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  • ASP.NET MVC 2 from Scratch &ndash; Part 1 Listing Data from Database

    - by Max
    Part 1 - Listing Data from Database: Let us now learn ASP.NET MVC 2 from Scratch by actually developing a front end website for the Chinook database, which is an alternative to the traditional Northwind database. You can get the Chinook database from here. As always the best way to learn something is by working on it and doing something. The Chinook database has the following schema, a quick look will help us implementing the application in a efficient way. Let us first implement a grid view table with the list of Employees with some details, this table also has the Details, Edit and Delete buttons on it to do some operations. This is series of post will concentrate on creating a simple CRUD front end for Chinook DB using ASP.NET MVC 2. In this post, we will look at listing all the possible Employees in the database in a tabular format, from which, we can then edit and delete them as required. In this post, we will concentrate on setting up our environment and then just designing a page to show a tabular information from the database. We need to first setup the SQL Server database, you can download the required version and then set it up in your localhost. Then we need to add the LINQ to SQL Classes required for us to enable interaction with our database. Now after you do the above step, just use your Server Explorer in VS 2010 to actually navigate to the database, expand the tables node and then drag drop all the tables onto the Object Relational Designer space and you go you will have the tables visualized as classes. As simple as that. Now for the purpose of displaying the data from Employee in a table, we will show only the EmployeeID, Firstname and lastname. So let us create a class to hold this information. So let us add a new class called EmployeeList to the ViewModels. We will send this data model to the View and this can be displayed in the page. public class EmployeeList { public int EmployeeID { get; set; } public string Firstname { get; set; } public string Lastname { get; set; } public EmployeeList(int empID, string fname, string lname) { this.EmployeeID = empID; this.Firstname = fname; this.Lastname = lname; } } Ok now we have got the backend ready. Let us now look at the front end view now. We will first create a master called Site.Master and reuse it across the site. The Site.Master content will be <%@ Master Language="C#" AutoEventWireup="true" CodeBehind="Site.Master.cs" Inherits="ChinookMvcSample.Views.Shared.Site" %>   <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head id="Head1" runat="server"> <title></title> <style type="text/css"> html { background-color: gray; } .content { width: 880px; position: relative; background-color: #ffffff; min-width: 880px; min-height: 800px; float: inherit; text-align: justify; } </style> <script src="../../Scripts/jquery-1.4.1.min.js" type="text/javascript"></script> <asp:ContentPlaceHolder ID="head" runat="server"> </asp:ContentPlaceHolder> </head> <body> <center> <h1> My Website</h1> <div class="content"> <asp:ContentPlaceHolder ID="body" runat="server"> </asp:ContentPlaceHolder> </div> </center> </body> </html> The backend Site.Master.cs does not contain anything. In the actual Index.aspx view, we add the code to simply iterate through the collection of EmployeeList that was sent to the View via the Controller. So in the top of the Index.aspx view, we have this inherits which says Inherits="System.Web.Mvc.ViewPage<IEnumerable<ChinookMvcSample.ViewModels.EmployeeList>>" In this above line, we dictate that the page is consuming a IEnumerable collection of EmployeeList. So once we specify this and compile the project. Then in our Index.aspx page, we can consume the EmployeeList object and access all its methods and properties. <table class="styled" cellpadding="3" border="0" cellspacing="0"> <tr> <th colspan="3"> </th> <th> First Name </th> <th> Last Name </th> </tr> <% foreach (var item in Model) { %> <tr> <td align="center"> <%: Html.ActionLink("Edit", "Edit", new { id = item.EmployeeID }, new { id = "links" })%> </td> <td align="center"> <%: Html.ActionLink("Details", "Details", new { id = item.EmployeeID }, new { id = "links" })%> </td> <td align="center"> <%: Html.ActionLink("Delete", "Delete", new { id = item.EmployeeID }, new { id = "links" })%> </td> <td> <%: item.Firstname %> </td> <td> <%: item.Lastname %> </td> </tr> <% } %> <tr> <td colspan="5"> <%: Html.ActionLink("Create New", "Create") %> </td> </tr> </table> The Html.ActionLink is a Html Helper to a create a hyperlink in the page, in the one we have used, the first parameter is the text that is to be used for the hyperlink, second one is the action name, third one is the parameter to be passed, last one is the attributes to be added while the hyperlink is rendered in the page. Here we are adding the id=”links” to the hyperlinks that is created in the page. In the index.aspx page, we add some jQuery stuff add alternate row colours and highlight colours for rows on mouse over. Now the Controller that handles the requests and directs the request to the right view. For the index view, the controller would be public ActionResult Index() { //var Employees = from e in data.Employees select new EmployeeList(e.EmployeeId,e.FirstName,e.LastName); //return View(Employees.ToList()); return View(_data.Employees.Select(p => new EmployeeList(p.EmployeeId, p.FirstName, p.LastName))); } Let us also write a unit test using NUnit for the above, just testing EmployeeController’s Index. DataClasses1DataContext _data; public EmployeeControllerTest() { _data = new DataClasses1DataContext("Data Source=(local);Initial Catalog=Chinook;Integrated Security=True"); }   [Test] public void TestEmployeeIndex() { var e = new EmployeeController(_data); var result = e.Index() as ViewResult; var employeeList = result.ViewData.Model; Assert.IsNotNull(employeeList, "Result is null."); } In the first EmployeeControllerTest constructor, we set the data context to be used while running the tests. And then in the actual test, We just ensure that the View results returned by Index is not null. Here is the zip of the entire solution files until this point. Let me know if you have any doubts or clarifications. Cheers! Have a nice day.

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  • How to create per-vertex normals when reusing vertex data?

    - by Chris Smith
    I am displaying a cube using a vertex buffer object (gl.ELEMENT_ARRAY_BUFFER). This allows me to specify vertex indicies, rather than having duplicate vertexes. In the case of displaying a simple cube, this means I only need to have eight vertices total. Opposed to needing three vertices per triangle, times two triangles per face, times six faces. Sound correct so far? My question is, how do I now deal with vertex attribute data such as color, texture coordinates, and normals when reusing vertices using the vertex buffer object? If I am reusing the same vertex data in my indexed vertex buffer, how can I differentiate when vertex X is used as part of the cube's front face versus the cube's left face? In both cases I would like the surface normal and texture coordinates to be different. I understand I could average the surface normal, however I would like to render a cube. Also, this still doesn't work for texture coordinates. Is there a way to save memory using a vertex buffer object while being able to provide different vertex attribute data based on context? (Per-triangle would be idea.) Or should I just duplicate each vertex for each context in which it gets rendered. (So there is a one-to-one mapping between vertex, normal, color, etc.) Note: I'm using OpenGL ES.

