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  • Quartz.Net Windows Service Configure Logging

    - by Tarun Arora
    In this blog post I’ll be covering, Logging for Quartz.Net Windows Service 01 – Why doesn’t Quartz.Net Windows Service log by default 02 – Configuring Quartz.Net windows service for logging to eventlog, file, console, etc 03 – Results: Logging in action If you are new to Quartz.Net I would recommend going through, A brief Introduction to Quartz.net Walkthrough of Installing & Testing Quartz.Net as a Windows Service Writing & Scheduling your First HelloWorld job with Quartz.Net   01 – Why doesn’t Quartz.Net Windows Service log by default If you are trying to figure out why… The Quartz.Net windows service isn’t logging The Quartz.Net windows service isn’t writing anything to the event log The Quartz.Net windows service isn’t writing anything to a file How do I configure Quartz.Net windows service to use log4Net How do I change the level of logging for Quartz.Net Look no further, This blog post should help you answer these questions. Quartz.NET uses the Common.Logging framework for all of its logging needs. If you navigate to the directory where Quartz.Net Windows Service is installed (I have the service installed in C:\Program Files (x86)\Quartz.net, you can find out the location by looking at the properties of the service) and open ‘Quartz.Server.exe.config’ you’ll see that the Quartz.Net is already set up for logging to ConsoleAppender and EventLogAppender, but only ‘ConsoleAppender’ is set up as active. So, unless you have the console associated to the Quartz.Net service you won’t be able to see any logging. <log4net> <appender name="ConsoleAppender" type="log4net.Appender.ConsoleAppender"> <layout type="log4net.Layout.PatternLayout"> <conversionPattern value="%d [%t] %-5p %l - %m%n" /> </layout> </appender> <appender name="EventLogAppender" type="log4net.Appender.EventLogAppender"> <layout type="log4net.Layout.PatternLayout"> <conversionPattern value="%d [%t] %-5p %l - %m%n" /> </layout> </appender> <root> <level value="INFO" /> <appender-ref ref="ConsoleAppender" /> <!-- uncomment to enable event log appending --> <!-- <appender-ref ref="EventLogAppender" /> --> </root> </log4net> Problem: In the configuration above Quartz.Net Windows Service only has ConsoleAppender active. So, no logging will be done to EventLog. More over the RollingFileAppender isn’t setup at all. So, Quartz.Net will not log to an application trace log file. 02 – Configuring Quartz.Net windows service for logging to eventlog, file, console, etc Let’s change this behaviour by changing the config file… In the below config file, I have added the RollingFileAppender. This will configure Quartz.Net service to write to a log file. (<appender name="GeneralLog" type="log4net.Appender.RollingFileAppender">) I have specified the location for the log file (<arg key="configFile" value="Trace/application.log.txt"/>) I have enabled the EventLogAppender and RollingFileAppender to be written to by Quartz. Net windows service Changed the default level of logging from ‘Info’ to ‘All’. This means all activity performed by Quartz.Net Windows service will be logged. You might want to tune this back to ‘Debug’ or ‘Info’ later as logging ‘All’ will produce too much data to the logs. (<level value="ALL"/>) Since I have changed the logging level to ‘All’, I have added applicationSetting to remove logging log4Net internal debugging. (<add key="log4net.Internal.Debug" value="false"/>) <?xml version="1.0" encoding="utf-8" ?> <configuration> <configSections> <section name="quartz" type="System.Configuration.NameValueSectionHandler, System, Version=1.0.5000.0,Culture=neutral, PublicKeyToken=b77a5c561934e089" /> <section name="log4net" type="log4net.Config.Log4NetConfigurationSectionHandler, log4net" /> <sectionGroup name="common"> <section name="logging" type="Common.Logging.ConfigurationSectionHandler, Common.Logging" /> </sectionGroup> </configSections> <common> <logging> <factoryAdapter type="Common.Logging.Log4Net.Log4NetLoggerFactoryAdapter, Common.Logging.Log4net"> <arg key="configType" value="INLINE" /> <arg key="configFile" value="Trace/application.log.txt"/> <arg key="level" value="ALL" /> </factoryAdapter> </logging> </common> <appSettings> <add key="log4net.Internal.Debug" value="false"/> </appSettings> <log4net> <appender name="ConsoleAppender" type="log4net.Appender.ConsoleAppender"> <layout type="log4net.Layout.PatternLayout"> <conversionPattern value="%d [%t] %-5p %l - %m%n" /> </layout> </appender> <appender name="EventLogAppender" type="log4net.Appender.EventLogAppender"> <layout type="log4net.Layout.PatternLayout"> <conversionPattern value="%d [%t] %-5p %l - %m%n" /> </layout> </appender> <appender name="GeneralLog" type="log4net.Appender.RollingFileAppender"> <file value="Trace/application.log.txt"/> <appendToFile value="true"/> <maximumFileSize value="1024KB"/> <rollingStyle value="Size"/> <layout type="log4net.Layout.PatternLayout"> <conversionPattern value="%d{HH:mm:ss} [%t] %-5p %c - %m%n"/> </layout> </appender> <root> <level value="ALL" /> <appender-ref ref="ConsoleAppender" /> <appender-ref ref="EventLogAppender" /> <appender-ref ref="GeneralLog"/> </root> </log4net> </configuration>   Note – Please ensure you restart the Quartz.Net Windows service for the config changes to be picked up by the service   03 – Results: Logging in action Once you start the Quartz.Net Windows Service up, the logging should be initiated to write all activities in the Console, EventLog and File… See screen shots below… Figure – Quartz.Net Windows Service logging all activity to the event log Figure – Quartz.Net Windows Service logging all activity to the application log file Where is the output from log4Net ConsoleAppender? As a default behaviour, the console isn't available in windows services, web services, windows forms. The output will simply be dismissed. Unless you are running the process interactively. Which you can do by firing up Quartz.Server.exe –i to see the output   This was fourth in the series of posts on enterprise scheduling using Quartz.net, in the next post I’ll be covering troubleshooting why a scheduled task hasn’t fired on Quartz.net windows service. All Quartz.Net specific blog posts can listed here. Thank you for taking the time out and reading this blog post. If you enjoyed the post, remember to subscribe to http://feeds.feedburner.com/TarunArora. Stay tuned!

