int] IDENTITY(1,1) NOT NULL, [FirstName] [nvarchar](max) NOT NULL, [LastName] [nvarchar](max) NOT NULL, [Email] [nvarchar](250) NOT NULL, [Password] [nvarchar](max) NULL, [UserName] [nvarchar](250) NOT NULL, [LanguageId] [int] NOT NULL, [Data] [xml] NULL, [IsDeleted] [bit] NOT NULL,... In the Data column there's this xml <data> <RRN>...</RRN> <DateOfBirth>...</DateOfBirth> <Gender>...</Gender> </data> Now, executing this query: SELECT UserId FROM Users WHERE data.value('(/data/RRN)[1]', 'nvarchar(max)') = @RRN after clearing the cache takes (if I execute it a couple of times after each other) 910, 739, 630, 635, ... ms. Now, a db specialist told me that adding a function, a view and changing the query would make it much more faster to search a user with a given RRN. But, instead, these are the results when I execute with the changes from the db specialist: 2584, 2342, 2322, 2383, ... This is the added function: CREATE FUNCTION dbo.fn_Users_RRN(@data xml) RETURNS varchar(100) WITH SCHEMABINDING AS BEGIN RETURN @data.value('(/data/RRN)[1]', 'varchar(max)'); END; The added view: CREATE VIEW vwi_Users WITH SCHEMABINDING AS SELECT UserId, dbo.fn_Users_RRN(Data) AS RRN from dbo.Users Indexes: CREATE UNIQUE CLUSTERED INDEX cx_vwi_Users ON vwi_Users(UserId) CREATE NONCLUSTERED INDEX cx_vwi_Users__RRN ON vwi_Users(RRN) And then the changed query: SELECT UserId FROM Users WHERE dbo.fn_Users_RRN(Data) = '59021626919-61861855-S_FA1E11' Why is the solution with a function and a view going slower?

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  • mysql subquery strangely slow

    - by aviv
    I have a query to select from another sub-query select. While the two queries look almost the same the second query (in this sample) runs much slower: SELECT user.id ,user.first_name -- user.* FROM user WHERE user.id IN (SELECT ref_id FROM education WHERE ref_type='user' AND education.institute_id='58' AND education.institute_type='1' ); This query takes 1.2s Explain on this query results: id select_type table type possible_keys key key_len ref rows Extra 1 PRIMARY user index first_name 152 141192 Using where; Using index 2 DEPENDENT SUBQUERY education index_subquery ref_type,ref_id,institute_id,institute_type,ref_type_2 ref_id 4 func 1 Using where The second query: SELECT -- user.id -- user.first_name user.* FROM user WHERE user.id IN (SELECT ref_id FROM education WHERE ref_type='user' AND education.institute_id='58' AND education.institute_type='1' ); Takes 45sec to run, with explain: id select_type table type possible_keys key key_len ref rows Extra 1 PRIMARY user ALL 141192 Using where 2 DEPENDENT SUBQUERY education index_subquery ref_type,ref_id,institute_id,institute_type,ref_type_2 ref_id 4 func 1 Using where Why is it slower if i query only by index fields? Why both queries scans the full length of the user table? Any ideas how to improve? Thanks.

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  • Unicorn: Which number of worker processes to use?

    - by blackbird07
    I am running a Ruby on Rails app on a virtual Linux server that is capped at 1GB RAM. Currently, I am constantly hitting the limit and would like to optimize memory utilization. One option I am looking at is reducing the number of unicorn workers. So what is the best way to determine the number of unicorn workers to use? The current setting is 10 workers, but the maximum number of requests per second I have seen on Google Analytics Real-Time is 3 (only scored once at a peak time; in 99% of the time not going above 1 request per second). So is it a save assumption that I can - for now - go with 4 workers, leaving room for unexpected amounts of requests? What are the metrics I should have a look at for determining the number of workers and what are the tools I can use for that on my Ubuntu machine?

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  • What limits scaling in this simple OpenMP program?

    - by Douglas B. Staple
    I'm trying to understand limits to parallelization on a 48-core system (4xAMD Opteron 6348, 2.8 Ghz, 12 cores per CPU). I wrote this tiny OpenMP code to test the speedup in what I thought would be the best possible situation (the task is embarrassingly parallel): // Compile with: gcc scaling.c -std=c99 -fopenmp -O3 #include <stdio.h> #include <stdint.h> int main(){ const uint64_t umin=1; const uint64_t umax=10000000000LL; double sum=0.; #pragma omp parallel for reduction(+:sum) for(uint64_t u=umin; u<umax; u++) sum+=1./u/u; printf("%e\n", sum); } I was surprised to find that the scaling is highly nonlinear. It takes about 2.9s for the code to run with 48 threads, 3.1s with 36 threads, 3.7s with 24 threads, 4.9s with 12 threads, and 57s for the code to run with 1 thread. Unfortunately I have to say that there is one process running on the computer using 100% of one core, so that might be affecting it. It's not my process, so I can't end it to test the difference, but somehow I doubt that's making the difference between a 19~20x speedup and the ideal 48x speedup. To make sure it wasn't an OpenMP issue, I ran two copies of the program at the same time with 24 threads each (one with umin=1, umax=5000000000, and the other with umin=5000000000, umax=10000000000). In that case both copies of the program finish after 2.9s, so it's exactly the same as running 48 threads with a single instance of the program. What's preventing linear scaling with this simple program?

