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  • What is the most complicated data structure you have used in a practical situation?

    - by Fanatic23
    The germ for this question came up from a discussion I was having with couple of fellow developers from the industry. Turns out that in a lot of places project managers are wary about complex data structures, and generally insist on whatever exists out-of-the-box from standard library/packages. The general idea seems to be like use a combination of whats already available unless performance is seriously impeded. This helps keeping the code base simple, which to the non-diplomatic would mean "we have high attrition, and newer ones we hire may not be that good". So no bloom filter or skip-lists or splay trees for you CS junkies. So here's the question (again): Whats the most complicated data structure you did or used in office? Helps get a sense of how good/sophisticated real world software are.

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  • Is it a good practice to use smaller data types for variables to save memory?

    - by ThePlan
    When I learned the C++ language for the first time I learned that besides int, float etc, smaller or bigger versions of these data types existed within the language. For example I could call a variable x int x; or short int x; The main difference being that short int takes 2 bytes of memory while int takes 4 bytes, and short int has a lesser value, but we could also call this to make it even smaller: int x; short int x; unsigned short int x; which is even more restrictive. My question here is if it's a good practice to use separate data types according to what values your variable take within the program. Is it a good idea to always declare variables according to these data types?

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  • SQL SERVER – Integrate Your Data with Skyvia – Cloud ETL Solution

    - by Pinal Dave
    In our days data integration often becomes a key aspect of business success. For business analysts it’s very important to get integrated data from various sources, such as relational databases, cloud CRMs, etc. to make correct and successful decisions. There are various data integration solutions on market, and today I will tell about one of them – Skyvia. Skyvia is a cloud data integration service, which allows integrating data in cloud CRMs and different relational databases. It is a completely online solution and does not require anything except for a browser. Skyvia provides powerful etl tools for data import, export, replication, and synchronization for SQL Server and other databases and cloud CRMs. You can use Skyvia data import tools to load data from various sources to SQL Server (and SQL Azure). Skyvia supports such cloud CRMs as Salesforce and Microsoft Dynamics CRM and such databases as MySQL and PostgreSQL. You even can migrate data from SQL Server to SQL Server, or from SQL Server to other databases and cloud CRMs. Additionally Skyvia supports import of CSV files, either uploaded manually or stored on cloud file storage services, such as Dropbox, Box, Google Drive, or FTP servers. When data import is not enough, Skyvia offers bidirectional data synchronization. With this tool, you can synchronize SQL Server data with other databases and cloud CRMs. After performing the first synchronization, Skyvia tracks data changes in the synchronized data storages. In SQL Server databases (and other relational databases) it creates additional tracking tables and triggers. This allows synchronizing only the changed data. Skyvia also maps records by their primary key values to each other, so it does not require different sources to have the same primary key structure. It still can match the corresponding records without having to add any additional columns or changing data structure. The only requirement for synchronization is that primary keys must be autogenerated. With Skyvia it’s not necessary for data to have the same structure in integrated data storages. Skyvia supports powerful mapping mechanisms that allow synchronizing data with completely different structure. It provides support for complex mathematical and string expressions when mapping data, using lookups, etc. You may use data splitting – loading data from a single CSV file or source table to multiple related target tables. Or you may load data from several source CSV files or tables to several related target tables. In each case Skyvia preserves data relations. It builds corresponding relations between the target data automatically. When you often work with cloud CRM data, native CRM data reporting and analysis tools may be not enough for you. And there is a vast set of professional data analysis and reporting tools available for SQL Server. With Skyvia you can quickly copy your cloud CRM data to an SQL Server database and apply corresponding SQL Server tools to the data. In such case you can use Skyvia data replication tools. It allows you to quickly copy cloud CRM data to SQL Server or other databases without customizing any mapping. You need just to specify columns to copy data from. Target database tables will be created automatically. Skyvia offers powerful filtering settings to replicate only the records you need. Skyvia also provides capability to export data from SQL Server (including SQL Azure) and other databases and cloud CRMs to CSV files. These files can be either downloadable manually or loaded to cloud file storages or FTP server. You can use export, for example, to backup SQL Azure data to Dropbox. Any data integration operation can be scheduled for automatic execution. Thus, you can automate your SQL Azure data backup or data synchronization – just configure it once, then schedule it, and benefit from automatic data integration with Skyvia. Currently registration and using Skyvia is completely free, so you can try it yourself and find out whether its data migration and integration tools suits for you. Visit this link to register on Skyvia: https://app.skyvia.com/register Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Cloud Computing

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  • SQL SERVER – Why Do We Need Master Data Management – Importance and Significance of Master Data Management (MDM)