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  • Wireless Networking 802.11n

    It';s been years in development but this September it looks like 802.11n Wi-Fi will finally become a standard... well, an official standard anyway. Presently the majority of the wireless hardware you... [Author: Chris Holgate - Computers and Internet - April 08, 2010]

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  • Errors trying to run MongoDB

    - by SomeKittens
    I'm running Ubuntu Server 12.04 (32 bit) on an old (1998) computer. Everything's working fine until I try and start MongoDB. somekittens@DLserver01:~$ mongo MongoDB shell version: 2.2.2 connecting to: test Sun Dec 16 22:47:50 Error: couldn't connect to server 127.0.0.1:27017 src/mongo/shell/mongo.js:91 exception: connect failed Googling the error lead me to all sorts of "repair" options, none of which fixed anything. I've also removed MongoDB and installed it again (using apt-get, have not built from source). Mongo's log shows the following error: Thu Dec 13 18:36:32 warning: 32-bit servers don't have journaling enabled by default. Please use --journal if you want durability. Thu Dec 13 18:36:32 Thu Dec 13 18:36:32 [initandlisten] MongoDB starting : pid=758 port=27017 dbpath=/var/lib/mongodb 32-bit host=DLserver01 Thu Dec 13 18:36:32 [initandlisten] Thu Dec 13 18:36:32 [initandlisten] ** NOTE: when using MongoDB 32 bit, you are limited to about 2 gigabytes of data Thu Dec 13 18:36:32 [initandlisten] ** see http://blog.mongodb.org/post/137788967/32-bit-limitations Thu Dec 13 18:36:32 [initandlisten] ** with --journal, the limit is lower Thu Dec 13 18:36:32 [initandlisten] Thu Dec 13 18:36:32 [initandlisten] db version v2.2.2, pdfile version 4.5 Thu Dec 13 18:36:32 [initandlisten] git version: d1b43b61a5308c4ad0679d34b262c5af9d664267 Thu Dec 13 18:36:32 [initandlisten] build info: Linux domU-12-31-39-01-70-B4 2.6.21.7-2.fc8xen #1 SMP Fri Feb 15 12:39:36 EST 2008 i686 BOOST_LIB_VERSION=1_49 Thu Dec 13 18:36:32 [initandlisten] options: { config: "/etc/mongodb.conf", dbpath: "/var/lib/mongodb", logappend: "true", logpath: "/var/log/mongodb/mongodb.log" } Thu Dec 13 18:36:32 [initandlisten] Unable to check for journal files due to: boost::filesystem::basic_directory_iterator constructor: No such file or directory: "/var/lib/mongodb/journal" ************** Unclean shutdown detected. Please visit http://dochub.mongodb.org/core/repair for recovery instructions. ************* Thu Dec 13 18:36:32 [initandlisten] exception in initAndListen: 12596 old lock file, terminating Thu Dec 13 18:36:32 dbexit: Thu Dec 13 18:36:32 [initandlisten] shutdown: going to close listening sockets... Thu Dec 13 18:36:32 [initandlisten] shutdown: going to flush diaglog... Thu Dec 13 18:36:32 [initandlisten] shutdown: going to close sockets... Thu Dec 13 18:36:32 [initandlisten] shutdown: waiting for fs preallocator... Thu Dec 13 18:36:32 [initandlisten] shutdown: closing all files... Thu Dec 13 18:36:32 [initandlisten] closeAllFiles() finished Thu Dec 13 18:36:32 dbexit: really exiting now Running through the recovery instructions lead to the following adventure: somekittens@DLserver01:/var/log/mongodb$ mongod --repair Sun Dec 16 22:42:54 Sun Dec 16 22:42:54 warning: 32-bit servers don't have journaling enabled by default. Please use --journal if you want durability. Sun Dec 16 22:42:54 Sun Dec 16 22:42:54 [initandlisten] MongoDB starting : pid=1887 port=27017 dbpath=/data/db/ 32-bit host=DLserver01 Sun Dec 16 22:42:54 [initandlisten] Sun Dec 16 22:42:54 [initandlisten] ** NOTE: when using MongoDB 32 bit, you are limited to about 2 gigabytes of data Sun Dec 16 22:42:54 [initandlisten] ** see http://blog.mongodb.org/post/137788967/32-bit-limitations Sun Dec 16 22:42:54 [initandlisten] ** with --journal, the limit is lower Sun Dec 16 22:42:54 [initandlisten] Sun Dec 16 22:42:54 [initandlisten] db version v2.2.2, pdfile version 4.5 Sun Dec 16 22:42:54 [initandlisten] git version: d1b43b61a5308c4ad0679d34b262c5af9d664267 Sun Dec 16 22:42:54 [initandlisten] build info: Linux domU-12-31-39-01-70-B4 2.6.21.7-2.fc8xen #1 SMP Fri Feb 15 12:39:36 EST 2008 i686 BOOST_LIB_VERSION=1_49 Sun Dec 16 22:42:54 [initandlisten] options: { repair: true } Sun Dec 16 22:42:54 [initandlisten] exception in initAndListen: 10296 ********************************************************************* ERROR: dbpath (/data/db/) does not exist. Create this directory or give existing directory in --dbpath. See http://dochub.mongodb.org/core/startingandstoppingmongo ********************************************************************* , terminating Sun Dec 16 22:42:54 dbexit: Sun Dec 16 22:42:54 [initandlisten] shutdown: going to close listening sockets... Sun Dec 16 22:42:54 [initandlisten] shutdown: going to flush diaglog... Sun Dec 16 22:42:54 [initandlisten] shutdown: going to close sockets... Sun Dec 16 22:42:54 [initandlisten] shutdown: waiting for fs preallocator... Sun Dec 16 22:42:54 [initandlisten] shutdown: closing all files... Sun Dec 16 22:42:54 [initandlisten] closeAllFiles() finished Sun Dec 16 22:42:54 dbexit: really exiting now somekittens@DLserver01:/var/log/mongodb$ sudo mkdir /data somekittens@DLserver01:/var/log/mongodb$ sudo mkdir /data/db somekittens@DLserver01:/var/log/mongodb$ mongod --repair Sun Dec 16 22:43:51 Sun Dec 16 22:43:51 warning: 32-bit servers don't have journaling enabled by default. Please use --journal if you want durability. Sun Dec 16 22:43:51 Sun Dec 16 22:43:51 [initandlisten] MongoDB starting : pid=1909 port=27017 dbpath=/data/db/ 32-bit host=DLserver01 Sun Dec 16 22:43:51 [initandlisten] Sun Dec 16 22:43:51 [initandlisten] ** NOTE: when using MongoDB 32 bit, you are limited to about 2 gigabytes of data Sun Dec 16 22:43:51 [initandlisten] ** see http://blog.mongodb.org/post/137788967/32-bit-limitations Sun Dec 16 22:43:51 [initandlisten] ** with --journal, the limit is lower Sun Dec 16 22:43:51 [initandlisten] Sun Dec 16 22:43:51 [initandlisten] db version v2.2.2, pdfile version 4.5 Sun Dec 16 22:43:51 [initandlisten] git version: d1b43b61a5308c4ad0679d34b262c5af9d664267 Sun Dec 16 22:43:51 [initandlisten] build info: Linux domU-12-31-39-01-70-B4 2.6.21.7-2.fc8xen #1 SMP Fri Feb 15 12:39:36 EST 2008 i686 BOOST_LIB_VERSION=1_49 Sun Dec 16 22:43:51 [initandlisten] options: { repair: true } Sun Dec 16 22:43:51 [initandlisten] exception in initAndListen: 10309 Unable to create/open lock file: /data/db/mongod.lock errno:13 Permission denied Is a mongod instance already running?, terminating Sun Dec 16 22:43:51 dbexit: Sun Dec 16 22:43:51 [initandlisten] shutdown: going to close listening sockets... Sun Dec 16 22:43:51 [initandlisten] shutdown: going to flush diaglog... Sun Dec 16 22:43:51 [initandlisten] shutdown: going to close sockets... Sun Dec 16 22:43:51 [initandlisten] shutdown: waiting for fs preallocator... Sun Dec 16 22:43:51 [initandlisten] shutdown: closing all files... Sun Dec 16 22:43:51 [initandlisten] closeAllFiles() finished Sun Dec 16 22:43:51 [initandlisten] shutdown: removing fs lock... Sun Dec 16 22:43:51 [initandlisten] couldn't remove fs lock errno:9 Bad file descriptor Sun Dec 16 22:43:51 dbexit: really exiting now somekittens@DLserver01:/var/log/mongodb$ service mongodb stop stop: Unknown instance: somekittens@DLserver01:/var/log/mongodb$ sudo mongod --repair Sun Dec 16 22:45:04 Sun Dec 16 22:45:04 warning: 32-bit servers don't have journaling enabled by default. Please use --journal if you want durability. Sun Dec 16 22:45:04 Sun Dec 16 22:45:04 [initandlisten] MongoDB starting : pid=1921 port=27017 dbpath=/data/db/ 32-bit host=DLserver01 Sun Dec 16 22:45:04 [initandlisten] Sun Dec 16 22:45:04 [initandlisten] ** NOTE: when using MongoDB 32 bit, you are limited to about 2 gigabytes of data Sun Dec 16 22:45:04 [initandlisten] ** see http://blog.mongodb.org/post/137788967/32-bit-limitations Sun Dec 16 22:45:04 [initandlisten] ** with --journal, the limit is lower Sun Dec 16 22:45:04 [initandlisten] Sun Dec 16 22:45:04 [initandlisten] db version v2.2.2, pdfile version 4.5 Sun Dec 16 22:45:04 [initandlisten] git version: d1b43b61a5308c4ad0679d34b262c5af9d664267 Sun Dec 16 22:45:04 [initandlisten] build info: Linux domU-12-31-39-01-70-B4 2.6.21.7-2.fc8xen #1 SMP Fri Feb 15 12:39:36 EST 2008 i686 BOOST_LIB_VERSION=1_49 Sun Dec 16 22:45:04 [initandlisten] options: { repair: true } Sun Dec 16 22:45:04 [initandlisten] Unable to check for journal files due to: boost::filesystem::basic_directory_iterator constructor: No such file or directory: "/data/db/journal" Sun Dec 16 22:45:04 [initandlisten] finished checking dbs Sun Dec 16 22:45:04 dbexit: Sun Dec 16 22:45:04 [initandlisten] shutdown: going to close listening sockets... Sun Dec 16 22:45:04 [initandlisten] shutdown: going to flush diaglog... Sun Dec 16 22:45:04 [initandlisten] shutdown: going to close sockets... Sun Dec 16 22:45:04 [initandlisten] shutdown: waiting for fs preallocator... Sun Dec 16 22:45:04 [initandlisten] shutdown: closing all files... Sun Dec 16 22:45:04 [initandlisten] closeAllFiles() finished Sun Dec 16 22:45:04 [initandlisten] shutdown: removing fs lock... Sun Dec 16 22:45:04 dbexit: really exiting now Which didn't change anything. What can I do to resolve this? It's an old computer (640MB RAM, single-core P2). Could that be causing it?

