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  • jQuery: How to find elements *without* a class set

    - by Alan
    Hey jQuery clever peeps, Why does this fail... $( 'div.contactAperson input' ).not( 'input.hadFocus' ).focus(function() { $(this).attr('value', '' ); }); ...it's meant to sniff out input's that have not got the class .hadFocus and then when one of that subset receives focus it should zap the value to null. Right now, input values are always getting zapped -- the test .not( 'input.hadFocus' ) is failing to stop execution. Btw, preceding the above code is the following code, which is working fine: $( 'div.contactAperson input' ).focus(function() { $( this ).addClass( 'hadFocus' ); }); Thanks for any cleverness - cheers, -Alan

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  • Cannot Start Nginx Compiled from Source

    - by Jason Alan Kennedy
    I am trying to compile Nginx from source based on the original compiled Nginx server running on my DigitalOcean server ( Ubuntu-14.04 64x ) but with a few extra modules. I can get everything installed smoothly but I can not get it to start. I am sure the ini is correct because I copied the original source off the current running Nginx server [ Even though I see that Nginx now adds the ini when compiling fron source ]. Below is the [ lengthy process ] that I am performing - add sorry but I wanted to be thorough for those who are in need of the info ]. Because I am a newB to Nginx, I am sure I am missing something or just have it all wrong. If you may look over what I have done and see if you spot anything I need/need to change, I will greatly appreciate it. Thnx! With the original Nginx server still running: I check the current/running Nginx configuration so I can build the new Nginx instance the same but with the added modules: nginx -V # The out-put: configure arguments: --with-cc-opt='-g -O2 -fstack-protector --param=ssp-buffer-size=4 -Wformat -Werror=format-security -D_FORTIFY_SOURCE=2' --with-ld-opt='-Wl,-Bsymbolic-functions -Wl,-z,relro' --prefix=/usr/share/nginx --conf-path=/etc/nginx/nginx.conf --http-log-path=/var/log/nginx/access.log --error-log-path=/var/log/nginx/error.log --lock-path=/var/lock/nginx.lock --pid-path=/run/nginx.pid --http-client-body-temp-path=/var/lib/nginx/body --http-fastcgi-temp-path=/var/lib/nginx/fastcgi --http-proxy-temp-path=/var/lib/nginx/proxy --http-scgi-temp-path=/var/lib/nginx/scgi --http-uwsgi-temp-path=/var/lib/nginx/uwsgi --with-debug --with-pcre-jit --with-ipv6 --with-http_ssl_module --with-http_stub_status_module --with-http_realip_module --with-http_addition_module --with-http_dav_module --with-http_geoip_module --with-http_gzip_static_module --with-http_image_filter_module --with-http_spdy_module --with-http_sub_module --with-http_xslt_module NOTE: The configure arguments below return errors during 'make' so I removed them. I don't know what they are - could this be related to my issue??? --with-cc-opt='-g -O2 -fstack-protector --param=ssp-buffer-size=4 -Wformat -Werror=format-security -D_FORTIFY_SOURCE=2' --with-ld-opt='-Wl,-Bsymbolic-functions -Wl,-z,relro' Moving on: # So I don't have to sudo every line: sudo bash # Check for updates first thing: apt-get update # Install various prerequisites needed to compile Nginx: apt-get install build-essential libgd2-xpm-dev lsb-base zlib1g-dev libpcre3 libpcre3-dev libbz2-dev libxslt1-dev libxml2 libssl-dev libgeoip-dev tar unzip openssl # Create System users [ if it doesn't exist - but I see its there on DigitalOceans' Droplets all-ready ]: adduser --system --no-create-home --disabled-login --disabled-password --group www-data # Download NGINX wget http://nginx.org/download/nginx-1.7.4.tar.gz tar -xvzf nginx-1.7.4.tar.gz # Then Google PageSpeed: wget https://github.com/pagespeed/ngx_pagespeed/archive/release-1.8.31.4-beta.zip unzip release-1.8.31.4-beta.zip # cd into the PageSpeed Directory cd ngx_pagespeed-release-1.8.31.4-beta/ # and add the PSOL files in there: wget https://dl.google.com/dl/page-speed/psol/1.8.31.4.tar.gz tar -xzvf 1.8.31.4.tar.gz # Get back to the root directory: cd # I add the ngx_cache_purge module and will install the Nginx Helper plugin for WP later: wget https://github.com/FRiCKLE/ngx_cache_purge/archive/2.1.zip unzip 2.1.zip # Add the headers-more-nginx-module: wget https://github.com/openresty/headers-more-nginx-module/archive/v0.25.zip unzip v0.25.zip # and the naxsi module for added security: wget https://github.com/nbs-system/naxsi/archive/0.53-2.tar.gz tar -xvzf 0.53-2.tar.gz # cd to the new Nginx directory cd nginx-1.7.4 # Set up the configuration build based on the current running Nginx config args and add my additional modules: ./configure \ --add-module=$HOME/naxsi-0.53-2/naxsi_src \ --prefix=/usr/share/nginx \ --conf-path=/etc/nginx/nginx.conf \ --http-log-path=/var/log/nginx/access.log \ --error-log-path=/var/log/nginx/error.log \ --lock-path=/var/lock/nginx.lock \ --pid-path=/run/nginx.pid \ --http-client-body-temp-path=/var/lib/nginx/body \ --http-fastcgi-temp-path=/var/lib/nginx/fastcgi \ --http-proxy-temp-path=/var/lib/nginx/proxy \ --http-scgi-temp-path=/var/lib/nginx/scgi \ --http-uwsgi-temp-path=/var/lib/nginx/uwsgi \ --user=www-data \ --group=www-data \ --with-debug \ --with-pcre-jit \ --with-ipv6 \ --with-http_ssl_module \ --with-http_stub_status_module \ --with-http_realip_module \ --with-http_addition_module \ --with-http_dav_module \ --with-http_geoip_module \ --with-http_gzip_static_module \ --with-http_image_filter_module \ --with-http_spdy_module \ --with-http_sub_module \ --with-http_xslt_module \ --with-mail \ --with-mail_ssl_module \ --add-module=$HOME/ngx_pagespeed-release-1.8.31.4-beta \ --add-module=$HOME/ngx_cache_purge-2.1 \ --add-module=$HOME/headers-more-nginx-module-0.25 [ENTER] Configuration Summary: Configuration summary + using system PCRE library + using system OpenSSL library + md5: using OpenSSL library + sha1: using OpenSSL library + using system zlib library nginx path prefix: "/usr/share/nginx" nginx binary file: "/usr/share/nginx/sbin/nginx" nginx configuration prefix: "/etc/nginx" nginx configuration file: "/etc/nginx/nginx.conf" nginx pid file: "/run/nginx.pid" nginx error log file: "/var/log/nginx/error.log" nginx http access log file: "/var/log/nginx/access.log" nginx http client request body temporary files: "/var/lib/nginx/body" nginx http proxy temporary files: "/var/lib/nginx/proxy" nginx http fastcgi temporary files: "/var/lib/nginx/fastcgi" nginx http uwsgi temporary files: "/var/lib/nginx/uwsgi" nginx http scgi temporary files: "/var/lib/nginx/scgi" Next step: I cd to root and I check the old Nginx folder locations and double checked the 'make' output to see that they are the same: whereis nginx #Output: nginx: /usr/sbin/nginx /etc/nginx /usr/share/nginx NOTE: Not sure about the '/usr/sbin/nginx' - Possible issue??? Next I copy the old /etc/nginx/nginx.conf, /etc/nginx/sites-available/default, /etc/nginx/sites-enabled/default, /etc/init.d/nginx to a text file locally for safe keeping to use in the new Nginx server. Then stop the running Nginx server: service nginx stop , verify it's stopped: service --status-all and the output is: [ - ] nginx To verify that there are two Nginx directories, I cd to: cd nginx* and the output is an error indicating there are two nginx folders - Cool Beans! :) Now Install the new Nginx server: cd nginx-1.7.4 make install # INSTALL OUTPUT ######################################## make -f objs/Makefile install make[1]: Entering directory `/home/walkingfish/nginx-1.7.4' test -d '/usr/share/nginx' || mkdir -p '/usr/share/nginx' test -d '/usr/share/nginx/sbin' || mkdir -p '/usr/share/nginx/sbin' test ! -f '/usr/share/nginx/sbin/nginx' || mv '/usr/share/nginx/sbin/nginx' '/usr/share/nginx/sbin/nginx.old' cp objs/nginx '/usr/share/nginx/sbin/nginx' test -d '/etc/nginx' || mkdir -p '/etc/nginx' cp conf/koi-win '/etc/nginx' cp conf/koi-utf '/etc/nginx' cp conf/win-utf '/etc/nginx' test -f '/etc/nginx/mime.types' || cp conf/mime.types '/etc/nginx' cp conf/mime.types '/etc/nginx/mime.types.default' test -f '/etc/nginx/fastcgi_params' || cp conf/fastcgi_params '/etc/nginx' cp conf/fastcgi_params '/etc/nginx/fastcgi_params.default' test -f '/etc/nginx/fastcgi.conf' || cp conf/fastcgi.conf '/etc/nginx' cp conf/fastcgi.conf '/etc/nginx/fastcgi.conf.default' test -f '/etc/nginx/uwsgi_params' || cp conf/uwsgi_params '/etc/nginx' cp conf/uwsgi_params '/etc/nginx/uwsgi_params.default' test -f '/etc/nginx/scgi_params' || cp conf/scgi_params '/etc/nginx' cp conf/scgi_params '/etc/nginx/scgi_params.default' test -f '/etc/nginx/nginx.conf' || cp conf/nginx.conf '/etc/nginx/nginx.conf' cp conf/nginx.conf '/etc/nginx/nginx.conf.default' test -d '/run' || mkdir -p '/run' test -d '/var/log/nginx' || mkdir -p '/var/log/nginx' test -d '/usr/share/nginx/html' || cp -R html '/usr/share/nginx' test -d '/var/log/nginx' || mkdir -p '/var/log/nginx' ######################################################### I copy/create the files that I saved earlier to txt files in sites-available, the config, default and ini files then symlink them to sites-enabled, and so on. And now to start the server: service nginx start And this is where s#!+ hits the fan - Nada. I check to see if Nginx is running with service --status-all and its not. Also with nginx -V and its not installed??? I reboot the system too and still nothing. So I am not sure what is wrong here. The ini was copied over from the old server along with all the other config files after deleting the old files. When I opened the new compiled files, the nginx default data was present so I replaced them with my old original data prior to starting the new server for the first time. Also to be safe, I rm /etc/nginx/sites-enabled/default and symlinked with ln -s /etc/nginx/sites-available/default /etc/nginx/sites-enabled/default with no errors and I verified that the data was in the sites-enabled/default file. I don't think the server really/fully installed because of the nginx -V result: The program 'nginx' can be found in the following packages: * nginx-core * nginx-extras * nginx-full * nginx-light * nginx-naxsi Try: apt-get install <selected package> Do/should I apt-get install nginx-1.7.4 ?? Or what package do I use being that its a custom package and make install earlier did nothing?? If you need to see the conf files I copied over from the old to the custom server, LMK and I'll post them. Again your help here would be appreciated!

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  • TV Playout software for Windows Server without DirectX?

