Search Results

Search found 31357 results on 1255 pages for 'database indexes'.

Page 458/1255 | < Previous Page | 454 455 456 457 458 459 460 461 462 463 464 465  | Next Page >

  • PASS Summit 2011 &ndash; Part IV

    - by Tara Kizer
    This is the final blog for my PASS Summit 2011 series.  Well okay, a mini-series, I guess. On the last day of the conference, I attended Keith Elmore’ and Boris Baryshnikov’s (both from Microsoft) “Introducing the Microsoft SQL Server Code Named “Denali” Performance Dashboard Reports, Jeremiah Peschka’s (blog|twitter) “Rewrite your T-SQL for Great Good!”, and Kimberly Tripp’s (blog|twitter) “Isolated Disasters in VLDBs”. Keith and Boris talked about the lifecycle of a session, figuring out the running time and the waiting time.  They pointed out the transient nature of the reports.  You could be drilling into it to uncover a problem, but the session may have ended by the time you’ve drilled all of the way down.  Also, the reports are for troubleshooting live problems and not historical ones.  You can use Management Data Warehouse for historical troubleshooting.  The reports provide similar benefits to the Activity Monitor, however Activity Monitor doesn’t provide context sensitive drill through. One thing I learned in Keith’s and Boris’ session was that the buffer cache hit ratio should really never be below 87% due to the read-ahead mechanism in SQL Server.  When a page is read, it will read the entire extent.  So for every page read, you get 7 more read.  If you need any of those 7 extra pages, well they are already in cache.  I had a lot of fun in Jeremiah’s session about refactoring code plus I learned a lot.  His slides were visually presented in a fun way, which just made for a more upbeat presentation.  Jeremiah says that before you start refactoring, you should look at your system.  Investigate missing or too many indexes, out-of-date statistics, and other areas that could be leading to your code running slow.  He talked about code standards.  He suggested using common abbreviations for aliases instead of one-letter aliases.  I’m a big offender of one-letter aliases, but he makes a good point.  He said that join order does not matter to the optimizer, but it does matter to those who have to read your code.  Now let’s get into refactoring! Eliminate useless things – useless/unneeded joins and columns.  If you don’t need it, get rid of it! Instead of using DISTINCT/JOIN, replace with EXISTS Simplify your conditions; use UNION or better yet UNION ALL instead of OR to avoid a scan and use indexes for each union query Branching logic – instead of IF this, IF that, and on and on…use dynamic SQL (sp_executesql, please!) or use a parameterized query in the application Correlated subqueries – YUCK! Replace with a join Eliminate repeated patterns Last, but certainly not least, was Kimberly’s session.  Kimberly is my favorite speaker.  I attended her two-day pre-conference seminar at PASS Summit 2005 as well as a SQL Immersion Event last December.  Did I mention she’s my favorite speaker?  Okay, enough of that. Kimberly’s session was packed with demos.  I had seen some of it in the SQL Immersion Event, but it was very nice to get a refresher on these, especially since I’ve got a VLDB with some growing pains.  One key takeaway from her session is the idea to use a log shipping solution with a load delay, such as 6, 8, or 24 hours behind the primary.  In the case of say an accidentally dropped table in a VLDB, we could retrieve it from the secondary database rather than waiting an eternity for a restore to complete.  Kimberly let us know that in SQL Server 2012 (it finally has a name!), online rebuilds are supported even if there are LOB columns in your table.  This will simplify custom code that intelligently figures out if an online rebuild is possible. There was actually one last time slot for sessions that day, but I had an airplane to catch and my kids to see!

    Read the article

  • Whether to use UNION or OR in SQL Server Queries

    - by Dinesh Asanka
    Recently I came across with an article on DB2 about using Union instead of OR. So I thought of carrying out a research on SQL Server on what scenarios UNION is optimal in and which scenarios OR would be best. I will analyze this with a few scenarios using samples taken  from the AdventureWorks database Sales.SalesOrderDetail table. Scenario 1: Selecting all columns So we are going to select all columns and you have a non-clustered index on the ProductID column. --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR ProductID =709 OR ProductID =998 OR ProductID =875 OR ProductID =976 OR ProductID =874 --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 709 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 998 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 875 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 976 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 874 So query 1 is using OR and the later is using UNION. Let us analyze the execution plans for these queries. Query 1 Query 2 As expected Query 1 will use Clustered Index Scan but Query 2, uses all sorts of things. In this case, since it is using multiple CPUs you might have CX_PACKET waits as well. Let’s look at the profiler results for these two queries: CPU Reads Duration Row Counts OR 78 1252 389 3854 UNION 250 7495 660 3854 You can see from the above table the UNION query is not performing well as the  OR query though both are retuning same no of rows (3854).These results indicate that, for the above scenario UNION should be used. Scenario 2: Non-Clustered and Clustered Index Columns only --Query 1 : OR SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR ProductID =709 OR ProductID =998 OR ProductID =875 OR ProductID =976 OR ProductID =874 GO --Query 2 : UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 709 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 998 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 875 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 976 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 874 GO So this time, we will be selecting only index columns, which means these queries will avoid a data page lookup. As in the previous case we will analyze the execution plans: Query 1 Query 2 Again, Query 2 is more complex than Query 1. Let us look at the profile analysis: CPU Reads Duration Row Counts OR 0 24 208 3854 UNION 0 38 193 3854 In this analyzis, there is only slight difference between OR and UNION. Scenario 3: Selecting all columns for different fields Up to now, we were using only one column (ProductID) in the where clause.  What if we have two columns for where clauses and let us assume both are covered by non-clustered indexes? --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR CarrierTrackingNumber LIKE 'D0B8%' --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE CarrierTrackingNumber  LIKE 'D0B8%' Query 1 Query 2: As we can see, the query plan for the second query has improved. Let us see the profiler results. CPU Reads Duration Row Counts OR 47 1278 443 1228 UNION 31 1334 400 1228 So in this case too, there is little difference between OR and UNION. Scenario 4: Selecting Clustered index columns for different fields Now let us go only with clustered indexes: --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR CarrierTrackingNumber LIKE 'D0B8%' --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE CarrierTrackingNumber  LIKE 'D0B8%' Query 1 Query 2 Now both execution plans are almost identical except is an additional Stream Aggregate is used in the first query. This means UNION has advantage over OR in this scenario. Let us see profiler results for these queries again. CPU Reads Duration Row Counts OR 0 319 366 1228 UNION 0 50 193 1228 Now see the differences, in this scenario UNION has somewhat of an advantage over OR. Conclusion Using UNION or OR depends on the scenario you are faced with. So you need to do your analyzing before selecting the appropriate method. Also, above the four scenarios are not all an exhaustive list of scenarios, I selected those for the broad description purposes only.

    Read the article

  • Implementing a modern web application with Web API on top of old services

    - by Gaui
    My company has many WCF services which may or may not be replaced in the near future. The old web application is written in WebForms and communicates straight with these services via SOAP and returns DataTables. Now I am designing a new modern web application in a modern style, an AngularJS client which communicates with an ASP.NET Web API via JSON. The Web API then communicates with the WCF services via SOAP. In the future I want to let the Web API handle all requests and go straight to the database, but because the business logic implemented in the WCF services is complicated it's going to take some time to rewrite and replace it. Now to the problem: I'm trying to make it easy in the near future to replace the WCF services with some other data storage, e.g. another endpoint, database or whatever. I also want to make it easy to unit test the business logic. That's why I have structured the Web API with a repository layer and a service layer. The repository layer has a straight communication with the data storage (WCF service, database, or whatever) and the service layer then uses the repository (Dependency Injection) to get the data. It doesn't care where it gets the data from. Later on I can be in control and structure the data returned from the data storage (DataTable to POCO) and be able to test the logic in the service layer with some mock repository (using Dependency Injection). Below is some code to explain where I'm going with this. But my question is, does this all make sense? Am I making this overly complicated and could this be simplified in any way possible? Does this simplicity make this too complicated to maintain? My main goal is to make it as easy as possible to switch to another data storage later on, e.g. an ORM and be able to test the logic in the service layer. And because the majority of the business logic is implemented in these WCF services (and they return DataTables), I want to be in control of the data and the structure returned to the client. Any advice is greatly appreciated. Update 20/08/14 I created a repository factory, so services would all share repositories. Now it's easy to mock a repository, add it to the factory and create a provider using that factory. Any advice is much appreciated. I want to know if I'm making things more complicated than they should be. So it looks like this: 1. Repository Factory public class RepositoryFactory { private Dictionary<Type, IServiceRepository> repositories; public RepositoryFactory() { this.repositories = new Dictionary<Type, IServiceRepository>(); } public void AddRepository<T>(IServiceRepository repo) where T : class { if (this.repositories.ContainsKey(typeof(T))) { this.repositories.Remove(typeof(T)); } this.repositories.Add(typeof(T), repo); } public dynamic GetRepository<T>() { if (this.repositories.ContainsKey(typeof(T))) { return this.repositories[typeof(T)]; } throw new RepositoryNotFoundException("No repository found for " + typeof(T).Name); } } I'm not very fond of dynamic but I don't know how to retrieve that repository otherwise. 2. Repository and service // Service repository interface // All repository interfaces extend this public interface IServiceRepository { } // Invoice repository interface // Makes it easy to mock the repository later on public interface IInvoiceServiceRepository : IServiceRepository { List<Invoice> GetInvoices(); } // Invoice repository // Connects to some data storage to retrieve invoices public class InvoiceServiceRepository : IInvoiceServiceRepository { public List<Invoice> GetInvoices() { // Get the invoices from somewhere // This could be a WCF, a database, or whatever using(InvoiceServiceClient proxy = new InvoiceServiceClient()) { return proxy.GetInvoices(); } } } // Invoice service // Service that handles talking to a real or a mock repository public class InvoiceService { // Repository factory RepositoryFactory repoFactory; // Default constructor // Default connects to the real repository public InvoiceService(RepositoryFactory repo) { repoFactory = repo; } // Service function that gets all invoices from some repository (mock or real) public List<Invoice> GetInvoices() { // Query the repository return repoFactory.GetRepository<IInvoiceServiceRepository>().GetInvoices(); } }

