Groovy's XmlParser makes it easy to parse an XML file, XML input stream, or XML string using one its overloaded parse methods (or parseText in the case of the String). The XML content parsed with any of these methods is made available as a groovy.util.Node instance. This blog post describes how to make the return trip and write the content of the Node back to XML in alternative formats such as a File or aString. Groovy's MarkupBuilder provides a convenient approach for generating XML from Groovy code. For example, I demonstrated writing XML based on SQL query results in the post GroovySql and MarkupBuilder: SQL-to-XML. However, when one wishes to write/serialize XML from a Groovy Node, an easy and appropriate approach is to use XmlNodePrinter as demonstrated in Updating XML with XmlParser. The next code listing, parseAndPrintXml.groovy demonstrates use of XmlParser to parse XML from a provided file and use of XmlNodePrinter to write that Node parsed from the file to standard output as XML. parseAndPrintXml.groovy : Writing XML to Standard Output #!/usr/bin/env groovy // parseAndPrintXml.groovy // // Uses Groovy's XmlParser to parse provided XML file and uses Groovy's // XmlNodePrinter to print the contents of the Node parsed from the XML with // XmlParser to standard output. if (args.length < 1) { println "USAGE: groovy parseAndPrintXml.groovy " System.exit(-1) } XmlParser xmlParser = new XmlParser() Node xml = xmlParser.parse(new File(args[0])) XmlNodePrinter nodePrinter = new XmlNodePrinter(preserveWhitespace:true) nodePrinter.print(xml) Putting aside the comments and code for checking command line arguments, there are really 4 lines (lines 15-18) in the above code listing of significance to this discussion. These four lines demonstrate instantiating anXmlParser (line 15), using the instance of XmlParser to "parse" a File instance based on a provided argument file name (line 16), instantiating an XmlNodePrinter (line 17), and using that XmlNodePrinterinstance to "print" the parsed XML to standard output (line 18). Although writing XML to standard output can be useful for a user to review or to redirect output to another script or tool, there are times when it is more useful to have access to the parsed XML as a String. The next code listing is just a bit more involved than the last one and demonstrates use of XmlNodePrinter to write the parsed XML contained in an Node instance as a Java String. parseXmlToString.groovy : Writing XML to Java String #!/usr/bin/env groovy // parseXmlToString.groovy // // Uses Groovy's XmlParser to parse provided XML file and uses Groovy's // XmlNodePrinter to write the contents of the Node parsed from the XML with // XmlParser into a Java String. if (args.length < 1) { println "USAGE: groovy parseXmlToString.groovy " System.exit(-1) } XmlParser xmlParser = new XmlParser() Node xml = xmlParser.parse(new File(args[0])) StringWriter stringWriter = new StringWriter() XmlNodePrinter nodePrinter = new XmlNodePrinter(new PrintWriter(stringWriter)) nodePrinter.setPreserveWhitespace(true) nodePrinter.print(xml) String xmlString = stringWriter.toString() println "XML as String:\n${xmlString}" As the just-shown code listing demonstrates, one can instantiate an instance of XmlNodePrinter that writes to a PrintWriter that was instantiated with a StringWriter. This StringWriter ultimately makes the XML available as a Java String. Writing XML from a groovy.util.Node to a File is very similar to writing it to a String with a FileWriterused instead of a StringWriter. This is demonstrated in the next code listing. parseAndSaveXml.groovy : Write XML to File #!/usr/bin/env groovy // parseAndSaveXml.groovy // // Uses Groovy's XmlParser to parse provided XML file and uses Groovy's // XmlNodePrinter to write the contents of the Node parsed from the XML with // XmlParser to file with provided name. if (args.length < 2) { println "USAGE: groovy parseAndSaveXml.groovy " System.exit(-1) } XmlParser xmlParser = new XmlParser() Node xml = xmlParser.parse(new File(args[0])) FileWriter fileWriter = new FileWriter(args[1]) XmlNodePrinter nodePrinter = new XmlNodePrinter(new PrintWriter(fileWriter)) nodePrinter.setPreserveWhitespace(true) nodePrinter.print(xml) I don't show it in this post, but the value of being able to write a Node back out as XML often comes after modifying that Node instance. Updating XML with XmlParser demonstrates the type of functionality that can be performed on a Node before serializing the modified instance back out.

Retry-After is a lesser known HTTP response header.

Even though I was supposed to write a series of blog posts about micro-infra-spring here at Too Much Coding blog, today I'll write about how we've managed to decrease our biggest project's build time from 90 to 8 minutes! In one of the companies I've been working for we've faced a big problem related to pull request build times. We have one monolithic application that we are in progress of slicing into microservices but still until this process is finished we have to build that big app for each PR. We needed to change things to have really fast feedback from our build so that pull request builds don't get queued up endlessly in our CI. You can only imagine the frustration of developers who can't have their branches merged to master because of the waiting time. Structure In that project we have over 200 Gradle modules and over a dozen big projects (countries) from which we can build some (really fat) fat-jars. We have also a core module that if we change then we would have to rebuild all the big projects to check if they weren't affected by the modifications. There are a few old countries that are using GWT compilers and we have some JS tasks executed too. Initial stats Before we started to work on optimization of the process the whole application (all the countries) was built in about 1h 30 minutes. Current build time: ~90 minutes. Profile your build First thing that we've done was to run the build with the --profile switch. ./gradlew clean buildAll --profile That way Gradle created awesome stats for our build. If you are doing any sort of optimization then it's crucial to gather measurements and statistics. Check out this Gradle page about profiling your build for more info on that switch and features. Exclude long running tasks in dev mode It turned out that we are spending a lot of time on JS minification and on GWT compilation. That's why we have added a custom property -PdevMode to disable some long running tasks in dev mode build. Those tasks were: excluded JS minification benefit: 13 countries * ~60 secs * at least 2 modules where minification occurred ~ 26 minutes optimized GWT compilation: have permutations done for only 1 browser (by default it's done for multiple browsers) disable optimization of the compilation (-optimize 0) add the -draftCompile switch to to compile quickly with minimal optimizations benefit: about 2 minutes less on GWT compilation * sth like 5 projects with GWT ~ 10 minutes Overall gain: ~ 40 minutes. Current build time: ~50 minutes. Check out your tests Together with the one and only Adam Chudzik we have started to write our own Gradle Test Profiler (it's a super beta version ;) ) that created a single CSV with sorted tests by their execution time. We needed quick and easy gains without endless test refactoring and it turned out that it's really simple. One of our tests took 50 seconds to execute and it was testing a feature that has and will never be turned on on production. Of course there were plenty of other tests that we should take a look into (we'd have to look for test duplication, check out the test setup etc.) but it would involve more time, help of a QA and we needed quick gains. Benefit: By simple disabling this test we gained about 1 minute. Overall gain: ~ 41 minutes. Current build time: ~49 minutes. Turn on the --parallel Gradle flag at least for the compilation Even though at this point our gains were more or less 40 minutes it was still unacceptable for us to wait 40 minutes for the pull request to be built. That's why we decided to go parallel! Let's build the projects (over 200) in parallel and we'll gain a lot of time on that. When you execute the Gradle build with the --parallel flag Gradle calculates how many threads can be used to concurrently build the modules. For more info go to the Gradle's documentation on parallel project execution. It's an incubating feature so wen we started to get BindExceptions on port allocation we initially thought that most likely it's Gradle's fault. Then we had a chat with Szczepan Faberwho worked for Gradleware and it turns out that the feature is actually really mature (thx Szczepan for the help BTW :) ). We needed quick gains so instead of fixing the port binding stuff we decided only to compile everything in parallel and then run tests sequentially. ./gradlew clean buildAll -PdevMode -x test --parallel && ./gradlew buildAll-PdevMode Benefit: By doing this lame looking hack we gained ~4 mintues (on my 8 core laptop). Overall gain: ~ 45 minutes. Current build time: ~45 minutes. Don't be a jerk - just prepare your tests for parallelization This command seemed so lame that we couldn't even look at it. That's why we said - let's not be jerks and just fix the port issues. So we went through the code, randomized all the fixed ports, patched micro-infra-spring so it does the same upon Wiremock and Zookeeper instantiation and just ran the building of the project like this: ./gradlew clean buildAll-PdevMode --parallel We were sure that this is the killer feature that we were lacking and we're going to win the lottery. Much to our surprise the result was really disappointing. Benefit: Concurrent project build decreased the time by ~5 minutes. Overall gain: ~ 50 minutes. Current build time: ~40 minutes. Check out your project structure You can only imagine the number of WTFs that were there in our office. How on earth is that possible? We've opened up htop, iotop and all the possible tools including vmstat to see what the hell was going on. It turned out that context switching is at an acceptable level whereas at some point of the build only part of the cores are used as if sth was executed sequentially! The answer to that mystery was pretty simple. We had a wrong project structure. We had a module that ended up as a test-jar in testCompile dependency of other projects. That means that the vast majority of modules where waiting for this project to be built. Built means compiled and tested. It turned out that this test-jar module had also plenty of slow integration tests in it so only after those tests were executed could other modules be actually built! Simple source moving can drastically increase your speed By simply moving those slow tests to a separate module we've unblocked the build of all modules that were previously waiting. Now we could do further optimization - we've split the slow integration tests into two modules to make all the modules in the whole project be built in more or less equal time (around 3,5 minutes). . Benefit: Fixing the project structure decreased the time by ~10 minutes Overall gain: ~ 60 minutes. Current build time: ~30 minutes. Don't save on machine power We've invested in some big AWS instance with 32 cores and 60 gb of RAM to really profit from the parallel build's possibilities. We're paying about 1.68$ per one hour of such machine's (c3.8xlarge) working time. If someone form the management tells you that that machine costs a lot of money and the company can't afford it you can actually do a fast calculation. You can ask this manager what is more expensive - paying for the machine or paying the developer for 77 minutes * number of builds of waiting? Benefit: Paying for a really good machine on AWS decreased the build time by ~22 minutes Overall gain: ~ 82 minutes. Current build time: ~8 minutes. What else can we do? Is that it? Can we decrease the time further on? Sure we can! Possible solutions are: Go through all of the tests and check why some of them take so long to run Go through the integration tests and check if don't duplicate the logic - we will remove them We're using Liquibase for schema versioning and we haven't merged the changests for some time thus sth like 100 changesets are executed each time we boot up Spring context (it takes more or less 30 seconds) We could limit the Spring context scope for different parts of our applications so that Spring boots up faster Buy a more powerful machine ;) There is also another, better way ;) SPLIT THE MONOLITH INTO MICROSERVICES AND GO TO PRODUCTION IN 5 MINUTES ;) Summary Hopefully I've managed to show you how you can really speed up your build process. The work to be done is difficult, sometimes really frustrating but as you can see very fruitful.

