We recently wanted to get the Git history of a file which we knew existed but had now been deleted so we could find out what had happened to it. Using a simple git log didn’t work: git log deletedFile.txt fatal: ambiguous argument 'deletedFile.txt': unknown revision or path not in the working tree. We eventually came across Francois Marier’s blog post which points out that you need to use the following command instead: git log -- deletedFile.txt I’ve tried reading through the man page but I’m still not entirely sure what the distinction between using – and not using it is supposed to be. If someone could explain it that’d be cool… From http://www.markhneedham.com/blog/2011/10/04/git-getting-the-history-of-a-deleted-file

If you're looking for a cloud expert, specifically someone who knows Amazon Web Services and EC2, you'll want to have a battery of questions to assess their knowledge.

The integration framework Apache Camel already supports several important cloud services (see my overview article at http://www.kai-waehner.de/blog/2011/07/09/cloud-computing-heterogeneity-will-require-cloud-integration-apache-camel-is-already-prepared for more details). This article describes the combination of Apache Camel and the Amazon Web Services (AWS) interfaces of Simple Storage Service (S3), Simple Queue Service (SQS) and Simple Notification Service (SNS). Thus, The concept of Infrastructure as a Service (IaaS) is used to access messaging systems and data storage without any need for configuration. Registration to AWS and Setup of Camel First, you have to register to the Amazon Web Services (for free). Most AWS services include a free monthly quota, which is absolutely sufficient to play around and develop some simple applications. As its name states, AWS uses technology-independent web services. Besides, APIs for several different programming languages are available to ease development. By the way, Camel uses the AWS SDK for Java (http://aws.amazon.com/sdkforjava), of course. The documentation is detailed and easy to understand, including tutorials, screenshots and code examples . Hint 1: You should read the introductions to S3, SQS and SNS (go to http://aws.amazon.com and click on „products“) and play around with the AWS Management Console (http://aws.amazon.com/console) before you continue. This step is very easy and takes less than one hour. Then, you will have a much better understanding about AWS and where Camel can help you! Hint 2: It really helps to look at the source code of the camel-aws component, It helps you to understand how Camel uses the AWS Java API internally. If you want to write tests, you can do it the same way. In the past, I was afraid of looking at „complex“ source code of open source frameworks. But there is no need to be scared! The camel-aws component (and most other camel components) contain only of a few classes. Everything is easy to understand. It helps you to understand Camel internals, the AWS API, and to spot and solve errors due to exceptions in your code. In the meanwhile, the current Camel version 2.8 supports three AWS services: S3, SQS and SNS. All of them use similar concepts. Therefore, they are included in one single camel component: „camel-aws“. You have to add the libraries to your existing Camel project. As always, the simplest way is to use Maven and add the following dependency to the pom.xml: org.apache.camel camel-aws ${camel-version} Configuration of the Camel Endpoint The implementation and configuration of all three services is very similar. The URI looks like this (the code shows the SQS service): aws-sqs://queue-name[?options] There are two alternatives to configure your endpoint. Using Parameters The easy way is to use two paramters in the URI of your endpoint: „accessKey“ and „secretKey“ (you receive both after your AWS registration). “aws-sqs://unique-queue-name?accessKey=“INSERT_ME“&secretKey=INSERT_ME” Be aware of the following problem, which can result in a strange, non-speaking exception (thanks to Brendan Long): You’ll need to URL encode any +’s in your secret key (otherwise, they’ll be treated as spaces). + = %2B, so if your secretkey was “my+secret\key”, your Camel URL should have “secretKey=my%2Bsecret\key”. “Within the query string, the plus sign is reserved as shorthand notation for a space. Therefore, real plus signs must be encoded. This method was used to make query URIs easier to pass in systems which did not allow spaces.” Source: WC3 URI Recommendations Adding a configured AmazonClient to the Registry If you need to do more configuration (e.g. because your system is behind a firewall), you have to add an AmazonClient object to your registry. The following code shows an example using SQS, but SNS and S3 use exactly the same concept. @Override protected JndiRegistry createRegistry() throws Exception { JndiRegistry registry = super.createRegistry(); AWSCredentials awsCredentials = new BasicAWSCredentials(“INSERT_ME”, “INSERT_ME”); ClientConfiguration clientConfiguration = new ClientConfiguration(); clientConfiguration.setProxyHost(“http://myProxyHost”); clientConfiguration.setProxyPort(8080); AmazonSQSClient client = new AmazonSQSClient(awsCredentials, clientConfiguration); registry.bind(“amazonSQSClient”, client); return registry; } This example overwrites the createRegistry() method of a JUnit test (extending CamelTestSupport). You can also add this information to your runtime Camel application, of course. Apache Camel and the Simple Storage Service (S3) Simple Storage Service (S3) is a key-value-store. You can store small to very large data. The usage is very easy. You create buckets and put key-value data into these buckets. You can also create folders within buckets to organize your data. That’s it. You can monitor your buckets using the AWS Management Console – an intuitive GUI supporting most AWS services. The following example shows both alternatives for accessing the Amazon services (as described above): Paramenters and the AmazonClient. // Transfer data from your file inbox to the AWS S3 service from(“file:files/inbox”) // This is the key of your key-value data .setHeader(S3Constants.KEY, simple(“This is a static key”)) // Using parameters for accessing the AWS service .to(“aws-s3://camel-integration-bucket-mwea-kw?accessKey=INSERT_ME&secretKey=INSERT_ME&region=eu-west-1″); // Transfer data from the AWS S3 service to your file outbox from(“aws-s3://camel-integration-bucket-mwea-kw?amazonS3Client=#amazonS3Client&region=eu-wes”) .to(“file:files/outbox”); There are some additional parameters, for instance you can submit the desired AWS region or delete data after receiving it (see http://camel.apache.org/aws-s3.html and the corresponding SQS and SNS sites for more details about parameters and message headers). As you see in the code, you can use the AWS-S3 endpoint for producing and for consuming messages. Each bucket must be unique, thus you have to add some specific information such as your company to its name. Hint: If a bucket does not exist, Camel is creating it automatically (as the AWS API does). This concept is also used for SQS queues and SNS topics. Apache Camel and the Simple Queue Service (SQS) The Simple Queue Service (SQS) is similar to a JMS provider such as WebSphere MQ or ActiveMQ (but with some differences). You create queues and send messages to them. Consumers receive the messages. Contrary to most other AWS services, you cannot monitor queues by using the AWS management console directly. You have to use the service „Cloudwatch“ (http://aws.amazon.com/cloudwatch) and start an EC2 instance to monitor queues and its content. As you can see in the following code example, the syntax and concepts are almost the same as for the S3 service: from(“file:inbox”) .to(“aws-sqs://camel-integration-queue-mwea-kw?accessKey=INSERT_ME&secretKey=INSERT_ME”); from(“aws-sqs://camel-integration-queue-mwea-kw?amazonSQSClient=#amazonSQSClient”) .to(“file:outbox?fileName=sqs-${date:now:yyyy.MM.dd-hh:mm:ss:SS}”); Again, you can use the AWS-SQS endpoint for producing and for consuming messages. Each queue name must be unique. There exist two important differences to JMS (copy & paste from the AWS documentation): Q: How many times will I receive each message? Amazon SQS is engineered to provide “at least once” delivery of all messages in its queues. Although most of the time each message will be delivered to your application exactly once, you should design your system so that processing a message more than once does not create any errors or inconsistencies. Q: Why are there separate ReceiveMessage and DeleteMessage operations? When Amazon SQS returns a message to you, that message stays in the queue, whether or not you actually received the message. You are responsible for deleting the message; the delete request acknowledges that you’re done processing the message. If you don’t delete the message, Amazon SQS will deliver it again on another receive request. Apache Camel and the Simple Notification Service (SNS) The Simple Notification Service (SNS) acts like JMS topics. You create a topic, consumers subscribe to the topic and then receive notifications. Several transport protocols are supported: HTTP(S), Email and SQS. Further interfaces will be added in the future, e.g. the Short Message Service (SMS) for mobile phones. Contrary to S3 and SQS, Camel only offers a producer endpoint for this AWS service. You can only create topics and send messages via Camel. The reason is simple: Camel already offers endpoints for consuming these messages: HTTP, Email and SQS are already available. There is one tradeoff: A consumer cannot subscribe to topics using Camel – at the moment. The AWS Management Console has to be used. A very interesting discussion can be read on the Camel JIRA issue regarding the following questions: Should Camel be able to subscribe to topics? Should the producer contain this feature or should there be a consumer? In my opinion, there should be a consumer which is able to subscribe to topics, otherwise Camel is missing a key part of the AWS SNS service! Please read the discussion and contribute your opinion: https://issues.apache.org/jira/browse/CAMEL-3476. Apache Camel is already ready for the Cloud Computing Era AWS offers many more services for the cloud. Probably, it does not make sense to integrate everyone into Camel, but more AWS services will be supported in the future. For instance, SimpleDB and the Relational Database Service (RDS) are already planned and make sende, too: http://camel.apache.org/aws.html. The conclusion is easy: Apache Camel is already ready for the cloud computing era. Several important cloud services are already supported. Cloud integration will become very important in the future. Thus, Camel is on a very good way. Hopefully, we will see more cloud components, soon. I will continue to write articles about other Camel cloud components (and new AWS addons, ouf course). For instance, a component for the Platform as a Service (PaaS) product Google App Engine (GAE) is already available. If you have any additional important information, questions or other feedback, please write a comment. Thank you in advance… Best regards, Kai Wähner (Twitter: @KaiWaehner) [Content from my Blog: Cloud Integration with Apache Camel and Amazon Web Services (AWS): S3, SQS and SNS]

