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  • Sql query: use where in or foreach?

    - by phenevo
    Hi, I'm using query, where the piece is: ...where code in ('va1','var2'...') I have about 50k of this codes. It was working when I has 30k codes, but know I get: The query processor ran out of internal resources and could not produce a query plan. This is a rare event and only expected for extremely complex queries or queries that reference a very large number of tables or partition I think that problem is related with IN... So now I'm planning use foreach(string code in codes) ...where code =code Is it good Idea ??

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  • when is java faster than c++ (or when is JIT faster then precompiled)?

    - by kostja
    I have heard that under certain circumstances, Java programs or rather parts of java programs are able to be executed faster than the "same" code in C++ (or other precompiled code) due to JIT optimizations. This is due to the compiler being able to determine the scope of some variables, avoid some conditionals and pull similar tricks at runtime. Could you give an (or better - some) example, where this applies? And maybe outline the exact conditions under which the compiler is able to optimize the bytecode beyond what is possible with precompiled code? NOTE : This question is not about comparing Java to C++. Its about the possibilities of JIT compiling. Please no flaming. I am also not aware of any duplicates. Please point them out if you are.

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

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

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  • Is there a lightweight datagrid alternative in Flex ?

    - by Wayne
    What is the most performant way of displaying a table of data in Flex? Are there alternatives to the native Flex Datagrid Component? Alternatives that are noted for their rendering speed? Are there other ways to display a table? I have a datagrid with roughly 70 lines and 7 columns of simple text data. This is currently created and loaded in memory. This is being refreshed rapidly (about 800 msec) and there is a slight lag in other animations when it is rendering the table... So I am trying to cut down this render time.

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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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  • Scalability of Ruby on Rails versus PHP

    - by Daniel
    Can anyone comment on which is more scalable between RoR and PHP? I have heard that RoR is less scalable than PHP since RoR has a little more overhead with its MVC framework while PHP is more low level and lighter. This is a bit vague - can anyone explain better?

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  • Hashtable is that fast

    - by Costa
    Hi s[0]*31^(n-1) + s[1]*31^(n-2) + ... + s[n-1]. Is the hash function of the java string, I assume the rest of languages is similar or close to this implementation. If we have hash-Table and a list of 50 elements. each element is 7 chars ABCDEF1, ABCDEF2, ABCDEF3..... ABCDEFn If each bucket of hashtable contains 5 strings (I think this function will make it one string per bucket, but let us assume it is 5). If we call col.Contains("ABCDEFn"); // will do 6 comparisons and discover the difference on the 7th. The hash-table will take around 70 operations (multiplication and additions) to get the hashcode and to compare with 5 strings in bucket. and BANG it found. For list it will take around 300 comparisons to find it. for the case that there is only 10 elements, the list will take around 70 operations but the Hashtable will take around 50 operations. and note that hashtable operations are more time consuming (it is multiplications). I conclude that HybirdDictionary in .Net probably is the best choice for that most cases that require Hashtable with unknown size, because it will let me use a list till the list becomes more than 10 elements. still need something like HashSet rather than a Dictionary of keys and values, I wonder why there is no HybirdSet!! So what do u think? Thanks

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  • Queue-like data structure with fast search and insertion

    - by Max
    I need a datastructure with the following properties: It contains integer numbers, no duplicates. After it reaches the maximal size the first element is removed. So if the capacity is 3, then this is how it would look when putting in it sequential numbers: {}, {1}, {1, 2}, {1, 2, 3}, {2, 3, 4}, {3, 4, 5} etc. Only two operations are needed: inserting a number into this container (INSERT) and checking if the number is already in the container (EXISTS). The number of EXISTS operations is expected to be approximately 2 * number of INSERT operations. I need these operations to be as fast as possible. What would be the fastest data structure or combination of data structures for this scenario?

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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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  • Partitioning requests in code among several servers

    - by Jacques René Mesrine
    I have several forum servers (what they are is irrelevant) which stores posts from users and I want to be able to partition requests among these servers. I'm currently leaning towards partitioning them by geographic location. To improve the locality of data, users will be separated into regions e.g. North America, South America and so on. Is there any design pattern on how to implement the function that maps the partioning property to the server, so that this piece of code has high availability and would not become a single point of failure ? f( Region ) -> Server IP

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  • web service filling gridview awfully slow, as is paging/sorting