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  • ASP.NET and WIF: Showing custom profile username as User.Identity.Name

    - by DigiMortal
    I am building ASP.NET MVC application that uses external services to authenticate users. For ASP.NET users are fully authenticated when they are redirected back from external service. In system they are logically authenticated when they have created user profiles. In this posting I will show you how to force ASP.NET MVC controller actions to demand existence of custom user profiles. Using external authentication sources with AppFabric Suppose you want to be user-friendly and you don’t force users to keep in mind another username/password when they visit your site. You can accept logins from different popular sites like Windows Live, Facebook, Yahoo, Google and many more. If user has account in some of these services then he or she can use his or her account to log in to your site. If you have community site then you usually have support for user profiles too. Some of these providers give you some information about users and other don’t. So only thing in common you get from all those providers is some unique ID that identifies user in service uniquely. Image above shows you how new user joins your site. Existing users who already have profile are directed to users homepage after they are authenticated. You can read more about how to solve semi-authorized users problem from my blog posting ASP.NET MVC: Using ProfileRequiredAttribute to restrict access to pages. The other problem is related to usernames that we don’t get from all identity providers. Why is IIdentity.Name sometimes empty? The problem is described more specifically in my blog posting Identifying AppFabric Access Control Service users uniquely. Shortly the problem is that not all providers have claim called http://schemas.xmlsoap.org/ws/2005/05/identity/claims/name. The following diagram illustrates what happens when user got token from AppFabric ACS and was redirected to your site. Now, when user was authenticated using Windows Live ID then we don’t have name claim in token and that’s why User.Identity.Name is empty. Okay, we can force nameidentifier to be used as name (we can do it in web.config file) but we have user profiles and we want username from profile to be shown when username is asked. Modifying name claim Now let’s force IClaimsIdentity to use username from our user profiles. You can read more about my profiles topic from my blog posting ASP.NET MVC: Using ProfileRequiredAttribute to restrict access to pages and you can find some useful extension methods for claims identity from my blog posting Identifying AppFabric Access Control Service users uniquely. Here is what we do to set User.Identity.Name: we will check if user has profile, if user has profile we will check if User.Identity.Name matches the name given by profile, if names does not match then probably identity provider returned some name for user, we will remove name claim and recreate it with correct username, we will add new name claim to claims collection. All this stuff happens in Application_AuthorizeRequest event of our web application. The code is here. protected void Application_AuthorizeRequest() {     if (string.IsNullOrEmpty(User.Identity.Name))     {         var identity = User.Identity;         var profile = identity.GetProfile();         if (profile != null)         {             if (profile.UserName != identity.Name)             {                 identity.RemoveName();                   var claim = new Claim("http://schemas.xmlsoap.org/ws/2005/05/identity/claims/name", profile.UserName);                 var claimsIdentity = (IClaimsIdentity)identity;                 claimsIdentity.Claims.Add(claim);             }         }     } } RemoveName extension method is simple – it looks for name claims of IClaimsIdentity claims collection and removes them. public static void RemoveName(this IIdentity identity) {     if (identity == null)         return;       var claimsIndentity = identity as ClaimsIdentity;     if (claimsIndentity == null)         return;       for (var i = claimsIndentity.Claims.Count - 1; i >= 0; i--)     {         var claim = claimsIndentity.Claims[i];         if (claim.ClaimType == "http://schemas.xmlsoap.org/ws/2005/05/identity/claims/name")             claimsIndentity.Claims.RemoveAt(i);     } } And we are done. Now User.Identity.Name returns the username from user profile and you can use it to show username of current user everywhere in your site. Conclusion Mixing AppFabric Access Control Service and Windows Identity Foundation with custom authorization logic is not impossible but a little bit tricky. This posting finishes my little series about AppFabric ACS and WIF for this time and hopefully you found some useful tricks, tips, hacks and code pieces you can use in your own applications.