The "WZL Gear Toolbox", by the Laboratory for Machine Tools and Production Engineering at RWTH Aachen University, represents a unified graphical user interface containing different simulation programs for gear applications. It enables the usage of the following simulations: manufacturing simulation "GearGenerator" process simulation "SPARTApro" process simulation "KegelSpan" tooth contact analysis "ZaKo3D" The uniform graphical user interface enables the user to realize the simulations and to analyze the calculation results in a comfortable way. Thus, the "WZL Gear Toolbox" enables the analysis of the running behavior of gears by means of tooth contact analysis of the manufacturing-related deviations from the generating grinding. The long-term goal of the uniform graphical user interface is to provide a software tool containing the whole production chain of gear manufacturing. The "WZL Gear Toolbox" is funded by the WZL Gear Research Circle. Screenshot

I am Angelo D'Agnano and currently I work at the NATO Programming Centre as Software Architect.

This article describes how to create a simple HTML5 chat application using WebSockets to connect to a Java back-end.

The most common scenario to use diff is to see what changes you made after your last commit. Let’s see how to do it.

I am an experienced Java developer who has used various IDEs and prefer NetBeans IDE over all others by a long shot. I am also very fond of Maven as the tool to simplify and automate nearly every aspect of the development of my Java project throughout its lifecycle. Recently, I started developing Android applications and naturally I looked for a Maven plugin that would manage my Android projects. Luckily I found the maven-android-plugin which worked like a charm and allowed me to use Maven for developing my Android projects. The Android Emulator from the Android SDK seemed unusably slow. Lucklily, I found a way to use an Android Virtual Machine for VirtualBox that worked nearly as fast as my native computer! This page documents my experiences. Tested Environment Dev machine: Ubuntu 11.04 Linux IDE: NetBeans VirtualBox: 4.0.8 r71778 Android SDK Revision 11, Add on XML Schema #1, Repository XML Schema #3 (from About in SDK and AVD Manager) Android Version: 2.2 Overview of Steps Download and install the Android SDK on your dev machine Attach an Android Device to dev machine Configure and load your device for development and other use Create an initial Android maven project Connect Android Device to Android SDK Debug Android app using NetBeans Graphical Debuger Download and Install Android SDK Download and install the Android SDK on your dev machine as described here. Make sure to set the following in dev machine ~/.bashrc file: export ANDROID_HOME=$HOME/android-sdk-linux_x86 #Change as needed export PATH="$ANDROID_HOME/tools:$ANDROID_HOME/platform-tools:$PATH" Attaching an Android Device to Dev Machine If you have an actual device that is usually always best. If not, you must use a virtual Android device which usually has various limitations (e.g. no GPS, Camera etc.). The Android SDK makes it easy to create a new Virtual Device but the resulting device is painfully slow in my experience and not usable. Do not bother with this. Instead, create a virtual Android device using VirtualBox as described in the following steps: Install virtual box and initial Android VM as described here: http://androidspin.com/2011/01/24/howto-install-android-x86-2-2-in-virtualbox/ http://geeknizer.com/how-to-run-google-android-in-virtualbox-vmware-on-netbooks/ Configure Android VM so it is connected bidirectionally with your dev machine over TCP as described here: http://stackoverflow.com/questions/61156/virtualbox-host-guest-network-setup I used the approach of configuring a HOST ONLY network adapater and a second NAT adapter on the Android VM within virtual box. Configuring your Android Device This section describes various things I did to setup a dev environment for my Android device: Root the device. I used Universal AndRoot Install ConnectBot so you have ssh and related network utilities Creating Initial Android Maven Application Create initial project using instructions here. I found it best to create stub project structure using the maven-archtype-plugin and the archtypes at https://github.com/akquinet/android-archetypes/wiki Connecting Android VM Device to Android SDK In order for your code to be deployed from NetBeans IDE to Android Device and in order for you to monitor your deployed app from the Dalvik Debug Monitor (ddms) you need to connect your android VM device to the android sdk over TCP as described in the following steps. On Android Device open the Terminal Emulator Type su to become root (your device must be rooted for this Type following commands in root shell: setprop service.adb.tcp.port 5555 stop adbd start adbd Type the following commands on dev machine shell. TODO: Note that IP address below is whatever is the ip address associated with the device (see ifconfig on linux for device vboxnet0) adb tcpip 5555 adb connect 192.168.0.101:5555 For details on above steps see: http://stackoverflow.com/questions/2604727/how-can-i-connect-to-android-with-adb-over-tcp Set up port forwarding as described here http://redkrieg.com/2010/10/11/adb-over-ssh-fun-with-port-forwards/ (this is where I am most fuzzy) Build your maven android project using Right-Click / Clean and Build Now for the acid test whether you can deploy your app to the device from NetBeans IDE! Right-click / Custom / Goal to show Run Maven dialog. Enter android:deploy in Goals field. Select Remember As button and enter android:deploy for its text field. If all is well, the app will deploy to the device and will show up in its "Applications" screen. Debugging Android App Using NetBeans Graphical Debugger Once you can build and deploy your app to the real or virtual Android device, here are the steps to debug the app using NetBeans debugger: On Device: Start the app (TODO: determine how to start app on device with JVM options so it can wait for debugger connection. This should be easy) On Dev Machine run Dalvik Debug Monitor (ddms) in background: $ANDROID_HOME/tools/ddms & Lookup your app in ddms and get its debug port. This is described here but does not address NetBeans specifically In NetBeans do: Debug / Attach Debugger and specify the port looked up in ddms in previous step. You may leave rest of the fields with defaults. Click OK

A little tip that can be very useful, how to restore a deleted Git tag. If you juste deleted a tag by error, you can easily restore it following these steps. First, use git fsck --unreachable | grep tag then, you will see the unreachable tag. If you have several tags on the list, use git show KEY to found the good tag and finally, when you know which tag to restore, use git update-ref refs/tags/NAME KEY and the previously deleted tag with restore with NAME. Thanks to Shawn Pearce for the tip. From http://www.baptiste-wicht.com/2011/06/git-tip-restore-a-deleted-tag/

Git is a backup system itself: for example, you can version your .txt folders containing TODO lists. Since Git version your files just like it does for code, after accidental deletion or modifications it will be able to bring you back. Yet, if you do not regularly push your commits, a problem with the drive containing the repository may cause the loss of all your work. You can put the repository in Dropbox or on a similar service, but I don't trust it. Dropbox syncs files in .git independently from the rest and from one another, and it may break temporarily or for good the repository. By the way, I only want to snapshot a backup at specific points in time, not always occupying my connection by instant mirroring. A note before beginning: with binary data Git is not proficient as a backup tool: text works a lot better (it's like code). This article is dedicated to the backup of code and textual content. Push is not a backup For example, because it may lack branches. In general, pushing to origin is not even an option as you may not want to push your changes yet, but still perform a backup. It's only in the open source world that backup corresponds to publishing online. However, thanks to decentralization there are some simple solutions, involving the creation of repositorite different from origin: git clone /path/to/working/copy #creates the backup git pull #origin master of course, updates the backup # you can specify better branches via the local configuration of the backup copy (git config) The inverse solution, involging pulling, is also possible: git init . #in the folder of your backup, or you can use a remote repository git remote add backup_repo /path/to/backup/repo #or a git:// repo git push backup #master usually, but also multiple branches git push --all backup #an alternative that pushes all branches All the commands, also the one that will follow, are just bash commands: it's easy to create a script and automate its execution with cron, anacron or whatever you want. The Force"del" Unix is powerful in you. git bundle git bundle is another command that may be used for backup purposes. It will create a single file containing all the refs you need to export from your local repository. It's often used for publishing commits via USB keys or other media in absence of a connection. For one branch, it's simple. This command will create a myrepo.bundle file. git bundle create myrepo.bundle master For more branches or tags, it's still simple: git bundle create myrepo.bundle master other_branch Restoring the content of the bundle is a single comment. Inside an empty repo, type: git bundle unbundle myrepo.bundle Instead if you do not have a repo, and just want to recreate the old one: git clone myrepo.bundle -b master myrepo_folder In emergency situations, bundle comes handy. But my issue with that command is that I always forget something when I use it: for example in my tutorial repository I had a lot of tags, but bundle did not include them by default (you have to specify the whole references list like for master other_branch.) Tarballs An alternative is just to archive the repository in a tar.gz or tar.bz file. tar -cf repository.tar repository/ gzip repository.tar # or bzip2 repository.tar After that, you can use scp or even rsync (but I don't think it will speed up much) to put repository.tar.gz on another medium. The weight is higher in this case, since the repository contains also the checked out working copy. But you don't have to learn new commands: apart from the weight and the lack of incremental updates, this solution works fine. Bare repositories You can use git clone --bare repository/ backup_folder/ to create a bare copy of the repository, as a backup. The bare repository does not maintain a checked out working tree, and as so saves space and time for its transferral. This method can be used in conjunction with the pull/push or the tarball method. For restoring the backup: git clone backup_folder/ new_repository/ will recreate the original situation in new_repository. In any of the cases the new folders are created automatically. I won't advise to just copy the folder as often on other backup filesystems (like an USB key's vfat) permissions, owner and other metadata are lost. Conclusion So now you have some alternatives for backing up your repositories or transporting them without setting up a server like Gitosis or passing from the publicly available Github. In fact, I researched this techniques for transporting my tutorial code to phpDay 2011 and the Dutch PHP Conference, and they have worked pretty well.