Spock supports JUnit rules out of the box. We simply add a rule with the @Rule annotation to our Spock specification and the rule can be used just like in a JUnit test. The Spring Boot project contains a JUnit rule OutputCapture to capture the output of System.out and System.err. In the following example specification we apply the OutputCapture rule and use it in two feature methods: package com.mrhaki.spock @Grab('org.spockframework:spock-core:0.7-groovy-2.0') import spock.lang.* @Grab('org.springframework.boot:spring-boot:1.2.1.RELEASE') import org.springframework.boot.test.OutputCapture class CaptureOutputSpec extends Specification { @org.junit.Rule OutputCapture capture = new OutputCapture() def "capture output print method"() { when: print 'Groovy rocks' then: capture.toString() == 'Groovy rocks' } def "banner text must contain given messagen and fixed header"() { given: final Banner banner = new Banner(message: 'Spock is gr8!') when: banner.print() then: final List lines = capture.toString().tokenize(System.properties['line.separator']) lines.first() == '*** Message ***' lines.last() == ' Spock is gr8! ' } } /** * Class under test. The print method * uses println statements to display * some message on the console. */ class Banner { String message void print() { println ' Message '.center(15, '*') println message.center(15) } } Written with Spock-0.7-groovy-2.0.

Learn how to handle exception in Spring controller using: ResponseEntity and HttpStatus, @ResponseStatus on the custom exception class, and more custom methods.

Adding a feature to legacy code while trying to improve it can be quite challenging, but also quite straightforward. Nothing angers me more (ok, I might be a little exaggerating) than stumbling upon such pattern: public Foo getFoo(Bar bar) { if (bar instanceof BarA) { return new FooA(); } else if (bar instanceof BarB) { return new FooB(); } else if (bar instanceof BarC) { return new FooC(); } else if (bar instanceof BarD) { return new FooD(); } throw new BarNotFoundException(); } Apply Object-Oriented Programming The first reflex when writing such thing – yes, please don’t wait for the poor guy coming after you to clean your mess, should be to ask yourself whether applying basic Object-Oriented Programming couldn’t help you. In this case, you would have multiple children classes of: public interface FooBarFunction extends Function For example public class FooBarAFunction implements FooBarFunction { public FooA apply(BarA bar) { return new FooA(); } } Note: not enjoying the benefits of Java 8 is not reason not to use this: just create your own Function interface or use Guava’s. Use a Map I must admit that it not only scatters tightly related code in multiple files (this is Java…), it’s unfortunately not always possible to easily apply OOP. In that case, it’s quite easy to initialise a map that returns the correct type. public class FooBarFunction { private static final Map, Foo> MAPPINGS = new HashMap<>(); static { MAPPINGS.put(BarA.class, new FooA()); MAPPINGS.put(BarB.class, new FooB()); MAPPINGS.put(BarC.class, new FooC()); MAPPINGS.put(BarD.class, new FooD()); } public Foo getFoo(Bar bar) { Foo foo = MAPPINGS.get(bar.getClass()); if (foo == null) { throw new BarNotFoundException(); } return foo; } } Note this is only a basic example, and users of Dependency Injection can easily pass the map in the object constructor instead. More than a return The previous Map trick works quite well with return statements but not with code snippets. In this case, you need to use the map to return an enum and associate it with a switch-case. public class FooBarFunction { private enum BarEnum { A, B, C, D } private static final Map, BarEnum> MAPPINGS = new HashMap<>(); static { MAPPINGS.put(BarA.class, BarEnum.A); MAPPINGS.put(BarB.class, BarEnum.B); MAPPINGS.put(BarC.class, BarEnum.C); MAPPINGS.put(BarD.class, BarEnum.D); } public Foo getFoo(Bar bar) { BarEnum barEnum = MAPPINGS.get(bar.getClass()); switch(barEnum) { case BarEnum.A: // Do something; break; case BarEnum.B: // Do something; break; case BarEnum.C: // Do something; break; case BarEnum.D: // Do something; break; default: throw new BarNotFoundException(); } } } Note that not only I believe that this code is more readable but it’s also a fact it has better performance and the switch is evaluated once as opposite to each if…else being evaluated in sequence until it returns true. Note it’s expected not to put the code directly in the statement but use dedicated method calls. Conclusion I hope that at this point, you’re convinced there are other ways than sequences of if…else. The rest is in your hands. - See more at: http://blog.frankel.ch/avoid-sequences-else-statements#sthash.UTxFt2Nt.dpuf

Each group consists of only one observation. Do you need to adjust the group aesthetic? I’ve been playing around with some weather data over the last couple of days which I aggregated down to the average temperature per month over the last 4 years and stored in a CSV file. This is what the file looks like: $ cat /tmp/averageTemperatureByMonth.csv "month","aveTemperature" "January",6.02684563758389 "February",5.89380530973451 "March",7.54838709677419 "April",10.875 "May",13.3064516129032 "June",15.9666666666667 "July",18.8387096774194 "August",18.3709677419355 "September",16.2583333333333 "October",13.4596774193548 "November",9.19166666666667 "December",7.01612903225806 I wanted to create a simple line chart which would show the months of the year in ascending order with the appropriate temperature. My first attempt was the following: df = read.csv("/tmp/averageTemperatureByMonth.csv") df$month = factor(df$month, month.name) ggplot(aes(x = month, y = aveTemperature), data = df) + geom_line( ) + ggtitle("Temperature by month") which resulted in the following error: geom_path: Each group consist of only one observation. Do you need to adjust the group aesthetic? My understanding is that the points don’t get joined up by default because the variable on the x axis is not a continuous one but rather a factor variable. One way to work around this problem is to make it numeric, like so: ggplot(aes(x = as.numeric(month), y = aveTemperature), data = df) + geom_line( ) + ggtitle("Temperature by month") which results in the following chart: This isn’t bad but it’d be much nicer if we could have the month names along the bottom instead. It turns out we can but we need to specify a group that each point belongs to. ggplot will then connects points which belong to the same group. In this case we don’t really have one so we’ll define a dummy one instead: ggplot(aes(x = month, y = aveTemperature, group=1), data = df) + geom_line( ) + ggtitle("Temperature by month") And now we get the visualisation we want: Be Sociable, Share!

