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  • Implementing synchronous MediaTypeFormatters in ASP.NET Web API

    - by cibrax
    One of main characteristics of MediaTypeFormatter’s in ASP.NET Web API is that they leverage the Task Parallel Library (TPL) for reading or writing an model into an stream. When you derive your class from the base class MediaTypeFormatter, you have to either implement the WriteToStreamAsync or ReadFromStreamAsync methods for writing or reading a model from a stream respectively. These two methods return a Task, which internally does all the serialization work, as it is illustrated bellow. public abstract class MediaTypeFormatter { public virtual Task WriteToStreamAsync(Type type, object value, Stream writeStream, HttpContent content, TransportContext transportContext); public virtual Task<object> ReadFromStreamAsync(Type type, Stream readStream, HttpContent content, IFormatterLogger formatterLogger); }   .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } However, most of the times, serialization is a safe operation that can be done synchronously. In fact, many of the serializer classes you will find in the .NET framework only provide sync methods. So the question is, how you can transform that synchronous work into a Task ?. Creating a new task using the method Task.Factory.StartNew for doing all the serialization work would be probably the typical answer. That would work, as a new task is going to be scheduled. However, that might involve some unnecessary context switches, which are out of our control and might be affect performance on server code specially.   If you take a look at the source code of the MediaTypeFormatters shipped as part of the framework, you will notice that they actually using another pattern, which uses a TaskCompletionSource class. public Task WriteToStreamAsync(Type type, object value, Stream writeStream, HttpContent content, TransportContext transportContext) {   var tsc = new TaskCompletionSource<AsyncVoid>(); tsc.SetResult(default(AsyncVoid));   //Do all the serialization work here synchronously   return tsc.Task; }   /// <summary> /// Used as the T in a "conversion" of a Task into a Task{T} /// </summary> private struct AsyncVoid { } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } They are basically doing all the serialization work synchronously and using a TaskCompletionSource for returning a task already done. To conclude this post, this is another approach you might want to consider when using serializers that are not compatible with an async model. Update: Henrik Nielsen from the ASP.NET team pointed out the existence of a built-in media type formatter for writing sync formatters. BufferedMediaTypeFormatter http://t.co/FxOfeI5x

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  • Software Design & Web Service Design

    - by 001
    I'm about to design my Web service API, most of the functions of my API is basically very simular to my web application. Now the question is, should I create 1 single method and reuse them for both the web application and the web service api? (This seems to be the logical solution, however its very complicated; it's much easier to duplicate the method used by the web application, and keep both separate, ie one method for the web application and one method for the web service.) How do you guys do it? 1) REUSE: one main method and reuse them for both web application and web service application (I like this but it's complicated) WebAppMethodX --uses-- COMMONFUNCTIONMETHOD_X APIMethodX ---uses---- COMMONFUNCTIONMETHOD_X ie common function performs functions such as creating/updating/deleting records etc 2) DUPLICATE: two methods, one method for the web application and one method for the web service. WebAppMethodX APIMethodX

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  • Is there a way that I can hard code a const XmlNameTable to be reused by all of my XmlTextReader(s)?

    - by highone
    Before I continue I would just like to say I know that "Premature optimization is the root of all evil." However this program is only a hobby project and I enjoy trying to find ways to optimize it. That being said, I was reading an article on improving xml performance and it recommended sharing "the XmlNameTable class that is used to store element and attribute names across multiple XML documents of the same type to improve performance." I wasn't able to find any information about doing this in my googling, so it is likely that this is either not possible, a no-no, or a stupid question, but what's the harm in asking?

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  • How to configure the web page of a web application to be browsed maximized ?

    - by user493325
    I have developed a web project using PowerBuilder V12.0 and it is published in ASP.net web file formats (*.aspx). I have hosted my web project on a web server machine with operating system (Windows Server 2003 - Enterprise Edition) and IIS V6.0 as Web Server Hosting Application. I would like to make the home page (Default.aspx) opened maximized so that no internet toolbars appears in the Internet Explorere or any other internet browser like Firefox and so on. It seems this is a web server configuration and setting as now I host the same web application in two development web servers and it opens maximized in one of them and opens normal in the other so No changes are needed in the web project files. I do not know exactly what is this option or configuration,, Is there a property like window size or width and height in web configuration files like web.config and machine.config ? I guess there is a property like WindowSize:Maximized. If you had experience with that before please let me know the options and configurations needed to do that. Thanks for your help.

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  • Best way to handle MySQL date for performance with thousands of users

    - by bitLost
    I am currently part of a team designing a site that will potentially have thousands of users who will be doing a number of date related searches. During the design phase we have been trying to determine which makes more sense for performance optimization. Should we store the datetime field as a mysql datetime. Or should be break it up into a number of fields (year, month, day, hour, minute, ...) The question is with a large data set and a potentially large set of users, would we gain performance wise breaking the datetime into multiple fields and saving on relying on mysql date functions? Or is mysql already optimized for this?

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  • LAMP server has gone down a few times. Ideas for server optimization?

    - by MattB
    Hi all, Our production web server has gone down a few times over the course of the last half year. In the end, we've needed to contact the web host and have them restart as I'm unable to even SSH in. This appears to only affect the web server and not the MySQL database server which is separate. When it affects the web server, all hosted websites time out. I'd like to examine web server optimization/corrections to get to the root of this issue. Any recommendations on how to proceed with that? I'm sure log files would play a role. I'm able to find my way around a Linux-based server and make needed changes, but would be interested in any tips I may not have thought of yet. It may be best for us to speak with an outside consultant as another option. Thanks.

