The last couple of weeks I've been playing around with docker and kubernetes. If you are not familiar with kubernetes let's just say for now that its an open source container cluster management implementation, which I find really really awesome. One of the first things I wanted to try out was running an Apache ZooKeeper ensemble inside kubernetes and I thought that it would be nice to share the experience. For my experiments I used Docker v. 1.3.0 and Openshift V3, which I built from source and includes Kubernetes. ZooKeeper on Docker Managing a ZooKeeper ensemble is definitely not a trivial task. You usually need to configure an odd number of servers and all of the servers need to be aware of each other. This is a PITA on its own, but it gets even more painful when you are working with something as static as docker images. The main difficulty could be expressed as: "How can you create multiple containers out of the same image and have them point to each other?" One approach would be to use docker volumes and provide the configuration externally. This would mean that you have created the configuration for each container, stored it somewhere in the docker host and then pass the configuration to each container as a volume at creation time. I've never tried that myself, I can't tell if its a good or bad practice, I can see some benefits, but I can also see that this is something I am not really excited about. It could look like this: docker run -p 2181:2181 -v /path/to/my/conf:/opt/zookeeper/conf my/zookeeper An other approach would be to pass all the required information as environment variables to the container at creation time and then create a wrapper script which will read the environment variables, modify the configuration files accordingly, launch zookeeper. This is definitely easier to use, but its not that flexible to perform other types of tuning without rebuilding the image itself. Last but not least one could combine the two approaches into one and do something like: Make it possible to provide the base configuration externally using volumes. Use env and scripting to just configure the ensemble. There are plenty of images out there that take one or the other approach. I am more fond of the environment variables approach and since I needed something that would follow some of the kubernetes conventions in terms of naming, I decided to hack an image of my own using the env variables way. Creating a custom image for ZooKeeper I will just focus on the configuration that is required for the ensemble. In order to configure a ZooKeeper ensemble, for each server one has to assign a numeric id and then add in its configuration an entry per zookeeper server, that contains the ip of the server, the peer port of the server and the election port. The server id is added in a file called myid under the dataDir. The rest of the configuration looks like: server.1=server1.example.com:2888:3888 server.2=server2.example.com:2888:3888 server.3=server3.example.com:2888:3888 ... server.current=[bind address]:[peer binding port]:[election biding port]Note that if the server id is X the server.X entry needs to contain the bind ip and ports and not the connection ip and ports. So what we actually need to pass to the container as environment variables are the following: The server id. For each server in the ensemble: The hostname or ip The peer port The election port If these are set, then the script that updates the configuration could look like: if [ ! -z "$SERVER_ID" ]; then echo "$SERVER_ID" > /opt/zookeeper/data/myid #Find the servers exposed in env. for i in `echo {1..15}`;do HOST=`envValue ZK_PEER_${i}_SERVICE_HOST` PEER=`envValue ZK_PEER_${i}_SERVICE_PORT` ELECTION=`envValue ZK_ELECTION_${i}_SERVICE_PORT` if [ "$SERVER_ID" = "$i" ];then echo "server.$i=0.0.0.0:2888:3888" >> conf/zoo.cfg elif [ -z "$HOST" ] || [ -z "$PEER" ] || [ -z "$ELECTION" ] ; then #if a server is not fully defined stop the loop here. break else echo "server.$i=$HOST:$PEER:$ELECTION" >> conf/zoo.cfg fi done fi For simplicity the function that read the keys and values from env are excluded. The complete image and helping scripts to launch zookeeper ensembles of variables size can be found in the fabric8io repository. ZooKeeper on Kubernetes The docker image above, can be used directly with docker, provided that you take care of the environment variables. Now I am going to describe how this image can be used with kubernetes. But first a little rambling... What I really like about using kubernetes with ZooKeeper, is that kubernetes will recreate the container, if it dies or the health check fails. For ZooKeeper this also means that if a container that hosts an ensemble server dies, it will get replaced by a new one. This guarantees that there will be constantly a quorum of ZooKeeper servers. I also like that you don't need to worry about the connection string that the clients will use, if containers come and go. You can use kubernetes services to load balance across all the available servers and you can even expose that outside of kubernetes. Creating a Kubernetes confing for ZooKeeper I'll try to explain how you can create 3 ZooKeeper Server Ensemble in Kubernetes. What we need is 3 docker containers all running ZooKeeper with the right environment variables: { "image": "fabric8/zookeeper", "name": "zookeeper-server-1", "env": [ { "name": "ZK_SERVER_ID", "value": "1" } ], "ports": [ { "name": "zookeeper-client-port", "containerPort": 2181, "protocol": "TCP" }, { "name": "zookeeper-peer-port", "containerPort": 2888, "protocol": "TCP" }, { "name": "zookeeper-election-port", "containerPort": 3888, "protocol": "TCP" } ] } The env needs to specify all the parameters discussed previously. So we need to add along with the ZK_SERVER_ID, the following: ZK_PEER_1_SERVICE_HOST ZK_PEER_1_SERVICE_PORT ZK_ELECTION_1_SERVICE_PORT ZK_PEER_2_SERVICE_HOST ZK_PEER_2_SERVICE_PORT ZK_ELECTION_2_SERVICE_PORT ZK_PEER_3_SERVICE_HOST ZK_PEER_3_SERVICE_PORT ZK_ELECTION_3_SERVICE_PORT An alternative approach could be instead of adding all these manual configuration, to expose peer and election as kubernetes services. I tend to favor the later approach as it can make things simpler when working with multiple hosts. It's also a nice exercise for learning kubernetes. So how do we configure those services? To configure them we need to know: the name of the port the kubernetes pod the provide the service The name of the port is already defined in the previous snippet. So we just need to find out how to select the pod. For this use case, it make sense to have a different pod for each zookeeper server container. So we just need to have a label for each pod, the designates that its a zookeeper server pod and also a label that designates the zookeeper server id. "labels": { "name": "zookeeper-pod", "server": 1 } Something like the above could work. Now we are ready to define the service. I will just show how we can expose the peer port of server with id 1, as a service. The rest can be done in a similar fashion: { "apiVersion": "v1beta1", "creationTimestamp": null, "id": "zk-peer-1", "kind": "Service", "port": 2888, "containerPort": "zookeeper-peer-port", "selector": { "name": "zookeeper-pod", "server": 1 } } The basic idea is that in the service definition, you create a selector which can be used to query/filter pods. Then you define the name of the port to expose and this is pretty much it. Just to clarify, we need a service definition just like the one above per zookeeper server container. And of course we need to do the same for the election port. Finally, we can define an other kind of service, for the client connection port. This time we are not going to specify the sever id, in the selector, which means that all 3 servers will be selected. In this case kubernetes will load balance across all ZooKeeper servers. Since ZooKeeper provides a single system image (it doesn't matter on which server you are connected) then this is pretty handy. { "apiVersion": "v1beta1", "creationTimestamp": null, "id": "zk-client", "kind": "Service", "port": 2181, "createExternalLoadBalancer": "true", "containerPort": "zookeeper-client-port", "selector": { "name": "zookeeper-pod" } } The basic idea is that in the service definition, you create a selector which can be used to query/filter pods. Then you define the name of the port to expose and this is pretty much it. Just to clarify, we need a service definition just like the one above per zookeeper server container. And of course we need to do the same for the election port. Finally, we can define an other kind of service, for the client connection port. This time we are not going to specify the sever id, in the selector, which means that all 3 servers will be selected. In this case kubernetes will load balance across all ZooKeeper servers. Since ZooKeeper provides a single system image (it doesn't matter on which server you are connected) then this is pretty handy. { "apiVersion": "v1beta1", "creationTimestamp": null, "id": "zk-client", "kind": "Service", "port": 2181, "createExternalLoadBalancer": "true", "containerPort": "zookeeper-client-port", "selector": { "name": "zookeeper-pod" } } I hope you found it useful. There is definitely room for improvement so feel free to leave comments.

