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  • Is it possible to use the Raring install image as a package repo (like the old alternate CD)?

    - by jamadagni
    I use Kubuntu and recently upgraded to Raring directly from Precise. Until Precise, I always installed the OS using the alternate CD and not the desktop CD, because I could later on mount the image and use it as an offline package repo. For instance if I remove a package installed by the default installer and later I want to install it again, I can just install it from the ISO without needing to download it again. However, since Quantal the alternate CD no longer exists, so I am not sure how to set up the installed image as a local repo. I mean, doing find . -name "*.deb" inside the ISO tree after loopmounting it only shows a few packages like libc6 gcc and such and not the full set of packages that are actually installed -- I presume they are included in pre-installed form inside casper/filesystem.squashfs. Given this situation, is it or is it not possible to use the Raring install images as offline repos? If yes, how? Thank you!

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  • Getting an Ajax response from Zend Framework Controller

    - by JavaLava
    I'm doing an Ajax request on one of my views to a Controller but I am unable to send back a response to the Ajax method. In the snippet below, I am trying to send the word 'hellopanda' back but in the alert message, I'll get data as an object. View : $.ajax({ type: "POST", url: "localhost/some-activity", data: dataString, success: function(data) { alert( "Data is: " + data); //do something with data }, error: function(data){ alert( "Data is: " + data); //do something with data }, onComplete: function(){ } }); Controller: public function someActivityAction(){ //do stuff echo "hellopanda"; } I'm pretty sure the echo is the problem. Any insights on to how to do a proper response to the view would be greatly appreciated.

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  • Cannot install g++ on 12.10

    - by Ullen
    sudo apt-get install g++ Reading package lists... Done Building dependency tree Reading state information... Done Some packages could not be installed. This may mean that you have requested an impossible situation or if you are using the unstable distribution that some required packages have not yet been created or been moved out of Incoming. The following information may help to resolve the situation: The following packages have unmet dependencies: g++ : Depends: g++-4.7 (>= 4.7.0-1~) but it is not going to be installed E: Unable to correct problems, you have held broken packages.

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  • [android]layout like printest

    - by Dcboy
    I want to make a custom view like pinterest in my code,i use scrollView and 3 linearlayout inside scrollview I custom my view name waterfallView here is the code: public class WaterfallView extends LinearLayout { private ListAdapter m_Adapter; private OnClickListener onClickListener = null; private LinearLayout m_Line1; private LinearLayout m_Line2; private LinearLayout m_Line3; public WaterfallView(Context context) { super(context); // TODO Auto-generated constructor stub InitLine(); } public WaterfallView(Context context, AttributeSet attrs) { super(context, attrs); InitLine(); } private void InitLine() { LinearLayout.LayoutParams lp = new LinearLayout.LayoutParams( LinearLayout.LayoutParams.MATCH_PARENT, LinearLayout.LayoutParams.MATCH_PARENT); lp.weight = 1; // line2 m_Line1 = new LinearLayout(this.getContext()); m_Line1.setOrientation(VERTICAL); m_Line1.setLayoutParams(lp); // line2 m_Line2 = new LinearLayout(this.getContext()); m_Line2.setOrientation(VERTICAL); m_Line2.setLayoutParams(lp); // line3 m_Line3 = new LinearLayout(this.getContext()); m_Line3.setOrientation(VERTICAL); m_Line3.setLayoutParams(lp); addView(m_Line1); addView(m_Line2); addView(m_Line3); } public ListAdapter getAdapter() { return m_Adapter; } private void BindLayout() { int count = m_Adapter.getCount(); for (int i = 0; i < count; i++) { View v = m_Adapter.getView(i, null, null); v.setOnClickListener(this.onClickListener); if (i == 0 || i % 3 == 0) m_Line1.addView(v); if (i == 1 || i % 3 == 1) m_Line2.addView(v); if (i == 2 || i % 3 == 2) m_Line3.addView(v); } Log.v("countTAG", "" + count); } private void AddItem(){ } public void setAdapter(ListAdapter adapter) { this.m_Adapter = adapter; BindLayout(); } public OnClickListener getOnclickListner() { return onClickListener; } public void setOnclickLinstener(OnClickListener onClickListener) { this.onClickListener = onClickListener; } } In the BindLayout function there is m_Adapter.getView(i, null, null); then the second param convertView i would like to have AbsListView class using RecycleBin How could I do that?

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  • Yii CGridView: how to add a static WHERE condtion?

    - by realtebo
    I've a standard Gii created admin view, which use a CGridView, and it's showing my user table data. the problem is that user with name 'root' must NOT BE VISIBLE. Is there a way to add a static where condition " ... and username !='root' " ? admin.php [view] 'columns'=>array( 'id', 'username', 'password', 'realname', 'email', ..... user.php [model] public function search() { // Warning: Please modify the following code to remove attributes that // should not be searched. $criteria=new CDbCriteria; $criteria->compare('id',$this->id); $criteria->compare('username',$this->username,true); $criteria->compare('password',$this->password,true); $criteria->compare('realname',$this->realname,true); $criteria->compare('email',$this->email,true); ...... return new CActiveDataProvider($this, array( 'criteria'=>$criteria, )); }

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  • rails - REST or create another method

    - by user1304740
    Let's assume we have two models linked with a 1-to-many relationship (like clients and invoices - a client can have many invoices). In a view of a 'client' (let's say the 'show' view), there is a form to capture an 'invoice'. I found 2 approaches: This form should be handled by the 'invoice' controller (method create), having client_id passed as a parameter This form should be handled by a new method in 'client' controller, probably a PUT method defined in routes.rb. Is there a 'Rails way', or both of them are good? Is there a preffered way? Thanks!

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  • CakePHP ACL use case(s)

    - by Jonathan
    I have got a simple web app in development, i want to establish a couple of user groups; Admin, Doctors & Patients. Each group would have their access restricted to particular controller actions rather than individual content. So for example, Doctors can view patient records (index & view actions), but cannot delete them. Usually i would create a groups model, and assign the various users to a group. And filter in the beforeFilter() method to determine if the user has access. But if ACL can do the job, why right the code, right? Thanks

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  • how to get IndexPath

    - by user145883
    in iphone application. I'm trying to get indexPath.row value to do something on the basis of row selected in programmatically created tableview. Can someone please tell me why is the indexPath.row value is not coming correct. It's some thing like 21487...3? NSUInteger nSections = [myTableView numberOfSections]; NSUInteger nRows = [myTableView numberOfRowsInSection:nSections]; NSIndexPath *indexPath = [NSIndexPath indexPathForRow: nRows inSection:nSections]; NSLog(@"No of sections in my table view %d",nSections); NSLog(@"No of rows in my table view %d",nRows); NSLog(@"Value of selected indexPath Row %d", indexPath.row); Thanks, Aaryan

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  • Why is this mod_rewrite RewriteRule directive not working in the .htaccess file?

    - by morgant
    I've got a site that was hosted on a linux el cheapo hosting service that I'm migrating to my Mac OS X 10.5 Leopard Server server running Apache 2.2.8 & PHP 5.2.5 w/rewrite_module enabled and AllowOverride All, but I'm running into an issue with the following lines in the .htaccess file: RewriteEngine On #RewriteRule ^view/([^/\.]+)/?$ /view.php?item=$1 [L] #RewriteRule ^order/([^/\.]+)/?$ /order.php?item=$1 [L] RewriteRule ^category/([^/\.]+)/?$ /category.php?category=$1 [L] As you can see, I've commented out the RewriteRule directives for /view/ and /order/, so I'm only dealing with /category/. When I attempt to load http://domain.tld/category/2/ it runs category.php (I've added debug code to confirm), but $_SERVER['REQUEST_URI'] comes through as /category/2/ and $_GET['category'] comes through as empty. I'm usually fine with troubleshooting .htaccess files and mod_rewrite directives, but this one's got me stumped for some reason. Update: I followed Josh's suggestion and here's the what's dumped to mod_rewrite.log when I try to access http://domain.tld/category/2/: 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (2) init rewrite engine with requested uri /category/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) applying pattern '.*' to uri '/category/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (1) pass through /category/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] add path info postfix: /Library/WebServer/Documents/tld.domain.www/category.php -> /Library/WebServer/Documents/tld.domain.www/category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] strip per-dir prefix: /Library/WebServer/Documents/tld.domain.www/category.php/13 -> category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] applying pattern '^category/([^/\.]+)/?$' to uri 'category.php/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (1) [perdir /Library/WebServer/Documents/tld.domain.www/] pass through /Library/WebServer/Documents/tld.domain.www/category.php 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] add path info postfix: /Library/WebServer/Documents/tld.domain.www/category.php -> /Library/WebServer/Documents/tld.domain.www/category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] strip per-dir prefix: /Library/WebServer/Documents/tld.domain.www/category.php/13 -> category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] applying pattern '^category/([^/\.]+)/?$' to uri 'category.php/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (1) [perdir /Library/WebServer/Documents/tld.domain.www/] pass through /Library/WebServer/Documents/tld.domain.www/category.php 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (2) init rewrite engine with requested uri /13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (3) applying pattern '.*' to uri '/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (1) pass through /13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] strip per-dir prefix: /Library/WebServer/Documents/tld.domain.www/13 -> 13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] applying pattern '^category/([^/\.]+)/?$' to uri '13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (1) [perdir /Library/WebServer/Documents/tld.domain.www/] pass through /Library/WebServer/Documents/tld.domain.www/13

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  • Why is this mod_rewrite RewriteRule directive not working in the .htaccess file?