I've been intrigued by JHipster ever since I first tried it last September. I'd worked with AngularJS and Spring Boot quite a bit, and I liked the idea that someone had combined them, adding some nifty features along the way. When I spoke about AngularJS earlier this month, I included a few slides on JHipster near the end of the presentation. This week, I received an email from someone who attended that presentation. Hey Matt, We met a few weeks back when you presented at DOSUG. You were talking about JHipster which I had been eyeing for a few months and wanted your quick .02 cents. I have built a pretty heavy application over the last 6 months that is using mostly the same tech as JHipster. Java Spring JPA AngularJS Compass Grunt It's ridiculously close for most of the tech stack. So, I was debating rolling it over into a JHipster app to make it a more familiar stack for folks. My concern is that it I will spend months trying to shoehorn it in for not much ROI. Any thoughts on going down this path? What are the biggest issues you've seen in using JHipster? It seems pretty straightforward except for the entity generators. I'm concerned they are totally different than what I am using. The main difference in what I'm doing compared to JHipster is my almost complete use of groovy instead of old school Java in the app. I would have to be forced into going back to regular java beans... Thoughts? I replied with the following advice: JHipster is great for starting a project, but I don't know that it buys you much value after the first few months. I would stick with your current setup and consider JHipster for your next project. I've only prototyped with it, I haven't created any client apps or put anything in production. I have with Spring Boot and AngularJS though, so I like that JHipster combines them for me. JHipster doesn't generate Scala or Groovy code, but you could still use them in a project as long as you had Maven/Gradle configured properly. You might try generating a new app with JHipster and examine how they're doing this. At the very least, it can be a good learning tool, even if you're not using it directly. Java Hipsters: Do you agree with this advice? Have you tried migrating an existing app to JHipster? Are any of you using Scala or Groovy in your JHipster projects?

Recently a few people were asking me why I have a blog. Some of them were not programmers. It reminded me about a draft of this post, which I have had for more than a year now. I planned to extend it, but I think keeping it short, and maybe edit in the future would be a better solution. Here are the reasons why I have a blog: The Ghost Who Codes: How Anonymity is Killing Your Programming Career One of the best ways to learn is to Teach What You’ve Learned to Another Person (TWYLAP) Improve my writing skills To keep my own journal To be able to Google solutions for problems I had (e.g., like this) To market myself, show who I am, and what my interests and beliefs are

Google guice provides a neat way to select a target implementation if there are multiple implementations of an interface. My samples are based on anexcellent article by Josh Long(@starbuxman) on a similar mechanism that Spring provides. So, consider an interface called MarketPlace having two implementations, an AndroidMarketPlace and AppleMarketPlace: interface MarketPlace { } class AppleMarketPlace implements MarketPlace { @Override public String toString() { return "apple"; } } class GoogleMarketPlace implements MarketPlace { @Override public String toString() { return "android"; } } and consider a user of these implementations: class MarketPlaceUser { private final MarketPlace marketPlace; public MarketPlaceUser(MarketPlace marketPlace) { System.out.println("MarketPlaceUser constructor called.."); this.marketPlace = marketPlace; } public String showMarketPlace() { return this.marketPlace.toString(); } } A good way for MarketPlaceUser to disambiguate between these implementations is to use a guice feature called Binding Annotations. To make use of this feature, start by defining annotations for each of these implementations this way: @Retention(RetentionPolicy.RUNTIME) @Target({ElementType.FIELD, ElementType.PARAMETER}) @BindingAnnotation @interface Android {} @Retention(RetentionPolicy.RUNTIME) @Target({ElementType.FIELD, ElementType.PARAMETER}) @BindingAnnotation @interface Ios {} and inform the Guice binder about these annotations and the appropriate implementation corresponding to the annotation: class MultipleInstancesModule extends AbstractModule { @Override protected void configure() { bind(MarketPlace.class).annotatedWith(Ios.class).to(AppleMarketPlace.class).in(Scopes.SINGLETON); bind(MarketPlace.class).annotatedWith(Android.class).to(GoogleMarketPlace.class).in(Scopes.SINGLETON); bind(MarketPlaceUser.class).in(Scopes.SINGLETON); } } Now, if MarketPlaceUser needs to use one or the other implementation, this is how the dependency can be injected in: import com.google.inject.*; class MarketPlaceUser { private final MarketPlace marketPlace; @Inject public MarketPlaceUser(@Ios MarketPlace marketPlace) { this.marketPlace = marketPlace; } } This is very intuitive. If you have concerns about defining so many annotations, another approach could be to use @Named built-in Google Guice annotation, this way: class MultipleInstancesModule extends AbstractModule { @Override protected void configure() { bind(MarketPlace.class).annotatedWith(Names.named("ios")).to(AppleMarketPlace.class).in(Scopes.SINGLETON); bind(MarketPlace.class).annotatedWith(Names.named("android")).to(GoogleMarketPlace.class).in(Scopes.SINGLETON); bind(MarketPlaceUser.class).in(Scopes.SINGLETON); } } and use it this way, where the dependency is required: import com.google.inject.*; class MarketPlaceUser { private final MarketPlace marketPlace; @Inject public MarketPlaceUser(@Named("ios") MarketPlace marketPlace) { this.marketPlace = marketPlace; } } If you are interested in exploring this further, here is the Google guice sample and an equivalent sample using Spring framework

Basic Authentication is the simplest way to secure access to a resource.