NetBeans 8.0 introduces several new Java hints. Although there are a large number of these new hints related to Java Persistence API, I focus on five new hints in the Performance category. The five new "Performance Hints" introduced with NetBeans 8.0 are: Boxing of already boxed value Redundant String.toString() Replace StringBuffer/StringBuilder by String Unnecessary temporary during conversion from String Unnecessary temporary during conversion to String Each of these five performance-related Java hints are illustrated in this post with screen snapshots taken from NetBeans 8.0 with code that demonstrates these hints. There are two screen snapshots for each hint, one each showing the text displayed when the cursor hovers over the line of code marked with yellow underlining and one each showing the suggested course of action to be applied to address that hint (shown when clicking on the yellow light bulb to the left of the flagged line). Some of the captured screen snapshots include examples of code that avoid the hint. Boxing of Already Boxed Value Redundant String.toString() Replace StringBuffer/StringBuilder by String Unnecessary Temporary During Conversion from String Unnecessary Temporary During Conversion to String Unless I've done something incorrectly, there appears to be a minor bug with this hint in that it reports "Unnecessary temporary when converting from String" when, in this case, it should really be "Unnecessary temporary when converting to String". This is not a big deal as the condition is flagged and the action to fix it seems appropriate. Conclusion The five performance-related hints introduced by NetBeans 8.0 and illustrated here can help Java developers avoid unnecessary object instantiations and other unnecessary runtime cost. Although the benefit of this optimization as shown in my simple examples is almost negligible, it could lead to much greater savings when used in code with loops that perform these same unnecessary instantiations thousands of times. Even without consideration of the performance benefit, these hints help to remind Java developers and teach developers new to Java about the most appropriate mechanisms for acquiring instances and primitive values.

One of my favourite functions in Neo4j’s cypher query language is COLLECT which allows us to group items into an array for later consumption. However, I’ve noticed that people sometimes have trouble working out how to collect multiple items with COLLECT and struggle to find a way to do so. Consider the following data set: create (p:Person {name: "Mark"}) create (e1:Event {name: "Event1", timestamp: 1234}) create (e2:Event {name: "Event2", timestamp: 4567}) create (p)-[:EVENT]->(e1) create (p)-[:EVENT]->(e2) If we wanted to return each person along with a collection of the event names they’d participated in we could write the following: $ MATCH (p:Person)-[:EVENT]->(e) > RETURN p, COLLECT(e.name); +--------------------------------------------+ | p | COLLECT(e.name) | +--------------------------------------------+ | Node[0]{name:"Mark"} | ["Event1","Event2"] | +--------------------------------------------+ 1 row That works nicely, but what about if we want to collect the event name and the timestamp but don’t want to return the entire event node? An approach I’ve seen a few people try during workshops is the following: MATCH (p:Person)-[:EVENT]->(e) RETURN p, COLLECT(e.name, e.timestamp) Unfortunately this doesn’t compile: SyntaxException: Too many parameters for function 'collect' (line 2, column 11) "RETURN p, COLLECT(e.name, e.timestamp)" ^ As the error message suggests, the COLLECT function only takes one argument so we need to find another way to solve our problem. One way is to put the two values into a literal array which will result in an array of arrays as our return result: $ MATCH (p:Person)-[:EVENT]->(e) > RETURN p, COLLECT([e.name, e.timestamp]); +----------------------------------------------------------+ | p | COLLECT([e.name, e.timestamp]) | +----------------------------------------------------------+ | Node[0]{name:"Mark"} | [["Event1",1234],["Event2",4567]] | +----------------------------------------------------------+ 1 row The annoying thing about this approach is that as you add more items you’ll forget in which position you’ve put each bit of data so I think a preferable approach is to collect a map of items instead: $ MATCH (p:Person)-[:EVENT]->(e) > RETURN p, COLLECT({eventName: e.name, eventTimestamp: e.timestamp}); +--------------------------------------------------------------------------------------------------------------------------+ | p | COLLECT({eventName: e.name, eventTimestamp: e.timestamp}) | +--------------------------------------------------------------------------------------------------------------------------+ | Node[0]{name:"Mark"} | [{eventName -> "Event1", eventTimestamp -> 1234},{eventName -> "Event2", eventTimestamp -> 4567}] | +--------------------------------------------------------------------------------------------------------------------------+ 1 row During the Clojure Neo4j Hackathon that we ran earlier this week this proved to be a particularly pleasing approach as we could easily destructure the collection of maps in our Clojure code.

It is possible to disable HTTP access on S3 bucket, limiting S3 traffic to only HTTPS requests. The documentation is scattered around the Amazon AWS documentation, but the solution is actually straightforward. All you need to do to block HTTP traffic on an S3 bucket is add a Condition in your bucket's policy. AWS supports a global condition for verifying SSL. So you can add a condition like this: "Condition": { "Bool": { "aws:SecureTransport": "true" } } Here's a complete example: { "Version": "2008-10-17", "Id": "some_policy", "Statement": [ { "Sid": "AddPerm", "Effect": "Allow", "Principal": { "AWS": "*" }, "Action": "s3:GetObject", "Resource": "arn:aws:s3:::my_bucket/*", "Condition": { "Bool": { "aws:SecureTransport": "true" } } } ] } Now accessing the contents of my_bucket over HTTP will produce a 403 error, while using HTTPS will work fine.

There are some instances when you want to store your passwords in files to be used by programs or scripts. But storing your passwords in plain text is not a good idea. Use the SecurePasswordVault to encrypt your passwords before storing and get it decrypted when you want to use it. You can use the SecurePasswordVault described here to store any number of encrypted passwords. Passwords are stored as key value pairs. Key - any name given by the user for the password Value - encrypted password SecurePasswordVault will create a file with the given name in the working directory if it doesn't exist. If a file exists then the information in that file will be read. Passwords are encrypted using the MAC address of the network card. SecurePasswordVault will use the first network card MAC which is not the loop back interface. So the encrypted file can only be decrypted with that particular MAC address. If you want to reset the pass word details, just delete the password file and run the SecurePasswordVault. You can download the sample code from the following GitHub repository https://github.com/jsdjayanga/secure_password com.wso2.devgov; import org.bouncycastle.util.encoders.Base64; import javax.crypto.*; import javax.crypto.spec.SecretKeySpec; import java.io.*; import java.net.NetworkInterface; import java.net.SocketException; import java.security.InvalidKeyException; import java.security.NoSuchAlgorithmException; import java.security.Security; import java.util.*; /** * Created by jayanga on 3/31/14. */ public class SecurePasswordVault { private static final int AES_KEY_LEN = 32; private static final int PASSWORD_LEN = 256; private static boolean initialized; private final String secureFile; private final byte[] networkHardwareHaddress; private Map secureDataMap; private List secureDataList; SecretKeySpec secretKey; public SecurePasswordVault(String filename, String[] secureData) throws IOException { Security.addProvider(new org.bouncycastle.jce.provider.BouncyCastleProvider()); initialized = false; secureFile = filename; networkHardwareHaddress = SecurePasswordVault.readNetworkHardwareAddress(); secureDataMap = new HashMap(); this.secureDataList = new ArrayList(secureData.length); Collections.addAll(secureDataList, secureData); byte[] key = new byte[AES_KEY_LEN]; Arrays.fill(key, (byte)0); for(int index = 0; index < networkHardwareHaddress.length; index++){ key[index] = networkHardwareHaddress[index]; } secretKey = new SecretKeySpec(key, "AES"); if (!isInitialized()){ readSecureData(secureDataList); persistSecureData(); } readSecureDataFromFile(); } private boolean isInitialized(){ if (initialized == true){ return true; }else{ File file = new File(secureFile); if (file.exists()){ initialized = true; return initialized; } } return false; } private static byte[] readNetworkHardwareAddress() throws SocketException { Enumeration networkInterfaceEnumeration = NetworkInterface.getNetworkInterfaces(); if (networkInterfaceEnumeration != null){ NetworkInterface networkInterface = null; while (networkInterfaceEnumeration.hasMoreElements()){ networkInterface = networkInterfaceEnumeration.nextElement(); if (!networkInterface.isLoopback()){ break; } } if (networkInterface == null){ networkInterface = networkInterfaceEnumeration.nextElement(); } byte[] hwaddr = networkInterface.getHardwareAddress(); return hwaddr; }else{ throw new RuntimeException("Cannot initialize. Failed to generate unique id."); } } private byte[] encrypt(String word) { byte[] password = new byte[PASSWORD_LEN]; Arrays.fill(password, (byte)0); byte[] pw = new byte[0]; try { pw = word.getBytes("UTF-8"); for(int index = 0; index < pw.length; index++){ password[index] = pw[index]; } byte[] cipherText = new byte[password.length]; Cipher cipher = null; try { cipher = Cipher.getInstance("AES/ECB/NoPadding"); try { cipher.init(Cipher.ENCRYPT_MODE, secretKey); int ctLen = 0; try { ctLen = cipher.update(password, 0, password.length, cipherText, 0); ctLen += cipher.doFinal(cipherText, ctLen); return cipherText; } catch (ShortBufferException e) { e.printStackTrace(); } catch (BadPaddingException e) { e.printStackTrace(); } catch (IllegalBlockSizeException e) { e.printStackTrace(); } } catch (InvalidKeyException e) { e.printStackTrace(); } } catch (NoSuchAlgorithmException e) { e.printStackTrace(); } catch (NoSuchPaddingException e) { e.printStackTrace(); } } catch (UnsupportedEncodingException e) { e.printStackTrace(); } return null; } private String decrypt(byte[] cipherText) { byte[] plainText = new byte[PASSWORD_LEN]; Cipher cipher = null; try { cipher = Cipher.getInstance("AES/ECB/NoPadding"); try { cipher.init(Cipher.DECRYPT_MODE, secretKey); int plainTextLen = 0; try { plainTextLen = cipher.update(cipherText, 0, PASSWORD_LEN, plainText, 0); try { plainTextLen += cipher.doFinal(plainText, plainTextLen); String password = new String(plainText); return password.trim(); } catch (IllegalBlockSizeException e) { e.printStackTrace(); } catch (BadPaddingException e) { e.printStackTrace(); } } catch (ShortBufferException e) { e.printStackTrace(); } } catch (InvalidKeyException e) { e.printStackTrace(); } } catch (NoSuchAlgorithmException e) { e.printStackTrace(); } catch (NoSuchPaddingException e) { e.printStackTrace(); } return null; } public void readSecureData(List secureDataList) throws IOException { BufferedReader bufferRead = new BufferedReader(new InputStreamReader(System.in)); for(int index = 0; index < secureDataList.size(); index++){ System.out.println("Please enter the value for :" + secureDataList.get(index)); String value = new String(Base64.encode(encrypt(bufferRead.readLine()))); secureDataMap.put(secureDataList.get(index), value); } } public String getSecureData(String key) { String value = secureDataMap.get(key); if (value != null){ return decrypt(Base64.decode(value.getBytes())); } throw new RuntimeException("Given key is unknown. [key=" + key + "]"); } private void readSecureDataFromFile() throws IOException { BufferedReader br = new BufferedReader(new FileReader(secureFile)); String line; while ((line = br.readLine()) != null){ int dividerPoint = line.indexOf("="); if (dividerPoint > 0){ secureDataMap.put(line.substring(0, dividerPoint), line.substring(dividerPoint + 1)); } } } private void persistSecureData() throws IOException { FileWriter fileWriter = new FileWriter(secureFile); for(String key : secureDataMap.keySet()){ fileWriter.append(key + "=" + secureDataMap.get(key) + "\n"); } fileWriter.close(); } }