    - by pinaldave
    Let me paint a picture of everyday life for you.  Let’s say you and your wife both have address books for your groups of friends.  There is definitely overlap between them, so that you both have the addresses for your mutual friends, and there are addresses that only you know, and some only she knows.  They also might be organized differently.  You might list your friend under “J” for “Joe” or even under “W” for “Work,” while she might list him under “S” for “Joe Smith” or under your name because he is your friend.  If you happened to trade, neither of you would be able to find anything! This is where data management would be very important.  If you were to consolidate into one address book, you would have to set rules about how to organize the book, and both of you would have to follow them.  You would also make sure that poor Joe doesn’t get entered twice under “J” and under “S.” This might be a familiar situation to you, whether you are thinking about address books, record collections, books, or even shopping lists.  Wherever there is a lot of data to consolidate, you are going to run into problems unless everyone is following the same rules. I’m sure that my readers can figure out where I am going with this.  What is SQL Server but a computerized way to organize data?  And Microsoft is making it easier and easier to get all your “addresses” into one place.  In the  2008 version of SQL they introduced a new tool called Master Data Services (MDS) for Master Data Management, and they have improved it for the new 2012 version. MDM was hailed as a major improvement for business intelligence.  You might not think that an organizational system is terribly exciting, but think about the kind of “address books” a company might have.  Many companies have lots of important information, like addresses, credit card numbers, purchase history, and so much more.  To organize all this efficiently so that customers are well cared for and properly billed (only once, not never or multiple times!) is a major part of business intelligence. MDM comes into play because it will comb through these mountains of data and make sure that all the information is consistent, accurate, and all placed in one database so that employees don’t have to search high and low and waste their time. MDM also has operational MDM functions.  This is not a redundancy.  Operational MDM means that when one employee updates one bit of information in the database, for example – updating a new address for a customer, operational MDM ensures that this address is updated throughout the system so that all departments will have the correct information. Another cool thing about MDM is that it features Master Data Services Configuration Manager, which is exactly what it sounds like.  It has a built-in “helper” that lets you set up your database quickly, easily, and with the correct configurations.  While talking about cool features, I can’t skip over the add-in for Excel.  This allows you to link certain data to Excel files for easier sharing and uploading. In summary, I want to emphasize that the scariest part of the database is slowly disappearing.  Everyone knows that a database – one consolidated area for all your data – is a good idea, but the idea of setting one up is daunting.  But SQL Server is making data management easier and easier with features like Master Data Services (MDS). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Master Data Services, MDM

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  • Data breakpoints to find points where data gets broken

    - by raccoon_tim
    When working with a large code base, finding reasons for bizarre bugs can often be like finding a needle in a hay stack. Finding out why an object gets corrupted without no apparent reason can be quite daunting, especially when it seems to happen randomly and totally out of context. Scenario Take the following scenario as an example. You have defined the a class that contains an array of characters that is 256 characters long. You now implement a method for filling this buffer with a string passed as an argument. At this point you mistakenly expect the buffer to be 256 characters long. At some point you notice that you require another character buffer and you add that after the previous one in the class definition. You now figure that you don’t need the 256 characters that the first member can hold and you shorten that to 128 to conserve space. At this point you should start thinking that you also have to modify the method defined above to safeguard against buffer overflow. It so happens, however, that in this not so perfect world this does not cross your mind. Buffer overflow is one of the most frequent sources for errors in a piece of software and often one of the most difficult ones to detect, especially when data is read from an outside source. Many mass copy functions provided by the C run-time provide versions that have boundary checking (defined with the _s suffix) but they can not guard against hard coded buffer lengths that at some point get changed. Finding the bug Getting back to the scenario, you’re now wondering why does the second string get modified with data that makes no sense at all. Luckily, Visual Studio provides you with a tool to help you with finding just these kinds of errors. It’s called data breakpoints. To add a data breakpoint, you first run your application in debug mode or attach to it in the usual way, and then go to Debug, select New Breakpoint and New Data Breakpoint. In the popup that opens, you can type in the memory address and the amount of bytes you wish to monitor. You can also use an expression here, but it’s often difficult to come up with an expression for data in an object allocated on the heap when not in the context of a certain stack frame. There are a couple of things to note about data breakpoints, however. First of all, Visual Studio supports a maximum of four data breakpoints at any given time. Another important thing to notice is that some C run-time functions modify memory in kernel space which does not trigger the data breakpoint. For instance, calling ReadFile on a buffer that is monitored by a data breakpoint will not trigger the breakpoint. The application will now break at the address you specified it to. Often you might immediately spot the issue but the very least this feature can do is point you in the right direction in search for the real reason why the memory gets inadvertently modified. Conclusions Data breakpoints are a great feature, especially when doing a lot of low level operations where multiple locations modify the same data. With the exception of some special cases, like kernel memory modification, you can use it whenever you need to check when memory at a certain location gets changed on purpose or inadvertently.

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  • Metro: Declarative Data Binding