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  • Validating a linked item&rsquo;s data template in Sitecore

    - by Kyle Burns
    I’ve been doing quite a bit of work in Sitecore recently and last week I encountered a situation that it appears many others have hit.  I was working with a field that had been configured originally as a grouped droplink, but now needed to be updated to support additional levels of hierarchy in the folder structure.  If you’ve done any work in Sitecore that statement makes sense, but if not it may seem a bit cryptic.  Sitecore offers a number of different field types and a subset of these field types focus on providing links either to other items on the content tree or to content that is not stored in Sitecore.  In the case of the grouped droplink, the field is configured with a “root” folder and each direct descendant of this folder is considered to be a header for a grouping of other items and displayed in a dropdown.  A picture is worth a thousand words, so consider the following piece of a content tree: If I configure a grouped droplink field to use the “Current” folder as its datasource, the control that gets to my content author looks like this: This presents a nicely organized display and limits the user to selecting only the direct grandchildren of the folder root.  It also presents the limitation that struck as we were thinking through the content architecture and how it would hold up over time – the authors cannot further organize content under the root folder because of the structure required for the dropdown to work.  Over time, not allowing the hierarchy to go any deeper would prevent out authors from being able to organize their content in a way that it would be found when needed, so the grouped droplink data type was not going to fit the bill. I needed to look for an alternative data type that allowed for selection of a single item and limited my choices to descendants of a specific node on the content tree.  After looking at the options available for links in Sitecore and considering them against each other, one option stood out as nearly perfect – the droptree.  This field type stores its data identically to the droplink and allows for the selection of zero or one items under a specific node in the content tree.  By changing my data template to use droptree instead of grouped droplink, the author is now presented with the following when selecting a linked item: Sounds great, but a did say almost perfect – there’s still one flaw.  The code intended to display the linked item is expecting the selection to use a specific data template (or more precisely it makes certain assumptions about the fields that will be present), but the droptree does nothing to prevent the author from selecting a folder (since folders are items too) instead of one of the items contained within a folder.  I looked to see if anyone had already solved this problem.  I found many people discussing the problem, but the closest that I found to a solution was the statement “the best thing would probably be to create a custom validator” with no further discussion in regards to what this validator might look like.  I needed to create my own validator to ensure that the user had not selected a folder.  Since so many people had the same issue, I decided to make the validator as reusable as possible and share it here. The validator that I created inherits from StandardValidator.  In order to make the validator more intuitive to developers that are familiar with the TreeList controls in Sitecore, I chose to implement the following parameters: ExcludeTemplatesForSelection – serves as a “deny list”.  If the data template of the selected item is in this list it will not validate IncludeTemplatesForSelection – this can either be empty to indicate that any template not contained in the exclusion list is acceptable or it can contain the list of acceptable templates Now that I’ve explained the parameters and the purpose of the validator, I’ll let the code do the rest of the talking: 1: /// <summary> 2: /// Validates that a link field value meets template requirements 3: /// specified using the following parameters: 4: /// - ExcludeTemplatesForSelection: If present, the item being 5: /// based on an excluded template will cause validation to fail. 6: /// - IncludeTemplatesForSelection: If present, the item not being 7: /// based on an included template will cause validation to fail 8: /// 9: /// ExcludeTemplatesForSelection trumps IncludeTemplatesForSelection 10: /// if the same value appears in both lists. Lists are comma seperated 11: /// </summary> 12: [Serializable] 13: public class LinkItemTemplateValidator : StandardValidator 14: { 15: public LinkItemTemplateValidator() 16: { 17: } 18:   19: /// <summary> 20: /// Serialization constructor is required by the runtime 21: /// </summary> 22: /// <param name="info"></param> 23: /// <param name="context"></param> 24: public LinkItemTemplateValidator(SerializationInfo info, StreamingContext context) : base(info, context) { } 25:   26: /// <summary> 27: /// Returns whether the linked item meets the template 28: /// constraints specified in the parameters 29: /// </summary> 30: /// <returns> 31: /// The result of the evaluation. 32: /// </returns> 33: protected override ValidatorResult Evaluate() 34: { 35: if (string.IsNullOrWhiteSpace(ControlValidationValue)) 36: { 37: return ValidatorResult.Valid; // let "required" validation handle 38: } 39:   40: var excludeString = Parameters["ExcludeTemplatesForSelection"]; 41: var includeString = Parameters["IncludeTemplatesForSelection"]; 42: if (string.IsNullOrWhiteSpace(excludeString) && string.IsNullOrWhiteSpace(includeString)) 43: { 44: return ValidatorResult.Valid; // "allow anything" if no params 45: } 46:   47: Guid linkedItemGuid; 48: if (!Guid.TryParse(ControlValidationValue, out linkedItemGuid)) 49: { 50: return ValidatorResult.Valid; // probably put validator on wrong field 51: } 52:   53: var item = GetItem(); 54: var linkedItem = item.Database.GetItem(new ID(linkedItemGuid)); 55:   56: if (linkedItem == null) 57: { 58: return ValidatorResult.Valid; // this validator isn't for broken links 59: } 60:   61: var exclusionList = (excludeString ?? string.Empty).Split(','); 62: var inclusionList = (includeString ?? string.Empty).Split(','); 63:   64: if ((inclusionList.Length == 0 || inclusionList.Contains(linkedItem.TemplateName)) 65: && !exclusionList.Contains(linkedItem.TemplateName)) 66: { 67: return ValidatorResult.Valid; 68: } 69:   70: Text = GetText("The field \"{0}\" specifies an item which is based on template \"{1}\". This template is not valid for selection", GetFieldDisplayName(), linkedItem.TemplateName); 71:   72: return GetFailedResult(ValidatorResult.FatalError); 73: } 74:   75: protected override ValidatorResult GetMaxValidatorResult() 76: { 77: return ValidatorResult.FatalError; 78: } 79:   80: public override string Name 81: { 82: get { return @"LinkItemTemplateValidator"; } 83: } 84: }   In this blog entry, I have shared some code that I found useful in solving a problem that seemed fairly common.  Hopefully the next person that is looking for this answer finds it useful as well.

