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  • database design help for game / user levels / progress

    - by sprugman
    Sorry this got long and all prose-y. I'm creating my first truly gamified web app and could use some help thinking about how to structure the data. The Set-up Users need to accomplish tasks in each of several categories before they can move up a level. I've got my Users, Tasks, and Categories tables, and a UserTasks table which joins the three. ("User 3 has added Task 42 in Category 8. Now they've completed it.") That's all fine and working wonderfully. The Challenge I'm not sure of the best way to track the progress in the individual categories toward each level. The "business" rules are: You have to achieve a certain number of points in each category to move up. If you get the number of points needed in Cat 8, but still have other work to do to complete the level, any new Cat 8 points count toward your overall score, but don't "roll over" into the next level. The number of Categories is small (five currently) and unlikely to change often, but by no means absolutely fixed. The number of points needed to level-up will vary per level, probably by a formula, or perhaps a lookup table. So the challenge is to track each user's progress toward the next level in each category. I've thought of a few potential approaches: Possible Solutions Add a column to the users table for each category and reset them all to zero each time a user levels-up. Have a separate UserProgress table with a row for each category for each user and the number of points they have. (Basically a Many-to-Many version of #1.) Add a userLevel column to the UserTasks table and use that to derive their progress with some kind of SUM statement. Their current level will be a simple int in the User table. Pros & Cons (1) seems like by far the most straightforward, but it's also the least flexible. Perhaps I could use a naming convention based on the category ids to help overcome some of that. (With code like "select cats; for each cat, get the value from Users.progress_{cat.id}.") It's also the one where I lose the most data -- I won't know which points counted toward leveling up. I don't have a need in mind for that, so maybe I don't care about that. (2) seems complicated: every time I add or subtract a user or a category, I have to maintain the other table. I foresee synchronization challenges. (3) Is somewhere in between -- cleaner than #2, but less intuitive than #1. In order to find out where a user is, I'd have mildly complex SQL like: SELECT categoryId, SUM(points) from UserTasks WHERE userId={user.id} & countsTowardLevel={user.level} groupBy categoryId Hmm... that doesn't seem so bad. I think I'm talking myself into #3 here, but would love any input, advice or other ideas.

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  • How to map one class against multiple tables with SQLAlchemy?

    - by tote
    Lets say that I have a database structure with three tables that look like this: items - item_id - item_handle attributes - attribute_id - attribute_name item_attributes - item_attribute_id - item_id - attribute_id - attribute_value I would like to be able to do this in SQLAlchemy: item = Item('item1') item.foo = 'bar' session.add(item) session.commit() item1 = session.query(Item).filter_by(handle='item1').one() print item1.foo # => 'bar' I'm new to SQLAlchemy and I found this in the documentation (http://www.sqlalchemy.org/docs/05/mappers.html#mapping-a-class-against-multiple-tables): j = join(items, item_attributes, items.c.item_id == item_attributes.c.item_id). \ join(attributes, item_attributes.c.attribute_id == attributes.c.attribute_id) mapper(Item, j, properties={ 'item_id': [items.c.item_id, item_attributes.c.item_id], 'attribute_id': [item_attributes.c.attribute_id, attributes.c.attribute_id], }) It only adds item_id and attribute_id to Item and its not possible to add attributes to Item object. Is what I'm trying to achieve possible with SQLAlchemy? Is there a better way to structure the database to get the same behaviour of "dynamic columns"?

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  • How to store opening weekdays in a database

    - by JoaoPedro
    I have a group of checkboxes where the user selects some of the weekdays (the opening days of a store). How can I save the selected days? Should I save something like 0111111 (zero means closed on sunday) on the same field and split the result when reading the data? Or create a field for each day and store 0 or 1 on each (weird)?

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  • mysql database design: threads and replies

    - by ajsie
    in my forum i have threads and replies. one thread has multiple replies. but then, a reply can be a reply of an reply (like google wave). because of that a reply has to have a column "reply_id" so it can point to the parent reply. but then, the "top-level" replies (the replies directly under the thread) will have no parent reply. so how can i fix this? how should the columns be in the reply table (and thread table). at the moment it looks like this: threads: id title body replies: id thread_id (all replies will belong to a thread) reply_id (here lies the problem. the top-level replies wont have a parent reply) body what could a smart design look like to enable reply a reply?

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  • How to retrieve items from a database c#

    - by Poppy
    I have 3 tables "pics", "shows", "showpics" I want to be able to edit the table "shows". In order to do this i need to retrive the pictures that the show contains (the pictures are stored in the table "pics") the "showpics" table acts as a link does anyone have any ideas as im completely lost and have no idea where to even start Thanks

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  • What kind of database to use in C#

    - by Chris
    I'm writing a program in C# that will need to store a few Data Tables on the user's computer and load them back when he restarts the program: Up to about 10000 records consisting of text and integers. I don't want to use a CSV file, and I had some trouble with SQLite. Are there any other good options to try?

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  • What kind of database to use in .NET

    - by Chris
    I'm writing a program in C# that will need to store a few Data Tables on the user's computer and load them back when he restarts the program: Up to about 10000 records consisting of text and integers. I don't want to use a CSV file, and I had some trouble with SQLite. Are there any other good options to try?

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  • SQLite - executeUpdate exception not caught when database does not exist? (Java)

    - by giant91
    So I was purposely trying to break my program, and I've succeeded. I deleted the sqlite database the program uses, while the program was running, after I already created the connection. Then I attempted to update the database as seen below. Statement stmt; try { stmt = Foo.con.createStatement(); stmt.executeUpdate("INSERT INTO "+table+" VALUES (\'" + itemToAdd + "\')"); } catch(SQLException e) { System.out.println("Error: " + e.toString()); } The problem is, it didn't catch the exception, and continued to run as if the database was updated successfully. Meanwhile the database didn't even exist at that point since this was after I deleted it. Doesn't it check if the database still exists when updating? Do I have to check the database connection manually, every time I update to ensure that the database wasn't corrupted/deleted? Is this the way it is normally done, or is there a simpler/more robust approach? Thank you.

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  • Is this distributed database server idea feasible?

    - by David
    I often use SQLite for creating simple programs in companies. The database is placed on a file server. This works fine as long as there are not more than about 50 users working towards the database concurrently (though depending on whether it is reads or writes). Once there are more than this, they will notice a slowdown if there are a lot of concurrent writing on the server as lots of time is spent on locks, and there is nothing like a cache as there is no database server. The advantage of not needing a database server is that the time to set up something like a company Wiki or similar can be reduced from several months to just days. It often takes several months because some IT-department needs to order the server and it needs to conform with the company policies and security rules and it needs to be placed on the outsourced server hosting facility, which screws up and places it in the wrong localtion etc. etc. Therefore, I thought of an idea to create a distributed database server. The process would be as follows: A user on a company computer edits something on a Wiki page (which uses this database as its backend), to do this he reads a file on the local harddisk stating the ip-address of the last desktop computer to be a database server. He then tries to contact this computer directly via TCP/IP. If it does not answer, then he will read a file on the file server stating the ip-address of the last desktop computer to be a database server. If this server does not answer either, his own desktop computer will become the database server and register its ip-address in the same file. The SQL update statement can then be executed, and other desktop computers can connect to his directly. The point with this architecture is that, the higher load, the better it will function, as each desktop computer will always know the ip-address of the database server. Also, using this setup, I believe that a database placed on a fileserver could serve hundreds of desktop computers instead of the current 50 or so. I also do not believe that the load on the single desktop computer, which has become database server will ever be noticable, as there will be no hard disk operations on this desktop, only on the file server. Is this idea feasible? Does it already exist? What kind of database could support such an architecture?