If you use Java for programming, read on to learn about tools like Eclipse IDE, the Java Development Kit, and other must-know tools.

A recurring customer issue seen by the Percona Support team involves how to make the ibdata1 file “shrink” within MySQL. I'll show you how to handle big tables.

Originally written by Virgil Dodson Actuate recently released a new, free BIRT server called the BIRT iHub F-Type. It incorporates all the functionality of BIRT iHub and is limited only by the capacity of output it can deliver on a daily basis. It is ideal for departmental and smaller scale applications. When BIRT F-Type reaches its maximum output capacity, additional capacity can be purchased on a subscription based model. Some of the key features of BIRT iHub F-Type that will help improve your BIRT content applications are: Interactivity – Allow end-users to modify and personalize reports, and answer questions themselves. Scheduling – Automate report generation based on rules and calendar, and then notify users. Sharing – Secure document management and distribution that allows users to only access content/data they are entitled to. Excel Emitter – Export as native Excel (not CSV) with formulas/pivot tables/worksheets/charts. Integration – JavaScript API to embed dynamic reports and visualizations in your web app. Downloading BIRT iHub F-Type Before we get started with the installation process, we need to download BIRT iHub F-Type. There are three downloads available: Windows, Linux, and a VMware image. This blog will cover the Windows installation. If you’re installing either of the other types, you’ll find links to guides for them at the bottom of this blog post. Once you click on your chosen download, you’ll be asked to register. If you’ve already registered, click the “Click to Login” button. If not, fill out the short registration form to get started. Next, read and accept the license agreement. Once you’ve done that, click the checkbox, and a link for the download will appear. Click that to start your download. At this point, you should also receive an email with an activation code. Be sure to check your spam folder if you don’t see it in your inbox. Installing BIRT iHub F-Type After the download is complete, launch the executable file named ActuateBIRTiHubFType.exe. A welcome message will appear. Press Next to continue. You must read and accept the license agreement on the next screen. Choose a destination folder for the installation. The default is C:\Actuate\BIRTiHub. If you have existing BIRT designs that depend on a JDBC database driver, you can optionally specify the folder where these drivers are located. Press Next to continue. Once the installation has finished, press Finish to launch the BIRT iHub F-Type. A desktop shortcut is also created that points to the iHub F-Type URL at http://localhost:8700/iportal. The first time you launch the BIRT iHub F-Type, you will need to activate it. Enter the activation code that you should have received in an e-mail. After entering a valid activation code, you should receive a message that the code was accepted and the BIRT iHub F-Type should start initializing services. Once that has completed, you will be presented with the login screen. The default user name is “administrator” and the password is blank for your first log in. You’ll be able to change this after you have logged in. Press “Log In” to continue. The first time you launch the BIRT iHub F-Type, you will be in tutorial mode which will help you get started loading your BIRT content and required resources. You can bypass the tutorial mode at any time by pressing the “Exit Tutorial” button at the top right. Select a BIRT design (*.rptdesign) file and press the Upload button. If you don’t have a BIRT design, you can download a sample from the link on the same page. The BIRT design file is automatically inspected and if there are any dependent files needed, like images, data files, BIRT report libraries, CSS styles, or other linked BIRT designs, you will be asked to upload those files as well. Once your BIRT design and dependent files are uploaded, your BIRT report will be displayed in the BIRT iHub F-Type and is now ready to explore. Thanks for reading. Now, it’s time to unleash the full power of BIRT into your application. If you have any questions or comments, please feel free to use the comments section below or visit the BIRT iHub F-Type forum. -Virgil For more blogs in the “Introducing BIRT iHub F-Type” series, see the list below: Installing iHub F-Type: Linux | VMWare Image

The NetBeans Team has released NetBeans IDE 8.0.1, with significant enhancements to features relating to HTML5, JavaScript, and CSS3. An update to NetBeans IDE 8.0, this release includes the following notable changes: Modularity and enterprise JavaScript development support via integration of RequireJS Tools for working seamlessly with Grunt, Karma, and Bower Enhanced Java Editor, PHP Editor, and Git Tools Support for new versions of WebLogic, GlassFish, Tomcat, WildFly, and PrimeFaces Performance improvements and bug fixes Complete list of features: http://wiki.netbeans.org/NewAndNoteworthyNB801 To get the recent changes: Download and install NetBeans 8.0.1, which includes the recently released GlassFish 4.1 OR If you already have NetBeans IDE 8.0 installed, launch the IDE and an update notification will appear. Alternatively, choose Help | Check for Updates. Click the alert-box to install the updates. For details on upgrading, see the YouTube screencast "How to Upgrade to NetBeans IDE 8.0.1 from NetBeans IDE 8.0" on the NetBeans YouTube channel. NetBeans IDE 8.0.1 is available in English, Brazilian Portuguese, Japanese, Russian, and Simplified Chinese. We welcome feedback about your use of NetBeans software. Share your thoughts on the NetBeans mailing lists and forums; and keep track of NetBeans news by subscribing to the NetBeans Weekly Newsletter and following NetBeans on Twitter, Facebook, and YouTube.

if you have a .html file in a github repository and want to view that page directly, you would typically download or clone the repo to your local hard drive and run it from there. there is an easier way simply navigate to the repo in your github account that contains a html file as shown below: right-click the index.html file and select copy link address. you should have a url similar to the following structure: https://github.com///blob/master/index.html enter rawgit.com as the name implies, rawgit shows serves the raw files directly from github. to use it simply use the following format: https://rawgit.com///master/index.html if you want to use it in production, you can use: https://cdn.rawgit.com///master/index.html that was easy now, wasn’t it!

