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  • Should the code being tested compile to a DLL or an executable file?

    - by uriDium
    I have a solution with two projects. One for project for the production code and another project for the unit tests. I did this as per the suggestions I got here from SO. I noticed that in the Debug Folder that it includes the production code in executable form. I used NUnit to run the tests after removing the executable and they all fail trying to find the executable. So it definitely is trying to find it. I then did a quick read to find out which is better, a DLL or an executable. It seems that an DLL is much faster as they share memory space where communication between executables is slower. Unforunately our production code needs to be an exectuable. So the unit tests will be slightly slower. I am not too worried about that. But the project does rely on code written in another library which is also in executable format at the moment. Should the projects that expose some sort of SDK rather be compiled to an DLL and then the projects that use the SDK be compiled to executable?

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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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  • Massive speed diff in upgrade to Java 7

    - by Brett Rigby
    We use Java within our build process, as it is used to resolve/publish our dependencies via Ivy. No problem, nor have we had with it for 2 years, until we've tried to upgrade Java 6 Update 26 to Version 7 Update 7, whereas a build on a local developer PC (WinXP) now takes 2 hours to complete, instead of 10 minutes!! Nothing else has changed on the PC, making it the absolute target for our concerns. Does anyone know of any reason as to why version 7 of Java would make such a speed difference like this?

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  • fastest way to crawl recursive ntfs directories in C++

    - by Peter Parker
    I have written a small crawler to scan and resort directory structures. It based on dirent(which is a small wrapper around FindNextFileA) In my first benchmarks it is surprisingy slow: around 123473ms for 4500 files(thinkpad t60p local samsung 320 GB 2.5" HD). 121481 files found in 123473 milliseconds Is this speed normal? This is my code: int testPrintDir(std::string strDir, std::string strPattern="*", bool recurse=true){ struct dirent *ent; DIR *dir; dir = opendir (strDir.c_str()); int retVal = 0; if (dir != NULL) { while ((ent = readdir (dir)) != NULL) { if (strcmp(ent->d_name, ".") !=0 && strcmp(ent->d_name, "..") !=0){ std::string strFullName = strDir +"\\"+std::string(ent->d_name); std::string strType = "N/A"; bool isDir = (ent->data.dwFileAttributes & FILE_ATTRIBUTE_DIRECTORY) !=0; strType = (isDir)?"DIR":"FILE"; if ((!isDir)){ //printf ("%s <%s>\n", strFullName.c_str(),strType.c_str());//ent->d_name); retVal++; } if (isDir && recurse){ retVal += testPrintDir(strFullName, strPattern, recurse); } } } closedir (dir); return retVal; } else { /* could not open directory */ perror ("DIR NOT FOUND!"); return -1; } }

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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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  • Is opening too many datacontexts bad?

    - by ryudice
    I've been checking my application with linq 2 sql profiler, and I noticed that it opens a lot of datacontexts, most of them are opened by the linq datasource I used, since my repositories use only the instance stored in Request.Items, is it bad to open too many datacontext? and how can I make my linqdatasource to use the datacontext that I store in Request.Items for the duration of the request? thanks for any help!

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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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  • Optimizing a shared buffer in a producer/consumer multithreaded environment

    - by Etan
    I have some project where I have a single producer thread which writes events into a buffer, and an additional single consumer thread which takes events from the buffer. My goal is to optimize this thing for a single machine to achieve maximum throughput. Currently, I am using some simple lock-free ring buffer (lock-free is possible since I have only one consumer and one producer thread and therefore the pointers are only updated by a single thread). #define BUF_SIZE 32768 struct buf_t { volatile int writepos; volatile void * buffer[BUF_SIZE]; volatile int readpos;) }; void produce (buf_t *b, void * e) { int next = (b->writepos+1) % BUF_SIZE; while (b->readpos == next); // queue is full. wait b->buffer[b->writepos] = e; b->writepos = next; } void * consume (buf_t *b) { while (b->readpos == b->writepos); // nothing to consume. wait int next = (b->readpos+1) % BUF_SIZE; void * res = b->buffer[b->readpos]; b->readpos = next; return res; } buf_t *alloc () { buf_t *b = (buf_t *)malloc(sizeof(buf_t)); b->writepos = 0; b->readpos = 0; return b; } However, this implementation is not yet fast enough and should be optimized further. I've tried with different BUF_SIZE values and got some speed-up. Additionaly, I've moved writepos before the buffer and readpos after the buffer to ensure that both variables are on different cache lines which resulted also in some speed. What I need is a speedup of about 400 %. Do you have any ideas how I could achieve this using things like padding etc?

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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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  • Why is autorelease especially dangerous/expensive for iPhone applications?