    Read the article

  • Url rewrite subfolder to root and forbid accessing subfolder

    - by Alessandro Pezzato
    I have drupal installed in a subfolder drupal, but I want to access pages as it is in root folder: http://www.example.com instead of http://www.example.com/drupal I'm able to have this working, but it's also working with url containing subfolder, so I have http://www.example.com and a clone site in http://www.example.com/drupal What is the rule to forbid access to subfolder? I want all url starting with http://www.example.com/drupal being forbidden. This is .htaccess in / directory: Options -Indexes Options +FollowSymLinks <IfModule mod_rewrite.c> RewriteEngine on RewriteCond %{HTTP_HOST} ^www\.(.+)$ [NC] RewriteRule ^ http://%1%{REQUEST_URI} [L,R=301] RewriteRule ^(.*+)$ drupal/$1 [L,QSA] </IfModule> And this is drupal .htaccess in /drupal/ directory: Options -Indexes Options +FollowSymLinks ErrorDocument 404 index.php DirectoryIndex index.php index.html index.htm # Override PHP settings that cannot be changed at runtime. See # sites/default/default.settings.php and drupal_initialize_variables() in # includes/bootstrap.inc for settings that can be changed at runtime. # PHP 5, Apache 1 and 2. <IfModule mod_php5.c> php_flag magic_quotes_gpc off php_flag magic_quotes_sybase off php_flag register_globals off php_flag session.auto_start off php_value mbstring.http_input pass php_value mbstring.http_output pass php_flag mbstring.encoding_translation off </IfModule> # Requires mod_expires to be enabled. <IfModule mod_expires.c> # Enable expirations. ExpiresActive On # Cache all files for 2 weeks after access (A). ExpiresDefault A1209600 <FilesMatch \.php$> # Do not allow PHP scripts to be cached unless they explicitly send cache # headers themselves. Otherwise all scripts would have to overwrite the # headers set by mod_expires if they want another caching behavior. This may # fail if an error occurs early in the bootstrap process, and it may cause # problems if a non-Drupal PHP file is installed in a subdirectory. ExpiresActive Off </FilesMatch> </IfModule> # Various rewrite rules. <IfModule mod_rewrite.c> RewriteEngine on # Block access to "hidden" directories whose names begin with a period. This # includes directories used by version control systems such as Subversion or # Git to store control files. Files whose names begin with a period, as well # as the control files used by CVS, are protected by the FilesMatch directive # above. RewriteRule "(^|/)\." - [F] # To redirect all users to access the site WITH the 'www.' prefix, # (http://example.com/... will be redirected to http://www.example.com/...) # uncomment the following: # RewriteCond %{HTTP_HOST} !^www\. [NC] # RewriteRule ^ http://www.%{HTTP_HOST}%{REQUEST_URI} [L,R=301] # # To redirect all users to access the site WITHOUT the 'www.' prefix, # (http://www.example.com/... will be redirected to http://example.com/...) # uncomment the following: RewriteCond %{HTTP_HOST} ^www\.(.+)$ [NC] RewriteRule ^ http://%1%{REQUEST_URI} [L,R=301] RewriteBase /drupal # Pass all requests not referring directly to files in the filesystem to # index.php. Clean URLs are handled in drupal_environment_initialize(). RewriteCond %{REQUEST_FILENAME} !-f RewriteCond %{REQUEST_FILENAME} !-d RewriteCond %{REQUEST_URI} !=/favicon.ico #RewriteRule ^ index.php [L] RewriteRule ^(.*)$ index.php?q=$1 [L,QSA] # Rules to correctly serve gzip compressed CSS and JS files. # Requires both mod_rewrite and mod_headers to be enabled. <IfModule mod_headers.c> # Serve gzip compressed CSS files if they exist and the client accepts gzip. RewriteCond %{HTTP:Accept-encoding} gzip RewriteCond %{REQUEST_FILENAME}\.gz -s RewriteRule ^(.*)\.css $1\.css\.gz [QSA] # Serve gzip compressed JS files if they exist and the client accepts gzip. RewriteCond %{HTTP:Accept-encoding} gzip RewriteCond %{REQUEST_FILENAME}\.gz -s RewriteRule ^(.*)\.js $1\.js\.gz [QSA] # Serve correct content types, and prevent mod_deflate double gzip. RewriteRule \.css\.gz$ - [T=text/css,E=no-gzip:1] RewriteRule \.js\.gz$ - [T=text/javascript,E=no-gzip:1] <FilesMatch "(\.js\.gz|\.css\.gz)$"> # Serve correct encoding type. Header append Content-Encoding gzip # Force proxies to cache gzipped & non-gzipped css/js files separately. Header append Vary Accept-Encoding </FilesMatch> </IfModule> </IfModule>

    Read the article

  • ATG Live Webcast June 14: Technical Preview of EBS 12.2 Online Patching

    - by BillSawyer
    Online Patching is is one of the cornerstone new features in our upcoming Oracle E-Business Suite 12.2 release. This ground-breaking feature is based upon Edition-Based Redefinition, a new 11gR2 Database feature that was built to Oracle Applications division specifications to allow the E-Business Suite's database tier to be patched while the environment is running.  Online Patching combines the use of Edition-Based Redefinition and new E-Business Suite technologies to allow patching to the E-Business Suite's database and application tier servers while the environment is being actively used by its end-users. This webcast provides a detailed technical preview of: How this new feature works How it affects E-Business Suite end-users How it affects E-Business Suite database administrators and patching lifecycles How it affects developers and third-party software vendors responsible for E-Business Suite customizations and extensions The presenter for this event is Kevin Hudson, Senior Director and one of the Online Patching architects. There will be a special extended Q&A Session at the end of this presentation, given the nature of the materials and the questions that we expect from you. ATG Development staff supporting the Q&A session will include Elke Phelps, Santiago Bastidas, Max Arderius, and other ATG architects. Date:               Thursday, June 14, 2012Time:              8:00 AM - 10:00 AM Pacific Standard Time (Special 2-hour Time)Presenter:    Kevin Hudson, Senior Director, Applications Technology IntegrationWebcast Registration Link (Preregistration is optional but encouraged) To hear the audio feed:   Domestic Participant Dial-In Number:           877-697-8128   International Participant Dial-In Number:      706-634-9568   Dial-In Passcode:                                              100815To see the presentation:    The Direct Access Web Conference details are:    Website URL: https://ouweb.webex.com    Meeting Number:  597470987If you miss the webcast, or you have missed any webcast, don't worry -- we'll post links to the recording as soon as it's available from Oracle University.  You can monitor this blog for pointers to the replay. And, you can find our archive of our past webcasts and training here. When will Oracle E-Business Suite 12.2 be released? Oracle's Revenue Recognition rules prohibit us from discussing certification and release dates, but you're welcome to monitor or subscribe to this blog. We'll post updates here as soon as soon as they're available.    