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  • How to use the unit of work and repository patterns in a service oriented enviroment

    - by A. Karimi
    I've created an application framework using the unit of work and repository patterns for it's data layer. Data consumer layers such as presentation depend on the data layer design. For example a CRUD abstract form has a dependency to a repository (IRepository). This architecture works like a charm in client/server environments (Ex. a WPF application and a SQL Server). But I'm looking for a good pattern to change or reuse this architecture for a service oriented environment. Of course I have some ideas: Idea 1: The "Adapter" design pattern Keep the current architecture and create a new unit of work and repository implementation which can work with a service instead of the ORM. Data layer consumers are loosely coupled to the data layer so it's possible but the problem is about the unit of work; I have to create a context which tracks the objects state at the client side and sends the changes to the server side on calling the "Commit" (Something that I think the RIA has done for Silverlight). Here the diagram: ----------- CLIENT----------- | ------------------ SERVER ---------------------- [ UI ] -> [ UoW/Repository ] ---> [ Web Services ] -> [ UoW/Repository ] -> [DB] Idea 2: Add another layer Add another layer (let say "local services" or "data provider"), then put it between the data layer (unit of work and repository) and the data consumer layers (like UI). Then I have to rewrite the consumer classes (CRUD and other classes which are dependent to IRepository) to depend on another interface. And the diagram: ----------------- CLIENT ------------------ | ------------------- SERVER --------------------- [ UI ] -> [ Local Services/Data Provider ] ---> [ Web Services ] -> [ UoW/Repository ] -> [DB] Please note that I have the local services layer on the current architecture but it doesn't expose the data layer functionality. In another word the UI layer can communicate with both of the data and local services layers whereas the local services layer also uses the data layer. | | | | | | | | ---> | Local Services | ---> | | | UI | | | | Data | | | | | | | ----------------------------> | |

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  • A Big Data korszakban, túl az 1000. eladott Oracle Exadata Database Machine adatbázisgépen

    - by user645740
    Mint azt már egy ideje a szél is fújja, beköszöntött a BIG DATA korszak, azaz egyre több adat gyulik, egyre több adattal gazdálkodunk. A hatalmas mennyiségu adat jó részét Oracle adatbázisokban tárolják. Mi is futtathatná jobban, gyorsabban és hetékonyabban ezeket az Oracle adatbázisokat, mint az Oracle stratégiai high-end megoldása az Oracle Exadata Database Machine? Rengeteg forrása van a sok adatnak, néhány példa, ahol a növekedés óriási: kommunikációs adatok, CDR-ek banki és kormányzati tranzakciók hely információk spatial, location, GPS,..., mint ahogyan a közelmúltban az egyes telefonokkal ésoperációs rendszerekkel kapcsolatos "ügyekben" is olvashattuk, e-mail-ek, közösségi site-ok, intelligens méromuszerek, háztartási berendezések, .... Milyen ütemben no az Exadata értékesítés? Nos az Exadata 2008 oszén lett bejelentve. Az Oracle pénzügyi év végén a jelentésben azt olvashatjuk, hogy az Exadata páratlanul sikeres megoldás, már több mint 1000 Exadatát vásároltak meg az Oracle ügyfelek, mondta Mark Hurd, az Oracle alelnöke:   “In addition to record setting software sales, our Exadata and Exalogic systems also made a strong contribution to our growth in Q4,” said Oracle President, Mark Hurd. “Today there are more than 1,000 Exadata machines installed worldwide. Our goal is to triple that number in FY12.” Larry Ellison, az Oracle elso embere, azt nyilatkozta, hogy mind a felho - cloud computing, mind a memória-adatbázisok területén egyre gyorsabban növekszik az Oracle:   “In FY11 Oracle’s database business experienced its fastest growth in a decade,” said Oracle CEO, Larry Ellison. “Over the past few years we added features to the Oracle database for both cloud computing and in-memory databases that led to increased database sales this past year. Lately we’ve been focused on the big business opportunity presented by Big Data.” A Big Data korszakban  megtakarításokat érhetünk el az Exadatával, tekintse meg a következo videót, de óvatosan, mert gondolkodásra késztet:    -   Oracle Exadata: Are You Ready?.

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  • Form Validation Options

    The steps involved in transmitting form data from the client to the Web server User loads web form. User enters data in to web form fields User clicks submit On submit page validates fields using JavaScript. If validation errors are found then the validation script stops the browser from canceling posting the data to the web server and displays error messages as needed. If the form passes the data validation process then the browser will URL encode the values of every field and post it to the server.  The server reads the posted data from the query string and then again validates the data just to ensure data consistency and to prevent any non-validated data because JavaScript was turned off on the clients browser from being inserted in to a database or passed on to other process. If the data passes the second validation check then the server side code will continue with the requested processes. In my opinion, it is mandatory to validate data using client side and server side validation as a fail over process. The client side validation allows users to correct any error before they are sent to the web server for processing, and this allows for an immediate response back to the user regarding data that is not correct or in the proper format that is desired. In addition, this prevents unnecessary interaction between the user and the web server and will free up the server over time compared to doing only server side validation. Server validation is the last line of defense when it comes to validation because you can check to ensure the user’s data is correct before it is used in a business process or stored to a database. Honestly, I cannot foresee a scenario where I would only want to use one form of validation over another especially with the current cost of creating and maintaining data. In my opinion, the redundant validation is well worth the overhead.

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  • How to expose game data in the game without a singelton?

    - by zardon
    I'm quite new to cocos2d and games programming, and am currently I am writing a game that is currently in Prototype stage. Everything is going okay, but I've realized a potentially big problem and I am not sure how to solve it. I am using a singelton to store a bunch of arrays for everything, a global list of planets, a global list of troops, a global list of products, etc. And only now I'm realizing that all of this will be in memory and this is the wrong way to do it. I am not storing files or anything on the disk just yet, with exception to a save/load state, which is a capture of everything. My game makes use of a map which allows you to select a planet, then it will give you a breakdown of that planets troops and resources, Lets use this scenario: My game has 20 planets. On which you can have 20 troops. Straight away that's an array of 400! This does not add the NPC, which is another 10. So, 20x10 = 200 So, now we have 600 all in arrays inside a Singelton. This is obviously very bad, and very wrong. Especially as the game scales in the amount of data. But I need to expose pretty much everything, especially on the map page, and I am not sure how else to do it. I've been told that I can use a controller for the map page which has the information I need for each planet, and other controllers for other items I require global display for. I've also thought about storing each planet's data in a save file, using initWithCoder however there could be a boatload of files on the user's device? I really don't want to use a database, mainly because I would need to translate NSObjects and non-NSObjects like CGRects and CGPoints and Colors into/from SQL. I am open to other ideas on how to store and read game data to prevent using a singelton to store everything, everywhere. Thanks for your time.

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  • How to manage security of these self hosted web apis, to ensure that the request coming for accessing data is authenticated?

    - by Husrat Mehmood
    Let's pretend I am going to work on an enterprise application. Say I have 11 modules in the application and I would have to develop Dashboards for every role in the organization for whom I are going to develop application. We Decided to use Asp.Net Web Api and return json data from our apis. We are going to include 11 Self hosted web apis projects in our application (one self hosted web api) for every module. All 11 modules are connected to one Sql server 2012 Database. Then once api is ready we would have to create Business Dashboards (Based upon roles in Organization). So Now my web api client is Asp.Net Mvc application.Asp.Net mvc will consume those web apis. Here is the part for whom all explanation is done. How should I manage Security of all 11 self hosted web apis? How should I only authenticated request is coming? If I authenticate user by login and password and then redirect user to appropriate Dashboard designed for the role that user have and load data by consuming web apis. How should I ensure that the request coming for accessing data is authenticated?

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  • Essbase Analytics Link (EAL) - Performance of some operation of EAL could be improved by tuning of EAL Data Synchronization Server (DSS) parameters

    - by Ahmed Awan
    Generally, performance of some operation of EAL (Essbase Analytics Link) could be improved by tuning of EAL Data Synchronization Server (DSS) parameters. a. Expected that DSS machine will be 64-bit machine with 4-8 cores and 5-8 GB of RAM dedicated to DSS. b. To change DSS configuration - open EAL Configuration Tool on DSS machine.     ->Next:     and define: "Job Units" as <Number of Cores dedicated to DSS> * 1.5 "Max Memory Size" (if this is 64-bit machine) - ~1G for each Job Unit. If DSS machine is 32-bit - max memory size is 2600 MB. "Data Store Size" - depends on number of bridges and volume of HFM applications, but in most cases 50000 MB is enough. This volume should be available in defined "Data Store Dir" driver.   Continue with configuration and finish it. After that, DSS should be restarted to take new definitions.  

