An overview starting with some basic classes of the Java 8 package: Instant, LocalDate, LocalTime, and LocalDateTime.

Fake system clock is a design pattern addressing testability issues of programs heavily relying on system time. If business logic flow depends on current system time, testing various flows becomes cumbersome or even impossible. Examples of such problematic scenarios include: certain business flow runs only (or is ignored) during weekends some logic is triggered only after an hour since some other event when two events occur at the exact same time (typically 1 ms precision), something should happen … Each scenario above poses unique set of challenges. Taken literally our unit tests would have to run only on specific day (1) or sleep for an hour to observe some behaviour. Scenario (3) might even be impossible to test under some circumstances since system clock can tick 1 millisecond at any time, thus making test unreliable. Fake system clock addresses these issues by abstracting system time over simple interface. Essentially you never call new Date(), new GregorianCalendar() or System.currentTimeMillis() but always rely on this: import org.joda.time.{DateTime, Instant} trait Clock { def now(): Instant def dateNow(): DateTime } As you can see I am depending on Joda Time library. Since we are already in the Scala land, one might consider scala-timeor nscala-time wrappers. Moreover the abstract name Clock is not a coincidence. It’s short and descriptive, but more importantly it mimics java.time.Clock class from Java 8 - that happens to address the same problem discussed here at the JDK level! But since Java 8 is still not here, let’s stay with our sweet and small abstraction. The standard implementation that you would normally use simply delegates to system time: import org.joda.time.{Instant, DateTime} object SystemClock extends Clock { def now() = Instant.now() def dateNow() = DateTime.now() } For the purposes of unit testing we will develop other implementations, but first let’s focus on usage scenarios. In a typical Spring/JavaEE applications fake system clock can be turned into a dependency that the container can easily inject. This makes dependence on system time explicit and manageable, especially in tests: @Controller class FooController @Autowired() (fooService: FooService, clock: Clock) { def postFoo(name: String) = fooService store new Foo(name, clock) } Here I am using Spring constructor injection asking the container to provide some Clock implementation. Of course in this case SystemClock is marked as @Service. In unit tests I can pass fake implementation and in integration tests I can place another, @Primary bean in the context, shadowing the SystemClock. This works great, but becomes painful for certain types of objects, namely entity/DTO beans and utility (static) classes. These are typically not managed by Spring so it can’t inject Clock bean to them. This forces us to pass Clock manually from the last “managed” layer: class Foo(fooName: String, clock: Clock) { val name = fooName val time = clock.dateNow() } similarly: object TimeUtil { def firstFridayOfNextMonth(clock: Clock) = //... } It’s not bad from design perspective. Both Foo constructor and firstFridayOfNextMonth() method do rely on system time so let’s make it explicit. On the other hand Clock dependency must be dragged, sometimes through many layers, just so that it can be used in one single method somewhere. Again, this is not bad per se. If your high level method has Clockparameter you know from the beginning that it relies on current time. But still is seems like a lot of boilerplate and overhead for little gain. Luckily Scala can help us here with: implicit parameters Let us refactor our solution a little bit so that Clock is an implicit parameter: @Controller class FooController(fooService: FooService) { def postFoo(name: String)(implicit clock: Clock) = fooService store new Foo(name) } @Service class FooService(fooRepository: FooRepository) { def store(foo: Foo)(implicit clock: Clock) = fooRepository storeInFuture foo } @Repository class FooRepository { def storeInFuture(foo: Foo)(implicit clock: Clock) = { val friday = TimeUtil.firstFridayOfNextMonth() //... } } object TimeUtil { def firstFridayOfNextMonth()(implicit clock: Clock) = //... } Notice how we call fooRepository storeInFuture foo ignoring second clock parameter. However this alone is not enough. We still have to provide some Clock instance as second parameter, otherwise compilation error strikes: could not find implicit value for parameter clock: com.blogspot.nurkiewicz.foo.Clock controller.postFoo("Abc") ^ not enough arguments for method postFoo: (implicit clock: com.blogspot.nurkiewicz.foo.Clock)Unit. Unspecified value parameter clock. controller.postFoo("Abc") ^ The compiler tried to find implicit value for Clock parameter but failed. However we are really close, the simplest solution is to use package object: package com.blogspot.nurkiewicz.foo package object foo { implicit val clock = SystemClock } Where SystemClock was defined earlier. Here is what happens: every time I call a function with implicit clock: Clock parameter inside com.blogspot.nurkiewicz.foo package, the compiler will discover foo.clock implicit variable and pass it transparently. In other words the following code snippets are equivalent but the second one provides explicit Clock, thus ignoring implicits: TimeUtil.firstFridayOfNextMonth() TimeUtil.firstFridayOfNextMonth()(SystemClock) also equivalent (first form is turned into the second by the compiler): fooService.store(foo) fooService.store(foo)(SystemClock) Interestingly in the bytecode level, implicit parameters aren’t any different from normal parameters so if you want to call such method from Java, passing Clock instance is mandatory and explicit. implicit clock parameter seems to work quite well. It hides ubiquitous dependency while still giving possibility to override it. For example in: fooService.store(foo) fooService.store(foo)(SystemClock) Tests The whole point of abstracting system time was to enable unit testing by gaining full control over time flow. Let us begin with a simple fake system clock implementation that always returns the same, specified time: class FakeClock(fixed: DateTime) extends Clock { def now() = fixed.toInstant def dateNow() = fixed } Of course you are free to put any logic here: advancing time by arbitrary value, speeding it up, etc. You get the idea. Now remember, the reason for implicit parameter was to hide Clock from normal production code while still being able to supply alternative implementation. There are two approaches: either pass FakeClock explicitly in tests: val fakeClock = new FakeClock( new DateTime(2013, 7, 15, 0, 0, DateTimeZone.UTC)) controller.postFoo("Abc")(fakeClock) or make it implicit but more specific to the compiler resolution mechanism: implicit val fakeClock = new FakeClock( new DateTime(2013, 7, 15, 0, 0, DateTimeZone.UTC)) controller.postFoo("Abc") The latter approach is easier to maintain as you don’t have to remember about passing fakeClock to method under test all the time. Of course fakeClock can be defined more globally as a field or even inside test package object. No matter which technique of providing fakeClock we choose, it will be used throughout all calls to service, repository and utilities. The moment we given explicit value to this parameter, implicit parameter resolution is ignored. Problems and summary Solution above to testing systems heavily dependant on time is not free from issues on its own. First of all the implicitClock parameter must be propagated throughout all the layers up to the client code. Notice that Clock is only needed in repository/utility layer while we had to drag it up to the controller layer. It’s not a big deal since the compiler will fill it in for us, but sooner or later most of our methods will include this extra parameter. Also Java and frameworks working on top of our code are not aware of Scala implicit resolution happening at compile time. Therefore e.g. our Spring MVC controller will not work as Spring is not aware of SystemClock implicit variable. It can be worked around though with WebArgumentResolver. Fake system clock pattern in general works only when used consistently. If you have even one place when real time is used directly as opposed to Clock abstraction, good luck in finding test failure reason. This applies equally to libraries and SQL queries. Thus if you are designing a library relying on current time, consider providing pluggable Clock abstraction so that client code can supply custom implementation like FakeClock. In SQL, on the other hand, do not rely on functions likeNOW() but always explicitly provide dates from your code (and thus from custom Clock).