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  • Creating HTML5 Offline Web Applications with ASP.NET

    - by Stephen Walther
    The goal of this blog entry is to describe how you can create HTML5 Offline Web Applications when building ASP.NET web applications. I describe the method that I used to create an offline Web application when building the JavaScript Reference application. You can read about the HTML5 Offline Web Application standard by visiting the following links: Offline Web Applications Firefox Offline Web Applications Safari Offline Web Applications Currently, the HTML5 Offline Web Applications feature works with all modern browsers with one important exception. You can use Offline Web Applications with Firefox, Chrome, and Safari (including iPhone Safari). Unfortunately, however, Internet Explorer does not support Offline Web Applications (not even IE 9). Why Build an HTML5 Offline Web Application? The official reason to build an Offline Web Application is so that you do not need to be connected to the Internet to use it. For example, you can use the JavaScript Reference Application when flying in an airplane, riding a subway, or hiding in a cave in Borneo. The JavaScript Reference Application works great on my iPhone even when I am completely disconnected from any network. The following screenshot shows the JavaScript Reference Application running on my iPhone when airplane mode is enabled (notice the little orange airplane):   Admittedly, it is becoming increasingly difficult to find locations where you can’t get Internet access. A second, and possibly better, reason to create Offline Web Applications is speed. An Offline Web Application must be downloaded only once. After it gets downloaded, all of the files required by your Web application (HTML, CSS, JavaScript, Image) are stored persistently on your computer. Think of Offline Web Applications as providing you with a super browser cache. Normally, when you cache files in a browser, the files are cached on a file-by-file basis. For each HTML, CSS, image, or JavaScript file, you specify how long the file should remain in the cache by setting cache headers. Unlike the normal browser caching mechanism, the HTML5 Offline Web Application cache is used to specify a caching policy for an entire set of files. You use a manifest file to list the files that you want to cache and these files are cached until the manifest is changed. Another advantage of using the HTML5 offline cache is that the HTML5 standard supports several JavaScript events and methods related to the offline cache. For example, you can be notified in your JavaScript code whenever the offline application has been updated. You can use JavaScript methods, such as the ApplicationCache.update() method, to update the cache programmatically. Creating the Manifest File The HTML5 Offline Cache uses a manifest file to determine the files that get cached. Here’s what the manifest file looks like for the JavaScript Reference application: CACHE MANIFEST # v30 Default.aspx # Standard Script Libraries Scripts/jquery-1.4.4.min.js Scripts/jquery-ui-1.8.7.custom.min.js Scripts/jquery.tmpl.min.js Scripts/json2.js # App Scripts App_Scripts/combine.js App_Scripts/combine.debug.js # Content (CSS & images) Content/default.css Content/logo.png Content/ui-lightness/jquery-ui-1.8.7.custom.css Content/ui-lightness/images/ui-bg_glass_65_ffffff_1x400.png Content/ui-lightness/images/ui-bg_glass_100_f6f6f6_1x400.png Content/ui-lightness/images/ui-bg_highlight-soft_100_eeeeee_1x100.png Content/ui-lightness/images/ui-icons_222222_256x240.png Content/ui-lightness/images/ui-bg_glass_100_fdf5ce_1x400.png Content/ui-lightness/images/ui-bg_diagonals-thick_20_666666_40x40.png Content/ui-lightness/images/ui-bg_gloss-wave_35_f6a828_500x100.png Content/ui-lightness/images/ui-icons_ffffff_256x240.png Content/ui-lightness/images/ui-icons_ef8c08_256x240.png Content/browsers/c8.png Content/browsers/es3.png Content/browsers/es5.png Content/browsers/ff3_6.png Content/browsers/ie8.png Content/browsers/ie9.png Content/browsers/sf5.png NETWORK: Services/EntryService.svc http://superexpert.com/resources/JavaScriptReference/ A Cache Manifest file always starts with the line of text Cache Manifest. In the manifest above, all of the CSS, image, and JavaScript files required by the JavaScript Reference application are listed. For example, the Default.aspx ASP.NET page, jQuery library, JQuery UI library, and several images are listed. Notice that you can add comments to a manifest by starting a line with the hash character (#). I use comments in the manifest above to group JavaScript and image files. Finally, notice that there is a NETWORK: section of the manifest. You list any file that you do not want to cache (any file that requires network access) in this section. In the manifest above, the NETWORK: section includes the URL for a WCF Service named EntryService.svc. This service is called to get the JavaScript entries displayed by the JavaScript Reference. There are two important things that you need to be aware of when using a manifest file. First, all relative URLs listed in a manifest are resolved relative to the manifest file. The URLs listed in the manifest above are all resolved relative to the root of the application because the manifest file is located in the application root. Second, whenever you make a change to the manifest file, browsers will download all of the files contained in the manifest (all of them). For example, if you add a new file to the manifest then any browser that supports the Offline Cache standard will detect the change in the manifest and download all of the files listed in the manifest automatically. If you make changes to files in the manifest (for example, modify a JavaScript file) then you need to make a change in the manifest file in order for the new version of the file to be downloaded. The standard way of updating a manifest file is to include a comment with a version number. The manifest above includes a # v30 comment. If you make a change to a file then you need to modify the comment to be # v31 in order for the new file to be downloaded. When Are Updated Files Downloaded? When you make changes to a manifest, the changes are not reflected the very next time you open the offline application in your web browser. Your web browser will download the updated files in the background. This can be very confusing when you are working with JavaScript files. If you make a change to a JavaScript file, and you have cached the application offline, then the changes to the JavaScript file won’t appear when you reload the application. The HTML5 standard includes new JavaScript events and methods that you can use to track changes and make changes to the Application Cache. You can use the ApplicationCache.update() method to initiate an update to the application cache and you can use the ApplicationCache.swapCache() method to switch to the latest version of a cached application. My heartfelt recommendation is that you do not enable your application for offline storage until after you finish writing your application code. Otherwise, debugging the application can become a very confusing experience. Offline Web Applications versus Local Storage Be careful to not confuse the HTML5 Offline Web Application feature and HTML5 Local Storage (aka DOM storage) feature. The JavaScript Reference Application uses both features. HTML5 Local Storage enables you to store key/value pairs persistently. Think of Local Storage as a super cookie. I describe how the JavaScript Reference Application uses Local Storage to store the database of JavaScript entries in a separate blog entry. Offline Web Applications enable you to store static files persistently. Think of Offline Web Applications as a super cache. Creating a Manifest File in an ASP.NET Application A manifest file must be served with the MIME type text/cache-manifest. In order to serve the JavaScript Reference manifest with the proper MIME type, I added two files to the JavaScript Reference Application project: Manifest.txt – This text file contains the actual manifest file. Manifest.ashx – This generic handler sends the Manifest.txt file with the MIME type text/cache-manifest. Here’s the code for the generic handler: using System.Web; namespace JavaScriptReference { public class Manifest : IHttpHandler { public void ProcessRequest(HttpContext context) { context.Response.ContentType = "text/cache-manifest"; context.Response.WriteFile(context.Server.MapPath("Manifest.txt")); } public bool IsReusable { get { return false; } } } } The Default.aspx file contains a reference to the manifest. The opening HTML tag in the Default.aspx file looks like this: <html manifest="Manifest.ashx"> Notice that the HTML tag contains a manifest attribute that points to the Manifest.ashx generic handler. Internet Explorer simply ignores this attribute. Every other modern browser will download the manifest when the Default.aspx page is requested. Seeing the Offline Web Application in Action The experience of using an HTML5 Web Application is different with different browsers. When you first open the JavaScript Reference application with Firefox, you get the following warning: Notice that you are provided with the choice of whether you want to use the application offline or not. Browsers other than Firefox, such as Chrome and Safari, do not provide you with this choice. Chrome and Safari will create an offline cache automatically. If you click the Allow button then Firefox will download all of the files listed in the manifest. You can view the files contained in the Firefox offline application cache by typing about:cache in the Firefox address bar: You can view the actual items being cached by clicking the List Cache Entries link: The Offline Web Application experience is different in the case of Google Chrome. You can view the entries in the offline cache by opening the Developer Tools (hit Shift+CTRL+I), selecting the Storage tab, and selecting Application Cache: Notice that you view the status of the Application Cache. In the screen shot above, the status is UNCACHED which means that the files listed in the manifest have not been downloaded and cached yet. The different possible values for the status are included in the HTML5 Offline Web Application standard: UNCACHED – The Application Cache has not been initialized. IDLE – The Application Cache is not currently being updated. CHECKING – The Application Cache is being fetched and checked for updates. DOWNLOADING – The files in the Application Cache are being updated. UPDATEREADY – There is a new version of the Application. OBSOLETE – The contents of the Application Cache are obsolete. Summary In this blog entry, I provided a description of how you can use the HTML5 Offline Web Application feature in the context of an ASP.NET application. I described how this feature is used with the JavaScript Reference Application to store the entire application on a user’s computer. By taking advantage of this new feature of the HTML5 standard, you can improve the performance of your ASP.NET web applications by requiring users of your web application to download your application once and only once. Furthermore, you can enable users to take advantage of your applications anywhere -- regardless of whether or not they are connected to the Internet.