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  • EDQ Technical Enablement for OPN (Prague - June 17-19)

    - by milomir.vojvodic
    Oracle Enterprise Data Quality (EDQ) Technical Enablement and Partner Training Trusted Data for Your Enterprise Applications Oracle Enterprise Data Quality helps organizations achieve maximum value from their business-critical applications by delivering fit-for-purpose data. These products also enable individuals and collaborative teams to quickly and easily identify and resolve any problems in underlying data. With Oracle Enterprise Data Quality, customers can identify new opportunities, improve operational efficiency, and more efficiently comply with industry or governmental regulation. Oracle Enterprise Data Quality is designed to serve as a very channel friendly platform to OPN.  This means that pre-built extensions, components and even complete business solutions can readily be built and shared.  This allows our customers/partners to be highly efficient in how they deploy custom business solutions, but also allows our partners to develop specialized components, domain knowledge and even complete business solutions. Training is suitable for: · Database administrators · Architects · Technical staff Objectives of the training: After completing this course, participants should: · Have an understanding of the core functionality of EDQ across profiling, auditing, transforming, parsing and matching data · Be able to describe some of the key capabilities and benefits delivered by EDQ · Be able to create and run standalone EDQ processes and jobs · Be ready to start working with data from customers and (with practice) be able to demonstrate EDQ to customers Agenda 17th June Fundamentals For Demoing (Profile, Audit, Transform and More) Profiling Auditing Transforming Writing and exporting data Jobs and scheduling Publishing, packaging and copying EDQ processes Introduction to the Customer Data Extension Pack Realtime Processing via Web Services The Server Console Run Profiles Data Interfaces Sampling Publishing metrics to the Dashboard Users and security 18th June Matching Matching overview Basic matching configuration Matching rule hierarchies Clustering Merging Reviewing possible matches Outputting Match Data Case study 19th June Address Verification Address Verification Overview Configuration Accuracy Flags Parsing Parsing Overview Phrase profiling Tailoring a CDEP Parser Base Tokenization Classification Reclassification Selection Resolution Register Here Don’t miss this FREE event. Space is limited. Oracle University V Parku 2294/4 148 00 Praha 4 17.6. – 19.6. 2014 09:00 a.m.– 17:30 p.m.

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  • Is there a simple, flat, XML-based query-able data storage solution? [closed]

    - by alex gray
    I have been in long pursuit of an XML-based query-able data store, and despite continued searches and evaluations, I have yet to find a solution that meets the my needs, which include: Data is wholly contained within XML nodes, in flat text files. There is a "native" - or at least unobtrusive - method with which to perform Create/Read/Update/Delete (CRUD) operations onto the "schema". I would consider access via http, XHR, javascript, PHP, BASH, or PERL to be unobtrusive, dependent on the complexity of the set of dependencies. Server-side file-system reads and writes. A client-side interface element, accessible in any browser without a plug-in. Some extra, preferred (but optional) requirements include: Respond to simple SQL, or similarly syntax queries. Serve the data on a bare bones https server, with no "extra stuff", either via XMLHTTPRequest, HTTP proper, or JSON. A few thoughts: What I'm looking for may be possible via some Java server implementations, but for the sake of this question, please do not suggest that - unless it meets ALL the requirements. Java, especially on the client-side is not really an option, nor is it appealing from a development viewpoint.* I know walking the filesystem is a stretch, and I've heard it's possible with XPATH or XSLT, but as far as I know, that's not ready for primetime, nor even yet a recommendation. However the ability to recursively traverse the filesystem is needed for such a system to be of useful facility. At this point, I have basically implemented what I described via, of all things, CGI and Bash, but there has to be an easier way. Thoughts?

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  • Why values in my WCF data contract were suddenly wrong...

    - by mipsen
    A WCF Service I provided took a very simple data contract as parameter (containing one string and one int...) and had a very simple task to do. A .NET 3.5 client was created using the VS2008 feature "Add Service Reference". Everything worked as expected. Then a slight change came in: The client was expected to run on machines with .NET 2.0 only. So we set the Target  Framework to .NET 2.0, removed the references to System.ServiceModel, System.Runtime.Serialization and the ServiceReference and created a new Reference to the Service using the old "Add Web Reference" . A matter of 2 minutes.  When testing, the int value in the data contract arriving at the WCF Service suddenly was 0, instead of 38 as we expected. What happened? When generating an old  Web Reference on a WCF data contract an additional boolean field for each value-type field is created called [Fieldname]Specified (e.g. AgeSpecified) which defaults to "false". WCF inspects these boolean fields to determine if a value was provided for the value-type field. If the "Specified"-field is "false", WCF translates that to using the default-value of the value-type field. For int this is 0. So we had to insert  setting the "Specified"-field  for the int-value to "true" and everything was fine again. That was what we forgot after setting the Framework-version to 2.0...

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  • Sentiment analysis with NLTK python for sentences using sample data or webservice?

    - by Ke
    I am embarking upon a NLP project for sentiment analysis. I have successfully installed NLTK for python (seems like a great piece of software for this). However,I am having trouble understanding how it can be used to accomplish my task. Here is my task: I start with one long piece of data (lets say several hundred tweets on the subject of the UK election from their webservice) I would like to break this up into sentences (or info no longer than 100 or so chars) (I guess i can just do this in python??) Then to search through all the sentences for specific instances within that sentence e.g. "David Cameron" Then I would like to check for positive/negative sentiment in each sentence and count them accordingly NB: I am not really worried too much about accuracy because my data sets are large and also not worried too much about sarcasm. Here are the troubles I am having: All the data sets I can find e.g. the corpus movie review data that comes with NLTK arent in webservice format. It looks like this has had some processing done already. As far as I can see the processing (by stanford) was done with WEKA. Is it not possible for NLTK to do all this on its own? Here all the data sets have already been organised into positive/negative already e.g. polarity dataset http://www.cs.cornell.edu/People/pabo/movie-review-data/ How is this done? (to organise the sentences by sentiment, is it definitely WEKA? or something else?) I am not sure I understand why WEKA and NLTK would be used together. Seems like they do much the same thing. If im processing the data with WEKA first to find sentiment why would I need NLTK? Is it possible to explain why this might be necessary? I have found a few scripts that get somewhat near this task, but all are using the same pre-processed data. Is it not possible to process this data myself to find sentiment in sentences rather than using the data samples given in the link? Any help is much appreciated and will save me much hair! Cheers Ke

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  • Gridview - Is it necessary to grab data from database every time a filter, sort, or paging event occ

    - by hamlin11
    Regarding gridviews that are not bound to a Data Source Control: In most GridView tutorials that I have seen, when just about any GridView event occurs, the end of the event handler will include BindDataGrid(). In some form, these BindDataGrid() functions 1) Grab data from the database 2) Assign any Filter or Sort expressions to the data, and 3) Bind the gridview to that data source (usually a DataView or DataTable. Is there a better way to provide filterable & sortable data to a GridView without having to hit the database so often? Thanks