    - by Joel Kennedy
    I am trying to find a TV Playout software (video mixer) for Windows Server 2003/2008 which can stream via rtmp to Justin.tv without the need for DirectX. The reason for this is that the server which would run the TV Playout software is hosted/virtualized via an ESXi server, and does not have DirectX support. Even if there was software that could just stream a playlist of video files to Justin.tv that would be a start. Thanks

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  • Workaround for starting zabbix agent on Ubuntu. update-rc.d LSB mismatch

    - by bryan kennedy
    I am trying to run the zabbix-agent (1.8.1) on boot on Ubuntu (lucid 10.04). Zabbix is installed just fine, and it manually starts just fine with /etc/init.d/zabbix-agent start However it doesn't start on boot, because when I run: sudo update-rc.d zabbix-agent default I get: update-rc.d: warning: zabbix-agent start runlevel arguments (none) do not match LSB Default-Start values (2 3 4 5) update-rc.d: warning: zabbix-agent stop runlevel arguments (none) do not match LSB Default-Stop values (0 1 6) After googling around I found some cryptic information about this being a possible bug with Zabbix's startup scripts, but I can't find a workaround. I'm trying to understand how the update-rc.d system works, but I'm not getting very far. How can I modify this setup to start the zabbix-agent on startup?

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  • NX Client for Windows 7 Opens Remote Desktop in Multiple Windows

    - by Corey Kennedy
    What I'm trying to do: access my Ubuntu desktop remotely via NX Client on my Windows 7 laptop. My environment: server: Ubuntu 10.10 on AMD 1Ghz/512MB RAM PC client: Windows 7 on ThinkPad sl510 Software: server is running NXServer 3.4.0. Using xfce4 window manager. Laptop is using NXClient for Windows In my NX Client "Desktop" settings I've selected "Unix" and "Custom" for OS and environment. I've also specified "startxfce4" as the application to launch when NX connects. I am able to authenticate an NX session on my laptop. By this I mean, I can start the client on my laptop, enter credentials for my Linux user, and NX establishes a connection to the server and attempts to open a remote desktop window. The problem, though, is that this remote desktop is "fragmented" into many Windows. One window will display the bulk of my desktop (complete with desktop icons for "Home," "File System," and "Trash") while another window will contain the taskbar, and another window will contain the application strip. I can select each of these Windows individually, but I cannot click on any objects within them. I've searched Super User, Ubuntu Forums, NX help, Server Fault, and tried many Google searches - none have turned up another case of this particular problem. I'm stumped. Does anyone have any suggestions for what I might try? I'm guessing the problem has to do with my xfce config files, but I've only just setup this server - it's been a long time since I've used Linux and there's a lot I just don't know. What I am NOT trying to do: use Desktop sharing from Ubuntu, whereby I VNC into a desktop that I've already established on the server. I am trying to configure this Linux box as a headless server that I can stash someplace out-of-the-way in my house, then interact with through my laptop. I don't want to have a monitor or keyboard connected to the Linux box. Thanks for your help! edit: 1/19/2011 Well, this is truly bizarre. To my knowledge I've made no changes to either system - the laptop or the server. But today after starting up the server for the first time in a few days, and making sure that nxserver was running, I was able to connect with the nxclient from my laptop with no problems. I have a full desktop in a single window and I am able to interact with it normally. This is really weird, but the problem seems to be resolved.

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  • NX Client for Windows 7 Opens Remote Desktop in Multiple Windows

    - by Corey Kennedy
    What I'm trying to do: access my Ubuntu desktop remotely via NX Client on my Windows 7 laptop. My environment: server: Ubuntu 10.10 on AMD 1Ghz/512MB RAM PC client: Windows 7 on ThinkPad sl510 Software: server is running NXServer 3.4.0. Using xfce4 window manager. Laptop is using NXClient for Windows In my NX Client "Desktop" settings I've selected "Unix" and "Custom" for OS and environment. I've also specified "startxfce4" as the application to launch when NX connects. I am able to authenticate an NX session on my laptop. By this I mean, I can start the client on my laptop, enter credentials for my Linux user, and NX establishes a connection to the server and attempts to open a remote desktop window. The problem, though, is that this remote desktop is "fragmented" into many Windows. One window will display the bulk of my desktop (complete with desktop icons for "Home," "File System," and "Trash") while another window will contain the taskbar, and another window will contain the application strip. I can select each of these Windows individually, but I cannot click on any objects within them. I've searched Super User, Ubuntu Forums, NX help, Server Fault, and tried many Google searches - none have turned up another case of this particular problem. I'm stumped. Does anyone have any suggestions for what I might try? I'm guessing the problem has to do with my xfce config files, but I've only just setup this server - it's been a long time since I've used Linux and there's a lot I just don't know. What I am NOT trying to do: use Desktop sharing from Ubuntu, whereby I VNC into a desktop that I've already established on the server. I am trying to configure this Linux box as a headless server that I can stash someplace out-of-the-way in my house, then interact with through my laptop. I don't want to have a monitor or keyboard connected to the Linux box. Thanks for your help!

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  • How can I make gitosis distinguish between two users with the same username

    - by bryan kennedy
    I have a gitosis system that seems to be working correctly except for a common problem we run into where I can't distingush permissions between two users who have the same username, but different hosts. For example: [email protected] 's SSH key is in the key folder. And so is [email protected] 's SSH is also in the key folder. These two jsmith's are two different people on two different computers. However, when I configure them in the gitosis.conf file with the usernames jsmith@computer or jsmith@machine, it seems like each user just gets the same permission. Can gitosis not distinguish the full username (name and host)? If not, how do I deal with multiple users accessing our system with common usernames? Thanks for any help.

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  • Why do I have two different DNS suffix lists?

    - by Rob Kennedy
    My Windows XP laptop has two different DNS suffix lists. The first is the one I see by selecting the Properties dialog of any of my network connections, selecting Internet Protocol Properties Advanced DNS tab, and looking at the list under the "Append these DNS suffixes (in order)" option. The second list is the one shown under "DNS Suffix Search List" when I run ipconfig /all. As far as I can tell, only the second list ever gets used to resolve unqualified host names. Why are there two different lists? How do I configure the second list? Or how can I make my computer use the first list?

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  • How to have Jetty redirect http to https

    - by Noel Kennedy
    I want to redirect all requests for http to https using Jetty (6.1.24). For some reason (my ignorance) this is eluding me. This is what I have: <New id="redirect" class="org.mortbay.jetty.handler.rewrite.RedirectPatternRule"> <Set name="pattern">http://foobar.com/*</Set> <Set name="location">https://foobar.com</Set> </New> In response I get 200 - ok, and the body is the page over http, ie the redirect doesn't occur.

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  • Can't access server sound card when vnc'd into ubuntu server

    - by Corey Kennedy
    I've set up my ubunutu 10 server with xfce, nxserver, and now tightvncserver so that I can control it remotely from my Windows 7 laptop. NX is working fine for remote access, but when I run (for example) exaile, no sound will be sent through the server's sound card. I installed tightvncserver and connected, but ran into the same problem. Exaile opens, sound isn't muted, I can see that sound cards are installed (via cat /proc/asound/cards), but I can't seem to get the remote sessions to access the server's sound card. Also, just to confirm that the sound card was working I hooked up a montior/keyboard to the server and opened a local xfce session. That worked fine. While I had the local session running, I was also able to open a remote session with NXClient and start exaile - which then successfully piped sound to the local card. After disconnecting the monitor/keyboard and moving the box back to its normal spot, though, I was not able to play sound via either an NX or VNC session. Does anyone have any suggestions? Surely it's possible to configure my remote sessions to pipe sound to the server's sound card, right? Or at least get xfce up and running without a monitor or keyboard but with access to the sound card so I can VNC into it? Thanks!

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  • Installing EclipseFP on Mac OS X

    - by Dom Kennedy
    I am trying to install EclipseFP. I'm running OS X Mavericks. I've tried following both the official installation instructions and the advice in this answer on SU, but I'm still having the same problem. I can get the plugin itself installed painlessly using Help -> Install New Software..., Bbut when I restart and switch to the Haskell perspective, things start to go wrong. The installation instructions tells me that I should receive a prompt to install BuildWrapper and Scion Browser. I do not receive this prompt. Furthermore, if I create a new Haskell project, my code has no syntax highlighting, and the Hoogle search feature does not appear to do anything. It's clear that the plugin is not set up correctly yet. I've tried running cabal update in Terminal, but this does not change anything. After several attempts going round in circles with this on Eclipse Juno, I uninstalled Eclispe and the Haskell Platform and performed a clean install of Eclipse Luna and the latest Haskell Platform. However, the problems are persisting. I've tried going into Preferences to see if I could sort any of this out manually. I should initially point out that my GHC installation seems to be correctly references under Preferences -> Haskell Implementations Under Haskell -> Helper executables, there are areas for configuring the options of both BuildWrapper and Scion Browser. At present, both are blank. I tried clicking the Install from Hackage... button beside each of them with no success; I receive an error message saying Expected executable <workspace>/.metadata/.plugins/net.sf.eclipsefp.haskell.ui/sandbox/.cabal-sandbox/bin/buildwrapper not found!` (replace buildwrapper for scion-browser and the message is the same) The Eclipse console displays the following exception after doing the above with BuildWrapper: src/Language/Haskell/BuildWrapper/GHCStorage.hs:313:32: Not in scope: data constructor ‘MatchGroup’ cabal.real: Error: some packages failed to install: buildwrapper-0.7.4 failed during the building phase. The exception was: ExitFailure 1 and after doing it for Scion-Browser: zip-archive-0.2.3.4 (reinstall) changes: text-1.1.0.0 -> 0.11.3.1 pandoc-1.12.3.3 (latest: 1.13) -http-conduit (new version) Graphalyze-0.14.1.0 (reinstall) changes: pandoc-1.12.4.2 -> 1.12.3.3, text-1.1.0.0 -> 0.11.3.1 cabal.real: The following packages are likely to be broken by the reinstalls: pandoc-1.12.4.2 unordered-containers-0.2.4.0 aeson-0.7.0.4 scientific-0.2.0.2 case-insensitive-1.1.0.3 HTTP-4000.2.10 Use --force-reinstalls if you want to install anyway. After receiving similar results as the above on previous attempts, I've tried using force-reinstalls and ended up at more dead ends. I am at a loss as to what is wrong and how to solve this. I should point out that my GHC installation appears to be correctly configured under Preferences -> Haskell -> Haskell Implementations. Apologies if any of this information is irrelevant, I'm just not really sure what is important and what isn't at this point. Any help anyone could provide me with would be greatly appreciated.