    - by morgant
    I've got a site that was hosted on a linux el cheapo hosting service that I'm migrating to my Mac OS X 10.5 Leopard Server server running Apache 2.2.8 & PHP 5.2.5 w/rewrite_module enabled and AllowOverride All, but I'm running into an issue with the following lines in the .htaccess file: RewriteEngine On #RewriteRule ^view/([^/\.]+)/?$ /view.php?item=$1 [L] #RewriteRule ^order/([^/\.]+)/?$ /order.php?item=$1 [L] RewriteRule ^category/([^/\.]+)/?$ /category.php?category=$1 [L] As you can see, I've commented out the RewriteRule directives for /view/ and /order/, so I'm only dealing with /category/. When I attempt to load http://domain.tld/category/2/ it runs category.php (I've added debug code to confirm), but $_SERVER['REQUEST_URI'] comes through as /category/2/ and $_GET['category'] comes through as empty. I'm usually fine with troubleshooting .htaccess files and mod_rewrite directives, but this one's got me stumped for some reason. Update: I followed Josh's suggestion and here's the what's dumped to mod_rewrite.log when I try to access http://domain.tld/category/2/: 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (2) init rewrite engine with requested uri /category/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) applying pattern '.*' to uri '/category/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (1) pass through /category/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] add path info postfix: /Library/WebServer/Documents/tld.domain.www/category.php -> /Library/WebServer/Documents/tld.domain.www/category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] strip per-dir prefix: /Library/WebServer/Documents/tld.domain.www/category.php/13 -> category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] applying pattern '^category/([^/\.]+)/?$' to uri 'category.php/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6aa98/subreq] (1) [perdir /Library/WebServer/Documents/tld.domain.www/] pass through /Library/WebServer/Documents/tld.domain.www/category.php 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] add path info postfix: /Library/WebServer/Documents/tld.domain.www/category.php -> /Library/WebServer/Documents/tld.domain.www/category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] strip per-dir prefix: /Library/WebServer/Documents/tld.domain.www/category.php/13 -> category.php/13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] applying pattern '^category/([^/\.]+)/?$' to uri 'category.php/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b5ea98/initial] (1) [perdir /Library/WebServer/Documents/tld.domain.www/] pass through /Library/WebServer/Documents/tld.domain.www/category.php 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (2) init rewrite engine with requested uri /13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (3) applying pattern '.*' to uri '/13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (1) pass through /13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] strip per-dir prefix: /Library/WebServer/Documents/tld.domain.www/13 -> 13 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (3) [perdir /Library/WebServer/Documents/tld.domain.www/] applying pattern '^category/([^/\.]+)/?$' to uri '13' 65.19.81.253 - - [22/Oct/2009:17:31:53 --0400] [domain.tld/sid#100aae0b0][rid#100b6ea98/subreq] (1) [perdir /Library/WebServer/Documents/tld.domain.www/] pass through /Library/WebServer/Documents/tld.domain.www/13

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  • JBoss AS 5: starts but can't connect (Windows, remote)