    - by Stephen.Walther
    The goal of this blog post is to describe how declarative data binding works in the WinJS library. In particular, you learn how to use both the data-win-bind and data-win-bindsource attributes. You also learn how to use calculated properties and converters to format the value of a property automatically when performing data binding. By taking advantage of WinJS data binding, you can use the Model-View-ViewModel (MVVM) pattern when building Metro style applications with JavaScript. By using the MVVM pattern, you can prevent your JavaScript code from spinning into chaos. The MVVM pattern provides you with a standard pattern for organizing your JavaScript code which results in a more maintainable application. Using Declarative Bindings You can use the data-win-bind attribute with any HTML element in a page. The data-win-bind attribute enables you to bind (associate) an attribute of an HTML element to the value of a property. Imagine, for example, that you want to create a product details page. You want to show a product object in a page. In that case, you can create the following HTML page to display the product details: <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>Application1</title> <!-- WinJS references --> <link href="//Microsoft.WinJS.0.6/css/ui-dark.css" rel="stylesheet"> <script src="//Microsoft.WinJS.0.6/js/base.js"></script> <script src="//Microsoft.WinJS.0.6/js/ui.js"></script> <!-- Application1 references --> <link href="/css/default.css" rel="stylesheet"> <script src="/js/default.js"></script> </head> <body> <h1>Product Details</h1> <div class="field"> Product Name: <span data-win-bind="innerText:name"></span> </div> <div class="field"> Product Price: <span data-win-bind="innerText:price"></span> </div> <div class="field"> Product Picture: <br /> <img data-win-bind="src:photo;alt:name" /> </div> </body> </html> The HTML page above contains three data-win-bind attributes – one attribute for each product property displayed. You use the data-win-bind attribute to set properties of the HTML element associated with the data-win-attribute. The data-win-bind attribute takes a semicolon delimited list of element property names and data source property names: data-win-bind=”elementPropertyName:datasourcePropertyName; elementPropertyName:datasourcePropertyName;…” In the HTML page above, the first two data-win-bind attributes are used to set the values of the innerText property of the SPAN elements. The last data-win-bind attribute is used to set the values of the IMG element’s src and alt attributes. By the way, using data-win-bind attributes is perfectly valid HTML5. The HTML5 standard enables you to add custom attributes to an HTML document just as long as the custom attributes start with the prefix data-. So you can add custom attributes to an HTML5 document with names like data-stephen, data-funky, or data-rover-dog-is-hungry and your document will validate. The product object displayed in the page above with the data-win-bind attributes is created in the default.js file: (function () { "use strict"; var app = WinJS.Application; app.onactivated = function (eventObject) { if (eventObject.detail.kind === Windows.ApplicationModel.Activation.ActivationKind.launch) { var product = { name: "Tesla", price: 80000, photo: "/images/TeslaPhoto.png" }; WinJS.Binding.processAll(null, product); } }; app.start(); })(); In the code above, a product object is created with a name, price, and photo property. The WinJS.Binding.processAll() method is called to perform the actual binding (Don’t confuse WinJS.Binding.processAll() and WinJS.UI.processAll() – these are different methods). The first parameter passed to the processAll() method represents the root element for the binding. In other words, binding happens on this element and its child elements. If you provide the value null, then binding happens on the entire body of the document (document.body). The second parameter represents the data context. This is the object that has the properties which are displayed with the data-win-bind attributes. In the code above, the product object is passed as the data context parameter. Another word for data context is view model.  Creating Complex View Models In the previous section, we used the data-win-bind attribute to display the properties of a simple object: a single product. However, you can use binding with more complex view models including view models which represent multiple objects. For example, the view model in the following default.js file represents both a customer and a product object. Furthermore, the customer object has a nested address object: (function () { "use strict"; var app = WinJS.Application; app.onactivated = function (eventObject) { if (eventObject.detail.kind === Windows.ApplicationModel.Activation.ActivationKind.launch) { var viewModel = { customer: { firstName: "Fred", lastName: "Flintstone", address: { street: "1 Rocky Way", city: "Bedrock", country: "USA" } }, product: { name: "Bowling Ball", price: 34.55 } }; WinJS.Binding.processAll(null, viewModel); } }; app.start(); })(); The following page displays the customer (including the customer address) and the product. Notice that you can use dot notation to refer to child objects in a view model such as customer.address.street. <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>Application1</title> <!-- WinJS references --> <link href="//Microsoft.WinJS.0.6/css/ui-dark.css" rel="stylesheet"> <script src="//Microsoft.WinJS.0.6/js/base.js"></script> <script src="//Microsoft.WinJS.0.6/js/ui.js"></script> <!-- Application1 references --> <link href="/css/default.css" rel="stylesheet"> <script src="/js/default.js"></script> </head> <body> <h1>Customer Details</h1> <div class="field"> First Name: <span data-win-bind="innerText:customer.firstName"></span> </div> <div class="field"> Last Name: <span data-win-bind="innerText:customer.lastName"></span> </div> <div class="field"> Address: <address> <span data-win-bind="innerText:customer.address.street"></span> <br /> <span data-win-bind="innerText:customer.address.city"></span> <br /> <span data-win-bind="innerText:customer.address.country"></span> </address> </div> <h1>Product</h1> <div class="field"> Name: <span data-win-bind="innerText:product.name"></span> </div> <div class="field"> Price: <span data-win-bind="innerText:product.price"></span> </div> </body> </html> A view model can be as complicated as you need and you can bind the view model to a view (an HTML document) by using declarative bindings. Creating Calculated Properties You might want to modify a property before displaying the property. For example, you might want to format the product price property before displaying the property. You don’t want to display the raw product price “80000”. Instead, you want to display the formatted price “$80,000”. You also might need to combine multiple properties. For example, you might need to display the customer full name by combining the values of the customer first and last name properties. In these situations, it is tempting to call a function when performing binding. For example, you could create a function named fullName() which concatenates the customer first and last name. Unfortunately, the WinJS library does not support the following syntax: <span data-win-bind=”innerText:fullName()”></span> Instead, in these situations, you should create a new property in your view model that has a getter. For example, the customer object in the following default.js file includes a property named fullName which combines the values of the firstName and lastName properties: (function () { "use strict"; var app = WinJS.Application; app.onactivated = function (eventObject) { if (eventObject.detail.kind === Windows.ApplicationModel.Activation.ActivationKind.launch) { var customer = { firstName: "Fred", lastName: "Flintstone", get fullName() { return this.firstName + " " + this.lastName; } }; WinJS.Binding.processAll(null, customer); } }; app.start(); })(); The customer object has a firstName, lastName, and fullName property. Notice that the fullName property is defined with a getter function. When you read the fullName property, the values of the firstName and lastName properties are concatenated and returned. The following HTML page displays the fullName property in an H1 element. You can use the fullName property in a data-win-bind attribute in exactly the same way as any other property. <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>Application1</title> <!