Last week I was tasked with developing a quick prototype that used AngularJS for its client and Spring MVC for its server. A colleague developed the same application using Backbone.js and Spring MVC. At first, I considered using my boot-ionic project as a starting point. Then I realized I didn't need to develop a native mobile app, but rather a responsive web app. My colleague mentioned he was going to use RESThub as his starting point, so I figured I'd use JHipster as mine. We allocated a day to get our environments setup with the tools we needed, then timeboxed our first feature spike to four hours. My first experience with JHipster failed the 10-minute test. I spent a lot of time flailing about with various "npm" and "yo" commands, getting permissions issues along the way. After getting thinks to work with some sudo action, I figured I'd try its Docker development environment. This experience was no better. JHipster seems like a nice project, so I figured I'd try to find the causes of my issues. This article is designed to save you the pain I had. If you'd rather just see the steps to get up and running quickly, skip to the summary. The "npm" and "yo" issues I had seemed to be caused by a bad node/npm installation. To fix this, I removed node and installed nvm. Here's the commands I needed to remove node and npm: sudo rm -rf /usr/local/lib/node_modules sudo rm -rf /usr/local/include/node sudo rm /usr/local/bin/node sudo rm -rf /usr/local/bin/npm sudo rm /usr/local/share/man/man1/node.1 sudo rm -rf /usr/local/lib/dtrace/node.d sudo rm -rf ~/.npm Next, I ran "brew doctor" to make sure Homebrew was still happy. It told me some things were broken: $ brew doctor Warning: Broken symlinks were found. Remove them with `brew prune`: /usr/local/bin/yo /usr/local/bin/ionic /usr/local/bin/grunt /usr/local/bin/bower I ran brew update && brew prune, followed by brew install nvm. Next, I added the following to my ~/.profile: source $(brew --prefix nvm)/nvm.sh To install the latest version of node, I ran the commands below and set the latest version as the default: nvm ls-remote nvm install v0.11.13 nvm alias default v0.11.13 Once I had a fresh version of Node.js, I was able to run JHipster's local installation instructions. npm install -g yo npm install -g generator-jhipster Then I created my project: yo jhipster I was disappointed to find this created all the project files in my current directory, rather than in a subdirectory. I'd recommend you do the following instead: mkdir ~/projectname && cd ~/projectname && yo jhipster Before creating your project, JHipster asks you a number of questions. To see what they are, see its documentation on creating an application. Two things to be aware of: Hot reloading Java code doesn't work well (yet) with Java 8 Its OAuth2 implementation doesn't work with WebSockets In other words, I'd recommend using Java 7 + (cookie-based authentication with websockets) or (oauth2 authentication w/o websockets). After creating my project, I was able to run it using "mvn spring-boot:run" and view it at http://localhost:8080. To get hot-reloading for the client, I ran "grunt server" and opened my browser to http://localhost:9000. JHipster + Docker on OS X I had no luck getting the Docker instructions to work initially. I spent a couple hours on it, then gave up. A couple of days ago, I decided to give it another good ol' college-try. To make sure I figured out everything from scratch, I started by removing Docker. I re-installed Docker and pulled the JHipster image using the following: sudo docker pull jdubois/jhipster-docker The error I got from this was the following: 2014/09/05 19:43:38 Post http:///var/run/docker.sock/images/create?fromImage=jdubois%2Fjhipster-docker&tag=: dial unix /var/run/docker.sock: no such file or directory After doing some research, I learned I needed to run boot2docker init first. Next I ran boot2docker up to start the Docker daemon. Then I copied/pasted "export DOCKER_HOST=tcp://192.168.59.103:2375" into my console and tried to run docker pull again. It failed with the same error. The solution was simpler than you might think: don't use sudo. $ docker pull jdubois/jhipster-docker Pulling repository jdubois/jhipster-docker 01bdc74025db: Pulling dependent layers 511136ea3c5a: Download complete ... The next command that JHipster's documentation recommends is to run the Docker image, forward ports and share folders. When you run it, the terminal seems to hang and trying to ssh into it doesn't work. Others have recently reported a similar issue. I discovered the hanging is caused by a missing "-d" parameter and ssh doesn't work because you need to add a portmap to the VM to expose the port to your host. You can fix this by running the following: boot2docker down VBoxManage modifyvm "boot2docker-vm" --natpf1 "containerssh,tcp,,4022,,4022" VBoxManage modifyvm "boot2docker-vm" --natpf1 "containertomcat,tcp,,8080,,8080" VBoxManage modifyvm "boot2docker-vm" --natpf1 "containergruntserver,tcp,,9000,,9000" VBoxManage modifyvm "boot2docker-vm" --natpf1 "containergruntreload,tcp,,35729,,35729" boot2docker start After making these changes, I was able to start the image and ssh into it. docker run -d -v ~/jhipster:/jhipster -p 8080:8080 -p 9000:9000 -p 35729:35729 -p 4022:22 -t jdubois/jhipster-docker ssh -p 4022 jhipster@localhost I tried creating a new project within the VM (cd /jhipster && yo jhipster), but it failed with the following error: /usr/lib/node_modules/generator-jhipster/node_modules/yeoman-generator/node_modules/mkdirp/index.js:89 throw err0; ^ Error: EACCES, permission denied '/jhipster/src' The fix was giving the "jhipster" user ownership of the directory. sudo chown jhipster /jhipster After doing this, I was able to generate an app and run it using "mvn spring-boot:run" and access it from my Mac at http://localhost:8080. I was also able to run "grunt server" and see it at http://localhost:9000 However, I was puzzled to see that there was nothing in my ~/jhipster directory. After doing some searching, I found that the docker run -v /host/path:/container/path doesn't work on OS X. David Gageot's A Better Boot2Docker on OSX led me to svendowideit/samba, which solved this problem. The specifics are documented in boot2docker's folder sharing section. I shutdown my docker container by running "docker ps", grabbing the first two characters of the id and then running: docker stop [2chars] I started the JHipster container without the -v parameter, used "docker ps" to find its name (backstabbing_galileo in this case), then used that to add samba support. docker run -d -p 8080:8080 -p 9000:9000 -p 35729:35729 -p 4022:22 -t jdubois/jhipster-docker docker run --rm -v /usr/local/bin/docker:/docker -v /var/run/docker.sock:/docker.sock svendowideit/samba backstabbing_galileo Then I was able to connect using Finder > Go > Connect to Server, using the following for the server address: cifs://192.168.59.103/jhipster To make this volume appear in my regular development area, I created a symlink: ln -s /Volumes/jhipster ~/dev/jhipster After doing this, all the files were marked as read-only. To fix, I ran "chmod -R 777 ." in the directory on the server. I noticed that this also worked if I ran it from my Mac's terminal, but it took quite a while to traverse all the files. I noticed a similar delay when loading the project into IntelliJ. Summary Phew! That's a lot of information that can be condensed down into four JHipster + Docker on OS X tips. Make sure your npm installation doesn't require sudo rights. If it does, reinstall using nvm. Add portmaps to your VM to expose ports 4022, 8080, 9000 and 35729 to your host. Change ownership on the /jhipster in the Docker image: sudo chown jhipster /jhipster. Use svendowideit/samba to share your VM's directories with OS X.