    - by Nuwan
    Hello I installed Jboss 5.0GA and Its works fine in localhost.But I want It to access through remote Machine.Then I bind my IP address to my server and started it.This is the command I used run.bat -b 10.17.62.63 Then the server Starts fine This is the console log when starting the server > =============================================================================== > > JBoss Bootstrap Environment > > JBOSS_HOME: C:\jboss-5.0.0.GA > > JAVA: C:\Program Files\Java\jdk1.6.0_34\bin\java > > JAVA_OPTS: -Dprogram.name=run.bat -server -Xms128m -Xmx512m > -XX:MaxPermSize=25 6m -Dorg.jboss.resolver.warning=true -Dsun.rmi.dgc.client.gcInterval=3600000 -Ds un.rmi.dgc.server.gcInterval=3600000 > > CLASSPATH: C:\jboss-5.0.0.GA\bin\run.jar > > =============================================================================== > > run.bat: unused non-option argument: ûb run.bat: unused non-option > argument: 0.0.0.0 13:43:38,179 INFO [ServerImpl] Starting JBoss > (Microcontainer)... 13:43:38,179 INFO [ServerImpl] Release ID: JBoss > [Morpheus] 5.0.0.GA (build: SV NTag=JBoss_5_0_0_GA date=200812041714) > 13:43:38,179 INFO [ServerImpl] Bootstrap URL: null 13:43:38,179 INFO > [ServerImpl] Home Dir: C:\jboss-5.0.0.GA 13:43:38,179 INFO > [ServerImpl] Home URL: file:/C:/jboss-5.0.0.GA/ 13:43:38,195 INFO > [ServerImpl] Library URL: file:/C:/jboss-5.0.0.GA/lib/ 13:43:38,195 > INFO [ServerImpl] Patch URL: null 13:43:38,195 INFO [ServerImpl] > Common Base URL: file:/C:/jboss-5.0.0.GA/common/ > > 13:43:38,195 INFO [ServerImpl] Common Library URL: > file:/C:/jboss-5.0.0.GA/comm on/lib/ 13:43:38,195 INFO [ServerImpl] > Server Name: default 13:43:38,195 INFO [ServerImpl] Server Base Dir: > C:\jboss-5.0.0.GA\server 13:43:38,195 INFO [ServerImpl] Server Base > URL: file:/C:/jboss-5.0.0.GA/server/ > > 13:43:38,210 INFO [ServerImpl] Server Config URL: > file:/C:/jboss-5.0.0.GA/serve r/default/conf/ 13:43:38,210 INFO > [ServerImpl] Server Home Dir: C:\jboss-5.0.0.GA\server\defaul t > 13:43:38,210 INFO [ServerImpl] Server Home URL: > file:/C:/jboss-5.0.0.GA/server/ default/ 13:43:38,210 INFO > [ServerImpl] Server Data Dir: C:\jboss-5.0.0.GA\server\defaul t\data > 13:43:38,210 INFO [ServerImpl] Server Library URL: > file:/C:/jboss-5.0.0.GA/serv er/default/lib/ 13:43:38,210 INFO > [ServerImpl] Server Log Dir: C:\jboss-5.0.0.GA\server\default \log > 13:43:38,210 INFO [ServerImpl] Server Native Dir: > C:\jboss-5.0.0.GA\server\defa ult\tmp\native 13:43:38,210 INFO > [ServerImpl] Server Temp Dir: C:\jboss-5.0.0.GA\server\defaul t\tmp > 13:43:38,210 INFO [ServerImpl] Server Temp Deploy Dir: > C:\jboss-5.0.0.GA\server \default\tmp\deploy 13:43:39,710 INFO > [ServerImpl] Starting Microcontainer, bootstrapURL=file:/C:/j > boss-5.0.0.GA/server/default/conf/bootstrap.xml 13:43:40,851 INFO > [VFSCacheFactory] Initializing VFSCache [org.jboss.virtual.pl > ugins.cache.IterableTimedVFSCache] 13:43:40,866 INFO > [VFSCacheFactory] Using VFSCache [IterableTimedVFSCache{lifet > ime=1800, resolution=60}] 13:43:41,616 INFO [CopyMechanism] VFS temp > dir: C:\jboss-5.0.0.GA\server\defaul t\tmp 13:43:41,648 INFO > [ZipEntryContext] VFS force nested jars copy-mode is enabled. > > 13:43:44,288 INFO [ServerInfo] Java version: 1.6.0_34,Sun > Microsystems Inc. 13:43:44,288 INFO [ServerInfo] Java VM: Java > HotSpot(TM) Server VM 20.9-b04,Sun Microsystems Inc. 13:43:44,288 > INFO [ServerInfo] OS-System: Windows XP 5.1,x86 13:43:44,569 INFO > [JMXKernel] Legacy JMX core initialized 13:43:50,148 INFO > [ProfileServiceImpl] Loading profile: default from: org.jboss > .system.server.profileservice.repository.SerializableDeploymentRepository@e72f0c > (root=C:\jboss-5.0.0.GA\server, > key=org.jboss.profileservice.spi.ProfileKey@143b > 82c3[domain=default,server=default,name=default]) 13:43:50,148 INFO > [ProfileImpl] Using repository:org.jboss.system.server.profil > eservice.repository.SerializableDeploymentRepository@e72f0c(root=C:\jboss-5.0.0. > GA\server, > key=org.jboss.profileservice.spi.ProfileKey@143b82c3[domain=default,s > erver=default,name=default]) 13:43:50,148 INFO [ProfileServiceImpl] > Loaded profile: ProfileImpl@8b3bb3{key=o > rg.jboss.profileservice.spi.ProfileKey@143b82c3[domain=default,server=default,na > me=default]} 13:43:54,804 INFO [WebService] Using RMI server > codebase: http://127.0.0.1:8083 / 13:44:12,147 INFO [CXFServerConfig] > JBoss Web Services - Stack CXF Runtime Serv er 13:44:12,147 INFO > [CXFServerConfig] 3.1.2.GA 13:44:29,788 INFO > [Ejb3DependenciesDeployer] Encountered deployment AbstractVFS > DeploymentContext@29776073{vfszip:/C:/jboss-5.0.0.GA/server/default/deploy/myE-e > jb.jar} 13:44:29,819 INFO [Ejb3DependenciesDeployer] Encountered > deployment AbstractVFS > DeploymentContext@29776073{vfszip:/C:/jboss-5.0.0.GA/server/default/deploy/myE-e > jb.jar} 13:44:29,819 INFO [Ejb3DependenciesDeployer] Encountered > deployment AbstractVFS > DeploymentContext@29776073{vfszip:/C:/jboss-5.0.0.GA/server/default/deploy/myE-e > jb.jar} 13:44:29,819 INFO [Ejb3DependenciesDeployer] Encountered > deployment AbstractVFS > DeploymentContext@29776073{vfszip:/C:/jboss-5.0.0.GA/server/default/deploy/myE-e > jb.jar} 13:44:37,116 INFO [JMXConnectorServerService] JMX Connector > server: service:jmx > :rmi://127.0.0.1/jndi/rmi://127.0.0.1:1090/jmxconnector 13:44:38,022 > INFO [MailService] Mail Service bound to java:/Mail 13:44:43,162 WARN > [JBossASSecurityMetadataStore] WARNING! POTENTIAL SECURITY RI SK. It > has been detected that the MessageSucker component which sucks > messages f rom one node to another has not had its password changed > from the installation d efault. Please see the JBoss Messaging user > guide for instructions on how to do this. 13:44:43,209 WARN > [AnnotationCreator] No ClassLoader provided, using TCCL: org. > jboss.managed.api.annotation.ManagementComponent 13:44:43,600 INFO > [TransactionManagerService] JBossTS Transaction Service (JTA version) > - JBoss Inc. 13:44:43,600 INFO [TransactionManagerService] Setting up property manager MBean and JMX layer 13:44:44,366 INFO > [TransactionManagerService] Initializing recovery manager 13:44:44,678 > INFO [TransactionManagerService] Recovery manager configured > 13:44:44,678 INFO [TransactionManagerService] Binding > TransactionManager JNDI R eference 13:44:44,787 INFO > [TransactionManagerService] Starting transaction recovery man ager > 13:44:46,428 INFO [Http11Protocol] Initializing Coyote HTTP/1.1 on > http-127.0.0 .1-8080 13:44:46,459 INFO [AjpProtocol] Initializing > Coyote AJP/1.3 on ajp-127.0.0.1-80 09 13:44:46,459 INFO > [StandardService] Starting service jboss.web 13:44:46,475 INFO > [StandardEngine] Starting Servlet Engine: JBoss Web/2.1.1.GA > 13:44:46,616 INFO [Catalina] Server startup in 350 ms 13:44:46,709 > INFO [TomcatDeployment] deploy, ctxPath=/web-console, vfsUrl=manag > ement/console-mgr.sar/web-console.war 13:44:48,553 INFO > [TomcatDeployment] deploy, ctxPath=/juddi, vfsUrl=juddi-servi > ce.sar/juddi.war 13:44:48,678 INFO [RegistryServlet] Loading jUDDI > configuration. 13:44:48,694 INFO [RegistryServlet] Resources loaded > from: /WEB-INF/juddi.prope rties 13:44:48,709 INFO [RegistryServlet] > Initializing jUDDI components. 