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  • How does one rein in the complexities of web development ?

    - by Rahul
    I have been a server-side programmer for most of my career and have only recently started spending more time on web development. I am amazed at the number of things I need to master in order to write a decent web application. Just to list down a few tools/technologies I need to learn, Server side programming language (Java/JSP, ASP, PHP, Ruby or something else) A decent web framework (for any medium to big size application). HTML & CSS Javascript Javascript library (JQuery/ExtJS etc. primarily for AJAX). Good to know even if not necessary. At least a basic knowledge of web design - layouts, colors, fonts etc. A good understanding of web security. A good understanding of Performance/scalability issues. Testing, browser compatibility issues etc. The list goes on. So, my question to seasoned web developers is - How do you guys manage to learn and keep yourself updated on so many things? While developing a web application, how do you handle the complexities involved in these areas and yet manage to write an application that is well designed, user friendly, secure, performant and scalable. As a web developer, does one have to be a jack of all trades or should one specialize in one or two areas and leave the rest to other members of the team ?

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  • Are web service handler chains possible under IIS / ASP.NET

    - by Mike
    I'm working with a client who wants me to implement a particular design in an IIS/ASP.NET environment. This design was already implemented in Java, but I am not sure it is possible using Microsoft technologies. In a Tomcat/Java environment one can create so call Handler Chains. In essence a handler runs on the server on which the web service is running and it intercepts the SOAP message coming to the web service. The handler can perform a number of tasks before passing control to the web service. Some of these tasks may refer to authentication and authorization. Moreover, one can create handler chains, such that the handlers can run in a particular sequence before passing control to the web service. This is a very elegant solution, as certain aspects of authentication and authorization can be automatically performed, without the developer of the client application and of the web service having to invest anything in it. The code for the client application and the web service is not affected. You may find a number of articles on internet on this subject by searching on Google for "web service handler chain". I performed searches for web service handlers in IIS or ASP.NET. I get some hits, but apparently handlers in IIS have another meaning than that described above. My question therefor is: Can handler chains (as available in Java and Tomcat) be created in IIS? If so, how (any article, book, forum...)? Either a negative or a positive answer will be greatly appreciated. Mike

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  • Shadow volume shader optimization (GLSL)

    - by Soubok
    I wondering if there is a way to optimize this vertex shader. This vertex shader projects (in the light direction) a vertex to the far plane if it is in the shadow. void main(void) { vec3 lightDir = (gl_ModelViewMatrix * gl_Vertex - gl_LightSource[0].position).xyz; // if the vertex is lit if ( dot(lightDir, gl_NormalMatrix * gl_Normal) < 0.01 ) { // don't move it gl_Position = ftransform(); } else { // move it far, is the light direction vec4 fin = gl_ProjectionMatrix * ( gl_ModelViewMatrix * gl_Vertex + vec4(normalize(lightDir) * 100000.0, 0.0) ); if ( fin.z > fin.w ) // if fin is behind the far plane fin.z = fin.w; // move to the far plane (needed for z-fail algo.) gl_Position = fin; } }

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  • MySql query optimization help