Recently I had the opportunity to work on a project were I needed to create a custom SQL Server image for use with Azure VMs. The process was a little more challenging than I initially anticipated. I think this is mostly because I was not familiar with the process of preparing a SQL Server image. Perhaps this isn’t much of a challenge for an experienced SQL Server DBA or IT Pro. For me, it was a great learning experience. Why a Custom SQL Server Image? The Azure VM image gallery already contains a SQL Server image. It’s very easy to create a new SQL Server VM using this image. However, doing so has a few important trade-offs to consider: Unable to fully customize the base install of SQL Server. This is a template/image after all – you get a VM configured the way the image was configured. Unable to use your own SQL Server license. If your company has an Enterprise Agreement (EA) with Microsoft, it’s likely there is already some SQL Server licenses built into that agreement. Depending on the details, it may be significantly cheaper to use the licenses from the EA instead of paying the SQL Server VM image upcharge from Azure. The Basic Steps There are 6 basic steps to creating a custom SQL Server VM image for use in Azure. Provision a new base Windows Server VM Download the SQL Server installation media Run SQL Server setup to prepare an image Configure Windows to complete the installation of SQL Server Capture the image and add it to the Azure VM image gallery Create a new VM instance using the custom SQL Server image The basic idea here is to create a base VM, customize it with a SQL Server image, capture the VM to create an image, and then provision new VMs using that captured VM image. Let’s dive into each of these in a little more detail. Note: the terminology here can be a little confusing. When referring to the VM used to create the template/image, I’ll use the term “base VM”. When referring to the VM created from the base VM, I’ll use the term “VM instance”. 1. Provision a new base Windows Server VM There are multiple ways to create a Windows Server VM in Azure. Creating a VM via the Azure management portal and PowerShell are probably the two most popular options. Be sure to check out this tutorial to learn how to do so via the portal. For the purposes of this post, I’ll do so via PowerShell. $img = Get-AzureVMImage ` | where { ( $_.PublisherName -ilike "Microsoft*" -and $_.ImageFamily -ilike "Windows Server 2012 Datacenter" ) } ` | Sort-Object -Unique -Descending -Property ImageFamily ` | sort -Descending -Property PublishDate ` | select -First(1) $vmConfig = New-AzureVMConfig -Name "sql-1" -InstanceSize Small -ImageName $img.ImageName | Add-AzureProvisioningConfig -Windows -AdminUsername "[admin-username-here]" -Password "[admin-password-here]" New-AzureVM -ServiceName "SQLServerVMTemplate" -VMs $vmConfig -Location "East US" -WaitForBoot 2. Download the SQL Server installation media With the base Windows Server 2012 VM created, we can now get ready to prepare (sysprep) the SQL Server installation. To do that, we need to get the SQL Server installation media onto the machine. The easiest way I found to do this was to leverage Azure blob storage. Upload the SQL Server ISO file to Azure blob storage Remote Desktop (RDP) into the base VM From the VM, download the SQL Server ISO file to the local disk Mount the SQL Server ISO file to the VM Copy the ISO contents (not the ISO file itself) to the VM’s C:\ drive. For example, use C:\sql The SQL Server installation media files need to be copied to the local C: drive so it can be used later to complete the SQL Server installation (when provisioning the actual SQL Server VM instance). 3. Run SQL Server setup to prepare an image In order to prepare the (sysprep’d) SQL Server VM image (which we can use as a template for future VMs), we need to run the SQL Server installation and instruct it topreparean image – not run the full installation. An easy way to do this is with a SQL Server configuration file, an example of which I’ve included below. ConfigurationFile.ini ;SQL Server 2012 Configuration File [OPTIONS] ; Specifies a Setup workflow, like INSTALL, UNINSTALL, or UPGRADE. This is a required parameter. ACTION="PrepareImage" ; Detailed help for command line argument ENU has not been defined yet. ENU="True" ; Parameter that controls the user interface behavior. Valid values are Normal for the full UI, AutoAdvance for a simplified UI, and EnableUIOnServerCore for bypassing Server Core setup GUI block. ;UIMODE="Normal" ; Specifies setup not display any user interface. ;QUIET="False" ; Specifies setup to display progress only, without any user interaction. QUIETSIMPLE="True" ; Specifies whether SQL Server Setup should discover and include product updates. The valid values are True and False or 1 and 0. By default SQL Server Setup will include updates that are found. UpdateEnabled="True" ; Specifies features to install, uninstall, or upgrade. The list of top-level features include SQL, AS, RS, IS, MDS, and Tools. The SQL feature will install the Database Engine, Replication, Full-Text, and Data Quality Services (DQS) server. The Tools feature will install Management Tools, Books online components, SQL Server Data Tools, and other shared components. FEATURES=SQLENGINE ; Specifies the location where SQL Server Setup will obtain product updates. The valid values are "MU" to search Microsoft Update, a valid folder path, a relative path such as .\MyUpdates or a UNC share. By default SQL Server Setup will search Microsoft Update or a Windows Update service through the Window Server Update Services. UpdateSource="MU" ; Displays the command line parameters usage HELP="False" ; Specifies that the detailed Setup log should be piped to the console. INDICATEPROGRESS="False" ; Specifies that Setup should install into WOW64. This command line argument is not supported on an IA64 or a 32-bit system. X86="False" ; Specifies the root installation directory for shared components. This directory remains unchanged after shared components are already installed. INSTALLSHAREDDIR="C:\Program Files\Microsoft SQL Server" ; Specifies the root installation directory for the WOW64 shared components. This directory remains unchanged after WOW64 shared components are already installed. INSTALLSHAREDWOWDIR="C:\Program Files (x86)\Microsoft SQL Server" ; Specifies the Instance ID for the SQL Server features you have specified. SQL Server directory structure, registry structure, and service names will incorporate the instance ID of the SQL Server instance. INSTANCEID="MSSQLSERVER" ; Specifies the installation directory. INSTANCEDIR="C:\Program Files\Microsoft SQL Server" There are two steps in this process: Copy the ConfigurationFile.ini file (from your local PC) to the same location as the SQL Server installation media (i.e.c:\sql) on the base VM. Run SQL Server setup to prepare an image. From a command prompt (on the base VM), navigate to theC:\sqlfolder and then execute the following command: Setup.exe /ConfigurationFile=ConfigurationFile.ini /IAcceptSQLServerLicenseTerms=true 4. Configure Windows to complete the installation of SQL Server At this point the base VM should have an “installation” of SQL Server that is not fully completed. The SQL Server bits are in place, but they’re not configured for a full server install . . . at least not yet. The final configuration of SQL Server will take place when the VM instance (of which this template/image is the base) is provisioned and boots up for the first time. This is accomplished by using a CMD file with the following content: @ECHO OFF && SETLOCAL && SETLOCAL ENABLEDELAYEDEXPANSION && SETLOCAL ENABLEEXTENSIONS REM All commands will be executed during first Virtual Machine boot "C:\Program Files\Microsoft SQL Server\110\Setup Bootstrap\SQLServer2012\setup.exe" /QS /ACTION=CompleteImage /INSTANCEID=MSSQLSERVER /INSTANCENAME=MSSQLSERVER /IACCEPTSQLSERVERLICENSETERMS=1 /SQLSYSADMINACCOUNTS=%COMPUTERNAME%\Administrators /BROWSERSVCSTARTUPTYPE=AUTOMATIC /INDICATEPROGRESS /TCPENABLED=1 /PID="[YOUR-SQL-SERVER-PRODUCT-ID-HERE]" On your local PC, save the file as SetupComplete2.cmd RDP / log into the base VM Copy the SetupComplete2.cmd from your local PC file to the c:\Windows\OEM folder on the base VM Change the value for the SQLSYSADMINACCOUNTS value to be that of the administrative account created on the VM (or better yet – the local Administrators group account) If needed, supply the SQL Server product ID (PID) value. When Windows starts on the new VM instance for the first time, the SetupComplete2.cmd file should automatically run. It is invoked by the SetupComplete.cmd file already on the machine. 5. Capture the image and add it to the Azure VM image gallery At this point a base SQL Server VM has been created and the groundwork laid to complete the install. Now it is time to create the VM image from the base VM, and do to that you sysprep and capture the base VM. Please follow the guide on How to Capture a Windows Virtual Machine to Use as a Template. 6. Create a new VM using the custom SQL Server image With a new custom VM image template available in the VM image gallery, you can provision a new VM instance using that custom template. Upon first boot, the newly provisioned VM should complete the full SQL Server installation as laid out in your SetupComplete2.cmd file. Please follow the guide on How to Create a Custom Virtual Machine for more information on creating the VM from the template. Closing Thoughts One of the quirks I noticed when preparing the base SQL Server image is that it was not possible to prepare the image with SQL Server Management Studio (SSMS). I would have to do the install after the newly provisioned VM instance is created. Not hard, but time consuming (an annoying if doing this on multiple VM instances). I later learned that SQL Server 2012 Cumulative Update 1 does allow for preparing a SQL Server image with SSMS installed. I’ve included a link below that describes the process for creating a SQL Server image with CU1. In the end, this process really is not all that hard. Time consuming? Yes! The worst part (at least for me) was really just understanding how the SQL Server installation and sysprep process works. Once I wrapped my head around that, the process was a lot smoother. Helpful Resources While I was learning how to create a custom SQL Server VM image, the following resources were very helpful: How to: Create a Windows Azure Virtual Machine Operating System Image for Microsoft Dynamics NAV. This MSDN article provided the jumping off point on learning how to install SQL Server by using a sysprep image. Install SQL Server 2012 from the Command Prompt Install SQL Server 2012 Using a Configuration File Install SQL Server 2012 Using SysPrep How to create a slipstream SQL Server 2012 and Cumulative Update 1 image –http://sqlperformance.com/2012/12/system-configuration/sql-2012-slipstream I would like to thank Scott Klein for his assistance in verifying these steps. His help was extremely valuable to ensure I was doing this the right way.