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  • What is the typical maximum number of database connections for Oracle running on Windows server ?

    - by Sake
    We are maintaining a database server that serve a large number of clients. Each client typically running serveral client-applications. The total number of connections to the database server (Oracle 9i) is reaching 800 connections on peak load. The windows 2003 server is starting to run out of memory. We are now planning to move to 64bit Windows in order to gain higher memory capability. As a developer I suggest moving to multi-tier architecture with conneciton pooling, which I believe is a natural solution to this problem. However, in order to support my idea, I want the information on: what exactly is the typical number of connections allowed for Oracle database ? What is the problem when the number connections is too high ? Too much memory comsumption ? or too many sockets opened ? or too many context switching between threads ? To be a little bit specific, how could Oracle Forms application scale to thousand of users without facing this problem ? Shall Oracle RAC applied to this case ? I'm sure the answer to this question should depend on quite a number of factors, like the exact spec of the hardware being used. I'm expecting a rough estimation or some experience from the real world.

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  • Using jQuery to Insert a New Database Record

    - by Stephen Walther
    The goal of this blog entry is to explore the easiest way of inserting a new record into a database using jQuery and .NET. I’m going to explore two approaches: using Generic Handlers and using a WCF service (In a future blog entry I’ll take a look at OData and WCF Data Services). Create the ASP.NET Project I’ll start by creating a new empty ASP.NET application with Visual Studio 2010. Select the menu option File, New Project and select the ASP.NET Empty Web Application project template. Setup the Database and Data Model I’ll use my standard MoviesDB.mdf movies database. This database contains one table named Movies that looks like this: I’ll use the ADO.NET Entity Framework to represent my database data: Select the menu option Project, Add New Item and select the ADO.NET Entity Data Model project item. Name the data model MoviesDB.edmx and click the Add button. In the Choose Model Contents step, select Generate from database and click the Next button. In the Choose Your Data Connection step, leave all of the defaults and click the Next button. In the Choose Your Data Objects step, select the Movies table and click the Finish button. Unfortunately, Visual Studio 2010 cannot spell movie correctly :) You need to click on Movy and change the name of the class to Movie. In the Properties window, change the Entity Set Name to Movies. Using a Generic Handler In this section, we’ll use jQuery with an ASP.NET generic handler to insert a new record into the database. A generic handler is similar to an ASP.NET page, but it does not have any of the overhead. It consists of one method named ProcessRequest(). Select the menu option Project, Add New Item and select the Generic Handler project item. Name your new generic handler InsertMovie.ashx and click the Add button. Modify your handler so it looks like Listing 1: Listing 1 – InsertMovie.ashx using System.Web; namespace WebApplication1 { /// <summary> /// Inserts a new movie into the database /// </summary> public class InsertMovie : IHttpHandler { private MoviesDBEntities _dataContext = new MoviesDBEntities(); public void ProcessRequest(HttpContext context) { context.Response.ContentType = "text/plain"; // Extract form fields var title = context.Request["title"]; var director = context.Request["director"]; // Create movie to insert var movieToInsert = new Movie { Title = title, Director = director }; // Save new movie to DB _dataContext.AddToMovies(movieToInsert); _dataContext.SaveChanges(); // Return success context.Response.Write("success"); } public bool IsReusable { get { return true; } } } } In Listing 1, the ProcessRequest() method is used to retrieve a title and director from form parameters. Next, a new Movie is created with the form values. Finally, the new movie is saved to the database and the string “success” is returned. Using jQuery with the Generic Handler We can call the InsertMovie.ashx generic handler from jQuery by using the standard jQuery post() method. The following HTML page illustrates how you can retrieve form field values and post the values to the generic handler: Listing 2 – Default.htm <!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> <title>Add Movie</title> <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> </head> <body> <form> <label>Title:</label> <input name="title" /> <br /> <label>Director:</label> <input name="director" /> </form> <button id="btnAdd">Add Movie</button> <script type="text/javascript"> $("#btnAdd").click(function () { $.post("InsertMovie.ashx", $("form").serialize(), insertCallback); }); function insertCallback(result) { if (result == "success") { alert("Movie added!"); } else { alert("Could not add movie!"); } } </script> </body> </html>     When you open the page in Listing 2 in a web browser, you get a simple HTML form: Notice that the page in Listing 2 includes the jQuery library. The jQuery library is included with the following SCRIPT tag: <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> The jQuery library is included on the Microsoft Ajax CDN so you can always easily include the jQuery library in your applications. You can learn more about the CDN at this website: http://www.asp.net/ajaxLibrary/cdn.ashx When you click the Add Movie button, the jQuery post() method is called to post the form data to the InsertMovie.ashx generic handler. Notice that the form values are serialized into a URL encoded string by calling the jQuery serialize() method. The serialize() method uses the name attribute of form fields and not the id attribute. Notes on this Approach This is a very low-level approach to interacting with .NET through jQuery – but it is simple and it works! And, you don’t need to use any JavaScript libraries in addition to the jQuery library to use this approach. The signature for the jQuery post() callback method looks like this: callback(data, textStatus, XmlHttpRequest) The second parameter, textStatus, returns the HTTP status code from the server. I tried returning different status codes from the generic handler with an eye towards implementing server validation by returning a status code such as 400 Bad Request when validation fails (see http://www.w3.org/Protocols/rfc2616/rfc2616-sec10.html ). I finally figured out that the callback is not invoked when the textStatus has any value other than “success”. Using a WCF Service As an alternative to posting to a generic handler, you can create a WCF service. You create a new WCF service by selecting the menu option Project, Add New Item and selecting the Ajax-enabled WCF Service project item. Name your WCF service InsertMovie.svc and click the Add button. Modify the WCF service so that it looks like Listing 3: Listing 3 – InsertMovie.svc using System.ServiceModel; using System.ServiceModel.Activation; namespace WebApplication1 { [ServiceBehavior(IncludeExceptionDetailInFaults=true)] [ServiceContract(Namespace = "")] [AspNetCompatibilityRequirements(RequirementsMode = AspNetCompatibilityRequirementsMode.Allowed)] public class MovieService { private MoviesDBEntities _dataContext = new MoviesDBEntities(); [OperationContract] public bool Insert(string title, string director) { // Create movie to insert var movieToInsert = new Movie { Title = title, Director = director }; // Save new movie to DB _dataContext.AddToMovies(movieToInsert); _dataContext.SaveChanges(); // Return movie (with primary key) return true; } } }   The WCF service in Listing 3 uses the Entity Framework to insert a record into the Movies database table. The service always returns the value true. Notice that the service in Listing 3 includes the following attribute: [ServiceBehavior(IncludeExceptionDetailInFaults=true)] You need to include this attribute if you want to get detailed error information back to the client. When you are building an application, you should always include this attribute. When you are ready to release your application, you should remove this attribute for security reasons. Using jQuery with the WCF Service Calling a WCF service from jQuery requires a little more work than calling a generic handler from jQuery. Here are some good blog posts on some of the issues with using jQuery with WCF: http://encosia.com/2008/06/05/3-mistakes-to-avoid-when-using-jquery-with-aspnet-ajax/ http://encosia.com/2008/03/27/using-jquery-to-consume-aspnet-json-web-services/ http://weblogs.asp.net/scottgu/archive/2007/04/04/json-hijacking-and-how-asp-net-ajax-1-0-mitigates-these-attacks.aspx http://www.west-wind.com/Weblog/posts/896411.aspx http://www.west-wind.com/weblog/posts/324917.aspx http://professionalaspnet.com/archive/tags/WCF/default.aspx The primary requirement when calling WCF from jQuery is that the request use JSON: The request must include a content-type:application/json header. Any parameters included with the request must be JSON encoded. Unfortunately, jQuery does not include a method for serializing JSON (Although, oddly, jQuery does include a parseJSON() method for deserializing JSON). Therefore, we need to use an additional library to handle the JSON serialization. The page in Listing 4 illustrates how you can call a WCF service from jQuery. Listing 4 – Default2.aspx <!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> <title>Add Movie</title> <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> <script src="Scripts/json2.js" type="text/javascript"></script> </head> <body> <form> <label>Title:</label> <input id="title" /> <br /> <label>Director:</label> <input id="director" /> </form> <button id="btnAdd">Add Movie</button> <script type="text/javascript"> $("#btnAdd").click(function () { // Convert the form into an object var data = { title: $("#title").val(), director: $("#director").val() }; // JSONify the data data = JSON.stringify(data); // Post it $.ajax({ type: "POST", contentType: "application/json; charset=utf-8", url: "MovieService.svc/Insert", data: data, dataType: "json", success: insertCallback }); }); function insertCallback(result) { // unwrap result result = result["d"]; if (result === true) { alert("Movie added!"); } else { alert("Could not add movie!"); } } </script> </body> </html> There are several things to notice about Listing 4. First, notice that the page includes both the jQuery library and Douglas Crockford’s JSON2 library: <script src="Scripts/json2.js" type="text/javascript"></script> You need to include the JSON2 library to serialize the form values into JSON. You can download the JSON2 library from the following location: http://www.json.org/js.html When you click the button to submit the form, the form data is converted into a JavaScript object: // Convert the form into an object var data = { title: $("#title").val(), director: $("#director").val() }; Next, the data is serialized into JSON using the JSON2 library: // JSONify the data var data = JSON.stringify(data); Finally, the form data is posted to the WCF service by calling the jQuery ajax() method: // Post it $.ajax({   type: "POST",   contentType: "application/json; charset=utf-8",   url: "MovieService.svc/Insert",   data: data,   dataType: "json",   success: insertCallback }); You can’t use the standard jQuery post() method because you must set the content-type of the request to be application/json. Otherwise, the WCF service will reject the request for security reasons. For details, see the Scott Guthrie blog post: http://weblogs.asp.net/scottgu/archive/2007/04/04/json-hijacking-and-how-asp-net-ajax-1-0-mitigates-these-attacks.aspx The insertCallback() method is called when the WCF service returns a response. This method looks like this: function insertCallback(result) {   // unwrap result   result = result["d"];   if (result === true) {       alert("Movie added!");   } else {     alert("Could not add movie!");   } } When we called the jQuery ajax() method, we set the dataType to JSON. That causes the jQuery ajax() method to deserialize the response from the WCF service from JSON into a JavaScript object automatically. The following value is passed to the insertCallback method: {"d":true} For security reasons, a WCF service always returns a response with a “d” wrapper. The following line of code removes the “d” wrapper: // unwrap result result = result["d"]; To learn more about the “d” wrapper, I recommend that you read the following blog posts: http://encosia.com/2009/02/10/a-breaking-change-between-versions-of-aspnet-ajax/ http://encosia.com/2009/06/29/never-worry-about-asp-net-ajaxs-d-again/ Summary In this blog entry, I explored two methods of inserting a database record using jQuery and .NET. First, we created a generic handler and called the handler from jQuery. This is a very low-level approach. However, it is a simple approach that works. Next, we looked at how you can call a WCF service using jQuery. This approach required a little more work because you need to serialize objects into JSON. We used the JSON2 library to perform the serialization. In the next blog post, I want to explore how you can use jQuery with OData and WCF Data Services.