    - by rohitgu
    I have few queries and am not able to figure out how to optimize them, QUERY 1 select * from t_twitter_tracking where classified is null and tweetType='ENGLISH' order by id limit 500; QUERY 2 Select count(*) as cnt, DATE_FORMAT(CONVERT_TZ(wrdTrk.createdOnGMTDate,'+00:00','+05:30'),'%Y-%m-%d') as dat from t_twitter_tracking wrdTrk where wrdTrk.word like ('dell') and CONVERT_TZ(wrdTrk.createdOnGMTDate,'+00:00','+05:30') between '2010-12-12 00:00:00' and '2010-12-26 00:00:00' group by dat; Both these queries run on the same table, CREATE TABLE `t_twitter_tracking` ( `id` BIGINT(20) NOT NULL AUTO_INCREMENT, `word` VARCHAR(200) NOT NULL, `tweetId` BIGINT(100) NOT NULL, `twtText` VARCHAR(800) NULL DEFAULT NULL, `language` TEXT NULL, `links` TEXT NULL, `tweetType` VARCHAR(20) NULL DEFAULT NULL, `source` TEXT NULL, `sourceStripped` TEXT NULL, `isTruncated` VARCHAR(40) NULL DEFAULT NULL, `inReplyToStatusId` BIGINT(30) NULL DEFAULT NULL, `inReplyToUserId` INT(11) NULL DEFAULT NULL, `rtUsrProfilePicUrl` TEXT NULL, `isFavorited` VARCHAR(40) NULL DEFAULT NULL, `inReplyToScreenName` VARCHAR(40) NULL DEFAULT NULL, `latitude` BIGINT(100) NOT NULL, `longitude` BIGINT(100) NOT NULL, `retweetedStatus` VARCHAR(40) NULL DEFAULT NULL, `statusInReplyToStatusId` BIGINT(100) NOT NULL, `statusInReplyToUserId` BIGINT(100) NOT NULL, `statusFavorited` VARCHAR(40) NULL DEFAULT NULL, `statusInReplyToScreenName` TEXT NULL, `screenName` TEXT NULL, `profilePicUrl` TEXT NULL, `twitterId` BIGINT(100) NOT NULL, `name` TEXT NULL, `location` VARCHAR(100) NULL DEFAULT NULL, `bio` TEXT NULL, `url` TEXT NULL COLLATE 'latin1_swedish_ci', `utcOffset` INT(11) NULL DEFAULT NULL, `timeZone` VARCHAR(100) NULL DEFAULT NULL, `frenCnt` BIGINT(20) NULL DEFAULT '0', `createdAt` DATETIME NULL DEFAULT NULL, `createdOnGMT` VARCHAR(40) NULL DEFAULT NULL, `createdOnServerTime` DATETIME NULL DEFAULT NULL, `follCnt` BIGINT(20) NULL DEFAULT '0', `favCnt` BIGINT(20) NULL DEFAULT '0', `totStatusCnt` BIGINT(20) NULL DEFAULT NULL, `usrCrtDate` VARCHAR(200) NULL DEFAULT NULL, `humanSentiment` VARCHAR(30) NULL DEFAULT NULL, `replied` BIT(1) NULL DEFAULT NULL, `replyMsg` TEXT NULL, `classified` INT(32) NULL DEFAULT NULL, `createdOnGMTDate` DATETIME NULL DEFAULT NULL, `locationDetail` TEXT NULL, `geonameid` INT(11) NULL DEFAULT NULL, `country` VARCHAR(255) NULL DEFAULT NULL, `continent` CHAR(2) NULL DEFAULT NULL, `placeLongitude` FLOAT NULL DEFAULT NULL, `placeLatitude` FLOAT NULL DEFAULT NULL, PRIMARY KEY (`id`), INDEX `id` (`id`, `word`), INDEX `createdOnGMT_index` (`createdOnGMT`) USING BTREE, INDEX `word_index` (`word`) USING BTREE, INDEX `location_index` (`location`) USING BTREE, INDEX `classified_index` (`classified`) USING BTREE, INDEX `tweetType_index` (`tweetType`) USING BTREE, INDEX `getunclassified_index` (`classified`, `tweetType`) USING BTREE, INDEX `timeline_index` (`word`, `createdOnGMTDate`, `classified`) USING BTREE, INDEX `createdOnGMTDate_index` (`createdOnGMTDate`) USING BTREE, INDEX `locdetail_index` (`country`, `id`) USING BTREE, FULLTEXT INDEX `twtText_index` (`twtText`) ) COLLATE='utf8_general_ci' ENGINE=MyISAM ROW_FORMAT=DEFAULT AUTO_INCREMENT=12608048; The table has more than 10 million records. How can I optimize it?

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  • Mysql Sub Select Query Optimization

    - by Matt
    I'm running a query daily to compile stats - but it seems really inefficient. This is the Query: SELECT a.id, tstamp, label_id, (SELECT author_id FROM b WHERE b.tid = a.id ORDER BY b.tstamp DESC LIMIT 1) AS author_id FROM a, b WHERE (status = '2' OR status = '3') AND category != 6 AND a.id = b.tid AND (b.type = 'C' OR b.type = 'R') AND a.tstamp1 BETWEEN {$timestamp_start} AND {$timestamp_end} ORDER BY b.tstamp DESC LIMIT 500 This query seems to run really slow. Apologies for the crap naming - I've been asked to not reveal the actual table names. The reason there is a sub select is because the outer select gets one row from the table a and it gets a row from table b. But also need to know the latest author_id from table b as well, so I run a subselect to return that one. I don't want to run another select inside a php loop - as that is also inefficient. It works correctly - I just need to find a much faster way of getting this data set.

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  • Java code optimization on matrix windowing computes in more time