13:44:48,991 INFO [TomcatDeployment] > deploy, ctxPath=/invoker, vfsUrl=http-invo ker.sar/invoker.war > 13:44:49,162 INFO [TomcatDeployment] deploy, ctxPath=/jbossws, > vfsUrl=jbossws.s ar/jbossws-management.war 13:44:49,475 INFO > [RARDeployment] Required license terms exist, view vfszip:/C: > /jboss-5.0.0.GA/server/default/deploy/jboss-local-jdbc.rar/META-INF/ra.xml > 13:44:49,569 INFO [RARDeployment] Required license terms exist, view > vfszip:/C: > /jboss-5.0.0.GA/server/default/deploy/jboss-xa-jdbc.rar/META-INF/ra.xml > 13:44:49,741 INFO [RARDeployment] Required license terms exist, view > vfszip:/C: > /jboss-5.0.0.GA/server/default/deploy/jms-ra.rar/META-INF/ra.xml > 13:44:49,819 INFO [RARDeployment] Required license terms exist, view > vfszip:/C: > /jboss-5.0.0.GA/server/default/deploy/mail-ra.rar/META-INF/ra.xml > 13:44:49,912 INFO [RARDeployment] Required license terms exist, view > vfszip:/C: > /jboss-5.0.0.GA/server/default/deploy/quartz-ra.rar/META-INF/ra.xml > 13:44:50,069 INFO [SimpleThreadPool] Job execution threads will use > class loade r of thread: main 13:44:50,115 INFO [QuartzScheduler] > Quartz Scheduler v.1.5.2 created. 13:44:50,131 INFO [RAMJobStore] > RAMJobStore initialized. 13:44:50,131 INFO [StdSchedulerFactory] > Quartz scheduler 'DefaultQuartzSchedule r' initialized from default > resource file in Quartz package: 'quartz.properties' > > 13:44:50,131 INFO [StdSchedulerFactory] Quartz scheduler version: > 1.5.2 13:44:50,131 INFO [QuartzScheduler] Scheduler DefaultQuartzScheduler_$_NON_CLUS TERED started. 13:44:51,194 INFO > [ConnectionFactoryBindingService] Bound ConnectionManager 'jb > oss.jca:service=DataSourceBinding,name=DefaultDS' to JNDI name > 'java:DefaultDS' 13:44:51,819 WARN [QuartzTimerServiceFactory] sql > failed: CREATE TABLE QRTZ_JOB > _DETAILS(JOB_NAME VARCHAR(80) NOT NULL, JOB_GROUP VARCHAR(80) NOT NULL, DESCRIPT ION VARCHAR(120) NULL, JOB_CLASS_NAME VARCHAR(128) NOT > NULL, IS_DURABLE VARCHAR( 1) NOT NULL, IS_VOLATILE VARCHAR(1) NOT > NULL, IS_STATEFUL VARCHAR(1) NOT NULL, R EQUESTS_RECOVERY VARCHAR(1) > NOT NULL, JOB_DATA BINARY NULL, PRIMARY KEY (JOB_NAM E,JOB_GROUP)) > 13:44:51,912 INFO [SimpleThreadPool] Job execution threads will use > class loade r of thread: main 13:44:51,928 INFO [QuartzScheduler] > Quartz Scheduler v.1.5.2 created. 13:44:51,928 INFO [JobStoreCMT] > Using db table-based data access locking (synch ronization). > 13:44:51,944 INFO [JobStoreCMT] Removed 0 Volatile Trigger(s). > 13:44:51,944 INFO [JobStoreCMT] Removed 0 Volatile Job(s). > 13:44:51,944 INFO [JobStoreCMT] JobStoreCMT initialized. 13:44:51,944 > INFO [StdSchedulerFactory] Quartz scheduler 'JBossEJB3QuartzSchedu > ler' initialized from an externally provided properties instance. > 13:44:51,959 INFO [StdSchedulerFactory] Quartz scheduler version: > 1.5.2 13:44:51,959 INFO [JobStoreCMT] Freed 0 triggers from 'acquired' / 'blocked' st ate. 13:44:51,975 INFO [JobStoreCMT] > Recovering 0 jobs that were in-progress at the time of the last > shut-down. 13:44:51,975 INFO [JobStoreCMT] Recovery complete. > 13:44:51,975 INFO [JobStoreCMT] Removed 0 'complete' triggers. > 13:44:51,975 INFO [JobStoreCMT] Removed 0 stale fired job entries. > 13:44:51,990 INFO [QuartzScheduler] Scheduler > JBossEJB3QuartzScheduler_$_NON_CL USTERED started. 13:44:52,381 INFO > [ServerPeer] JBoss Messaging 1.4.1.GA server [0] started 13:44:52,569 > INFO [QueueService] Queue[/queue/DLQ] started, fullSize=200000, pa > geSize=2000, downCacheSize=2000 13:44:52,584 INFO [QueueService] > Queue[/queue/ExpiryQueue] started, fullSize=20 0000, pageSize=2000, > downCacheSize=2000 13:44:52,709 INFO [ConnectionFactory] Connector > bisocket://127.0.0.1:4457 has l easing enabled, lease period 10000 > milliseconds 13:44:52,709 INFO [ConnectionFactory] > org.jboss.jms.server.connectionfactory.Co nnectionFactory@1a8ac5e > started 13:44:52,725 WARN [ConnectionFactoryJNDIMapper] > supportsFailover attribute is t rue on connection factory: > jboss.messaging.connectionfactory:service=ClusteredCo nnectionFactory > but post office is non clustered. So connection factory will *no t* > support failover 13:44:52,725 WARN [ConnectionFactoryJNDIMapper] > supportsLoadBalancing attribute is true on connection factory: > jboss.messaging.connectionfactory:service=Cluste redConnectionFactory > but post office is non clustered. So connection factory wil l *not* > support load balancing 13:44:52,740 INFO [ConnectionFactory] > Connector bisocket://127.0.0.1:4457 has l easing enabled, lease period > 10000 milliseconds 13:44:52,740 INFO [ConnectionFactory] > org.jboss.jms.server.connectionfactory.Co nnectionFactory@1d43178 > started 13:44:52,740 INFO [ConnectionFactory] Connector > bisocket://127.0.0.1:4457 has l easing enabled, lease period 10000 > milliseconds 13:44:52,756 INFO [ConnectionFactory] > org.jboss.jms.server.connectionfactory.Co nnectionFactory@52728a > started 13:44:53,084 INFO [ConnectionFactoryBindingService] Bound > ConnectionManager 'jb > oss.jca:service=ConnectionFactoryBinding,name=JmsXA' to JNDI name > 'java:JmsXA' 13:44:53,225 INFO [TomcatDeployment] deploy, ctxPath=/, > vfsUrl=ROOT.war 13:44:53,553 INFO [TomcatDeployment] deploy, > ctxPath=/jmx-console, vfsUrl=jmx-c onsole.war 13:44:53,975 INFO > [TomcatDeployment] deploy, ctxPath=/TestService, vfsUrl=TestS > erviceEAR.ear/TestService.war 13:44:55,662 INFO [JBossASKernel] > Created KernelDeployment for: myE-ejb.jar 13:44:55,709 INFO > [JBossASKernel] installing bean: jboss.j2ee:jar=myE-ejb.jar,n > ame=RPSService,service=EJB3 13:44:55,725 INFO [JBossASKernel] with > dependencies: 13:44:55,725 INFO [JBossASKernel] and demands: > 13:44:55,725 INFO [JBossASKernel] > jboss.ejb:service=EJBTimerService 13:44:55,725 INFO [JBossASKernel] > and supplies: 13:44:55,725 INFO [JBossASKernel] > jndi:RPSService/remote 13:44:55,725 INFO [JBossASKernel] Added > bean(jboss.j2ee:jar=myE-ejb.jar,name=RP SService,service=EJB3) to > KernelDeployment of: myE-ejb.jar 13:44:56,772 INFO > [SessionSpecContainer] Starting jboss.j2ee:jar=myE-ejb.jar,na > me=RPSService,service=EJB3 13:44:56,803 INFO [EJBContainer] STARTED > EJB: com.monz.rpz.RPSService ejbName: RPSService 13:44:56,819 INFO > [JndiSessionRegistrarBase] Binding the following Entries in G lobal > JNDI: > > > 13:44:57,381 INFO [DefaultEndpointRegistry] register: > jboss.ws:context=myE-ejb, endpoint=RPSService 13:44:57,428 INFO > [DescriptorDeploymentAspect] Add Service id=RPSService > address=http://127.0.0.1:8080/myE-ejb/RPSService > implementor=com.monz.rpz.RPSService > invoker=org.jboss.wsf.stack.cxf.InvokerEJB3 mtomEnabled=false > 13:44:57,459 INFO [DescriptorDeploymentAspect] JBossWS-CXF > configuration genera ted: > file:/C:/jboss-5.0.0.GA/server/default/tmp/jbossws/jbossws-cxf1864137209199 > 110130.xml 13:44:57,569 INFO [TomcatDeployment] deploy, ctxPath=/myE-ejb, vfsUrl=myE-ejb.j ar 13:44:57,709 WARN [config] > Unable to process deployment descriptor for context '/myE-ejb' > 13:44:59,334 INFO [Http11Protocol] Starting Coyote HTTP/1.1 on > http-127.0.0.1-8 080 13:44:59,397 INFO [AjpProtocol] Starting Coyote > AJP/1.3 on ajp-127.0.0.1-8009 13:44:59,459 INFO [ServerImpl] JBoss > (Microcontainer) [5.0.0.GA (build: SVNTag= JBoss_5_0_0_GA > date=200812041714)] Started in 1m:21s:233ms But Still I cant connect to It when I Type my IP address in my browser thanks