I previously wrote a blog post describing how I’ve been trying to learn more about network sockets in which I created some server sockets and connected to them using netcat. The next step was to do the same thing in Java and I started out by writing a server socket which echoed any messages sent by the client: public class EchoServer { public static void main(String[] args) throws IOException { int port = 4444; ServerSocket serverSocket = new ServerSocket(port, 50, InetAddress.getByAddress(new byte[] {0x7f,0x00,0x00,0x01})); System.err.println("Started server on port " + port); while (true) { Socket clientSocket = serverSocket.accept(); System.err.println("Accepted connection from client: " + clientSocket.getRemoteSocketAddress() ); In in = new In (clientSocket); Out out = new Out(clientSocket); String s; while ((s = in.readLine()) != null) { out.println(s); } System.err.println("Closing connection with client: " + clientSocket.getInetAddress()); out.close(); in.close(); clientSocket.close(); } } } public final class In { private Scanner scanner; public In(java.net.Socket socket) { try { InputStream is = socket.getInputStream(); scanner = new Scanner(new BufferedInputStream(is), "UTF-8"); } catch (IOException ioe) { System.err.println("Could not open " + socket); } } public String readLine() { String line; try { line = scanner.nextLine(); } catch (Exception e) { line = null; } return line; } public void close() { scanner.close(); } } public class Out { private PrintWriter out; public Out(Socket socket) { try { out = new PrintWriter(socket.getOutputStream(), true); } catch (IOException ioe) { ioe.printStackTrace(); } } public void close() { out.close(); } public void println(Object x) { out.println(x); out.flush(); } } I ran the main method of the class and this creates a server socket on port 4444 listening on the 127.0.0.1 interface and we can connect to it using netcat like so: $ nc -v 127.0.0.1 4444 Connection to 127.0.0.1 4444 port [tcp/krb524] succeeded! hello hello The output in my IntelliJ console looked like this: Started server on port 4444 Accepted connection from client: /127.0.0.1:63222 Closing connection with client: /127.0.0.1 Using netcat is fine but what I actually wanted to do was write some test code which would check that I’d made sure the server socket on port 4444 was accessible via all interfaces i.e. bound to 0.0.0.0. There are actually some quite nice classes in Java which make this very easy to do and wiring those together I ended up with the following client code: public static void main(String[] args) throws IOException { Enumeration nets = NetworkInterface.getNetworkInterfaces(); for (NetworkInterface networkInterface : Collections.list(nets)) { for (InetAddress inetAddress : Collections.list(networkInterface.getInetAddresses())) { Socket socket = null; try { socket = new Socket(inetAddress, 4444); System.out.println(String.format("Connected using %s [%s]", networkInterface.getDisplayName(), inetAddress)); } catch (ConnectException ex) { System.out.println(String.format("Failed to connect using %s [%s]", networkInterface.getDisplayName(), inetAddress)); } finally { if (socket != null) { socket.close(); } } } } } } If we run the main method of that class we’ll see the following output (on my machine at least!): Failed to connect using en0 [/fe80:0:0:0:9afe:94ff:fe4f:ee50%4] Failed to connect using en0 [/192.168.1.89] Failed to connect using lo0 [/0:0:0:0:0:0:0:1] Failed to connect using lo0 [/fe80:0:0:0:0:0:0:1%1] Connected using lo0 [/127.0.0.1] Interestingly we can’t even connect via the loopback interface using IPv6 which is perhaps not that surprising in retrospect given we bound using an IPv4 address. If we tweak the second line of EchoServer from: ServerSocket serverSocket = new ServerSocket(port, 50, InetAddress.getByAddress(new byte[] {0x7f,0x00,0x00,0x01})); to ServerSocket serverSocket = new ServerSocket(port, 50, InetAddress.getByAddress(new byte[] {0x00,0x00,0x00,0x00})); And restart the server before re-running the client we can now connect through all interfaces: Connected using en0 [/fe80:0:0:0:9afe:94ff:fe4f:ee50%4] Connected using en0 [/192.168.1.89] Connected using lo0 [/0:0:0:0:0:0:0:1] Connected using lo0 [/fe80:0:0:0:0:0:0:1%1] Connected using lo0 [/127.0.0.1] We can then wrap the EchoClient code into our testing framework to assert that we can connect via all the interfaces.