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  • Copyrighting software, templates, etc. under real name or screen name?

    - by Abluescarab
    My question is hopefully simple--should I copyright my work (art, software, web design, etc.) under my real name or my screen name? My real name and screen name are also easily connected with a bit of searching, so does it really matter in the end? I'm not a professional (at this point). I read this article: Is it a bad idea to sell Android apps in the Android Market under your real name? and they recommended releasing on the app market under a company name. I also read this article: On what name should I claim copyright in open source software?, but that didn't answer my question. I know it probably matters for big projects, but for little projects, does it matter? Thanks ahead of time!

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  • How large is a "buffer" in PostgreSQL

    - by Konrad Garus
    I am using pg_buffercache module for finding hogs eating up my RAM cache. For example when I run this query: SELECT c.relname, count(*) AS buffers FROM pg_buffercache b INNER JOIN pg_class c ON b.relfilenode = c.relfilenode AND b.reldatabase IN (0, (SELECT oid FROM pg_database WHERE datname = current_database())) GROUP BY c.relname ORDER BY 2 DESC LIMIT 10; I discover that sample_table is using 120 buffers. How much is 120 buffers in bytes?

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  • Pros and Cons of using SqlCommand Prepare in C#?

    - by MadBoy
    When i was reading books to learn C# (might be some old Visual Studio 2005 books) I've encountered advice to always use SqlCommand.Prepare everytime I execute SQL call (whether its' a SELECT/UPDATE or INSERT on SQL SERVER 2005/2008) and I pass parameters to it. But is it really so? Should it be done every time? Or just sometimes? Does it matter whether it's one parameter being passed or five or twenty? What boost should it give if any? Would it be noticeable at all (I've been using SqlCommand.Prepare here and skipped it there and never had any problems or noticeable differences). For the sake of the question this is my usual code that I use, but this is more of a general question. public static decimal pobierzBenchmarkKolejny(string varPortfelID, DateTime data, decimal varBenchmarkPoprzedni, decimal varStopaOdniesienia) { const string preparedCommand = @"SELECT [dbo].[ufn_BenchmarkKolejny](@varPortfelID, @data, @varBenchmarkPoprzedni, @varStopaOdniesienia) AS 'Benchmark'"; using (var varConnection = Locale.sqlConnectOneTime(Locale.sqlDataConnectionDetailsDZP)) //if (varConnection != null) { using (var sqlQuery = new SqlCommand(preparedCommand, varConnection)) { sqlQuery.Prepare(); sqlQuery.Parameters.AddWithValue("@varPortfelID", varPortfelID); sqlQuery.Parameters.AddWithValue("@varStopaOdniesienia", varStopaOdniesienia); sqlQuery.Parameters.AddWithValue("@data", data); sqlQuery.Parameters.AddWithValue("@varBenchmarkPoprzedni", varBenchmarkPoprzedni); using (var sqlQueryResult = sqlQuery.ExecuteReader()) if (sqlQueryResult != null) { while (sqlQueryResult.Read()) { //sqlQueryResult["Benchmark"]; } } } }

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  • NHibernate unintential lazy property loading

    - by chiccodoro
    I introduced a mapping for a business object which has (among others) a property called "Name": public class Foo : BusinessObjectBase { ... public virtual string Name { get; set; } } For some reason, when I fetch "Foo" objects, NHibernate seems to apply lazy property loading (for simple properties, not associations): The following code piece generates n+1 SQL statements, whereof the first only fetches the ids, and the remaining n fetch the Name for each record: ISession session = ...IQuery query = session.CreateQuery(queryString); ITransaction tx = session.BeginTransaction(); List<Foo> result = new List<Foo>(); foreach (Foo foo in query.Enumerable()) { result.Add(foo); } tx.Commit(); session.Close(); produces: NHibernate: select foo0_.FOO_ID as col_0_0_ from V1_FOO foo0_ NHibernate: SELECT foo0_.FOO_ID as FOO1_2_0_, foo0_.NAME as NAME2_0_ FROM V1_FOO foo0_ WHERE foo0_.FOO_ID=:p0;:p0 = 81 NHibernate: SELECT foo0_.FOO_ID as FOO1_2_0_, foo0_.NAME as NAME2_0_ FROM V1_FOO foo0_ WHERE foo0_.FOO_ID=:p0;:p0 = 36470 NHibernate: SELECT foo0_.FOO_ID as FOO1_2_0_, foo0_.NAME as NAME2_0_ FROM V1_FOO foo0_ WHERE foo0_.FOO_ID=:p0;:p0 = 36473 Similarly, the following code leads to a LazyLoadingException after session is closed: ISession session = ... ITransaction tx = session.BeginTransaction(); Foo result = session.Load<Foo>(id); tx.Commit(); session.Close(); Console.WriteLine(result.Name); Following this post, "lazy properties ... is rarely an important feature to enable ... (and) in Hibernate 3, is disabled by default." So what am I doing wrong? I managed to work around the LazyLoadingException by doing a NHibernateUtil.Initialize(foo) but the even worse part are the n+1 sql statements which bring my application to its knees. This is how the mapping looks like: <class name="Foo" table="V1_FOO"> ... <property name="Name" column="NAME"/> </class> BTW: The abstract "BusinessObjectBase" base class encapsulates the ID property which serves as the internal identifier.