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  • What if Google’s ‘Project Glass’ Ran on Windows? [Funny Video]

    - by Asian Angel
    The tech sphere has been abuzz lately about Google’s new ‘Project Glass’, but what would happen if it ran on Windows? You can view the original ‘Project Glass’ video below… Windows Project Glass: One day too… [via Geeks are Sexy] How to Stress Test the Hard Drives in Your PC or Server How To Customize Your Android Lock Screen with WidgetLocker The Best Free Portable Apps for Your Flash Drive Toolkit

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  • Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 1

    - by rajbk
    The Open Data Protocol, referred to as OData, is a new data-sharing standard that breaks down silos and fosters an interoperative ecosystem for data consumers (clients) and producers (services) that is far more powerful than currently possible. It enables more applications to make sense of a broader set of data, and helps every data service and client add value to the whole ecosystem. WCF Data Services (previously known as ADO.NET Data Services), then, was the first Microsoft technology to support the Open Data Protocol in Visual Studio 2008 SP1. It provides developers with client libraries for .NET, Silverlight, AJAX, PHP and Java. Microsoft now also supports OData in SQL Server 2008 R2, Windows Azure Storage, Excel 2010 (through PowerPivot), and SharePoint 2010. Many other other applications in the works. * This post walks you through how to create an OData feed, define a shape for the data and pre-filter the data using Visual Studio 2010, WCF Data Services and the Entity Framework. A sample project is attached at the bottom of Part 2 of this post. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Create the Web Application File –› New –› Project, Select “ASP.NET Empty Web Application” Add the Entity Data Model Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “ADO.NET Entity Data Model” under "Data”. Name the Model “Northwind” and click “Add”.   In the “Choose Model Contents”, select “Generate Model From Database” and click “Next”   Define a connection to your database containing the Northwind database in the next screen. We are going to expose the Products table through our OData feed. Select “Products” in the “Choose your Database Object” screen.   Click “Finish”. We are done creating our Entity Data Model. Save the Northwind.edmx file created. Add the WCF Data Service Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “WCF Data Service” from the list and call the service “DataService” (creative, huh?). Click “Add”.   Enable Access to the Data Service Open the DataService.svc.cs class. The class is well commented and instructs us on the next steps. public class DataService : DataService< /* TODO: put your data source class name here */ > { // This method is called only once to initialize service-wide policies. public static void InitializeService(DataServiceConfiguration config) { // TODO: set rules to indicate which entity sets and service operations are visible, updatable, etc. // Examples: // config.SetEntitySetAccessRule("MyEntityset", EntitySetRights.AllRead); // config.SetServiceOperationAccessRule("MyServiceOperation", ServiceOperationRights.All); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } Replace the comment that starts with “/* TODO:” with “NorthwindEntities” (the entity container name of the Model we created earlier).  WCF Data Services is initially locked down by default, FTW! No data is exposed without you explicitly setting it. You have explicitly specify which Entity sets you wish to expose and what rights are allowed by using the SetEntitySetAccessRule. The SetServiceOperationAccessRule on the other hand sets rules for a specified operation. Let us define an access rule to expose the Products Entity we created earlier. We use the EnititySetRights.AllRead since we want to give read only access. Our modified code is shown below. public class DataService : DataService<NorthwindEntities> { public static void InitializeService(DataServiceConfiguration config) { config.SetEntitySetAccessRule("Products", EntitySetRights.AllRead); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } We are done setting up our ODataFeed! Compile your project. Right click on DataService.svc and select “View in Browser” to see the OData feed. To view the feed in IE, you must make sure that "Feed Reading View" is turned off. You set this under Tools -› Internet Options -› Content tab.   If you navigate to “Products”, you should see the Products feed. Note also that URIs are case sensitive. ie. Products work but products doesn’t.   Filtering our data OData has a set of system query operations you can use to perform common operations against data exposed by the model. For example, to see only Products in CategoryID 2, we can use the following request: /DataService.svc/Products?$filter=CategoryID eq 2 At the time of this writing, supported operations are $orderby, $top, $skip, $filter, $expand, $format†, $select, $inlinecount. Pre-filtering our data using Query Interceptors The Product feed currently returns all Products. We want to change that so that it contains only Products that have not been discontinued. WCF introduces the concept of interceptors which allows us to inject custom validation/policy logic into the request/response pipeline of a WCF data service. We will use a QueryInterceptor to pre-filter the data so that it returns only Products that are not discontinued. To create a QueryInterceptor, write a method that returns an Expression<Func<T, bool>> and mark it with the QueryInterceptor attribute as shown below. [QueryInterceptor("Products")] public Expression<Func<Product, bool>> OnReadProducts() { return o => o.Discontinued == false; } Viewing the feed after compilation will only show products that have not been discontinued. We also confirm this by looking at the WHERE clause in the SQL generated by the entity framework. SELECT [Extent1].[ProductID] AS [ProductID], ... ... [Extent1].[Discontinued] AS [Discontinued] FROM [dbo].[Products] AS [Extent1] WHERE 0 = [Extent1].[Discontinued] Other examples of Query/Change interceptors can be seen here including an example to filter data based on the identity of the authenticated user. We are done pre-filtering our data. In the next part of this post, we will see how to shape our data. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Foot Notes * http://msdn.microsoft.com/en-us/data/aa937697.aspx † $format did not work for me. The way to get a Json response is to include the following in the  request header “Accept: application/json, text/javascript, */*” when making the request. This is easily done with most JavaScript libraries.

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  • Visual Studio 2010 Zooming – Keyboard Commands, Global Zoom

    - by Jon Galloway
    One of my favorite features in Visual Studio 2010 is zoom. It first caught my attention as a useful tool for screencasts and presentations, but after getting used to it I’m finding that it’s really useful when I’m developing – letting me zoom out to see the big picture, then zoom in to concentrate on a few lines of code. Zooming without the scroll wheel The common way you’ll see this feature demonstrated is with the mouse wheel – you hold down the control key and scroll up or down to change font size. However, I’m often using this on my laptop, which doesn’t have a mouse wheel. It turns out that there are other ways to control zooming in Visual Studio 2010. Keyboard commands You can use Control+Shift+Comma to zoom out and Control+Shift+Period to zoom in. I find it’s easier to remember these by the greater-than / less-than signs, so it’s really Control+> to zoom in and Control+< to zoom out. Like most Visual Studio commands, you can change those the keyboard buttons. In the tools menu, select Options / Keyboard, then either scroll down the list to the three View.Zoom commands or filter by typing View.Zoom into the “Show commands containing” textbox. The Scroll Dropdown If you forget the keyboard commands and you don’t have a scroll wheel, there’s a zoom menu in the text editor. I’m mostly pointing it out because I’ve been using Visual Studio 2010 for months and never noticed it until this week. It’s down in the lower left corner. Keeping Zoom In Sync Across All Tabs Zoom setting is per-tab, which is a problem if you’re cranking up your font sizes for a presentation. Fortunately there’s a great new Visual Studio Extension called Presentation Zoom. It’s a nice, simple extension that just does one thing – updates all your editor windows to keep the zoom setting in sync. It’s written by Chris Granger, a Visual Studio Program Manager, in case you’re worried about installing random extensions. See it in action Of course, if you’ve got Visual Studio 2010 installed, you’ve hopefully already been zooming like mad as you read this. If not, you can watch a 2 minute video by the Visual Studio showing it off.

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  • Show Your Mac Love with the Simply Apple Theme for Windows 7

    - by Asian Angel
    Are you a huge fan of Apple products and ready to show some Mac love on your desktop? Then this is the theme for you. The theme comes with 30 Hi-Res wallpapers, custom icons, sounds, and a set of cursors to complete the package. View Additional Screenshots of the Theme [VikiTech] Download the Theme [VikiTech] Use Amazon’s Barcode Scanner to Easily Buy Anything from Your Phone How To Migrate Windows 7 to a Solid State Drive Follow How-To Geek on Google+

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  • Improving Partitioned Table Join Performance

    - by Paul White
    The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • Setup Reverse DNS with Cpanel and WHM?

    - by m3d
    I needed to set-up a reverse DNS via cpanel. I followed the steps in this tutorial but it didn't work: http://docs.cpanel.net/twiki/bin/view/11_30/WHMDocs/RdnsForBind. I use my own name servers registered with go-daddy. But I am with VPS hosting company. I did use a new serial number and exactly as the tutorial however didnt seems to be working When I check this via windows nslookup {ip-address} I still get the my hosting company name, when reversed.

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  • C#/.NET Little Wonders: The Concurrent Collections (1 of 3)