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  • SQL SERVER – Database Dynamic Caching by Automatic SQL Server Performance Acceleration

    - by pinaldave
    My second look at SafePeak’s new version (2.1) revealed to me few additional interesting features. For those of you who hadn’t read my previous reviews SafePeak and not familiar with it, here is a quick brief: SafePeak is in business of accelerating performance of SQL Server applications, as well as their scalability, without making code changes to the applications or to the databases. SafePeak performs database dynamic caching, by caching in memory result sets of queries and stored procedures while keeping all those cache correct and up to date. Cached queries are retrieved from the SafePeak RAM in microsecond speed and not send to the SQL Server. The application gets much faster results (100-500 micro seconds), the load on the SQL Server is reduced (less CPU and IO) and the application or the infrastructure gets better scalability. SafePeak solution is hosted either within your cloud servers, hosted servers or your enterprise servers, as part of the application architecture. Connection of the application is done via change of connection strings or adding reroute line in the c:\windows\system32\drivers\etc\hosts file on all application servers. For those who would like to learn more on SafePeak architecture and how it works, I suggest to read this vendor’s webpage: SafePeak Architecture. More interesting new features in SafePeak 2.1 In my previous review of SafePeak new I covered the first 4 things I noticed in the new SafePeak (check out my article “SQLAuthority News – SafePeak Releases a Major Update: SafePeak version 2.1 for SQL Server Performance Acceleration”): Cache setup and fine-tuning – a critical part for getting good caching results Database templates Choosing which database to cache Monitoring and analysis options by SafePeak Since then I had a chance to play with SafePeak some more and here is what I found. 5. Analysis of SQL Performance (present and history): In SafePeak v.2.1 the tools for understanding of performance became more comprehensive. Every 15 minutes SafePeak creates and updates various performance statistics. Each query (or a procedure execute) that arrives to SafePeak gets a SQL pattern, and after it is used again there are statistics for such pattern. An important part of this product is that it understands the dependencies of every pattern (list of tables, views, user defined functions and procs). From this understanding SafePeak creates important analysis information on performance of every object: response time from the database, response time from SafePeak cache, average response time, percent of traffic and break down of behavior. One of the interesting things this behavior column shows is how often the object is actually pdated. The break down analysis allows knowing the above information for: queries and procedures, tables, views, databases and even instances level. The data is show now on all arriving queries, both read queries (that can be cached), but also any types of updates like DMLs, DDLs, DCLs, and even session settings queries. The stats are being updated every 15 minutes and SafePeak dashboard allows going back in time and investigating what happened within any time frame. 6. Logon trigger, for making sure nothing corrupts SafePeak cache data If you have an application with many parts, many servers many possible locations that can actually update the database, or the SQL Server is accessible to many DBAs or software engineers, each can access some database directly and do some changes without going thru SafePeak – this can create a potential corruption of the data stored in SafePeak cache. To make sure SafePeak cache is correct it needs to get all updates to arrive to SafePeak, and if a DBA will access the database directly and do some changes, for example, then SafePeak will simply not know about it and will not clean SafePeak cache. In the new version, SafePeak brought a new feature called “Logon Trigger” to solve the above challenge. By special click of a button SafePeak can deploy a special server logon trigger (with a CLR object) on your SQL Server that actually monitors all connections and informs SafePeak on any connection that is coming not from SafePeak. In SafePeak dashboard there is an interface that allows to control which logins can be ignored based on login names and IPs, while the rest will invoke cache cleanup of SafePeak and actually locks SafePeak cache until this connection will not be closed. Important to note, that this does not interrupt any logins, only informs SafePeak on such connection. On the Dashboard screen in SafePeak you will be able to see those connections and then decide what to do with them. Configuration of this feature in SafePeak dashboard can be done here: Settings -> SQL instances management -> click on instance -> Logon Trigger tab. Other features: 7. User management ability to grant permissions to someone without changing its configuration and only use SafePeak as performance analysis tool. 8. Better reports for analysis of performance using 15 minute resolution charts. 9. Caching of client cursors 10. Support for IPv6 Summary SafePeak is a great SQL Server performance acceleration solution for users who want immediate results for sites with performance, scalability and peak spikes challenges. Especially if your apps are packaged or 3rd party, since no code changes are done. SafePeak can significantly increase response times, by reducing network roundtrip to the database, decreasing CPU resource usage, eliminating I/O and storage access. SafePeak team provides a free fully functional trial www.safepeak.com/download and actually provides a one-on-one assistance during such trial. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, Pinal Dave, PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology

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  • Survey: Which new database platforms are you adopting?

    Database technologies are always improving, which database platforms will you be using tomorrow? Red Gate wants to stay ahead to make sure you have the tools you need to do awesome work. Help us by completing this short survey. Compare and Sync database schemasWhether creating new databases or updating older ones, SQL Compare means no object gets left behind. It’s the gold standard, and you can try it free.

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  • Database platform migration from Windows-32bit to Linux-64bit

    - by [email protected]
    We have a customer which have all they core business database on RAC over Windows OS. Last year they were affected by a virus that destroyed the registry and all their RAC environments were "OUT OF ORDER", the result, thousand people on vacation for a day.They were distrustful about Linux and after came an agreement to migrate their Enterprise Manager from Windows to Linux (OMS and Repository). How we did demonstrate how powerful and easy is RMAN to migrate databases across platforms.Fist of check of target platform is available from sourceSQL> select platform_name from v$db_transportable_platform;PLATFORM_NAME-----------------------------------------------------------Microsoft Windows IA (32-bit)Linux IA (32-bit)HP Tru64 UNIXLinux IA (64-bit)HP Open VMSMicrosoft Windows IA (64-bit)Linux 64-bit for AMDMicrosoft Windows 64-bit for AMDSolaris Operating System (x86)Check database object as directories that can change across platforms, also check external tables.Startup source database in read only modeRun the following RMAN ScriptRMAN> connect target / RMAN> convert database on target platform convert script 'c:/temp/convert_grid.rman'transport script 'c:/TEMP/transporta_grid.sql' new database 'gridbd' format 'c:/temp/gridmydb%U' db_file_name_convert 'C:\oracle\oradata\grid','/oracle/gridbd/data2/data';(Notice tha path change on db_file_name_convert)Move from source to target:PfileNew scriptsexternal table filesbfilesdata filesCheck pfile, and ensure that the paths are OKCreate temporary control file to connect rmanExecute the RMAN scriptRMAN> connect target / RMAN> @/home/oracle/pboixeda/win2lnx.rmanShutdown the instance and remove temporary control filesRecreate controlfile/s, take care about the used paths.Execute the transport script, transporta_grid.sqlDue we were moving from a 32-bit architecture to a 64-bit architecture, there is bug reported in 386990.1 note, we had to recreate OLAP , check the note for more details. Alter or Recreate all necessary objects Launch utlrpAfter this experience with Linux they are on the way to migrate all their RAC from 10gR2 on Windows to 11gR2 Linux 64 bit.Hope it helps

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  • Force.com presents Database.com SQL Azure/Amazon RDS unfazed

    - by Sarang
    At the DreamForce 2010 event in San Francisco Force.com unveiled their next big thing in the Fat SaaS portfolio "Database.com".  I am still wondering how would they would've shelled out for that domain name. Now why would a already established SaaS player foray into a key building block like Database? Potentially allowing enterprises to build apps that do not utilize the Force.com stack! One key reason is being seen as the Fat SaaS player with evey trick in the SaaS space under his belt. You want CRM come hither, want a custom development PaaS like solution welcome home (VMForce), want all your apps to talk to a cloud DB and minimize latency by having it reside closer to you cloud apps? You've come to the right place sire! Other is potentially killing foray of smaller DB players like Oracle (Not surprisingly, the Database.com offering is a highly customized and scalable Oracle database) from entering the lucrative SaaS db marketplace. The feature set promised looks great out of the box for someone who likes to visualize cool new architectures. The ground realities are certainly going to be a lot different considering the SOAP/REST style access patterns in lieu of the comfortable old shoe of SQL. Microsoft suffered heavily with SDS (SQL Data Services) offering in early 2009 and had to pull the plug on the product only to reintroduce as a simple SQL Server in the cloud, SQL Windows Azure. Though MSFT is playing cool by providing OData semantics to work with SQL Windows Azure satisfying atleast some needs of the Web-Style to a DB. The other features like Social data models including Profiles, Status updates, feeds seem interesting as well. (Although I beleive social is just one of the aspects of large scale collaborative computing). All these features start "Free" for devs its a good news but the good news stops here. The overall pricing model of $ per Users per Transactions / Month is highly disproportionate compared to Amazon RDS (Based on MySQL) or SQL Windows Azure (Based on MSSQL). Roger Jennigs of Oakleaf did an interesting comparo based on 3, 10, 100, 500 users and it turns out that Database.com going by current understanding is way too expensive for the services on offer. The offering may not impact the decision for DotNet shops mulling their cloud stategy or even some Java/MySQL shops thinking about Amazon RDS, however for enterprises having already invested in other force.com offerings this could be a very important piece in the cloud strategy jigsaw. One which would address a key cloud DB issue of "Latency" for them at least it will help having the DB in the neighborhood. The tooling and "SQL like" access provider drivers (Think ODBC/JDBC) will be available later this year. Progress Software has already announced their JDBC driver stack for Database.com. It remains to be seen how effective the overall solutions proves to be in the longer run but for starts its a important decision towards consolidating Force.com's already strong positioning in the SaaS space. As always contrasting views are welcome! :)

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  • How to find and fix performance problems in ORM powered applications