-- WinJS references --> <link href="//Microsoft.WinJS.0.6/css/ui-dark.css" rel="stylesheet"> <script src="//Microsoft.WinJS.0.6/js/base.js"></script> <script src="//Microsoft.WinJS.0.6/js/ui.js"></script> <!-- Application1 references --> <link href="/css/default.css" rel="stylesheet"> <script src="/js/default.js"></script> </head> <body> <h1 data-win-bind="innerText:fullName"></h1> <div class="field"> First Name: <span data-win-bind="innerText:firstName"></span> </div> <div class="field"> Last Name: <span data-win-bind="innerText:lastName"></span> </div> </body> </html> Creating a Converter In the previous section, you learned how to format the value of a property by creating a property with a getter. This approach makes sense when the formatting logic is specific to a particular view model. If, on the other hand, you need to perform the same type of formatting for multiple view models then it makes more sense to create a converter function. A converter function is a function which you can apply whenever you are using the data-win-bind attribute. Imagine, for example, that you want to create a general function for displaying dates. You always want to display dates using a short format such as 12/25/1988. The following JavaScript file – named converters.js – contains a shortDate() converter: (function (WinJS) { var shortDate = WinJS.Binding.converter(function (date) { return date.getMonth() + 1 + "/" + date.getDate() + "/" + date.getFullYear(); }); // Export shortDate WinJS.Namespace.define("MyApp.Converters", { shortDate: shortDate }); })(WinJS); The file above uses the Module Pattern, a pattern which is used through the WinJS library. To learn more about the Module Pattern, see my blog entry on namespaces and modules: http://stephenwalther.com/blog/archive/2012/02/22/windows-web-applications-namespaces-and-modules.aspx The file contains the definition for a converter function named shortDate(). This function converts a JavaScript date object into a short date string such as 12/1/1988. The converter function is created with the help of the WinJS.Binding.converter() method. This method takes a normal function and converts it into a converter function. Finally, the shortDate() converter is added to the MyApp.Converters namespace. You can call the shortDate() function by calling MyApp.Converters.shortDate(). The default.js file contains the customer object that we want to bind. Notice that the customer object has a firstName, lastName, and birthday property. We will use our new shortDate() converter when displaying the customer birthday property: (function () { "use strict"; var app = WinJS.Application; app.onactivated = function (eventObject) { if (eventObject.detail.kind === Windows.ApplicationModel.Activation.ActivationKind.launch) { var customer = { firstName: "Fred", lastName: "Flintstone", birthday: new Date("12/1/1988") }; WinJS.Binding.processAll(null, customer); } }; app.start(); })(); We actually use our shortDate converter in the HTML document. The following HTML document displays all of the customer properties: <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>Application1</title> <!-- WinJS references --> <link href="//Microsoft.WinJS.0.6/css/ui-dark.css" rel="stylesheet"> <script src="//Microsoft.WinJS.0.6/js/base.js"></script> <script src="//Microsoft.WinJS.0.6/js/ui.js"></script> <!-- Application1 references --> <link href="/css/default.css" rel="stylesheet"> <script src="/js/default.js"></script> <script type="text/javascript" src="js/converters.js"></script> </head> <body> <h1>Customer Details</h1> <div class="field"> First Name: <span data-win-bind="innerText:firstName"></span> </div> <div class="field"> Last Name: <span data-win-bind="innerText:lastName"></span> </div> <div class="field"> Birthday: <span data-win-bind="innerText:birthday MyApp.Converters.shortDate"></span> </div> </body> </html> Notice the data-win-bind attribute used to display the birthday property. It looks like this: <span data-win-bind="innerText:birthday MyApp.Converters.shortDate"></span> The shortDate converter is applied to the birthday property when the birthday property is bound to the SPAN element’s innerText property. Using data-win-bindsource Normally, you pass the view model (the data context) which you want to use with the data-win-bind attributes in a page by passing the view model to the WinJS.Binding.processAll() method like this: WinJS.Binding.processAll(null, viewModel); As an alternative, you can specify the view model declaratively in your markup by using the data-win-datasource attribute. For example, the following default.js script exposes a view model with the fully-qualified name of MyWinWebApp.viewModel: (function () { "use strict"; var app = WinJS.Application; app.onactivated = function (eventObject) { if (eventObject.detail.kind === Windows.ApplicationModel.Activation.ActivationKind.launch) { // Create view model var viewModel = { customer: { firstName: "Fred", lastName: "Flintstone" }, product: { name: "Bowling Ball", price: 12.99 } }; // Export view model to be seen by universe WinJS.Namespace.define("MyWinWebApp", { viewModel: viewModel }); // Process data-win-bind attributes WinJS.Binding.processAll(); } }; app.start(); })(); In the code above, a view model which represents a customer and a product is exposed as MyWinWebApp.viewModel. The following HTML page illustrates how you can use the data-win-bindsource attribute to bind to this view model: <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>Application1</title> <!-- WinJS references --> <link href="//Microsoft.WinJS.0.6/css/ui-dark.css" rel="stylesheet"> <script src="//Microsoft.WinJS.0.6/js/base.js"></script> <script src="//Microsoft.WinJS.0.6/js/ui.js"></script> <!-- Application1 references --> <link href="/css/default.css" rel="stylesheet"> <script src="/js/default.js"></script> </head> <body> <h1>Customer Details</h1> <div data-win-bindsource="MyWinWebApp.viewModel.customer"> <div class="field"> First Name: <span data-win-bind="innerText:firstName"></span> </div> <div class="field"> Last Name: <span data-win-bind="innerText:lastName"></span> </div> </div> <h1>Product</h1> <div data-win-bindsource="MyWinWebApp.viewModel.product"> <div class="field"> Name: <span data-win-bind="innerText:name"></span> </div> <div class="field"> Price: <span data-win-bind="innerText:price"></span> </div> </div> </body> </html> The data-win-bindsource attribute is used twice in the page above: it is used with the DIV element which contains the customer details and it is used with the DIV element which contains the product details. If an element has a data-win-bindsource attribute then all of the child elements of that element are affected. The data-win-bind attributes of all of the child elements are bound to the data source represented by the data-win-bindsource attribute. Summary The focus of this blog entry was data binding using the WinJS library. You learned how to use the data-win-bind attribute to bind the properties of an HTML element to a view model. We also discussed several advanced features of data binding. We examined how to create calculated properties by including a property with a getter in your view model. We also discussed how you can create a converter function to format the value of a view model property when binding the property. Finally, you learned how to use the data-win-bindsource attribute to specify a view model declaratively.