    Read the article

  • Top 10 Linked Blogs of 2010

    - by Bill Graziano
    Each week I send out a SQL Server newsletter and include links to interesting blog posts.  I’ve linked to over 500 blog posts so far in 2010.  Late last year I started storing those links in a database so I could do a little reporting.  I tend to link to posts related to the OLTP engine.  I also try to link to the individual blogger in the group blogs.  Unfortunately that wasn’t possible for the SQLCAT and CSS blogs.  I also have a real weakness for posts related to PASS. These are the top 10 blogs that I linked to during the year ordered by the number of posts I linked to. Paul Randal – Paul writes extensively on the internals of the relational engine.  Lots of great posts around transactions, transaction log, disaster recovery, corruption, indexes and DBCC.  I also linked to many of his SQL Server myths posts. Glenn Berry – Glenn writes very interesting posts on how hardware affects SQL Server.  I especially like his posts on the various CPU platforms.  These aren’t necessarily topics that I’m searching for but I really enjoy reading them. The SQLCAT Team – This Microsoft team focuses on the largest and most interesting SQL Server installations.  The regularly publish white papers and best practices. SQL Server CSS Team – These are the top engineers from the Microsoft Customer Service and Support group.  These are the folks you finally talk to after your case has been escalated about 20 times.  They write about the interesting problems they find. Brent Ozar – The posts I linked to mostly focused on the relational engine: CPU, NUMA, SSD drives, performance monitoring, etc.  But Brent writes about a real variety of topics including blogging, social networking, speaking, the MCM, SQL Azure and anything else that seems to strike his fancy.  His posts are always well written and though provoking. Jeremiah Peschka – A number of Jeremiah’s posts weren’t about SQL Server.  He’s very active in the “NoSQL” area and I linked to a number of those posts.  I think it’s important for people to know what other technologies are out there. Brad McGehee – Brad writes about being a DBA including maintenance plans, DBA checklists, compression and audit. Thomas LaRock – I linked to a variety of posts from PBM to networking to 24 Hours of PASS to TDE.  Just a real variety of topics.  Tom always writes with an interesting style usually mixing in a movie theme and/or bacon. Aaron Bertrand – Many of my links this year were Denali features.  He also had a great series on bad habits to kick. Michael J. Swart – This last one surprised me.  There are some well known SQL Server bloggers below Michael on this list.  I linked to posts on indexes, hierarchies, transactions and I/O performance and a variety of other engine related posts.  All are interesting and well thought out.  Many of his non-SQL posts are also very good.  He seems to have an interest in puzzles and other brain teasers.  Michael, I won’t be surprised again!

    Read the article

  • T-SQL in Chicago – the LobsterPot teams with DataEducation

    - by Rob Farley
    In May, I’ll be in the US. I have board meetings for PASS at the SQLRally event in Dallas, and then I’m going to be spending a bit of time in Chicago. The big news is that while I’m in Chicago (May 14-16), I’m going to teach my “Advanced T-SQL Querying and Reporting: Building Effectiveness” course. This is a course that I’ve been teaching since the 2005 days, and have modified over time for 2008 and 2012. It’s very much my most popular course, and I love teaching it. Let me tell you why. For years, I wrote queries and thought I was good at it. I was a developer. I’d written a lot of C (and other, more fun languages like Prolog and Lisp) at university, and then got into the ‘real world’ and coded in VB, PL/SQL, and so on through to C#, and saw SQL (whichever database system it was) as just a way of getting the data back. I could write a query to return just about whatever data I wanted, and that was good. I was better at it than the people around me, and that helped. (It didn’t help my progression into management, then it just became a frustration, but for the most part, it was good to know that I was good at this particular thing.) But then I discovered the other side of querying – the execution plan. I started to learn about the translation from what I’d written into the plan, and this impacted my query-writing significantly. I look back at the queries I wrote before I understood this, and shudder. I wrote queries that were correct, but often a long way from effective. I’d done query tuning, but had largely done it without considering the plan, just inferring what indexes would help. This is not a performance-tuning course. It’s focused on the T-SQL that you read and write. But performance is a significant and recurring theme. Effective T-SQL has to be about performance – it’s the biggest way that a query becomes effective. There are other aspects too though – such as using constructs better. For example – I can write code that modifies data nicely, but if I haven’t learned about the MERGE statement and the way that it can impact things, I’m missing a few tricks. If you’re going to do this course, a good place to be is the situation I was in a few years before I wrote this course. You’re probably comfortable with writing T-SQL queries. You know how to make a SELECT statement do what you need it to, but feel there has to be a better way. You can write JOINs easily, and understand how to use LEFT JOIN to make sure you don’t filter out rows from the first table, but you’re coding blind. The first module I cover is on Query Execution. Take a look at the Course Outline at Data Education’s website. The first part of the first module is on the components of a SELECT statement (where I make you think harder about GROUP BY than you probably have before), but then we jump straight into Execution Plans. Some stuff on indexes is in there too, as is simplification and SARGability. Some of this is stuff that you may have heard me present on at conferences, but here you have me for three days straight. I’m sure you can imagine that we revisit these topics throughout the rest of the course as well, and you’d be right. In the second and third modules we look at a bunch of other aspects, including some of the T-SQL constructs that lots of people don’t know, and various other things that can help your T-SQL be, well, more effective. I’ve had quite a lot of people do this course and be itching to get back to work even on the first day. That’s not a comment about the jokes I tell, but because people want to look at the queries they run. LobsterPot Solutions is thrilled to be partnering with Data Education to bring this training to Chicago. Visit their website to register for the course. @rob_farley

    Read the article

  • SQL SERVER – Select the Most Optimal Backup Methods for Server

    - by pinaldave
    Backup and Restore are very interesting concepts and one should be very much with the concept if you are dealing with production database. One never knows when a natural disaster or user error will surface and the first thing everybody wants is to get back on point in time when things were all fine. Well, in this article I have attempted to answer a few of the common questions related to Backup methodology. How to Select a SQL Server Backup Type In order to select a proper SQL Server backup type, a SQL Server administrator needs to understand the difference between the major backup types clearly. Since a picture is worth a thousand words, let me offer it to you below. Select a Recovery Model First The very first question that you should ask yourself is: Can I afford to lose at least a little (15 min, 1 hour, 1 day) worth of data? Resist the temptation to save it all as it comes with the overhead – majority of businesses outside finances can actually afford to lose a bit of data. If your answer is YES, I can afford to lose some data – select a SIMPLE (default) recovery model in the properties of your database, otherwise you need to select a FULL recovery model. The additional advantage of the Full recovery model is that it allows you to restore the data to a specific point in time vs to only last backup time in the Simple recovery model, but it exceeds the scope of this article Backups in SIMPLE Recovery Model In SIMPLE recovery model you can select to do just Full backups or Full + Differential. Full Backup This is the simplest type of backup that contains all information needed to restore the database and should be your first choice. It is often sufficient for small databases, but note that it makes a big impact on the performance of your database Full + Differential Backup After Full, Differential backup picks up all of the changes since the last Full backup. This means if you made Full, Diff, Diff backup – the last Diff backup contains all of the changes and you don’t need the previous Differential backup. Differential backup is obviously smaller and carries less performance overhead Backups in FULL Recovery Model In FULL recovery model you can select Full + Transaction Log or Full + Differential + Transaction Log backup. You have to create Transaction Log backup, because at that time the log is being truncated. Otherwise your Transaction Log will grow uncontrollably. Full + Transaction Log Backup You would always need to perform a Full backup first. Then a series of Transaction log backup. Note that (in contrast to Differential) you need ALL transactions to log since the last Full of Diff backup to properly restore. Transaction log backups have the smallest performance overhead and can be performed often. Full + Differential + Transaction Log Backup If you want to ease the performance overhead on your server, you can replace some of the Full backup in the previous scenario with Differential. You restore scenario would start from Full, then the Last Differential, then all of the remaining transactions log backups Typical backup Scenarios You may say “Well, it is all nice – give me the examples now”. As you may already know, my favorite SQL backup software is SQLBackupAndFTP. If you go to Advanced Backup Schedule form in this program and click “Load a typical backup plan…” link, it will give you these scenarios that I think are quite common – see the image below. The Simplest Way to Schedule SQL Backups I hate to repeat myself, but backup scheduling in SQL agent leaves a lot to be desired. I do not know the simple way to schedule your SQL server backups than in SQLBackupAndFTP – see the image below. The whole backup scheduling with compression, encryption and upload to a Network Folder / HDD / NAS Drive / FTP / Dropbox / Google Drive / Amazon S3 takes just a few minutes – see my previous post for the review. Final Words This post offered an explanation for major backup types only. For more complicated scenarios or to research other options as usually go to MSDN. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