    - by FransBouma
    Once in a while we get requests about how to fix performance problems with our framework. As it comes down to following the same steps and looking into the same things every single time, I decided to write a blogpost about it instead, so more people can learn from this and solve performance problems in their O/R mapper powered applications. In some parts it's focused on LLBLGen Pro but it's also usable for other O/R mapping frameworks, as the vast majority of performance problems in O/R mapper powered applications are not specific for a certain O/R mapper framework. Too often, the developer looks at the wrong part of the application, trying to fix what isn't a problem in that part, and getting frustrated that 'things are so slow with <insert your favorite framework X here>'. I'm in the O/R mapper business for a long time now (almost 10 years, full time) and as it's a small world, we O/R mapper developers know almost all tricks to pull off by now: we all know what to do to make task ABC faster and what compromises (because there are almost always compromises) to deal with if we decide to make ABC faster that way. Some O/R mapper frameworks are faster in X, others in Y, but you can be sure the difference is mainly a result of a compromise some developers are willing to deal with and others aren't. That's why the O/R mapper frameworks on the market today are different in many ways, even though they all fetch and save entities from and to a database. I'm not suggesting there's no room for improvement in today's O/R mapper frameworks, there always is, but it's not a matter of 'the slowness of the application is caused by the O/R mapper' anymore. Perhaps query generation can be optimized a bit here, row materialization can be optimized a bit there, but it's mainly coming down to milliseconds. Still worth it if you're a framework developer, but it's not much compared to the time spend inside databases and in user code: if a complete fetch takes 40ms or 50ms (from call to entity object collection), it won't make a difference for your application as that 10ms difference won't be noticed. That's why it's very important to find the real locations of the problems so developers can fix them properly and don't get frustrated because their quest to get a fast, performing application failed. Performance tuning basics and rules Finding and fixing performance problems in any application is a strict procedure with four prescribed steps: isolate, analyze, interpret and fix, in that order. It's key that you don't skip a step nor make assumptions: these steps help you find the reason of a problem which seems to be there, and how to fix it or leave it as-is. Skipping a step, or when you assume things will be bad/slow without doing analysis will lead to the path of premature optimization and won't actually solve your problems, only create new ones. The most important rule of finding and fixing performance problems in software is that you have to understand what 'performance problem' actually means. Most developers will say "when a piece of software / code is slow, you have a performance problem". But is that actually the case? If I write a Linq query which will aggregate, group and sort 5 million rows from several tables to produce a resultset of 10 rows, it might take more than a couple of milliseconds before that resultset is ready to be consumed by other logic. If I solely look at the Linq query, the code consuming the resultset of the 10 rows and then look at the time it takes to complete the whole procedure, it will appear to me to be slow: all that time taken to produce and consume 10 rows? But if you look closer, if you analyze and interpret the situation, you'll see it does a tremendous amount of work, and in that light it might even be extremely fast. With every performance problem you encounter, always do realize that what you're trying to solve is perhaps not a technical problem at all, but a perception problem. The second most important rule you have to understand is based on the old saying "Penny wise, Pound Foolish": the part which takes e.g. 5% of the total time T for a given task isn't worth optimizing if you have another part which takes a much larger part of the total time T for that same given task. Optimizing parts which are relatively insignificant for the total time taken is not going to bring you better results overall, even if you totally optimize that part away. This is the core reason why analysis of the complete set of application parts which participate in a given task is key to being successful in solving performance problems: No analysis -> no problem -> no solution. One warning up front: hunting for performance will always include making compromises. Fast software can be made maintainable, but if you want to squeeze as much performance out of your software, you will inevitably be faced with the dilemma of compromising one or more from the group {readability, maintainability, features} for the extra performance you think you'll gain. It's then up to you to decide whether it's worth it. In almost all cases it's not. The reason for this is simple: the vast majority of performance problems can be solved by implementing the proper algorithms, the ones with proven Big O-characteristics so you know the performance you'll get plus you know the algorithm will work. The time taken by the algorithm implementing code is inevitable: you already implemented the best algorithm. You might find some optimizations on the technical level but in general these are minor. Let's look at the four steps to see how they guide us through the quest to find and fix performance problems. Isolate The first thing you need to do is to isolate the areas in your application which are assumed to be slow. For example, if your application is a web application and a given page is taking several seconds or even minutes to load, it's a good candidate to check out. It's important to start with the isolate step because it allows you to focus on a single code path per area with a clear begin and end and ignore the rest. The rest of the steps are taken per identified problematic area. Keep in mind that isolation focuses on tasks in an application, not code snippets. A task is something that's started in your application by either another task or the user, or another program, and has a beginning and an end. You can see a task as a piece of functionality offered by your application.  Analyze Once you've determined the problem areas, you have to perform analysis on the code paths of each area, to see where the performance problems occur and which areas are not the problem. This is a multi-layered effort: an application which uses an O/R mapper typically consists of multiple parts: there's likely some kind of interface (web, webservice, windows etc.), a part which controls the interface and business logic, the O/R mapper part and the RDBMS, all connected with either a network or inter-process connections provided by the OS or other means. Each of these parts, including the connectivity plumbing, eat up a part of the total time it takes to complete a task, e.g. load a webpage with all orders of a given customer X. To understand which parts participate in the task / area we're investigating and how much they contribute to the total time taken to complete the task, analysis of each participating task is essential. Start with the code you wrote which starts the task, analyze the code and track the path it follows through your application. What does the code do along the way, verify whether it's correct or not. Analyze whether you have implemented the right algorithms in your code for this particular area. Remember we're looking at one area at a time, which means we're ignoring all other code paths, just the code path of the current problematic area, from begin to end and back. Don't dig in and start optimizing at the code level just yet. We're just analyzing. If your analysis reveals big architectural stupidity, it's perhaps a good idea to rethink the architecture at this point. For the rest, we're analyzing which means we collect data about what could be wrong, for each participating part of the complete application. Reviewing the code you wrote is a good tool to get deeper understanding of what is going on for a given task but ultimately it lacks precision and overview what really happens: humans aren't good code interpreters, computers are. We therefore need to utilize tools to get deeper understanding about which parts contribute how much time to the total task, triggered by which other parts and for example how many times are they called. There are two different kind of tools which are necessary: .NET profilers and O/R mapper / RDBMS profilers. .NET profiling .NET profilers (e.g. dotTrace by JetBrains or Ants by Red Gate software) show exactly which pieces of code are called, how many times they're called, and the time it took to run that piece of code, at the method level and sometimes even at the line level. The .NET profilers are essential tools for understanding whether the time taken to complete a given task / area in your application is consumed by .NET code, where exactly in your code, the path to that code, how many times that code was called by other code and thus reveals where hotspots are located: the areas where a solution can be found. Importantly, they also reveal which areas can be left alone: remember our penny wise pound foolish saying: if a profiler reveals that a group of methods are fast, or don't contribute much to the total time taken for a given task, ignore them. Even if the code in them is perhaps complex and looks like a candidate for optimization: you can work all day on that, it won't matter.  As we're focusing on a single area of the application, it's best to start profiling right before you actually activate the task/area. Most .NET profilers support this by starting the application without starting the profiling procedure just yet. You navigate to the particular part which is slow, start profiling in the profiler, in your application you perform the actions which are considered slow, and afterwards you get a snapshot in the profiler. The snapshot contains the data collected by the profiler during the slow action, so most data is produced by code in the area to investigate. This is important, because it allows you to stay focused on a single area. O/R mapper and RDBMS profiling .NET profilers give you a good insight in the .NET side of things, but not in the RDBMS side of the application. As this article is about O/R mapper powered applications, we're also looking at databases, and the software making it possible to consume the database in your application: the O/R mapper. To understand which parts of the O/R mapper and database participate how much to the total time taken for task T, we need different tools. There are two kind of tools focusing on O/R mappers and database performance profiling: O/R mapper profilers and RDBMS profilers. For O/R mapper profilers, you can look at LLBLGen Prof by hibernating rhinos or the Linq to Sql/LLBLGen Pro profiler by Huagati. Hibernating rhinos also have profilers for other O/R mappers like NHibernate (NHProf) and Entity Framework (EFProf) and work the same as LLBLGen Prof. For RDBMS profilers, you have to look whether the RDBMS vendor has a profiler. For example for SQL Server, the profiler is shipped with SQL Server, for Oracle it's build into the RDBMS, however there are also 3rd party tools. Which tool you're using isn't really important, what's important is that you get insight in which queries are executed during the task / area we're currently focused on and how long they took. Here, the O/R mapper profilers have an advantage as they collect the time it took to execute the query from the application's perspective so they also collect the time it took to transport data across the network. This is important