    - by e.James
    I'm looking for a primary source (or a really good explanation) to back up the claim that the use of autorelease is dangerous or overly expensive when writing software for the iPhone. Several developers make this claim, and I have even heard that Apple does not recommend it, but I have not been able to turn up any concrete sources to back it up. SO references: autorelease-iphone Why does this create a memory leak (iPhone)? Note: I can see, from a conceptual point of view, that autorelease is slightly more expensive than a simple call to release, but I don't think that small penalty is enough to make Apple recommend against it. What's the real story?

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  • What is the most efficient way to store a mapping "key -> event stream"?

    - by jkff
    Suppose there are ~10,000's of keys, where each key corresponds to a stream of events. I'd like to support the following operations: push(key, timestamp, event) - pushes event to the event queue for key, marked with the given timestamp. It is guaranteed that event timestamps for a particular key are pushed in sorted or almost sorted order. tail(key, timestamp) - get all events for key since the given timestamp. Usually the timestamp requests for a given key are almost monotonically increasing, almost synchronously with pushes for the same key. This stuff has to be persistent (although it is not absolutely necessary to persist pushes immediately and to keep tails with pushes strictly in sync), so I'm going to use some kind of database. What is the optimal kind of database structure for this task? Would it be better to use a relational database, a key-value storage, or something else?

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  • How to decide on what hardware to deploy web application

    - by Yuval A
    Suppose you have a web application, no specific stack (Java/.NET/LAMP/Django/Rails, all good). How would you decide on which hardware to deploy it? What rules of thumb exist when determining how many machines you need? How would you formulate parameters such as concurrent users, simultaneous connections and DB read/write ratio to a decision on how much, and which, hardware you need? Any resources on this issue would be very helpful...

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  • ~1 second TcpListener Pending()/AcceptTcpClient() lag

    - by cpf
    Probably just watch this video: http://screencast.com/t/OWE1OWVkO As you see, the delay between a connection being initiated (via telnet or firefox) and my program first getting word of it. Here's the code that waits for the connection public IDLServer(System.Net.IPAddress addr,int port) { Listener = new TcpListener(addr, port); Listener.Server.NoDelay = true;//I added this just for testing, it has no impact Listener.Start(); ConnectionThread = new Thread(ConnectionListener); ConnectionThread.Start(); } private void ConnectionListener() { while (Running) { while (Listener.Pending() == false) { System.Threading.Thread.Sleep(1); }//this is the part with the lag Console.WriteLine("Client available");//from this point on everything runs perfectly fast TcpClient cl = Listener.AcceptTcpClient(); Thread proct = new Thread(new ParameterizedThreadStart(InstanceHandler)); proct.Start(cl); } } (I was having some trouble getting the code into a code block) I've tried a couple different things, could it be I'm using TcpClient/Listener instead of a raw Socket object? It's not a mandatory TCP overhead I know, and I've tried running everything in the same thread, etc.

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  • Speeding up jQuery empty() or replaceWith() Functions When Dealing with Large DOM Elements

    - by Levi Hackwith
    Let me start off by apologizing for not giving a code snippet. The project I'm working on is proprietary and I'm afraid I can't show exactly what I'm working on. However, I'll do my best to be descriptive. Here's a breakdown of what goes on in my application: User clicks a button Server retrieves a list of images in the form of a data-table Each row in the table contains 8 data-cells that in turn each contain one hyperlink Each request by the user can contain up to 50 rows (I can change this number if need be) That means the table contains upwards of 800 individual DOM elements My analysis shows that jQuery("#dataTable").empty() and jQuery("#dataTable).replaceWith(tableCloneObject) take up 97% of my overall processing time and take on average 4 - 6 seconds to complete. I'm looking for a way to speed up either of the above mentioned jQuery functions when dealing with massive DOM elements that need to be removed / replaced. I hope my explanation helps.

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  • Avoid having a huge collection of ids by calling a DAO.getAll()

    - by Michael Bavin
    Instead of returning a List<Long> of ids when calling PersonDao.getAll() we wanted not to have an entire collection of ids in memory. Seems like returning a org.springframework.jdbc.support.rowset.SqlRowSet and iterate over this rowset would not hold every object in memory. The only problem here is i cannot cast this row to my entity. Is there a better way for this?

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  • Best method to select an object from another unknown jQuery object

    - by Yosi
    Lets say I have a jQuery object/collection stored in a variable named obj, which should contain a DOM element with an id named target. I don't know in advance if target will be a child in obj, i.e.: obj = $('<div id="parent"><div id="target"></div></div>'); or if obj equals target, i.e.: obj = $('<div id="target"></div>'); or if target is a top-level element inside obj, i.e.: obj = $('<div id="target"/><span id="other"/>'); I need a way to select target from obj, but I don't know in advance when to use .find and when to use .filter. What would be the fastest and/or most concise method of extracting target from obj? What I've come up with is: var $target = obj.find("#target").add(obj.filter("#target")); UPDATE I'm adding solutions to a JSPERF test page to see which one is the best. Currently my solution is still the fastest. Here is the link, please run the tests so that we'll have more data: http://jsperf.com/jquery-selecting-objects

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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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  • 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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  • 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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  • 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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