Written by Dave Syer in the Spring blog In this article we continue our discussion of how to use Spring Security with Angular JS in a “single page application”. Here we show how to build an API Gateway to control the authentication and access to the backend resources using Spring Cloud. This is the fourth in a series of articles, and you can catch up on the basic building blocks of the application or build it from scratch by reading the first article, or you can just go straight to the source code in Github. In the last article we built a simple distributed application that used Spring Session to authenticate the backend resources. In this one we make the UI server into a reverse proxy to the backend resource server, fixing the issues with the last implementation (technical complexity introduced by custom token authentication), and giving us a lot of new options for controlling access from the browser client. Reminder: if you are working through this article with the sample application, be sure to clear your browser cache of cookies and HTTP Basic credentials. In Chrome the best way to do that for a single server is to open a new incognito window. Creating an API Gateway An API Gateway is a single point of entry (and control) for front end clients, which could be browser based (like the examples in this article) or mobile. The client only has to know the URL of one server, and the backend can be refactored at will with no change, which is a significant advantage. There are other advantages in terms of centralization and control: rate limiting, authentication, auditing and logging. And implementing a simple reverse proxy is really simple with Spring Cloud. If you were following along in the code, you will know that the application implementation at the end of the last article was a bit complicated, so it’s not a great place to iterate away from. There was, however, a halfway point which we could start from more easily, where the backend resource wasn’t yet secured with Spring Security. The source code for this is a separate project in Github so we are going to start from there. It has a UI server and a resource server and they are talking to each other. The resource server doesn’t have Spring Security yet so we can get the system working first and then add that layer. Declarative Reverse Proxy in One Line To turn it into an API Gateawy, the UI server needs one small tweak. Somewhere in the Spring configuration we need to add an @EnableZuulProxy annotation, e.g. in the main (only)application class: @SpringBootApplication @RestController @EnableZuulProxy public class UiApplication { ... } and in an external configuration file we need to map a local resource in the UI server to a remote one in the external configuration (“application.yml”): security: ... zuul: routes: resource: path: /resource/** url: http://localhost:9000 This says “map paths with the pattern /resource/** in this server to the same paths in the remote server at localhost:9000”. Simple and yet effective (OK so it’s 6 lines including the YAML, but you don’t always need that)! All we need to make this work is the right stuff on the classpath. For that purpose we have a few new lines in our Maven POM: org.springframework.cloud spring-cloud-starter-parent 1.0.0.BUILD-SNAPSHOT pom import org.springframework.cloud spring-cloud-starter-zuul ... Note the use of the “spring-cloud-starter-zuul” - it’s a starter POM just like the Spring Boot ones, but it governs the dependencies we need for this Zuul proxy. We are also using because we want to be able to depend on all the versions of transitive dependencies being correct. Consuming the Proxy in the Client With those changes in place our application still works, but we haven’t actually used the new proxy yet until we modify the client. Fortunately that’s trivial. We just need to go from this implementation of the “home” controller: angular.module('hello', [ 'ngRoute' ]) ... .controller('home', function($scope, $http) { $http.get('http://localhost:9000/').success(function(data) { $scope.greeting = data; }) }); to a local resource: angular.module('hello', [ 'ngRoute' ]) ... .controller('home', function($scope, $http) { $http.get('resource/').success(function(data) { $scope.greeting = data; }) }); Now when we fire up the servers everything is working and the requests are being proxied through the UI (API Gateway) to the resource server. Further Simplifications Even better: we don’t need the CORS filter any more in the resource server. We threw that one together pretty quickly anyway, and it should have been a red light that we had to do anything as technically focused by hand (especially where it concerns security). Fortunately it is now redundant, so we can just throw it away, and go back to sleeping at night! Securing the Resource Server You might remember in the intermediate state that we started from there is no security in place for the resource server. Aside: Lack of software security might not even be a problem if your network architecture mirrors the application architecture (you can just make the resource server physically inaccessible to anyone but the UI server). As a simple demonstration of that we can make the resource server only accessible on localhost. Just add this to application.properties in the resource server: server.address: 127.0.0.1 Wow, that was easy! Do that with a network address that’s only visible in your data center and you have a security solution that works for all resource servers and all user desktops. Suppose that we decide we do need security at the software level (quite likely for a number of reasons). That’s not going to be a problem, because all we need to do is add Spring Security as a dependency (in the resource server POM): org.springframework.boot spring-boot-starter-security That’s enough to get us a secure resource server, but it won’t get us a working application yet, for the same reason that it didn’t in Part III: there is no shared authentication state between the two servers. Sharing Authentication State We can use the same mechanism to share authentication (and CSRF) state as we did in the last, i.e. Spring Session. We add the dependency to both servers as before: org.springframework.session spring-session 1.0.0.RELEASE org.springframework.boot spring-boot-starter-redis but this time the configuration is much simpler because we can just add the same Filterdeclaration to both. First the UI server (adding @EnableRedisHttpSession): @SpringBootApplication @RestController @EnableZuulProxy @EnableRedisHttpSession public class UiApplication { ... } and then the resource server. There are two changes to make: one is adding@EnableRedisHttpSession and a HeaderHttpSessionStrategy bean to theResourceApplication: @SpringBootApplication @RestController @EnableRedisHttpSession class ResourceApplication { ... @Bean HeaderHttpSessionStrategy sessionStrategy() { new HeaderHttpSessionStrategy(); } } and the other is to explicitly ask for a non-stateless session creation policy inapplication.properties: security.sessions: NEVER As long as redis is still running in the background (use the fig.yml if you like to start it) then the system will work. Load the homepage for the UI at http://localhost:8080 and login and you will see the message from the backend rendered on the homepage. How Does it Work? What is going on behind the scenes now? First we can look at the HTTP requests in the UI server (and API Gateway): VERB PATH STATUS RESPONSE GET / 200 index.html GET /css/angular-bootstrap.css 200 Twitter bootstrap CSS GET /js/angular-bootstrap.js 200 Bootstrap and Angular JS GET /js/hello.js 200 Application logic GET /user 302 Redirect to login page GET /login 200 Whitelabel login page (ignored) GET /resource 302 Redirect to login page GET /login 200 Whitelabel login page (ignored) GET /login.html 200 Angular login form partial POST /login 302 Redirect to home page (ignored) GET /user 200 JSON authenticated user GET /resource 200 (Proxied) JSON greeting That’s identical to the sequence at the end of Part II except for the fact that the cookie names are slightly different (“SESSION” instead of “JSESSIONID”) because we are using Spring Session. But the architecture is different and that last request to “/resource” is special because it was proxied to the resource server. We can see the reverse proxy in action by looking at the “/trace” endpoint in the UI server (from Spring Boot Actuator, which we added with the Spring Cloud dependencies). Go tohttp://localhost:8080/trace in a browser and scroll to the end (if you don’t have one already get a JSON plugin for your browser to make it nice and readable). You will need to authenticate with HTTP Basic (browser popup), but the same credentials are valid as for your login form. At or near the end you should see a pair of requests something like this: { "timestamp": 1420558194546, "info": { "method": "GET", "path": "/", "query": "" "remote": true, "proxy": "resource", "headers": { "request": { "accept": "application/json, text/plain, */*", "x-xsrf-token": "542c7005-309c-4f50-8a1d-d6c74afe8260", "cookie": "SESSION=c18846b5-f805-4679-9820-cd13bd83be67; XSRF-TOKEN=542c7005-309c-4f50-8a1d-d6c74afe8260", "x-forwarded-prefix": "/resource", "x-forwarded-host": "localhost:8080" }, "response": { "Content-Type": "application/json;charset=UTF-8", "status": "200" } }, } }, { "timestamp": 1420558200232, "info": { "method": "GET", "path": "/resource/", "headers": { "request": { "host": "localhost:8080", "accept": "application/json, text/plain, */*", "x-xsrf-token": "542c7005-309c-4f50-8a1d-d6c74afe8260", "cookie": "SESSION=c18846b5-f805-4679-9820-cd13bd83be67; XSRF-TOKEN=542c7005-309c-4f50-8a1d-d6c74afe8260" }, "response": { "Content-Type": "application/json;charset=UTF-8", "status": "200" } } } }, The second entry there is the request from the client to the gateway on “/resource” and you can see the cookies (added by the browser) and the CSRF header (added by Angular as discussed inPart II). The first entry has remote: true and that means it’s tracing the call to the resource server. You can see it went out to a uri path “/” and you can see that (crucially) the cookies and CSRF headers have been sent too. Without Spring Session these headers would be meaningless to the resource server, but the way we have set it up it can now use those headers to re-constitute a session with authentication and CSRF token data. So the request is permitted and we are in business! Conclusion We covered quite a lot in this article but we got to a really nice place where there is a minimal amount of boilerplate code in our two servers, they are both nicely secure and the user experience isn’t compromised. That alone would be a reason to use the API Gateway pattern, but really we have only scratched the surface of what that might be used for (Netflix uses it for a lot of things). Read up on Spring Cloud to find out more on how to make it easy to add more features to the gateway. The next article in this series will extend the application architecture a bit by extracting the authentication responsibilities to a separate server (the Single Sign On pattern).

I think living in a beautiful city in a fantastic climate has its advantages. Not just the obvious ones, but we find people unusually keen to come and visit us on the pretence of presenting at the Sevilla Java User Group (and please, DO come and present at our JUG, welove visitors). This week we were really lucky, we had Georges Saab and Aurelio Garcia-Ribeyro giving us an update on where Java is now and where it looks like it’s going in the future. I’m just starting to use Java 8 in real life, so this could not have been better timed - I got to ask the guys a bunch of questions about the intentions behind some of the Java 8 features, and the current vision for the future. 2015 Java update and roadmap, JUG sevilla from Georges Saab and Aurelio Garcia-Ribeyro My notes from the session: Lambdas could be just a syntax change, but they could be more than that - they could impact the language, the libraries and the JVM. They could have a positive impact on performance, and this work can continue to go on through small updates to Java that don’t impact the syntax. Streams are a pipeline of operations, made possible/easier/more readable by lambdas. The aim is to make operations on collections easier and more readable. In the Old World Order, you had to care about how to perform certain operations. With streams, you don’t need to tell the computer exactly how it’s done, you can simply say what operations you want performed. This makes it easier for developers Streams will take all the operations you pass in and perform them in a single pass of the data, so you don’t have to write multiple loops to perform multiple operations on the same data structure, or tie your brain in knots figuring out how to do it in one loop. There are also no intermediate data structures when you use streams. The implementation can be optimised under the covers (e.g. not performing the sort operation if the data is already ordered correctly), and the developer doesn’t have to worry about it. Java can introduce further optimisations in later releases without changing the API or impacting the code a developer has already written. These new features in Java have a focus on readability, since code is much more often read than written. The operations are easier to parallelise, because the developer is no longer dictating the how - multiple for loops might not be easy to parallelise, but a series of operations can be. Default methods and new support for static methods on interfacesare interesting. I’d forgotten you could put static methods on interfaces and I’m going to sneak them into my latest project. Nashorn is here to replace Rhino. Personally I haven’t worked in the sort of environment that would need server-side JavaScript so this whole area has passed me by somewhat, but seems it might be interesting for Node.js or creating a REPL in JavaScript that you want to run on the JVM. The additional annotation support in Java 8 will be useful for Java EE. As this is something I’m currently playing with (specifically web sockets) I’m interested in this, but it seems like it will be a while before this filters into the Java EE that’s used on a daily basis. Mission Control and Flight Recorder - look interesting. Feel like I should play with them. Many people are skipping straight from Java 6 to 8 - the new language features and improved performance are major driving factors End of public updates of Java 7 in April. Having libraries that, um…encourage… adoption of the latest version of Java makes life a lot easier for those who develop the Java language, as they can concentrate on moving the language forward and not be tied down supporting old versions. Either this is the first time I’ve heard of JavaDB, or my memory has completely discarded it. I had no idea what it was. Java 9 is well under way, check out the JEPs. (This is the JEP process) Jigsaw was explained, and actually I could see myself using it for the project I’m working on right now. I had a look to see if I could use it via the OpenJDK, but it looks like the groundwork is there, but not the actual modules themselves. The G1 Garbage Collector is “…the go forward GC”, it’s the one that’s being actively worked on. This is the first I’ve heard of Enhanced Volatiles, I’m so behind the times! Access to internal packages is going away in Java 9. So don’t use any sun.* packages. Use jdeps to identify any dependencies in your code that need to change. …and, looking further ahead than Java 9, we have value types andProject Valhalla …a REPL for Java …possibly a lightweight JSON API …and VarHandles were also mentioned. Finally, the guys mentioned a talk by Brian Goetz called “Stewardship: the Sobering Parts”, which has gone onto my to-watch list. Ideas It became clear throughout the talk there are plenty of ideas that we could explore in later presentations. If you want to see any of the following, add a comment or ping me or IsraKaos on twitter or Meetup and we’ll try and schedule it. Similarly, if you can present on any of these topics and want to come to a beautiful, sunny city with amazing food to do so, drop me a line: The OpenJDK The JCP, the purpose, the processes, the people Adopt a JSR, Adopt OpenJDK New Date/Time (JSR310) JavaFX Code optimisation vs Data optimisation (I honestly don’t know what this means, but I wrote it down in my notes) Java EE Further Reading I really liked Richard Warburton’s Lambdas and Streams book Java 8 in Action has details on other Java 8 features like Date and Time Java 8 for the Really Impatient covers JavaFX too, and highlights some Java 7 features you might like Brian Goetz did a great talk last year, “Lambdas in Java: A peek under the hood”. I had to watch it twice before even half of the info sank in, but it’s really interesting. Stephen Colebourne, the guy behind Joda time and the new Date and Time API, has this talk about the new API. Java 9 OpenJDK page