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  • Aluminum Laptop Cases vs Leather Laptop Cases

    Both aluminum and leather have been known for their excellent qualities in the world of business, travel and even fashion; but when it comes to choosing one, there are certain qualities that put alum... [Author: Shannon Hilson - Computers and Internet - March 23, 2010]

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  • SQL SERVER – Shrinking Database is Bad – Increases Fragmentation – Reduces Performance

    - by pinaldave
    Earlier, I had written two articles related to Shrinking Database. I wrote about why Shrinking Database is not good. SQL SERVER – SHRINKDATABASE For Every Database in the SQL Server SQL SERVER – What the Business Says Is Not What the Business Wants I received many comments on Why Database Shrinking is bad. Today we will go over a very interesting example that I have created for the same. Here are the quick steps of the example. Create a test database Create two tables and populate with data Check the size of both the tables Size of database is very low Check the Fragmentation of one table Fragmentation will be very low Truncate another table Check the size of the table Check the fragmentation of the one table Fragmentation will be very low SHRINK Database Check the size of the table Check the fragmentation of the one table Fragmentation will be very HIGH REBUILD index on one table Check the size of the table Size of database is very HIGH Check the fragmentation of the one table Fragmentation will be very low Here is the script for the same. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO Let us check the table size and fragmentation. Now let us TRUNCATE the table and check the size and Fragmentation. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can clearly see that after TRUNCATE, the size of the database is not reduced and it is still the same as before TRUNCATE operation. After the Shrinking database operation, we were able to reduce the size of the database. If you notice the fragmentation, it is considerably high. The major problem with the Shrink operation is that it increases fragmentation of the database to very high value. Higher fragmentation reduces the performance of the database as reading from that particular table becomes very expensive. One of the ways to reduce the fragmentation is to rebuild index on the database. Let us rebuild the index and observe fragmentation and database size. -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REBUILD GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can notice that after rebuilding, Fragmentation reduces to a very low value (almost same to original value); however the database size increases way higher than the original. Before rebuilding, the size of the database was 5 MB, and after rebuilding, it is around 20 MB. Regular rebuilding the index is rebuild in the same user database where the index is placed. This usually increases the size of the database. Look at irony of the Shrinking database. One person shrinks the database to gain space (thinking it will help performance), which leads to increase in fragmentation (reducing performance). To reduce the fragmentation, one rebuilds index, which leads to size of the database to increase way more than the original size of the database (before shrinking). Well, by Shrinking, one did not gain what he was looking for usually. Rebuild indexing is not the best suggestion as that will create database grow again. I have always remembered the excellent post from Paul Randal regarding Shrinking the database is bad. I suggest every one to read that for accuracy and interesting conversation. Let us run following script where we Shrink the database and REORGANIZE. -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Shrink the Database DBCC SHRINKDATABASE (ShrinkIsBed); GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REORGANIZE GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can see that REORGANIZE does not increase the size of the database or remove the fragmentation. Again, I no way suggest that REORGANIZE is the solution over here. This is purely observation using demo. Read the blog post of Paul Randal. Following script will clean up the database -- Clean up USE MASTER GO ALTER DATABASE ShrinkIsBed SET SINGLE_USER WITH ROLLBACK IMMEDIATE GO DROP DATABASE ShrinkIsBed GO There are few valid cases of the Shrinking database as well, but that is not covered in this blog post. We will cover that area some other time in future. Additionally, one can rebuild index in the tempdb as well, and we will also talk about the same in future. Brent has written a good summary blog post as well. Are you Shrinking your database? Well, when are you going to stop Shrinking it? Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Big Data – Is Big Data Relevant to me? – Big Data Questionnaires – Guest Post by Vinod Kumar