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  • content show problem

    - by nonab
    I still fight with some jquery scripts:) With my first problem Jens Fahnenbruck helped me here: http://stackoverflow.com/questions/3021476/problem-with-hide-show-in-jquery thanks:) Now i added another fancy thing - jquery tabs Made a few modifications and it works like this: When you click on tab and it loads different main image for every tab. The problem is that i used $(document).ready(function() to handle those image changes. When i click any of 2x2 box images (on any tab) it will permanently change the image on the right and when i click on tabs it won't work like it did at the beginning. online example: http://rarelips.ayz.pl/testy/2/ code: <style type="text/css"> body { font: Arial, Helvetica, sans-serif normal 10px; margin: 0; padding: 0; } * {margin: 0; padding: 0;} img {border: none;} .container { height: 500px; width: 1000px; margin: -180px 0 0 -450px; top: 50%; left: 50%; position: absolute; } ul.thumb { float: left; list-style: none; margin: 0; padding: 10px; width: 360px; } ul.thumb li { margin: 0; padding: 5px; float: left; position: relative; width: 165px; height: 165px; } ul.thumb li img { width: 150px; height: 150px; border: 1px solid #ddd; padding: 10px; background: #f0f0f0; position: absolute; left: 0; top: 0; -ms-interpolation-mode: bicubic; } ul.thumb li img.hover { background:url(thumb_bg.png) no-repeat center center; border: none; } #main_view { float: left; padding: 9px 0; margin-left: -10px; } #main_view2 { float: left; padding: 9px 0; margin-left: -10px; } #main_view3 { float: left; padding: 9px 0; margin-left: -10px; } #main_view4 { float: left; padding: 9px 0; margin-left: -10px; } #wiecej { float: right; padding: 9px 0; margin-right: 20px; } .demo-show { width: 350px; margin: 1em .5em; } .demo-show h3 { margin: 0; padding: .25em; background: #bfcd93; border-top: 1px solid #386785; border-bottom: 1px solid #386785; } .demo-show div { padding: .5em .25em; } /* styl do tabek */ ul.tabs { margin: 0; padding: 0; float: left; list-style: none; height: 32px; /*--Set height of tabs--*/ border-bottom: 1px solid #999; border-left: 1px solid #999; width: 100%; } ul.tabs li { float: left; margin: 0; padding: 0; height: 31px; /*--Subtract 1px from the height of the unordered list--*/ line-height: 31px; /*--Vertically aligns the text within the tab--*/ border: 1px solid #999; border-left: none; margin-bottom: -1px; /*--Pull the list item down 1px--*/ overflow: hidden; position: relative; background: #e0e0e0; } ul.tabs li a { text-decoration: none; color: #000; display: block; font-size: 1.2em; padding: 0 20px; border: 1px solid #fff; /*--Gives the bevel look with a 1px white border inside the list item--*/ outline: none; } ul.tabs li a:hover { background: #ccc; } html ul.tabs li.active, html ul.tabs li.active a:hover { /*--Makes sure that the active tab does not listen to the hover properties--*/ background: #fff; border-bottom: 1px solid #fff; /*--Makes the active tab look like it's connected with its content--*/ } .tab_container { border: 1px solid #999; border-top: none; overflow: hidden; clear: both; float: left; width: 100%; background: #fff; } .tab_content { padding: 20px; font-size: 1.2em; } </style> <script type="text/javascript" src="index_pliki/jquery-latest.js"></script> <script type="text/javascript"> $(document).ready(function(){ //Larger thumbnail preview $("ul.thumb li").hover(function() { $(this).css({'z-index' : '10'}); $(this).find('img').addClass("hover").stop() .animate({ marginTop: '-110px', marginLeft: '-110px', top: '50%', left: '50%', width: '200px', height: '200px', padding: '5px' }, 200); } , function() { $(this).css({'z-index' : '0'}); $(this).find('img').removeClass("hover").stop() .animate({ marginTop: '0', marginLeft: '0', top: '0', left: '0', width: '150px', height: '150px', padding: '10px' }, 400); }); //Swap Image on Click $("ul.thumb li a").click(function() { var mainImage = $(this).attr("href"); //Find Image Name $("#main_view img").attr({ src: mainImage }); $("#main_view2 img").attr({ src: mainImage }); $("#main_view3 img").attr({ src: mainImage }); $("#main_view4 img").attr({ src: mainImage }); return false; }); }); </script> <script type="text/javascript"> $(document).ready(function() { $("#main_view img").attr({ src: './index_pliki/max1.jpg' }); $("#slickbox div[data-id=" + '01' + "].slickbox").show('slow'); $('a.slick-toggle').click(function() { var dataID = $(this).attr("data-id"); $('#slickbox div.slickbox').hide(); $("#slickbox div[data-id=" + dataID + "].slickbox").show('slow'); return false; }); }); </script> <script type="text/javascript"> $(document).ready(function() { $("#main_view2 img").attr({ src: './index_pliki/max2.jpg' }); $("#slickbox2 div[data-id=" + '11' + "].slickbox2").show('slow'); $('a.slick-toggle').click(function() { var dataID = $(this).attr("data-id"); $('#slickbox2 div.slickbox2').hide(); $("#slickbox2 div[data-id=" + dataID + "].slickbox2").show('slow'); return false; }); }); </script> <script type="text/javascript"> $(document).ready(function() { $("#main_view3 img").attr({ src: './index_pliki/max3.jpg' }); $("#slickbox3 div[data-id=" + '21' + "].slickbox3").show('slow'); $('a.slick-toggle').click(function() { var dataID = $(this).attr("data-id"); $('#slickbox3 div.slickbox3').hide(); $("#slickbox3 div[data-id=" + dataID + "].slickbox3").show('slow'); return false; }); }); </script> <script type="text/javascript"> $(document).ready(function() { $("#main_view4 img").attr({ src: './index_pliki/max4.jpg' }); $("#slickbox4 div[data-id=" + '31' + "].slickbox4").show('slow'); $('a.slick-toggle').click(function() { var dataID = $(this).attr("data-id"); $('#slickbox4 div.slickbox4').hide(); $("#slickbox4 div[data-id=" + dataID + "].slickbox4").show('slow'); return false; }); }); </script> <script type ="text/javascript"> $(document).ready(function() { //When page loads... $(".tab_content").hide(); //Hide all content $("ul.tabs li:first").addClass("active").show(); //Activate first tab $(".tab_content:first").show(); //Show first tab content //On Click Event $("ul.tabs li").click(function() { $("ul.tabs li").removeClass("active"); //Remove any "active" class $(this).addClass("active"); //Add "active" class to selected tab $(".tab_content").hide(); //Hide all tab content var activeTab = $(this).find("a").attr("href"); //Find the href attribute value to identify the active tab + content $(activeTab).fadeIn(); //Fade in the active ID content return false; }); }); </script> </head> <body> <div class="container"> <ul class="tabs"> <li><a href="#tab1">1</a></li> <li><a href="#tab2">2</a></li> <li><a href="#tab3">3</a></li> <li><a href="#tab4">4</a></li> </ul> <div class="tab_container"> <div id="tab1" class="tab_content"> <!--Content--> <ul class="thumb"> <li><a class="slick-toggle" href="./index_pliki/max1.jpg" data-id="01"><img src="./index_pliki/min1.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max2.jpg" data-id="02"><img src="./index_pliki/min2.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max3.jpg" data-id="03"><img src="./index_pliki/min3.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max4.jpg" data-id="04"><img src="./index_pliki/min4.jpg" alt="" /></a></li> </ul> <div id="main_view"> <a href="index.htm"><img src="index_pliki/max1.jpg" alt=""/></a> <small style="float: right; color: rgb(153, 153, 153);"> </small> </div> <div id="wiecej"> <div id="slickbox"> <div id="someOtherID" class="slickbox" data-id="01" style="display: none;"> 1.1 </div> <div id="someOtherID" class="slickbox" data-id="02" style="display: none;"> 1.2 </div> <div id="someOtherID" class="slickbox" data-id="03" style="display: none;"> 1.3 </div> <div id="someOtherID" class="slickbox" data-id="04" style="display: none;"> 1.4 </div> <!-- <a href="#" id="slick-show"><img src="http://www.amptech.pl/images/more.jpg" alt="Zobacz wiecej" /></a> <a href="#" id="slick-hide"><img src="http://www.amptech.pl/images/online.jpg" alt="Zobacz wiecej" /></a>&nbsp;&nbsp; --> </div> </div> </div> <!-- tutaj wklejalem reszte --> <div id="tab2" class="tab_content"> <!--Content--> <ul class="thumb"> <li><a class="slick-toggle" href="./index_pliki/max4.jpg" data-id="11"><img src="./index_pliki/min4.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max3.jpg" data-id="12"><img src="./index_pliki/min3.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max2.jpg" data-id="13"><img src="./index_pliki/min2.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max1.jpg" data-id="14"><img src="./index_pliki/min1.jpg" alt="" /></a></li> </ul> <div id="main_view2"> <a href="index.htm"><img src="index_pliki/max1.jpg" alt=""/></a> <small style="float: right; color: rgb(153, 153, 153);"> </small> </div> <div id="wiecej"> <div id="slickbox2"> <div id="someOtherID" class="slickbox2" data-id="11" style="display: none;"> 2.1 </div> <div id="someOtherID" class="slickbox2" data-id="12" style="display: none;"> 2.2 </div> <div id="someOtherID" class="slickbox2" data-id="13" style="display: none;"> 2.3 </div> <div id="someOtherID" class="slickbox2" data-id="14" style="display: none;"> 2.4 </div> </div> </div> </div> <div id="tab3" class="tab_content"> <ul class="thumb"> <li><a class="slick-toggle" href="./index_pliki/max4.jpg" data-id="21"><img src="./index_pliki/min4.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max3.jpg" data-id="22"><img src="./index_pliki/min3.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max2.jpg" data-id="23"><img src="./index_pliki/min2.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max1.jpg" data-id="24"><img src="./index_pliki/min1.jpg" alt="" /></a></li> </ul> <div id="main_view3"> <a href="index.htm"><img src="index_pliki/max1.jpg" alt=""/></a> <small style="float: right; color: rgb(153, 153, 153);"> </small> </div> <div id="wiecej"> <div id="slickbox3"> <div id="someOtherID" class="slickbox3" data-id="21" style="display: none;"> 3.1 </div> <div id="someOtherID" class="slickbox3" data-id="22" style="display: none;"> 3.2 </div> <div id="someOtherID" class="slickbox3" data-id="23" style="display: none;"> 3.3 </div> <div id="someOtherID" class="slickbox3" data-id="24" style="display: none;"> 3.4 </div> </div> </div> </div> <div id="tab4" class="tab_content"> <ul class="thumb"> <li><a class="slick-toggle" href="./index_pliki/max4.jpg" data-id="31"><img src="./index_pliki/min4.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max3.jpg" data-id="32"><img src="./index_pliki/min3.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max2.jpg" data-id="33"><img src="./index_pliki/min2.jpg" alt="" /></a></li> <li><a class="slick-toggle" href="./index_pliki/max1.jpg" data-id="34"><img src="./index_pliki/min1.jpg" alt="" /></a></li> </ul> <div id="main_view4"> <a href="index.htm"><img src="index_pliki/max1.jpg" alt=""/></a> <small style="float: right; color: rgb(153, 153, 153);"> </small> </div> <div id="wiecej"> <div id="slickbox4"> <div id="someOtherID" class="slickbox4" data-id="31" style="display: none;"> 4.1 </div> <div id="someOtherID" class="slickbox4" data-id="32" style="display: none;"> 4.2 </div> <div id="someOtherID" class="slickbox4" data-id="33" style="display: none;"> 4.3 </div> <div id="someOtherID" class="slickbox4" data-id="34" style="display: none;"> 4.4 </div> </div> </div> </div> </div> </div>