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  • Transactional Messaging in the Windows Azure Service Bus

    - by Alan Smith
    Introduction I’m currently working on broadening the content in the Windows Azure Service Bus Developer Guide. One of the features I have been looking at over the past week is the support for transactional messaging. When using the direct programming model and the WCF interface some, but not all, messaging operations can participate in transactions. This allows developers to improve the reliability of messaging systems. There are some limitations in the transactional model, transactions can only include one top level messaging entity (such as a queue or topic, subscriptions are no top level entities), and transactions cannot include other systems, such as databases. As the transaction model is currently not well documented I have had to figure out how things work through experimentation, with some help from the development team to confirm any questions I had. Hopefully I’ve got the content mostly correct, I will update the content in the e-book if I find any errors or improvements that can be made (any feedback would be very welcome). I’ve not had a chance to look into the code for transactions and asynchronous operations, maybe that would make a nice challenge lab for my Windows Azure Service Bus course. Transactional Messaging Messaging entities in the Windows Azure Service Bus provide support for participation in transactions. This allows developers to perform several messaging operations within a transactional scope, and ensure that all the actions are committed or, if there is a failure, none of the actions are committed. There are a number of scenarios where the use of transactions can increase the reliability of messaging systems. Using TransactionScope In .NET the TransactionScope class can be used to perform a series of actions in a transaction. The using declaration is typically used de define the scope of the transaction. Any transactional operations that are contained within the scope can be committed by calling the Complete method. If the Complete method is not called, any transactional methods in the scope will not commit.   // Create a transactional scope. using (TransactionScope scope = new TransactionScope()) {     // Do something.       // Do something else.       // Commit the transaction.     scope.Complete(); }     In order for methods to participate in the transaction, they must provide support for transactional operations. Database and message queue operations typically provide support for transactions. Transactions in Brokered Messaging Transaction support in Service Bus Brokered Messaging allows message operations to be performed within a transactional scope; however there are some limitations around what operations can be performed within the transaction. In the current release, only one top level messaging entity, such as a queue or topic can participate in a transaction, and the transaction cannot include any other transaction resource managers, making transactions spanning a messaging entity and a database not possible. When sending messages, the send operations can participate in a transaction allowing multiple messages to be sent within a transactional scope. This allows for “all or nothing” delivery of a series of messages to a single queue or topic. When receiving messages, messages that are received in the peek-lock receive mode can be completed, deadlettered or deferred within a transactional scope. In the current release the Abandon method will not participate in a transaction. The same restrictions of only one top level messaging entity applies here, so the Complete method can be called transitionally on messages received from the same queue, or messages received from one or more subscriptions in the same topic. Sending Multiple Messages in a Transaction A transactional scope can be used to send multiple messages to a queue or topic. This will ensure that all the messages will be enqueued or, if the transaction fails to commit, no messages will be enqueued.     An example of the code used to send 10 messages to a queue as a single transaction from a console application is shown below.   QueueClient queueClient = messagingFactory.CreateQueueClient(Queue1);   Console.Write("Sending");   // Create a transaction scope. using (TransactionScope scope = new TransactionScope()) {     for (int i = 0; i < 10; i++)     {         // Send a message         BrokeredMessage msg = new BrokeredMessage("Message: " + i);         queueClient.Send(msg);         Console.Write(".");     }     Console.WriteLine("Done!");     Console.WriteLine();       // Should we commit the transaction?     Console.WriteLine("Commit send 10 messages? (yes or no)");     string reply = Console.ReadLine();     if (reply.ToLower().Equals("yes"))     {         // Commit the transaction.         scope.Complete();     } } Console.WriteLine(); messagingFactory.Close();     The transaction scope is used to wrap the sending of 10 messages. Once the messages have been sent the user has the option to either commit the transaction or abandon the transaction. If the user enters “yes”, the Complete method is called on the scope, which will commit the transaction and result in the messages being enqueued. If the user enters anything other than “yes”, the transaction will not commit, and the messages will not be enqueued. Receiving Multiple Messages in a Transaction The receiving of multiple messages is another scenario where the use of transactions can improve reliability. When receiving a group of messages that are related together, maybe in the same message session, it is possible to receive the messages in the peek-lock receive mode, and then complete, defer, or deadletter the messages in one transaction. (In the current version of Service Bus, abandon is not transactional.)   The following code shows how this can be achieved. using (TransactionScope scope = new TransactionScope()) {       while (true)     {         // Receive a message.         BrokeredMessage msg = q1Client.Receive(TimeSpan.FromSeconds(1));         if (msg != null)         {             // Wrote message body and complete message.             string text = msg.GetBody<string>();             Console.WriteLine("Received: " + text);             msg.Complete();         }         else         {             break;         }     }     Console.WriteLine();       // Should we commit?     Console.WriteLine("Commit receive? (yes or no)");     string reply = Console.ReadLine();     if (reply.ToLower().Equals("yes"))     {         // Commit the transaction.         scope.Complete();     }     Console.WriteLine(); }     Note that if there are a large number of messages to be received, there will be a chance that the transaction may time out before it can be committed. It is possible to specify a longer timeout when the transaction is created, but It may be better to receive and commit smaller amounts of messages within the transaction. It is also possible to complete, defer, or deadletter messages received from more than one subscription, as long as all the subscriptions are contained in the same topic. As subscriptions are not top level messaging entities this scenarios will work. The following code shows how this can be achieved. try {     using (TransactionScope scope = new TransactionScope())     {         // Receive one message from each subscription.         BrokeredMessage msg1 = subscriptionClient1.Receive();         BrokeredMessage msg2 = subscriptionClient2.Receive();           // Complete the message receives.         msg1.Complete();         msg2.Complete();           Console.WriteLine("Msg1: " + msg1.GetBody<string>());         Console.WriteLine("Msg2: " + msg2.GetBody<string>());           // Commit the transaction.         scope.Complete();     } } catch (Exception ex) {     Console.WriteLine(ex.Message); }     Unsupported Scenarios The restriction of only one top level messaging entity being able to participate in a transaction makes some useful scenarios unsupported. As the Windows Azure Service Bus is under continuous development and new releases are expected to be frequent it is possible that this restriction may not be present in future releases. The first is the scenario where messages are to be routed to two different systems. The following code attempts to do this.   try {     // Create a transaction scope.     using (TransactionScope scope = new TransactionScope())     {         BrokeredMessage msg1 = new BrokeredMessage("Message1");         BrokeredMessage msg2 = new BrokeredMessage("Message2");           // Send a message to Queue1         Console.WriteLine("Sending Message1");         queue1Client.Send(msg1);           // Send a message to Queue2         Console.WriteLine("Sending Message2");         queue2Client.Send(msg2);           // Commit the transaction.         Console.WriteLine("Committing transaction...");         scope.Complete();     } } catch (Exception ex) {     Console.WriteLine(ex.Message); }     The results of running the code are shown below. When attempting to send a message to the second queue the following exception is thrown: No active Transaction was found for ID '35ad2495-ee8a-4956-bbad-eb4fedf4a96e:1'. The Transaction may have timed out or attempted to span multiple top-level entities such as Queue or Topic. The server Transaction timeout is: 00:01:00..TrackingId:947b8c4b-7754-4044-b91b-4a959c3f9192_3_3,TimeStamp:3/29/2012 7:47:32 AM.   Another scenario where transactional support could be useful is when forwarding messages from one queue to another queue. This would also involve more than one top level messaging entity, and is therefore not supported.   Another scenario that developers may wish to implement is performing transactions across messaging entities and other transactional systems, such as an on-premise database. In the current release this is not supported.   Workarounds for Unsupported Scenarios There are some techniques that developers can use to work around the one top level entity limitation of transactions. When sending two messages to two systems, topics and subscriptions can be used. If the same message is to be sent to two destinations then the subscriptions would have the default subscriptions, and the client would only send one message. If two different messages are to be sent, then filters on the subscriptions can route the messages to the appropriate destination. The client can then send the two messages to the topic in the same transaction.   In scenarios where a message needs to be received and then forwarded to another system within the same transaction topics and subscriptions can also be used. A message can be received from a subscription, and then sent to a topic within the same transaction. As a topic is a top level messaging entity, and a subscription is not, this scenario will work.

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  • Pygame surface rotation, rect rotation or sprite rotation?

    - by Alan
    i seem to have a conceptual misunderstanding of the surface and rect object in pygame. I currently observe these objects this way: Surface Just the loaded image rect the 'hard' representation of the ingame object (sprite). Used for simplifying object moment and collision detection sprite rect and surface grouped together What i want to do is rotate my sprite. The only available method i found for rotation is pygame.transform.rotate. How do i rotate the rectangle, or even better, the whole sprite? Below is the image of how i visualize this problem.

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  • Michael Stephenson joins CloudCasts

    - by Alan Smith
    Mike Stephenson has recorded a couple of webcasts focusing on build and test in BizTalk Server 2009. These are part of the “BizTalk Light & Easy” series of webcasts created by some of the BizTalk Server MVPs. Testing BizTalk Applications Implementing an Automated Build Process with BizTalk Server 2009

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  • links for 2010-04-01

    - by Bob Rhubart
    Jason Williamson: Oracle Releases New Mainframe Re-Hosting in Oracle Tuxedo 11g Jason Williamson's update on new features in the latest release of Oracle Tuxedo 11g. (tags: otn oracle entarch) Jeanne Waldman: Using Oracle ADF Data Visualization Tools (DVT) Line Graphs to Display Weather Information Jeanne Waldman illustrates the nuts and bolts of modifications she made to a a simple JDeveloper Fusion application that retrieves weather data. I have a simple JDeveloper Fusion application that retrieves weather data. (tags: oracle otn virtualization jdeveloper ADF) Brian Harrison: Oracle WebCenter Interaction - New Release Overivew, Part 2 Brian Harrison continue his discussion of the next release of Oracle WebCenter Interaction with a look at at a few other new features. (tags: oracle otn enterprise2.0 webcenter)

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  • Plan Operator Tuesday round-up

    - by Rob Farley
    Eighteen posts for T-SQL Tuesday #43 this month, discussing Plan Operators. I put them together and made the following clickable plan. It’s 1000px wide, so I hope you have a monitor wide enough. Let me explain this plan for you (people’s names are the links to the articles on their blogs – the same links as in the plan above). It was clearly a SELECT statement. Wayne Sheffield (@dbawayne) wrote about that, so we start with a SELECT physical operator, leveraging the logical operator Wayne Sheffield. The SELECT operator calls the Paul White operator, discussed by Jason Brimhall (@sqlrnnr) in his post. The Paul White operator is quite remarkable, and can consume three streams of data. Let’s look at those streams. The first pulls data from a Table Scan – Boris Hristov (@borishristov)’s post – using parallel threads (Bradley Ball – @sqlballs) that pull the data eagerly through a Table Spool (Oliver Asmus – @oliverasmus). A scalar operation is also performed on it, thanks to Jeffrey Verheul (@devjef)’s Compute Scalar operator. The second stream of data applies Evil (I figured that must mean a procedural TVF, but could’ve been anything), courtesy of Jason Strate (@stratesql). It performs this Evil on the merging of parallel streams (Steve Jones – @way0utwest), which suck data out of a Switch (Paul White – @sql_kiwi). This Switch operator is consuming data from up to four lookups, thanks to Kalen Delaney (@sqlqueen), Rick Krueger (@dataogre), Mickey Stuewe (@sqlmickey) and Kathi Kellenberger (@auntkathi). Unfortunately Kathi’s name is a bit long and has been truncated, just like in real plans. The last stream performs a join of two others via a Nested Loop (Matan Yungman – @matanyungman). One pulls data from a Spool (my post – @rob_farley) populated from a Table Scan (Jon Morisi). The other applies a catchall operator (the catchall is because Tamera Clark (@tameraclark) didn’t specify any particular operator, and a catchall is what gets shown when SSMS doesn’t know what to show. Surprisingly, it’s showing the yellow one, which is about cursors. Hopefully that’s not what Tamera planned, but anyway...) to the output from an Index Seek operator (Sebastian Meine – @sqlity). Lastly, I think everyone put in 110% effort, so that’s what all the operators cost. That didn’t leave anything for me, unfortunately, but that’s okay. Also, because he decided to use the Paul White operator, Jason Brimhall gets 0%, and his 110% was given to Paul’s Switch operator post. I hope you’ve enjoyed this T-SQL Tuesday, and have learned something extra about Plan Operators. Keep your eye out for next month’s one by watching the Twitter Hashtag #tsql2sday, and why not contribute a post to the party? Big thanks to Adam Machanic as usual for starting all this. @rob_farley