The inspection of the error logs is a common way to detect errors and bugs. We also can show errors on-screen within our developement server, or we even can use great tools like firePHP to show our PHP errors and warnings inside our firebug console. That’s cool, but we only can see our session errors/warnings. If we want to see another’s errors we need to inspect the error log. tail -f is our friend, but we need to surf against all the warnings of all sessions to see our desired ones. Because of that I want to build a tool to monitor my PHP applications in real-time. Let’s start: What’s the idea? The idea is catch all PHP’s errors and warnings at run time and send them to a node.js HTTP server. This server will work similar than a chat server but our clients will only be able to read the server’s logs. Basically the applications have three parts: the node.js server, the web client (html5) and the server part (PHP). Let me explain a bit each part: The node Server Basically it has two parts: a http server to handle the PHP errors/warnings and a websocket server to manage the realtime communications with the browser. When I say that I’m using websockets that’s means the web client will only work with a browser with websocket support like chrome. Anyway it’s pretty straightforward swap from a websocket sever to a socket.io server to use it with every browser. But websockets seems to be the future, so I will use websockets in this example. The http server: http.createServer(function (req, res) { var remoteAdrress = req.socket.remoteAddress; if (allowedIP.indexOf(remoteAdrress) >= 0) { res.writeHead(200, { 'Content-Type': 'text/plain' }); res.end('Ok\n'); try { var parsedUrl = url.parse(req.url, true); var type = parsedUrl.query.type; var logString = parsedUrl.query.logString; var ip = eval(parsedUrl.query.logString)[0]; if (inspectingUrl == "" || inspectingUrl == ip) { clients.forEach(function(client) { client.write(logString); }); } } catch(err) { console.log("500 to " + remoteAdrress); res.writeHead(500, { 'Content-Type': 'text/plain' }); res.end('System Error\n'); } } else { console.log("401 to " + remoteAdrress); res.writeHead(401, { 'Content-Type': 'text/plain' }); res.end('Not Authorized\n'); } }).listen(httpConf.port, httpConf.host); and the web socket server: var inspectingUrl = undefined; ws.createServer(function(websocket) { websocket.on('connect', function(resource) { var parsedUrl = url.parse(resource, true); inspectingUrl = parsedUrl.query.ip; clients.push(websocket); }); websocket.on('close', function() { var pos = clients.indexOf(websocket); if (pos >= 0) { clients.splice(pos, 1); } }); }).listen(wsConf.port, wsConf.host); If you want to know more about node.js and see more examples, have a look to the great site: http://nodetuts.com/. In this site Pedro Teixeira will show examples and node.js tutorials. In fact my node.js http + websoket server is a mix of two tutorials from this site. The web client. The web client is a simple websockets application. We will handle the websockets connection, reconnect if it dies and a bit more. I’s based on node.js chat demo Real time monitor Socket status: Conecting ...IP: [all]" ?>count: 0 And the javascript magic var timeout = 5000; var wsServer = '192.168.2.2:8880'; var unread = 0; var focus = false; var count = 0; function updateCount() { count++; $("#count").text(count); } function cleanString(string) { return string.replace(/&/g,"&").replace(//g,">"); } function updateUptime () { var now = new Date(); $("#uptime").text(now.toRelativeTime()); } function updateTitle(){ if (unread) { document.title = "(" + unread.toString() + ") Real time " + selectedIp + " monitor"; } else { document.title = "Real time " + selectedIp + " monitor"; } } function pad(n) { return ("0" + n).slice(-2); } function startWs(ip) { try { ws = new WebSocket("ws://" + wsServer + "?ip=" + ip); $('#toolbar').css('background', '#65A33F'); $('#socketStatus').html('Connected to ' + wsServer); //console.log("startWs:" + ip); //listen for browser events so we know to update the document title $(window).bind("blur", function() { focus = false; updateTitle(); }); $(window).bind("focus", function() { focus = true; unread = 0; updateTitle(); }); } catch (err) { //console.log(err); setTimeout(startWs, timeout); } ws.onmessage = function(event) { unread++; updateTitle(); var now = new Date(); var hh = pad(now.getHours()); var mm = pad(now.getMinutes()); var ss = pad(now.getSeconds()); var timeMark = '[' + hh + ':' + mm + ':' + ss + '] '; logString = eval(event.data); var host = logString[0]; var line = "" + timeMark + "" + host + ""; line += "" + logString[1]; + ""; if (logString[2]) { line += " " + logString[2] + ""; } $('#log').append(line); updateCount(); window.scrollBy(0, 100000000000000000); }; ws.onclose = function(){ //console.log("ws.onclose"); $('#toolbar').css('background', '#933'); $('#socketStatus').html('Disconected'); setTimeout(function() {startWs(selectedIp)}, timeout); } } $(document).ready(function() { startWs(selectedIp); }); The server part: The server part will handle silently all PHP warnings and errors and it will send them to the node server. The idea is to place a minimal PHP line of code at the beginning of the application that we want to monitor. Imagine the following piece of PHP code $a = $var[1]; $a = 1/0; class Dummy { static function err() { throw new Exception("error"); } } Dummy1::err(); it will throw: A notice: Undefined variable: var A warning: Division by zero An Uncaught exception ‘Exception’ with message ‘error’ So we will add our small library to catch those errors and send them to the node server include('client/NodeLog.php'); NodeLog::init('192.168.2.2'); $a = $var[1]; $a = 1/0; class Dummy { static function err() { throw new Exception("error"); } } Dummy1::err(); The script will work in the same way than the fist version but if we start our node.js server in a console: $ node server.js HTTP server started at 192.168.2.2::5672 Web Socket server started at 192.168.2.2::8880 We will see those errors/warnings in real-time when we start our browser Here we can see a small screencast with the working application: This is the server side library: class NodeLog { const NODE_DEF_HOST = '127.0.0.1'; const NODE_DEF_PORT = 5672; private $_host; private $_port; /** * @param String $host * @param Integer $port * @return NodeLog */ static function connect($host = null, $port = null) { return new self(is_null($host) ? self::$_defHost : $host, is_null($port) ? self::$_defPort : $port); } function __construct($host, $port) { $this->_host = $host; $this->_port = $port; } /** * @param String $log * @return Array array($status, $response) */ public function log($log) { list($status, $response) = $this->send(json_encode($log)); return array($status, $response); } private function send($log) { $url = "http://{$this->_host}:{$this->_port}?logString=" . urlencode($log); $ch = curl_init(); curl_setopt($ch, CURLOPT_URL, $url); curl_setopt($ch, CURLOPT_NOBODY, true); curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); $response = curl_exec($ch); $status = curl_getinfo($ch, CURLINFO_HTTP_CODE); curl_close($ch); return array($status, $response); } static function getip() { $realip = '0.0.0.0'; if ($_SERVER) { if ( isset($_SERVER['HTTP_X_FORWARDED_FOR']) && $_SERVER['HTTP_X_FORWARDED_FOR'] ) { $realip = $_SERVER["HTTP_X_FORWARDED_FOR"]; } elseif ( isset($_SERVER['HTTP_CLIENT_IP']) && $_SERVER["HTTP_CLIENT_IP"] ) { $realip = $_SERVER["HTTP_CLIENT_IP"]; } else { $realip = $_SERVER["REMOTE_ADDR"]; } } else { if ( getenv('HTTP_X_FORWARDED_FOR') ) { $realip = getenv('HTTP_X_FORWARDED_FOR'); } elseif ( getenv('HTTP_CLIENT_IP') ) { $realip = getenv('HTTP_CLIENT_IP'); } else { $realip = getenv('REMOTE_ADDR'); } } return $realip; } public static function getErrorName($err) { $errors = array( E_ERROR => 'ERROR', E_RECOVERABLE_ERROR => 'RECOVERABLE_ERROR', E_WARNING => 'WARNING', E_PARSE => 'PARSE', E_NOTICE => 'NOTICE', E_STRICT => 'STRICT', E_DEPRECATED => 'DEPRECATED', E_CORE_ERROR => 'CORE_ERROR', E_CORE_WARNING => 'CORE_WARNING', E_COMPILE_ERROR => 'COMPILE_ERROR', E_COMPILE_WARNING => 'COMPILE_WARNING', E_USER_ERROR => 'USER_ERROR', E_USER_WARNING => 'USER_WARNING', E_USER_NOTICE => 'USER_NOTICE', E_USER_DEPRECATED => 'USER_DEPRECATED', ); return $errors[$err]; } private static function set_error_handler($nodeHost, $nodePort) { set_error_handler(function ($errno, $errstr, $errfile, $errline) use($nodeHost, $nodePort) { $err = NodeLog::getErrorName($errno); /* if (!(error_reporting() & $errno)) { // This error code is not included in error_reporting return; } */ $log = array( NodeLog::getip(), "{$err} {$errfile}:{$errline}", nl2br($errstr) ); NodeLog::connect($nodeHost, $nodePort)->log($log); return false; }); } private static function register_exceptionHandler($nodeHost, $nodePort) { set_exception_handler(function($exception) use($nodeHost, $nodePort) { $exceptionName = get_class($exception); $message = $exception->getMessage(); $file = $exception->getFile(); $line = $exception->getLine(); $trace = $exception->getTraceAsString(); $msg = count($trace) > 0 ? "Stack trace:\n{$trace}" : null; $log = array( NodeLog::getip(), nl2br("Uncaught exception '{$exceptionName}' with message '{$message}' in {$file}:{$line}"), nl2br($msg) ); NodeLog::connect($nodeHost, $nodePort)->log($log); return false; }); } private static function register_shutdown_function($nodeHost, $nodePort) { register_shutdown_function(function() use($nodeHost, $nodePort) { $error = error_get_last(); if ($error['type'] == E_ERROR) { $err = NodeLog::getErrorName($error['type']); $log = array( NodeLog::getip(), "{$err} {$error['file']}:{$error['line']}", nl2br($error['message']) ); NodeLog::connect($nodeHost, $nodePort)->log($log); } echo NodeLog::connect($nodeHost, $nodePort)->end(); }); } private static $_defHost = self::NODE_DEF_HOST; private static $_defPort = self::NODE_DEF_PORT; /** * @param String $host * @param Integer $port * @return NodeLog */ public static function init($host = self::NODE_DEF_HOST, $port = self::NODE_DEF_PORT) { self::$_defHost = $host; self::$_defPort = $port; self::register_exceptionHandler($host, $port); self::set_error_handler($host, $port); self::register_shutdown_function($host, $port); $node = self::connect($host, $port); $node->start(); return $node; } private static $time; private static $mem; public function start() { self::$time = microtime(TRUE); self::$mem = memory_get_usage(); $log = array(NodeLog::getip(), "Start >>>> {$_SERVER['REQUEST_URI']}"); $this->log($log); } public function end() { $mem = (memory_get_usage() - self::$mem) / (1024 * 1024); $time = microtime(TRUE) - self::$time; $log = array(NodeLog::getip(), "End <<<< mem: {$mem} time {$time}"); $this->log($log); } } And of course the full code on gitHub: RealTimeMonitor