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  • How to troubleshoot a Highcharts script that's not rendering data when date is added and hanging the JS engine with large datasets?

    - by ylluminate
    I have a Highchart JS graph that I'm building in Rails (although I don't think Ruby has real bearing on this problem unless it's the Date output format) to which I'm adding the timestamp of each datapoint. Presently the array of floats is rendering fine without timestamps, however when I add the timestamp to the series it fails to rend. What's worse is that when the series has hundreds of entries all sorts of problems arise, not the least of which is the browser entirely hanging and requiring a force quit / kill. I'm using the following to build the array of arrays data series: series1 = readings.map{|row| [(row.date.to_i * 1000), (row.data1.to_f if BigDecimal(row.data1) != BigDecimal("-1000.0"))] } This yields a result like this: series: [{"name":"Data 1","data":[[1326262980000,1.79e-09],[1326262920000,1.29e-09],[1326262860000,1.22e-09],[1326262800000,1.42e-09],[1326262740000,1.29e-09],[1326262680000,1.34e-09],[1326262620000,1.31e-09],[1326262560000,1.51e-09],[1326262500000,1.24e-09],[1326262440000,1.7e-09],[1326262380000,1.24e-09],[1326262320000,1.29e-09],[1326262260000,1.53e-09],[1326262200000,1.23e-09],[1326262140000,1.21e-09]],"color":"blue"}] Yet nothing appears on the graph as noted. Notwithstanding, when I compare the data series in one of their very similar examples here: http://www.highcharts.com/demo/spline-irregular-time It appears that really the data series are formatted identically (except in mine I use the timestamp vs date method). This leads me to think I've got a problem with the timestamp output, but I'm just not able to figure out where / how as I'm converting the date output to an integer multipled by 1000 to convert it to milliseconds as per explained in a similar Railscasts tutorial. I would very much appreciate it if someone could point me in the right direction here as to what I may be doing wrong. What could cause no data to appear on the graph in smaller sized sets (<100 points) and when into the hundreds causes an apparent hang in the javascript engine in this case? Perhaps ultimately the key lies here as this is the entire js that's being generated and not rendering: jQuery(function() { // 1. Define JSON options var options = { chart: {"defaultSeriesType":"spline","renderTo":"chart_name"}, title: {"text":"Title"}, legend: {"layout":"vertical","style":{}}, xAxis: {"title":{"text":"UTC Time"},"type":"datetime"}, yAxis: [{"title":{"text":"Left Title","margin":10}},{"title":{"text":"Right Groups Title"},"opposite":true}], tooltip: {"enabled":true}, credits: {"enabled":false}, plotOptions: {"areaspline":{}}, series: [{"name":"Data 1","data":[[1326262980000,1.79e-08],[1326262920000,1.69e-08],[1326262860000,1.62e-08],[1326262800000,1.42e-08],[1326262740000,1.29e-08],[1326262680000,1.34e-08],[1326262620000,1.31e-08],[1326262560000,1.51e-08],[1326262500000,1.64e-08],[1326262440000,1.7e-08],[1326262380000,1.64e-08],[1326262320000,1.69e-08],[1326262260000,1.53e-08],[1326262200000,1.23e-08],[1326262140000,1.21e-08]],"color":"blue"},{"name":"Data 2","data":[[1326262980000,9.79e-09],[1326262920000,9.78e-09],[1326262860000,9.8e-09],[1326262800000,9.82e-09],[1326262740000,9.88e-09],[1326262680000,9.89e-09],[1326262620000,1.3e-06],[1326262560000,1.32e-06],[1326262500000,1.33e-06],[1326262440000,1.33e-06],[1326262380000,1.34e-06],[1326262320000,1.33e-06],[1326262260000,1.32e-06],[1326262200000,1.32e-06],[1326262140000,1.32e-06]],"color":"red"}], subtitle: {} }; // 2. Add callbacks (non-JSON compliant) // 3. Build the chart var chart = new Highcharts.StockChart(options); });

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  • Which term to use when referring to functional data structures: persistent or immutable?