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  • 256 Windows Azure Worker Roles, Windows Kinect and a 90's Text-Based Ray-Tracer

    - by Alan Smith
    For a couple of years I have been demoing a simple render farm hosted in Windows Azure using worker roles and the Azure Storage service. At the start of the presentation I deploy an Azure application that uses 16 worker roles to render a 1,500 frame 3D ray-traced animation. At the end of the presentation, when the animation was complete, I would play the animation delete the Azure deployment. The standing joke with the audience was that it was that it was a “$2 demo”, as the compute charges for running the 16 instances for an hour was $1.92, factor in the bandwidth charges and it’s a couple of dollars. The point of the demo is that it highlights one of the great benefits of cloud computing, you pay for what you use, and if you need massive compute power for a short period of time using Windows Azure can work out very cost effective. The “$2 demo” was great for presenting at user groups and conferences in that it could be deployed to Azure, used to render an animation, and then removed in a one hour session. I have always had the idea of doing something a bit more impressive with the demo, and scaling it from a “$2 demo” to a “$30 demo”. The challenge was to create a visually appealing animation in high definition format and keep the demo time down to one hour.  This article will take a run through how I achieved this. Ray Tracing Ray tracing, a technique for generating high quality photorealistic images, gained popularity in the 90’s with companies like Pixar creating feature length computer animations, and also the emergence of shareware text-based ray tracers that could run on a home PC. In order to render a ray traced image, the ray of light that would pass from the view point must be tracked until it intersects with an object. At the intersection, the color, reflectiveness, transparency, and refractive index of the object are used to calculate if the ray will be reflected or refracted. Each pixel may require thousands of calculations to determine what color it will be in the rendered image. Pin-Board Toys Having very little artistic talent and a basic understanding of maths I decided to focus on an animation that could be modeled fairly easily and would look visually impressive. I’ve always liked the pin-board desktop toys that become popular in the 80’s and when I was working as a 3D animator back in the 90’s I always had the idea of creating a 3D ray-traced animation of a pin-board, but never found the energy to do it. Even if I had a go at it, the render time to produce an animation that would look respectable on a 486 would have been measured in months. PolyRay Back in 1995 I landed my first real job, after spending three years being a beach-ski-climbing-paragliding-bum, and was employed to create 3D ray-traced animations for a CD-ROM that school kids would use to learn physics. I had got into the strange and wonderful world of text-based ray tracing, and was using a shareware ray-tracer called PolyRay. PolyRay takes a text file describing a scene as input and, after a few hours processing on a 486, produced a high quality ray-traced image. The following is an example of a basic PolyRay scene file. background Midnight_Blue   static define matte surface { ambient 0.1 diffuse 0.7 } define matte_white texture { matte { color white } } define matte_black texture { matte { color dark_slate_gray } } define position_cylindrical 3 define lookup_sawtooth 1 define light_wood <0.6, 0.24, 0.1> define median_wood <0.3, 0.12, 0.03> define dark_wood <0.05, 0.01, 0.005>     define wooden texture { noise surface { ambient 0.2  diffuse 0.7  specular white, 0.5 microfacet Reitz 10 position_fn position_cylindrical position_scale 1  lookup_fn lookup_sawtooth octaves 1 turbulence 1 color_map( [0.0, 0.2, light_wood, light_wood] [0.2, 0.3, light_wood, median_wood] [0.3, 0.4, median_wood, light_wood] [0.4, 0.7, light_wood, light_wood] [0.7, 0.8, light_wood, median_wood] [0.8, 0.9, median_wood, light_wood] [0.9, 1.0, light_wood, dark_wood]) } } define glass texture { surface { ambient 0 diffuse 0 specular 0.2 reflection white, 0.1 transmission white, 1, 1.5 }} define shiny surface { ambient 0.1 diffuse 0.6 specular white, 0.6 microfacet Phong 7  } define steely_blue texture { shiny { color black } } define chrome texture { surface { color white ambient 0.0 diffuse 0.2 specular 0.4 microfacet Phong 10 reflection 0.8 } }   viewpoint {     from <4.000, -1.000, 1.000> at <0.000, 0.000, 0.000> up <0, 1, 0> angle 60     resolution 640, 480 aspect 1.6 image_format 0 }       light <-10, 30, 20> light <-10, 30, -20>   object { disc <0, -2, 0>, <0, 1, 0>, 30 wooden }   object { sphere <0.000, 0.000, 0.000>, 1.00 chrome } object { cylinder <0.000, 0.000, 0.000>, <0.000, 0.000, -4.000>, 0.50 chrome }   After setting up the background and defining colors and textures, the viewpoint is specified. The “camera” is located at a point in 3D space, and it looks towards another point. The angle, image resolution, and aspect ratio are specified. Two lights are present in the image at defined coordinates. The three objects in the image are a wooden disc to represent a table top, and a sphere and cylinder that intersect to form a pin that will be used for the pin board toy in the final animation. When the image is rendered, the following image is produced. The pins are modeled with a chrome surface, so they reflect the environment around them. Note that the scale of the pin shaft is not correct, this will be fixed later. Modeling the Pin Board The frame of the pin-board is made up of three boxes, and six cylinders, the front box is modeled using a clear, slightly reflective solid, with the same refractive index of glass. The other shapes are modeled as metal. object { box <-5.5, -1.5, 1>, <5.5, 5.5, 1.2> glass } object { box <-5.5, -1.5, -0.04>, <5.5, 5.5, -0.09> steely_blue } object { box <-5.5, -1.5, -0.52>, <5.5, 5.5, -0.59> steely_blue } object { cylinder <-5.2, -1.2, 1.4>, <-5.2, -1.2, -0.74>, 0.2 steely_blue } object { cylinder <5.2, -1.2, 1.4>, <5.2, -1.2, -0.74>, 0.2 steely_blue } object { cylinder <-5.2, 5.2, 1.4>, <-5.2, 5.2, -0.74>, 0.2 steely_blue } object { cylinder <5.2, 5.2, 1.4>, <5.2, 5.2, -0.74>, 0.2 steely_blue } object { cylinder <0, -1.2, 1.4>, <0, -1.2, -0.74>, 0.2 steely_blue } object { cylinder <0, 5.2, 1.4>, <0, 5.2, -0.74>, 0.2 steely_blue }   In order to create the matrix of pins that make up the pin board I used a basic console application with a few nested loops to create two intersecting matrixes of pins, which models the layout used in the pin boards. The resulting image is shown below. The pin board contains 11,481 pins, with the scene file containing 23,709 lines of code. For the complete animation 2,000 scene files will be created, which is over 47 million lines of code. Each pin in the pin-board will slide out a specific distance when an object is pressed into the back of the board. This is easily modeled by setting the Z coordinate of the pin to a specific value. In order to set all of the pins in the pin-board to the correct position, a bitmap image can be used. The position of the pin can be set based on the color of the pixel at the appropriate position in the image. When the Windows Azure logo is used to set the Z coordinate of the pins, the following image is generated. The challenge now was to make a cool animation. The Azure Logo is fine, but it is static. Using a normal video to animate the pins would not work; the colors in the video would not be the same as the depth of the objects from the camera. In order to simulate the pin board accurately a series of frames from a depth camera could be used. Windows Kinect The Kenect controllers for the X-Box 360 and Windows feature a depth camera. The Kinect SDK for Windows provides a programming interface for Kenect, providing easy access for .NET developers to the Kinect sensors. The Kinect Explorer provided with the Kinect SDK is a great starting point for exploring Kinect from a developers perspective. Both the X-Box 360 Kinect and the Windows Kinect will work with the Kinect SDK, the Windows Kinect is required for commercial applications, but the X-Box Kinect can be used for hobby projects. The Windows Kinect has the advantage of providing a mode to allow depth capture with objects closer to the camera, which makes for a more accurate depth image for setting the pin positions. Creating a Depth Field Animation The depth field animation used to set the positions of the pin in the pin board was created using a modified version of the Kinect Explorer sample application. In order to simulate the pin board accurately, a small section of the depth range from the depth sensor will be used. Any part of the object in front of the depth range will result in a white pixel; anything behind the depth range will be black. Within the depth range the pixels in the image will be set to RGB values from 0,0,0 to 255,255,255. A screen shot of the modified Kinect Explorer application is shown below. The Kinect Explorer sample application was modified to include slider controls that are used to set the depth range that forms the image from the depth stream. This allows the fine tuning of the depth image that is required for simulating the position of the pins in the pin board. The Kinect Explorer was also modified to record a series of images from the depth camera and save them as a sequence JPEG files that will be used to animate the pins in the animation the Start and Stop buttons are used to start and stop the image recording. En example of one of the depth images is shown below. Once a series of 2,000 depth images has been captured, the task of creating the animation can begin. Rendering a Test Frame In order to test the creation of frames and get an approximation of the time required to render each frame a test frame was rendered on-premise using PolyRay. The output of the rendering process is shown below. The test frame contained 23,629 primitive shapes, most of which are the spheres and cylinders that are used for the 11,800 or so pins in the pin board. The 1280x720 image contains 921,600 pixels, but as anti-aliasing was used the number of rays that were calculated was 4,235,777, with 3,478,754,073 object boundaries checked. The test frame of the pin board with the depth field image applied is shown below. The tracing time for the test frame was 4 minutes 27 seconds, which means rendering the2,000 frames in the animation would take over 148 hours, or a little over 6 days. Although this is much faster that an old 486, waiting almost a week to see the results of an animation would make it challenging for animators to create, view, and refine their animations. It would be much better if the animation could be rendered in less than one hour. Windows Azure Worker Roles The cost of creating an on-premise render farm to render animations increases in proportion to the number of servers. The table below shows the cost of servers for creating a render farm, assuming a cost of $500 per server. Number of Servers Cost 1 $500 16 $8,000 256 $128,000   As well as the cost of the servers, there would be additional costs for networking, racks etc. Hosting an environment of 256 servers on-premise would require a server room with cooling, and some pretty hefty power cabling. The Windows Azure compute services provide worker roles, which are ideal for performing processor intensive compute tasks. With the scalability available in Windows Azure a job that takes 256 hours to complete could be perfumed using different numbers of worker roles. The time and cost of using 1, 16 or 256 worker roles is shown below. Number of Worker Roles Render Time Cost 1 256 hours $30.72 16 16 hours $30.72 256 1 hour $30.72   Using worker roles in Windows Azure provides the same cost for the 256 hour job, irrespective of the number of worker roles used. Provided the compute task can be broken down into many small units, and the worker role compute power can be used effectively, it makes sense to scale the application so that the task is completed quickly, making the results available in a timely fashion. The task of rendering 2,000 frames in an animation is one that can easily be broken down into 2,000 individual pieces, which can be performed by a number of worker roles. Creating a Render Farm in Windows Azure The architecture of the render farm is shown in the following diagram. The render farm is a hybrid application with the following components: ·         On-Premise o   Windows Kinect – Used combined with the Kinect Explorer to create a stream of depth images. o   Animation Creator – This application uses the depth images from the Kinect sensor to create scene description files for PolyRay. These files are then uploaded to the jobs blob container, and job messages added to the jobs queue. o   Process Monitor – This application queries the role instance lifecycle table and displays statistics about the render farm environment and render process. o   Image Downloader – This application polls the image queue and downloads the rendered animation files once they are complete. ·         Windows Azure o   Azure Storage – Queues and blobs are used for the scene description files and completed frames. A table is used to store the statistics about the rendering environment.   The architecture of each worker role is shown below.   The worker role is configured to use local storage, which provides file storage on the worker role instance that can be use by the applications to render the image and transform the format of the image. The service definition for the worker role with the local storage configuration highlighted is shown below. <?xml version="1.0" encoding="utf-8"?> <ServiceDefinition name="CloudRay" >   <WorkerRole name="CloudRayWorkerRole" vmsize="Small">     <Imports>     </Imports>     <ConfigurationSettings>       <Setting name="DataConnectionString" />     </ConfigurationSettings>     <LocalResources>       <LocalStorage name="RayFolder" cleanOnRoleRecycle="true" />     </LocalResources>   </WorkerRole> </ServiceDefinition>     The two executable programs, PolyRay.exe and DTA.exe are included in the Azure project, with Copy Always set as the property. PolyRay will take the scene description file and render it to a Truevision TGA file. As the TGA format has not seen much use since the mid 90’s it is converted to a JPG image using Dave's Targa Animator, another shareware application from the 90’s. Each worker roll will use the following process to render the animation frames. 