Five easy steps to reset MySQL root password. Stop the MySQL server. Start the MySQL server with the --skip-grant-tables option. (it will not prompt for password) Connect to MySQL server as the root user. Setup new MySQL root password. Exit and restart the MySQL server. ### Shell Commands ### /etc/init.d/mysql stop mysqld_safe --skip-grant-tables & mysql -u root ### SQL Commands ### use mysql; UPDATE user SET password=PASSWORD("new-password") WHERE user='root'; flush privileges; exit ### Shell Commands ### /etc/init.d/mysql stop /etc/init.d/mysql start mysql -u root -pnew-password

Bixo Labs shows how to use Solr as a NoSQL solution for big data Many people use the Hadoop open source project to process large data sets because it’s a great solution for scalable, reliable data processing workflows. Hadoop is by far the most popular system for handling big data, with companies using massive clusters to store and process petabytes of data on thousands of servers. Since it emerged from the Nutch open source web crawler project in 2006, Hadoop has grown in every way imaginable – users, developers, associated projects (aka the “Hadoop ecosystem”). Starting at roughly the same time, the Solr open source project has become the most widely used search solution on planet Earth. Solr wraps the API-level indexing and search functionality of Lucene with a RESTful API, GUI, and lots of useful administrative and data integration functionality. The interesting thing about combining these two open source projects is that you can use Hadoop to crunch the data, and then serve it up in Solr. And we’re not talking about just free-text search; Solr can be used as a key-value store (i.e. a NoSQL database) via its support for range queries. Even on a single server, Solr can easily handle many millions of records (“documents” in Lucene lingo). Even better, Solr now supports sharding and replication via the new, cutting-edge SolrCloud functionality. Background I started using Hadoop & Solr about five years ago, as key pieces of the Krugle code search startup I co-founded in 2005. Back then, Hadoop was still part of the Nutch web crawler we used to extract information about open source projects. And Solr was fresh out of the oven, having just been released as open source by CNET. At Bixo Labs we use Hadoop, Solr, Cascading, Mahout, and many other open source technologies to create custom data processing workflows. The web is a common source of our input data, which we crawl using the Bixo open source project. The Problem During a web crawl, the state of the crawl is contained in something commonly called a “crawl DB”. For broad crawls, this has to be something that works with billions of records, since you need one entry for each known URL. Each “record” has the URL as the key, and contains important state information such as the time and result of the last request. For Hadoop-based crawlers such as Nutch and Bixo, the crawl DB is commonly kept in a set of flat files, where each file is a Hadoop “SequenceFile”. These are just a packed array of serialized key/value objects. Sometimes we need to poke at this data, and here’s where the simple flat-file structure creates a problem. There’s no easy way run queries against the data, but we can’t store it in a traditional database since billions of records + RDBMS == pain and suffering. Here is where scalable NoSQL solutions shine. For example, the Nutch project is currently re-factoring this crawl DB layer to allow plugging in HBase. Other options include Cassandra, MongoDB, CouchDB, etc. But for simple analytics and exploration on smaller datasets, a Solr-based solution works and is easier to configure. Plus you get useful and surprising fun functionality like facets, geospatial queries, range queries, free-form text search, and lots of other goodies for free. Architecture So what exactly would such a Hadoop + Solr system look like? As mentioned previously, in this example our input data comes from a Bixo web crawler’s CrawlDB, with one entry for each known URL. But the input data could just as easily be log files, or records from a traditional RDBMS, or the output of another data processing workflow. The key point is that we’re going to take a bunch of input data, (optionally) munge it into a more useful format, and then generate a Lucene index that we access via Solr. Hadoop For the uninitiated, Hadoop implements both a distributed file system (aka “HDFS”) and an execution layer that supports the map-reduce programming model. Typically data is loaded and transformed during the map phase, and then combined/saved during the reduce phase. In our example, the map phase reads in Hadoop compressed SequenceFiles that contain the state of our web crawl, and our reduce phase write out Lucene indexes. The focus of this article isn’t on how to write Hadoop map-reduce jobs, but I did want to show you the code that implements the guts of the job. Note that it’s not typical Hadoop key/value manipulation code, which is painful to write, debug, and maintain. Instead we use Cascading, which is an open source workflow planning and data processing API that creates Hadoop jobs from shorter, more representative code. The snippet below reads SequenceFiles from HDFS, and pipes those records into a sink (output) that stores them using a LuceneScheme, which in turn saves records as Lucene documents in an index. Tap source = new Hfs(new SequenceFile(CRAWLDB_FIELDS), inputDir); Pipe urlPipe = new Pipe("crawldb urls"); urlPipe = new Each(urlPipe, new ExtractDomain()); Tap sink = new Hfs(new LuceneScheme(SOLR_FIELDS, STORE_SETTINGS, INDEX_SETTINGS, StandardAnalyzer.class, MAX_FIELD_LENGTH), outputDir, true); FlowConnector fc = new FlowConnector(); fc.connect(source, sink, urlPipe).complete(); We defined CRAWLDB_FIELDS and SOLR_FIELDS to be the set of input and output data elements, using names like “url” and “status”. We take advantage of the Lucene Scheme that we’ve created for Cascading, which lets us easily map from Cascading’s view of the world (records with fields) to Lucene’s index (documents with fields). We don’t have a Cascading Scheme that directly supports Solr (wouldn’t that be handy?), but we can make-do for now since we can do simple analysis for this example. We indexed all of the fields so that we can perform queries against them. Only the status message contains normal English text, so that’s the only one we have to analyze (i.e., break the text up into terms using spaces and other token delimiters). In addition, the ExtractDomain operation pulls the domain from the URL field and builds a new Solr field containing just the domain. This will allow us to do queries against the domain of the URL as well as the complete URL. We could also have chosen to apply a custom analyzer to the URL to break it into several pieces (i.e., protocol, domain, port, path, query parameters) that could have been queried individually. Running the Hadoop Job For simplicity and pay-as-you-go, it’s hard to beat Amazon’s EC2 and Elastic Mapreduce offerings for running Hadoop jobs. You can easily spin up a cluster of 50 servers, run your job, save the results, and shut it down – all without needing to buy hardware or pay for IT support. There are many ways to create and configure a Hadoop cluster; for us, we’re very familiar with the (modified) EC2 Hadoop scripts that you can find in the Bixo distribution. Step-by-step instructions are available at http://openbixo.org/documentation/running-bixo-in-ec2/ The code for this article is available via GitHub, at http://github.com/bixolabs/hadoop2solr. The README displayed on that page contains step-by-step instructions for building and running the job. After the job is done, we’ll copy the resulting index out of the Hadoop distributed file system (HDFS) and onto the Hadoop cluster’s master server, then kill off the one slave we used. The Hadoop master is now ready to be configured as our Solr server. Solr On the Solr side of things, we need to create a schema that matches the index we’re generating. The key section of our schema.xml file is where we define the fields. These fields have a one-to-one correspondence with the SOLR_FIELDS we defined in our Hadoop workflow. They also need to use the same Lucene settings as what we defined in the static IndexWorkflow.java STORE_SETTINGS and INDEX_SETTINGS. Once we have this defined, all that’s left is to set up a server that we can use. To keep it simple, we’ll use the single EC2 instance in Amazon’s cloud (m1.large) that we used as our master for the Hadoop job, and run the simple Solr search server that relies on embedded Jetty to provide the webapp container. Similar to the Hadoop job, step-by-step instructions are in the README for the hadoop2solr project on GitHub. But in a nutshell, we’ll copy and unzip a Solr 1.4.1 setup on the EC2 server, do the same for our custom Solr configuration, create a symlink to the index, and then start it running with: Giving it a Try Now comes the interesting part. Since we opened up the default Jetty port used by Solr (8983) on this EC2 instance, we can directly access Solr’s handy admin console by pointing our browser at http://:8983/solr/admin % cd solr % java -Dsolr.solr.home=../solr-conf -Dsolr.data.dir=../solr-data -jar start.jar From here we can run queries against Solr: We can also use curl to talk to the server via HTTP requests: curl http://:8983/solr/select/?q=-status%3AFETCHED+and+-status%3AUNFETCHED The response is XML by default. Below is an example of the response from the above request, where we found 2,546 matches in 94ms. Now here’s what I find amazing. For an index of 82 million documents, running on a fairly wimpy box (EC2 m1.large = 2 virtual cores), the typical response time for a simple query like “status:FETCHED” is only 400 milliseconds, to find 9M documents. Even a complex query such as (status not FETCHED and not UNFETCHED) only takes six seconds. Scaling Obviously we could use beefier boxes. If we switched to something like m1.xlarge (15GB of memory, 4 virtual cores) then it’s likely we could handle upwards of 200M “records” in our Solr index and still get reasonable response times. If we wanted to scale beyond a single box, there are a number of solutions. Even out of the box Solr supports sharding, where your HTTP request can specify multiple servers to use in parallel. More recently, the Solr trunk has support for SolrCloud. This uses the ZooKeeper open source project to simplify coordination of multiple Solr servers. Finally, the Katta open source project supports Lucene-level distributed search, with many of the features needed for production quality distributed search that have not yet been added to SolrCloud. Summary The combination of Hadoop and Solr makes it easy to crunch lots of data and then quickly serve up the results via a fast, flexible search & query API. Because Solr supports query-style requests, it’s suitable as a NoSQL replacement for traditional databases in many situations, especially when the size of the data exceeds what is reasonable with a typical RDBMS. Solr has some limitations that you should be aware of, specifically: · Updating the index works best as a batch operation. Individual records can be updated, but each commit (index update) generates a new Lucene segment, which will impact performance. · Current support for replication, fail-over, and other attributes that you’d want in a production-grade solution aren’t yet there in SolrCloud. If this matters to you, consider Katta instead. · Many SQL queries can’t be easily mapped to Solr queries. The code for this article is available via GitHub, at http://github.com/bixolabs/hadoop2solr. The README displayed on that page contains additional technical details.