    Read the article

  • MaxTotalSizeInBytes - Blind spots in Usage file and Web Analytics Reports

    - by Gino Abraham
    Originally posted on: http://geekswithblogs.net/GinoAbraham/archive/2013/10/28/maxtotalsizeinbytes---blind-spots-in-usage-file-and-web-analytics.aspx http://blogs.msdn.com/b/sharepoint_strategery/archive/2012/04/16/usage-file-and-web-analytics-reports-with-blind-spots.aspx In my previous post (Troubleshooting SharePoint 2010 Web Analytics), I referenced a problem that can occur when exceeding the daily partition size for the LoggingDB, which generates the ULS message “[Partition] has exceeded the max bytes”. Below, I wanted to provide some additional info on this particular issue and help identify some options if this occurs. As an aside, this post only applies if you are missing portions of Usage data - think blind spots on intermittent days or user activity regularly sparse for the afternoon/evening. If this fits your scenario - read on. But if Usage logs are outright missing, go check out my Troubleshooting post first.  Background on the problem:The LoggingDB database has a default maximum size of ~6GB. However, SharePoint evenly splits this total size into fixed sized logical partitions – and the number of partitions is defined by the number of days to retain Usage data (by default 14 days). In this case, 14 partitions would be created to account for the 14 days of retention. If the retention were halved to 7 days, the LoggingDBwould be split into 7 corresponding partitions at twice the size. In other words, the partition size is generally defined as [max size for DB] / [number of retention days].Going back to the default scenario, the “max size” for the LoggingDB is 6200000000 bytes (~6GB) and the retention period is 14 days. Using our formula, this would be [~6GB] / [14 days], which equates to 444858368 bytes (~425MB) per partition per day. Again, if the retention were halved to 7 days (which halves the number of partitions), the resulting partition size becomes [~6GB] / [7 days], or ~850MB per partition.From my experience, when the partition size for any given day is exceeded, the usage logging for the remainder of the day is essentially thrown away because SharePoint won’t allow any more to be written to that day’s partition. The only clue that this is occurring (beyond truncated usage data) is an error such as the following that gets reported in the ULS:04/08/2012 09:30:04.78    OWSTIMER.EXE (0x1E24)    0x2C98    SharePoint Foundation    Health    i0m6     High    Table RequestUsage_Partition12 has 444858368 bytes that has exceeded the max bytes 444858368It’s also worth noting that the exact bytes reported (e.g. ‘444858368’ above) may slightly vary among farms. For example, you may instead see 445226812, 439123456, or something else in the ballpark. The exact number itself doesn't matter, but this error message intends to indicates that the reporting usage has exceeded the partition size for the given day.What it means:The error itself is easy to miss, which can lead to substantial gaps in the reporting data (your mileage may vary) if not identified. At this point, I can only advise to periodically check the ULS logs for this message. Down the road, I plan to explore if [Developing a Custom Health Rule] could be leveraged to identify the issue (If you've ever built Custom Health Rules, I'd be interested to hear about your experiences). Overcoming this issue also poses a challenge, with workaround options including:Lower the retentionBecause the partition size is generally defined as [max size] / [number of retention days], the first option is to lower the number of days to retain the data – the lower the retention, the lower the divisor and thus a bigger partition. For example, halving the retention from 14 to 7 days would halve the number of partitions, but double the partition size to ~850MB (e.g. [6200000000 bytes] / [7 days] = ~850GB partitions). Lowering it to 2 days would result in two ~3GB partitions… and so on.Recreate the LoggingDB with an increased sizeThe property MaxTotalSizeInBytes is exposed by OM code for the SPUsageDefinition object and can be updated with the example PowerShell snippet below. However, updating this value has no immediate impact because this size only applies when creating a LoggingDB. Therefore, you must create a newLoggingDB for the Usage Service Application. The gotcha: this effectively deletes all prior Usage databecause the Usage Service Application can only have a single LoggingDB.Here is an example snippet to update the "Page Requests" Usage Definition:$def=Get-SPUsageDefinition -Identity "page requests" $def.MaxTotalSizeInBytes=12400000000 $def.update()Create a new Logging database and attach to the Usage Service Application using the following command: Get-spusageapplication | Set-SPUsageApplication -DatabaseServer <dbServer> -DatabaseName <newDBname> Updated (5/10/2012): Once the new database has been created, you can confirm the setting has truly taken by running the following SQL Query (be sure to replace the database name in the following query with the name provided in the PowerShell above)SELECT * FROM [WSS_UsageApplication].[dbo].[Configuration] WITH (nolock) WHERE ConfigName LIKE 'Max Total Bytes - RequestUsage'

    Read the article

  • Best of OTN - Week of Oct 21st

    - by CassandraClark-OTN
    This week's Best of OTN, for you, the best devs, dba's, sysadmins and architects out there!  In these weekly posts the OTN team will highlight the top content from each community; Architect, Database, Systems and Java.  Since we'll be publishing this on Fridays, we'll also mix in a little fun! Architect Community Top Content- The Road Ahead for WebLogic 12c | Edwin BiemondOracle ACE Edwin Biemond shares his thoughts on announced new features in Oracle WebLogic 12.1.3 & 12.1.4 and compares those upcoming releases to Oracle WebLogic 12.1.2. A Roadmap for SOA Development and Delivery | Mark NelsonDo you know the way to S-O-A? Mark Nelson does. His latest blog post, part of an ongoing series, will help to keep you from getting lost along the way. Updated ODI Statement of Direction | Robert SchweighardtHeads up Oracle Data Integrator fans! A new statement of product direction document is available, offering an overview of the strategic product plans for Oracle’s data integration products for bulk data movement and transformation, specifically Oracle Data Integrator (ODI) and Oracle Warehouse Builder (OWB). Bob Rhubart, Architect Community Manager Friday Funny - "Some people approach every problem with an open mouth." — Adlai E. Stevenson (October 23, 1835 – June 14, 1914) 23rd Vice President of the United States Database Community Top Content - Pre-Built Developer VMs (for Oracle VM VirtualBox)Heard all the chatter about Oracle VirtualBox? Over 1 million downloads per week and look: pre-built virtual appliances designed specifically for developers. Video: Big Data, or BIG DATA?Oracle Ace Director Ben Prusinski explains the differences.?? Webcast Series - Developing Applications in Oracle's Public CloudTime to get started on developing and deploying cloud applications by moving to the cloud. Good friend Gene Eun from Oracle's Cloud team posted this two-part Webcast series that has an overview and demonstration of the Oracle Database Cloud Service. Check out the demos on how to migrate your data to the cloud, extend your application with interactive reporting, and create and access RESTful Web services. Registration required, but so worth it! Laura Ramsey, Database Community Manager Friday Funny - Systems Community Top Content - Video: What Kind of Scalability is Better, Horizontal or Vertical?Rick Ramsey asks the question "Is Oracle's approach to large vertically scaled servers at odds with today's trend of combining lots and lots of small, low-cost servers systems with networking to build a cloud, or is it a better approach?" Michael Palmeter, Director of Solaris Product Management, and Renato Ribeiro, Director Product Management for SPARC Servers, discuss.Video: An Engineer Takes a Minute to Explain CloudBart Smaalders, long-time Oracle Solaris core engineer, takes a minute to explain cloud from a sysadmin point of view. ?Hands-On Lab: How to Deploy and Manage a Private IaaS Cloud Soup to nuts. This lab shows you how to set up and manage a private cloud with Oracle Enterprise Manager Cloud Control 12c in an Infrastructure as a service (IaaS) model. You will first configure the IaaS cloud as the cloud administrator and then deploy guest virtual machines (VMs) as a self-service user. Rick Ramsey, Systems Community Manager Friday Funny - Video: Drunk Airline Pilot - Dean Martin - Foster Brooks Java Community Top Content - Video: NightHacking Interview with James GoslingJames Gosling, the Father of Java, discusses robotics, Java and how to keep his autonomous WaveGliders in the ocean for weeks at a time. Live from Hawaii.  Video: Raspberry Pi Developer Challenge: Remote Controller A developer who knew nothing about Java Embedded or Raspberry Pi shows how he can now control a robot with his phone. The project was built during the Java Embedded Challenge for Raspberry Pi at JavaOne 2013.Java EE 7 Certification Survey - Participants NeededHelp us define how to server your training and certification needs for Java EE 7. Tori Wieldt, Java Community Manager Friday Funny - Programmers have a strong sensitivity to Yak's pheromone. Causes irresistible desire to shave said Yak. Thanks, @rickasaurus! To follow and take part in the conversation follow/like etc. at one or all of the resources below -  OTN TechBlog The Java Source Blog The OTN Garage Blog The OTN ArchBeat Blog @oracletechnet @java @OTN_Garage @OTNArchBeat @OracleDBDev OTN I Love Java OTN Garage OTN ArchBeat Oracle DB Dev OTN Java