This blog post explains the essential algorithms for the well-known Windows game "Minesweeper." Game Rules The board is a two-dimensional space, which has a predetermined number of mines. Cells have two states, opened and closed. If you left-click on a closed cell: Cell is empty and opened. If neighbor cell(s) have mine(s), this opened cell shows neighbor mine count. If neighbor cells have no mines, all neighbor cells are opened automatically. Cell has a mine, game ends with FAIL. If you right-click on a closed cell, you put a flag which shows that "I know this cell has a mine". If you multi-click (both right and left click) on a cell which is opened and has at least one mine on its neighbors: If neighbor cells' total flag count equals to this multi-clicked cell's count and predicted mine locations are true, all closed and unflagged neighbor cells are opened automatically. If neighbor cells' total flag count equals to this multi-clicked cell's count and at least one predicted mine location is wrong, game ends with FAIL. If all cells (without mines) are opened using left clicks and/or multi-clicks, game ends with SUCCESS. Data Structures We may think of each cell as a UI structure (e.g. button), which has the following attributes: colCoord = 0 to colCount rowCoord = 0 to rowCount isOpened = true / false (default false) hasFlag = true / false (default false) hasMine = true / false (default false) neighborMineCount 0 to 8 (default 0, total count of mines on neighbor cells) So, we have a two-dimensional "Button[][] cells" data structure to handle game actions. Algorithms Before Start: Assign mines to cells randomly (set hasMine=true) . Calculate neighborMineCount values for each cell, which have hasMine=false. (This step may be done for each clicked cell while game continues but it may be inefficient.) Note 1: Neighbor cells should be accessed with the coordinates: {(colCoord-1, rowCoord-1),(colCoord-1, rowCoord),(colCoord-1, rowCoord+1),(colCoord, rowCoord-1),(colCoord, rowCoord+1),(colCoord+1, rowCoord-1),(colCoord+1, rowCoord),(colCoord+1, rowCoord+1)} And don't forget that neighbor cell counts may be 3 (for corner cells), 5 (for edge cells) or 8 (for middle cells). Note 2: It's recommended to handle mouse clicks with "mouse release" actions instead of "mouse pressed/click" actions, otherwise a left or right click may be understood as a multi-click or vice versa. Right Click on a Cell: If cell isOpened=true, do nothing. If cell isOpened=false, set cell hasFlag=true and show a flag on the cell. Left Click on a Cell: If cell isOpened=true, do nothing. If cell isOpened=false: If cell hasMine=true, game over. If cell hasMine=false: If cell has neighborMineCount > 0, set isOpened=true, show neighborMineCount on the cell. If all cells which hasMine=false are opened, end game with SUCCESS. If cell has neighborMineCount == 0, set isOpened=true, call Left Click on a Cell for all neighbor cells, which hasFlag=false and isOpened=false. Note: The last step may be implemented with a recursive call or by using a stacked data structure. Multi Click (both Left and Right Click) on a Cell: If cell isOpened=false, do nothing. If cell isOpened=true: If cell neighborMineCount == 0, no nothing. If cell neighborMineCount > 0: If cell neighborMineCount != "neighbor hasFlag=true cell count", do nothing. If cell neighborMineCount == "neighbor hasFlag=true cell count": If all neighbor hasFlag=true cells are not hasMine=true, game over. If all neighbor hasFlag=true cells are hasMine=true (every flag is put on correct cell), call Left Click on a Cell for all neighbor cells, which hasFlag=false and isOpened=false. Note: The last step may be implemented with a recursive call or by using a stacked data structure.

Originally Written by Mat Keep For the better part of a generation, the database landscape had changed very little. No one could say “this is not your father’s database.” They had become, in a word, boring. Then a combination of factors catalyzed an era of innovation in database technologies: cheap storage and compute resources; pervasive connectivity; social networks; smartphones; the proliferation of sensors; open source software. Data volumes grew (and are growing) at exponential rates. Over 80% of today’s data no longer fits neatly into the normalized row and column table formats of the past. And so developers began engineering solutions to a new set of problems with a very different set of resources and assumptions. Today these new options include a variety of database architectures built around diverse data models – from key-value to document to wide-column and graph. And of course you still have the option of the venerable relational database. For the enterprise these new technologies hold great promise. They open the door to new applications that could not be imagined before, or to more efficiently solve existing problems. They attract new technical talent. They facilitate the migration of systems to more cost effective infrastructure based on commodity hardware and cloud platforms. But at the same time, evaluation of these new options requires careful consideration. Selecting the appropriate database for a new project requires evaluation against multiple criteria, including: Development considerations: includes the data model, query functionality, available drivers, data consistency. These factors dictate the functionality of your application, and how quickly you can build it. Operational considerations: performance and scalability, high availability, data center awareness, security, management and backups. Over the application’s lifetime, operational costs will contribute a significant percentage to the project’s Total Cost of Ownership (TCO), and so these factors constitute your ability to meet SLAs while minimizing administrative overhead. Commercial considerations: licensing, pricing and support. You need to know that the database you choose is available in a way that is aligned with how you do business. Each these considerations need to be evaluated in context of specific application requirements as well as internal technology standards, skills availability and integration with your existing enterprise architecture. So, where to start? The Database Selection Matrix is designed to serve as a decision framework by teams responsible for database selection. It has been developed in collaboration with several large enterprises who have the choice of running multiple databases in production, and who wanted to institute a systematic methodology for database evaluation. Responses to questions in the matrix helped them identify key requirements and guide selection. And it can do the same for you. Lets illustrate how the Database Selection Matrix can be used by working through a practical example. The Database Selection Matrix in Action! ACME Retail Corporation runs a large vehicle fleet to distribute produce to its nationwide network of stores. The CEO is intent on improving distribution efficiency and so tasks her enterprise architects to build a new platform that can utilize sensor data generated by the company’s trucks. By capturing and analyzing this data, the organization believes it can optimize route planning, improve delivery times, cut wastage and reduce business interruptions caused by breakdowns. ACME Retail Corp is typical of many enterprises that see the opportunity to unlock new efficiencies by leveraging the “Internet of Things”. As Morgan Stanley stated in the “Internet of Things is Now” research “We do not believe traditional data storage architectures are well- suited to accommodate the volume, velocity, and variety of IoT data”. For this reason, enterprises are looking beyond traditional RDBMS technology to the swathe of new database options available to them. Bosch SI did exactly this when it took the decision to use MongoDB to power the Bosch IoT Suite. Of course, MongoDB may not be a perfect fit for every IoT project. There are many choices available – as there for every new type of project – and the ACME architecture group needs a way to navigate the complex landscape of modern databases. Using the Database Selection Matrix, they have the framework to ask the key questions that will guide their technology decisions. So lets put it into practice. Development Considerations In this opening phase, the architects need to evaluate how their shortlisted database options meet the functional requirements of the app that is being built. This is impacted directly by multiple factors – and these are the questions they will need to ask. The Data Model: Will the application need to handle data of varying structure and types? How large can each data type be – is our data made up of simple integers, strings and timestamps or can it also be large binary files such as images or videos? Can our data just be represented as a set of opaque values, or does it need to be typed so other applications can make sense of it? Do we know the data structure will remain constant, or will it vary as we introduce new sensor data and as the business updates application requirements? Does the application require its data to be strongly consistent (i.e. read our own writes), or can eventually consistent data be tolerated (and do our developers know how to handle the complexity it introduces?). Do we end up trading performance and availability if we configure the database to only return the freshest data? The Query Model: What sort of queries are we going to run against the database? Is it simple key-value lookups that we know in advance or do we need to execute ad-hoc queries and complex aggregations to support real-time analytics that the business wants to see? Can we run analytics directly against the database, or do we need to replicate data to dedicated search or analytics engines? Will the application be handling geospatial queries and text search? Does the data need to be integrated with our BI & analytics tools, and what about our new Hadoop cluster, or the data warehouse? Which languages will our engineers be using to develop the application, and does the database have drivers available for them? Operational Considerations In this second phase, the ACME Retail architects need to evaluate how each database would run in production. No-one wants to hand-feed a custom technology, so they need to understand if the database can meet the availability, scalability and security needs of the business, and interoperate with the existing management frameworks. Service Availability: What is the application’s availability SLA? What are our RTO and RPO objectives? Will our operations teams manage failure recovery, or is this something that should be fully automated by the database? What capabilities does the database offer to maintain availability during routine maintenance? Are there tools available to manage this or do we need to script something ourselves? Are there specific requirements to replicate data between our data centers to support disaster recovery? Scalability: How do we expect this application to grow? Will the database need to scale beyond the limits of just a few servers? If data is to be distributed across multiple nodes, will it be partitioned in such a way that it is still optimized for the application’s query patterns? Do we need to scale this across data centers? Can we write and read data locally to reduce the effects of geographic latency? Can we scale storage capacity and I/O by compressing the data, and are different compression algorithms available to optimize compression ratio to CPU overhead? Security: What types of data access control do we need? Can we just use authentication controls within the database or do we need to integrate with our existing LDAP infrastructure? What type of authorization controls are available, and how granular can we get? Do these controls needs to extend down to the level of individual attributes within a document? Is encryption needed, and will those pesky compliance officers need to audit every action taken against the database? Administration: How are going to run this thing? Does the database provide tools to automate provisioning and upgrades or do we need to create our own scripts? How about backups? Can we get incremental backups. How about point in time backups? And then monitoring. We need to know, for example, if disk utilization is peaking above 60% so we can take action before we hit a problem. Can we add these alerts into our existing operational workflow tools? Can we integrate the database’s management platform into our own operational tooling so we don’t need to leave our single screen? Commercial Considerations Once the ACME architects have profiled their technology requirements, they will need to understand how the database is licensed and priced, before legal and procurement come knocking at the door: Licensing: what license is used, and is this acceptable to our legal team? Are commercial licenses available? Support: What support options are open to me? Can I get support SLAs from my vendor, even if I use a community version of their product? What is the SLA I can expect if I do hit an issue? What sort of training is available? Is my only option to send my engineers to public classes, or can we get trained on-demand, at our own pace? What’s Next? The ACME example is designed to illustrate some of the key questions engineering teams need to ask. It is true that the database landscape is more complex than ever. But it needn’t be bewildering – the Database Selection Matrix is designed to help you identify and compare what is most critical as you build your next app, so go ahead and download it now. Looking for additional information about database selection? Learn why organizations choose MongoDB to deliver applications and outcomes that were never previously possible. Download the white paper below: THE VALUE OF DATABASE SELECTION