because a query which returns a massive resultset or a resultset with large blob/clob/ntext/image fields takes more time to get transported across the network than a small resultset and a database profiler doesn't take this into account most of the time. Another tool to use in this case, which is more low level and not all O/R mappers support it (though LLBLGen Pro and NHibernate as well do) is tracing: most O/R mappers offer some form of tracing or logging system which you can use to collect the SQL generated and executed and often also other activity behind the scenes. While tracing can produce a tremendous amount of data in some cases, it also gives insight in what's going on. Interpret After we've completed the analysis step it's time to look at the data we've collected. We've done code reviews to see whether we've done anything stupid and which parts actually take place and if the proper algorithms have been implemented. We've done .NET profiling to see which parts are choke points and how much time they contribute to the total time taken to complete the task we're investigating. We've performed O/R mapper profiling and RDBMS profiling to see which queries were executed during the task, how many queries were generated and executed and how long they took to complete, including network transportation. All this data reveals two things: which parts are big contributors to the total time taken and which parts are irrelevant. Both aspects are very important. The parts which are irrelevant (i.e. don't contribute significantly to the total time taken) can be ignored from now on, we won't look at them. The parts which contribute a lot to the total time taken are important to look at. We now have to first look at the .NET profiler results, to see whether the time taken is consumed in our own code, in .NET framework code, in the O/R mapper itself or somewhere else. For example if most of the time is consumed by DbCommand.ExecuteReader, the time it took to complete the task is depending on the time the data is fetched from the database. If there was just 1 query executed, according to tracing or O/R mapper profilers / RDBMS profilers, check whether that query is optimal, uses indexes or has to deal with a lot of data. Interpret means that you follow the path from begin to end through the data collected and determine where, along the path, the most time is contributed. It also means that you have to check whether this was expected or is totally unexpected. My previous example of the 10 row resultset of a query which groups millions of rows will likely reveal that a long time is spend inside the database and almost no time is spend in the .NET code, meaning the RDBMS part contributes the most to the total time taken, the rest is compared to that time, irrelevant. Considering the vastness of the source data set, it's expected this will take some time. However, does it need tweaking? Perhaps all possible tweaks are already in place. In the interpret step you then have to decide that further action in this area is necessary or not, based on what the analysis results show: if the analysis results were unexpected and in the area where the most time is contributed to the total time taken is room for improvement, action should be taken. If not, you can only accept the situation and move on. In all cases, document your decision together with the analysis you've done. If you decide that the perceived performance problem is actually expected due to the nature of the task performed, it's essential that in the future when someone else looks at the application and starts asking questions you can answer them properly and new analysis is only necessary if situations changed. Fix After interpreting the analysis results you've concluded that some areas need adjustment. This is the fix step: you're actively correcting the performance problem with proper action targeted at the real cause. In many cases related to O/R mapper powered applications it means you'll use different features of the O/R mapper to achieve the same goal, or apply optimizations at the RDBMS level. It could also mean you apply caching inside your application (compromise memory consumption over performance) to avoid unnecessary re-querying data and re-consuming the results. After applying a change, it's key you re-do the analysis and interpretation steps: compare the results and expectations with what you had before, to see whether your actions had any effect or whether it moved the problem to a different part of the application. Don't fall into the trap to do partly analysis: do the full analysis again: .NET profiling and O/R mapper / RDBMS profiling. It might very well be that the changes you've made make one part faster but another part significantly slower, in such a way that the overall problem hasn't changed at all. Performance tuning is dealing with compromises and making choices: to use one feature over the other, to accept a higher memory footprint, to go away from the strict-OO path and execute queries directly onto the RDBMS, these are choices and compromises which will cross your path if you want to fix performance problems with respect to O/R mappers or data-access and databases in general. In most cases it's not a big issue: alternatives are often good choices too and the compromises aren't that hard to deal with. What is important is that you document why you made a choice, a compromise: which analysis data, which interpretation led you to the choice made. This is key for good maintainability in the years to come. Most common performance problems with O/R mappers Below is an incomplete list of common performance problems related to data-access / O/R mappers / RDBMS code. It will help you with fixing the hotspots you found in the interpretation step. SELECT N+1: (Lazy-loading specific). Lazy loading triggered performance bottlenecks. Consider a list of Orders bound to a grid. You have a Field mapped onto a related field in Order, Customer.CompanyName. Showing this column in the grid will make the grid fetch (indirectly) for each row the Customer row. This means you'll get for the single list not 1 query (for the orders) but 1+(the number of orders shown) queries. To solve this: use eager loading using a prefetch path to fetch the customers with the orders. SELECT N+1 is easy to spot with an O/R mapper profiler or RDBMS profiler: if you see a lot of identical queries executed at once, you have this problem. Prefetch paths using many path nodes or sorting, or limiting. Eager loading problem. Prefetch paths can help with performance, but as 1 query is fetched per node, it can be the number of data fetched in a child node is bigger than you think. Also consider that data in every node is merged on the client within the parent. This is fast, but it also can take some time if you fetch massive amounts of entities. If you keep fetches small, you can use tuning parameters like the ParameterizedPrefetchPathThreshold setting to get more optimal queries. Deep inheritance hierarchies of type Target Per Entity/Type. If you use inheritance of type Target per Entity / Type (each type in the inheritance hierarchy is mapped onto its own table/view), fetches will join subtype- and supertype tables in many cases, which can lead to a lot of performance problems if the hierarchy has many types. With this problem, keep inheritance to a minimum if possible, or switch to a hierarchy of type Target Per Hierarchy, which means all entities in the inheritance hierarchy are mapped onto the same table/view. Of course this has its own set of drawbacks, but it's a compromise you might want to take. Fetching massive amounts of data by fetching large lists of entities. LLBLGen Pro supports paging (and limiting the # of rows returned), which is often key to process through large sets of data. Use paging on the RDBMS if possible (so a query is executed which returns only the rows in the page requested). When using paging in a web application, be sure that you switch server-side paging on on the datasourcecontrol used. In this case, paging on the grid alone is not enough: this can lead to fetching a lot of data which is then loaded into the grid and paged there. Keep note that analyzing queries for paging could lead to the false assumption that paging doesn't occur, e.g. when the query contains a field of type ntext/image/clob/blob and DISTINCT can't be applied while it should have (e.g. due to a join): the datareader will do DISTINCT filtering on the client. this is a little slower but it does perform paging functionality on the data-reader so it won't fetch all rows even if the query suggests it does. Fetch massive amounts of data because blob/clob/ntext/image fields aren't excluded. LLBLGen Pro supports field exclusion for queries. You can exclude fields (also in prefetch paths) per query to avoid fetching all fields of an entity, e.g. when you don't need them for the logic consuming the resultset. Excluding fields can greatly reduce the amount of time spend on data-transport across the network. Use this optimization if you see that there's a big difference between query execution time on the RDBMS and the time reported by the .NET profiler for the ExecuteReader method call. Doing client-side aggregates/scalar calculations by consuming a lot of data. If possible, try to formulate a scalar query or group by query using the projection system or GetScalar functionality of LLBLGen Pro to do data consumption on the RDBMS server. It's far more efficient to process data on the RDBMS server than to first load it all in memory, then traverse the data in-memory to calculate a value. Using .ToList() constructs inside linq queries. It might be you use .ToList() somewhere in a Linq query which makes the query be run partially in-memory. Example: var q = from c in metaData.Customers.ToList() where c.Country=="Norway" select c; This will actually fetch all customers in-memory and do an in-memory filtering, as the linq query is defined on an IEnumerable<T>, and not on the IQueryable<T>. Linq is nice, but it can often be a bit unclear where some parts of a Linq query might run. Fetching all entities to delete into memory first. To delete a set of entities it's rather inefficient to first fetch them all into memory and then delete them one by one. It's more efficient to execute a DELETE FROM ... WHERE query on the database directly to delete the entities in one go. LLBLGen Pro supports this feature, and so do some other O/R mappers. It's not always possible to do this operation in the context of an O/R mapper however: if an O/R mapper relies on a cache, these kind of operations are likely not supported because they make it impossible to track whether an entity is actually removed from the DB and thus can be removed from the cache. Fetching all entities to update with an expression into memory first. Similar to the previous point: it is more efficient to update a set of entities directly with a single UPDATE query using an expression instead of fetching the entities into memory first and then updating the entities in a loop, and afterwards saving them. It might however be a compromise you don't want to take as it is working around the idea of having an object graph in memory which is manipulated and instead makes the code fully aware there's a RDBMS somewhere. Conclusion Performance tuning is almost always about compromises and making choices. It's also about knowing where to look and how the systems in play behave and should behave. The four steps I provided should help you stay focused on the real problem and lead you towards the solution. Knowing how to optimally use the systems participating in your own code (.NET framework, O/R mapper, RDBMS, network/services) is key for success as well as knowing what's going on inside the application you built. I hope you'll find this guide useful in tracking down performance problems and dealing with them in a useful way.  