    Read the article

  • SQL Constraints &ndash; CHECK and NOCHECK

    - by David Turner
    One performance issue i faced at a recent project was with the way that our constraints were being managed, we were using Subsonic as our ORM, and it has a useful tool for generating your ORM code called SubStage – once configured, you can regenerate your DAL code easily based on your database schema, and it can even be integrated into your build as a pre-build event if you want to do this.  SubStage also offers the useful feature of being able to generate DDL scripts for your entire database, and can script your data for you too. The problem came when we decided to use the generate scripts feature to migrate the database onto a test database instance – it turns out that the DDL scripts that it generates include the WITH NOCHECK option, so when we executed them on the test instance, and performed some testing, we found that performance wasn’t as expected. A constraint can be disabled, enabled but not trusted, or enabled and trusted.  When it is disabled, data can be inserted that violates the constraint because it is not being enforced, this is useful for bulk load scenarios where performance is important.  So what does it mean to say that a constraint is trusted or not trusted?  Well this refers to the SQL Server Query Optimizer, and whether it trusts that the constraint is valid.  If it trusts the constraint then it doesn’t check it is valid when executing a query, so the query can be executed much faster. Here is an example base in this article on TechNet, here we create two tables with a Foreign Key constraint between them, and add a single row to each.  We then query the tables: 1 DROP TABLE t2 2 DROP TABLE t1 3 GO 4 5 CREATE TABLE t1(col1 int NOT NULL PRIMARY KEY) 6 CREATE TABLE t2(col1 int NOT NULL) 7 8 ALTER TABLE t2 WITH CHECK ADD CONSTRAINT fk_t2_t1 FOREIGN KEY(col1) 9 REFERENCES t1(col1) 10 11 INSERT INTO t1 VALUES(1) 12 INSERT INTO t2 VALUES(1) 13 GO14 15 SELECT COUNT(*) FROM t2 16 WHERE EXISTS17 (SELECT *18 FROM t1 19 WHERE t1.col1 = t2.col1) This all works fine, and in this scenario the constraint is enabled and trusted.  We can verify this by executing the following SQL to query the ‘is_disabled’ and ‘is_not_trusted’ properties: 1 select name, is_disabled, is_not_trusted from sys.foreign_keys This gives the following result: We can disable the constraint using this SQL: 1 alter table t2 NOCHECK CONSTRAINT fk_t2_t1 And when we query the constraints again, we see that the constraint is disabled and not trusted: So the constraint won’t be enforced and we can insert data into the table t2 that doesn’t match the data in t1, but we don’t want to do this, so we can enable the constraint again using this SQL: 1 alter table t2 CHECK CONSTRAINT fk_t2_t1 But when we query the constraints again, we see that the constraint is enabled, but it is still not trusted: This means that the optimizer will check the constraint each time a query is executed over it, which will impact the performance of the query, and this is definitely not what we want, so we need to make the constraint trusted by the optimizer again.  First we should check that our constraints haven’t been violated, which we can do by running DBCC: 1 DBCC CHECKCONSTRAINTS (t2) Hopefully you see the following message indicating that DBCC completed without finding any violations of your constraint: Having verified that the constraint was not violated while it was disabled, we can simply execute the following SQL:   1 alter table t2 WITH CHECK CHECK CONSTRAINT fk_t2_t1 At first glance this looks like it must be a typo to have the keyword CHECK repeated twice in succession, but it is the correct syntax and when we query the constraints properties, we find that it is now trusted again: To fix our specific problem, we created a script that checked all constraints on our tables, using the following syntax: 1 ALTER TABLE t2 WITH CHECK CHECK CONSTRAINT ALL

    Read the article

  • New R Interface to Oracle Data Mining Available for Download

    - by charlie.berger
      The R Interface to Oracle Data Mining ( R-ODM) allows R users to access the power of Oracle Data Mining's in-database functions using the familiar R syntax. R-ODM provides a powerful environment for prototyping data analysis and data mining methodologies. R-ODM is especially useful for: Quick prototyping of vertical or domain-based applications where the Oracle Database supports the application Scripting of "production" data mining methodologies Customizing graphics of ODM data mining results (examples: classification, regression, anomaly detection) The R-ODM interface allows R users to mine data using Oracle Data Mining from the R programming environment. It consists of a set of function wrappers written in source R language that pass data and parameters from the R environment to the Oracle RDBMS enterprise edition as standard user PL/SQL queries via an ODBC interface. The R-ODM interface code is a thin layer of logic and SQL that calls through an ODBC interface. R-ODM does not use or expose any Oracle product code as it is completely an external interface and not part of any Oracle product. R-ODM is similar to the example scripts (e.g., the PL/SQL demo code) that illustrates the use of Oracle Data Mining, for example, how to create Data Mining models, pass arguments, retrieve results etc. R-ODM is packaged as a standard R source package and is distributed freely as part of the R environment's Comprehensive R Archive Network (CRAN). For information about the R environment, R packages and CRAN, see www.r-project.org. R-ODM is particularly intended for data analysts and statisticians familiar with R but not necessarily familiar with the Oracle database environment or PL/SQL. It is a convenient environment to rapidly experiment and prototype Data Mining models and applications. Data Mining models prototyped in the R environment can easily be deployed in their final form in the database environment, just like any other standard Oracle Data Mining model. What is R? R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files. The design of R has been heavily influenced by two existing languages: Becker, Chambers & Wilks' S and Sussman's Scheme. Whereas the resulting language is very similar in appearance to S, the underlying implementation and semantics are derived from Scheme. R was initially written by Ross Ihaka and Robert Gentleman at the Department of Statistics of the University of Auckland in Auckland, New Zealand. Since mid-1997 there has been a core group (the "R Core Team") who can modify the R source code archive. Besides this core group many R users have contributed application code as represented in the near 1,500 publicly-available packages in the CRAN archive (which has shown exponential growth since 2001; R News Volume 8/2, October 2008). Today the R community is a vibrant and growing group of dozens of thousands of users worldwide. It is free software distributed under a GNU-style copyleft, and an official part of the GNU project ("GNU S"). Resources: R website / CRAN R-ODM

    Read the article

  • GoldenGate 12c - MySQL Active-Active Replication Setup

    - by Jinyu Wang-Oracle
    Active-active  (also called Master-Master or Bi-Directional) replication captures data changes from two or more systems and replicat the changes to synchronize the data.  Active-Active replication is often needed for high availability, load balancing and scaling out purposes.   Oracle GoldenGate is known to be one of the first and the best replication tool handling active-active replications. As of Oracle GoldenGate 12c, it provides (Refer to Oracle GoldenGate 12.1.2 Documentation - Configuring Oracle GoldenGate for Active-Active High Availability for more information) the followings: Robust loop-back prevention Comprehensive conflict resolution and detection support Heterogeneous support across different database versions and operation systems.  Oracle GoldenGate supports active-active configurations for DB2 on z/OS, LUW, and IBM i, MySQL, Oracle, SQL/MX,SQL Server, Sybase, and Teradata. However, the setup is different from database to database. In this example, I will show you how to setup an active-active data replication between two MySQL database instances. The example setup below is to have active-active replication between MySQL 5.5 and MySQL 5.6 instances and is shown as follows: MySQL 5.5 (Manager Port: 15105)  Extract EXTRACT demoex01 SETENV (MYSQL_UNIX_PORT='/home/oracle/software/mysql_5.5.38/data/mysql.sock') DBOPTIONS CONNECTIONPORT 3305 DBOPTIONS HOST oraclelinux6.localdomain SOURCEDB test USERID root, PASSWORD mysql EXTTRAIL ./dirdat/extract/de TRANLOGOPTIONS ALTLOGDEST "/home/oracle/software/mysql_5.5.38/data/binlog/bin-log.index" FILTERTABLE test.checkpoint_tbl REPORTROLLOVER AT 05:30 ON saturday TABLE test.TCUSTMER; TABLE test.TCUSTORD; Pump EXTRACT demopm01 RMTHOST localhost, MGRPORT 15106, COMPRESS, TIMEOUT 30 RMTTRAIL ./dirdat/replicat/ps PASSTHRU TABLE test.TCUSTMER; TABLE test.TCUSTORD; Replicat replicat demorp01 setenv (MYSQL_UNIX_PORT='/home/oracle/software/mysql_5.5.38/data/mysql.sock') dboptions host oraclelinux6.localdomain, connectionport 3305 targetdb test, userid root, password mysql sourcedefs ./dirdat/replicat/democust.def discardfile ./dirrpt/demprp01.dsc, purge REPERROR (DEFAULT, ABEND) REPERROR(1062, IGNORE) map test.TCUSTMER, target test.TCUSTMER,colmap(usedefaults, region_code="region code"); map test.TCUSTORD, target test.TCUSTORD; MySQL 5.6 (Manager Port: 15106) Replicat replicat demorp01 setenv (MYSQL_UNIX_PORT='/home/oracle/software/mysql_5.6.19/data/mysql.sock') dboptions host oraclelinux6.localdomain, connectionport 3306 targetdb test, userid root, password mysql --assumetargetdefs sourcedefs ./dirdat/replicat/democust.def discardfile ./dirrpt/demprp01.dsc, purge map test.TCUSTMER, target test.TCUSTMER, colmap(usedefaults, "region code"=region_code); map test.TCUSTORD, target test.TCUSTORD; Extract EXTRACT demoex01 SETENV (MYSQL_UNIX_PORT='/home/oracle/software/mysql_5.6.19/data/mysql.sock') DBOPTIONS CONNECTIONPORT 3306 DBOPTIONS HOST oraclelinux6.localdomain SOURCEDB test USERID root, USERID mysql EXTTRAIL ./dirdat/extract/de TRANLOGOPTIONS ALTLOGDEST "/usr/local/mysql56/data/binlog/bin-log.index" FILTERTABLE test.checkpoint_tbl TABLE test.TCUSTMER; TABLE test.TCUSTORD; Pump EXTRACT demopm01 RMTHOST localhost, MGRPORT 15105, COMPRESS, TIMEOUT 30 RMTTRAIL ./dirdat/replicat/ps PASSTHRU TABLE test.TCUSTMER; TABLE test.TCUSTORD; The setup parameters are quite self-explanatory. The key setup is to avoid the replication data  looping. Oracle GoldenGate for MySQL uses the information in the replication checkpoint table to identify the transaction applied by replicats and thus avoid extracting those transactions by Oracle GoldenGate extracts. The example setup in the extract in MySQL 5.5 instance is shown as follows.  TRANLOGOPTIONS ALTLOGDEST "/home/oracle/software/mysql_5.5.38/data/binlog/bin-log.index" FILTERTABLE test.checkpoint_tbl Setting up an active-active replication is often more complicated than this and requires the following additional considerations. I would elaborate on this in the follow-up discussions. 