1.       The worker process polls the job queue, if a job is available the scene description file is downloaded from blob storage to local storage. 2.       PolyRay.exe is started in a process with the appropriate command line arguments to render the image as a TGA file. 3.       DTA.exe is started in a process with the appropriate command line arguments convert the TGA file to a JPG file. 4.       The JPG file is uploaded from local storage to the images blob container. 5.       A message is placed on the images queue to indicate a new image is available for download. 6.       The job message is deleted from the job queue. 7.       The role instance lifecycle table is updated with statistics on the number of frames rendered by the worker role instance, and the CPU time used. The code for this is shown below. public override void Run() {     // Set environment variables     string polyRayPath = Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), PolyRayLocation);     string dtaPath = Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), DTALocation);       LocalResource rayStorage = RoleEnvironment.GetLocalResource("RayFolder");     string localStorageRootPath = rayStorage.RootPath;       JobQueue jobQueue = new JobQueue("renderjobs");     JobQueue downloadQueue = new JobQueue("renderimagedownloadjobs");     CloudRayBlob sceneBlob = new CloudRayBlob("scenes");     CloudRayBlob imageBlob = new CloudRayBlob("images");     RoleLifecycleDataSource roleLifecycleDataSource = new RoleLifecycleDataSource();       Frames = 0;       while (true)     {         // Get the render job from the queue         CloudQueueMessage jobMsg = jobQueue.Get();           if (jobMsg != null)         {             // Get the file details             string sceneFile = jobMsg.AsString;             string tgaFile = sceneFile.Replace(".pi", ".tga");             string jpgFile = sceneFile.Replace(".pi", ".jpg");               string sceneFilePath = Path.Combine(localStorageRootPath, sceneFile);             string tgaFilePath = Path.Combine(localStorageRootPath, tgaFile);             string jpgFilePath = Path.Combine(localStorageRootPath, jpgFile);               // Copy the scene file to local storage             sceneBlob.DownloadFile(sceneFilePath);               // Run the ray tracer.             string polyrayArguments =                 string.Format("\"{0}\" -o \"{1}\" -a 2", sceneFilePath, tgaFilePath);             Process polyRayProcess = new Process();             polyRayProcess.StartInfo.FileName =                 Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), polyRayPath);             polyRayProcess.StartInfo.Arguments = polyrayArguments;             polyRayProcess.Start();             polyRayProcess.WaitForExit();               // Convert the image             string dtaArguments =                 string.Format(" {0} /FJ /P{1}", tgaFilePath, Path.GetDirectoryName (jpgFilePath));             Process dtaProcess = new Process();             dtaProcess.StartInfo.FileName =                 Path.Combine(Environment.GetEnvironmentVariable("RoleRoot"), dtaPath);             dtaProcess.StartInfo.Arguments = dtaArguments;             dtaProcess.Start();             dtaProcess.WaitForExit();               // Upload the image to blob storage             imageBlob.UploadFile(jpgFilePath);               // Add a download job.             downloadQueue.Add(jpgFile);               // Delete the render job message             jobQueue.Delete(jobMsg);               Frames++;         }         else         {             Thread.Sleep(1000);         }           // Log the worker role activity.         roleLifecycleDataSource.Alive             ("CloudRayWorker", RoleLifecycleDataSource.RoleLifecycleId, Frames);     } }     Monitoring Worker Role Instance Lifecycle In order to get more accurate statistics about the lifecycle of the worker role instances used to render the animation data was tracked in an Azure storage table. The following class was used to track the worker role lifecycles in Azure storage.   public class RoleLifecycle : TableServiceEntity {     public string ServerName { get; set; }     public string Status { get; set; }     public DateTime StartTime { get; set; }     public DateTime EndTime { get; set; }     public long SecondsRunning { get; set; }     public DateTime LastActiveTime { get; set; }     public int Frames { get; set; }     public string Comment { get; set; }       public RoleLifecycle()     {     }       public RoleLifecycle(string roleName)     {         PartitionKey = roleName;         RowKey = Utils.GetAscendingRowKey();         Status = "Started";         StartTime = DateTime.UtcNow;         LastActiveTime = StartTime;         EndTime = StartTime;         SecondsRunning = 0;         Frames = 0;     } }     A new instance of this class is created and added to the storage table when the role starts. It is then updated each time the worker renders a frame to record the total number of frames rendered and the total processing time. These statistics are used be the monitoring application to determine the effectiveness of use of resources in the render farm. Rendering the Animation The Azure solution was deployed to Windows Azure with the service configuration set to 16 worker role instances. This allows for the application to be tested in the cloud environment, and the performance of the application determined. When I demo the application at conferences and user groups I often start with 16 instances, and then scale up the application to the full 256 instances. The configuration to run 16 instances is shown below. <?xml version="1.0" encoding="utf-8"?> <ServiceConfiguration serviceName="CloudRay" xmlns="http://schemas.microsoft.com/ServiceHosting/2008/10/ServiceConfiguration" osFamily="1" osVersion="*">   <Role name="CloudRayWorkerRole">     <Instances count="16" />     <ConfigurationSettings>       <Setting name="DataConnectionString"         value="DefaultEndpointsProtocol=https;AccountName=cloudraydata;AccountKey=..." />     </ConfigurationSettings>   </Role> </ServiceConfiguration>     About six minutes after deploying the application the first worker roles become active and start to render the first frames of the animation. The CloudRay Monitor application displays an icon for each worker role instance, with a number indicating the number of frames that the worker role has rendered. The statistics on the left show the number of active worker roles and statistics about the render process. The render time is the time since the first worker role became active; the CPU time is the total amount of processing time used by all worker role instances to render the frames.   Five minutes after the first worker role became active the last of the 16 worker roles activated. By this time the first seven worker roles had each rendered one frame of the animation.   With 16 worker roles u and running it can be seen that one hour and 45 minutes CPU time has been used to render 32 frames with a render time of just under 10 minutes.     At this rate it would take over 10 hours to render the 2,000 frames of the full animation. In order to complete the animation in under an hour more processing power will be required. Scaling the render farm from 16 instances to 256 instances is easy using the new management portal. The slider is set to 256 instances, and the configuration saved. We do not need to re-deploy the application, and the 16 instances that are up and running will not be affected. Alternatively, the configuration file for the Azure service could be modified to specify 256 instances.   <?xml version="1.0" encoding="utf-8"?> <ServiceConfiguration serviceName="CloudRay" xmlns="http://schemas.microsoft.com/ServiceHosting/2008/10/ServiceConfiguration" osFamily="1" osVersion="*">   <Role name="CloudRayWorkerRole">     <Instances count="256" />     <ConfigurationSettings>       <Setting name="DataConnectionString"         value="DefaultEndpointsProtocol=https;AccountName=cloudraydata;AccountKey=..." />     </ConfigurationSettings>   </Role> </ServiceConfiguration>     Six minutes after the new configuration has been applied 75 new worker roles have activated and are processing their first frames.   Five minutes later the full configuration of 256 worker roles is up and running. We can see that the average rate of frame rendering has increased from 3 to 12 frames per minute, and that over 17 hours of CPU time has been utilized in 23 minutes. In this test the time to provision 140 worker roles was about 11 minutes, which works out at about one every five seconds.   We are now half way through the rendering, with 1,000 frames complete. This has utilized just under three days of CPU time in a little over 35 minutes.   The animation is now complete, with 2,000 frames rendered in a little over 52 minutes. The CPU time used by the 256 worker roles is 6 days, 7 hours and 22 minutes with an average frame rate of 38 frames per minute. The rendering of the last 1,000 frames took 16 minutes 27 seconds, which works out at a rendering rate of 60 frames per minute. The frame counts in the server instances indicate that the use of a queue to distribute the workload has been very effective in distributing the load across the 256 worker role instances. The first 16 instances that were deployed first have rendered between 11 and 13 frames each, whilst the 240 instances that were added when the application was scaled have rendered between 6 and 9 frames each.   Completed Animation I’ve uploaded the completed animation to YouTube, a low resolution preview is shown below. Pin Board Animation Created using Windows Kinect and 256 Windows Azure Worker Roles   The animation can be viewed in 1280x720 resolution at the following link: http://www.youtube.com/watch?v=n5jy6bvSxWc Effective Use of Resources According to the CloudRay monitor statistics the animation took 6 days, 7 hours and 22 minutes CPU to render, this works out at 152 hours of compute time, rounded up to the nearest hour. As the usage for the worker role instances are billed for the full hour, it may have been possible to render the animation using fewer than 256 worker roles. When deciding the optimal usage of resources, the time required to provision and start the worker roles must also be considered. In the demo I started with 16 worker roles, and then scaled the application to 256 worker roles. It would have been more optimal to start the application with maybe 200 worker roles, and utilized the full hour that I was being billed for. This would, however, have prevented showing the ease of scalability of the application. The new management portal displays the CPU usage across the worker roles in the deployment. The average CPU usage across all instances is 93.27%, with over 99% used when all the instances are up and running. This shows that the worker role resources are being used very effectively. Grid Computing Scenarios Although I am using this scenario for a hobby project, there are many scenarios where a large amount of compute power is required for a short period of time. Windows Azure provides a great platform for developing these types of grid computing applications, and can work out very cost effective. ·         Windows Azure can provide massive compute power, on demand, in a matter of minutes. ·         The use of queues to manage the load balancing of jobs between role instances is a simple and effective solution. ·         Using a cloud-computing platform like Windows Azure allows proof-of-concept scenarios to be tested and evaluated on a very low budget. ·         No charges for inbound data transfer makes the uploading of large data sets to Windows Azure Storage services cost effective. (Transaction charges still apply.) Tips for using Windows Azure for Grid Computing Scenarios I found the implementation of a render farm using Windows Azure a fairly simple scenario to implement. I was impressed by ease of scalability that Azure provides, and by the short time that the application took to scale from 16 to 256 worker role instances. In this case it was around 13 minutes, in other tests it took between 10 and 20 minutes. The following tips may be useful when implementing a grid computing project in Windows Azure. ·         Using an Azure Storage queue to load-balance the units of work across multiple worker roles is simple and very effective. The design I have used in this scenario could easily scale to many thousands of worker role instances. ·         Windows Azure accounts are typically limited to 20 cores. If you need to use more than this, a call to support and a credit card check will be required. ·         Be aware of how the billing model works. You will be charged for worker role instances for the full clock our in which the instance is deployed. Schedule the workload to start just after the clock hour has started. ·         Monitor the utilization of the resources you are provisioning, ensure that you are not paying for worker roles that are idle. ·         If you are deploying third party applications to worker roles, you may well run into licensing issues. Purchasing software licenses on a per-processor basis when using hundreds of processors for a short time period would not be cost effective. ·         Third party software may also require installation onto the worker roles, which can be accomplished using start-up tasks. Bear in mind that adding a startup task and possible re-boot will add to the time required for the worker role instance to start and activate. An alternative may be to use a prepared VM and use VM roles. ·         Consider using the Windows Azure Autoscaling Application Block (WASABi) to autoscale the worker roles in your application. When using a large number of worker roles, the utilization must be carefully monitored, if the scaling algorithms are not optimal it could get very expensive!