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  • SQL Server Management Data Warehouse - quick tour on setting health monitoring policies

    - by ssqa.net
    Profiler, Perfmon, DMVs & scripts are legendary tools for a DBA to monitor the SQL arena. In line with these tools SQL Server 2008 throws a powerful stream with policy based management (PBM) framework & management data warehouse (MDW) methods, which is a relational database that contains the data that is collected from a server that is a data collection target. This data is used to generate the reports for the System Data collection sets, and can also be used to create custom reports. .....(read more)

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  • Data Flow Diagrams - Difference between Lines and Arrows

    - by Howdy_McGee
    I'm currently working with Visio to create Data Flow Diagrams for a System Analysis and Design class but I'm unsure what the difference between ------ and ------> is. I can connect 2 shapes together with a line (process, entity, data store) but does the single line connecting the two mean data flow? Do I need to explicitly use the data flow arrow to show which way data is flowing? (There doesn't seem to be tags for this topic, maybe im in the wrong place?)

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  • Big Data Videos

    - by Jean-Pierre Dijcks
    You can view them all on YouTube using the following links: Overview for the Boss: http://youtu.be/ikJyrmKdJWc Hadoop: http://youtu.be/acWtid-OOWM Acquiring Big Data: http://youtu.be/TfuhuA_uaho Organizing Big Data: http://youtu.be/IC6jVRO2Hq4 Analyzing Big Data: http://youtu.be/2yf_jrBhz5w These videos are a great place to start learning about big data, the value it can bring to your organisation and how Oracle can help you start working with big data today.

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  • SQL Server and the XML Data Type : Data Manipulation

    The introduction of the xml data type, with its own set of methods for processing xml data, made it possible for SQL Server developers to create columns and variables of the type xml. Deanna Dicken examines the modify() method, which provides for data manipulation of the XML data stored in the xml data type via XML DML statements.

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  • Behavior of <- NULL on lists versus data.frames for removing data

    - by Ananda Mahto
    Many R users eventually figure out lots of ways to remove elements from their data. One way is to use NULL, particularly when you want to do something like drop a column from a data.frame or drop an element from a list. Eventually, a user comes across a situation where they want to drop several columns from a data.frame at once, and they hit upon <- list(NULL) as the solution (since using <- NULL will result in an error). A data.frame is a special type of list, so it wouldn't be too tough to imagine that the approaches for removing items from a list should be the same as removing columns from a data.frame. However, they produce different results, as can be seen in the example below. ## Make some small data--two data.frames and two lists cars1 <- cars2 <- head(mtcars)[1:4] cars3 <- cars4 <- as.list(cars2) ## Demonstration that the `list(NULL)` approach works cars1[c("mpg", "cyl")] <- list(NULL) cars1 # disp hp # Mazda RX4 160 110 # Mazda RX4 Wag 160 110 # Datsun 710 108 93 # Hornet 4 Drive 258 110 # Hornet Sportabout 360 175 # Valiant 225 105 ## Demonstration that simply using `NULL` does not work cars2[c("mpg", "cyl")] <- NULL # Error in `[<-.data.frame`(`*tmp*`, c("mpg", "cyl"), value = NULL) : # replacement has 0 items, need 12 Switch to applying the same concept to a list, and compare the difference in behavior. ## Does not fully drop the items, but sets them to `NULL` cars3[c("mpg", "cyl")] <- list(NULL) # $mpg # NULL # # $cyl # NULL # # $disp # [1] 160 160 108 258 360 225 # # $hp # [1] 110 110 93 110 175 105 ## *Does* drop the `list` items while this would ## have produced an error with a `data.frame` cars4[c("mpg", "cyl")] <- NULL # $disp # [1] 160 160 108 258 360 225 # # $hp # [1] 110 110 93 110 175 105 The main questions I have are, if a data.frame is a list, why does it behave so differently in this scenario? Is there a foolproof way of knowing when an element will be dropped, when it will produce an error, and when it will simply be given a NULL value? Or do we depend on trial-and-error for this?

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  • How does jQuery stores data with .data()?

    - by TK
    I am a little confused how jQuery stores data with .data() functions. Is this something called expando? Or is this using HTML5 Web Storage although I think this is very unlikely? The documentation says: The .data() method allows us to attach data of any type to DOM elements in a way that is safe from circular references and therefore from memory leaks. As I read about expando, it seems to have a rick of memory leak. Unfortunately my skills are not enough to read and understand jQuery code itself, but I want to know how jQuery stores such data by using data(). http://api.jquery.com/data/

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  • ASP.Net Layered app - Share Entity Data Model amongst layers

    - by Chris Klepeis
    How can I share the auto-generated entity data model (generated object classes) amongst all layers of my C# web app whilst only granting query access in the data layer? This uses the typical 3 layer approach: data, business, presentation. My data layer returns an IEnumerable<T> to my business layer, but I cannot return type T to the presentation layer because I do not want the presentation layer to know of the existence of the data layer - which is where the entity framework auto-generated my classes. It was recommended to have a seperate layer with just the data model, but I'm unsure how to seperate the data model from the query functionality the entity framework provides.

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  • How does jQuery store data with .data()?