    Read the article

  • SQL SERVER – Finding Different ColumnName From Almost Identitical Tables

    - by pinaldave
    I have mentioned earlier on this blog that I love social media – Facebook and Twitter. I receive so many interesting questions that sometimes I wonder how come I never faced them in my real life scenario. Well, let us see one of the similar situation. Here is one of the questions which I received on my social media handle. “Pinal, I have a large database. I did not develop this database but I have inherited this database. In our database we have many tables but all the tables are in pairs. We have one archive table and one current table. Now here is interesting situation. For a while due to some reason our organization has stopped paying attention to archive data. We did not archive anything for a while. If this was not enough we  even changed the schema of current table but did not change the corresponding archive table. This is now becoming a huge huge problem. We know for sure that in current table we have added few column but we do not know which ones. Is there any way we can figure out what are the new column added in the current table and does not exist in the archive tables? We cannot use any third party tool. Would you please guide us?” Well here is the interesting example of how we can use sys.column catalogue views and get the details of the newly added column. I have previously written about EXCEPT over here which is very similar to MINUS of Oracle. In following example we are going to create two tables. One of the tables has extra column. In our resultset we will get the name of the extra column as we are comparing the catalogue view of the column name. USE AdventureWorks2012 GO CREATE TABLE ArchiveTable (ID INT, Col1 VARCHAR(10), Col2 VARCHAR(100), Col3 VARCHAR(100)); CREATE TABLE CurrentTable (ID INT, Col1 VARCHAR(10), Col2 VARCHAR(100), Col3 VARCHAR(100), ExtraCol INT); GO -- Columns in ArchiveTable but not in CurrentTable SELECT name ColumnName FROM sys.columns WHERE OBJECT_NAME(OBJECT_ID) = 'ArchiveTable' EXCEPT SELECT name ColumnName FROM sys.columns WHERE OBJECT_NAME(OBJECT_ID) = 'CurrentTable' GO -- Columns in CurrentTable but not in ArchiveTable SELECT name ColumnName FROM sys.columns WHERE OBJECT_NAME(OBJECT_ID) = 'CurrentTable' EXCEPT SELECT name ColumnName FROM sys.columns WHERE OBJECT_NAME(OBJECT_ID) = 'ArchiveTable' GO DROP TABLE ArchiveTable; DROP TABLE CurrentTable; GO The above query will return us following result. I hope this solves the problems. It is not the most elegant solution ever possible but it works. Here is the puzzle back to you – what native T-SQL solution would you have provided in this situation? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL System Table, SQL Tips and Tricks, T SQL, Technology

    Read the article

  • SQL SERVER – Importance of User Without Login

    - by pinaldave
    Some questions are very open ended and it is very hard to come up with exact requirements. Here is one question I was asked in recent User Group Meeting. Question: “In recent version of SQL Server we can create user without login. What is the use of it?” Great question indeed. Let me first attempt to answer this question but after reading my answer I need your help. I want you to help him as well with adding more value to it. Answer: Let us visualize a scenario. An application has lots of different operations and many of them are very sensitive operations. The common practice was to do give application specific role which has more permissions and access level. When a regular user login (not system admin), he/she might have very restrictive permissions. The application itself had a user name and password which means applications can directly login into the database and perform the operation. Developers were well aware of the username and password as it was embedded in the application. When developer leaves the organization or when the password was changed, the part of the application had to be changed where the same username and passwords were used. Additionally, developers were able to use the same username and password and login directly to the same application. In earlier version of SQL Server there were application roles. The same is later on replaced by “User without Login”. Now let us recreate the above scenario using this new “User without Login”. In this case, User will have to login using their own credentials into SQL Server. This means that the user who is logged in will have his/her own username and password. Once the login is done in SQL Server, the user will be able to use the application. Now the database should have another User without Login which has all the necessary permissions and rights to execute various operations. Now, Application will be able to execute the script by impersonating “user without login – with more permissions”. Here there is assumed that user login does not have enough permissions and another user (without login) there are more rights. If a user knows how the application is using the database and their various operations, he can switch the context to user without login making him enable for doing further modification. Make sure to explicitly DENY view definition permission on the database. This will make things further difficult for user as he will have to know exact details to get additional permissions. If a user is System Admin all the details which I just mentioned in above three paragraphs does not apply as admin always have access to everything. Additionally, the method describes above is just one of the architecture and if someone is attempting to damage the system, they will still be able to figure out a workaround. You will have to put further auditing and policy based management to prevent such incidents and accidents. I guess this is my answer. I read it multiple times but I still feel that I am missing something. There should be more to this concept than what I have just described. I have merely described one scenario but there will be many more scenarios where this situation will be useful. Now is your turn to help – please leave a comment with the additional suggestion where exactly “User without Login” will be useful as well did I miss anything when I described above scenario. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, T SQL, Technology

    Read the article

  • World Record Siebel PSPP Benchmark on SPARC T4 Servers

    - by Brian
    Oracle's SPARC T4 servers set a new World Record for Oracle's Siebel Platform Sizing and Performance Program (PSPP) benchmark suite. The result used Oracle's Siebel Customer Relationship Management (CRM) Industry Applications Release 8.1.1.4 and Oracle Database 11g Release 2 running Oracle Solaris on three SPARC T4-2 and two SPARC T4-1 servers. The SPARC T4 servers running the Siebel PSPP 8.1.1.4 workload which includes Siebel Call Center and Order Management System demonstrates impressive throughput performance of the SPARC T4 processor by achieving 29,000 users. This is the first Siebel PSPP 8.1.1.4 benchmark supporting 29,000 concurrent users with a rate of 239,748 Business Transactions/hour. The benchmark demonstrates vertical and horizontal scalability of Siebel CRM Release 8.1.1.4 on SPARC T4 servers. Performance Landscape Systems Txn/hr Users Call Center Order Management Response Times (sec) 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – Web 3 x SPARC T4-2 (2 x SPARC T4 2.85 GHz) – App/Gateway 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – DB 239,748 29,000 0.165 0.925 Oracle: Call Center + Order Management Transactions: 197,128 + 42,620 Users: 20300 + 8700 Configuration Summary Web Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 10 8/11 iPlanet Web Server 7 Application Server Configuration: 3 x SPARC T4-2 servers, each with 2 x SPARC T4 processor, 2.85 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 10 8/11 Siebel CRM 8.1.1.5 SIA Database Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.2) Storage Configuration: 1 x Sun Storage F5100 Flash Array 80 x 24 GB flash modules Benchmark Description Siebel 8.1 PSPP benchmark includes Call Center and Order Management: Siebel Financial Services Call Center – Provides the most complete solution for sales and service, allowing customer service and telesales representatives to provide superior customer support, improve customer loyalty, and increase revenues through cross-selling and up-selling. High-level description of the use cases tested: Incoming Call Creates Opportunity, Quote and Order and Incoming Call Creates Service Request . Three complex business transactions are executed simultaneously for specific number of concurrent users. The ratios of these 3 scenarios were 30%, 40%, 30% respectively, which together were totaling 70% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 10, 13, and 35 seconds respectively. Siebel Order Management – Oracle's Siebel Order Management allows employees such as salespeople and call center agents to create and manage quotes and orders through their entire life cycle. Siebel Order Management can be tightly integrated with back-office applications allowing users to perform tasks such as checking credit, confirming availability, and monitoring the fulfillment process. High-level description of the use cases tested: Order & Order Items Creation and Order Updates. Two complex Order Management transactions were executed simultaneously for specific number of concurrent users concurrently with aforementioned three Call Center scenarios above. The ratio of these 2 scenarios was 50% each, which together were totaling 30% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 20 and 67 seconds respectively. Key Points and Best Practices No processor cores or cache were activated or deactivated on the SPARC T-Series systems to achieve special benchmark effects. See Also Siebel White Papers SPARC T4-1 Server oracle.com OTN SPARC T4-2 Server oracle.com OTN Siebel CRM oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 30 September 2012.