Learn Fibonacci Series patterns and best practices with easy Java 8 source code examples in this outstanding tutorial by Pierre-Yves Saumont

A common problem that people encounter when trying to import CSV files into Neo4j using Cypher’s LOAD CSV command is how to handle empty or ‘null’ entries in said files. For example let’s try and import the following file which has 3 columns, 1 populated, 2 empty: $ cat /tmp/foo.csv a,b,c mark,, load csv with headers from "file:/tmp/foo.csv" as row MERGE (p:Person {a: row.a}) SET p.b = row.b, p.c = row.c RETURN p When we execute that query we’ll see that our Person node has properties ‘b’ and ‘c’ with no value: ==> +-----------------------------+ ==> | p | ==> +-----------------------------+ ==> | Node[5]{a:"mark",b:"",c:""} | ==> +-----------------------------+ ==> 1 row ==> Nodes created: 1 ==> Properties set: 3 ==> Labels added: 1 ==> 26 ms That isn’t what we want – we don’t want those properties to be set unless they have a value. TO achieve this we need to introduce a conditional when setting the ‘b’ and ‘c’ properties. We’ll assume that ‘a’ is always present as that’s the key for our Person nodes. The following query will do what we want: load csv with headers from "file:/tmp/foo.csv" as row MERGE (p:Person {a: row.a}) FOREACH(ignoreMe IN CASE WHEN trim(row.b) <> "" THEN [1] ELSE [] END | SET p.b = row.b) FOREACH(ignoreMe IN CASE WHEN trim(row.c) <> "" THEN [1] ELSE [] END | SET p.c = row.c) RETURN p Since there’s no if or else statements in cypher we create our own conditional statement by using FOREACH. If there’s a value in the CSV column then we’ll loop once and set the property and if not we won’t loop at all and therefore no property will be set. ==> +-------------------+ ==> | p | ==> +-------------------+ ==> | Node[4]{a:"mark"} | ==> +-------------------+ ==> 1 row ==> Nodes created: 1 ==> Properties set: 1 ==> Labels added: 1

This is a post in a series discussing using spring-boot and docker for deployment. Refer to the end of the first post for a table of contents. Shortly after you start building docker containers you will realize that you need some place to publish your images. You could push to the central docker registry. However, the central registry is public. Not a great idea if you are working on a private project. If this is your case, you can simply run a local docker registry. To install and run your private registry run $ docker run -p 5000:5000 -d registry Surprise!!! It is ran in a docker container. You can now start pushing to your local repository. As an example, I will pull the latest postgres image and push version 9.4 to my local registry. $ docker pull postgres $ docker tag postgres:9.4 localhost:5000/postgres:9.4 $ docker push localhost:5000/postgres Outputs: The push refers to a repository [localhost:5000/postgres] (len: 1) Sending image list Pushing repository localhost:5000/postgres (1 tags) 511136ea3c5a: Image successfully pushed ec3443b7b068: Image successfully pushed 06af7ad6cff1: Image successfully pushed 37eae31ff4e9: Image successfully pushed 83e30bf01299: Image successfully pushed 499da968a652: Image successfully pushed bf09bd07d760: Image successfully pushed 1eee820e762b: Image successfully pushed 7bf9287ccfce: Image successfully pushed 288b8d534217: Image successfully pushed f20dbf0acb45: Image successfully pushed bd511e81a5ed: Image successfully pushed 8fe7eb38aea1: Image successfully pushed 464263a50f65: Image successfully pushed 1f58a67adecd: Image successfully pushed a99fb4ee814d: Image successfully pushed 6112f975feab: Image successfully pushed 6dff1b5c2259: Image successfully pushed Pushing tag for rev [6dff1b5c2259] on {http://localhost:5000/v1/repositories/postgres/tags/9.4} Looking at the current images, you will notice that the version tagged with localhost and the official images have the same information. Notice that I had to retag the image with the location of the repository. I thought the requirement to put the location address as part of the image name was a little odd. However, after using docker longer, it makes sense. It ensures you know where the image was originally pulled. $ docker images postgres 9.4 6dff1b5c2259 5 days ago 244.4 MB localhost:5000/postgres 9.4 6dff1b5c2259 5 days ago 244.4 MB Since docker tags are not permanent, and newer version of the postgres:9.4 image could be pushed to the public registry. When you self-host images, you are in control of when updates are pushed to any base image that you have extended. Someday I intend to learn how to build an image completely from scratch. Docker-ize All the Things!

Actuate recently released a new, free BIRT server called the BIRT iHub F-Type. It incorporates all the functionality of BIRT iHub and is limited only by the capacity of output it can deliver on a daily basis. It is ideal for departmental and smaller scale applications. When BIRT F-Type reaches its maximum output capacity, additional capacity can be purchased on a subscription based model. Some of the key features of BIRT iHub F-Type that will help improve your BIRT content applications are: Interactivity – Allow end-users to modify and personalize reports, and answer questions themselves. Scheduling – Automate report generation based on rules and calendar, and then notify users. Sharing – Secure document management and distribution that allows users to only access content/data they are entitled to. Excel Emitter – Export as native Excel (not CSV) with formulas/pivot tables/worksheets/charts. Integration – JavaScript API to embed dynamic reports and visualizations in your web app. Downloading BIRT iHub F-Type Before we get started with the installation process, we need to download BIRT iHub F-Type. There are three downloads available: Windows, Linux, and a VMware image. This blog will cover the Windows installation. If you’re installing either of the other types, you’ll find links to guides for them at the bottom of this blog post. Once you click on your chosen download, you’ll be asked to register. If you’ve already registered, click the “Click to Login” button. If not, fill out the short registration form to get started. Next, read and accept the license agreement. Once you’ve done that, click the checkbox, and a link for the download will appear. Click that to start your download. At this point, you should also receive an email with an activation code. Be sure to check your spam folder if you don’t see it in your inbox. Installing BIRT iHub F-Type After the download is complete, launch the executable file named ActuateBIRTiHubFType.exe. A welcome message will appear. Press Next to continue. You must read and accept the license agreement on the next screen. Choose a destination folder for the installation. The default is C:\Actuate\BIRTiHub. If you have existing BIRT designs that depend on a JDBC database driver, you can optionally specify the folder where these drivers are located. Press Next to continue. Once the installation has finished, press Finish to launch the BIRT iHub F-Type. A desktop shortcut is also created that points to the iHub F-Type URL at http://localhost:8700/iportal. The first time you launch the BIRT iHub F-Type, you will need to activate it. Enter the activation code that you should have received in an e-mail. After entering a valid activation code, you should receive a message that the code was accepted and the BIRT iHub F-Type should start initializing services. Once that has completed, you will be presented with the login screen. The default user name is “administrator” and the password is blank for your first log in. You’ll be able to change this after you have logged in. Press “Log In” to continue. The first time you launch the BIRT iHub F-Type, you will be in tutorial mode which will help you get started loading your BIRT content and required resources. You can bypass the tutorial mode at any time by pressing the “Exit Tutorial” button at the top right. Select a BIRT design (*.rptdesign) file and press the Upload button. If you don’t have a BIRT design, you can download a sample from the link on the same page. The BIRT design file is automatically inspected and if there are any dependent files needed, like images, data files, BIRT report libraries, CSS styles, or other linked BIRT designs, you will be asked to upload those files as well. Once your BIRT design and dependent files are uploaded, your BIRT report will be displayed in the BIRT iHub F-Type and is now ready to explore. Thanks for reading. Now, it’s time to unleash the full power of BIRT into your application. If you have any questions or comments, please feel free to use the comments section below or visit the BIRT iHub F-Type forum. -Virgil For more blogs in the “Introducing BIRT iHub F-Type” series, see the list below: Installing iHub F-Type: Linux | VMWare Image - See more at: http://blogs.actuate.com/introducing-birt-ihub-f-type-installing-on-windows/#sthash.QPJhv2gw.dpuf