I’ve written a couple of posts (here and here) about Java and the JDBC Driver for SQL Server with the promise of eventually writing about how to get a Java application running on the Windows Azure platform. In this post, I’ll deliver on that promise. Specifically, I’ll show you two things: 1) how to connect to a SQL Azure Database from a Java application running locally, and 2) how to connect to a SQL Azure database from an application running in Windows Azure. You should consider these as two ordered steps in moving an application from running locally against SQL Server to running in Windows Azure against SQL Azure. In both steps, connection to SQL Azure relies on the JDBC Driver for SQL Server and SQL Azure. The instructions below assume that you already have a Windows Azure subscription. If you don’t already have one, you can create one here: http://www.microsoft.com/windowsazure/offers/. (You’ll need a Windows Live ID to sign up.) I chose the Free Trial Introductory Special, which allows me to get started for free as long as keep my usage limited. (This is a limited offer. For complete pricing details, see http://www.microsoft.com/windowsazure/pricing/.) After you purchase your subscription, you will have to activate it before you can begin using it (activation instructions will be provided in an email after signing up). Connecting to SQL Azure from an application running locally I’m going to assume you already have an application running locally and that it uses the JDBC Driver for SQL Server. If that isn’t the case, then you can start from scratch by following the steps in this post: Getting Started with the SQL Server JDBC Driver. Once you have an application running locally, then the process for running that application with a SQL Azure back-end requires two steps: 1. Migrate your database to SQL Azure. This only takes a couple of minutes (depending on the size of your database) with the SQL Azure Migration Wizard - follow the steps in the Creating a SQL Azure Server and Creating a SQL Azure Database sections of this post. 2. Change the database connection string in your application. Once you have moved your local database to SQL Azure, you only have to change the connection string in your application to use SQL Azure as your data store. In my case (using the Northwind database), this meant changing this… String connectionUrl = "jdbc:sqlserver://serverName\\sqlexpress;" + "database=Northwind;" + "user=UserName;" + "password=Password"; …to this… String connectionUrl = "jdbc:sqlserver://xxxxxxxxxx.database.windows.net;" + "database=Northwind;" + "user=UserName@xxxxxxxxxx;" + "password=Password"; (where xxxxxxxxxx is your SQL Azure server ID). Connecting to SQL Azure from an application running in Windows Azure The heading for this section might be a bit misleading. Once you have a locally running application that is using SQL Azure, then all you have to do is move your application to Windows Azure. The connecting part is easy (see above), but moving your Java application to Windows Azure takes a bit more work. Fortunately, Ben Lobaugh has written a great post that that shows how to use the Windows Azure Starter Kit for Java to get a Java application (a JSP application, actually) running in Windows Azure: Deploying a Java application to Windows Azure with Command-Line Ant. (If you are using Eclipse, see Ben’s related post: Deploying a Java application to Windows Azure with Eclipse.) I won’t repeat his work here, but I will call out the steps I took in modifying his instructions to deploy a simple JSP page that connects to SQL Azure. 1. Add the JDBC Driver for SQL Server to the Java archive. One step in Ben’s tutorial (see the Select the Java Runtime Environment section) requires that you create a .zip file from your local Java installation and add it to your Java/Azure application. Most likely, your local Java installation references the JDBC driver by setting the classpath environment variable. When you create a .zip file from your java installation, the JDBC driver will not be included and the classpath variable will not be set in the Azure environment. I found the easiest way around this was to simply add the sqljdbc4.jar file (probably located in C:\Program Files\Microsoft SQL Server JDBC Driver\sqljdbc_3.0\enu) to the \lib\ext directory of my local Java installation before creating the .zip file. Note: You can put the JDBC driver in a separate directory, include it when you create the .zip folder, and set the classpath environment variable in the startup.bat script. But, I found the above approach to be easier. 2. Modify the JSP page. Instead of the code Ben suggests for the HelloWorld.jsp file (see the Prepare your Java Application section), use code from your locally running application. In my case, I just used the code from this post after changing the connection string and making a couple minor JSP-specific changes: Northwind Customers That’s it!. To summarize the steps… Migrate your database to SQL Azure with the SQL Azure Migration Wizard. Change the database connection in your locally running application. Use the Windows Azure Starter Kit for Java to move your application to Windows Azure. (You’ll need to follow instructions in this post and instructions above.) Thanks. -Brian