There are quite a few configuration libraries available in Java, such as this one available from Apache Commons, and they usually follow a very similar pattern: they parse a variety of configuration files and in the end, give you a Property or Map like structure where you can query your values: Double double = config.getDouble("number"); Integer integer = config.getInteger("number"); I have always been unsatisfied with this approach for a couple of reasons: A lot of boiler plate to retrieve these parameters. Having to share the whole configuration object even if I only need one parameter from it. It’s very easy to misspell a property and received incorrect values. A while ago, I was reading the Guice documentation and I came across a paragraph that made me realize that maybe, we could do better. Here is the relevant excerpt: Guice supports binding annotations that have attribute values. In the rare case that you need such an annotation: Create the annotation @interface. Create a class that implements the annotation interface. Follow the guidelines for equals() and hashCode() specified in the Annotation Javadoc. Pass an instance of this to the annotatedWith() binding clause. I thought that using this technique might be exactly what I needed to create a smarter configuration framework, even though I had different plans than using this trick with the annotatedWith method, as suggested by this paragraph. The relevance of this snippet will become clear later, so let’s start with the goals. Objectives I want to: Be able to inject individual configuration values anyhere in my code base and I want this to be type safe. No @Named or other string-based lookup. Have a canonical list of all the properties available to the application, with their full type, default value, documentation and leaving the door open for improvements (e.g. is this option mandatory or optional, detecting when some properties are not used anywhere, deprecation, aliasing, etc…). I don’t care much about the front end: how these properties get gathered is not relevant to this framework, they can come from XML, JSON, the network, a database, and they can have arbitrarily complex resolution and overriding rules, let’s save this for a future post. The input of this framework is a Map of properties and I take it from there. By the time we’re done, we will be able to do something like this: # Some property file host=foo.com port=1234 Using these configuration values in your code: public class A { @Inject @Prop(Property.HOST) private String host; @Inject @Prop(Property.PORT) private Integer port; // ... } Implementation The definition of the Prop annotation is trivial: @Retention(RUNTIME) @Target({ ElementType.FIELD, ElementType.PARAMETER }) @BindingAnnotation public @interface Prop { Property value(); } Property is an enum that captures all the information necessary for all your properties. In our case: public enum Property { HOST("host", "The host name", new TypeLiteral() {}, "foo.com"), PORT("port", "The port", new TypeLiteral() {}, 1234); } This enum contains the string name of the property, a description, its default value and its type. Note that this type is a TypeLiteral, so we can even offer properties that have generic types that would otherwise be erased, a trick that comes in handy to inject caches or other generic collections. Obviously, you can have additional parameters as you see fit (e.g. “boolean deprecated“). The next step is to tie all the properties that we parsed as input — we’ll use a Map called "allProps"— into our module so that Guice knows how to inject them. In order to do this, we iterate all these properties and bind them to their own provider. Because we are using typed names, note the use of Key.get from the Guice API, which lets us specifically target each property with a specific annotation: for (Property prop : Property.values()) { Object value = PropertyConverters.getValue(prop.getType(), prop, allProps.asMap()); binder.bind(Key.get(prop.getType(), new PropImpl(prop))) .toProvider(new PropertyProvider(prop, value)); } There are three classes in this piece of code that I haven’t explained yet. The first one isPropertyConverters, which simply reads the string version of the property and converts it to a Java type. The second one is PropertyProvider, a trivial Guice provider: public class PropertyProvider implements Provider { private final T value; private final Property property; public PropertyProvider(Property property, T value) { this.property = property; this.value = value; } @Override public T get() { return value; } } PropImpl is more tricky and also the one thing that has always prevented me from implementing such a framework, until I came across this obscure tidbit of the Guice documentation quoted above. In order to understand the necessity of its existence, we need to understand how Guice’s Key.get() works. Guice uses this class to translate a type into a unique key that it can use to inject the correct value. The important part here is to notice that not only does this method work with both Class andTypeLiteral (which we are using), but it can also be given a specific annotation. This annotation can be @Named, which I’m not a big fan of because it’s a string, so susceptible to typos, or a real annotation, which is what we want. However, annotations are special beasts in Java and you can’t get an instance of them just like that. This is where the trick mentioned at the top of this article comes into play: Java actually allows you to implement an annotation with a regular class. The implementation turns out to be fairly trivial, the difficulty was realizing that this was possible at all. Now that we have all this in place, let’s back track and dissect how the magic happens: @Inject @Prop(Property.HOST) private String host; When Guice encounters this injection point, it looks into its binders and it finds multiple bindings forStrings. However, because they have all been bound with a Key, the key is actually a pair: (String, a Prop). In this case, it will look up the pair String, Property.HOST and it will find a provider there. This provider was instantiated with the value found in the property file, so it knows what value to return. Generalizing Once I had the basic logic in place, I wondered if I could turn this mini framework into a library so that others could use it. The only missing piece would be to allow the specification of a more general Propannotation. In the example above, this annotation has a value of type Property, which is specific to my application: @Retention(RUNTIME) @Target({ ElementType.FIELD, ElementType.PARAMETER }) @BindingAnnotation public @interface Prop { Property value(); } In order to make this more general, I need to make this attribute return an enum instead of my own: @Retention(RUNTIME) @Target({ ElementType.FIELD, ElementType.PARAMETER }) @BindingAnnotation public @interface Prop { Enum value(); } Unfortunately, this is not legal Java, because according to the JLS section 8.9, Enum and its generic variants are not enum types, something that Josh Bloch confirmed, to my consternation. Therefore, this cannot be turned into a library, so if you are interested in using it in your project, you will have to copy the source and make a few modifications to adjust it to your needs, starting by havingProp#value have the type of the enum that captures your configuration. You can find a small proof of concept here, which I hope you’ll find useful. Note: this is a copy of the article I posted on our work blog.