    - by Pinal Dave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions of SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. I think the series from Pinal is a good one for anyone planning to start on Big Data journey from the basics. In my daily customer interactions this buzz of “Big Data” always comes up, I react generally saying – “Sir, do you really have a ‘Big Data’ problem or do you have a big Data problem?” Generally, there is a silence in the air when I ask this question. Data is everywhere in organizations – be it big data, small data, all data and for few it is bad data which is same as no data :). Wow, don’t discount me as someone who opposes “Big Data”, I am a big supporter as much as I am a critic of the abuse of this term by the people. In this post, I wanted to let my mind flow so that you can also think in the direction I want you to see these concepts. In any case, this is not an exhaustive dump of what is in my mind – but you will surely get the drift how I am going to question Big Data terms from customers!!! Is Big Data Relevant to me? Many of my customers talk to me like blank whiteboard with no idea – “why Big Data”. They want to jump into the bandwagon of technology and they want to decipher insights from their unexplored data a.k.a. unstructured data with structured data. So what are these industry scenario’s that come to mind? Here are some of them: Financials Fraud detection: Banks and Credit cards are monitoring your spending habits on real-time basis. Customer Segmentation: applies in every industry from Banking to Retail to Aviation to Utility and others where they deal with end customer who consume their products and services. Customer Sentiment Analysis: Responding to negative brand perception on social or amplify the positive perception. Sales and Marketing Campaign: Understand the impact and get closer to customer delight. Call Center Analysis: attempt to take unstructured voice recordings and analyze them for content and sentiment. Medical Reduce Re-admissions: How to build a proactive follow-up engagements with patients. Patient Monitoring: How to track Inpatient, Out-Patient, Emergency Visits, Intensive Care Units etc. Preventive Care: Disease identification and Risk stratification is a very crucial business function for medical. Claims fraud detection: There is no precise dollars that one can put here, but this is a big thing for the medical field. Retail Customer Sentiment Analysis, Customer Care Centers, Campaign Management. Supply Chain Analysis: Every sensors and RFID data can be tracked for warehouse space optimization. Location based marketing: Based on where a check-in happens retail stores can be optimize their marketing. Telecom Price optimization and Plans, Finding Customer churn, Customer loyalty programs Call Detail Record (CDR) Analysis, Network optimizations, User Location analysis Customer Behavior Analysis Insurance Fraud Detection & Analysis, Pricing based on customer Sentiment Analysis, Loyalty Management Agents Analysis, Customer Value Management This list can go on to other areas like Utility, Manufacturing, Travel, ITES etc. So as you can see, there are obviously interesting use cases for each of these industry verticals. These are just representative list. Where to start? A lot of times I try to quiz customers on a number of dimensions before starting a Big Data conversation. Are you getting the data you need the way you want it and in a timely manner? Can you get in and analyze the data you need? How quickly is IT to respond to your BI Requests? How easily can you get at the data that you need to run your business/department/project? How are you currently measuring your business? Can you get the data you need to react WITHIN THE QUARTER to impact behaviors to meet your numbers or is it always “rear-view mirror?” How are you measuring: The Brand Customer Sentiment Your Competition Your Pricing Your performance Supply Chain Efficiencies Predictive product / service positioning What are your key challenges of driving collaboration across your global business?  What the challenges in innovation? What challenges are you facing in getting more information out of your data? Note: Garbage-in is Garbage-out. Hold good for all reporting / analytics requirements Big Data POCs? A number of customers get into the realm of setting a small team to work on Big Data – well it is a great start from an understanding point of view, but I tend to ask a number of other questions to such customers. Some of these common questions are: To what degree is your advanced analytics (natural language processing, sentiment analysis, predictive analytics and classification) paired with your Big Data’s efforts? Do you have dedicated resources exploring the possibilities of advanced analytics in Big Data for your business line? Do you plan to employ machine learning technology while doing Advanced Analytics? How is Social Media being monitored in your organization? What is your ability to scale in terms of storage and processing power? Do you have a system in place to sort incoming data in near real time by potential value, data quality, and use frequency? Do you use event-driven architecture to manage incoming data? Do you have specialized data services that can accommodate different formats, security, and the management requirements of multiple data sources? Is your organization currently using or considering in-memory analytics? To what degree are you able to correlate data from your Big Data infrastructure with that from your enterprise data warehouse? Have you extended the role of Data Stewards to include ownership of big data components? Do you prioritize data quality based on the source system (that is Facebook/Twitter data has lower quality thresholds than radio frequency identification (RFID) for a tracking system)? Do your retention policies consider the different legal responsibilities for storing Big Data for a specific amount of time? Do Data Scientists work in close collaboration with Data Stewards to ensure data quality? How is access to attributes of Big Data being given out in the organization? Are roles related to Big Data (Advanced Analyst, Data Scientist) clearly defined? How involved is risk management in the Big Data governance process? Is there a set of documented policies regarding Big Data governance? Is there an enforcement mechanism or approach to ensure that policies are followed? Who is the key sponsor for your Big Data governance program? (The CIO is best) Do you have defined policies surrounding the use of social media data for potential employees and customers, as well as the use of customer Geo-location data? How accessible are complex analytic routines to your user base? What is the level of involvement with outside vendors and third parties in regard to the planning and execution of Big Data projects? What programming technologies are utilized by your data warehouse/BI staff when working with Big Data? These are some of the important questions I ask each customer who is actively evaluating Big Data trends for their organizations. These questions give you a sense of direction where to start, what to use, how to secure, how to analyze and more. Sign off Any Big data is analysis is incomplete without a compelling story. The best way to understand this is to watch Hans Rosling – Gapminder (2:17 to 6:06) videos about the third world myths. Don’t get overwhelmed with the Big Data buzz word, the destination to what your data speaks is important. In this blog post, we did not particularly look at any Big Data technologies. This is a set of questionnaire one needs to keep in mind as they embark their journey of Big Data. I did write some of the basics in my blog: Big Data – Big Hype yet Big Opportunity. Do let me know if these questions make sense?  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Listing common SQL Code Smells.