This tutorial assumes that you have installed the Java EE version of NetBeans 8.02. It is further assumed that you have replaced the default GlassFish server instance in NetBeans with a new instance with its own folder for the domain. This is required for all platforms. See my previous article “Creating a New Instance of GlassFish in NetBeans IDE” The other day I presented to my students the steps necessary to make GlassFish responsible for JDBC connections. As I went through the steps I realized that I needed to record the steps for my students to reference. Here then are these steps. Steps 1 through 4 are required, Step 5 is optional. Step 1a: Manually Adding the MySQL driver to the GlassFish Domain Before we even start NetBeans we must do a bit of preliminary work. With the exception of Derby, GlassFish does not include the MySQL driver or any other driver in its distribution. Go to the MySql Connector/J download site at http://dev.mysql.com/downloads/connector/j/ and download the latest version. I recommend downloading the Platform Independent version. If your OS is Windows download the ZIP archive otherwise download the TAR archive. You are looking for the driver file named mysql-connector-java-5.1.34-bin.jar in the archive. Copy the driver file to the lib folder in the directory where you placed your domain. On my system the folder is located at C:\Users\Ken\personal_domain\lib. If GlassFish is already running then you will have to restart it so that it picks up the new library. Step 1b: Automatically Adding the MySQL driver to the GlassFish Domain NetBeans has a feature that deploys the database driver to the domain’s lib folder if that driver is in NetBeans’ folder of drivers. On my Windows 8.1 system the MySQL driver can be found in C:\Program Files\NetBeans 8.0.2\ide\modules\ext. Start NetBeans and go to the Services tab, expand Servers and right mouse click on your GlassFish Server. Click on Properties and the Servers dialog will appear. On this dialog you will see a check box labelled Enable JDBC Driver Deployment. By default it is checked. NetBeans determines the driver to copy to GlassFish from the file glassfish-resources.xml that we will create in Step 4 of this tutorial. Without this file and if you have not copied the driver into GlassFish manually then GlassFish will not be able to connect to the database. Any code in your web application will not work and all you will likely see are blank pages. Step 1a or Step 1b? I recommend Step 1a and manually add the driver. The reason I prefer this approach is that I can be certain that the most recent driver is in use. As of this writing NetBeans contains version 5.1.23 of the connector but the current version is 5.1.34. If you copy a driver into the lib folder then NetBeans will not replace it with an older driver even if the check box on the Server dialog is checked. NetBeans does not replace a driver if one is already in place. If you need a driver that NetBeans does have a copy of then Step 1b is your only choice. Step 2: Create a Database Connection in NetBeans One feature I have always liked in NetBeans is that it has an interface for working with databases. All that is required is that you create a connection to the database. It also has additional features for managing a MySQL server but we won’t need those. If you have not already started your MySQL DBMS then do that now. I assume that the database you wish to connect to already exists. Go to the Services tab and right mouse click on New Connection. In the next dialog you must choose the database driver you wish to use. It defaults to Java DB (Embedded). Pull down the combobox labeled Driver: and select MySQL (Connector/J driver). Click on Next and you will now see the Customize Connection dialog. Here you can enter the details of the connection. On my system the server is localhost and the database name is Aquarium. Here is what my dialog looks like. Notice the Test Connection button. I have clicked on mine and so I have the message Connection Succeeded. Click on Next. There is nothing to do on this dialog so click on Next. On this last dialog you have the option of assigning a name to the connection. By default it uses the URL but I prefer a more meaningful name. I have used AquariumMySQL. Click on Finish and the connection will appear under Databases. If the icon next to AquariumMySQL has what looks like a crack in it similar to the jdbc:derby connection then this means that a connection to the database could not be made. Verify that the database is running and is accessible. If it is then delete the connection and start over. Having a connection to the database in NetBeans is invaluable. You can interact with the database directly and issue SQL commands. As a MySQL user this means that I do not need to run the MySQL command line program to interact with the database. Step 3: Create a Web Application Project in NetBeans If you have not already done so create a New Project in NetBeans. I require my students to create a New Project in the Maven category of a Web Application project. Click on Next. In this dialog you can give the project a name and a location in your file system. The Artifact Id, Group Id and Version are used by Maven. The final dialog lets you select the application server that your application will use and the version of Java EE that your code must be compliant with. Here is my project ready for the next step. Step 4: Create the GlassFish JDBC Resource For GlassFish to manage your database connection you need to set up two resources, a JDBC Connection Pool and a JDBC Resource. You can create both in one step by creating a GlassFish JDBC Resource because you can create the Connection Pool as part of the same operation. Right mouse click on the project name and select New and then Other … Scroll down the Categories list and select GlassFish. In the File Types list select JDBC Resource. Click on Next. The next dialog is the General Attributes. Click on the radio button for Create New JDBC Connection Pool. In the text field JNDI Name enter a name that is unique for the project. JNDI names for connection resources always begin with jdbc/ followed by a name that starts with a lower case letter. I have used jdbc/myAquarium. Do not prefix the name with java:app/ as some tutorials suggest. An upcoming article will explain why. Click on Next. There is nothing for us to enter on the Properties dialog. Click on Next. On the Choose Database Connection dialog we will give our connection pool a name and select the database connection we created in Step 2. Notice that in the list of available connections you are shown the connection URL and not the name you assigned to it back in Step 2. Click on Next. On the Add Connection Pool Properties dialog you will see the connection URL and the user name and password. We do need to make one change. The resource type shows javax.sql.DataSource and we must change it to javax.sql.ConnectionPoolDataSource. Click on Next. There is nothing we need to change on Add Connection Pool Optional Properties so click on Finish. A new folder has appeared in the Projects view named Other Sources. It contains a sub folder named setup. In this folder is the file glassfish-resources.xml. The glassfish-resources.xml file will contain the following. I have reformatted the file for easier viewing. OPTIONAL Step 5: Configure GlassFish with glassfish-resources.xml The glassfish-resources.xml file, when included in the application’s WAR file in the WEB-INF folder, can configure the resource and pool for the application when it is deployed in GlassFish. When the application is un-deployed the resource and pool are removed. If you want to set up the resource and pool permanently in GlassFish then follow these steps. Go to the Services tab and select Servers and then right mouse click on GlassFish. If GlassFish is not running then click on Start. With the server started click on View Domain Admin Console. Your web browser will now open and show you the GlassFish console. If you assigned a user name and password to the server you will have to enter this information before you see the console. In the Common Tasks tree select Resources. You should now see in the panel adjacent to the tree the following: Click on Add Resources. You should now see: In the Location click on Choose File and locate your glassfish-resources.xml file. Mine is found at D:\NetBeansProjects\GlassFishTutorial\src\main\setup. You should now see: Click on OK. If everything has gone well you should see: The final task in this step is to test if the connection works. In the Common Tasks tree select Resources, JDBC, JDBC Connection Pools and aquariumPool. Click on Ping. You should see: The most common reason for the Ping to fail is that the database driver is not in the domain’s lib folder. Go to Step 1a and manually add the driver. The resources are now visible in NetBeans. Having the resource and pool add to GlassFish permanently will allow other applications to share this same resource and pool. You are now ready to code!