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  • Spin-off of "Project: Memory++" in Khan academy [on hold]

    - by smraj
    This is the link of the program that I am trying https://www.khanacademy.org/cs/memory-tile-game/5966959895642112 When I am placing the mouse over the block it should change to red colour and when it is released the image should be displayed but my issue is that when i place the mouse over the block it changes its color ,but on release the image is not displayed.I kindly request someone in solving this

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  • Slab uses 88Gb of 128Gb available. What could cause this?

    - by Joris Meys
    We run a debian 2.6.26-2-amd64 x86_64 GNU/Linux on a server with 128 Gb. Recently it our available memory became rather low. Looking at the /proc/meminfo showed that the Slab was using 88Gb, which is counted in the used memory off course. Is this a problem? I suspect that memory will be freed when necessary, but I don't know if that could have unwanted side effects. Why would Slab need that much memory? Is there a clear cause for that? can we avoid this to happen in the future? How can we free this memory? thank you in advance > cat /proc/meminfo MemTotal: 132304500 kB MemFree: 26669388 kB Buffers: 237504 kB Cached: 11881136 kB SwapCached: 48 kB Active: 5244640 kB Inactive: 11714308 kB SwapTotal: 5751228 kB SwapFree: 5750436 kB Dirty: 24 kB Writeback: 0 kB AnonPages: 4840256 kB Mapped: 163968 kB Slab: 88314840 kB SReclaimable: 88275644 kB SUnreclaim: 39196 kB PageTables: 80852 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 71903476 kB Committed_AS: 6818332 kB VmallocTotal: 34359738367 kB VmallocUsed: 505724 kB VmallocChunk: 34359231963 kB

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  • 12/12 Live Webcast: Introducing Next-Generation Enterprise Auditing and Database Firewall

    - by jgelhaus
    Join Oracle Security gurus to hear how Oracle products monitor Oracle and non-Oracle database traffic, detect unauthorized activity including SQL injection attacks, and block internal and external threats from reaching the database. Hear how organizations such as TransUnion Interactive and SquareTwo Financial rely on Oracle to monitor and secure their Oracle and non-Oracle database environments. Register for the webcast here.

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  • Monitoring Database disk space

    - by Michael Freidgeim
    An article Data files: To Autogrow Or Not To Autogrow? recommends NOT to rely on auto-grow, because it causing delays in unplanned times.We should mtonitor database files(both data and log), and if they close to max capacity, manually increase the size. However it doesn't give references, how to monitor the free space inside databases. I've tried to look how to do it. It can be done manually using   execute sp_spaceused for the database in question or  sp_SOS (can be downloaded from http://searchsqlserver.techtarget.com/tip/Find-size-of-SQL-Server-tables-and-other-objects-with-stored-procedure)Alternatively you can run SQL commands as suggested in Http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=82359 by Michael Valentine Jonesselect [FREE_SPACE_MB] = convert(decimal(12,2),round((a.size-fileproperty(a.name,'SpaceUsed'))/128.000,2)) from dbo.sysfiles aMore useful article Monitor database file sizes with SQL Server Jobs describes how to setup monitoring Finally I found the excellent articleManaging Database Data Usage With Custom Space Alerts, that can be followed even support personnel without much DBA experience.

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  • SQL SERVER – Core Concepts – Elasticity, Scalability and ACID Properties – Exploring NuoDB an Elastically Scalable Database System