    - by rano
    I have a matrix which represents an image and I need to cycle over each pixel and for each one of those I have to compute the sum of all its neighbors, ie the pixels that belong to a window of radius rad centered on the pixel. I came up with three alternatives: The simplest way, the one that recomputes the window for each pixel The more optimized way that uses a queue to store the sums of the window columns and cycling through the columns of the matrix updates this queue by adding a new element and removing the oldes The even more optimized way that does not need to recompute the queue for each row but incrementally adjusts a previously saved one I implemented them in c++ using a queue for the second method and a combination of deques for the third (I need to iterate through their elements without destructing them) and scored their times to see if there was an actual improvement. it appears that the third method is indeed faster. Then I tried to port the code to Java (and I must admit that I'm not very comfortable with it). I used ArrayDeque for the second method and LinkedLists for the third resulting in the third being inefficient in time. Here is the simplest method in C++ (I'm not posting the java version since it is almost identical): void normalWindowing(int mat[][MAX], int cols, int rows, int rad){ int i, j; int h = 0; for (i = 0; i < rows; ++i) { for (j = 0; j < cols; j++) { h = 0; for (int ry =- rad; ry <= rad; ry++) { int y = i + ry; if (y >= 0 && y < rows) { for (int rx =- rad; rx <= rad; rx++) { int x = j + rx; if (x >= 0 && x < cols) { h += mat[y][x]; } } } } } } } Here is the second method (the one optimized through columns) in C++: void opt1Windowing(int mat[][MAX], int cols, int rows, int rad){ int i, j, h, y, col; queue<int>* q = NULL; for (i = 0; i < rows; ++i) { if (q != NULL) delete(q); q = new queue<int>(); h = 0; for (int rx = 0; rx <= rad; rx++) { if (rx < cols) { int mem = 0; for (int ry =- rad; ry <= rad; ry++) { y = i + ry; if (y >= 0 && y < rows) { mem += mat[y][rx]; } } q->push(mem); h += mem; } } for (j = 1; j < cols; j++) { col = j + rad; if (j - rad > 0) { h -= q->front(); q->pop(); } if (j + rad < cols) { int mem = 0; for (int ry =- rad; ry <= rad; ry++) { y = i + ry; if (y >= 0 && y < rows) { mem += mat[y][col]; } } q->push(mem); h += mem; } } } } And here is the Java version: public static void opt1Windowing(int [][] mat, int rad){ int i, j = 0, h, y, col; int cols = mat[0].length; int rows = mat.length; ArrayDeque<Integer> q = null; for (i = 0; i < rows; ++i) { q = new ArrayDeque<Integer>(); h = 0; for (int rx = 0; rx <= rad; rx++) { if (rx < cols) { int mem = 0; for (int ry =- rad; ry <= rad; ry++) { y = i + ry; if (y >= 0 && y < rows) { mem += mat[y][rx]; } } q.addLast(mem); h += mem; } } j = 0; for (j = 1; j < cols; j++) { col = j + rad; if (j - rad > 0) { h -= q.peekFirst(); q.pop(); } if (j + rad < cols) { int mem = 0; for (int ry =- rad; ry <= rad; ry++) { y = i + ry; if (y >= 0 && y < rows) { mem += mat[y][col]; } } q.addLast(mem); h += mem; } } } } I recognize this post will be a wall of text. Here is the third method in C++: void opt2Windowing(int mat[][MAX], int cols, int rows, int rad){ int i = 0; int j = 0; int h = 0; int hh = 0; deque< deque<int> *> * M = new deque< deque<int> *>(); for (int ry = 0; ry <= rad; ry++) { if (ry < rows) { deque<int> * q = new deque<int>(); M->push_back(q); for (int rx = 0; rx <= rad; rx++) { if (rx < cols) { int val = mat[ry][rx]; q->push_back(val); h += val; } } } } deque<int> * C = new deque<int>(M->front()->size()); deque<int> * Q = new deque<int>(M->front()->size()); deque<int> * R = new deque<int>(M->size()); deque< deque<int> *>::iterator mit; deque< deque<int> *>::iterator mstart = M->begin(); deque< deque<int> *>::iterator mend = M->end(); deque<int>::iterator rit; deque<int>::iterator rstart = R->begin(); deque<int>::iterator rend = R->end(); deque<int>::iterator cit; deque<int>::iterator cstart = C->begin(); deque<int>::iterator cend = C->end(); for (mit = mstart, rit = rstart; mit != mend, rit != rend; ++mit, ++rit) { deque<int>::iterator pit; deque<int>::iterator pstart = (* mit)->begin(); deque<int>::iterator pend = (* mit)->end(); for(cit = cstart, pit = pstart; cit != cend && pit != pend; ++cit, ++pit) { (* cit) += (* pit); (* rit) += (* pit); } } for (i = 0; i < rows; ++i) { j = 0; if (i - rad > 0) { deque<int>::iterator cit; deque<int>::iterator cstart = C->begin(); deque<int>::iterator cend = C->end(); deque<int>::iterator pit; deque<int>::iterator pstart = (M->front())->begin(); deque<int>::iterator pend = (M->front())->end(); for(cit = cstart, pit = pstart; cit != cend; ++cit, ++pit) { (* cit) -= (* pit); } deque<int> * k = M->front(); M->pop_front(); delete k; h -= R->front(); R->pop_front(); } int row = i + rad; if (row < rows && i > 0) { deque<int> * newQ = new deque<int>(); M->push_back(newQ); deque<int>::iterator cit; deque<int>::iterator cstart = C->begin(); deque<int>::iterator cend = C->end(); int rx; int tot = 0; for (rx = 0, cit = cstart; rx <= rad; rx++, ++cit) { if (rx < cols) { int val = mat[row][rx]; newQ->push_back(val); (* cit) += val; tot += val; } } R->push_back(tot); h += tot; } hh = h; copy(C->begin(), C->end(), Q->begin()); for (j = 1; j < cols; j++) { int col = j + rad; if (j - rad > 0) { hh -= Q->front(); Q->pop_front(); } if (j + rad < cols) { int val = 0; for (int ry =- rad; ry <= rad; ry++) { int y = i + ry; if (y >= 0 && y < rows) { val += mat[y][col]; } } hh += val; Q->push_back(val); } } } } And finally its Java version: public static void opt2Windowing(int [][] mat, int rad){ int cols = mat[0].length; int rows = mat.length; int i = 0; int j = 0; int h = 0; int hh = 0; LinkedList<LinkedList<Integer>> M = new LinkedList<LinkedList<Integer>>(); for (int ry = 0; ry <= rad; ry++) { if (ry < rows) { LinkedList<Integer> q = new LinkedList<Integer>(); M.addLast(q); for (int rx = 0; rx <= rad; rx++) { if (rx < cols) { int val = mat[ry][rx]; q.addLast(val); h += val; } } } } int firstSize = M.getFirst().size(); int mSize = M.size(); LinkedList<Integer> C = new LinkedList<Integer>(); LinkedList<Integer> Q = null; LinkedList<Integer> R = new LinkedList<Integer>(); for (int k = 0; k < firstSize; k++) { C.add(0); } for (int k = 0; k < mSize; k++) { R.add(0); } ListIterator<LinkedList<Integer>> mit; ListIterator<Integer> rit; ListIterator<Integer> cit; ListIterator<Integer> pit; for (mit = M.listIterator(), rit = R.listIterator(); mit.hasNext();) { Integer r = rit.next(); int rsum = 0; for (cit = C.listIterator(), pit = (mit.next()).listIterator(); cit.hasNext();) { Integer c = cit.next(); Integer p = pit.next(); rsum += p; cit.set(c + p); } rit.set(r + rsum); } for (i = 0; i < rows; ++i) { j = 0; if (i - rad > 0) { for(cit = C.listIterator(), pit = M.getFirst().listIterator(); cit.hasNext();) { Integer c = cit.next(); Integer p = pit.next(); cit.set(c - p); } M.removeFirst(); h -= R.getFirst(); R.removeFirst(); } int row = i + rad; if (row < rows && i > 0) { LinkedList<Integer> newQ = new LinkedList<Integer>(); M.addLast(newQ); int rx; int tot = 0; for (rx = 0, cit = C.listIterator(); rx <= rad; rx++) { if (rx < cols) { Integer c = cit.next(); int val = mat[row][rx]; newQ.addLast(val); cit.set(c + val); tot += val; } } R.addLast(tot); h += tot; } hh = h; Q = new LinkedList<Integer>(); Q.addAll(C); for (j = 1; j < cols; j++) { int col = j + rad; if (j - rad > 0) { hh -= Q.getFirst(); Q.pop(); } if (j + rad < cols) { int val = 0; for (int ry =- rad; ry <= rad; ry++) { int y = i + ry; if (y >= 0 && y < rows) { val += mat[y][col]; } } hh += val; Q.addLast(val); } } } } I guess that most is due to the poor choice of the LinkedList in Java and to the lack of an efficient (not shallow) copy method between two LinkedList. How can I improve the third Java method? Am I doing some conceptual error? As always, any criticisms is welcome. UPDATE Even if it does not solve the issue, using ArrayLists, as being suggested, instead of LinkedList improves the third method. The second one performs still better (but when the number of rows and columns of the matrix is lower than 300 and the window radius is small the first unoptimized method is the fastest in Java)