Creating a statically linked version of a unix software saves you in all the circumstances where you can’t install the software as root, when you don’t have development tools on the target machine, when you cannot find a prepackaged version for the specific server, when the libraries available on a server are conflicting with the ones required by your software, etc. Examples: The unix server that hosts this blog, provides me a restricted shell to manage mysql and public web files with minimal access privileges. On this server I periodically update WordPress and other things, and I like to keep the changes under control and backed up with git. The problem is that on this server I haven’t git binaries, and I cannot install software and libraries required. Having the files of my WordPress installation under git version control saved me a lot of time in the past when somebody hacked into the server and changed the php files to do nasty stuff. I was able to easily check what was exactly changed since last legitimate update with “git status” command, and restore things as before. I own a little NAS (network attached storage) which runs a mini distribution of Linux which doesn’t have a prepackaged version of git to install, nor I cannot use any package management tool like apt rpm or yum etc. So I thought that I can compile by myself the git binaries and have them deployed on the target machine. It is possible, but there is an important note: when you build a software on a unix server, the resulting binaries are referencing the libraries installed there, so you cannot easily port the binaries between servers since they have dependencies. What you need is a “statically linked” version of the software, which fortunately it’s not so difficult to achieve. Binaries which are statically linked are usually bigger in size and will possibly require more memory to execute, but they won’t require the specific libraries to be present on the executing computer, since the libraries code is contained in the binaries themselves. Here is how I built a static version of git on an ubuntu virtual machine, that can be ported to other unix servers: # let's make sure we have all we need to proceed $ sudo apt-get install libexpat1-dev asciidoc libz-dev gettext curl # let's create the directory to host the built artifacts $ sudo mkdir /opt/git-1.7.4.1-static # we are ready to download and unpack latest version of git sources $ curl http://kernel.org/pub/software/scm/git/git-1.7.4.1.tar.bz2 | tar xvj $ cd git-1.7.4.1/ # then compile and install the files in the target directory we created $ ./configure --prefix=/opt/git-1.7.4.1-static CFLAGS="${CFLAGS} -static" NO_OPENSSL=1 NO_CURL=1 $ sudo make install $ sudo make install-doc On the above commands, the thing to notice is the CFLAGS=”${CFLAGS} -static” which is used to specify that the libraries must be statically linked with the binaries. The last thing to do is create a tarball of /opt/git-1.7.4.1-static folder and copy that on the target machine; adding the /opt/git-1.7.4.1-static/bin directory to the PATH variable and the /opt/git-1.7.4.1-static/share/man to the MANPATH variable. If possible, it’s a good idea to keep the same installation path on target machine (/opt/git-1.7.4.1-static) since this path gets hardcoded in some git scripts during the build process. But it shouldn’t give too many problems, anyway. From http://en.newinstance.it/2011/02/27/how-to-create-a-statically-linked-version-of-git-binaries/

While we have been evaluating in our blog posts the various features available on popular Cloud Computing platforms today, I thought it might be a good idea to understand when and how all this started and look back at where this began and trace some of the key events in the progress of cloud computing. Amazon like all other Internet companies in the period of the dot com bubble were left with large amounts of underutilized computing infrastructure, reports suggest less than 10% of the server infrastructure of many companies were being used. Amazon may have use cloud computing as a way to provide this unused resources as utility computing service when they launched S3 as the first true cloud computing service in March 2006. 1. Launch of Amazon Web Services in July 2002 The initial version of AWS in 2002 was focused more on making information available from Amazon to partners through a web services model with programmatic and developer support and was very focused on Amazon as a retailer. While this set the stage for the next steps the launch of S3 was the true step towards building a cloud platform. Amazon Press Release 2. S3 Launches in March 2006 Here are some interesting articles on the launch of S3 in 2006. The real breakthrough however was the pricing model for S3 which defined the model of 'pay-per-use' which has now become the defacto standard for cloud pricing. Also the launch of S3 really defined the shift of Amazon from being just a retailer to a strong player in the technology space. Techcrunch Post on S3 on March 14th, 2006 Read Write Web Post on S3 and EC2 on Nov 3rd, 2006 Business Week Article on Jeff Bezos vision on cloud computing on Nov 13th, 2006 3. EC2 Launches in August 2006 EC2 had a much quieter launch in August 2006 but i would think had the bigger impact by making core computing infrastructure available. This completed the loop on enabling a more complete cloud infrastructure being available. In fact at that time analysts had some difficulty in understanding what the big deal is, and thought it looks similar to other hosting services available online only with a different pricing model. Some interesting articles from that time on the launch: Technologyevangelist Blog Virtualization Info 4. Launch of Google App Engine in April 2008 The launch of Google App Engine in 2008 was the entry of the first pure play technology company into the Cloud Computing market. Google a dominant Internet company entering into this market was clearly a major step towards wide spread adoption of cloud computing. As with all their other products they introduced radical pricing models with a free entry level plan and extremely low cost computing and storage services which are currently among the lowest in the market. Techcrunch post on App Engine Launch Google App Engine Launch Post 5. Windows Azure launches Beta in Nov 2009 The entry of Microsoft into Cloud Computing is a clear indication of the growth of the space. Microsoft for long has not accepted the Internet and the web as a significant market and has continued to focus on the desktop market for all these years. I think this is a realization that a clear shift is taking place. The launch of Azure is a key event in the history of cloud computing with the largest software company making a small but significant shift to the web. Launch of Azure Beta Azure General Availability - Feb 2010 You might also like: Cloud Computing, Google App Engine: How big is the market Really ? Comparing Google App Engine with Amazon EC2 Comparing Amazon EC2 and Microsoft Azure Languages Supported by Google App Engine Cloud Computing: What is it really ?

Generally NetBeans IDE works with a default workspace. In this scenario, if you want to manage multiple sets of projects, you have to create a project group, which allows you to switch between project groups as and when required. But the problem in this is that if the workspace is damaged, and you delete it, all your settings are lost and everything is reset to the default NetBeans IDE settings. The solution is to work with multiple workspaces, that is, multiple instances, of NetBeans IDE. And here is how to do that: Right-click the NetBeans IDE shortcut and choose "Properties". In the shortcut tab, in Target, type after netbeans.exe "--userdir [Folder Path]". Make another shortcut of NetBeans IDE and provide a different folder path. Like this you can create as many workspaces as you want. If one workspace is damaged, it will not effect the settings of the others. Isn't that great? :) Also posted at: http://goo.gl/fb/rrvnA

I've blogged a few times now about Git (which I pronounce with a hard 'g' a la "get", as it's supposed to be named for Linus Torvalds, a self-described git, but which I've also heard called pronounced with a soft 'g' like "jet"). Either way, I'm finding it way more efficient and less painful than either CVS or SVN combined. So, to continue this series ([1], [2], [3]), here is how (and why) to pull an SVN repo down as a Git repo, but with the omission of old (irrelevant) revisions and branches. Using SVN for SVN repos In days of yore when working with the JBoss Tools and JBoss Developer Studio SVN repos, I would keep a copy of everything in trunk on disk, plus the current active branch (most recent milestone or stable branch maintenance). With all the SVN metadata, this would eat up substantial amounts of disk space but still require network access to pull any old history of files. The two repos were about 2G of space on disk, for each branch. Sure, there's tooling to be able to diff and merge between branches w/o having both branches physically checked out, but nothing beats the ability to place two folders side by side OFFLINE for deep comparisons. So, at times, I would burn as much as 6-8G of disk simply to have a few branches of source for comparison and merging. With my painfullly slow IDE drive, this would grind my machine to a halt, especially when doing any SVN operation or counting files / disk usage. Using Git for SVN repos naively Recently, I started using git-svn to pull the whole JBDS repo into a local Git repo, but it was slow to create and still unwieldy. And the JBoss Tools repo was too large to even create as a Git repo - the operation would run out of memory while processing old revisions of code to play forward. At this point, I was stuck having individual Git repos for each JBoss Tools component (major source folder) in SVN: archives, as, birt, bpel, build, etc. It worked, but replicating it when I needed to create a matching repo-collection for a branch was painful and time-consuming. As well, all the old revision information was eating even more disk than before: jbosstools' trunk as multiple git-svn clones: 6.1G devstudio's trunk as single git-svn clone: 1.3G So, now, instead of a couple Gb per branch, I was at nearly 4x as much disk usage. But at least I could work offline and not deal w/ network-intense activity just to check history or commit a change. Still, far from ideal. Cloning SVN with standard layout & partial history This past week, I discovered two ways to make the git-svn experience at least an order of magnitude better: Standard layout (-s) - this allows your generated Git repo to contain the usual trunk, branches/* and tags/* layout that's present in the source SVN repo. This is a win because it means your repo will contain the branch information so you can easily switch between branches within the same repo on disk. No more remote network access needed! Revision filter (-r) - this allows your generated Git repo to start from a known revision number instead of starting at its birth. Now instead of taking hours to generate, you can get a repo in minutes by excluding irrelevant (ancient) revisions. So, why is this cool? Because now, instead of having 2G of source+metadata to copy when I want to do a local comparison between branches, the size on disk is merely: jbosstools' trunk as single git-svn clone w/ trunk and single branch: 1.3G devstudio's trunk as single git-svn clone w/ trunk and single branch: 0.13G So, not only is the footprint smaller, but the performance is better and I need never do a full clone (or svn checkout) again - instead, I can just copy the existing Git repo, and rebase it to a different branch. Instead of hours, this operation takes seconds (or minutes) and happens without the need for a network connection. Okay, enough blather. Show me the code! Check out the repo, including only the trunk & most recent branch # Figure out the revision number based on when a branch was created, then # from r28571, returns -r28571:HEAD rev=$(svn log --stop-on-copy \ http://svn.jboss.org/repos/jbosstools/branches/jbosstools-3.2.x \ | egrep "r[0-9]+" | tail -1 | sed -e "s#\(r[0-9]\+\).\+#-\1:HEAD#") # now, fetch repo starting from the branch's initial commit git svn clone -s $rev http://svn.jboss.org/repos/jbosstools jbosstools_GIT Now you have a repo which contains trunk & a single branch git branch -a # list local (Git) and remote (SVN) branches * master remotes/jbosstools-3.2.x remotes/trunk Switch to the branch git checkout -b local/jbosstools-3.2.x jbosstools-3.2.x # connect a new local branch to remote one Checking out files: 100% (609/609), done. Switched to a new branch 'local/jbosstools-3.2.x' git svn info # verify now working in branch URL: http://svn.jboss.org/repos/jbosstools/branches/jbosstools-3.2.x Repository Root: http://svn.jboss.org/repos/jbosstools Switch back to trunk git checkout -b local/trunk trunk # connect a new local branch to remote trunk Switched to a new branch 'local/trunk' git svn info # verify now working in branch URL: http://svn.jboss.org/repos/jbosstools/trunk Repository Root: http://svn.jboss.org/repos/jbosstools Rewind your changes, pull updates from SVN repo, apply your changes; won't work if you have local uncommitted changes git svn rebase Fetch updates from SVN repo (ignoring local changes?) git svn fetch Create a new branch (remotely with SVN) svn copy \ http://svn.jboss.org/repos/jbosstools/branches/jbosstools-3.2.x \ http://svn.jboss.org/repos/jbosstools/branches/some-new-branch From http://divby0.blogspot.com/2011/01/howto-partially-clone-svn-repo-to-git.html