    - by Bob
    In the context of functional programming which is the correct term to use: persistent or immutable? When I Google "immutable data structures" I get a Wikipedia link to an article on "Persistent data structure" which even goes on to say: such data structures are effectively immutable Which further confuses things for me. Do functional programs rely on persistent data structures or immutable data structures? Or are they always the same thing?

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  • Problem with receiving data form serial port in c#?

    - by moon
    hello i have problem with receiving data from serial port in c# in am inserting a new line operator at the end of data buffer. then i send this data buffer on serial port, after this my c# GUI receiver will take this data via Readline() function but it always give me raw data not the actual one how to resolve this problem.

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  • Indexing with pointer C/C++

    - by Leavenotrace
    Hey I'm trying to write a program to carry out newtons method and find the roots of the equation exp(-x)-(x^2)+3. It works in so far as finding the root, but I also want it to print out the root after each iteration but I can't get it to work, Could anyone point out my mistake I think its something to do with my indexing? Thanks a million :) #include <stdio.h> #include <math.h> #include <malloc.h> //Define Functions: double evalf(double x) { double answer=exp(-x)-(x*x)+3; return(answer); } double evalfprime(double x) { double answer=-exp(-x)-2*x; return(answer); } double *newton(double initialrt,double accuracy,double *data) { double root[102]; data=root; int maxit = 0; root[0] = initialrt; for (int i=1;i<102;i++) { *(data+i)=*(data+i-1)-evalf(*(data+i-1))/evalfprime(*(data+i-1)); if(fabs(*(data+i)-*(data+i-1))<accuracy) { maxit=i; break; } maxit=i; } if((maxit+1==102)&&(fabs(*(data+maxit)-*(data+maxit-1))>accuracy)) { printf("\nMax iteration reached, method terminated"); } else { printf("\nMethod successful"); printf("\nNumber of iterations: %d\nRoot Estimate: %lf\n",maxit+1,*(data+maxit)); } return(data); } int main() { double root,accuracy; double *data=(double*)malloc(sizeof(double)*102); printf("NEWTONS METHOD PROGRAMME:\nEquation: f(x)=exp(-x)-x^2+3=0\nMax No iterations=100\n\nEnter initial root estimate\n>> "); scanf("%lf",&root); _flushall(); printf("\nEnter accuracy required:\n>>"); scanf("%lf",&accuracy); *data= *newton(root,accuracy,data); printf("Iteration Root Error\n "); printf("%d %lf \n", 0,*(data)); for(int i=1;i<102;i++) { printf("%d %5.5lf %5.5lf\n", i,*(data+i),*(data+i)-*(data+i-1)); if(*(data+i*sizeof(double))-*(data+i*sizeof(double)-1)==0) { break; } } getchar(); getchar(); free(data); return(0); }

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  • How to use an excel data-set for a multi-line ggplot in R?

    - by user1299887
    I have a data set in excel that I am trying to create a multiple line plot with on R. The data set contains 7 food groups and the calories consumed daily associated to the groups. As well, there is that set of data over 38 years (from 1970-2008) and I am attempting to use this data set to create a multiple line plot on R. I have tried for hours on end but can not seem to get R to recognize the variables within the data set.

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  • Configuring Multiple Instances of MySQL in Solaris 11

    - by rajeshr
    Recently someone asked me for steps to configure multiple instances of MySQL database in an Operating Platform. Coz of my familiarity with Solaris OE, I prepared some notes on configuring multiple instances of MySQL database on Solaris 11. Maybe it's useful for some: If you want to run Solaris Operating System (or any other OS of your choice) as a virtualized instance in desktop, consider using Virtual Box. To download Solaris Operating System, click here. Once you have your Solaris Operating System (Version 11) up and running and have Internet connectivity to gain access to the Image Packaging System (IPS), please follow the steps as mentioned below to install MySQL and configure multiple instances: 1. Install MySQL Database in Solaris 11 $ sudo pkg install mysql-51 2. Verify if the mysql is installed: $ svcs -a | grep mysql Note: Service FMRI will look similar to the one here: svc:/application/database/mysql:version_51 3. Prepare data file system for MySQL Instance 1 zfs create rpool/mysql zfs create rpool/mysql/data zfs set mountpoint=/mysql/data rpool/mysql/data 4. Prepare data file system for MySQL Instance 2 zfs create rpool/mysql/data2 zfs set mountpoint=/mysql/data rpool/mysql/data2 5. Change the mysql/datadir of the MySQL Service (SMF) to point to /mysql/data $ svcprop mysql:version_51 | grep mysql/data $ svccfg -s mysql:version_51 setprop mysql/data=/mysql/data 6. Create a new instance of MySQL 5.1 (a) Copy the manifest of the default instance to temporary directory: $ sudo cp /lib/svc/manifest/application/database/mysql_51.xml /var/tmp/mysql_51_2.xml (b) Make appropriate modifications on the XML file $ sudo vi /var/tmp/mysql_51_2.xml - Change the "instance name" section to a new value "version_51_2" - Change the value of property name "data" to point to the ZFS file system "/mysql/data2" 7. Import the manifest to the SMF repository: $ sudo svccfg import /var/tmp/mysql_51_2.xml 8. Before starting the service, copy the file /etc/mysql/my.cnf to the data directories /mysql/data & /mysql/data2. $ sudo cp /etc/mysql/my.cnf /mysql/data/ $ sudo cp /etc/mysql/my.cnf /mysql/data2/ 9. Make modifications to the my.cnf in each of the data directories as required: $ sudo vi /mysql/data/my.cnf Under the [client] section port=3306 socket=/tmp/mysql.sock ---- ---- Under the [mysqld] section port=3306 socket=/tmp/mysql.sock datadir=/mysql/data ----- ----- server-id=1 $ sudo vi /mysql/data2/my.cnf Under the [client] section port=3307 socket=/tmp/mysql2.sock ----- ----- Under the [mysqld] section port=3307 socket=/tmp/mysql2.sock datadir=/mysql/data2 ----- ----- server-id=2 10. Make appropriate modification to the startup script of MySQL (managed by SMF) to point to the appropriate my.cnf for each instance: $ sudo vi /lib/svc/method/mysql_51 Note: Search for all occurences of mysqld_safe command and modify it to include the --defaults-file option. An example entry would look as follows: ${MySQLBIN}/mysqld_safe --defaults-file=${MYSQLDATA}/my.cnf --user=mysql --datadir=${MYSQLDATA} --pid=file=${PIDFILE} 11. Start the service: $ sudo svcadm enable mysql:version_51_2 $ sudo svcadm enable mysql:version_51 12. Verify that the two services are running by using: $ svcs mysql 13. Verify the processes: $ ps -ef | grep mysqld 14. Connect to each mysqld instance and verify: $ mysql --defaults-file=/mysql/data/my.cnf -u root -p $ mysql --defaults-file=/mysql/data2/my.cnf -u root -p Some references for Solaris 11 newbies Taking your first steps with Solaris 11 Introducing the basics of Image Packaging System Service Management Facility How To Guide For a detailed list of official educational modules available on Solaris 11, please visit here For MySQL courses from Oracle University access this page.

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  • How would you gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    I'm relatively new to StackExchange and not sure if it's appropriate place to ask design question. Site gives me a hint "The question you're asking appears subjective and is likely to be closed". Please let me know. Anyway.. One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting? Thank you very much in advance for your thoughts.

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  • How can I gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting?

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  • Are there any Microsoft Exchange Clients for iOS and Android that store their local data in an encrypted manner?