    Read the article

  • SQL Server Optimizer Malfunction?

    - by Tony Davis
    There was a sharp intake of breath from the audience when Adam Machanic declared the SQL Server optimizer to be essentially "stuck in 1997". It was during his fascinating "Query Tuning Mastery: Manhandling Parallelism" session at the recent PASS SQL Summit. Paraphrasing somewhat, Adam (blog | @AdamMachanic) offered a convincing argument that the optimizer often delivers flawed plans based on assumptions that are no longer valid with today’s hardware. In 1997, when Microsoft engineers re-designed the database engine for SQL Server 7.0, SQL Server got its initial implementation of a cost-based optimizer. Up to SQL Server 2000, the developer often had to deploy a steady stream of hints in SQL statements to combat the occasionally wilful plan choices made by the optimizer. However, with each successive release, the optimizer has evolved and improved in its decision-making. It is still prone to the occasional stumble when we tackle difficult problems, join large numbers of tables, perform complex aggregations, and so on, but for most of us, most of the time, the optimizer purrs along efficiently in the background. Adam, however, challenged further any assumption that the current optimizer is competent at providing the most efficient plans for our more complex analytical queries, and in particular of offering up correctly parallelized plans. He painted a picture of a present where complex analytical queries have become ever more prevalent; where disk IO is ever faster so that reads from disk come into buffer cache faster than ever; where the improving RAM-to-data ratio means that we have a better chance of finding our data in cache. Most importantly, we have more CPUs at our disposal than ever before. To get these queries to perform, we not only need to have the right indexes, but also to be able to split the data up into subsets and spread its processing evenly across all these available CPUs. Improvements such as support for ColumnStore indexes are taking things in the right direction, but, unfortunately, deficiencies in the current Optimizer mean that SQL Server is yet to be able to exploit properly all those extra CPUs. Adam’s contention was that the current optimizer uses essentially the same costing model for many of its core operations as it did back in the days of SQL Server 7, based on assumptions that are no longer valid. One example he gave was a "slow disk" bias that may have been valid back in 1997 but certainly is not on modern disk systems. Essentially, the optimizer assesses the relative cost of serial versus parallel plans based on the assumption that there is no IO cost benefit from parallelization, only CPU. It assumes that a single request will saturate the IO channel, and so a query would not run any faster if we parallelized IO because the disk system simply wouldn’t be able to handle the extra pressure. As such, the optimizer often decides that a serial plan is lower cost, often in cases where a parallel plan would improve performance dramatically. It was challenging and thought provoking stuff, as were his techniques for driving parallelism through query logic based on subsets of rows that define the "grain" of the query. I highly recommend you catch the session if you missed it. I’m interested to hear though, when and how often people feel the force of the optimizer’s shortcomings. Barring mistakes, such as stale statistics, how often do you feel the Optimizer fails to find the plan you think it should, and what are the most common causes? Is it fighting to induce it toward parallelism? Combating unexpected plans, arising from table partitioning? Something altogether more prosaic? Cheers, Tony.

    Read the article

  • Perm SSIS Developer Urgently Required

    - by blakmk
      Job Role To provide dedicated data services support to the company, by designing, creating, maintaining and enhancing database objects, ensuring data quality, consistency and integrity. Migrating data from various sources to central SQL 2008 data warehouse will be the primary function. Migration of data from bespoke legacy database’s to SQL 2008 data warehouse. Understand key business requirements, Liaising with various aspects of the company. Create advanced transformations of data, with focus on data cleansing, redundant data and duplication. Creating complex business rules regarding data services, migration, Integrity and support (Best Practices). Experience ·         Minimum 3 year SSIS experience, in a project or BI Development role and involvement in at least 3 full ETL project life cycles, using the following methodologies and tools o    Excellent knowledge of ETL concepts including data migration & integrity, focusing on SSIS. o    Extensive experience with SQL 2005 products, SQL 2008 desirable. o    Working knowledge of SSRS and its integration with other BI products. o    Extensive knowledge of T-SQL, stored procedures, triggers (Table/Database), views, functions in particular coding and querying. o    Data cleansing and harmonisation. o    Understanding and knowledge of indexes, statistics and table structure. o    SQL Agent – Scheduling jobs, optimisation, multiple jobs, DTS. o    Troubleshoot, diagnose and tune database and physical server performance. o    Knowledge and understanding of locking, blocks, table and index design and SQL configuration. ·         Demonstrable ability to understand and analyse business processes. ·         Experience in creating business rules on best practices for data services. ·         Experience in working with, supporting and troubleshooting MS SQL servers running enterprise applications ·         Proven ability to work well within a team and liaise with other technical support staff such as networking administrators, system administrators and support engineers. ·         Ability to create formal documentation, work procedures, and service level agreements. ·         Ability to communicate technical issues at all levels including to a non technical audience. ·         Good working knowledge of MS Word, Excel, PowerPoint, Visio and Project.   Location Based in Crawley with possibility of some remote working Contact me for more info: http://sqlblogcasts.com/blogs/blakmk/contact.aspx      

    Read the article

  • Investigating on xVelocity (VertiPaq) column size

    - by Marco Russo (SQLBI)
      In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

    Read the article

  • RAID controller dropping the wrong drive

    - by bramp
    I've been having an issue with 3ware 9500S-8 RAID 10, and I have contracted their tech support, but I wanted to hear the serverfault community's recommendations. Firstly, all my data is backuped and secure, so I don't mind blowing my RAID away if I have to. But let me describe the problem I've been seeing. A month ago, disk 6 dropped out of the RAID. It is mirrored with disk 7, so I wasn't that bothered. I went to the data centre and replaced it. When I got back to the office, I noticed that disk 6 will still not in the RAID, and in fact the controller was show the name of the old drive still. A week later I went back and replace the drive again, thinking I might have swapped in a bad drive. Still the same problem. I decided to reboot the machine, to see if that would "force" the controller into seeing the new drive. It did, and a rebuild started to happen (from disk 7). Eventually both drives were showing as good. A week later, the MySQL database has flagged the database is corrupt, and is unable to repair it. I don't know what has gone wrong, but I suspected this 6-7 pair. At this point I noticed that the RAID had constantly been verifying itself, over and over. Regardless of this I began to rebuild the database, which took about 19 hours. It's a big database. Near the end of the repair, the RAID controller told me it had dropped disk 7, and that some data was most likely corrupted. I contacted LSI tech support, and they very promptly started to help me. I mentioned that drive 7 had been dropped. They suspect that drive 7 was always at fault, and drive 6 had always been good. I want to know how often a RAID controller would drop the wrong drive (in this case dropping drive 6 a month ago, instead of 7). I foolishly didn't run smartctl on the drives before I started swapping them out. I just assumed the RAID controller knew what it was talking about. I think my plan of action is to replace drive 7, rebuild the array from scratch, double check smartctl on ALL the disks, and then start restoring my data again. I would appreciate anyone's input on what the correct procedure for swapping drives is, and how often failures like this happen. If anyone would like more information then I'd be happy to provide it. thanks in advance. Oh some more information. I'm running CentOS 5.3, with two RAID arrays, a simple RAID 1 for the OS, and RAID 10 for the database. Both arrays are on different controllers. The RAID 10 is made of 10 identical ST3640323AS drives, until I swapped in a SAMSUNG HD103SJ last month.