Troy Giunipero (pictured, right) is a student at the University of Edinburgh studying toward an MSc in Computer Science. Formerly, he was one of the NetBeans Docs writers based in Prague, Czech Republic, where he spent most of his time writing Java web tutorials. In this interview, Troy introduces you to The NetBeans E-commerce Tutorial. This is a very detailed tutorial describing just about everything you need to know when creating an e-commerce web application in Java. It has received a lot of very positive feedback. Let's find out about the background of this tutorial and what Troy learnt in writing it. Hi Troy! During your time on the NetBeans team, you wrote a very large tutorial describing how to create an e-commerce site. How and why did you start writing it? Well, there’s a short answer and a long answer to this. The short answer is that I was lucky to take part in Sun’s SEED (Sun Engineering Enrichment and Development) program. I wanted to focus on technical aspects, so I based my curriculum on developing an e-commerce application using Java technologies. I documented my efforts and applied them toward deliverables for the IDE’s 6.8 and 6.9 releases, resulting in the 13-part NetBeans E-commerce Tutorial. The long answer is that I had previously been tasked with creating an e-commerce application for my degree project (I was studying toward a BSc in IT and Computing), and ran into loads of trouble trying to integrate the various technologies into a cohesive, functioning application. I was coming from a non-technical background and found there was a steep learning curve involved in web development. My work was fraught with problems which I can now attribute to poor time-management, and a lack of good, practical, hands-on learning resources. So in a way, working on the AffableBean project (this is the project used in the NetBeans E-commerce Tutorial) was a way for me to go back and attempt to do the whole thing right. With the tutorial, I had two goals in mind: one, I wanted to consolidate my understanding of everything by writing about it, and two, I wanted to help others avoid the problems and pitfalls that I’d earlier ran into by designing a piece of documentation that puts everything together. Can you run us through the basic parts and what they provide? Certainly. First I want to point out that there’s a live demo application (http://dot.netbeans.org:8080/AffableBean/) which I managed to get up and running with help from Honza Pirek from the NetBeans Web Team (thanks Honza!): The application is modeled on the well-known MVC architecture: The tutorial refers to the above diagram at various points, and covers a bunch of different concepts and technologies along the way, including: Project design and planning (unit 2) Designing a data model (using MySQL WorkBench) (unit 4) Forward-engineering the data model into a database schema (unit 4) Database connectivity (units 3, 4, 6) Servlet, JSP/EL and JSTL technologies (units 3, 5, 6) EJB 3 and JPA 2 technologies (unit 7), and transactional support (unit 9) Session management (i.e., for the shopping cart mechanism) (unit 8) Form validation and data conversion (unit 9) Multilingual support (unit 10) Security (i.e., using form-based authentication and encrypted communication) (unit 11) Load testing with JMeter (unit 12) Monitoring the application with the IDE’s Profiler (unit 12) Tips for deployment to a production server (units 12, 13) Also, the tutorial aims to provide ample background information on the whole “Java specifications” concept, with an introduction to the Java Community Process, how final releases include reference implementations, and how these relate to the tutorial application using the IDE’s bundled GlassFish server (units 1, 7). Finally, the tutorial is as much about the above concepts and technologies as it is about learning to make best use of the IDE. I really tried to squeeze as much IDE-centric information in there as possible. So for example you’ll find: An introduction to the IDE’s main windows and their functions (unit 3) A section dedicated to editor tips and tricks (unit 5), and abundant usage of keyboard shortcuts in steps throughout the tutorial Use of the debugger (unit 8) Special “tip boxes” that discuss IDE functionality that is sometimes difficult to fit into conventional documentation. For example, there are tips on using the IDE’s Template Manager (unit 5), GUI support for database tables (unit 6), Javadoc support (unit 8), and support for code templates (unit 9). Did you learn any new things yourself while writing it? Yes! Three things immediately come to mind: EJB 3 technology. Initially this was a big hurdle for me. Using EJB 3 effectively seems to be something of an art form. If you know what you’re doing and understand exactly how to use the EntityManager to handle persistence operations on a database, EJB lets you do some amazingly smart things with just a few lines of code. But there seems to be a lack of good free documentation online—especially since EJB 3 is a significant departure from EJB 2. Therefore, almost all of the tutorial’s information on EJB comes from the very excellent book, EJB in Action by Debu Panda and Reza Rahman. Interpreting the NetBeans Profiler. The final hands-on unit, Testing an Profiling, was the most difficult for me to write, primarily because I just wasn’t familiar with the Profiler at all. I spent an unhealthy amount of time just watching the Telemetry graph run against my JMeter test plan, which is only slightly more stimulating than watching water come to boil. That being said, I feel that by just examining the graphs and other windows over time, critical logical associations start to jump out at you after a while. Likewise with JMeter. Hopefully unit 12 was able to capture and relay some of these. How to search online for decent articles and learning materials. The old Sun Technical Articles site was a great resource. Many of the links in the See Also sections at the bottom of tutorial units were found by adding site:java.sun.com/developer/technicalArticles/ to a Google search. Also the official forums (found at forums.sun.com) became a good place for questions I couldn’t find ready answers to. I had both the Java EE 5 and 6 Tutorials bookmarked. And Marty Hall’s Core Servlets and JavaServer Pages became an invaluable resource for the first half of the tutorial. What are your personal favorite features of the technologies discussed in the tutorial? I particularly liked learning about session management—using the HttpSession object to carry user-specific data between requests, and working with JSP’s corresponding implicit objects in the front-end pages. Session management is a defining aspect for e-commerce applications, as they need to provide some sort of shopping cart mechanism... ...and so the Managing Sessions unit (unit 8) was a key chapter in the tutorial. It’s extremely useful to be able to suspend the debugger on a portion of code that includes session-scoped variables, then hover the mouse over a given variable in the editor to determine its current value. I used the debugger continuously during this phase, and so I went so far as to incorporate use of the debugger throughout the Managing Sessions unit. What kind of background does someone starting the tutorial need to have? Someone can come to the tutorial with little or absolutely no experience using NetBeans. I’ve tried to be particularly careful in providing clear and easy-to-follow instructions in this respect. But one would be best off having some background or knowledge in basic web technologies, and at least some exposure to relational databases. With this foundation, I think that the topics covered in the second half of the tutorial, like applying entity classes and session beans, language support and security, won’t seem too daunting. I’ve noticed that the vast majority of feedback that comes in relates to the first half of the tutorial, and I sometimes get the impression that people feel they need to follow the tutorial units consecutively. Not so. The units are 90% modular. In other words, if somebody just wants to run through the security unit (unit 11), they can do so by downloading the associated project snapshot, follow the setup instructions, and then just follow along without needing to even look at other parts of the tutorial. What will they be able to do at the end of it? Naturally, anybody who completes individual tutorial units will be able to apply the concepts and technologies to their own work. But anyone who completes the tutorial in its entirety will gain an insight into the development process as a whole, and I think will also get a certain confidence that comes with knowing how “all the pieces fit together”—from gathering customer requirements all the way to deployment of the completed app to a production server. They’ll also have gained a solid familiarity with the NetBeans IDE, and be in a good position to explore popular Java web frameworks that work on top of servlet technology or impose an MVC architecture on their own, such as JSF, Spring, Struts, or Wicket. Do you see any problems in the technologies discussed and what would be your suggestions for enhancements? Well there’s one thing that comes to mind. When I started working on this project, I was studying the Duke’s BookStore example from the Java EE 5 Tutorial. A wonderful example that demonstrates how to progressively implement the same application using various technologies and combinations thereof. So for example you start out with an all-servlet implementation, then move on to a JSP/servlet version. Then there’s a JSTL implementation and ultimately, a version using JavaServer Faces. It’s great learning material, but also terrifically outdated. Right around this time, Sun was gearing up for the big Java EE 6 release (Dec. 2009), and I was also trying to learn about the new upcoming technologies, namely CDI, JSF 2, and EJB 3, for my regular NetBeans documentation work. I was getting the definite sense that JSP and JSTL were slowly being pushed aside—in the case of JavaServer Faces, Facelets templating was the new page authoring technology. So really, the E-commerce Tutorial application has become a sort of EE 5/EE 6 hybrid by combining JSP/JSTL with EJB 3 and JPA 2. Now the problem I see from the perspective of a student trying to learn this stuff from scratch, is that the leap from basic servlet technology to a full-blown JSF/EJB/JPA solution is tremendous, and cannot readily be taught through a single tutorial. Naturally, others may disagree with me here. I’m not sure if there’s a solution other than to compensate by producing a lot of quality learning material that covers lots of different use-cases. I’d suggest that the E-commerce Tutorial puts one in a very advantageous position to begin learning about Java-based frameworks, such as GWT, Spring, and JSF, which is a natural course of action for people looking to get a job with this knowledge. Planning any more parts to the tutorial or a new one? No more parts. The E-commerce Tutorial is done. Upon committing the final installments and changes last November, I rejoiced. However, I’m still actively responding to feedback [the ‘Send Us Your Feedback’ links at the bottom of tutorials] and plan to maintain it indefinitely, so if anyone spots any typos, has questions or comments, recommendations for improvement, etc., please write in! :-)