    - by TK
    I am a little confused how jQuery stores data with .data() functions. Is this something called expando? Or is this using HTML5 Web Storage although I think this is very unlikely? The documentation says: The .data() method allows us to attach data of any type to DOM elements in a way that is safe from circular references and therefore from memory leaks. As I read about expando, it seems to have a rick of memory leak. Unfortunately my skills are not enough to read and understand jQuery code itself, but I want to know how jQuery stores such data by using data(). http://api.jquery.com/data/

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  • Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

    Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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  • SQLAuthority News – Fast Track Data Warehouse 3.0 Reference Guide

    - by pinaldave
    http://msdn.microsoft.com/en-us/library/gg605238.aspx I am very excited that Fast Track Data Warehouse 3.0 reference guide has been announced. As a consultant I have always enjoyed working with Fast Track Data Warehouse project as it truly expresses the potential of the SQL Server Engine. Here is few details of the enhancement of the Fast Track Data Warehouse 3.0 reference architecture. The SQL Server Fast Track Data Warehouse initiative provides a basic methodology and concrete examples for the deployment of balanced hardware and database configuration for a data warehousing workload. Balance is measured across the key components of a SQL Server installation; storage, server, application settings, and configuration settings for each component are evaluated. Description Note FTDW 3.0 Architecture Basic component architecture for FT 3.0 based systems. New Memory Guidelines Minimum and maximum tested memory configurations by server socket count. Additional Startup Options Notes for T-834 and setting for Lock Pages in Memory. Storage Configuration RAID1+0 now standard (RAID1 was used in FT 2.0). Evaluating Fragmentation Query provided for evaluating logical fragmentation. Loading Data Additional options for CI table loads. MCR Additional detail and explanation of FTDW MCR Rating. Read white paper on fast track data warehousing. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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  • Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

    Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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  • Is it conceivable to have millions of lists of data in memory in Python?

    - by Codemonkey
    I have over the last 30 days been developing a Python application that utilizes a MySQL database of information (specifically about Norwegian addresses) to perform address validation and correction. The database contains approximately 2.1 million rows (43 columns) of data and occupies 640MB of disk space. I'm thinking about speed optimizations, and I've got to assume that when validating 10,000+ addresses, each validation running up to 20 queries to the database, networking is a speed bottleneck. I haven't done any measuring or timing yet, and I'm sure there are simpler ways of speed optimizing the application at the moment, but I just want to get the experts' opinions on how realistic it is to load this amount of data into a row-of-rows structure in Python. Also, would it even be any faster? Surely MySQL is optimized for looking up records among vast amounts of data, so how much help would it even be to remove the networking step? Can you imagine any other viable methods of removing the networking step? The location of the MySQL server will vary, as the application might well be run from a laptop at home or at the office, where the server would be local.

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  • MATLAB: What is an appropriate Data Structure for a Matrix with Random Variable Entries?

    - by user12707
    I'm working in an area that is related to simulation and trying to design a data structure that can include random variables within matrices. I am currently coding in MATLAB. To motivate this let me say I have the following matrix: [a b; c d] I want to find a data structure that will allow for a, b, c, d to be either real numbers or random variables. As an example, let's say that a = 1, b = -1, c = 2 but let d be a normally distributed random variable with mean 20 and SD 40. The data structure that I have in mind will give no value to d. However, I also want to be able to design a function that can take in the structure, simulate an uniform(0,1), obtain a value for d using an inverse CDF and then spit out an actual matrix. I have several ideas to do this (all related to the MATLAB icdf function) but would like to know how more experienced programmers would do it. In this application, it's important that the structure is as "lean" as possible since I will be working with very very large matrices and memory will be an issue.

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  • extjs data store load data on fly

    - by CKeven
    I'm trying to create a data store that will load the data schema and records on fly. Here is the current code i have and I'm not sure how to setup the array reader properly since i don't have the schema before query returns. ds = new Ext.data.Store({ url: 'http://10.10.97.83/cgi-bin/cgiip.exe/WService=wsdev/majax/jsbrdgx.p', baseParams: { cr: Ext.util.JSON.encode(omgtobxParms) }, reader: new Ext.data.ArrayReader({ //root:data.value.records }, col_names) }); {"name": "tmp_buy_book", "schema": [ { "name": "a", "type": "C"}, { "name": "b", "type": "C"} "records": [["1", ""], ["1",""]]}

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  • What's the right way to do mutable data structures (e.g., skip lists, splay trees) in F#?