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  • Matlab: Optimization by perturbing variable

    - by S_H
    My main script contains following code: %# Grid and model parameters nModel=50; nModel_want=1; nI_grid1=5; Nth=1; nRow.Scale1=5; nCol.Scale1=5; nRow.Scale2=5^2; nCol.Scale2=5^2; theta = 90; % degrees a_minor = 2; % range along minor direction a_major = 5; % range along major direction sill = var(reshape(Deff_matrix_NthModel,nCell.Scale1,1)); % variance of the coarse data matrix of size nRow.Scale1 X nCol.Scale1 %# Covariance computation % Scale 1 for ihRow = 1:nRow.Scale1 for ihCol = 1:nCol.Scale1 [cov.Scale1(ihRow,ihCol),heff.Scale1(ihRow,ihCol)] = general_CovModel(theta, ihCol, ihRow, a_minor, a_major, sill, 'Exp'); end end % Scale 2 for ihRow = 1:nRow.Scale2 for ihCol = 1:nCol.Scale2 [cov.Scale2(ihRow,ihCol),heff.Scale2(ihRow,ihCol)] = general_CovModel(theta, ihCol/(nCol.Scale2/nCol.Scale1), ihRow/(nRow.Scale2/nRow.Scale1), a_minor, a_major, sill/(nRow.Scale2*nCol.Scale2), 'Exp'); end end %# Scale-up of fine scale values by averaging [covAvg.Scale2,var_covAvg.Scale2,varNorm_covAvg.Scale2] = general_AverageProperty(nRow.Scale2/nRow.Scale1,nCol.Scale2/nCol.Scale1,1,nRow.Scale1,nCol.Scale1,1,cov.Scale2,1); I am using two functions, general_CovModel() and general_AverageProperty(), in my main script which are given as following: function [cov,h_eff] = general_CovModel(theta, hx, hy, a_minor, a_major, sill, mod_type) % mod_type should be in strings angle_rad = theta*(pi/180); % theta in degrees, angle_rad in radians R_theta = [sin(angle_rad) cos(angle_rad); -cos(angle_rad) sin(angle_rad)]; h = [hx; hy]; lambda = a_minor/a_major; D_lambda = [lambda 0; 0 1]; h_2prime = D_lambda*R_theta*h; h_eff = sqrt((h_2prime(1)^2)+(h_2prime(2)^2)); if strcmp(mod_type,'Sph')==1 || strcmp(mod_type,'sph') ==1 if h_eff<=a cov = sill - sill.*(1.5*(h_eff/a_minor)-0.5*((h_eff/a_minor)^3)); else cov = sill; end elseif strcmp(mod_type,'Exp')==1 || strcmp(mod_type,'exp') ==1 cov = sill-(sill.*(1-exp(-(3*h_eff)/a_minor))); elseif strcmp(mod_type,'Gauss')==1 || strcmp(mod_type,'gauss') ==1 cov = sill-(sill.*(1-exp(-((3*h_eff)^2/(a_minor^2))))); end and function [PropertyAvg,variance_PropertyAvg,NormVariance_PropertyAvg]=... general_AverageProperty(blocksize_row,blocksize_col,blocksize_t,... nUpscaledRow,nUpscaledCol,nUpscaledT,PropertyArray,omega) % This function computes average of a property and variance of that averaged % property using power averaging PropertyAvg=zeros(nUpscaledRow,nUpscaledCol,nUpscaledT); %# Average of property for k=1:nUpscaledT, for j=1:nUpscaledCol, for i=1:nUpscaledRow, sum=0; for a=1:blocksize_row, for b=1:blocksize_col, for c=1:blocksize_t, sum=sum+(PropertyArray((i-1)*blocksize_row+a,(j-1)*blocksize_col+b,(k-1)*blocksize_t+c).^omega); % add all the property values in 'blocksize_x','blocksize_y','blocksize_t' to one variable end end end PropertyAvg(i,j,k)=(sum/(blocksize_row*blocksize_col*blocksize_t)).^(1/omega); % take average of the summed property end end end %# Variance of averageed property variance_PropertyAvg=var(reshape(PropertyAvg,... nUpscaledRow*nUpscaledCol*nUpscaledT,1),1,1); %# Normalized variance of averageed property NormVariance_PropertyAvg=variance_PropertyAvg./(var(reshape(... PropertyArray,numel(PropertyArray),1),1,1)); Question: Using Matlab, I would like to optimize covAvg.Scale2 such that it matches closely with cov.Scale1 by perturbing/varying any (or all) of the following variables 1) a_minor 2) a_major 3) theta Thanks.

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  • Project Euler: Programmatic Optimization for Problem 7?

    - by bmucklow
    So I would call myself a fairly novice programmer as I focused mostly on hardware in my schooling and not a lot of Computer Science courses. So I solved Problem 7 of Project Euler: By listing the first six prime numbers: 2, 3, 5, 7, 11, and 13, we can see that the 6th prime is 13. What is the 10001st prime number? I managed to solve this without problem in Java, but when I ran my solution it took 8 and change seconds to run. I was wondering how this could be optimized from a programming standpoint, not a mathematical standpoint. Is the array looping and while statements the main things eating up processing time? And how could this be optimized? Again not looking for a fancy mathematical equation..there are plenty of those in the solution thread. SPOILER My solution is listed below. public class PrimeNumberList { private ArrayList<BigInteger> primesList = new ArrayList<BigInteger>(); public void fillList(int numberOfPrimes) { primesList.add(new BigInteger("2")); primesList.add(new BigInteger("3")); while (primesList.size() < numberOfPrimes){ getNextPrime(); } } private void getNextPrime() { BigInteger lastPrime = primesList.get(primesList.size()-1); BigInteger currentTestNumber = lastPrime; BigInteger modulusResult; boolean prime = false; while(!prime){ prime = true; currentTestNumber = currentTestNumber.add(new BigInteger("2")); for (BigInteger bi : primesList){ modulusResult = currentTestNumber.mod(bi); if (modulusResult.equals(BigInteger.ZERO)){ prime = false; break; } } if(prime){ primesList.add(currentTestNumber); } } } public BigInteger get(int primeTerm) { return primesList.get(primeTerm - 1); } }