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In the next few weeks, we will discuss the concurrent collections and how they have changed the face of concurrent programming. This week’s post will begin with a general introduction and discuss the ConcurrentStack<T> and ConcurrentQueue<T>.  Then in the following post we’ll discuss the ConcurrentDictionary<T> and ConcurrentBag<T>.  Finally, we shall close on the third post with a discussion of the BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. A brief history of collections In the beginning was the .NET 1.0 Framework.  And out of this framework emerged the System.Collections namespace, and it was good.  It contained all the basic things a growing programming language needs like the ArrayList and Hashtable collections.  The main problem, of course, with these original collections is that they held items of type object which means you had to be disciplined enough to use them correctly or you could end up with runtime errors if you got an object of a type you weren't expecting. Then came .NET 2.0 and generics and our world changed forever!  With generics the C# language finally got an equivalent of the very powerful C++ templates.  As such, the System.Collections.Generic was born and we got type-safe versions of all are favorite collections.  The List<T> succeeded the ArrayList and the Dictionary<TKey,TValue> succeeded the Hashtable and so on.  The new versions of the library were not only safer because they checked types at compile-time, in many cases they were more performant as well.  So much so that it's Microsoft's recommendation that the System.Collections original collections only be used for backwards compatibility. So we as developers came to know and love the generic collections and took them into our hearts and embraced them.  The problem is, thread safety in both the original collections and the generic collections can be problematic, for very different reasons. Now, if you are only doing single-threaded development you may not care – after all, no locking is required.  Even if you do have multiple threads, if a collection is “load-once, read-many” you don’t need to do anything to protect that container from multi-threaded access, as illustrated below: 1: public static class OrderTypeTranslator 2: { 3: // because this dictionary is loaded once before it is ever accessed, we don't need to synchronize 4: // multi-threaded read access 5: private static readonly Dictionary<string, char> _translator = new Dictionary<string, char> 6: { 7: {"New", 'N'}, 8: {"Update", 'U'}, 9: {"Cancel", 'X'} 10: }; 11:  12: // the only public interface into the dictionary is for reading, so inherently thread-safe 13: public static char? Translate(string orderType) 14: { 15: char charValue; 16: if (_translator.TryGetValue(orderType, out charValue)) 17: { 18: return charValue; 19: } 20:  21: return null; 22: } 23: } Unfortunately, most of our computer science problems cannot get by with just single-threaded applications or with multi-threading in a load-once manner.  Looking at  today's trends, it's clear to see that computers are not so much getting faster because of faster processor speeds -- we've nearly reached the limits we can push through with today's technologies -- but more because we're adding more cores to the boxes.  With this new hardware paradigm, it is even more important to use multi-threaded applications to take full advantage of parallel processing to achieve higher application speeds. So let's look at how to use collections in a thread-safe manner. Using historical collections in a concurrent fashion The early .NET collections (System.Collections) had a Synchronized() static method that could be used to wrap the early collections to make them completely thread-safe.  This paradigm was dropped in the generic collections (System.Collections.Generic) because having a synchronized wrapper resulted in atomic locks for all operations, which could prove overkill in many multithreading situations.  Thus the paradigm shifted to having the user of the collection specify their own locking, usually with an external object: 1: public class OrderAggregator 2: { 3: private static readonly Dictionary<string, List<Order>> _orders = new Dictionary<string, List<Order>>(); 4: private static readonly _orderLock = new object(); 5:  6: public void Add(string accountNumber, Order newOrder) 7: { 8: List<Order> ordersForAccount; 9:  10: // a complex operation like this should all be protected 11: lock (_orderLock) 12: { 13: if (!_orders.TryGetValue(accountNumber, out ordersForAccount)) 14: { 15: _orders.Add(accountNumber, ordersForAccount = new List<Order>()); 16: } 17:  18: ordersForAccount.Add(newOrder); 19: } 20: } 21: } Notice how we’re performing several operations on the dictionary under one lock.  With the Synchronized() static methods of the early collections, you wouldn’t be able to specify this level of locking (a more macro-level).  So in the generic collections, it was decided that if a user needed synchronization, they could implement their own locking scheme instead so that they could provide synchronization as needed. The need for better concurrent access to collections Here’s the problem: it’s relatively easy to write a collection that locks itself down completely for access, but anything more complex than that can be difficult and error-prone to write, and much less to make it perform efficiently!  For example, what if you have a Dictionary that has frequent reads but in-frequent updates?  Do you want to lock down the entire Dictionary for every access?  This would be overkill and would prevent concurrent reads.  In such cases you could use something like a ReaderWriterLockSlim which allows for multiple readers in a lock, and then once a writer grabs the lock it blocks all further readers until the writer is done (in a nutshell).  This is all very complex stuff to consider. Fortunately, this is where the Concurrent Collections come in.  The Parallel Computing Platform team at Microsoft went through great pains to determine how to make a set of concurrent collections that would have the best performance characteristics for general case multi-threaded use. Now, as in all things involving threading, you should always make sure you evaluate all your container options based on the particular usage scenario and the degree of parallelism you wish to acheive. This article should not be taken to understand that these collections are always supperior to the generic collections. Each fills a particular need for a particular situation. Understanding what each container is optimized for is key to the success of your application whether it be single-threaded or multi-threaded. General points to consider with the concurrent collections The MSDN points out that the concurrent collections all support the ICollection interface. However, since the collections are already synchronized, the IsSynchronized property always returns false, and SyncRoot always returns null.  Thus you should not attempt to use these properties for synchronization purposes. Note that since the concurrent collections also may have different operations than the traditional data structures you may be used to.  Now you may ask why they did this, but it was done out of necessity to keep operations safe and atomic.  For example, in order to do a Pop() on a stack you have to know the stack is non-empty, but between the time you check the stack’s IsEmpty property and then do the Pop() another thread may have come in and made the stack empty!  This is why some of the traditional operations have been changed to make them safe for concurrent use. In addition, some properties and methods in the concurrent collections achieve concurrency by creating a snapshot of the collection, which means that some operations that were traditionally O(1) may now be O(n) in the concurrent models.  I’ll try to point these out as we talk about each collection so you can be aware of any potential performance impacts.  Finally, all the concurrent containers are safe for enumeration even while being modified, but some of the containers support this in different ways (snapshot vs. dirty iteration).  Once again I’ll highlight how thread-safe enumeration works for each collection. ConcurrentStack<T>: The thread-safe LIFO container The ConcurrentStack<T> is the thread-safe counterpart to the System.Collections.Generic.Stack<T>, which as you may remember is your standard last-in-first-out container.  If you think of algorithms that favor stack usage (for example, depth-first searches of graphs and trees) then you can see how using a thread-safe stack would be of benefit. The ConcurrentStack<T> achieves thread-safe access by using System.Threading.Interlocked operations.  This means that the multi-threaded access to the stack requires no traditional locking and is very, very fast! For the most part, the ConcurrentStack<T> behaves like it’s Stack<T> counterpart with a few differences: Pop() was removed in favor of TryPop() Returns true if an item existed and was popped and false if empty. PushRange() and TryPopRange() were added Allows you to push multiple items and pop multiple items atomically. Count takes a snapshot of the stack and then counts the items. This means it is a O(n) operation, if you just want to check for an empty stack, call IsEmpty instead which is O(1). ToArray() and GetEnumerator() both also take snapshots. This means that iteration over a stack will give you a static view at the time of the call and will not reflect updates. Pushing on a ConcurrentStack<T> works just like you’d expect except for the aforementioned PushRange() method that was added to allow you to push a range of items concurrently. 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: // but you can also push multiple items in one atomic operation (no interleaves) 7: stack.PushRange(new [] { "Second", "Third", "Fourth" }); For looking at the top item of the stack (without removing it) the Peek() method has been removed in favor of a TryPeek().  This is because in order to do a peek the stack must be non-empty, but between the time you check for empty and the time you execute the peek the stack contents may have changed.  Thus the TryPeek() was created to be an atomic check for empty, and then peek if not empty: 1: // to look at top item of stack without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (stack.TryPeek(out item)) 5: { 6: Console.WriteLine("Top item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Stack was empty."); 11: } Finally, to remove items from the stack, we have the TryPop() for single, and TryPopRange() for multiple items.  Just like the TryPeek(), these operations replace Pop() since we need to ensure atomically that the stack is non-empty before we pop from it: 1: // to remove items, use TryPop or TryPopRange to get multiple items atomically (no interleaves) 2: if (stack.TryPop(out item)) 3: { 4: Console.WriteLine("Popped " + item); 5: } 6:  7: // TryPopRange will only pop up to the number of spaces in the array, the actual number popped is returned. 8: var poppedItems = new string[2]; 9: int numPopped = stack.TryPopRange(poppedItems); 10:  11: foreach (var theItem in poppedItems.Take(numPopped)) 12: { 13: Console.WriteLine("Popped " + theItem); 14: } Finally, note that as stated before, GetEnumerator() and ToArray() gets a snapshot of the data at the time of the call.  That means if you are enumerating the stack you will get a snapshot of the stack at the time of the call.  This is illustrated below: 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: var results = stack.GetEnumerator(); 7:  8: // but you can also push multiple items in one atomic operation (no interleaves) 9: stack.PushRange(new [] { "Second", "Third", "Fourth" }); 10:  11: while(results.MoveNext()) 12: { 13: Console.WriteLine("Stack only has: " + results.Current); 14: } The only item that will be printed out in the above code is "First" because the snapshot was taken before the other items were added. This may sound like an issue, but it’s really for safety and is more correct.  You don’t want to enumerate a stack and have half a view of the stack before an update and half a view of the stack after an update, after all.  In addition, note that this is still thread-safe, whereas iterating through a non-concurrent collection while updating it in the old collections would cause an exception. ConcurrentQueue<T>: The thread-safe FIFO container The ConcurrentQueue<T> is the thread-safe counterpart of the System.Collections.Generic.Queue<T> class.  The concurrent queue uses an underlying list of small arrays and lock-free System.Threading.Interlocked operations on the head and tail arrays.  Once again, this allows us to do thread-safe operations without the need for heavy locks! The ConcurrentQueue<T> (like the ConcurrentStack<T>) has some departures from the non-concurrent counterpart.  Most notably: Dequeue() was removed in favor of TryDequeue(). Returns true if an item existed and was dequeued and false if empty. Count does not take a snapshot It subtracts the head and tail index to get the count.  This results overall in a O(1) complexity which is quite good.  It’s still recommended, however, that for empty checks you call IsEmpty instead of comparing Count to zero. ToArray() and GetEnumerator() both take snapshots. This means that iteration over a queue will give you a static view at the time of the call and will not reflect updates. The Enqueue() method on the ConcurrentQueue<T> works much the same as the generic Queue<T>: 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5: queue.Enqueue("Second"); 6: queue.Enqueue("Third"); For front item access, the TryPeek() method must be used to attempt to see the first item if the queue.  There is no Peek() method since, as you’ll remember, we can only peek on a non-empty queue, so we must have an atomic TryPeek() that checks for empty and then returns the first item if the queue is non-empty. 1: // to look at first item in queue without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (queue.TryPeek(out item)) 5: { 6: Console.WriteLine("First item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Queue was empty."); 11: } Then, to remove items you use TryDequeue().  Once again this is for the same reason we have TryPeek() and not Peek(): 1: // to remove items, use TryDequeue. If queue is empty returns false. 2: if (queue.TryDequeue(out item)) 3: { 4: Console.WriteLine("Dequeued first item " + item); 5: } Just like the concurrent stack, the ConcurrentQueue<T> takes a snapshot when you call ToArray() or GetEnumerator() which means that subsequent updates to the queue will not be seen when you iterate over the results.  Thus once again the code below will only show the first item, since the other items were added after the snapshot. 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5:  6: var iterator = queue.GetEnumerator(); 7:  8: queue.Enqueue("Second"); 9: queue.Enqueue("Third"); 10:  11: // only shows First 12: while (iterator.MoveNext()) 13: { 14: Console.WriteLine("Dequeued item " + iterator.Current); 15: } Using collections concurrently You’ll notice in the examples above I stuck to using single-threaded examples so as to make them deterministic and the results obvious.  Of course, if we used these collections in a truly multi-threaded way the results would be less deterministic, but would still be thread-safe and with no locking on your part required! For example, say you have an order processor that takes an IEnumerable<Order> and handles each other in a multi-threaded fashion, then groups the responses together in a concurrent collection for aggregation.  This can be done easily with the TPL’s Parallel.ForEach(): 1: public static IEnumerable<OrderResult> ProcessOrders(IEnumerable<Order> orderList) 2: { 3: var proxy = new OrderProxy(); 4: var results = new ConcurrentQueue<OrderResult>(); 5:  6: // notice that we can process all these in parallel and put the results 7: // into our concurrent collection without needing any external locking! 8: Parallel.ForEach(orderList, 9: order => 10: { 11: var result = proxy.PlaceOrder(order); 12:  13: results.Enqueue(result); 14: }); 15:  16: return results; 17: } Summary Obviously, if you do not need multi-threaded safety, you don’t need to use these collections, but when you do need multi-threaded collections these are just the ticket! The plethora of features (I always think of the movie The Three Amigos when I say plethora) built into these containers and the amazing way they acheive thread-safe access in an efficient manner is wonderful to behold. Stay tuned next week where we’ll continue our discussion with the ConcurrentBag<T> and the ConcurrentDictionary<TKey,TValue>. For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here.   Tweet Technorati Tags: C#,.NET,Concurrent Collections,Collections,Multi-Threading,Little Wonders,BlackRabbitCoder,James Michael Hare