A question every customer asks me is: How can you manage and monitor integration routes implemented with Apache Camel (http://camel.apache.org/) and / or Talend ESB (http://en.talend.com/products/esb) (which is based on Apache Camel and also available as open source version)? This blog post will show different alternatives to answer this question. The good news first: As Apache Camel and Talend ESB are based on open standards, you can use your own frameworks and tools if tooling of the product is not sufficient. So, I will not talk just about features of Apache Camel or Talend ESB, but also about additional options. Except for Talend Administration Center (user interface on top of Talend ESB’s service monitoring and clustering features), all tools are open source. Talend Administration Center is only available in Talend’s enterprise editions. Management of Apache Camel and Talend ESB Let’s begin with management of Apache Camel and Talend ESB routes. I define management as “controlling server instances, services and integration routes”. Besides Talend Administration Center, a Talend-specific web application, several other options exist. I will show jconsole and hawtio. However, as Apache Camel and Talend ESB are standards-based, you can use any other management tool, which supports the Java Management Extensions (JMX) standard, e.g. Hyperic, Nagios or IBM Tivoli. Talend Administration Center Talend Administration Center (http://www.talendforge.org/tutorials/tutorial.php?idTuto=54) is a web application to configure and monitor different server instances. Besides, you can install, start and stop Camel routes and SOAP / REST web services. Provisioning (i.e. deploying and managing routes and services on different server instances) can be automated easily because Talend ESB container supports Apache Karaf Cellar, an OSGi addon which is built exactly for this reason. Therefore, you can create so-called “virtual servers” within Talend Administration Center. Service locator is another feature, which is based on Apache Zookeeper to implement load balancing and high availability under the hood. Administrators can monitor the state of server instances, Camel routes and REST / SOAP web services within Talend Administration Center. Since Talend ESB 5.3, Talend Administration Center contains other important enterprise features, especially management of Talend’s new service registry (based on Apache Jackrabbit) for service discovery and policy enforcement, and its new identity management (based on Apache Syncope) for authorization. Let’s now talk about two other alternatives for managing Camel and Talend ESB via JMX standard interface. jconsole jconsole is a graphical monitoring tool to monitor Java Virtual Machine (JVM) and java applications both on a local or remote machine. jconsole uses underlying features of JVM to provide information on performance and resource consumption of applications running on the Java platform using JMX technology. jconsole comes as part of Java Development Kit (JDK) and the graphical console can be started using “jconsole” command. Apache Camel and Talend ESB offer several JMX interfaces to monitor and manage integration routes, endpoints, error handlers, etc. jconsole has a very simple user interface, but is sufficient for some projects. hawtio hawtio (http://hawt.io) is a highly modular single-page JavaScript application that fetches JMX metric data using Jolokia, a JMX-HTTP bridge. hawtio is a relatively new tool “on the market”. Nevertheless, it already contains plugins for several different technologies and frameworks such as Apache Camel (integration framework), Apache Karaf (OSGi container), Apache ActiveMQ (JMS messaging) and Apache Tomcat (Java EE web container). As Talend ESB uses respectively supports all of these technologies and frameworks, hawtio is a perfect match, too! hawtio is not “just another jconsole”, but offers some very cool additional features, for example a graphical presentation of Camel routes including real-time monitoring. hawtio was created by James Strachan (whom else?!) who is the creator of Apache Camel and some other great frameworks. Therefore, at the moment, most contributions come from JBoss (where James works after JBoss’ acquisition of FuseSource last year). In the future, I hope (and expect) to see other companies supporting this great open source project, too. Monitoring of Apache Camel and Talend ESB Let’s continue with some monitoring alternatives for Apache Camel and Talend ESB. I define monitoring as “searching and (visually) analyzing state of integration routes and services at runtime”. I will show you Talend’s Service Activity Monitoring for SOAP and REST web services. Besides, you will learn about logstash and Kibana, two awesome open source tools (based on ElasticSearch) for analysis and visualization of any (distributed) log files. Service Activity Monitoring (Part of Talend Administration Center) Service Activity Monitoring (SAM, http://www.liquid-reality.de/display/liquid/Talend+ESB+Service+Activity+Monitoring) is part of Talend Administration Center and allows for logging and monitoring SOAP and REST web service calls. For example, SAM could be used for collecting usage statistics and fault monitoring. SAM is a part of Talend’s OSGi container and can be installed via a single command. It can be activated for SOAP and REST web service providers and consumers within Talend Studio via a single click. So, without any additional efforts, you can monitor your SOAP and REST web services. You can sort by several different parameters and step into details within Talend Administration Center, i.e. you can look at every incoming request message and outgoing response message. logstash logstash (http://logstash.net) is a tool for managing events and logs. You can use it to collect different (distributed) logs, parse them, and store them for later use. Speaking of searching, logstash comes with a simple, but fine web interface for searching and drilling into all of your logs. It uses ElasticSearch under the hood. So, you can easily query through all your logs for specific errors or business analytics (e.g. searching for all lines matching an unique order id). I never used logstash before. I really love it now! However, documentation is not perfect for getting started. So, two hints for newbies: 1) logstash uses ElasticSearch under the hood. However, you do not have to install it separately. It is included and can be used as embedded server. 2) I thought logstash can process every log file by default. However, your log files have to contain a specific structure or you have to configure logstash to know your custom log structure. Especially, if logstash does not know the correct structure of your timestamp, most features will not work. This was not obvious to me. It took me some time to find out that nothing is happening due to wrong log structures (no errors or exceptions came up, just nothing happened at all). Apache Camel and Talend ESB do not offer support for logstash implicitly. One solution is to use Enterprise Integration Patterns (http://www.eaipatterns.com) such as Wire Tap or Message Store to implement logging. Afterwards, logstash can access and analyse these logs. logstash is really awesome, but its real power can be reached by combining it with Kibana. So let’s go to the next section. Kibana Kibana (http://three.kibana.org ) is a browser based analytics and search interface to logstash and other timestamped data sets stored in ElasticSearch. Kibana strives to be easy to get started with, while also being flexible and powerful, just like logstash and ElasticSearch. Main difference to logstash is a much more powerful HTML5 based web interface. You can use multiple concurrent search inputs highlight to drill down bar charts create line charts, stacked, unstacked, filled or unfilled, with or without points create Pie and donut charts that compare top terms or the results of multiple queries create custom dashboards with multiple charts and much more… Again, some hints for newbies (as documentation for installation and usage is very, very short without many important details, unfortunately): 1) Kibana uses logstash and ElasticSearch under the hood. Both are not included, but must be installed separately. As logstash contains an embedded ElasticSearch server, you can get started quickly by just installing logstash in advance. 