This is a sample that I have wanted to try for sometime - A Websocket application to tail the contents of a file. The following is the final view of the web-application: There are a few parts to this application: Generating a File to tail: I chose to use a set of 100 random quotes as a source of the file content, every few seconds the application generates a quote and writes this quote to the temporary file. Spring Integration is used for wiring this flow for writing the contents to the file: Just a quick note, Spring Integration flows can now also be written using a Java Based DSL, and this flow using Java is available here Tailing the file and sending the content to a broker The actual tailing of the file itself can be accomplished by OS specific tail command or by using a library like Apache Commons IO. Again in my case I decided to use Spring Integration which provides Inbound channel adapters to tail a file purely using configuration, this flow looks like this: and its working Java equivalent There is a reference to a "fileContentRecordingService" above, this is the component which will direct the lines of the file to a place where the Websocket client will subscribe to. Websocket server configuration Spring Websocket support makes it super simple to write a Websocket based application, in this instance the entire working configuration is the following: @Configuration @EnableWebSocketMessageBroker public class WebSocketDefaultConfig extends AbstractWebSocketMessageBrokerConfigurer { @Override public void configureMessageBroker(MessageBrokerRegistry config) { //config.enableStompBrokerRelay("/topic/", "/queue/"); config.enableSimpleBroker("/topic/", "/queue/"); config.setApplicationDestinationPrefixes("/app"); } @Override public void registerStompEndpoints(StompEndpointRegistry registry) { registry.addEndpoint("/tailfilesep").withSockJS(); } } This may seem a little over the top, but what these few lines of configuration does is very powerful and the configuration can be better understood by going through the reference here. In brief, it sets up a websocket endpoint at '/tailfileep' uri, this endpoint is enhanced with SockJS support, Stomp is used as a sub-protocol, endpoints `/topic` and `/queue` is configured to a real broker like RabbitMQ or ActiveMQ but in this specific to an in-memory one. Going back to the "fileContentRecordingService" once more, this component essentially takes the line of the file and sends it this in-memory broker, SimpMessagingTemplate facilitates this wiring: public class FileContentRecordingService { @Autowired private SimpMessagingTemplate simpMessagingTemplate; public void sendLinesToTopic(String line) { this.simpMessagingTemplate.convertAndSend("/topic/tailfiles", line); } } Websocket UI configuration The UI is angularjs based, the client controller is set up this way and internally uses the javascript libraries for sockjs and stomp support: var tailFilesApp = angular.module("tailFilesApp",[]); tailFilesApp.controller("TailFilesCtrl", function ($scope) { function init() { $scope.buffer = new CircularBuffer(20); } $scope.initSockets = function() { $scope.socket={}; $scope.socket.client = new SockJS("/tailfilesep); $scope.socket.stomp = Stomp.over($scope.socket.client); $scope.socket.stomp.connect({}, function() { $scope.socket.stomp.subscribe("/topic/tailfiles", $scope.notify); }); $scope.socket.client.onclose = $scope.reconnect; }; $scope.notify = function(message) { $scope.$apply(function() { $scope.buffer.add(angular.fromJson(message.body)); }); }; $scope.reconnect = function() { setTimeout($scope.initSockets, 10000); }; init(); $scope.initSockets(); }); The meat of this code is the "notify" function which the callback acting on the messages from the server, in this instance the new lines coming into the file and showing it in a textarea. This wraps up the entire application to tail a file. A complete working sample without any external dependencies is available at this github location, instructions to start it up is also available at that location. Conclusion Spring Websockets provides a concise way to create Websocket based applications, this sample provides a good demonstration of this support. I had presented on this topic recently at my local JUG (IndyJUG) and a deck with the presentation is available here

Closely approaching the one year mark of when I first joined MongoLab (and the MongoDB community), I had the pleasure of attending the inaugural MongoDB World conference put together by the incredible MongoDB team. Second only to the excitement around major MongoDB feature announcements was the collective disbelief that this was MongoDB’s first multi-day conference ever. A big congratulations to all those that worked hard to put on such a massive (did you see the Intrepid!?) event. All this planning would have been for naught if MongoDB leaders and engineers failed to deliver announcements and features that would meet and exceed expectations. From major public cloud announcements to the reveal of document-level locking in version 2.8, developers and conference goers had plenty to be excited about. There was a lot to digest from the conference… we’ll cover the major highlights in case you missed them. Big announcements in public cloud Our time at the MongoLab booth yielded many high-quality conversations, predominantly those about offloading previously internal processes and workloads to the public cloud. It was remarkable to see and hear so many enterprise teams with the exact same message: the public cloud is the future, and the future is now. It’s no surprise then that MongoDB, Inc. released not one, but two press releases around MongoDB solutions for the public cloud. Fully-managed MongoDB on the Microsoft Azure Store Nearly one year ago, MongoDB, Inc. chose to partner with the MongoLab team to build a production-ready MongoDB solution for developers on Microsoft Azure. On the first day of World, MongoDB, Inc. announced the product of our collaboration – a fully-managed highly available MongoDB-as-a-Service Add-On offering on the Microsoft Azure Store. This new service runs MongoDB Enterprise and offers replication, monitoring and support from MongoDB, Inc. It’s also backed by MongoDB Management Service (MMS), allowing for point-in-time recovery of MongoDB deployments. Now, teams without the expertise or resources to manage their MongoDB deployment(s) can outsource all the database operations (monitoring and alerting, backups, performance tuning, etc.) to both MongoLab and MongoDB’s expert support teams. You can check out the MongoDB add-on in the Azure Store: https://azure.microsoft.com/en-us/gallery/store/mongodb/mongodb-inc/ MongoDB solutions on Google Cloud Platform MongoDB, Inc. also announced the arrival of new resources to help Google Cloud Platform customers deploy MongoDB on Google Compute Engine. These resources include a “Click to Deploy” feature and a MongoDB on Google Compute Engine Solutions paper covering MongoDB best practices. If you are looking for a fully-managed solution, with automated provisioning, backups, integrated monitoring and alerting, along with expert support, MongoLab recently announced the arrival of production-ready replica sets on Google. Product Roadmap – MongoDB version 2.8 On the second day of MongoDB World, Eliot Horowitz, MongoDB, Inc. CTO & Co-founder, took center stage and announced two huge changes to the MongoDB core project: document-level locking and pluggable storage engines. These features not only reflect improvements to the core project, but also signal to the community that the MongoDB team is listening to its users and is capable of delivering the software needed to power the workloads of tomorrow. Document-level locking The slides above from Eliot’s keynote point to a current obstacle (database-level locking) in MongoDB that limits overall scalability. With database-level locking, any write operation to the database holds the write lock and prevents subsequent writes from executing on the database until the original operation holding the write lock completes. Eliot’s announcement of document-level locking moves the write lock contention from the database level to the document (MongoDB equivalent to SQL “records”) level. This change will allow users to achieve much higher write throughput (we saw a 10x performance improvement in the live demo) across their MongoDB deployments, improving write scalability. If you’d like to try out document-level locking, the MongoDB team has already pushed the feature to the master branch on GitHub. This should only be used for experimentation, not to be run in production. Pluggable storage engine As MongoDB matures, feature releases like document level locking will continue to allow developers to build robust systems on top of MongoDB. But as the number of use cases grows, different tooling tailored to specific use cases may prove to be extremely beneficial. For example, if Company X decides that they want to use MongoDB to warehouse some of their data, they would likely want to optimize their database for slow-moving data and storage efficiency (compression). With the introduction of pluggable storage engines, many new possibilities are open to the community. Teams can now write their own storage engine for a particular use case, configure replica set nodes with different storage engines for specific situations, or collaborate with the open-source community to architect innovative solutions. This feature not only allows for more granular control of the database, but also encourages the MongoDB community to work together. Takeaways: A maturing and thriving ecosystem Roughly a year ago, MongoLab CTO Todd Dampier recapped MongoSF 2013 and spoke to the health of the MongoDB ecosystem. How far we’ve come! After attending the inaugural MongoDB World and chatting with MongoDB Masters, interns, hackathon winners, power users and those new to the community, the enthusiasm is still surging and as positive as ever. This enthusiasm is well placed. Developers and hackers use MongoDB because so much rich data on the web is shared as JSON (think Facebook, Twitter, Google, etc.). As a result, MongoDB is the de-facto database for hackathons and bootstrapped projects. Just learn the API for the site you want to mine, throw the JSON in MongoDB and query your data with the rich query language- it’s that easy. The MongoDB ecosystem is maturing as well. Take a look at the Customer Success Stories and you’ll get a feel for the extent in which enterprises leverage the solution and use it in production. To further drive enterprise adoption, MongoDB, Inc.’s public cloud solutions and product roadmap features aim to help teams run MongoDB in production and give teams the confidence that MongoDB will continue to improve scalability and meet their growing project requirements. Congratulations again to the MongoDB team on their big announcements and for creating such a fantastic forum at which to learn and meet fellow MongoDB users. Our team at MongoLab had a great time making new friends and talking shop; we look forward to meeting more MongoDB users soon (at a MongoDB Days near you)! -Chris@MongoLab