    - by Zac B
    I don't feel like this is a product recommendation question, more of a "does this tech even exist and is it feasible" question, but if I'm wrong, feel free to give this question the boot. Context: Our company has a bunch of traveling employees who access the company's Exchange server via thier iDevices or android phones, but because of the data protection laws in the state where our company is based (and the nature of the data our company works with), a recent security audit found that all mobile devices (laptops, phones, etc) operated by our company need to have all company correspondence and related data encrypted all the time. For laptops, that was easy: BitLocker or TrueCrypt, problem solved. For phones and tablets, however, I'm stumped. Sure, you can put lock screens/passwords on the phones, but the data is still accessible via external extraction, as law enforcement authorities already know. Question: Are there any clients for Microsoft Exchange that run on iOS or Android which store local data encrypted? The people using our mobile devices do a lot of their work while offline, so just giving them OWA access with SSL connection security isn't enough. Are there apps/technologies that present an additional login credential prompt to decrypt locally stored data in the app's storage area on the phone? My gut reaction when I started looking into this was "that doesn't sound like something Apple would allow into the App Store", but I've been wrong before...

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  • Security implications of adding www-data to /etc/sudoers to run php-cgi as a different user

    - by BMiner
    What I really want to do is allow the 'www-data' user to have the ability to launch php-cgi as another user. I just want to make sure that I fully understand the security implications. The server should support a shared hosting environment where various (possibly untrusted) users have chroot'ed FTP access to the server to store their HTML and PHP files. Then, since PHP scripts can be malicious and read/write others' files, I'd like to ensure that each users' PHP scripts run with the same user permissions for that user (instead of running as www-data). Long story short, I have added the following line to my /etc/sudoers file, and I wanted to run it past the community as a sanity check: www-data ALL = (%www-data) NOPASSWD: /usr/bin/php-cgi This line should only allow www-data to run a command like this (without a password prompt): sudo -u some_user /usr/bin/php-cgi ...where some_user is a user in the group www-data. What are the security implications of this? This should then allow me to modify my Lighttpd configuration like this: fastcgi.server += ( ".php" => (( "bin-path" => "sudo -u some_user /usr/bin/php-cgi", "socket" => "/tmp/php.socket", "max-procs" => 1, "bin-environment" => ( "PHP_FCGI_CHILDREN" => "4", "PHP_FCGI_MAX_REQUESTS" => "10000" ), "bin-copy-environment" => ( "PATH", "SHELL", "USER" ), "broken-scriptfilename" => "enable" )) ) ...allowing me to spawn new FastCGI server instances for each user.

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  • Beware Sneaky Reads with Unique Indexes