    - by Phil Factor
    Once you’ve done a number of SQL Code-reviews, you’ll know those signs in the code that all might not be well. These ’Code Smells’ are coding styles that don’t directly cause a bug, but are indicators that all is not well with the code. . Kent Beck and Massimo Arnoldi seem to have coined the phrase in the "OnceAndOnlyOnce" page of www.C2.com, where Kent also said that code "wants to be simple". Bad Smells in Code was an essay by Kent Beck and Martin Fowler, published as Chapter 3 of the book ‘Refactoring: Improving the Design of Existing Code’ (ISBN 978-0201485677) Although there are generic code-smells, SQL has its own particular coding habits that will alert the programmer to the need to re-factor what has been written. See Exploring Smelly Code   and Code Deodorants for Code Smells by Nick Harrison for a grounding in Code Smells in C# I’ve always been tempted by the idea of automating a preliminary code-review for SQL. It would be so useful to trawl through code and pick up the various problems, much like the classic ‘Lint’ did for C, and how the Code Metrics plug-in for .NET Reflector by Jonathan 'Peli' de Halleux is used for finding Code Smells in .NET code. The problem is that few of the standard procedural code smells are relevant to SQL, and we need an agreed list of code smells. Merrilll Aldrich made a grand start last year in his blog Top 10 T-SQL Code Smells.However, I'd like to make a start by discovering if there is a general opinion amongst Database developers what the most important SQL Smells are. One can be a bit defensive about code smells. I will cheerfully write very long stored procedures, even though they are frowned on. I’ll use dynamic SQL occasionally. You can only use them as an aid for your own judgment and it is fine to ‘sign them off’ as being appropriate in particular circumstances. Also, whole classes of ‘code smells’ may be irrelevant for a particular database. The use of proprietary SQL, for example, is only a ‘code smell’ if there is a chance that the database will have to be ported to another RDBMS. The use of dynamic SQL is a risk only with certain security models. As the saying goes,  a CodeSmell is a hint of possible bad practice to a pragmatist, but a sure sign of bad practice to a purist. Plamen Ratchev’s wonderful article Ten Common SQL Programming Mistakes lists some of these ‘code smells’ along with out-and-out mistakes, but there are more. The use of nested transactions, for example, isn’t entirely incorrect, even though the database engine ignores all but the outermost: but it does flag up the possibility that the programmer thinks that nested transactions are supported. If anything requires some sort of general agreement, the definition of code smells is one. I’m therefore going to make this Blog ‘dynamic, in that, if anyone twitters a suggestion with a #SQLCodeSmells tag (or sends me a twitter) I’ll update the list here. If you add a comment to the blog with a suggestion of what should be added or removed, I’ll do my best to oblige. In other words, I’ll try to keep this blog up to date. The name against each 'smell' is the name of the person who Twittered me, commented about or who has written about the 'smell'. it does not imply that they were the first ever to think of the smell! Use of deprecated syntax such as *= (Dave Howard) Denormalisation that requires the shredding of the contents of columns. (Merrill Aldrich) Contrived interfaces Use of deprecated datatypes such as TEXT/NTEXT (Dave Howard) Datatype mis-matches in predicates that rely on implicit conversion.(Plamen Ratchev) Using Correlated subqueries instead of a join   (Dave_Levy/ Plamen Ratchev) The use of Hints in queries, especially NOLOCK (Dave Howard /Mike Reigler) Few or No comments. Use of functions in a WHERE clause. (Anil Das) Overuse of scalar UDFs (Dave Howard, Plamen Ratchev) Excessive ‘overloading’ of routines. The use of Exec xp_cmdShell (Merrill Aldrich) Excessive use of brackets. (Dave Levy) Lack of the use of a semicolon to terminate statements Use of non-SARGable functions on indexed columns in predicates (Plamen Ratchev) Duplicated code, or strikingly similar code. Misuse of SELECT * (Plamen Ratchev) Overuse of Cursors (Everyone. Special mention to Dave Levy & Adrian Hills) Overuse of CLR routines when not necessary (Sam Stange) Same column name in different tables with different datatypes. (Ian Stirk) Use of ‘broken’ functions such as ‘ISNUMERIC’ without additional checks. Excessive use of the WHILE loop (Merrill Aldrich) INSERT ... EXEC (Merrill Aldrich) The use of stored procedures where a view is sufficient (Merrill Aldrich) Not using two-part object names (Merrill Aldrich) Using INSERT INTO without specifying the columns and their order (Merrill Aldrich) Full outer joins even when they are not needed. (Plamen Ratchev) Huge stored procedures (hundreds/thousands of lines). Stored procedures that can produce different columns, or order of columns in their results, depending on the inputs. Code that is never used. Complex and nested conditionals WHILE (not done) loops without an error exit. Variable name same as the Datatype Vague identifiers. Storing complex data  or list in a character map, bitmap or XML field User procedures with sp_ prefix (Aaron Bertrand)Views that reference views that reference views that reference views (Aaron Bertrand) Inappropriate use of sql_variant (Neil Hambly) Errors with identity scope using SCOPE_IDENTITY @@IDENTITY or IDENT_CURRENT (Neil Hambly, Aaron Bertrand) Schemas that involve multiple dated copies of the same table instead of partitions (Matt Whitfield-Atlantis UK) Scalar UDFs that do data lookups (poor man's join) (Matt Whitfield-Atlantis UK) Code that allows SQL Injection (Mladen Prajdic) Tables without clustered indexes (Matt Whitfield-Atlantis UK) Use of "SELECT DISTINCT" to mask a join problem (Nick Harrison) Multiple stored procedures with nearly identical implementation. (Nick Harrison) Excessive column aliasing may point to a problem or it could be a mapping implementation. (Nick Harrison) Joining "too many" tables in a query. (Nick Harrison) Stored procedure returning more than one record set. (Nick Harrison) A NOT LIKE condition (Nick Harrison) excessive "OR" conditions. (Nick Harrison) User procedures with sp_ prefix (Aaron Bertrand) Views that reference views that reference views that reference views (Aaron Bertrand) sp_OACreate or anything related to it (Bill Fellows) Prefixing names with tbl_, vw_, fn_, and usp_ ('tibbling') (Jeremiah Peschka) Aliases that go a,b,c,d,e... (Dave Levy/Diane McNurlan) Overweight Queries (e.g. 4 inner joins, 8 left joins, 4 derived tables, 10 subqueries, 8 clustered GUIDs, 2 UDFs, 6 case statements = 1 query) (Robert L Davis) Order by 3,2 (Dave Levy) MultiStatement Table functions which are then filtered 'Sel * from Udf() where Udf.Col = Something' (Dave Ballantyne) running a SQL 2008 system in SQL 2000 compatibility mode(John Stafford)

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  • Developer’s Life – Disaster Lessons – Notes from the Field #039