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  • Compiler optimization of repeated accessor calls

    - by apocalypse9
    I've found recently that for some types of financial calculations that the following pattern is much easier to follow and test especially in situations where we may need to get numbers from various stages of the computation. public class nonsensical_calculator { ... double _rate; int _term; int _days; double monthlyRate { get { return _rate / 12; }} public double days { get { return (1 - i); }} double ar { get { return (1+ days) /(monthlyRate * days) double bleh { get { return Math.Pow(ar - days, _term) public double raar { get { return bleh * ar/2 * ar / days; }} .... } Obviously this often results in multiple calls to the same accessor within a given formula. I was curious as to whether or not the compiler is smart enough to optimize away these repeated calls with no intervening change in state, or whether this style is causing a decent performance hit. Further reading suggestions are always appreciated

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  • Optimization of running total calculation in SQL for multiple values per join condition

    - by Kiril
    I have the following table (test_table): date value --------------- d1 10.0 d1 20.0 d2 60.0 d2 10.0 d2 -20.0 d3 40.0 I calculate the running total as follows. I use the same query twice, because first I need to calculate the values for a specifi date, and afterwards I can calculate the running total. Otherwise, joining the two tables where date is not unique, I would get too many results from the join: SELECT t1.date, SUM(t2.value) AS total FROM (SELECT date, SUM(value) AS value FROM test_table GROUP BY date) AS t1 JOIN (SELECT date, SUM(value) AS value FROM test_table GROUP BY date) AS t2 ON t1.date >= t2.date GROUP BY t1.date ORDER BY t1.date This gives me (which is fine): date total ------------- d1 30.0 d2 80.0 d3 120.0 BUT, this query isn't very efficient, because I need to change conditions in two places, if necessary. In production, the test_table is a lot bigger ( 4 Mio. rows), and the query takes too much time to complete. Question: How can I avoid using the same query twice?

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  • Python optimization

    - by Rami Jarrar
    Hi, I do like this: f = open('wl4.txt', 'w') hh = 0 ###################################### for n in range(1,5): for l in range(33,127): if n==1: b = chr(l) + '\n' f.write(b) hh += 1 elif n==2: for s0 in range(33, 127): b = chr(l) + chr(s0) + '\n' f.write(b) hh += 1 elif n==3: for s0 in range(33, 127): for s1 in range(33, 127): b = chr(l) + chr(s0) + chr(s1) + '\n' f.write(b) hh += 1 elif n==4: for s0 in range(33, 127): for s1 in range(33, 127): for s2 in range(33,127): b = chr(l) + chr(s0) + chr(s1) + chr(s2) + '\n' f.write(b) hh += 1 ###################################### print "We Made %d Words." %(hh) ###################################### f.close() So, is there any method to make it faster?

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  • Open space sitting optimization algorithm

    - by Georgy Bolyuba
    As a result of changes in the company, we have to rearrange our sitting plan: one room with 10 desks in it. Some desks are more popular than others for number of reasons. One solution would be to draw a desk number from a hat. We think there is a better way to do it. We have 10 desks and 10 people. Lets give every person in this contest 50 hypothetical tokens to bid on the desks. There is no limit of how much you bid on one desk, you can put all 50, which would be saying "I want to sit only here, period". You can also say "I do not care" by giving every desk 5 tokens. Important note: nobody knows what other people are doing. Everyone has to decide based only on his/her best interest (sounds familiar?) Now lets say we obtained these hypothetical results: # | Desk# >| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 1 | Alise | 30 | 2 | 2 | 1 | 0 | 0 | 0 | 15 | 0 | 0 | = 50 2 | Bob | 20 | 15 | 0 | 10 | 1 | 1 | 1 | 1 | 1 | 0 | = 50 ... 10 | Zed | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | = 50 Now, what we need to find is that one (or more) configuration(s) that gives us maximum satisfaction (i.e. people get desks they wanted taking into account all the bids and maximizing on the total of the group. Naturally the assumption is the more one bade on the desk the more he/she wants it). Since there are only 10 people, I think we can brute force it looking into all possible configurations, but I was wondering it there is a better algorithm for solving this kind of problems?

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  • Compilier optimization of repeated accessor calls C#

    - by apocalypse9
    I've found recently that for some types of financial calculations that the following pattern is much easier to follow and test especially in situations where we may need to get numbers from various stages of the computation. public class nonsensical_calculator { ... double _rate; int _term; int _days; double monthlyRate { get { return _rate / 12; }} public double days { get { return (1 - i); }} double ar { get { return (1+ days) /(monthlyRate * days) double bleh { get { return Math.Pow(ar - days, _term) public double raar { get { return bleh * ar/2 * ar / days; }} .... } Obviously this often results in multiple calls to the same accessor within a given formula. I was curious as to whether or not the compiler is smart enough to optimize away these repeated calls with no intervening change in state, or whether this style is causing a decent performance hit. Further reading suggestions are always appreciated

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  • Python: Memory usage and optimization when modifying lists