    - by pinaldave
    I have been recently exploring Elasticity and Scalability attributes of databases. You can see that in my earlier blog posts about NuoDB where I wanted to look at Elasticity and Scalability concepts. The concepts are very interesting, and intriguing as well. I have discussed these concepts with my friend Joyti M and together we have come up with this interesting read. The goal of this article is to answer following simple questions What is Elasticity? What is Scalability? How ACID properties vary from NOSQL Concepts? What are the prevailing problems in the current database system architectures? Why is NuoDB  an innovative and welcome change in database paradigm? Elasticity This word’s original form is used in many different ways and honestly it does do a decent job in holding things together over the years as a person grows and contracts. Within the tech world, and specifically related to software systems (database, application servers), it has come to mean a few things - allow stretching of resources without reaching the breaking point (on demand). What are resources in this context? Resources are the usual suspects – RAM/CPU/IO/Bandwidth in the form of a container (a process or bunch of processes combined as modules). When it is about increasing resources the simplest idea which comes to mind is the addition of another container. Another container means adding a brand new physical node. When it is about adding a new node there are two questions which comes to mind. 1) Can we add another node to our software system? 2) If yes, does adding new node cause downtime for the system? Let us assume we have added new node, let us see what the new needs of the system are when a new node is added. Balancing incoming requests to multiple nodes Synchronization of a shared state across multiple nodes Identification of “downstate” and resolution action to bring it to “upstate” Well, adding a new node has its advantages as well. Here are few of the positive points Throughput can increase nearly horizontally across the node throughout the system Response times of application will increase as in-between layer interactions will be improved Now, Let us put the above concepts in the perspective of a Database. When we mention the term “running out of resources” or “application is bound to resources” the resources can be CPU, Memory or Bandwidth. The regular approach to “gain scalability” in the database is to look around for bottlenecks and increase the bottlenecked resource. When we have memory as a bottleneck we look at the data buffers, locks, query plans or indexes. After a point even this is not enough as there needs to be an efficient way of managing such large workload on a “single machine” across memory and CPU bound (right kind of scheduling)  workload. We next move on to either read/write separation of the workload or functionality-based sharing so that we still have control of the individual. But this requires lots of planning and change in client systems in terms of knowing where to go/update/read and for reporting applications to “aggregate the data” in an intelligent way. What we ideally need is an intelligent layer which allows us to do these things without us getting into managing, monitoring and distributing the workload. Scalability In the context of database/applications, scalability means three main things Ability to handle normal loads without pressure E.g. X users at the Y utilization of resources (CPU, Memory, Bandwidth) on the Z kind of hardware (4 processor, 32 GB machine with 15000 RPM SATA drives and 1 GHz Network switch) with T throughput Ability to scale up to expected peak load which is greater than normal load with acceptable response times Ability to provide acceptable response times across the system E.g. Response time in S milliseconds (or agreed upon unit of measure) – 90% of the time The Issue – Need of Scale In normal cases one can plan for the load testing to test out normal, peak, and stress scenarios to ensure specific hardware meets the needs. With help from Hardware and Software partners and best practices, bottlenecks can be identified and requisite resources added to the system. Unfortunately this vertical scale is expensive and difficult to achieve and most of the operational people need the ability to scale horizontally. This helps in getting better throughput as there are physical limits in terms of adding resources (Memory, CPU, Bandwidth and Storage) indefinitely. Today we have different options to achieve scalability: Read & Write Separation The idea here is to do actual writes to one store and configure slaves receiving the latest data with acceptable delays. Slaves can be used for balancing out reads. We can also explore functional separation or sharing as well. We can separate data operations by a specific identifier (e.g. region, year, month) and consolidate it for reporting purposes. For functional separation the major disadvantage is when schema changes or workload pattern changes. As the requirement grows one still needs to deal with scale need in manual ways by providing an abstraction in the middle tier code. Using NOSQL solutions The idea is to flatten out the structures in general to keep all values which are retrieved together at the same store and provide flexible schema. The issue with the stores is that they are compromising on mostly consistency (no ACID guarantees) and one has to use NON-SQL dialect to work with the store. The other major issue is about education with NOSQL solutions. Would one really want to make these compromises on the ability to connect and retrieve in simple SQL manner and learn other skill sets? Or for that matter give up on ACID guarantee and start dealing with consistency issues? Hybrid Deployment – Mac, Linux, Cloud, and Windows One of the challenges today that we see across On-premise vs Cloud infrastructure is a difference in abilities. Take for example SQL Azure – it is wonderful in its concepts of throttling (as it is shared deployment) of resources and ability to scale using federation. However, the same abilities are not available on premise. This is not a mistake, mind you – but a compromise of the sweet spot of workloads, customer requirements and operational SLAs which can be supported by the team. In today’s world it is imperative that databases are available across operating systems – which are a commodity and used by developers of all hues. An Ideal Database Ability List A system which allows a linear scale of the system (increase in throughput with reasonable response time) with the addition of resources A system which does not compromise on the ACID guarantees and require developers to learn new paradigms A system which does not force fit a new way interacting with database by learning Non-SQL dialect A system which does not force fit its mechanisms for providing availability across its various modules. Well NuoDB is the first database which has all of the above abilities and much more. In future articles I will cover my hands-on experience with it. 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: NuoDB

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  • Announcing: Oracle Database 11g R2 Certification on Oracle Linux 6

    - by Monica Kumar
    Oracle Announces the Certification of the Oracle Database on Oracle Linux 6 and Red Hat Enterprise Linux 6 Yesterday we announced the certification of Oracle Database 11g R2 with Oracle Linux 6 and Unbreakable Enterprise Kernel. Here are the key highlights: Oracle Database 11g Release 2 (R2) and Oracle Fusion Middleware 11g Release 1 (R1) are immediately available on Oracle Linux 6 with the Unbreakable Enterprise Kernel. Oracle Database 11g R2 and Oracle Fusion Middleware 11g R1 will be available on Red Hat Enterprise Linux 6 (RHEL6) and Oracle Linux 6 with the Red Hat Compatible Kernel in 90 days. Oracle offers direct Linux support to customers running RHEL6, Oracle Linux 6, or a combination of both. Oracle Linux will continue to maintain compatibility with Red Hat Linux. Read the full press release. 

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  • Ubuntu 12.04 NVIDIA GeForce Go 7600 black screen during boot

    - by Florian Schmidt
    I'm using Ubuntu as the only operating system since two years. In the first Ubuntu versions I had seen my BIOS screen and the boot screens. Actually im using Ubuntu 12.04 and my screen stays black until Ubuntu is started (both screens are missing). I guess this situation appeared the first time in Ubuntu 11 (not sure). I searched via google and tried the popular activities but was not able to fix my issue. I opened the laptop and checked all connections. I'm using boot option nomodeset. I had a look through many many web pages. I don't know how to continue and hope somebody could be helpful. My hardware: Acer Aspire 9300 AMD Turion 64 x2 NVIDIA GeForce Go 7600 (using proposed driver) lspci | grep NVIDIA 00:00.0 RAM memory: NVIDIA Corporation C51 Host Bridge (rev a2) 00:00.1 RAM memory: NVIDIA Corporation C51 Memory Controller 0 (rev a2) 00:00.2 RAM memory: NVIDIA Corporation C51 Memory Controller 1 (rev a2) 00:00.3 RAM memory: NVIDIA Corporation C51 Memory Controller 5 (rev a2) 00:00.4 RAM memory: NVIDIA Corporation C51 Memory Controller 4 (rev a2) 00:00.5 RAM memory: NVIDIA Corporation C51 Host Bridge (rev a2) 00:00.6 RAM memory: NVIDIA Corporation C51 Memory Controller 3 (rev a2) 00:00.7 RAM memory: NVIDIA Corporation C51 Memory Controller 2 (rev a2) 00:02.0 PCI bridge: NVIDIA Corporation C51 PCI Express Bridge (rev a1) 00:03.0 PCI bridge: NVIDIA Corporation C51 PCI Express Bridge (rev a1) 00:04.0 PCI bridge: NVIDIA Corporation C51 PCI Express Bridge (rev a1) 00:09.0 RAM memory: NVIDIA Corporation MCP51 Host Bridge (rev a2) 00:0a.0 ISA bridge: NVIDIA Corporation MCP51 LPC Bridge (rev a3) 00:0a.1 SMBus: NVIDIA Corporation MCP51 SMBus (rev a3) 00:0a.3 Co-processor: NVIDIA Corporation MCP51 PMU (rev a3) 00:0b.0 USB controller: NVIDIA Corporation MCP51 USB Controller (rev a3) 00:0b.1 USB controller: NVIDIA Corporation MCP51 USB Controller (rev a3) 00:0d.0 IDE interface: NVIDIA Corporation MCP51 IDE (rev f1) 00:0e.0 IDE interface: NVIDIA Corporation MCP51 Serial ATA Controller (rev f1) 00:10.0 PCI bridge: NVIDIA Corporation MCP51 PCI Bridge (rev a2) 00:10.1 Audio device: NVIDIA Corporation MCP51 High Definition Audio (rev a2) 00:14.0 Bridge: NVIDIA Corporation MCP51 Ethernet Controller (rev a3) 03:00.0 VGA compatible controller: NVIDIA Corporation G73 [GeForce Go 7600] (rev a1) So my question is what to do to fix the black screen during boot?

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