Vince Sheard (pictured right) is the Manager of the MPLAB® Integrated Development Environment (IDE) team at Microchip Technology Inc. He has been working at Microchip for more than 10 years, and was the lead architect for the MPLAB X IDE version 1.0, prior to stepping into the management roll. This, the port of MPLAB to the NetBeans Platform, is the sixth major architecture change of the MPLAB IDE since its inception in 1992. Microchip Technology Inc., headquartered in Chandler, Arizona, was spun off from General Instrument in 1989. The Company went public in 1993, and is a leading provider of microcontroller, analog, and Flash-IP solutions, providing low-risk product development, lower total system cost and faster time to market for thousands of diverse customer applications worldwide. Headquartered in Chandler, Arizona, Microchip offers outstanding technical support along with dependable delivery and quality. For more information, visit the Microchip website at http://www.microchip.com. (The MPLAB X landing page is http://www.microchip.com/mplabx, which will be available in the next few days.) Hi, Vince. What's MPLAB, in a nutshell? MPLAB® is an integrated development environment or IDE. It is similar to other IDEs, but there are two important differences. The first difference is that the MPLAB IDE is our customers’ window into Microchip’s PIC® microcontrollers embedded in their designs. Many people believe they understand their PC, because it is “right here.” An embedded device is more difficult to get a handle on. It’s the brain of a product “over there.” It’s not a computer, it’s a thing. The MPLAB IDE gives embedded developers an opportunity to dig into the brain of that thing. The second important difference is that the MPLAB IDE seamlessly covers Microchip’s entire portfolio of more than 700 8-bit, 16-bit and 32-bit PIC microcontrollers. The differences between these devices are massive, from a tiny 6-pin, 8-bit microcontroller that could fit under your fingernail, to a huge 32-bit microcontroller that is much more powerful than the iconic IBM mainframe of last century. The MPLAB IDE provides a consistent and supportive environment in which to debug our customers’ original, creative works of software that differentiate their products. What are the MPLAB IDE’s main features and how does it distinguish itself from its competitors? Integrated development environments share many features: project creation and management, programmers’ editor, language tool integration and build tools, image preparation and programming, and debug facilities. These are the MPLAB X IDE’s main features, too. A large difference comes in the presentation of an embedded target, rather than a PC target, which presents a developer with a less coupled and less easily controlled object for their development. That tightens the focus, but there are other IDEs that support embedded development. The MPLAB X IDE is distinguished by its seamless and timely support of Microchip devices, the vast ecosystem of tightly integrated compilers and hardware tools that also support those devices, and the evolutionary grace of a tool that has grown with our customers and technologies until the three form a smooth and supportive system for developing innovative embedded products. What are the typical technical challenges of an application of this kind? The principal challenge we face is how to provide the facilities developers need in the most intuitive and useful way possible. It’s easy to provide tons and tons of features, but with the GUI technologies of today, one can only present a small fraction of what is provided and available for use. One of the gauges for how well we’ve done our job is when our customers present a fine point of usage that we’ve already discussed and disagreed on how to implement. Those "complaints" are really wonderful because they come from expert tool users who understand the tools they are using. Of course, we are always hustling to present new Microchip devices in the same light that we present established devices. We’re also challenged to exploit the advanced debug facilities of new devices in a way that is most beneficial for our customers. What's the architecture of the application and why did you make the choices that you did? We’re moving away from a Windows OS-only, COM-based architecture. As our customers’ development sophistication has grown, so have their needs. Our customers now require Linux, Mac, and Windows support. Microchip is a worldwide company with customers who may only be fluent in a single language, so that impacts our choices. We also have a number of educational institutions who place interesting demands on the IDE, along with a number of advanced customers who are very forward-looking and are really pushing the envelope of what was previously thought possible. The most telling choice we had to make, though, was the choice of NetBeans as a fully capable, modern, lightweight and flexible platform for our next-generation MPLAB X IDE: Where does the NetBeans Platform fit into all of this? NetBeans is unique among current open-source IDE platform offerings, in that it is the most advanced for addressing our primary challenge, which I described above. The NetBeans IDE presents standard operations in a way that really minimizes hunting around and wasting time, to find out how to accomplish what you need to do. Take, for instance, the classic edit, compile, debug “cycle.” In NetBeans, like in other IDEs, the edit part is pretty easy: open the source file in the programmers’ editor and make the changes you need. It’s really not much different than editing a document with a word processor. The next step is where the difference really shows. In some IDEs, you have to compile or build an image and then figure out how to load it and start a debugging session. In some IDEs, that’s just brutal to figure out, especially in embedded systems where, as we said, the target is not “right here,” it’s “over there.” In NetBeans, it’s a single button press (DebugRun), even in an embedded context like ours. After that, the rest of the steps are taken care of. If any errors occur during the sequence, we take it home by capturing the errors and placing the user in context for an easy solution; and the ability to move on. That’s just one example. NetBeans is way ahead of the curve compared to other menu/toolbar/property sheet IDEs. What are the 3 main benefits of the NetBeans Platform, in this context? First and foremost is the ability to really optimize developers’ time. That’s a major factor in our customers’ focus. Second is the fact that NetBeans is a modern, lightweight and fully capable IDE platform. It doesn’t suffer from the bloat and outdated aspects of some other IDE platforms. Included with these benefits are the abilities to localize the IDE and to utilize it on multiple operating systems. Last, but not least, is the huge benefit of a professionally executed development, maintained by a focused organizing committee and maintained by a tight-knit development community—all headed by the Oracle contributions. That’s a significant departure from some other high-profile, open-source platforms that are available. How did you end up choosing the NetBeans Platform over its alternatives? When you consider all of the benefits I just mentioned, I think it’s pretty much a no-brainer. How did you get started with it? We first discussed the concepts with Sun Microsystems, as we wanted to provide a benefit to the overall NetBeans IDE from an embedded side. We created a proof of concept by plugging in our existing debuggers to the NetBeans IDE on a Windows operating system. We were fortunate to find someone who previously worked within Sun Microsystems on the NetBeans Platform, who came in on contract and gave us some one-on-one training. This was mainly because we had an aggressive schedule and wanted to be able to get up to speed faster. Any tips and tricks for others going down the same road? The mail lists are very helpful. We found many things we wanted to do being asked by others on the mailing lists. Many of the developers monitor these lists frequently, and respond more often than not in a timely fashion. The documentation suite, videos, written documents and interaction with the community are all extremely helpful in getting to the root of any matter quickly. The IDE is well organized and uses common techniques within the code base, which quickly become familiar. Other platforms treat information as job security. Some people may know, but they want you to pay for the information, in one way or another. Not so with NetBeans; everyone involved is completely open and collaborative. Any specific things that surprised you about the NetBeans Platform (in a good or bad way)? NetBeans prevents development with any form of interdependency between modules. For instance, you cannot have A->B and B->A. This really is a good thing and ensures that you break your modules up more to create a common module. The way JUnit is integrated into the IDE makes it so seamless to create your unit tests while developing the code. Source-code revision control worked quite smoothly from within the IDE. A hindrance for us is that there is no way to view a block of memory in hex form, when running under Java (using the JVM debugger). This is something often required when doing embedded development. Since we are developing code for our debug tools, we wanted to see the code blocks being transported from the IDE to the tool in hex, but could not. Anything else you'd like to share? It is great how fully featured the editor is. We are often so deep in developing what is required for the embedded side that we still discover things the editor does that we hadn’t come across. We are using the NetBeans IDE to create our own IDE, which is a completely new, yet compatible, incarnation of our IDE. The NetBeans developers at Oracle/Sun are extremely open to assist in getting value added to the current IDE, which makes our job even easier.