    - by Pinal Dave
    [Note from Pinal]: This is a 39th episode of Notes from the Field series. What is the best solution do you have when you encounter a disaster in your organization. Now many of you would answer that in this scenario you would have another standby machine or alternative which you will plug in. Now let me ask second question – What would you do if you as an individual faces disaster?  In this episode of the Notes from the Field series database expert Mike Walsh explains a very crucial issue we face in our career, which is not technical but more to relate to human nature. Read on this may be the best blog post you might read in recent times. Howdy! When it was my turn to share the Notes from the Field last time, I took a departure from my normal technical content to talk about Attitude and Communication.(http://blog.sqlauthority.com/2014/05/08/developers-life-attitude-and-communication-they-can-cause-problems-notes-from-the-field-027/) Pinal said it was a popular topic so I hope he won’t mind if I stick with Professional Development for another of my turns at sharing some information here. Like I said last time, the “soft skills” of the IT world are often just as important – sometimes more important – than the technical skills. As a consultant with Linchpin People – I see so many situations where the professional skills I’ve gained and use are more valuable to clients than knowing the best way to tune a query. Today I want to continue talking about professional development and tell you about the way I almost got myself hit by a train – and why that matters in our day jobs. Sometimes we can learn a lot from disasters. Whether we caused them or someone else did. If you are interested in learning about some of my observations in these lessons you can see more where I talk about lessons from disasters on my blog. For now, though, onto how I almost got my vehicle hit by a train… The Train Crash That Almost Was…. My family and I own a little schoolhouse building about a 10 mile drive away from our house. We use it as a free resource for families in the area that homeschool their children – so they can have some class space. I go up there a lot to check in on the property, to take care of the trash and to do work on the property. On the way there, there is a very small Stop Sign controlled railroad intersection. There is only two small freight trains a day passing there. Actually the same train, making a journey south and then back North. That’s it. This road is a small rural road, barely ever a second car driving in the neighborhood there when I am. The stop sign is pretty much there only for the train crossing. When we first bought the building, I was up there a lot doing renovations on the property. Being familiar with the area, I am also familiar with the train schedule and know the tracks are normally free of trains. So I developed a bad habit. You see, I’d approach the stop sign and slow down as I roll through it. Sometimes I’d do a quick look and come to an “almost” stop there but keep on going. I let my impatience and complacency take over. And that is because most of the time I was going there long after the train was done for the day or in between the runs. This habit became pretty well established after a couple years of driving the route. The behavior reinforced a bit by the success ratio. I saw others doing it as well from the neighborhood when I would happen to be there around the time another car was there. Well. You already know where this ends up by the title and backstory here. A few months ago I came to that little crossing, and I started to do the normal routine. I’d pretty much stopped looking in some respects because of the pattern I’d gotten into.  For some reason I looked and heard and saw the train slowly approaching and slammed on my brakes and stopped. It was an abrupt stop, and it was close. I probably would have made it okay, but I sat there thinking about lessons for IT professionals from the situation once I started breathing again and watched the cars loaded with sand and propane slowly labored down the tracks… Here are Those Lessons… It’s easy to get stuck into a routine – That isn’t always bad. Except when it’s a bad routine. Momentum and inertia are powerful. Once you have a habit and a routine developed – it’s really hard to break that. Make sure you are setting the right routines and habits TODAY. What almost dangerous things are you doing today? How are you almost messing up your production environment today? Stop doing that. Be Deliberate – (Even when you are the only one) – Like I said – a lot of people roll through that stop sign. Perhaps the neighbors or other drivers think “why is he fully stopping and looking… The train only comes two times a day!” – they can think that all they want. Through deliberate actions and forcing myself to pay attention, I will avoid that oops again. Slow down. Take a deep breath. Be Deliberate in your job. Pay attention to the small stuff and go out of your way to be careful. It will save you later. Be Observant – Keep your eyes open. By looking around, observing the situation and understanding what your servers, databases, users and vendors are doing – you’ll notice when something is out of place. But if you don’t know what is normal, if you don’t look to make sure nothing has changed – that train will come and get you. Where can you be more observant? What warning signs are you ignoring in your environment today? In the IT world – trains are everywhere. Projects move fast. Decisions happen fast. Problems turn from a warning sign to a disaster quickly. If you get stuck in a complacent pattern of “Everything is okay, it always has been and always will be” – that’s the time that you will most likely get stuck in a bad situation. Don’t let yourself get complacent, don’t let your team get complacent. That will lead to being proactive. And a proactive environment spends less money on consultants for troubleshooting problems you should have seen ahead of time. You can spend your money and IT budget on improving for your customers. If you want to get started with performance analytics and triage of virtualized SQL Servers with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Step by Step Guide to Beginning Data Quality Services in SQL Server 2012 – Introduction to DQS

    - by pinaldave
    Data Quality Services is a very important concept of SQL Server. I have recently started to explore the same and I am really learning some good concepts. Here are two very important blog posts which one should go over before continuing this blog post. Installing Data Quality Services (DQS) on SQL Server 2012 Connecting Error to Data Quality Services (DQS) on SQL Server 2012 This article is introduction to Data Quality Services for beginners. We will be using an Excel file Click on the image to enlarge the it. In the first article we learned to install DQS. In this article we will see how we can learn about building Knowledge Base and using it to help us identify the quality of the data as well help correct the bad quality of the data. Here are the two very important steps we will be learning in this tutorial. Building a New Knowledge Base  Creating a New Data Quality Project Let us start the building the Knowledge Base. Click on New Knowledge Base. In our project we will be using the Excel as a knowledge base. Here is the Excel which we will be using. There are two columns. One is Colors and another is Shade. They are independent columns and not related to each other. The point which I am trying to show is that in Column A there are unique data and in Column B there are duplicate records. Clicking on New Knowledge Base will bring up the following screen. Enter the name of the new knowledge base. Clicking NEXT will bring up following screen where it will allow to select the EXCE file and it will also let users select the source column. I have selected Colors and Shade both as a source column. Creating a domain is very important. Here you can create a unique domain or domain which is compositely build from Colors and Shade. As this is the first example, I will create unique domain – for Colors I will create domain Colors and for Shade I will create domain Shade. Here is the screen which will demonstrate how the screen will look after creating domains. Clicking NEXT it will bring you to following screen where you can do the data discovery. Clicking on the START will start the processing of the source data provided. Pre-processed data will show various information related to the source data. In our case it shows that Colors column have unique data whereas Shade have non-unique data and unique data rows are only two. In the next screen you can actually add more rows as well see the frequency of the data as the values are listed unique. Clicking next will publish the knowledge base which is just created. Now the knowledge base is created. We will try to take any random data and attempt to do DQS implementation over it. I am using another excel sheet here for simplicity purpose. In reality you can easily use SQL Server table for the same. Click on New Data Quality Project to see start DQS Project. In the next screen it will ask which knowledge base to use. We will be using our Colors knowledge base which we have recently created. In the Colors knowledge base we had two columns – 1) Colors and 2) Shade. In our case we will be using both of the mappings here. User can select one or multiple column mapping over here. Now the most important phase of the complete project. Click on Start and it will make the cleaning process and shows various results. In our case there were two columns to be processed and it completed the task with necessary information. It demonstrated that in Colors columns it has not corrected any value by itself but in Shade value there is a suggestion it has. We can train the DQS to correct values but let us keep that subject for future blog posts. Now click next and keep the domain Colors selected left side. It will demonstrate that there are two incorrect columns which it needs to be corrected. Here is the place where once corrected value will be auto-corrected in future. I manually corrected the value here and clicked on Approve radio buttons. As soon as I click on Approve buttons the rows will be disappeared from this tab and will move to Corrected Tab. If I had rejected tab it would have moved the rows to Invalid tab as well. In this screen you can see how the corrected 2 rows are demonstrated. You can click on Correct tab and see previously validated 6 rows which passed the DQS process. Now let us click on the Shade domain on the left side of the screen. This domain shows very interesting details as there DQS system guessed the correct answer as Dark with the confidence level of 77%. It is quite a high confidence level and manual observation also demonstrate that Dark is the correct answer. I clicked on Approve and the row moved to corrected tab. On the next screen DQS shows the summary of all the activities. It also demonstrates how the correction of the quality of the data was performed. The user can explore their data to a SQL Server Table, CSV file or Excel. The user also has an option to either explore data and all the associated cleansing info or data only. I will select Data only for demonstration purpose. Clicking explore will generate the files. Let us open the generated file. It will look as following and it looks pretty complete and corrected. Well, we have successfully completed DQS Process. The process is indeed very easy. I suggest you try this out yourself and you will find it very easy to learn. In future we will go over advanced concepts. Are you using this feature on your production server? If yes, would you please leave a comment with your environment and business need. It will be indeed interesting to see where it is implemented. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Data Quality Services, DQS

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