2) Kibana installation is tricky! If you google, go to Kibana website and navigate to its installation guide (http://kibana.org/intro.html), you will have to install it via Ruby. As always on my Mac, I had some trouble installing Ruby software (version and compiler problems, etc.). But finally I made it… Just to find out that this is an old version. Accidentally, I came to www.three.kibana.org/intro.html, which is the real up-to-date version. Kibana 3 !!! Here, you do NOT need to install Kibana via Ruby. Just download the web application and deploy it to your web container (e.g. Jetty, Tomcat) or Java EE container (e.g. Glassfish, WebSphere). This is so simple and just works with no further configuration. You can use Kibana to analyse and monitor your data as you do with logstash, i.e. you still have to use Enterprise Integration Patterns to log your data first. Afterwards, you can use Kibana’s web interface, which is much more powerful and comfortable than logstash. Finally, great news for Talend users: Kibana (including ElasticSearch) will be integrated into Talend 5.4 for event logging, complex event processing and visual monitoring. I am really looking forward to this awesome feature! Summary Your mission-critical projects need management and monitoring. Today, this is not just possible with complex and expensive tools of large vendors, but also with lightweight frameworks and products such as Apache Camel or Talend ESB. Management and monitoring of Apache Camel and Talend ESB integration routes and SOAP / REST web services is very easy. Several great alternatives are available. Once again, vendor-independent standards such as JXM show their benefits. You can use tooling which is available implicitly in the framework respectively product, or you can integrate your existing tooling very easily. Content from my blog (www.kai-waehner.de/blog). Feedback and other experiences or alternatives appreciated via comments or directly via @KaiWaehner / [email protected] / LinkedIn / Xing. Best regards, Kai Wähner

As you know, there are many frameworks for mobile app development and a growing number of them are based on HTML5. These next-generation tools help developers create mobile apps for phones and tablets without the steep learning curve associated with native SDKs and other programming languages like Objective-C or Java. For countless developers throughout the world, HTML5 represents the future for cross-platform mobile app development. But the question is why? Why has HTML5 become so popular? The widespread adoption of HTML5 involves the emergence of the bring your own device (BYOD) movement. BYOD means that developers can no longer limit application usage to a single platform because consumers want their apps to run on the devices they use every day. HTML5 allows developers to target multiple devices with a single codebase and deliver experiences that closely emulate native solutions, without writing the same application multiple times, using multiple languages or SDKs. The evolution of modern web browsers means that HTML5 can deliver cross-platform, multi-device solutions that mirror behaviors and experiences of “native” apps to the point that it’s often difficult to distinguish between an app written using native development tools and those using HTML. Multiple platform support, time to market and lower maintenance costs are just a few of the advantages inherent in HTML/JavaScript. It’s advantages don’t stop there. HTML’s ability to mitigate long-term risks associated with emerging technologies such as WinRT, ChromeOS, FirefoxOS, and Tizen is unmatched. Simply said, the only code that will work on all these platforms is HTML/JavaScript. Is there a price? Yes, certainly native app consumes less memory and will have faster or more responsive user experience. But in all cases where a web app would work, you can make a step further and create a mobile web app or even packaged application for the store, for multiple platforms, from single codebase. PhoneJS lets you get started fast. PhoneJS for Your Next Mobile Project PhoneJS is a cross-platform HTML5 mobile app development framework that was built to be versatile, flexible and efficient. PhoneJS is a single page application (SPA) framework, with view management and URL routing. Its layout engine allows you to abstract navigation away from views, so the same app can be rendered differently across different platforms or form factors. PhoneJS includes a rich collection of touch-optimized UI widgets with built-in styles for today’s most popular mobile platforms including iOS, Android, and Windows Phone 8. To better understand the principles of PhoneJS development and how you can create and publish applications in platform stores, let’s take a look at a simple demo app called TipCalculator. This application calculates tip amounts due based on a restaurant bill. The complete source code for this app is available here. The app can be found in the AppStore, Google Play, and Windows Store. PhoneJS Application Layout and Routing TipCalculator is a Single-Page Application (SPA) built with HTML5. The start page is index.html, with standard meta tags and links to CSS and JavaScript resources. It includes a script reference to the JavaScript file index.js, where you’ll find the code that configures PhoneJS app framework logic: TipCalculator.app = new DevExpress.framework.html.HtmlApplication({ namespace: TipCalculator, defaultLayout: "empty" }); Within this section, we must specify the default layout for the app. In this example, we’ll use the simplest option, an empty layout. More advanced layouts are available with full support for interactive navigation styles described in the following images: PhoneJS uses well-established layout methodologies supported by many server-side frameworks, including Ruby on Rails and ASP.NET MVC. Detailed information about Views and Layouts can be found in our online documentation. To configure view routing in our SPA, we must add an additional line of code in index.js: TipCalculator.app.router.register(":view", { view: "home" }); This registers a simple route that retrieves the view name from the URL (from the hash segment of the URL). The home view is used by default. Each view is defined in its own HTML file and is linked into the main application page index.html like this: PhoneJS ViewModel A viewmodel is a representation of data and operations used by the view. Each view has a function with the same base name as the view itself and returns the viewmodel for the view. For the home view, the views/home.js script defines the function home which creates the corresponding viewmodel. TipCalculator.home = function(params) { ... }; Three input parameters are used for the tip calculation algorithm: bill total, the number of people sharing the bill, and a tip percentage. These variables are defined as observables, which will be bound to corresponding UI widgets. Note: Observables functionality is supplied by Knockout.js, an important foundation for viewmodels used in PhoneJS. You can learn more about Knockout.js here. This is the code used in the home function to initialize the variables: var billTotal = ko.observable(), tipPercent = ko.observable(DEFAULT_TIP_PERCENT), splitNum = ko.observable(1); The result of the tip calculation is represented by four values: totalToPay, totalPerPerson, totalTip, tipPerPerson. Each value is a dependent observable (a computed value), which is automatically recalculated when any of the observables used in its definition change. Again, this is standard Knockout.js functionality. var totalTip = ko.computed(...); var tipPerPerson = ko.computed(...); var totalPerPerson = ko.computed(...); var totalToPay = ko.computed(...); For an example of business logic implementation in a viewmodel, let’s take a closer look at the observable totalToPay. The total sum to pay is usually rounded. For this purpose, we have two functions roundUp and roundDown that change the value of roundMode (another observable). These changes cause recalculation of totalToPay, because roundMode is used in the code associated with the totalToPay observable. var totalToPay = ko.computed(function() { var value = totalTip() + billTotalAsNumber(); switch(roundMode()) { case ROUND_DOWN: if(Math.floor(value) >= billTotalAsNumber()) return Math.floor(value); return value; case ROUND_UP: return Math.ceil(value); default: return value; } }); When any input parameter in the view changes, rounding should be disabled to allow the user to view precise values. We subscribe to the changes of the UI-bound observables to achieve this: billTotal.subscribe(function() { roundMode(ROUND_NONE); }); tipPercent.subscribe(function() { roundMode(ROUND_NONE); }); splitNum.subscribe(function() { roundMode(ROUND_NONE); }); The complete viewmodel can be found in home.js. It represents a simple example of a typical viewmodel. Note: In a more complex app, it may be useful to implement a structure that modularizes your viewmodels separate from view implementation files. In other words, a file like home.js need not contain the code to implement the viewmodel and instead call a helper function elsewhere for this purpose. In this walkthrough we’re trying to keep things structurally simple. PhoneJS Views Let’s now turn to the markup of the view located in the view/home.html file. The root div element represents a view with the name ‘home’. Within it is a div containing markup for a placeholder called ‘content’. ... A toolbar is located at the top of the view: dxToolbar is a PhoneJS UI widget. It’s defined in the markup using Knockout.js binding. A fieldset appears below the toolbar. To display a fieldset, we use two special CSS classes understood by PhoneJS: dx-fieldset and dx-field. The fieldset contains a text field for the bill total and two sliders for the tip percentage and the number of diners. Two buttons (dxButton) are displayed below the editors, allowing the user to round the total sum to pay. The remaining view displays fieldsets used for calculated results. Total to pay Total per person Total tip Tip per person This completes the description of the files required to create a simple app using PhoneJS. As you’ve seen, the process is simple, straightforward and intuitive. Start, Debug and Build for Stores Starting and debugging a PhoneJS app is just like any other HTML5 based app. You must deploy the folder containing HTML and JavaScript sources, along with any other required file to your web server. Because there is no server-side component to the architectural model, it doesn’t matter which web server you use as long as it can provide file access through HTTP. Once deployed, you can open the app on a device, in an emulator or a desktop browser by simply navigating app’s start page URL. If you want to view the app as it will appear in a phone or tablet within a desktop browser, you will have to override the UserAgent in the browser. Fortunately, this is easy to do with the developer tools that ship as part of today’s modern browsers: If you prefer not to modify UserAgent settings, you can use the Ripple Emulator to emulate multiple device types. At this point you have a web application that will work in the browser on the mobile device and look like native app. Modern mobile browsers provide access to local storage, location api, camera, so good chances are that your app already has anything it needs. Creating Store Ready Applications Using PhoneJS and PhoneGap But what if you need access to device features that browser does not provide? What if you want an app in the app store, not just a webpage. Then you’ll have to create a hybrid application and de-facto standard for such an app is Apache Cordova aka PhoneGap. PhoneGap project for each platform is a native app project that contains WebView (browser control) and a “bridge” that lets your JavaScript code inside WebView access native functions provided by PhoneGap libraries and plugins. To use it, you need to have SDK for each platform you are targeting, but you don’t need to know details of native development, you just need to put your HTML, CSS, JS files into right places and specify your app’s properties like name, version, icons, splashcreens and so on. To be able to publish your app, you will need to register as developer in the respective development portal. This process is well documented for each store and beyond the scope of this article. After that you’ll be able to receive certificates to sign your app package. The need to have SDK for each platform installed sounds challenging - especially after “write one, run everywhere” promise of HTML5/JS approach. This is a small price to pay for building hybrid application and have everything under control. But still there are several services and products that solves this problem for you. One is Adobe’s online service - PhoneGap Build which allows you to build one app for free (to build more, you’ll need a paid account). If you have all the required platform certificate files, the service can build your app for all supported platforms with a few mouse clicks. You only need to prepare app descriptions, promotional and informational content and icons in order to submit your app to an individual store. For Visual Studio developers, DevExpress offers a product called DevExtreme (it includes PhoneJS), which can build applications for iOS, Android and Windows Phone 8 directly within the Microsoft Visual Studio IDE. To summarize, if you need a web application that looks and feels like native on a mobile device, you need PhoneJS - it contains everything required to build touch-enabled, native-looking web application. If you want to go further and access device features, like the contact list or camera, from JavaScript code, you will need Cordova aka PhoneGap. PhoneGap also lets you compile your web app into a native app package. If you don’t want to install an SDK for each platform you are targeting, you can use the PhoneGapBuild service to build your package. Finally, if you have DevExtreme, you can build packages right inside Visual Studio.

Overview OpenHFT/Java Lang started as an Apache 2.0 library to provide the low level functionality used by Java Chronicle without the need to persist to a file. This allows serializable and deserialization of data and random access to memory in native space (off heap) It supports writing and reading enumerable types with object pooling. e.g. writing and reading String without creating an object (if it has been pooled). It also supports writing and read primitive types in binary and text without creating any garbage. Small messages can be serialized and deserialized in under a micro-second. Recent additions Java Lang supports a DirectStore which is like a ByteBuffer but can be any size (up to 40 to 48-bit on most systems) It support 64-bit sizes and offset. It support compacted types, and object serialization. It also supports thread safety features such as volatile reads, ordered (lazy) writes, CAS operations and using an int (4 bytes) as a lock in native memory. Testing a native memory lock in Java This test has one lock and a value which is toggled. One thread changes the value from 0 to 1 and the other switches it from 1 to 0. This goes around 20 million times, but has been run for longer final DirectStore store1 = DirectStore.allocate(1L << 12); final int lockCount = 20 * 1000 * 1000; new Thread(new Runnable() { @Override public void run() { manyToggles(store1, lockCount, 1, 0); } }).start(); manyToggles(store1, lockCount, 0, 1); store1.free(); The manyToggles method is more interesting. Note is using the 4 bytes at offset 0 as a lock. You can arrange any number of locks in native space this way. E.g. you might have fixed length records and want to be able to lock them before updating or access them. You can place a lock at the "head" of the record. private void manyToggles(DirectStore store1, int lockCount, int from, int to) { long id = Thread.currentThread().getId(); assertEquals(0, id >>> 24); System.out.println("Thread " + id); DirectBytes slice1 = store1.createSlice(); for (int i = 0; i < lockCount; i++) { assertTrue( slice1.tryLockNanosInt(0L, 10 * 1000 * 1000)); int toggle1 = slice1.readInt(4); if (toggle1 == from) { slice1.writeInt(4L, to); } else { i--; } slice1.unlockInt(0L); } } The size of the DataStore and the offsets within it are long, allowing you to allocate a continuous block of native memory into the many GB, and access it as you required. On my 2.6 GHz i5 laptop I get the following output for this test Contended lock rate was 9,096,824 per second This looks great but under heavy contention, one thread can be staved out. This is more useful for lots of locks and lower contention. Note: if I drop the timeout from 10 ms to 1 ms, it eventually fails meaning sometimes it takes more then 1 ms to get a lock! Conclusion The Java Lang library is taking the step of making it easier to use native memory with the same functionality available on the heap. The language support is not as good, but if you need to store say 128 GB of data you will get a much better GC behavior using off heap memory.