    - by xApple
    The problem My concern is the following: I am storing a relativity large dataset in a classical python list and in order to process the data I must iterate over the list several times, perform some operations on the elements, and often pop an item out of the list. It seems that deleting one item out of a Python list costs O(N) since Python has to copy all the items above the element at hand down one place. Furthermore, since the number of items to delete is approximately proportional to the number of elements in the list this results in an O(N^2) algorithm. I am hoping to find a solution that is cost effective (time and memory-wise). I have studied what I could find on the internet and have summarized my different options below. Which one is the best candidate ? Keeping a local index: while processingdata: index = 0 while index < len(somelist): item = somelist[index] dosomestuff(item) if somecondition(item): del somelist[index] else: index += 1 This is the original solution I came up with. Not only is this not very elegant, but I am hoping there is better way to do it that remains time and memory efficient. Walking the list backwards: while processingdata: for i in xrange(len(somelist) - 1, -1, -1): dosomestuff(item) if somecondition(somelist, i): somelist.pop(i) This avoids incrementing an index variable but ultimately has the same cost as the original version. It also breaks the logic of dosomestuff(item) that wishes to process them in the same order as they appear in the original list. Making a new list: while processingdata: for i, item in enumerate(somelist): dosomestuff(item) newlist = [] for item in somelist: if somecondition(item): newlist.append(item) somelist = newlist gc.collect() This is a very naive strategy for eliminating elements from a list and requires lots of memory since an almost full copy of the list must be made. Using list comprehensions: while processingdata: for i, item in enumerate(somelist): dosomestuff(item) somelist[:] = [x for x in somelist if somecondition(x)] This is very elegant but under-the-cover it walks the whole list one more time and must copy most of the elements in it. My intuition is that this operation probably costs more than the original del statement at least memory wise. Keep in mind that somelist can be huge and that any solution that will iterate through it only once per run will probably always win. Using the filter function: while processingdata: for i, item in enumerate(somelist): dosomestuff(item) somelist = filter(lambda x: not subtle_condition(x), somelist) This also creates a new list occupying lots of RAM. Using the itertools' filter function: from itertools import ifilterfalse while processingdata: for item in itertools.ifilterfalse(somecondtion, somelist): dosomestuff(item) This version of the filter call does not create a new list but will not call dosomestuff on every item breaking the logic of the algorithm. I am including this example only for the purpose of creating an exhaustive list. Moving items up the list while walking while processingdata: index = 0 for item in somelist: dosomestuff(item) if not somecondition(item): somelist[index] = item index += 1 del somelist[index:] This is a subtle method that seems cost effective. I think it will move each item (or the pointer to each item ?) exactly once resulting in an O(N) algorithm. Finally, I hope Python will be intelligent enough to resize the list at the end without allocating memory for a new copy of the list. Not sure though. Abandoning Python lists: class Doubly_Linked_List: def __init__(self): self.first = None self.last = None self.n = 0 def __len__(self): return self.n def __iter__(self): return DLLIter(self) def iterator(self): return self.__iter__() def append(self, x): x = DLLElement(x) x.next = None if self.last is None: x.prev = None self.last = x self.first = x self.n = 1 else: x.prev = self.last x.prev.next = x self.last = x self.n += 1 class DLLElement: def __init__(self, x): self.next = None self.data = x self.prev = None class DLLIter: etc... This type of object resembles a python list in a limited way. However, deletion of an element is guaranteed O(1). I would not like to go here since this would require massive amounts of code refactoring almost everywhere.

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  • Mysql Server Optimization

    - by Ish Kumar
    Hi Geeks, We are having serious MySQL(InnoDB) performance issues at a moment when we do: (10-20) insertions on TABLE1 (10-20) updates on TABLE2 Note: Both above operations happens within fraction of a second. And this occurs every few (10-15) minutes. And all online users (approx 400-600) doing read operation on join of TABLE1 & TABLE2 every 1 second. Here is our mysql configuration info: http://docs.google.com/View?id=dfrswh7c_117fmgcmb44 Issues: Lot queries wait and expire later (saw it from phpmyadmin / processes). My poor MySQL server crashes sometimes Questions Q1: Any suggestions to optimize at MySQL level? Q2: I thinking to use persistent connections at application level, is it right? Info Added Later: Database Engine: InnoDB TABLE1 : 400,000 rows (inserting 8,000 daily) & TABLE2: 8,000 rows 1 second query: SELECT b.id, b.user_id, b.description, b.debit, b.created, b.price, u.username, u.email, u.mobile FROM TABLE1 b, TABLE2 u WHERE b.credit = 0 AND b.user_id = u.id AND b.auction_id = "12345" ORDER BY b.id DESC LIMIT 10; // there are few more but they are not so critical. Indexing is good, we are using them wisely. In above query all id's are indexed And TABLE1 has frequent insertions and TABLE2 has frequent updates.

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  • MySQL query optimization JOIN

    - by Pierre
    Hi, I need your help to optimize those mysql query, both are in my slow query logs. SELECT a.nom, c.id_apps, c.id_commentaire, c.id_utilisateur, c.note_commentaire, u.nom_utilisateur FROM comments AS c LEFT JOIN apps AS a ON c.id_apps = a.id_apps LEFT JOIN users AS u ON c.id_utilisateur = u.id_utilisateur ORDER BY c.date_commentaire DESC LIMIT 5; There is a MySQL INDEX on c.id_apps, a.id_apps, c.id_utilisateur, u.id_utilisateur and c.date_commentaire. SELECT a.id_apps, a.id_itunes, a.nom, a.prix, a.resume, c.nom_fr_cat, e.nom_edit FROM apps AS a LEFT JOIN cat AS c ON a.categorie = c.id_cat LEFT JOIN edit AS e ON a.editeur = e.id_edit ORDER BY a.id_apps DESC LIMIT 20; There is a MySQL INDEX on a.categorie, c.id_cat, a.editeur, e.id_edit and a.id_apps Thanks

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  • optimization mvc code

    - by user276640
    i have such code var prj = _dataContext.Project.FirstOrDefault(p => p.isPopular == true); if (prj != null) { prj.isPopular = false; _dataContext.SaveChanges(); } prj = Details(id); prj.isPopular = true; _dataContext.SaveChanges(); idea-i have only one record with value true in field isPopular, so i get it and make false, then i get object by id and make it isPopular true. i don't like 2 calls on savechanges. any ideas?

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  • Solver Foundation Optimization - 1D Bin Packing

    - by Val Nolav
    I want to optimize loading marbles into trucks. I do not know, if I can use Solver Foundation class for that purpose. Before, I start writing code, I wanted to ask it here. 1- Marbles can be in any weight between 1 to 24 Tons. 2 - A truck can hold maximum of 24 Tons. 3- It can be loaded as many marble cubes, as it can take for upto 24 tones, which means there is no Volume limitation. 4- There can be between 200 up to 500 different marbles depending on time. GOAL - The goal is to load marbles in minimum truck shipment. How can I do that without writing a lot of if conditions and for loops? Can I use Microsoft Solver Foundation for that purpose? I read the documentation provided by Microsoft however, I could not find a scenario similar to mine. M1+ M2 + M3 + .... Mn <=24 this is for one truck shipment. Let say there are 200 different Marbles and Marble weights are Float. Thanks

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