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  • A GUID as the MySQL table's Primary Key or as a separate column

    - by Ben
    I have a multi-process program that performs, in a 2 hour period, 5-10 million inserts to a 34GB table within a single Master/Slave MySQL setup (plus an equal number of reads in that period). The table in question has only 5 fields and 3 (single field) indexes. The primary key is auto-incrementing. I am far from a DBA, but the database appears to be crippled during this two hour period. So, I have a couple of general questions. 1) How much bang will I get out of batching these writes into units of 10? Currently, I am writing each insert serially because, after writing, I immediately need to know, in my program, the resulting primary key of each insert. The PK is the only unique field presently and approximating the order of insertion with something like a Datetime field or a multi-column value is not acceptable. If I perform a bulk insert, I won't know these IDs, which is a problem. So, I've been thinking about turning the auto-increment primary key into a GUID and enforcing uniqueness. I've also been kicking around the idea of creating a new column just for the purposes of the GUID. I don't really see the what that achieves though, that the PK approach doesn't already offer. As far as I can tell, the big downside to making the PK a randomly generated number is that the index would take a long time to update on each insert (since insertion order would not be sequential). Is that an acceptable approach for a table that is taking this number of writes? Thanks, Ben

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  • STL find performs bettern than hand-crafter loop

    - by dusha
    Hello all, I have some question. Given the following C++ code fragment: #include <boost/progress.hpp> #include <vector> #include <algorithm> #include <numeric> #include <iostream> struct incrementor { incrementor() : curr_() {} unsigned int operator()() { return curr_++; } private: unsigned int curr_; }; template<class Vec> char const* value_found(Vec const& v, typename Vec::const_iterator i) { return i==v.end() ? "no" : "yes"; } template<class Vec> typename Vec::const_iterator find1(Vec const& v, typename Vec::value_type val) { return find(v.begin(), v.end(), val); } template<class Vec> typename Vec::const_iterator find2(Vec const& v, typename Vec::value_type val) { for(typename Vec::const_iterator i=v.begin(), end=v.end(); i<end; ++i) if(*i==val) return i; return v.end(); } int main() { using namespace std; typedef vector<unsigned int>::const_iterator iter; vector<unsigned int> vec; vec.reserve(10000000); boost::progress_timer pt; generate_n(back_inserter(vec), vec.capacity(), incrementor()); //added this line, to avoid any doubts, that compiler is able to // guess the data is sorted random_shuffle(vec.begin(), vec.end()); cout << "value generation required: " << pt.elapsed() << endl; double d; pt.restart(); iter found=find1(vec, vec.capacity()); d=pt.elapsed(); cout << "first search required: " << d << endl; cout << "first search found value: " << value_found(vec, found)<< endl; pt.restart(); found=find2(vec, vec.capacity()); d=pt.elapsed(); cout << "second search required: " << d << endl; cout << "second search found value: " << value_found(vec, found)<< endl; return 0; } On my machine (Intel i7, Windows Vista) STL find (call via find1) runs about 10 times faster than the hand-crafted loop (call via find2). I first thought that Visual C++ performs some kind of vectorization (may be I am mistaken here), but as far as I can see assembly does not look the way it uses vectorization. Why is STL loop faster? Hand-crafted loop is identical to the loop from the STL-find body. I was asked to post program's output. Without shuffle: value generation required: 0.078 first search required: 0.008 first search found value: no second search required: 0.098 second search found value: no With shuffle (caching effects): value generation required: 1.454 first search required: 0.009 first search found value: no second search required: 0.044 second search found value: no Many thanks, dusha. P.S. I return the iterator and write out the result (found or not), because I would like to prevent compiler optimization, that it thinks the loop is not required at all. The searched value is obviously not in the vector.

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  • Does the order of columns matter in a group by clause?

    - by Jeff Meatball Yang
    If I have two columns, one with very high cardinality and one with very low cardinality (unique # of values), does it matter in which order I group by? Here's an example: select dimensionName, dimensionCategory, sum(someFact) from SomeFact f join SomeDim d on f.dimensionKey = d.dimensionKey group by d.dimensionName, -- large number of unique values d.dimensionCategory -- small number of unique values Are there situations where it matters?

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