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  • Windows Azure Service Bus Splitter and Aggregator

    - by Alan Smith
    This article will cover basic implementations of the Splitter and Aggregator patterns using the Windows Azure Service Bus. The content will be included in the next release of the “Windows Azure Service Bus Developer Guide”, along with some other patterns I am working on. I’ve taken the pattern descriptions from the book “Enterprise Integration Patterns” by Gregor Hohpe. I bought a copy of the book in 2004, and recently dusted it off when I started to look at implementing the patterns on the Windows Azure Service Bus. Gregor has also presented an session in 2011 “Enterprise Integration Patterns: Past, Present and Future” which is well worth a look. I’ll be covering more patterns in the coming weeks, I’m currently working on Wire-Tap and Scatter-Gather. There will no doubt be a section on implementing these patterns in my “SOA, Connectivity and Integration using the Windows Azure Service Bus” course. There are a number of scenarios where a message needs to be divided into a number of sub messages, and also where a number of sub messages need to be combined to form one message. The splitter and aggregator patterns provide a definition of how this can be achieved. This section will focus on the implementation of basic splitter and aggregator patens using the Windows Azure Service Bus direct programming model. In BizTalk Server receive pipelines are typically used to implement the splitter patterns, with sequential convoy orchestrations often used to aggregate messages. In the current release of the Service Bus, there is no functionality in the direct programming model that implements these patterns, so it is up to the developer to implement them in the applications that send and receive messages. Splitter A message splitter takes a message and spits the message into a number of sub messages. As there are different scenarios for how a message can be split into sub messages, message splitters are implemented using different algorithms. The Enterprise Integration Patterns book describes the splatter pattern as follows: How can we process a message if it contains multiple elements, each of which may have to be processed in a different way? Use a Splitter to break out the composite message into a series of individual messages, each containing data related to one item. The Enterprise Integration Patterns website provides a description of the Splitter pattern here. In some scenarios a batch message could be split into the sub messages that are contained in the batch. The splitting of a message could be based on the message type of sub-message, or the trading partner that the sub message is to be sent to. Aggregator An aggregator takes a stream or related messages and combines them together to form one message. The Enterprise Integration Patterns book describes the aggregator pattern as follows: How do we combine the results of individual, but related messages so that they can be processed as a whole? Use a stateful filter, an Aggregator, to collect and store individual messages until a complete set of related messages has been received. Then, the Aggregator publishes a single message distilled from the individual messages. The Enterprise Integration Patterns website provides a description of the Aggregator pattern here. A common example of the need for an aggregator is in scenarios where a stream of messages needs to be combined into a daily batch to be sent to a legacy line-of-business application. The BizTalk Server EDI functionality provides support for batching messages in this way using a sequential convoy orchestration. Scenario The scenario for this implementation of the splitter and aggregator patterns is the sending and receiving of large messages using a Service Bus queue. In the current release, the Windows Azure Service Bus currently supports a maximum message size of 256 KB, with a maximum header size of 64 KB. This leaves a safe maximum body size of 192 KB. The BrokeredMessage class will support messages larger than 256 KB; in fact the Size property is of type long, implying that very large messages may be supported at some point in the future. The 256 KB size restriction is set in the service bus components that are deployed in the Windows Azure data centers. One of the ways of working around this size restriction is to split large messages into a sequence of smaller sub messages in the sending application, send them via a queue, and then reassemble them in the receiving application. This scenario will be used to demonstrate the pattern implementations. Implementation The splitter and aggregator will be used to provide functionality to send and receive large messages over the Windows Azure Service Bus. In order to make the implementations generic and reusable they will be implemented as a class library. The splitter will be implemented in the LargeMessageSender class and the aggregator in the LargeMessageReceiver class. A class diagram showing the two classes is shown below. Implementing the Splitter The splitter will take a large brokered message, and split the messages into a sequence of smaller sub-messages that can be transmitted over the service bus messaging entities. The LargeMessageSender class provides a Send method that takes a large brokered message as a parameter. The implementation of the class is shown below; console output has been added to provide details of the splitting operation. public class LargeMessageSender {     private static int SubMessageBodySize = 192 * 1024;     private QueueClient m_QueueClient;       public LargeMessageSender(QueueClient queueClient)     {         m_QueueClient = queueClient;     }       public void Send(BrokeredMessage message)     {         // Calculate the number of sub messages required.         long messageBodySize = message.Size;         int nrSubMessages = (int)(messageBodySize / SubMessageBodySize);         if (messageBodySize % SubMessageBodySize != 0)         {             nrSubMessages++;         }           // Create a unique session Id.         string sessionId = Guid.NewGuid().ToString();         Console.WriteLine("Message session Id: " + sessionId);         Console.Write("Sending {0} sub-messages", nrSubMessages);           Stream bodyStream = message.GetBody<Stream>();         for (int streamOffest = 0; streamOffest < messageBodySize;             streamOffest += SubMessageBodySize)         {                                     // Get the stream chunk from the large message             long arraySize = (messageBodySize - streamOffest) > SubMessageBodySize                 ? SubMessageBodySize : messageBodySize - streamOffest;             byte[] subMessageBytes = new byte[arraySize];             int result = bodyStream.Read(subMessageBytes, 0, (int)arraySize);             MemoryStream subMessageStream = new MemoryStream(subMessageBytes);               // Create a new message             BrokeredMessage subMessage = new BrokeredMessage(subMessageStream, true);             subMessage.SessionId = sessionId;               // Send the message             m_QueueClient.Send(subMessage);             Console.Write(".");         }         Console.WriteLine("Done!");     }} The LargeMessageSender class is initialized with a QueueClient that is created by the sending application. When the large message is sent, the number of sub messages is calculated based on the size of the body of the large message. A unique session Id is created to allow the sub messages to be sent as a message session, this session Id will be used for correlation in the aggregator. A for loop in then used to create the sequence of sub messages by creating chunks of data from the stream of the large message. The sub messages are then sent to the queue using the QueueClient. As sessions are used to correlate the messages, the queue used for message exchange must be created with the RequiresSession property set to true. Implementing the Aggregator The aggregator will receive the sub messages in the message session that was created by the splitter, and combine them to form a single, large message. The aggregator is implemented in the LargeMessageReceiver class, with a Receive method that returns a BrokeredMessage. The implementation of the class is shown below; console output has been added to provide details of the splitting operation.   public class LargeMessageReceiver {     private QueueClient m_QueueClient;       public LargeMessageReceiver(QueueClient queueClient)     {         m_QueueClient = queueClient;     }       public BrokeredMessage Receive()     {         // Create a memory stream to store the large message body.         MemoryStream largeMessageStream = new MemoryStream();           // Accept a message session from the queue.         MessageSession session = m_QueueClient.AcceptMessageSession();         Console.WriteLine("Message session Id: " + session.SessionId);         Console.Write("Receiving sub messages");           while (true)         {             // Receive a sub message             BrokeredMessage subMessage = session.Receive(TimeSpan.FromSeconds(5));               if (subMessage != null)             {                 // Copy the sub message body to the large message stream.                 Stream subMessageStream = subMessage.GetBody<Stream>();                 subMessageStream.CopyTo(largeMessageStream);                   // Mark the message as complete.                 subMessage.Complete();                 Console.Write(".");             }             else             {                 // The last message in the sequence is our completeness criteria.                 Console.WriteLine("Done!");                 break;             }         }                     // Create an aggregated message from the large message stream.         BrokeredMessage largeMessage = new BrokeredMessage(largeMessageStream, true);         return largeMessage;     } }   The LargeMessageReceiver initialized using a QueueClient that is created by the receiving application. The receive method creates a memory stream that will be used to aggregate the large message body. The AcceptMessageSession method on the QueueClient is then called, which will wait for the first message in a message session to become available on the queue. As the AcceptMessageSession can throw a timeout exception if no message is available on the queue after 60 seconds, a real-world implementation should handle this accordingly. Once the message session as accepted, the sub messages in the session are received, and their message body streams copied to the memory stream. Once all the messages have been received, the memory stream is used to create a large message, that is then returned to the receiving application. Testing the Implementation The splitter and aggregator are tested by creating a message sender and message receiver application. The payload for the large message will be one of the webcast video files from http://www.cloudcasts.net/, the file size is 9,697 KB, well over the 256 KB threshold imposed by the Service Bus. As the splitter and aggregator are implemented in a separate class library, the code used in the sender and receiver console is fairly basic. The implementation of the main method of the sending application is shown below.   static void Main(string[] args) {     // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Use the MessagingFactory to create a queue client     QueueClient queueClient = factory.CreateQueueClient(AccountDetails.QueueName);       // Open the input file.     FileStream fileStream = new FileStream(AccountDetails.TestFile, FileMode.Open);       // Create a BrokeredMessage for the file.     BrokeredMessage largeMessage = new BrokeredMessage(fileStream, true);       Console.WriteLine("Sending: " + AccountDetails.TestFile);     Console.WriteLine("Message body size: " + largeMessage.Size);     Console.WriteLine();         // Send the message with a LargeMessageSender     LargeMessageSender sender = new LargeMessageSender(queueClient);     sender.Send(largeMessage);       // Close the messaging facory.     factory.Close();  } The implementation of the main method of the receiving application is shown below. static void Main(string[] args) {       // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Use the MessagingFactory to create a queue client     QueueClient queueClient = factory.CreateQueueClient(AccountDetails.QueueName);       // Create a LargeMessageReceiver and receive the message.     LargeMessageReceiver receiver = new LargeMessageReceiver(queueClient);     BrokeredMessage largeMessage = receiver.Receive();       Console.WriteLine("Received message");     Console.WriteLine("Message body size: " + largeMessage.Size);       string testFile = AccountDetails.TestFile.Replace(@"\In\", @"\Out\");     Console.WriteLine("Saving file: " + testFile);       // Save the message body as a file.     Stream largeMessageStream = largeMessage.GetBody<Stream>();     largeMessageStream.Seek(0, SeekOrigin.Begin);     FileStream fileOut = new FileStream(testFile, FileMode.Create);     largeMessageStream.CopyTo(fileOut);     fileOut.Close();       Console.WriteLine("Done!"); } In order to test the application, the sending application is executed, which will use the LargeMessageSender class to split the message and place it on the queue. The output of the sender console is shown below. The console shows that the body size of the large message was 9,929,365 bytes, and the message was sent as a sequence of 51 sub messages. When the receiving application is executed the results are shown below. The console application shows that the aggregator has received the 51 messages from the message sequence that was creating in the sending application. The messages have been aggregated to form a massage with a body of 9,929,365 bytes, which is the same as the original large message. The message body is then saved as a file. Improvements to the Implementation The splitter and aggregator patterns in this implementation were created in order to show the usage of the patterns in a demo, which they do quite well. When implementing these patterns in a real-world scenario there are a number of improvements that could be made to the design. Copying Message Header Properties When sending a large message using these classes, it would be great if the message header properties in the message that was received were copied from the message that was sent. The sending application may well add information to the message context that will be required in the receiving application. When the sub messages are created in the splitter, the header properties in the first message could be set to the values in the original large message. The aggregator could then used the values from this first sub message to set the properties in the message header of the large message during the aggregation process. Using Asynchronous Methods The current implementation uses the synchronous send and receive methods of the QueueClient class. It would be much more performant to use the asynchronous methods, however doing so may well affect the sequence in which the sub messages are enqueued, which would require the implementation of a resequencer in the aggregator to restore the correct message sequence. Handling Exceptions In order to keep the code readable no exception handling was added to the implementations. In a real-world scenario exceptions should be handled accordingly.