    - by dan
    What's a good way to implement mutable data structures in F#? The reason I’m asking is because I want to go back and implement the data structures I learned about in the algorithms class I took this semester (skip lists, splay trees, fusion trees, y-fast tries, van Emde Boas trees, etc.), which was a pure theory course with no coding whatsoever, and I figure I might as well try to learn F# while I’m doing it. I know that I “should” use finger trees to get splay tree functionality in a functional language, and that I should do something with laziness to get skip-list functionality, etc. , but I want to get the basics nailed down before I try playing with purely functional implementations. There are lots of examples of how to do functional data structures in F#, but there isn’t much on how to do mutable data structures, so I started by fixing up the doubly linked list here into something that allows inserts and deletes anywhere. My plan is to turn this into a skip list, and then use a similar structure (discriminated union of a record) for the tree structures I want to implement. Before I start on something more substantial, is there a better way to do mutable structures like this in F#? Should I just use records and not bother with the discriminated union? Should I use a class instead? Is this question "not even wrong"? Should I be doing the mutable structures in C#, and not dip into F# until I want to compare them to their purely functional counterparts? And, if a DU of records is what I want, could I have written the code below better or more idiomatically? It seems like there's a lot of redundancy here, but I'm not sure how to get rid of it. module DoublyLinkedList = type 'a ll = | None | Node of 'a ll_node and 'a ll_node = { mutable Prev: 'a ll; Element : 'a ; mutable Next: 'a ll; } let insert x l = match l with | None -> Node({ Prev=None; Element=x; Next=None }) | Node(node) -> match node.Prev with | None -> let new_node = { Prev=None; Element=x; Next=Node(node)} node.Prev <- Node(new_node) Node(new_node) | Node(prev_node) -> let new_node = { Prev=node.Prev; Element=x; Next=Node(node)} node.Prev <- Node(new_node) prev_node.Next <- Node(new_node) Node(prev_node) let rec nth n l = match n, l with | _,None -> None | _,Node(node) when n > 0 -> nth (n-1) node.Next | _,Node(node) when n < 0 -> nth (n+1) node.Prev | _,Node(node) -> Node(node) //hopefully only when n = 0 :-) let rec printLinkedList head = match head with | None -> () | Node(x) -> let prev = match x.Prev with | None -> "-" | Node(y) -> y.Element.ToString() let cur = x.Element.ToString() let next = match x.Next with | None -> "-" | Node(y) -> y.Element.ToString() printfn "%s, <- %s -> %s" prev cur next printLinkedList x.Next

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  • Big Data – Buzz Words: What is MapReduce – Day 7 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is Hadoop. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – MapReduce. What is MapReduce? MapReduce was designed by Google as a programming model for processing large data sets with a parallel, distributed algorithm on a cluster. Though, MapReduce was originally Google proprietary technology, it has been quite a generalized term in the recent time. MapReduce comprises a Map() and Reduce() procedures. Procedure Map() performance filtering and sorting operation on data where as procedure Reduce() performs a summary operation of the data. This model is based on modified concepts of the map and reduce functions commonly available in functional programing. The library where procedure Map() and Reduce() belongs is written in many different languages. The most popular free implementation of MapReduce is Apache Hadoop which we will explore tomorrow. Advantages of MapReduce Procedures The MapReduce Framework usually contains distributed servers and it runs various tasks in parallel to each other. There are various components which manages the communications between various nodes of the data and provides the high availability and fault tolerance. Programs written in MapReduce functional styles are automatically parallelized and executed on commodity machines. The MapReduce Framework takes care of the details of partitioning the data and executing the processes on distributed server on run time. During this process if there is any disaster the framework provides high availability and other available modes take care of the responsibility of the failed node. As you can clearly see more this entire MapReduce Frameworks provides much more than just Map() and Reduce() procedures; it provides scalability and fault tolerance as well. A typical implementation of the MapReduce Framework processes many petabytes of data and thousands of the processing machines. How do MapReduce Framework Works? A typical MapReduce Framework contains petabytes of the data and thousands of the nodes. Here is the basic explanation of the MapReduce Procedures which uses this massive commodity of the servers. Map() Procedure There is always a master node in this infrastructure which takes an input. Right after taking input master node divides it into smaller sub-inputs or sub-problems. These sub-problems are distributed to worker nodes. A worker node later processes them and does necessary analysis. Once the worker node completes the process with this sub-problem it returns it back to master node. Reduce() Procedure All the worker nodes return the answer to the sub-problem assigned to them to master node. The master node collects the answer and once again aggregate that in the form of the answer to the original big problem which was assigned master node. The MapReduce Framework does the above Map () and Reduce () procedure in the parallel and independent to each other. All the Map() procedures can run parallel to each other and once each worker node had completed their task they can send it back to master code to compile it with a single answer. This particular procedure can be very effective when it is implemented on a very large amount of data (Big Data). The MapReduce Framework has five different steps: Preparing Map() Input Executing User Provided Map() Code Shuffle Map Output to Reduce Processor Executing User Provided Reduce Code Producing the Final Output Here is the Dataflow of MapReduce Framework: Input Reader Map Function Partition Function Compare Function Reduce Function Output Writer In a future blog post of this 31 day series we will explore various components of MapReduce in Detail. MapReduce in a Single Statement MapReduce is equivalent to SELECT and GROUP BY of a relational database for a very large database. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – HDFS. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL Developer Data Modeler v3.3 Early Adopter: Search

    - by thatjeffsmith
    photo: Stuck in Customs via photopin cc The next version of Oracle SQL Developer Data Modeler is now available as an Early Adopter (read, beta) release. There are many new major feature enhancements to talk about, but today’s focus will be on the brand new Search mechanism. Data, data, data – SO MUCH data Google has made countless billions of dollars around a very efficient and intelligent search business. People have become accustomed to having their data accessible AND searchable. Data models can have thousands of entities or tables, each having dozens of attributes or columns. Imagine how hard it could be to find what you’re looking for here. This is the challenge we have tackled head-on in v3.3. Same location as the Search toolbar in Oracle SQL Developer (and most web browsers) Here’s how it works: Search as you type – wicked fast as the entire model is loaded into memory Supports regular expressions (regex) Results loaded to a new panel below Search across designs, models Search EVERYTHING, or filter by type Save your frequent searches Save your search results as a report Open common properties of object in search results and edit basic properties on-the-fly Want to just watch the video? We have a new Oracle Learning Library resource available now which introduces the new and improved Search mechanism in SQL Developer Data Modeler. Go watch the video and then come back. Some Screenshots This will be a pretty easy feature to pick up. Search is intuitive – we’ve already learned how to do search. Now we just have a better interface for it in SQL Developer Data Modeler. But just in case you need a couple of pointers… The SYS data dictionary in model form with Search Results If I type ‘translation’ in the search dialog, then the results will come up as hits are ‘resolved.’ By default, everything is searched, although I can filter the results after-the-fact. You can see where the search finds a match in the ‘Content’ column Save the Results as a Report If you limit the search results to a category and a model, then you can save the results as a report. All of the usual suspects You can optionally include the search string, which displays in the top of of the report as ‘PATTERN.’ You can save you common reporting setups as a template and reuse those as well. Here’s a sample HTML report: Yes, I like to search my search results report! Two More Ways to Search You can search ‘in context’ by opening the ‘Find’ dialog from an active design. You can do this using the ‘Search’ toolbar button or from a model context menu. Searching a specific model Instead of bringing up the old modal Find dialog, you now get to use the new and improved Search panel. Notice there’s no ‘Model’ drop-down to select and that the active Search form is now in the Search panel versus the search toolbar up top. What else is new in SQL Developer Data Modeler version 3.3? All kinds of goodies. You can send your model to Excel for quick edits/reviews and suck the changes back into your model, you can share objects between models, and much much more. You’ll find new videos and blog posts on the subject in the new few days and weeks. Enjoy! If you have any feedback or want to report bugs, please visit our forums.