    - by Paul White NZ
    A few days ago, Sandra Mueller (twitter | blog) asked a question using twitter’s #sqlhelp hash tag: “Might SQL Server retrieve (out-of-row) LOB data from a table, even if the column isn’t referenced in the query?” Leaving aside trivial cases (like selecting a computed column that does reference the LOB data), one might be tempted to say that no, SQL Server does not read data you haven’t asked for.  In general, that’s quite correct; however there are cases where SQL Server might sneakily retrieve a LOB column… Example Table Here’s a T-SQL script to create that table and populate it with 1,000 rows: CREATE TABLE dbo.LOBtest ( pk INTEGER IDENTITY NOT NULL, some_value INTEGER NULL, lob_data VARCHAR(MAX) NULL, another_column CHAR(5) NULL, CONSTRAINT [PK dbo.LOBtest pk] PRIMARY KEY CLUSTERED (pk ASC) ); GO DECLARE @Data VARCHAR(MAX); SET @Data = REPLICATE(CONVERT(VARCHAR(MAX), 'x'), 65540);   WITH Numbers (n) AS ( SELECT ROW_NUMBER() OVER (ORDER BY (SELECT 0)) FROM master.sys.columns C1, master.sys.columns C2 ) INSERT LOBtest WITH (TABLOCKX) ( some_value, lob_data ) SELECT TOP (1000) N.n, @Data FROM Numbers N WHERE N.n <= 1000; Test 1: A Simple Update Let’s run a query to subtract one from every value in the some_value column: UPDATE dbo.LOBtest WITH (TABLOCKX) SET some_value = some_value - 1; As you might expect, modifying this integer column in 1,000 rows doesn’t take very long, or use many resources.  The STATITICS IO and TIME output shows a total of 9 logical reads, and 25ms elapsed time.  The query plan is also very simple: Looking at the Clustered Index Scan, we can see that SQL Server only retrieves the pk and some_value columns during the scan: The pk column is needed by the Clustered Index Update operator to uniquely identify the row that is being changed.  The some_value column is used by the Compute Scalar to calculate the new value.  (In case you are wondering what the Top operator is for, it is used to enforce SET ROWCOUNT). Test 2: Simple Update with an Index Now let’s create a nonclustered index keyed on the some_value column, with lob_data as an included column: CREATE NONCLUSTERED INDEX [IX dbo.LOBtest some_value (lob_data)] ON dbo.LOBtest (some_value) INCLUDE ( lob_data ) WITH ( FILLFACTOR = 100, MAXDOP = 1, SORT_IN_TEMPDB = ON ); This is not a useful index for our simple update query; imagine that someone else created it for a different purpose.  Let’s run our update query again: UPDATE dbo.LOBtest WITH (TABLOCKX) SET some_value = some_value - 1; We find that it now requires 4,014 logical reads and the elapsed query time has increased to around 100ms.  The extra logical reads (4 per row) are an expected consequence of maintaining the nonclustered index. The query plan is very similar to before (click to enlarge): The Clustered Index Update operator picks up the extra work of maintaining the nonclustered index. The new Compute Scalar operators detect whether the value in the some_value column has actually been changed by the update.  SQL Server may be able to skip maintaining the nonclustered index if the value hasn’t changed (see my previous post on non-updating updates for details).  Our simple query does change the value of some_data in every row, so this optimization doesn’t add any value in this specific case. The output list of columns from the Clustered Index Scan hasn’t changed from the one shown previously: SQL Server still just reads the pk and some_data columns.  Cool. Overall then, adding the nonclustered index hasn’t had any startling effects, and the LOB column data still isn’t being read from the table.  Let’s see what happens if we make the nonclustered index unique. Test 3: Simple Update with a Unique Index Here’s the script to create a new unique index, and drop the old one: CREATE UNIQUE NONCLUSTERED INDEX [UQ dbo.LOBtest some_value (lob_data)] ON dbo.LOBtest (some_value) INCLUDE ( lob_data ) WITH ( FILLFACTOR = 100, MAXDOP = 1, SORT_IN_TEMPDB = ON ); GO DROP INDEX [IX dbo.LOBtest some_value (lob_data)] ON dbo.LOBtest; Remember that SQL Server only enforces uniqueness on index keys (the some_data column).  The lob_data column is simply stored at the leaf-level of the non-clustered index.  With that in mind, we might expect this change to make very little difference.  Let’s see: UPDATE dbo.LOBtest WITH (TABLOCKX) SET some_value = some_value - 1; Whoa!  Now look at the elapsed time and logical reads: Scan count 1, logical reads 2016, physical reads 0, read-ahead reads 0, lob logical reads 36015, lob physical reads 0, lob read-ahead reads 15992.   CPU time = 172 ms, elapsed time = 16172 ms. Even with all the data and index pages in memory, the query took over 16 seconds to update just 1,000 rows, performing over 52,000 LOB logical reads (nearly 16,000 of those using read-ahead). Why on earth is SQL Server reading LOB data in a query that only updates a single integer column? The Query Plan The query plan for test 3 looks a bit more complex than before: In fact, the bottom level is exactly the same as we saw with the non-unique index.  The top level has heaps of new stuff though, which I’ll come to in a moment. You might be expecting to find that the Clustered Index Scan is now reading the lob_data column (for some reason).  After all, we need to explain where all the LOB logical reads are coming from.  Sadly, when we look at the properties of the Clustered Index Scan, we see exactly the same as before: SQL Server is still only reading the pk and some_value columns – so what’s doing the LOB reads? Updates that Sneakily Read Data We have to go as far as the Clustered Index Update operator before we see LOB data in the output list: [Expr1020] is a bit flag added by an earlier Compute Scalar.  It is set true if the some_value column has not been changed (part of the non-updating updates optimization I mentioned earlier). The Clustered Index Update operator adds two new columns: the lob_data column, and some_value_OLD.  The some_value_OLD column, as the name suggests, is the pre-update value of the some_value column.  At this point, the clustered index has already been updated with the new value, but we haven’t touched the nonclustered index yet. An interesting observation here is that the Clustered Index Update operator can read a column into the data flow as part of its update operation.  SQL Server could have read the LOB data as part of the initial Clustered Index Scan, but that would mean carrying the data through all the operations that occur prior to the Clustered Index Update.  The server knows it will have to go back to the clustered index row to update it, so it delays reading the LOB data until then.  Sneaky! Why the LOB Data Is Needed This is all very interesting (I hope), but why is SQL Server reading the LOB data?  For that matter, why does it need to pass the pre-update value of the some_value column out of the Clustered Index Update? The answer relates to the top row of the query plan for test 3.  I’ll reproduce it here for convenience: Notice that this is a wide (per-index) update plan.  SQL Server used a narrow (per-row) update plan in test 2, where the Clustered Index Update took care of maintaining the nonclustered index too.  I’ll talk more about this difference shortly. The Split/Sort/Collapse combination is an optimization, which aims to make per-index update plans more efficient.  It does this by breaking each update into a delete/insert pair, reordering the operations, removing any redundant operations, and finally applying the net effect of all the changes to the nonclustered index. Imagine we had a unique index which currently holds three rows with the values 1, 2, and 3.  If we run a query that adds 1 to each row value, we would end up with values 2, 3, and 4.  The net effect of all the changes is the same as if we simply deleted the value 1, and added a new value 4. By applying net changes, SQL Server can also avoid false unique-key violations.  If we tried to immediately update the value 1 to a 2, it would conflict with the existing value 2 (which would soon be updated to 3 of course) and the query would fail.  You might argue that SQL Server could avoid the uniqueness violation by starting with the highest value (3) and working down.  That’s fine, but it’s not possible to generalize this logic to work with every possible update query. SQL Server has to use a wide update plan if it sees any risk of false uniqueness violations.  It’s worth noting that the logic SQL Server uses to detect whether these violations are possible has definite limits.  As a result, you will often receive a wide update plan, even when you can see that no violations are possible. Another benefit of this optimization is that it includes a sort on the index key as part of its work.  Processing the index changes in index key order promotes sequential I/O against the nonclustered index. A side-effect of all this is that the net changes might include one or more inserts.  In order to insert a new row in the index, SQL Server obviously needs all the columns – the key column and the included LOB column.  This is the reason SQL Server reads the LOB data as part of the Clustered Index Update. In addition, the some_value_OLD column is required by the Split operator (it turns updates into delete/insert pairs).  In order to generate the correct index key delete operation, it needs the old key value. The irony is that in this case the Split/Sort/Collapse optimization is anything but.  Reading all that LOB data is extremely expensive, so it is sad that the current version of SQL Server has no way to avoid it. Finally, for completeness, I should mention that the Filter operator is there to filter out the non-updating updates. Beating the Set-Based Update with a Cursor One situation where SQL Server can see that false unique-key violations aren’t possible is where it can guarantee that only one row is being updated.  Armed with this knowledge, we can write a cursor (or the WHILE-loop equivalent) that updates one row at a time, and so avoids reading the LOB data: SET NOCOUNT ON; SET STATISTICS XML, IO, TIME OFF;   DECLARE @PK INTEGER, @StartTime DATETIME; SET @StartTime = GETUTCDATE();   DECLARE curUpdate CURSOR LOCAL FORWARD_ONLY KEYSET SCROLL_LOCKS FOR SELECT L.pk FROM LOBtest L ORDER BY L.pk ASC;   OPEN curUpdate;   WHILE (1 = 1) BEGIN FETCH NEXT FROM curUpdate INTO @PK;   IF @@FETCH_STATUS = -1 BREAK; IF @@FETCH_STATUS = -2 CONTINUE;   UPDATE dbo.LOBtest SET some_value = some_value - 1 WHERE CURRENT OF curUpdate; END;   CLOSE curUpdate; DEALLOCATE curUpdate;   SELECT DATEDIFF(MILLISECOND, @StartTime, GETUTCDATE()); That completes the update in 1280 milliseconds (remember test 3 took over 16 seconds!) I used the WHERE CURRENT OF syntax there and a KEYSET cursor, just for the fun of it.  One could just as well use a WHERE clause that specified the primary key value instead. Clustered Indexes A clustered index is the ultimate index with included columns: all non-key columns are included columns in a clustered index.  Let’s re-create the test table and data with an updatable primary key, and without any non-clustered indexes: IF OBJECT_ID(N'dbo.LOBtest', N'U') IS NOT NULL DROP TABLE dbo.LOBtest; GO CREATE TABLE dbo.LOBtest ( pk INTEGER NOT NULL, some_value INTEGER NULL, lob_data VARCHAR(MAX) NULL, another_column CHAR(5) NULL, CONSTRAINT [PK dbo.LOBtest pk] PRIMARY KEY CLUSTERED (pk ASC) ); GO DECLARE @Data VARCHAR(MAX); SET @Data = REPLICATE(CONVERT(VARCHAR(MAX), 'x'), 65540);   WITH Numbers (n) AS ( SELECT ROW_NUMBER() OVER (ORDER BY (SELECT 0)) FROM master.sys.columns C1, master.sys.columns C2 ) INSERT LOBtest WITH (TABLOCKX) ( pk, some_value, lob_data ) SELECT TOP (1000) N.n, N.n, @Data FROM Numbers N WHERE N.n <= 1000; Now here’s a query to modify the cluster keys: UPDATE dbo.LOBtest SET pk = pk + 1; The query plan is: As you can see, the Split/Sort/Collapse optimization is present, and we also gain an Eager Table Spool, for Halloween protection.  In addition, SQL Server now has no choice but to read the LOB data in the Clustered Index Scan: The performance is not great, as you might expect (even though there is no non-clustered index to maintain): Table 'LOBtest'. Scan count 1, logical reads 2011, physical reads 0, read-ahead reads 0, lob logical reads 36015, lob physical reads 0, lob read-ahead reads 15992.   Table 'Worktable'. Scan count 1, logical reads 2040, physical reads 0, read-ahead reads 0, lob logical reads 34000, lob physical reads 0, lob read-ahead reads 8000.   SQL Server Execution Times: CPU time = 483 ms, elapsed time = 17884 ms. Notice how the LOB data is read twice: once from the Clustered Index Scan, and again from the work table in tempdb used by the Eager Spool. If you try the same test with a non-unique clustered index (rather than a primary key), you’ll get a much more efficient plan that just passes the cluster key (including uniqueifier) around (no LOB data or other non-key columns): A unique non-clustered index (on a heap) works well too: Both those queries complete in a few tens of milliseconds, with no LOB reads, and just a few thousand logical reads.  (In fact the heap is rather more efficient). There are lots more fun combinations to try that I don’t have space for here. Final Thoughts The behaviour shown in this post is not limited to LOB data by any means.  If the conditions are met, any unique index that has included columns can produce similar behaviour – something to bear in mind when adding large INCLUDE columns to achieve covering queries, perhaps. Paul White Email: [email protected] Twitter: @PaulWhiteNZ

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