    - by nat
    Hi I am making a page which calls a web service to fill a gridview this is returning alot of data, and is horribly slow. i ran the svcutil.exe on the wsdl page and it generated me the class and config so i have a load of strongly typed objects coming back from each request to the many service functions. i am then using LINQ to loop around the objects grabbing the necessary information as i go, but for each row in the grid i need to loop around an object, and grab another list of objects (from the same request) and loop around each of them.. 1 to many parent object child one.. all of this then gets dropped into a custom datatable a row at a time.. hope that makes sense.... im not sure there is any way to speed up the initial load. but surely i should be able to page/sort alot faster than it is doing. as at the moment, it appears to be taking as long to page/sort as it is to load initially. i thought if when i first loaded i put the datasource of the grid in the session, that i could whip it out of the session to deal with paging/sorting and the like. basically it is doing the below protected void Page_Load(object sender, EventArgs e) { //init the datatable //grab the filter vars (if there are any) WebServiceObj WS = WSClient.Method(args); //fill the datatable (around and around we go) foreach (ParentObject po in WS.ReturnedObj) { var COs = from ChildObject c in WS.AnotherReturnedObj where c.whatever.equals(...) ...etc foreach(ChildObject c in COs){ myDataTable.Rows.Add(tlo.this, tlo.that, c.thisthing, c.thatthing, etc......); } } grdListing.DataSource = myDataTable; Session["dt"] = myDataTable; grdListing.DataBind(); } protected void Listing_PageIndexChanging(object sender, GridViewPageEventArgs e) { grdListing.PageIndex = e.NewPageIndex; grdListing.DataSource = Session["dt"] as DataTable; grdListing.DataBind(); } protected void Listing_Sorting(object sender, GridViewSortEventArgs e) { DataTable dt = Session["dt"] as DataTable; DataView dv = new DataView(dt); string sortDirection = " ASC"; if (e.SortDirection == SortDirection.Descending) sortDirection = " DESC"; dv.Sort = e.SortExpression + sortDirection; grdListing.DataSource = dv.ToTable(); grdListing.DataBind(); } am i doing this totally wrongly? or is the slowness just coming from the amount of data being bound in/return from the Web Service.. there are maybe 15 columns(ish) and a whole load of rows.. with more being added to the data the webservice is querying from all the time any suggestions / tips happily received thanks

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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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  • 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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  • 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 there a way to rewrite the SQL query efficiently

    - by user320587
    hi, I have two tables with following definition TableA TableB ID1 ID2 ID3 Value1 Value ID1 Value1 C1 P1 S1 S1 C1 P1 S2 S2 C1 P1 S3 S3 C1 P1 S5 S4 S5 The values are just examples in the table. TableA has a clustered primary key ID1, ID2 & ID3 and TableB has p.k. ID1 I need to create a table that has the missing records in TableA based on TableB The select query I am trying to create should give the following output C1 P1 S4 To do this, I have the following SQL query SELECT DISTINCT TableA.ID1, TableA.ID2, TableB.ID1 FROM TableA a, TableB b WHERE TableB.ID1 NOT IN ( SELECT DISTINCT [ID3] FROM TableA aa WHERE a.ID1 == aa.ID1 AND a.ID2 == aa.ID2 ) Though this query works, it performs poorly and my final TableA may have upto 1M records. is there a way to rewrite this more efficiently. Thanks for any help, Javid

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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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  • MSSQL Server high CPU and I/O activity database tuning

    - by zapping
    Our application tends to be running very slow recently. On debugging and tracing found out that the process is showing high cpu cycles and SQL Server shows high I/O activity. Can you please guide as to how it can be optimised? The application is now about an year old and the database file sizes are not very big or anything. The database is set to auto shrink. Its running on win2003, SQL Server 2005 and the application is a web application coded in c# i.e vs2005

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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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  • MySQL Locking Up

    - by Ian
    I've got a innodb table that gets a lot of reads and almost no writes (like, 1 write for every 400,000 reads approx). I'm running into a pretty big problem though when I do INSERT into the table. MySQL completely locks up. It uses 100% cpu, and every single other table (in other databases even) have their statuses set to "Locked" until the INSERT is done. This is a big problem because MySQL stays locked up for up to 4 minutes. I'm using version 5.1.47 (rpm from mysql.com). Any ideas?

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  • Which memory related Tomcat JVM startup parameters are worth tuning?

    - by knorv
    I'm trying to understand the fine art of tuning Tomcat memory settings. In this quest I have the following three questions: Which memory related JVM startup parameters are worth setting when running Tomcat? Why? What are useful rule-of-thumbs when fine-tuning the memory settings for a Tomcat installation? How do you monitor the memory consumption of your live Tomcat installation?

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