    Read the article

  • What is a good design pattern / lib for iOS 5 to synchronize with a web service?

    - by Junto
    We are developing an iOS application that needs to synchronize with a remote server using web services. The existing web services have an "operations" style rather than REST (implemented in WCF but exposing JSON HTTP endpoints). We are unsure of how to structure the web services to best fit with iOS and would love some advice. We are also interested in how to manage the synchronization process within iOS. Without going into detailed specifics, the application allows the user to estimate repair costs at a remote site. These costs are broken down by room and item. If the user has an internet connection this data can be sent back to the server. Multiple photographs can be taken of each item, but they will be held in a separate queue, which sends when the connection is optimal (ideally wifi). Our backend application controls the unique ids for each room and item. Thus, each time we send these costs to the server, the server echoes the central database ids back, thus, that they can be synchronized in the mobile app. I have simplified this a little, since the operations contract is actually much larger, but I just want to illustrate the basic requirements without complicating matters. Firstly, the web service architecture: We currently have two operations: GetCosts and UpdateCosts. My assumption is that if we used a strict REST architecture we would need to break our single web service operations into multiple smaller services. This would make the services much more chatty and we would also have to guarantee a delivery order from the app. For example, we need to make sure that containing rooms are added before the item. Although this seems much more RESTful, our perception is that these extra calls are expensive connections (security checks, database calls, etc). Does the type of web api (operation over service focus) determine chunky vs chatty? Since this is mobile (3G), are we better handling lots of smaller messages, or a few large ones? Secondly, the iOS side. What is the current advice on how to manage data synchronization within the iOS (5) app itself. We need multiple queues and we need to guarantee delivery order in each queue (and technically, ordering between queues). The server needs to control unique ids and other properties and echo them back to the application. The application then needs to update an internal database and when re-updating, make sure the correct ids are available in the update message (essentially multiple inserts and updates in one call). Our backend has a ton of business logic operating on these cost estimates. We don't want any of this in the app itself. Currently the iOS app sends the cost data, and then the server echoes that data back with populated ids (and other data). The existing cost data is deleted and the echoed response data is added to the client database on the device. This is causing us problems, because any photos might not have been sent, but the original entity tree has been removed and replaced. Obviously updating the costs tree rather than replacing it would remove this problem, but I'm not sure if there are any nice xcode libraries out there to do such things. I welcome any advice you might have.

    Read the article

  • Would this be a good web application architecture?

    - by Gustav Bertram
    My problem Our MVC based framework does not allow us to cache only part of our output. Ideally we want to cahce static and semi-static bits, and run dynamic bits. In addition, we need to consider data caching that reacts to database changes. My idea The concept I came up with was to represent a page as a tree of XML fragment objects. (I say XML, but I mean XHTML). Some of the fragments are dynamic, and can pull their data directly from models or other sources, but most of the fragments are static scaffolding. If a subtree of fragments is completely static, then I imagine that they could unfold into pure XML that would then be cached as the text representation of their parent element. This process would ideally continue until we are left with a root element that contains all of the static XML, and has a couple of dynamic XML fragments that are resolved and attached to the relevant nodes of the XML tree just before the page is displayed. In addition to separating content into dynamic and static fragments, some fragments could be dynamic and cached. A simple expiry time which propagates up through the XML fragment tree would indicate that a specific fragment should periodically be refreshed. A newspaper section or front page does not need to be updated each second. Minutes or sometimes even longer is sufficient. Other fragments would be dynamic and uncached. Typically too many articles are viewed for them to be cached - the cache would overflow. Some individual articles may be cached if they are extremely popular. Functional notes The folding mechanism could be to be smart enough to judge when it would be more profitable to fold a dynamic cached fragment and propagate the expiry date to the parent fragment, or to keep it separate and simple attach to the XML tree when resolving the page. If some dynamic cached fragments are associated to database objects through mechanisms like a globally unique content id, then changes to the database could trigger changes to the output cache. If fragments store the identifiers of parent fragments, then they could trigger a refolding process that would then include the updated data. A set of pure XML with an ordered array of fragment objects (that each store the identifying information of the node to which they should be attached), can be resolved in a fairly simple way by walking the XML tree, and merging the data from the fragments. Because it is not necessary to parse and construct the entire tree in memory before attaching nodes, processing should be fairly fast. The identifiers of each fragment would be a combination of relevant identity data and the type of fragment object. Cached parent fragments would contain references to these identifiers, in order to then either pull them from the fragment cache, or to run their code. The controller's responsibility is reduced to making changes to the database, and telling the root XML fragment object to render itself. The Question My question has two parts: Is this a good design? Are there any obvious flaws I'm missing? Has somebody else thought of this before? References? Is there an existing alternative that I should consider? A cool templating engine maybe?

    Read the article

  • Certify September Updates

    - by Sadia2
    We have added some release and platform certifications to MOS Certify. Applications: Oracle Demantra 12.2.2, 7.3.1.5, 7.3.1.4, 7.3.0.2.0, 7.3.0.0.0 Collaboration Technologies: Oracle Beehive 2.0.1.8.0 Database: Oracle Database Client 12.1.0.1.0, Oracle Clusterware 11.2.0.4.0, Oracle Database 11.2.0.4.0, Oracle Real Application Clusters 11.2.0.4.0 E-Business Suite: Oracle E-Business Suite 12.2.2, 12.1.3, 12.1.2, 12.1.1, 12.0.6, 11.5.10.2 Edge Applications: Oracle AutoVue 20.2.2, 20.2.1, 20.2.0 Enterprise Manager: Enterprise Manager Base Platform - OMS 12.1.0.3.0, Oracle Real User Experience Insight 12.1.0.4.0, 12.1.0.3.0, 12.1.0.1, 11.1 FSGBU Insurance Group: Oracle Health Insurance Claims 2.13.3.0.0 Fusion Middleware: Oracle Business Intelligence Applications 11.1.1.7.1, 7.9.6.4.0, Oracle Discoverer 11.1.1.6.0, Discoverer Administrator 11.1.1.6.0, Discoverer Desktop 11.1.1.6.0, Oracle JDK 1.7.0_40, 1.7.0_25", Oracle JRE 1.7.0_40, 1.7.0_25, Oracle JRockit 6u45 R28.2.7+, Oracle WebCenter Sites 11.1.1.8.0, Oracle WebCenter Sites: Community-Gadgets 11.1.1.8.0, Oracle WebCenter Sites: CIP for File Systems and MS SharePoint 11.1.1.8.0, Oracle WebCenter Sites: CIP for EMC Documentum 11.1.1.8.0 JD Edwards EnterpriseOne: JD Edwards EnterpriseOne Business Services Server 9.1.3.0, 9.1.2.0, 9.1.0.0, JD Edwards EnterpriseOne Mobile Applications 9.1.2.0 Oracle Fusion Applications: Oracle Fusion Applications 11.1.7.0.0 Primavera GBU: Primavera Unifier 9.13.0.0 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Siebel Enterprise: Siebel Application Server 8.2.2.4.0, 8.2.2.3.0, 8.2.2.2.0, 8.1.1.10.0, 8.1.1.9.0, Siebel Database Server 8.2.2.3.0, 8.1.1.10.0, 8.1.1.9.0, Siebel Remote Client 8.2.2.4.0, 8.2.2.3.0, 8.2.2.2.0, 8.1.1.11.0, 8.1.1.10.0, 8.1.1.9.0, Siebel Tools Client 8.2.2.4.0, 8.2.2.2.0, 8.1.1.11.0, 8.1.1.9.0, Siebel SSO Integration 8.2.2.4.0, 8.2.2.3.0, 8.2.2.2.0, 8.1.1.11.0, 8.1.1.10.0, 8.1.1.9.0

    Read the article

  • Investigating on xVelocity (VertiPaq) column size

    - by Marco Russo (SQLBI)
      In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

    Read the article

  • MySQL, An Ideal Choice for The Cloud

    - by Bertrand Matthelié
    As the world's most popular web database, MySQL has quickly become the leading database for the cloud, with most providers offering MySQL-based services. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Access our Resource Kit to discover: Why MySQL has become the leading database in the cloud, and how it addresses the critical attributes of cloud-based deployments How ISVs rely on MySQL to power their SaaS offerings Best practices to deploy the world’s most popular open source database in public and private clouds Normal 0 false false false EN-US X-NONE X-NONE You will also find out how you can leverage MySQL together with Hadoop and other technologies to unlock the value of Big Data, either on-premise or in the cloud. Access white papers, webinars, case studies and other resources in /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} our Resource Kit now!

    Read the article

< Previous Page | 454 455 456 457 458 459 460 461 462 463 464 465  | Next Page >