In the last post I talked about our need for some improved testing tools, our choice of Spock as something to spike, and how mocking looks in Spock. As that blog got rather long, I saved the next installment for a separate post. Today I want to look at stubbing. Stubbing Mocking is great for checking outputs - in the example in the last post, we're checking that the process of encoding an array calls the right things on the way out, if you like - that the right stuff gets poked onto the bsonWriter. Stubbing is great for faking your inputs (I don't know why this difference never occurred to me before, but Colin's talk at Devoxx UK made this really clear to me). One of the things we need to do in the compatibility layer of the new driver is to wrap all the new style Exceptions that can be thrown by the new architecture layer and turn them into old-style Exceptions, for backwards compatibility purposes. Sometimes testing the exceptional cases is... challenging. So I opted to do this with Spock. class DBCollectionSpecification extends Specification { private final Mongo mongo = Mock() private final ServerSelectingSession session = Mock() private final DB database = new DB(mongo, 'myDatabase', new DocumentCodec()) @Subject private final DBCollection collection = new DBCollection('collectionName', database, new DocumentCodec()) def setup() { mongo.getSession() >> { session } } def 'should throw com.mongodb.MongoException if rename fails'() { setup: session.execute(_) >> { throw new org.mongodb.MongoException('The error from the new Java layer') } when: collection.rename('newCollectionName'); then: thrown(com.mongodb.MongoException) } } So here we can use a real DB class, but with a mock Mongo that will return us a "mock" Session. It's not actually a mock though, it's more of a stub because we want to tell it how to behave when it's called - in this test, we want to force it to throw an org.mongodb.MongoException whenever execute is called. It doesn't matter to us what get passed in to the execute method (that's what the underscore means on line 16), what matters is that when it gets called it throws the correct type of Exception. Like before, the when: section shows the bit we're actually trying to test. In this case, we want to callrename. Then finally the then: section asserts that we received the correct sort of Exception. It's not enormously clear, although I've kept the full namespace in to try and clarify, but the aim is that anyorg.mongodb.MongoException that gets thrown by the new architecture gets turned into the appropriate com.mongodb.MongoException. We're sort of "lucky" because the old code is in the wrong package structure, and in the new architecture we've got a chance to fix this and put stuff into the right place. Once I'd tracked down all the places Exceptions can escape and started writing these sorts of tests to exercise those code paths, not only did I feel more secure that we wouldn't break backwards compatibility by leaking the wrong Exceptions, but we also found our test coverage went up - and more importantly, in the unhappy paths, which are often harder to test. I mentioned in the last post that we already did some simple stubbing to help us test the data driver. Why not just keep using that approach? Well, these stubs end up looking like this: private static class TestAsyncConnectionFactory implements AsyncConnectionFactory { @Override public AsyncConnection create(final ServerAddress serverAddress) { return new AsyncConnection() { @Override public void sendMessage(final List byteBuffers, final SingleResultCallback callback) { throw new UnsupportedOperationException(); } @Override public void receiveMessage(final ResponseSettings responseSettings, final SingleResultCallback callback) { throw new UnsupportedOperationException(); } @Override public void close() { } @Override public boolean isClosed() { throw new UnsupportedOperationException(); } @Override public ServerAddress getServerAddress() { throw new UnsupportedOperationException(); } }; } } Ick. And you end up extending them so you can just override the method you're interested in (particularly in the case of forcing a method to throw an exception). Most irritatingly to me, these stubs live away from the actual tests, so you can't easily see what the expected behaviour is. In the Spock test, the expected stubbed behaviour is defined on line 16, the call that will provoke it is on line 19 and the code that checks the expectation is on line 22. It's all within even the smallest monitor's window. So stubbing in Spock is painless. Next!

A couple of weeks ago Jim and I were building out a neo4j unmanaged extension from which we wanted to return the results of a traversal which had a lot of paths. Our code initially looked a bit like this: package com.markandjim @Path("/subgraph") public class ExtractSubGraphResource { private final GraphDatabaseService database; public ExtractSubGraphResource(@Context GraphDatabaseService database) { this.database = database; } @GET @Produces(MediaType.TEXT_PLAIN) @Path("/{nodeId}/{depth}") public Response hello(@PathParam("nodeId") long nodeId, @PathParam("depth") int depth) { Node node = database.getNodeById(nodeId); final Traverser paths = Traversal.description() .depthFirst() .relationships(DynamicRelationshipType.withName("whatever")) .evaluator( Evaluators.toDepth(depth) ) .traverse(node); StringBuilder allThePaths = new StringBuilder(); for (org.neo4j.graphdb.Path path : paths) { allThePaths.append(path.toString() + "\n"); } return Response.ok(allThePaths.toString()).build(); } } We then compiled that into a JAR, placed it in ‘plugins’ and added the following line to ‘conf/neo4j-server.properties’: org.neo4j.server.thirdparty_jaxrs_classes=com.markandjim=/unmanaged After we’d restarted the neo4j server we were able to call this end point using cURL like so: $ curl -v http://localhost:7474/unmanaged/subgraph/1000/10 This approach works quite well but Jim pointed out that it was quite inefficient to load all those paths up into memory so we thought it would be quite cool if we could stream it as we got to each path. Traverser wraps an iterator so we are lazily evaluating the result set in any case. After a bit of searching we came StreamingOutput which is exactly what we need. We adapted our code to use that instead: package com.markandjim @Path("/subgraph") public class ExtractSubGraphResource { private final GraphDatabaseService database; public ExtractSubGraphResource(@Context GraphDatabaseService database) { this.database = database; } @GET @Produces(MediaType.TEXT_PLAIN) @Path("/{nodeId}/{depth}") public Response hello(@PathParam("nodeId") long nodeId, @PathParam("depth") int depth) { Node node = database.getNodeById(nodeId); final Traverser paths = Traversal.description() .depthFirst() .relationships(DynamicRelationshipType.withName("whatever")) .evaluator( Evaluators.toDepth(depth) ) .traverse(node); StreamingOutput stream = new StreamingOutput() { @Override public void write(OutputStream os) throws IOException, WebApplicationException { Writer writer = new BufferedWriter(new OutputStreamWriter(os)); for (org.neo4j.graphdb.Path path : paths) { writer.write(path.toString() + "\n"); } writer.flush(); } }; return Response.ok(stream).build(); } As far as I can tell the only discernible difference between the two approaches is that you get an almost immediate response from the streamed approached whereas the first approach has to put everything in the StringBuilder first. Both approaches make use of chunked transfer encoding which according to tcpdump seems to have a maximum packet size of 16332 bytes: 00:10:27.361521 IP localhost.7474 > localhost.55473: Flags [.], seq 6098196:6114528, ack 179, win 9175, options [nop,nop,TS val 784819663 ecr 784819662], length 16332 00:10:27.362278 IP localhost.7474 > localhost.55473: Flags [.], seq 6147374:6163706, ack 179, win 9175, options [nop,nop,TS val 784819663 ecr 784819663], length 16332