In Groovy we can use the head and tail methods for a long time on Collection objects. With head we get the first element and with tailthe remaining elements of a collection. Since Groovy 2.4 we have a new method init which returns all elements but the last in a collection. In the following example we have a simple list and apply the different methods: def gr8Tech = ['Groovy', 'Grails', 'Spock', 'Gradle', 'Griffon'] // Since Groovy 2.4 we can use the init method. assert gr8Tech.init() == ['Groovy', 'Grails', 'Spock', 'Gradle'] assert gr8Tech.last() == 'Griffon' assert gr8Tech.head() == 'Groovy' assert gr8Tech.tail() == ['Grails', 'Spock', 'Gradle', 'Griffon'] Code written with Groovy 2.4.

Error in wday(date, label = TRUE, abbr = FALSE) : unused arguments (label = TRUE, abbr = FALSE) I spent a couple of hours playing around with data.table this evening and tried changing some code written using a data frame to use a data table instead. I started off by building a data frame which contains all the weekends between 2010 and 2015… > library(lubridate) > library(dplyr) > dates = data.frame(date = seq( dmy("01-01-2010"), to=dmy("01-01-2015"), by="day" )) > dates = dates %>% filter(wday(date, label = TRUE, abbr = FALSE) %in% c("Saturday", "Sunday")) …which works fine: > dates %>% head() date 1: 2010-01-02 2: 2010-01-03 3: 2010-01-09 4: 2010-01-10 5: 2010-01-16 6: 2010-01-17 I then tried to change the code to use a data table instead which led to the following error: > library(data.table) > dates = data.table(date = seq( dmy("01-01-2010"), to=dmy("01-01-2015"), by="day" )) > dates = dates %>% filter(wday(date, label = TRUE, abbr = FALSE) %in% c("Saturday", "Sunday")) Error in wday(date, label = TRUE, abbr = FALSE) : unused arguments (label = TRUE, abbr = FALSE) I wasn’t sure what was going on so I went back to the data frame version to check if that still worked… > dates = data.frame(date = seq( dmy("01-01-2010"), to=dmy("01-01-2015"), by="day" )) > dates = dates %>% filter(wday(date, label = TRUE, abbr = FALSE) %in% c("Saturday", "Sunday")) Error in wday(c(1262304000, 1262390400, 1262476800, 1262563200, 1262649600, : unused arguments (label = TRUE, abbr = FALSE) …except it now didn’t work either! I decided to check what wday was referring to… Help on topic ‘wday’ was found in the following packages: Integer based date class (in package data.table in library /Library/Frameworks/R.framework/Versions/3.1/Resources/library) Get/set days component of a date-time. (in package lubridate in library /Library/Frameworks/R.framework/Versions/3.1/Resources/library) …and realised that data.table has its own wday function – I’d been caught out by R’s global scoping of all the things! We can probably work around that by the order in which we require the various libraries but for now I’m just prefixing the call to wday and all is well: dates = dates %>% filter(lubridate::wday(date, label = TRUE, abbr = FALSE) %in% c("Saturday", "Sunday"))

I am really interested in Computer Vision technology, so I started to dig deeper in this topic. This is how I found the code below for edge detection, a method belonging to object detection. If you are interested in implementing edge detection in C#, too, here you can find the code I tried. The code is from a prewritten C# camera library you can all access. To develop the edge detection function you only need to have a Visual C# WPF Application created in Visual Studio and the VOIPSDK.dll and NVA.dll files (from www.camera-sdk.com ) added to the references. Creating the user interface is the first step. It will help you to use edge detection by providing an easy-to-use interface. You will have two fields to display the original image and the processed image of the camera, you can set values for Canny Threshold and Canny Threshold Linking and you can set whether you want the edges of the detected elements to be white or colorized. You can find the code of the GUI under Form1.Designer.cs. Under Form1.cs there is the code for the edge detection function. You can see how to code is built up and what you should to create this function. There will be the different methods you have to call and all the configurations are described. Trust me, guys, this source code will help you a lot, it made my life easier. Good luck! // Form1.Designer.cs namespace EdgeDetection { partial class Form1 { /// /// Required designer variable. /// private System.ComponentModel.IContainer components = null; /// /// Clean up any resources being used. /// /// true if managed resources should be disposed; otherwise, false. protected override void Dispose(bool disposing) { if (disposing && (components != null)) { components.Dispose(); } base.Dispose(disposing); } #region Windows Form Designer generated code /// /// Required method for Designer support - do not modify /// the contents of this method with the code editor. /// private void InitializeComponent() { this.label1 = new System.Windows.Forms.Label(); this.label2 = new System.Windows.Forms.Label(); this.btn_Set = new System.Windows.Forms.Button(); this.tb_CannyThreshold = new System.Windows.Forms.TextBox(); this.groupBox1 = new System.Windows.Forms.GroupBox(); this.chk_Colorized = new System.Windows.Forms.CheckBox(); this.label3 = new System.Windows.Forms.Label(); this.tb_CannyThresholdLinking = new System.Windows.Forms.TextBox(); this.label4 = new System.Windows.Forms.Label(); this.groupBox1.SuspendLayout(); this.SuspendLayout(); // // label1 // this.label1.AutoSize = true; this.label1.Font = new System.Drawing.Font("Microsoft Sans Serif", 8.25F, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, ((byte)(238))); this.label1.Location = new System.Drawing.Point(30, 265); this.label1.Name = "label1"; this.label1.Size = new System.Drawing.Size(87, 13); this.label1.TabIndex = 0; this.label1.Text = "Original image"; // // label2 // this.label2.AutoSize = true; this.label2.Font = new System.Drawing.Font("Microsoft Sans Serif", 8.25F, System.Drawing.FontStyle.Bold, System.Drawing.GraphicsUnit.Point, ((byte)(238))); this.label2.Location = new System.Drawing.Point(370, 265); this.label2.Name = "label2"; this.label2.Size = new System.Drawing.Size(103, 13); this.label2.TabIndex = 1; this.label2.Text = "Processed image"; // // btn_Set // this.btn_Set.Location = new System.Drawing.Point(182, 188); this.btn_Set.Name = "btn_Set"; this.btn_Set.Size = new System.Drawing.Size(58, 23); this.btn_Set.TabIndex = 2; this.btn_Set.Text = "Set"; this.btn_Set.UseVisualStyleBackColor = true; this.btn_Set.Click += new System.EventHandler(this.btn_Set_Click); // // tb_CannyThreshold // this.tb_CannyThreshold.Location = new System.Drawing.Point(153, 31); this.tb_CannyThreshold.Name = "tb_CannyThreshold"; this.tb_CannyThreshold.Size = new System.Drawing.Size(87, 20); this.tb_CannyThreshold.TabIndex = 4; // // groupBox1 // this.groupBox1.Controls.Add(this.chk_Colorized); this.groupBox1.Controls.Add(this.label3); this.groupBox1.Controls.Add(this.tb_CannyThresholdLinking); this.groupBox1.Controls.Add(this.label4); this.groupBox1.Controls.Add(this.btn_Set); this.groupBox1.Controls.Add(this.tb_CannyThreshold); this.groupBox1.Location = new System.Drawing.Point(677, 12); this.groupBox1.Name = "groupBox1"; this.groupBox1.Size = new System.Drawing.Size(258, 230); this.groupBox1.TabIndex = 12; this.groupBox1.TabStop = false; this.groupBox1.Text = "Settings"; // // chk_Colorized // this.chk_Colorized.AutoSize = true; this.chk_Colorized.CheckAlign = System.Drawing.ContentAlignment.MiddleRight; this.chk_Colorized.Location = new System.Drawing.Point(98, 115); this.chk_Colorized.Name = "chk_Colorized"; this.chk_Colorized.Size = new System.Drawing.Size(69, 17); this.chk_Colorized.TabIndex = 15; this.chk_Colorized.Text = "Colorized"; this.chk_Colorized.UseVisualStyleBackColor = true; // // label3 // this.label3.AutoSize = true; this.label3.Location = new System.Drawing.Point(27, 76); this.label3.Name = "label3"; this.label3.Size = new System.Drawing.Size(121, 13); this.label3.TabIndex = 14; this.label3.Text = "CannyThresholdLinking:"; // // tb_CannyThresholdLinking // this.tb_CannyThresholdLinking.Location = new System.Drawing.Point(153, 73); this.tb_CannyThresholdLinking.Name = "tb_CannyThresholdLinking"; this.tb_CannyThresholdLinking.Size = new System.Drawing.Size(87, 20); this.tb_CannyThresholdLinking.TabIndex = 13; // // label4 // this.label4.AutoSize = true; this.label4.Location = new System.Drawing.Point(61, 34); this.label4.Name = "label4"; this.label4.Size = new System.Drawing.Size(87, 13); this.label4.TabIndex = 11; this.label4.Text = "CannyThreshold:"; // // MainForm // this.AutoScaleDimensions = new System.Drawing.SizeF(6F, 13F); this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font; this.ClientSize = new System.Drawing.Size(947, 307); this.Controls.Add(this.groupBox1); this.Controls.Add(this.label2); this.Controls.Add(this.label1); this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.FixedSingle; this.MaximizeBox = false; this.Name = "MainForm"; this.Text = "Edge Detection"; this.Load += new System.EventHandler(this.MainForm_Load); this.groupBox1.ResumeLayout(false); this.groupBox1.PerformLayout(); this.ResumeLayout(false); this.PerformLayout(); } #endregion private System.Windows.Forms.Label label1; private System.Windows.Forms.Label label2; private System.Windows.Forms.Button btn_Set; private System.Windows.Forms.TextBox tb_CannyThreshold; private System.Windows.Forms.GroupBox groupBox1; private System.Windows.Forms.Label label4; private System.Windows.Forms.Label label3; private System.Windows.Forms.TextBox tb_CannyThresholdLinking; private System.Windows.Forms.CheckBox chk_Colorized; } } // Form1.cs using System; using System.Drawing; using System.Windows.Forms; using Ozeki.Media.MediaHandlers; using Ozeki.Media.MediaHandlers.Video; using Ozeki.Media.MediaHandlers.Video.CV; using Ozeki.Media.MediaHandlers.Video.CV.Processer; using Ozeki.Media.Video.Controls; namespace EdgeDetection { public partial class Form1 : Form { WebCamera _webCamera; MediaConnector _connector; ImageProcesserHandler _imageProcesserHandler; IEdgeDetector _edgeDetector; FrameCapture _frameCapture; VideoViewerWF _originalView; VideoViewerWF _processedView; DrawingImageProvider _originalImageProvider; DrawingImageProvider _processedImageProvider; public Form1() { InitializeComponent(); } void MainForm_Load(object sender, EventArgs e) { Init(); SetVideoViewers(); InitDetectorFields(); ConnectWebcam(); Start(); } void Init() { _frameCapture = new FrameCapture(); _frameCapture.SetInterval(5); _webCamera = WebCamera.GetDefaultDevice(); _connector = new MediaConnector(); _originalImageProvider = new DrawingImageProvider(); _processedImageProvider = new DrawingImageProvider(); _edgeDetector = ImageProcesserFactory.CreateEdgeDetector(); _imageProcesserHandler = new ImageProcesserHandler(); _imageProcesserHandler.AddProcesser(_edgeDetector); } void SetVideoViewers() { _originalView = new VideoViewerWF { BackColor = Color.Black, Location = new Point(10, 20), Size = new Size(320, 240) }; _originalView.SetImageProvider(_originalImageProvider); Controls.Add(_originalView); _processedView = new VideoViewerWF { BackColor = Color.Black, Location = new Point(350, 20), Size = new Size(320, 240) }; _processedView.SetImageProvider(_processedImageProvider); Controls.Add(_processedView); } void InitDetectorFields() { InvokeGUIThread(() => { tb_CannyThreshold.Text = _edgeDetector.CannyThreshold.ToString(); tb_CannyThresholdLinking.Text = _edgeDetector.CannyThresholdLinking.ToString(); chk_Colorized.Checked = _edgeDetector.Colorized; }); } void ConnectWebcam() { _connector.Connect(_webCamera, _originalImageProvider); _connector.Connect(_webCamera, _frameCapture); _connector.Connect(_frameCapture, _imageProcesserHandler); _connector.Connect(_imageProcesserHandler, _processedImageProvider); } void Start() { _originalView.Start(); _processedView.Start(); _frameCapture.Start(); _webCamera.Start(); } void btn_Set_Click(object sender, EventArgs e) { InvokeGUIThread(() => { _edgeDetector.CannyThreshold = Double.Parse(tb_CannyThreshold.Text); _edgeDetector.CannyThresholdLinking = Double.Parse(tb_CannyThresholdLinking.Text); _edgeDetector.Colorized = chk_Colorized.Checked; }); } void InvokeGUIThread(Action action) { BeginInvoke(action); } } }