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  • Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Relational Database and NoSQL database in the Big Data Story. In this article we will understand the role of Key-Value Pair Databases and Document Databases Supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (Yesterday’s post) NoSQL Databases (Yesterday’s post) Key-Value Pair Databases (This post) Document Databases (This post) Columnar Databases (Tomorrow’s post) Graph Databases (Tomorrow’s post) Spatial Databases (Tomorrow’s post) Key Value Pair Databases Key Value Pair Databases are also known as KVP databases. A key is a field name and attribute, an identifier. The content of that field is its value, the data that is being identified and stored. They have a very simple implementation of NoSQL database concepts. They do not have schema hence they are very flexible as well as scalable. The disadvantages of Key Value Pair (KVP) database are that they do not follow ACID (Atomicity, Consistency, Isolation, Durability) properties. Additionally, it will require data architects to plan for data placement, replication as well as high availability. In KVP databases the data is stored as strings. Here is a simple example of how Key Value Database will look like: Key Value Name Pinal Dave Color Blue Twitter @pinaldave Name Nupur Dave Movie The Hero As the number of users grow in Key Value Pair databases it starts getting difficult to manage the entire database. As there is no specific schema or rules associated with the database, there are chances that database grows exponentially as well. It is very crucial to select the right Key Value Pair Database which offers an additional set of tools to manage the data and provides finer control over various business aspects of the same. Riak Rick is one of the most popular Key Value Database. It is known for its scalability and performance in high volume and velocity database. Additionally, it implements a mechanism for collection key and values which further helps to build manageable system. We will further discuss Riak in future blog posts. Key Value Databases are a good choice for social media, communities, caching layers for connecting other databases. In simpler words, whenever we required flexibility of the data storage keeping scalability in mind – KVP databases are good options to consider. Document Database There are two different kinds of document databases. 1) Full document Content (web pages, word docs etc) and 2) Storing Document Components for storage. The second types of the document database we are talking about over here. They use Javascript Object Notation (JSON) and Binary JSON for the structure of the documents. JSON is very easy to understand language and it is very easy to write for applications. There are two major structures of JSON used for Document Database – 1) Name Value Pairs and 2) Ordered List. MongoDB and CouchDB are two of the most popular Open Source NonRelational Document Database. MongoDB MongoDB databases are called collections. Each collection is build of documents and each document is composed of fields. MongoDB collections can be indexed for optimal performance. MongoDB ecosystem is highly available, supports query services as well as MapReduce. It is often used in high volume content management system. CouchDB CouchDB databases are composed of documents which consists fields and attachments (known as description). It supports ACID properties. The main attraction points of CouchDB are that it will continue to operate even though network connectivity is sketchy. Due to this nature CouchDB prefers local data storage. Document Database is a good choice of the database when users have to generate dynamic reports from elements which are changing very frequently. A good example of document usages is in real time analytics in social networking or content management system. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • The data reader returned by the store data provider does not have enough columns

    - by molgan
    Hello I get the following error when I try to execute a stored procedure: "The data reader returned by the store data provider does not have enough columns" When I in the sql-manager execute it like this: DECLARE @return_value int, @EndDate datetime EXEC @return_value = [dbo].[GetSomeDate] @SomeID = 91, @EndDate = @EndDate OUTPUT SELECT @EndDate as N'@EndDate' SELECT 'Return Value' = @return_value GO It returns the value properly.... @SomeDate = '2010-03-24 09:00' And in my app I have: if (_entities.Connection.State == System.Data.ConnectionState.Closed) _entities.Connection.Open(); using (EntityCommand c = new EntityCommand("MyAppEntities.GetSomeDate", (EntityConnection)this._entities.Connection)) { c.CommandType = System.Data.CommandType.StoredProcedure; EntityParameter paramSomeID = new EntityParameter("SomeID", System.Data.DbType.Int32); paramSomeID.Direction = System.Data.ParameterDirection.Input; paramSomeID.Value = someID; c.Parameters.Add(paramSomeID); EntityParameter paramSomeDate = new EntityParameter("SomeDate", System.Data.DbType.DateTime); SomeDate.Direction = System.Data.ParameterDirection.Output; c.Parameters.Add(paramSomeDate); int retval = c.ExecuteNonQuery(); return (DateTime?)c.Parameters["SomeDate"].Value; Why does it complain about columns? I googled on error and someone said something about removing RETURN in sp, but I dont have any RETURN there. last like is like SELECT @SomeDate = D.SomeDate FROM .... /M

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