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  • Xobni Free Powers Up Outlook’s Search and Contacts

    - by Matthew Guay
    Want to find out more about your contacts, discover email trends, and even sync Yahoo! email accounts in Outlook?  Here’s how you can do this and more with Xobni Free. Email is one of the most important communications mediums today, but even with all of the advances in Outlook over the years it can still be difficult to keep track of conversations, files, and contacts.  Xobni makes it easy by indexing your emails and organizing them by sender.  You can use its powerful search to quickly find any email, find related messages, and then view more information about that contact with information from social networks.  And, to top it off, it even lets you view your Yahoo! emails directly in Outlook without upgrading to a Yahoo! Plus account.  Xobni runs in Outlook 2003, 2007, and 2010, including the 64 bit version of Outlook 2010, and users of older versions will especially enjoy the new features Xobni brings for free. Getting started Download the Xobni Free installer (link below), and run to start the installation.  Make sure to exit Outlook before installing.  Xobni may need to download additional files which may take a few moments. When the download is finished, proceed with the install as normal.  You can opt out of the Product Improvement Program at the end of the installation by unchecking the box.  Additionally, you are asked to share Xobni with your friends on social networks, but this is not required.   Next time you open Outlook, you’ll notice the new Xobni sidebar in Outlook.  You can choose to watch an introduction video that will help you quickly get up to speed on how Xobni works. While this is playing, Xobni is working at indexing your email in the background.  Once the first indexing is finished, click Let’s Go! to start using Xobni. Here’s how Xobni looks in Outlook 2010: Advanced Email Information Select an email, and now you can see lots of info about it in your new Xobni sidebar.   On the top of the sidebar, select the graph icon to see when and how often you email with a contact.  Each contact is given an Xobni rank so you can quickly see who you email the most.   You can see all related emails sorted into conversations, and also all attachments in the conversation, not just this email. Xobni can also show you all scheduled appointments and links exchanged with a contact, but this is only available in the Plus version.  If you’d rather not see the tab for a feature you can’t use, click Don’t show this tab to banish it from Xobni for good.   Searching emails from the Xobni toolbar is very fast, and you can preview a message by simply hovering over it from the search pane. Get More Information About Your Contacts Xobni’s coolest feature is its social integration.  Whenever you select an email, you may see a brief bio, picture, and more, all pulled from social networks.   Select one of the tabs to find more information.  You may need to login to view information on your contacts from certain networks. The Twitter tab lets you see recent tweets.  Xobni will search for related Twitter accounts, and will ask you to confirm if the choice is correct.   Now you can see this contact’s recent Tweets directly from Outlook.   The Hoovers tab can give you interesting information about the businesses you’re in contact with. If the information isn’t correct, you can edit it and add your own information.  Click the Edit button, and the add any information you want.   You can also remove a network you don’t wish to see.  Right-click on the network tabs, select Manage Extensions, and uncheck any you don’t want to see. But sometimes online contact just doesn’t cut it.  For these times, click on the orange folder button to request a contact’s phone number or schedule a time with them. This will open a new email message ready to send with the information you want.  Edit as you please, and send. Add Yahoo! Email to Outlook for Free One of Xobni’s neatest features is that it let’s you add your Yahoo! email account to Outlook for free.  Click the gear icon in the bottom of the Xobni sidebar and select Options to set it up. Select the Integration tab, and click Enable to add Yahoo! mail to Xobni. Sign in with your Yahoo! account, and make sure to check the Keep me signed in box. Note that you may have to re-signin every two weeks to keep your Yahoo! account connected.  Select I agree to finish setting it up. Xobni will now download and index your recent Yahoo! mail. Your Yahoo! messages will only show up in the Xobni sidebar.  Whenever you select a contact, you will see related messages from your Yahoo! account as well.  Or, you can search from the sidebar to find individual messages from your Yahoo! account.  Note the Y! logo beside Yahoo! messages.   Select a message to read it in the Sidebar.  You can open the email in Yahoo! in your browser, or can reply to it using your default Outlook email account. If you have many older messages in your Yahoo! account, make sure to go back to the Integration tab and select Index Yahoo! Mail to index all of your emails. Conclusion Xobni is a great tool to help you get more out of your daily Outlook experience.  Whether you struggle to find attachments a coworker sent you or want to access Yahoo! email from Outlook, Xobni might be the perfect tool for you.  And with the extra things you learn about your contacts with the social network integration, you might boost your own PR skills without even trying! Link Download Xobni Similar Articles Productive Geek Tips Speed up Windows Vista Start Menu Search By Limiting ResultsFix for New Contact Group Button Not Displaying in VistaGet Maps and Directions to Your Contacts in Outlook 2007Backup Windows Mail Messages and Contacts in VistaHow to Import Gmail Contacts Into Outlook 2007 TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Acronis Online Backup DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows iFixit Offers Gadget Repair Manuals Online Vista style sidebar for Windows 7 Create Nice Charts With These Web Based Tools Track Daily Goals With 42Goals Video Toolbox is a Superb Online Video Editor Fun with 47 charts and graphs

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  • iPad client for SharePoint