SOAP web services are not cutting edge technology by any means – although it still has it’s place, REST based web services are offering tough competition. Anyway – this is definitely not a REST vs SOAP post ! I have observed a few instances where Java based SOAP web services have been used in an less than ideal manner to say the least. I think this stems from a lack of understanding around some of the basics of JAX-WS (Java EE specification for SOAP based Web Services) in general. What’s mentioned in this post is pretty basic stuff related to SOAP based web services built using JAX-WS. Some of the points discussed are what’s the life cycle of a @WebService annotated POJO ? is it thread safe? what happens if concurrent client requests are fired at your web service ? The @WebService annotation Technically speaking, the @WebService annotation is all you need to turn a POJO into a SOAP endpoint. Not surprisingly enough, that’s all we generally do – annotate our class with @WebService and some other helper annotations like @WebMethod, @WebParam etc, deploy the WAR, fire up SoapUI, run a few tests and bask in glory ! Things you should know about POJOs annotated with @WebService A POJO annotated with @WebService deployed in a WAR is served by the Web Container (this is significant) Life cycle – a single instance of the POJO serves requests from the client. Pretty much like Servlets. Concurrency aspect (thread safety) – they are not thread safe. The same instance of the bean can be concurrently accessed by multiple threads. Although this is not a problem if your service is stateless i.e. does not use instance variables to store state – you might still face scalability issues though (after all, its just one instance !). If your POJO uses instance variables to store state, then you are in big soup and will definitely face issues w.r.t inconsistent behavior resulting from concurrent threads accessing a single instance of your web service class. // is this robust enough ? @WebService public class POJO_WS{ @WebMethod public String getDate(){ System.out.println("hashCode -- "+ this.hashCode()); return new Date().toString(); } } Ideally speaking . . . one should make the web services stateless – fire and forget style. Don’t end up storing state inside instance variables if you do choose to use instance variables – make sure that you as a developer, code your web service in a thread safe manner. There are multiple options here, some of which include using the good old synchronized (far from ideal though!), thread safe collections (ConcurrentHashMap) etc best solution IMO – if you are using a Java EE compliant application server (e.g. Weblogic), you should invariably deploy your web services as an EJB (I am not going to dive into the details of EJBs here ! You can refer to my previous posts if interested). What will you gain by that ? (1) EJBs are thread safe by default. You need not worry about coding concurrency and thread safety as a part of your business logic – you get that for free ! (2) EJBs are pooled components – The container caches instances in memory and allocates them to clients as per request. Scalability for free(note – EJB pooling configurations are container specific and each server defines a specific manner in which to achieve this) (3) EJBs are transnational by default – in case you are accessing back end databases as a part of your web service logic, EJBs are ideal (details of transactions are best dealt by a guy who really understands them in depth! I am not going to embarrass myself by trying to act as if I know them end to end) How do I ‘pump-up’ my web service ? (1) Just use the @Stateless annotation – this turns your mere POJO into a full fledged EJB which can now enjoy all the container services (2) deploy your web service not as a WAR, but as an EJB-JAR packed within an EAR. This will ensure that the EJB container catches hold of your POJO and weaves all the magic I have been bragging about! //not perfect - but better than just @WebService //will recieve free services from the EJB container, courtsey @Stateless ! @Stateless @WebService public class POJO_EJB_and_SOAP { public String fetchDate(){ System.out.println("hashCode -- "+ this.hashCode()); return new Date().toString(); } } Testing I am not a testing expert – but tools like JMeter can make me look smart! Do yourself a favor and user JMeter to ease your SOAP web service testing process. It’s not that hard. Trivial example below Client perspective As far as generating stubs from an existing WSDL is concerned, I would definitely opt for the standard capability within Java SE itself. I am simply stating this because this has worked flawlessly for me in the past instead of trying out other implementations like Axis 2 or Apache CXF I don’t mean to undermine them but I don’t see the value in wasting time looking into other stuff when the JDK itself has a well documented standard tool ! Just hop over toJAVA_HOME/bin, look for the wsimport command and get cracking. Most of the IDEs which provide stub generation capability leverage this very tool This was just a quick rant of sorts..! Hope it made sense Cheers!