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  • 256 Worker Role 3D Rendering Demo is now a Lab on my Azure Course

    - by Alan Smith
    Ever since I came up with the crazy idea of creating an Azure application that would spin up 256 worker roles (please vote if you like it ) to render a 3D animation created using the Kinect depth camera I have been trying to think of something useful to do with it. I have also been busy working on developing training materials for a Windows Azure course that I will be delivering through a training partner in Stockholm, and for customers wanting to learn Windows Azure. I hit on the idea of combining the render demo and a course lab and creating a lab where the students would create and deploy their own mini render farms, which would participate in a single render job, consisting of 2,000 frames. The architecture of the solution is shown below. As students would be creating and deploying their own applications, I thought it would be fun to introduce some competitiveness into the lab. In the 256 worker role demo I capture the rendering statistics for each role, so it was fairly simple to include the students name in these statistics. This allowed the process monitor application to capture the number of frames each student had rendered and display a high-score table. When I demoed the application I deployed one instance that started rendering a frame every few minutes, and the challenge for the students was to deploy and scale their applications, and then overtake my single role instance by the end of the lab time. I had the process monitor running on the projector during the lab so the class could see the progress of their deployments, and how they were performing against my implementation and their classmates. When I tested the lab for the first time in Oslo last week it was a great success, the students were keen to be the first to build and deploy their solution and then watch the frames appear. As the students mostly had MSDN suspicions they were able to scale to the full 20 worker role instances and before long we had over 100 worker roles working on the animation. There were, however, a few issues who the couple of issues caused by the competitive nature of the lab. The first student to scale the application to 20 instances would render the most frames and win; there was no way for others to catch up. Also, as they were competing against each other, there was no incentive to help others on the course get their application up and running. I have now re-written the lab to divide the student into teams that will compete to render the most frames. This means that if one developer on the team can deploy and scale quickly, the other team still has a chance to catch up. It also means that if a student finishes quickly and puts their team in the lead they will have an incentive to help the other developers on their team get up and running. As I was using “Sharks with Lasers” for a lot of my demos, and reserved the sharkswithfreakinlasers namespaces for some of the Azure services (well somebody had to do it), the students came up with some creative alternatives, like “Camels with Cannons” and “Honey Badgers with Homing Missiles”. That gave me the idea for the teams having to choose a creative name involving animals and weapons. The team rendering architecture diagram is shown below.   Render Challenge Rules In order to ensure fair play a number of rules are imposed on the lab. ·         The class will be divided into teams, each team choses a name. ·         The team name must consist of a ferocious animal combined with a hazardous weapon. ·         Teams can allocate as many worker roles as they can muster to the render job. ·         Frame processing statistics and rendered frames will be vigilantly monitored; any cheating, tampering, and other foul play will result in penalties. The screenshot below shows an example of the team render farm in action, Badgers with Bombs have taken a lead over Camels with Cannons, and both are  leaving the Sharks with Lasers standing. If you are interested in attending a scheduled delivery of my Windows Azure or Windows Azure Service bus courses, or would like on-site training, more details are here.

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  • Windows Azure Service Bus Scatter-Gather Implementation

    - by Alan Smith
    One of the more challenging enterprise integration patterns that developers may wish to implement is the Scatter-Gather pattern. In this article I will show the basic implementation of a scatter-gather pattern using the topic-subscription model of the windows azure service bus. I’ll be using the implementation in demos, and also as a lab in my training courses, and the pattern will also be included in the next release of my free e-book the “Windows Azure Service Bus Developer Guide”. The Scatter-Gather pattern answers the following scenario. How do you maintain the overall message flow when a message needs to be sent to multiple recipients, each of which may send a reply? Use a Scatter-Gather that broadcasts a message to multiple recipients and re-aggregates the responses back into a single message. The Enterprise Integration Patterns website provides a description of the Scatter-Gather pattern here.   The scatter-gather pattern uses a composite of the publish-subscribe channel pattern and the aggregator pattern. The publish-subscribe channel is used to broadcast messages to a number of receivers, and the aggregator is used to gather the response messages and aggregate them together to form a single message. Scatter-Gather Scenario The scenario for this scatter-gather implementation is an application that allows users to answer questions in a poll based voting scenario. A poll manager application will be used to broadcast questions to users, the users will use a voting application that will receive and display the questions and send the votes back to the poll manager. The poll manager application will receive the users’ votes and aggregate them together to display the results. The scenario should be able to scale to support a large number of users.   Scatter-Gather Implementation The diagram below shows the overall architecture for the scatter-gather implementation.       Messaging Entities Looking at the scatter-gather pattern diagram it can be seen that the topic-subscription architecture is well suited for broadcasting a message to a number of subscribers. The poll manager application can send the question messages to a topic, and each voting application can receive the question message on its own subscription. The static limit of 2,000 subscriptions per topic in the current release means that 2,000 voting applications can receive question messages and take part in voting. The vote messages can then be sent to the poll manager application using a queue. The voting applications will send their vote messages to the queue, and the poll manager will receive and process the vote messages. The questions topic and answer queue are created using the Windows Azure Developer Portal. Each instance of the voting application will create its own subscription in the questions topic when it starts, allowing the question messages to be broadcast to all subscribing voting applications. Data Contracts Two simple data contracts will be used to serialize the questions and votes as brokered messages. The code for these is shown below.   [DataContract] public class Question {     [DataMember]     public string QuestionText { get; set; } }     To keep the implementation of the voting functionality simple and focus on the pattern implementation, the users can only vote yes or no to the questions.   [DataContract] public class Vote {     [DataMember]     public string QuestionText { get; set; }       [DataMember]     public bool IsYes { get; set; } }     Poll Manager Application The poll manager application has been implemented as a simple WPF application; the user interface is shown below. A question can be entered in the text box, and sent to the topic by clicking the Add button. The topic and subscriptions used for broadcasting the messages are shown in a TreeView control. The questions that have been broadcast and the resulting votes are shown in a ListView control. When the application is started any existing subscriptions are cleared form the topic, clients are then created for the questions topic and votes queue, along with background workers for receiving and processing the vote messages, and updating the display of subscriptions.   public MainWindow() {     InitializeComponent();       // Create a new results list and data bind it.     Results = new ObservableCollection<Result>();     lsvResults.ItemsSource = Results;       // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Clear out any old subscriptions.     NamespaceManager = new NamespaceManager(serviceBusUri, credentials);     IEnumerable<SubscriptionDescription> subs =         NamespaceManager.GetSubscriptions(AccountDetails.ScatterGatherTopic);     foreach (SubscriptionDescription sub in subs)     {         NamespaceManager.DeleteSubscription(sub.TopicPath, sub.Name);     }       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Create the topic and queue clients.     ScatterGatherTopicClient =         factory.CreateTopicClient(AccountDetails.ScatterGatherTopic);     ScatterGatherQueueClient =         factory.CreateQueueClient(AccountDetails.ScatterGatherQueue);       // Start the background worker threads.     VotesBackgroundWorker = new BackgroundWorker();     VotesBackgroundWorker.DoWork += new DoWorkEventHandler(ReceiveMessages);     VotesBackgroundWorker.RunWorkerAsync();       SubscriptionsBackgroundWorker = new BackgroundWorker();     SubscriptionsBackgroundWorker.DoWork += new DoWorkEventHandler(UpdateSubscriptions);     SubscriptionsBackgroundWorker.RunWorkerAsync(); }     When the poll manager user nters a question in the text box and clicks the Add button a question message is created and sent to the topic. This message will be broadcast to all the subscribing voting applications. An instance of the Result class is also created to keep track of the votes cast, this is then added to an observable collection named Results, which is data-bound to the ListView control.   private void btnAddQuestion_Click(object sender, RoutedEventArgs e) {     // Create a new result for recording votes.     Result result = new Result()     {         Question = txtQuestion.Text     };     Results.Add(result);       // Send the question to the topic     Question question = new Question()     {         QuestionText = result.Question     };     BrokeredMessage msg = new BrokeredMessage(question);     ScatterGatherTopicClient.Send(msg);       txtQuestion.Text = ""; }     The Results class is implemented as follows.   public class Result : INotifyPropertyChanged {     public string Question { get; set; }       private int m_YesVotes;     private int m_NoVotes;       public event PropertyChangedEventHandler PropertyChanged;       public int YesVotes     {         get { return m_YesVotes; }         set         {             m_YesVotes = value;             NotifyPropertyChanged("YesVotes");         }     }       public int NoVotes     {         get { return m_NoVotes; }         set         {             m_NoVotes = value;             NotifyPropertyChanged("NoVotes");         }     }       private void NotifyPropertyChanged(string prop)     {         if(PropertyChanged != null)         {             PropertyChanged(this, new PropertyChangedEventArgs(prop));         }     } }     The INotifyPropertyChanged interface is implemented so that changes to the number of yes and no votes will be updated in the ListView control. Receiving the vote messages from the voting applications is done asynchronously, using a background worker thread.   // This runs on a background worker. private void ReceiveMessages(object sender, DoWorkEventArgs e) {     while (true)     {         // Receive a vote message from the queue         BrokeredMessage msg = ScatterGatherQueueClient.Receive();         if (msg != null)         {             // Deserialize the message.             Vote vote = msg.GetBody<Vote>();               // Update the results.             foreach (Result result in Results)             {                 if (result.Question.Equals(vote.QuestionText))                 {                     if (vote.IsYes)                     {                         result.YesVotes++;                     }                     else                     {                         result.NoVotes++;                     }                     break;                 }             }               // Mark the message as complete.             msg.Complete();         }       } }     When a vote message is received, the result that matches the vote question is updated with the vote from the user. The message is then marked as complete. A second background thread is used to update the display of subscriptions in the TreeView, with a dispatcher used to update the user interface. // This runs on a background worker. private void UpdateSubscriptions(object sender, DoWorkEventArgs e) {     while (true)     {         // Get a list of subscriptions.         IEnumerable<SubscriptionDescription> subscriptions =             NamespaceManager.GetSubscriptions(AccountDetails.ScatterGatherTopic);           // Update the user interface.         SimpleDelegate setQuestion = delegate()         {             trvSubscriptions.Items.Clear();             TreeViewItem topicItem = new TreeViewItem()             {                 Header = AccountDetails.ScatterGatherTopic             };               foreach (SubscriptionDescription subscription in subscriptions)             {                 TreeViewItem subscriptionItem = new TreeViewItem()                 {                     Header = subscription.Name                 };                 topicItem.Items.Add(subscriptionItem);             }             trvSubscriptions.Items.Add(topicItem);               topicItem.ExpandSubtree();         };         this.Dispatcher.BeginInvoke(DispatcherPriority.Send, setQuestion);           Thread.Sleep(3000);     } }       Voting Application The voting application is implemented as another WPF application. This one is more basic, and allows the user to vote “Yes” or “No” for the questions sent by the poll manager application. The user interface for that application is shown below. When an instance of the voting application is created it will create a subscription in the questions topic using a GUID as the subscription name. The application can then receive copies of every question message that is sent to the topic. Clients for the new subscription and the votes queue are created, along with a background worker to receive the question messages. The voting application is set to receiving mode, meaning it is ready to receive a question message from the subscription.   public MainWindow() {     InitializeComponent();       // Set the mode to receiving.     IsReceiving = true;       // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Create a subcription for this instance     NamespaceManager mgr = new NamespaceManager(serviceBusUri, credentials);     string subscriptionName = Guid.NewGuid().ToString();     mgr.CreateSubscription(AccountDetails.ScatterGatherTopic, subscriptionName);       // Create the subscription and queue clients.     ScatterGatherSubscriptionClient = factory.CreateSubscriptionClient         (AccountDetails.ScatterGatherTopic, subscriptionName);     ScatterGatherQueueClient =         factory.CreateQueueClient(AccountDetails.ScatterGatherQueue);       // Start the background worker thread.     BackgroundWorker = new BackgroundWorker();     BackgroundWorker.DoWork += new DoWorkEventHandler(ReceiveMessages);     BackgroundWorker.RunWorkerAsync(); }     I took the inspiration for creating the subscriptions in the voting application from the chat application that uses topics and subscriptions blogged by Ovais Akhter here. The method that receives the question messages runs on a background thread. If the application is in receive mode, a question message will be received from the subscription, the question will be displayed in the user interface, the voting buttons enabled, and IsReceiving set to false to prevent more questing from being received before the current one is answered.   // This runs on a background worker. private void ReceiveMessages(object sender, DoWorkEventArgs e) {     while (true)     {         if (IsReceiving)         {             // Receive a question message from the topic.             BrokeredMessage msg = ScatterGatherSubscriptionClient.Receive();             if (msg != null)             {                 // Deserialize the message.                 Question question = msg.GetBody<Question>();                   // Update the user interface.                 SimpleDelegate setQuestion = delegate()                 {                     lblQuestion.Content = question.QuestionText;                     btnYes.IsEnabled = true;                     btnNo.IsEnabled = true;                 };                 this.Dispatcher.BeginInvoke(DispatcherPriority.Send, setQuestion);                 IsReceiving = false;                   // Mark the message as complete.                 msg.Complete();             }         }         else         {             Thread.Sleep(1000);         }     } }     When the user clicks on the Yes or No button, the btnVote_Click method is called. This will create a new Vote data contract with the appropriate question and answer and send the message to the poll manager application using the votes queue. The user voting buttons are then disabled, the question text cleared, and the IsReceiving flag set to true to allow a new message to be received.   private void btnVote_Click(object sender, RoutedEventArgs e) {     // Create a new vote.     Vote vote = new Vote()     {         QuestionText = (string)lblQuestion.Content,         IsYes = ((sender as Button).Content as string).Equals("Yes")     };       // Send the vote message.     BrokeredMessage msg = new BrokeredMessage(vote);     ScatterGatherQueueClient.Send(msg);       // Update the user interface.     lblQuestion.Content = "";     btnYes.IsEnabled = false;     btnNo.IsEnabled = false;     IsReceiving = true; }     Testing the Application In order to test the application, an instance of the poll manager application is started; the user interface is shown below. As no instances of the voting application have been created there are no subscriptions present in the topic. When an instance of the voting application is created the subscription will be displayed in the poll manager. Now that a voting application is subscribing, a questing can be sent from the poll manager application. When the message is sent to the topic, the voting application will receive the message and display the question. The voter can then answer the question by clicking on the appropriate button. The results of the vote are updated in the poll manager application. When two more instances of the voting application are created, the poll manager will display the new subscriptions. More questions can then be broadcast to the voting applications. As the question messages are queued up in the subscription for each voting application, the users can answer the questions in their own time. The vote messages will be received by the poll manager application and aggregated to display the results. The screenshots of the applications part way through voting are shown below. The messages for each voting application are queued up in sequence on the voting application subscriptions, allowing the questions to be answered at different speeds by the voters.