    - by gabouy
    I´m pleased to announce that at SouthLabs we´ve released a native iPad client for SharePoint , called SharePlus Office Mobile Client , already available in the app store . It consumes SharePoint's web services API, and supports offline browsing. The following is a brief presentation on it, with some screenshots. SharePlus iPad client for SharePoint View more presentations from SouthLabs ....(read more)

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  • Hey, Google: It’s Time to Add Multi-Window Multitasking To Android

    - by Chris Hoffman
    In 2012, Google’s Dianne Hackborn threatened to revoke CyanogenMod’s access to the Android Market if they moved forward with adding “Cornerstone” multitasking to their custom ROM. Samsung has since created their own multi-window multitasking feature. Dianne Hackborn said this “is something that needs to be done at the mainline platform level” so apps wouldn’t break. She was right — Android needs this as a standard feature and it’s time for Google to provide it. Doesn’t Android Have Multitasking? Android originally stood out from Apple’s iOS with its powerful multitasking. Applications can continue running in the background while you’re using another application. This makes Android powerful — you can even have BitTorrent clients downloading files in the background while using another app. Android still kept the design of a single app on screen at a time. This made a lot of sense when Android only ran on smartphones with small screens. Today, Android runs on everything from smaller smartphones all the way up to huge “phablets” like the Galaxy Note. Android has gone beyond phones and runs on 12-inch tablets, convertibles with keyboard docks, laptops, and even Android desktops. Android isn’t just a phone operating system. Samsung’s Multi-Window Isn’t Good Enough Samsung has tried to add value to Android by adding a multi-window feature. When you’re using a high-end phone like the Galaxy Note or Galaxy S, or a Galaxy tablet, you have the ability to run certain apps side-by-side with each other. There are big problems here. This only works on Samsung devices, and only on specific Samsung devices. To add support for this feature in a way that doesn’t break other apps, Samsung’s multi-window feature also only works with specific apps. You can’t just run any app in multi-window view, only the apps on the Multi Window bar Samsung provides. This prevents third-party apps from breaking, which is what Google was worried about with CyanogenMod’s Cornerstone feature. A feature that only works with a handful of apps on specific devices from a single manufacturer isn’t good enough. This feature needs to work on every Android device — or at least ones with suitably large screens and powerful enough internals. It needs to be an Android platform feature so application developers can ensure their apps will work properly with it on every device. Android developers shouldn’t have to add support for each manufacturer’s own multi-window feature if other manufacturers decide to copy Samsung. Floating Apps Are a Dirty Hack Floating apps also enable real multitasking. Remember that Android allows apps to run in the background while you’re using an app in the foreground. These apps can present interfaces that appear floating above the current app — think of it like using “always on top” to make a window always appear over every other app on a desktop operating system. You can install floating apps to browse the web, take notes, chat, and watch videos while using any app. Only apps specifically designed to run as floating apps will work, so you have to seek them out. Floating apps are also awkward to use because they float over the app you’re using, blocking parts of its interface. Microsoft added floating-window support to Skype for Android. You can have a video conversation and the other person’s face will always appear on your screen, even when you leave the Skype app. Microsoft is using more of Android’s multi-window multitasking power than Google is. Custom ROMs and Root-Only Tweaks Aren’t Acceptable Some custom ROMs are adding this feature to Android. Google threatened to revoke CyanogenMod’s access to the Android Market (now known as Google Play) if they added this feature because it could potentially break third-party apps. Today, other custom ROMs are working on split-screen multitasking. Samsung added their own version to their own devices. You can also get this feature by using a root-only Xposed Framework tweak known as XMultiWindow. If you have root access, you can get multi-window multitasking or any app on your device. This shouldn’t require rooting your device or installing a custom ROM. These third-party solutions often have awkward interfaces and bugs. We need an integrated, supported solution that works the same on every device. Why Multi-Window is Important Microsoft’s Windows 8.1 stands out among tablet operating systems for its powerful multitasking support, allowing you to view several apps side-by-side at the same time. Apple is also reported to be working on adding side-by-side apps to the iPad with iOS 8. On every competitor’s operating system, you’ll be able to view a web page while you write an email, watch a video while you browse the web, or chat with someone while you do anything else. But Android’s still remained frozen in time. Despite all Android’s underlying power — and despite the way Android allows apps to adapt to different screen sizes — Google is resisting adding this feature. Large-screen Android tablets like the Nexus 10 (remember that tablet Google hasn’t updated in over 18 months?) need this feature. So do huge phones, convertibles, laptops, and Android desktops. If tablets are the future of personal computing, we should be able to do more than one thing at a time on our tablets’ big screens. Microsoft, Samsung, and even Apple are realizing this — now it’s Google’s turn. Image Credit: Sergey Galyonkin on Flickr, Karlis Dambrans on Flickr

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  • Daily tech links for .net and related technologies - Apr 26-28, 2010

    - by SanjeevAgarwal
    Daily tech links for .net and related technologies - Apr 26-28, 2010 Web Development MVC: Unit Testing Action Filters - Donn ASP.NET MVC 2: Ninja Black Belt Tips - Scott Hanselman Turn on Compile-time View Checking for ASP.NET MVC Projects in TFS Build 2010 - Jim Lamb Web Design List of 25+ New tags introduced in HTML 5 - techfreakstuff 15 CSS Habits to Develop for Frustration-Free Coding - noupe Silverlight, WPF & RIA Essential Silverlight and WPF Skills: The UI Thread, Dispatchers, Background...(read more)

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  • Slides and Code from my Silverlight MVVM Talk at DevConnections

    - by dwahlin
    I had a great time at the DevConnections conference in Las Vegas this year where Visual Studio 2010 and Silverlight 4 were launched. While at the conference I had the opportunity to give a full-day Silverlight workshop as well as 4 different talks and met a lot of people developing applications in Silverlight. I also had a chance to appear on a live broadcast of Channel 9 with John Papa, Ward Bell and Shawn Wildermuth, record a video with Rick Strahl covering jQuery versus Silverlight and record a few podcasts on Silverlight and ASP.NET MVC 2.  It was a really busy 4 days but I had a lot of fun chatting with people and hearing about different business problems they were solving with ASP.NET and/or Silverlight. Thanks to everyone who attended my sessions and took the time to ask questions and stop by to talk one-on-one. One of the talks I gave covered the Model-View-ViewModel pattern and how it can be used to build architecturally sound applications. Topics covered in the talk included: Understanding the MVVM pattern Benefits of the MVVM pattern Creating a ViewModel class Implementing INotifyPropertyChanged in a ViewModelBase class Binding a ViewModel declaratively in XAML Binding a ViewModel with code ICommand and ButtonBase commanding support in Silverlight 4 Using InvokeCommandBehavior to handle additional commanding needs Working with ViewModels and Sample Data in Blend Messaging support with EventBus classes, EventAggregator and Messenger My personal take on code in a code-beside file (I’m all in favor of it when used appropriately for message boxes, child windows, animations, etc.) One of the samples I showed in the talk was intended to teach all of the concepts mentioned above while keeping things as simple as possible.  The sample demonstrates quite a few things you can do with Silverlight and the MVVM pattern so check it out and feel free to leave feedback about things you like, things you’d do differently or anything else. MVVM is simply a pattern, not a way of life so there are many different ways to implement it. If you’re new to the subject of MVVM check out the following resources. I wish this talk would’ve been recorded (especially since my live and canned demos all worked :-)) but these resources will help get you going quickly. Getting Started with the MVVM Pattern in Silverlight Applications Model-View-ViewModel (MVVM) Explained Laurent Bugnion’s Excellent Talk at MIX10     Download sample code and slides from my DevConnections talk     For more information about onsite, online and video training, mentoring and consulting solutions for .NET, SharePoint or Silverlight please visit http://www.thewahlingroup.com.

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  • ASP.NET MVC Case Studies

    - by shiju
     The below are the some of the case studies of ASP.NET MVC Jwaala - Online Banking Solution Benefits after ASP.NET MVC Replaces Ruby on Rails, Linux http://www.microsoft.com/casestudies/Case_Study_Detail.aspx?casestudyid=4000006675 Stack Overflow - Developers See Faster Web Coding, Better Performance with Model-View-Controller http://www.microsoft.com/casestudies/Case_Study_Detail.aspx?casestudyid=4000006676 Kelley Blue Book - Pioneer Provider of Vehicle-Pricing Information Uses Technology to Expand Reach http://www.microsoft.com/casestudies/Case_Study_Detail.aspx?casestudyid=4000006272 

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