So you already know what Hadoop is? Why it is used? What problems you can solve with it?

This post exists to help with an MSDN Magazine article that I am authoring It provides some of the low-level details for the article How to install Mono and root certificates on a raspberry pi How to create an Azure mobile service How to create a Custom API inside Azure mobile services that the raspberry pi can call into How to create an Azure storage account MONO - HOW TO INSTALL ON A RASPBERRY PI Why Mono? How to install Mono on a raspberry pi Installing trusted root certificates on to the raspberry pi http://www.mono-project.com/Main_Page An open source, cross-platform, implementation of C# and the CLR that is binary compatible with Microsoft.NET Mono is a free and open source project led by Xamarin (formerly by Novell) that provides a .NET Framework-compatible set of tools including, among others, a C# compiler and a Common Language Runtime WHY MONO? Because it lets us write .net code compiled on Windows We can simply copy the binary files from Windows to Linux and run it as is From a raspberry pi device, it is possible to use a .net application to take a photo and upload it to Windows Azure storage HOW TO INSTALL ON A RASPBERRY PI RUNNING LINUX You will issue the following commands: pi@raspberrypi ~ $ sudo apt-get update pi@raspberrypi ~ $ sudo apt-get install mono-complete The first command makes sure all the local package index are up to date with the changes made in repositories. Second command installs the complete Mono tooling and runtime. MAKING SURE THAT YOUR MONO APPLICATIONS CAN MAKE A HTTPS REST-BASED CALLS This command downloads the trusted root certificates from the Mozilla LXR web site into the Mono certificate store. Once complete, the Raspberry PI will be capable of making web requests using HTTPS requests within Mono. pi@raspberrypi ~ $ mozroots --import --ask-remove --machine CREATING A NEW AZURE MOBILE SERVICES ACCOUNT The mobile services account is needed to host a Node.js application that provides shared access signatures to raspberry pi devices The shared access signature is needed by the raspberry pi, so that it can directly and securely upload photos to Azure storage STEPS TO CREATE AN AZURE MOBILE SERVICE The steps below will create an Azure mobile service The service will be used to host a Node.js application interacting with a raspberry pi devices We will provision a SQL database, although it will not be used initially FOLLOW THESE STEPS TO CREATE THE MOBILE SERVICE Login into the Azure Portal Select MOBILE SERVICES from the left menu pane at the Azure Portal. In the lower left corner select "+NEW" to create a new Azure Mobile Service. Make sure you've selected, "COMPUTE / MOBILE SERVICE / CREATE." You will now enter a url. We will call this service raspberrymobileservice. For the DATABASE, we will choose "Create a new SQL database instance." The REGION we chose is "West US." The BACKEND is "JavaScript." Click the "->" arrow to proceed to the next screen. In this screen you will "Specify database settings." The NAME of your database will based on the URL you entered previously. In this case, the database is called "raspberrymobileservice_db." You will need to choose a SERVER. We will choose "New SQL database server" from the drop-down list. You will need to provide a SERVER LOGIN NAME and a SERVER LOGIN PASSWORD. Take note of the login you provided as it will be needed later CREATING A CUSTOM API Azure mobile services allows you to create a custom API written in JavaScript that can be called from a raspberry pi device using REST This custom API is really just a Node.js application running in the server CREATING THE API TO RESPOND TO THE DEVICE TRYING TO UPLOAD PHOTOS Now that the service is established, we will turn our attention to creating an API that the device can call into to upload a photo. Login into the Azure Portal Your mobile service will take a few minutes to complete, and you should see the "Ready" flag as the "Status" for your service. Once it is ready you can drill into your service to customize its behavior. Just to the right of the service name, click the right arrow key "->" to drill into the service details. The top menu bar will offer many options, but we are interested in the one titled "API." The API allows you to create a series of node.JS API calls that a device can call into using rest-based approaches. Click on "API." from there, select "CREATE A CUSTOM API." You will be asked to provide an API name. Type in "photos" for the API name. Below you will see a series of drop-down combo boxes that relate to permission. We will keep the default value of "Anybody with the application key." This might not be the best option for all scenarios. You can read more about this here. http://msdn.microsoft.com/en-us/library/azure/jj193161.aspx. Click the checkmark to complete the process. The name of the AP you just created, "Photos," should be visible on the portal interface. To drill into the photos API click on the right arrow key "->". The right arrow key will be just to the right of the name of the API "Photos". At this point you should see a basic script that has been provided by default. We will overwrite this default script with our own script as described in the MSDN Magazine article. CREATING A STORAGE ACCOUNT TO STORE THE PHOTOS Navigate to the portal and create a storage account Create a container for the photos Obtain the: Storage Account Name (you will provide a name) Storage Account Access key (generated for you) Container Name (you will create) CREATING A STORAGE ACCOUNT We will need a storage account so that we can upload photos to it. The steps are well documented here: http://azure.microsoft.com/en-us/documentation/articles/storage-create-storage-account/ In our case we call the storage account raspberrystorage. This means that the URL that the device will use to upload photos is https://raspberrystorage.blob.core.windows.net/. As you complete these steps make sure that you choose the storage account location to be the same location as was used for your mobile services account. This avoids any unnecessary latency or bandwidth costs between data centers. Once the storage account is created, we will need to create a container within it. Photos or any blob for that matter, are always stored within a container. To create a container drill into your newly created storage account and select CONTAINERS from the top menu. From there, select CREATE A CONTAINER. The new container dialog box will ask for a name for your container. Take note of the name you provide. We are calling our container ?photocontainer.? When the raspberry pi device uploads photos to the storage account, it will target a specific container, such as the one we just created. You will next be asked to indicate ACCESS rights. To keep things simple we will select access rights of Public Blob. ENTERING APP SETTINGS Rather than hard-code storage account information inside your JavaScript/Node.js applications, you should consider using apps settings inside of the Azure mobile services portal This post also discusses it well: http://blogs.msdn.com/b/carlosfigueira/archive/2013/12/09/application-settings-in-azure-mobile-services.aspx ?The idea of application settings is a set of key-value pairs which can be set for the mobile service (either via the portal or via the command-line interface), and those values could be then read in the service runtime.? NAVIGATING TO APP SETTINGS Navigate to the Azure Mobile Services section of the portal. Drill into the specific service by hitting the arrow below Select from the Configure Menu at the top Scroll down to the very bottom to see app settings Note that we need to enter: - We need to get this from Azure Storage - PhotoContainerName - AccountName - AccountKey We get this information from the Azure Storage Section of the Portal. Note that you need to have provisioned a Storage Account to have this information. How to get the AccountKey with Azure Storage Services Now you can get the access keys HOW NODE.JS WILL ACCESS THE APP SETTINGS You will create a Node.js application inside of Azure Mobile Services See previous steps THE NODE.JS APPLICATION READING APP SETTINGS You will starting by going back to Azure Mobile Services and drill down into your newly minted service We called ours raspberrymobileservice Once you click API, you should see: Notice the app settings are being read on lines 12 to 14.