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  • Oracle Solaris 11.1 Blog Post Roundup

    - by Larry Wake
    Here are a few recent posts about the also-recent Oracle Solaris 11.1 release: Title Author What's New in Solaris 11.1? Karoly Vegh New ZFS Encryption features in Solaris 11.1 Darren Moffat Solaris 11.1: Encrypted Immutable Zones on (ZFS) Shared Storage Darren Moffat High Resolution Timeouts Steve Sistare Solaris 11.1: Changes to included FOSS packages Alan Coopersmith Documentation Changes in Solaris 11.1 Alan Coopersmith How to Update to Oracle Solaris 11.1 Usingthe Image Packaging System Peter Dennis svcbundle for easier SMF manifest creation Glynn Foster Controlling server configurations with IPS Bart Smallders You can also see Markus Weber's list of interesting posts about Oracle Solaris 11 from last year, or take a look at my shortcut on how to search for Solaris posts by tag. If that's not enough, don't forget to register for next Wednesday's Oracle Solaris 11.1 and Oracle Solaris Cluster 4.1 webcast with a live Q&A. It's November 7th, at 8 AM PT. The last time we did this, we got almost 300 questions, so for Wednesday, we're making sure we've got lots of engineers with fingers poised over their keyboards, ready for action.

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  • Faut-il être bon en math pour être un bon développeur ? Quelle place ont les maths dans votre parcou

    Faut-il être bon en math pour être un bon développeur ? Quelle place ont les maths dans votre métier et votre parcours ? Faut-il être bon en math pour être un bon développeur ? La question mérite d'être posée. Certes, l'informatique est à classer, dans le système universitaire, du coté des sciences "dures", par oppositions aux sciences sociales et humaines. L'enseignement des mathématiques et la rigueur qu'elles amènent paraissent donc indispensable. Pourtant, beaucoup, comme Alan Skorkin - qui vient d'aborder ce sujet sur son blog -, reconnaissent qu'ils n'ont jamais vraiment eu besoin des maths dans leur travail. La position de Alan Skorkin est c...

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  • Planning an Event&ndash;SPS NYC

    - by MOSSLover
    I bet some of you were wondering why I am not going to any events for the most part in June and July (aside from volunteering at SPS Chicago).  Well I basically have no life for the next 2 months.  We are approaching the 11th hour of SharePoint Saturday New York City.  The event is slated to have 350 to 400 attendees.  This is second year in a row I’ve helped run it with Jason Gallicchio.  It’s amazingly crazy how much effort this event requires versus Kansas City.  It’s literally 2x the volume of attendees, speakers, and sponsors plus don’t even get me started about volunteers.  So here is a bit of the break down… We have 30 volunteers+ that Tasha Scott from the Hampton Roads Area will be managing the day of the event to do things like timing the speakers, handing out food, making sure people don’t walk into the event that did not sign up until we get a count for fire code, registering people, watching the sharpees, watching the prizes, making sure attendees get to the right place,  opening and closing the partition in the big room, moving chairs, moving furniture, etc…Then there is Jason, Greg, and I who will be making sure that the speakers, sponsors, and everything is going smoothly in the background.  We need to make sure that everything is setup properly and in the right spot.  We also need to make sure signs are printed, schedules are created, bags are stuffed with sponsor material.  Plus we need to send out emails to sponsors reminding them to send us the right information to post on the site for charity sessions, send us boxes with material to stuff bags, and we need to make sure that Michael Lotter gets there information for invoicing.  We also need to check that Michael has invoiced everyone and who has paid, because we can’t order anything for the event without money.  Once people have paid we need to setup food orders, speaker and volunteer dinners, buy prizes, buy bags, buy speakers/volunteer/organizer shirts, etc…During this process we need all the abstracts from speakers, all the bios, pictures, shirt sizes, and other items so we can create schedules and order items.  We also need to keep track of who is attending the dinner the night before for volunteers and speakers and make sure we don’t hit capacity.  Then there is attendee tracking and making sure that we don’t hit too many attendees.  We need to make sure that attendees know where to go and what to do.  We have to make all kinds of random supply lists during this process and keep on track with a variety of lists and emails plus conference calls.  All in all it’s a lot of work and I am trying to keep track of it all the top so that we don’t duplicate anything or miss anything.  So basically all in all if you don’t see me around for another month don’t worry I do exist. Right now if you look at what I’m doing I am traveling every Monday morning and Thursday night back and forth to Washington DC from New Jersey.  Every night I am working on organizational stuff for SharePoint Saturday New York City.  Every Tuesday night we are running an event conference call.  Every weekend I am either with family or my boyfriend and cat trying hard not to touch the event.  So all my time is pretty much work, event, and family/boyfriend.  I have 0 bandwidth for anything in the community.  If you compound that with my severe allergy problems in DC and a doctor’s appointment every month plus a new med once a week I’m lucky I am still standing and walking.  So basically once July 30th hits hopefully Jason Gallicchio, Greg Hurlman, and myself will be able to breathe a little easier.  If I forget to do this thank you Greg and Jason.  Thank you Tom Daly.  Thank you Michael Lotter.  Thank you Tasha Scott.  Thank you Kevin Griffin.  Thank you all the volunteers, speakers, sponsors, and attendees who will and have made this event a success.  Hopefully, we have enough time until next year to regroup, recharge, and make the event grow bigger in a different venue.  Awesome job everyone we sole out within 3 days of registration and we still have several weeks to go.  Right now the waitlist is at 49 people with room to grow.  If you attend the event thank all these guys I mentioned above for making it possible.  It’s going to be awesome I know it but I probably won’t remember half of it due to the blur of things that we will all be taking care of the day of the event.  Catch you all in the end of July/Early August where I will attempt to post something useful and clever and possibly while wearing a fez. Technorati Tags: SPS NYC,SharePoint Saturday,SharePoint Saturday New York City

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  • Asciidoctor / NetBeans

    - by Geertjan
    With Jason Lee's NetBake plugin (https://bitbucket.org/jdlee/netbake), when you've installed JRuby and then the Asciidoctor gem, you're good to go to use Asciidoctor with NetBeans IDE. New Asciidoc files can be created, which have a Source view... ...and a Visual view. The current content of the text editor is parsed by the Asciidoctor gem and the resulting HTML is displayed in a JEditorPane: Awestruct support is also part of the NetBake plugin, with a new project type and other related features. An Options window is included for configuring the plugin: I've been in touch with Jason and we're discussing separating the Asciidoctor parts from the Awestruct parts and then putting them seperately as plugins on the NetBeans Plugin Portal.

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