A recent Java production performance problem forced me to revisit and truly appreciate the Java VM Just-In-Time (JIT) compiler. Most Java developers and support individuals have heard of this JVM run time performance optimization but how many truly understand and appreciate its benefits? This article will share with you a troubleshooting exercise I was involved with following the addition of a new virtual server (capacity improvement and horizontal scaling project). For a more in-depth coverage of JIT, I recommend the following articles: ## Just-in-time compilation http://en.wikipedia.org/wiki/Just-in-time_compilation ## The Java HotSpot Performance Engine Architecture http://www.oracle.com/technetwork/java/whitepaper-135217.html ## Understanding Just-In-Time Compilation and Optimization http://docs.oracle.com/cd/E15289_01/doc.40/e15058/underst_jit.htm ## How the JIT compiler optimizes code http://pic.dhe.ibm.com/infocenter/java7sdk/v7r0/index.jsp?topic=%2Fcom.ibm.java.zos.70.doc%2Fdiag%2Funderstanding%2Fjit_overview.html JIT compilation overview The JIT compilation is essentially a process that improves the performance of your Java applications at run time. The diagram below illustrates the different JVM layers and interaction. It describes the following high level process: Java source files are compiled by the Java compiler into platform independent bytecode or Java class files. After your fire your Java application, the JVM loads the compiled classes at run time and execute the proper computation semantic via the Java interpreter. When JIT is enabled, the JVM will analyze the Java application method calls and compile the bytecode (after some internal thresholds are reached) into native, more efficient, machine code. The JIT process is normally prioritized by the busiest method calls first. Once such method call is compiled into machine code, the JVM executes it directlyinstead of “interpreting” it. The above process leads to improved run time performance over time. Case study Now here is the background on the project I was referring to earlier. The primary goal was to add a new IBM P7 AIX virtual server (LPAR) to the production environment in order to improve the platform’s capacity. Find below the specifications of the platform itself: Java EE server: IBM WAS 6.1.0.37 & IBM WCC 7.0.1 OS: AIX 6.1 JDK: IBM J2RE 1.5.0 (SR12 FP3 +IZ94331) @64-bit RDBMS: Oracle 10g Platform type: Middle tier and batch processing In order to achieve the existing application performance levels, the exact same hardware specifications were purchased. The AIX OS version and other IBM software’s were also installed using the same version as per existing production. The following items (check list) were all verified in order to guarantee the same performance level of the application: Hardware specifications (# CPU cores, physical RAM, SAN…). OS version and patch level; including AIX kernel parameters. IBM WAS & IBM WCC version, patch level; including tuning parameters. IBM JRE version, patch level and tuning parameters (start-up arguments, Java heap size…). The network connectivity and performance were also assessed properly. After the new production server build was completed, functional testing was performed which did also confirm a proper behaviour of the online and batch applications. However, a major performance problem was detected on the very first day of its production operation. You will find below a summary matrix of the performance problems observed. Production server Operation elapsed time Volume processed (# orders) CPU % (average) Middleware health Existing server 10 hours 250 000 (baseline) 20% healthy *New* server 10 hours 50 000 -500% 80% +400% High thread utilization As you can see from the above view, the performance results were quite disastrous on the first production day. Not only much less orders were processed by the new production server but the physical resource utilization such as CPU % was much higher compared with the existing production servers. The situation was quite puzzling given the amount of time spent ensuring that the new server was built exactly like the existing ones. At that point, another core team was engaged in order to perform extra troubleshooting and identify the source of the performance problem. Troubleshooting: searching for the culprit... The troubleshooting team was split in 2 in order to focus on the items below: Identify the source of CPU % from the IBM WAS container and compare the CPU footprint with the existing production server. Perform more data and file compares between the existing and new production server. In order to understand the source of the CPU %, we did perform an AIX CPU per Thread analysis from the IBM JVM running IBM WAS and IBM WCC. As you can see from the screenshot below, many threads were found using between 5-20% each. The same analysis performed on the existing production server did reveal fewer # of threads with CPU footprint always around 5%. Conclusion: the same type of business process was using 3-4 times more CPU vs. the existing production server. In order to understand the type of processing performed, JVM thread dumps were captured at the same time of the CPU per Thread data. Now the first thing that we realized after reviewing the JVM thread dump (Java core) is that JIT was indeed disabled! The problem was also confirmed by running the java –version command from the running JVM processes. This finding was quite major, especially given that JIT was enabled on the existing production servers. Around the same time, the other team responsible of comparing the servers did finally find differences between the environment variables of the AIX user used to start the application. Such compare exercise was missed from the earlier gap analysis. What they found is that the new AIX production server had the following extra entry: JAVA_COMPILER=NONE As per the IBM documentation, adding such environment variable is one of the ways to disableJIT. Complex root cause analysis, simple solution In order to understand the impact of disabling JIT in our environment, you have to understand its implication. Disabling JIT essentially means that the entire JVM is now running ininterpretation mode. For our application, running in full interpretation mode not only reduces the application throughput significantly but also increases the pressure point on the server CPU utilization since each request/thread takes 3-4 more times CPU than a request executed with JIT (remember, when JIT is enabled, the JVM will perform many calls to the machine/native code directly). As expected, the removal of this environment variable along with the restart of the affected JVM processes did resolve the problem and restore the performnance level. Assessing the JIT benefits for your application I hope you appreciated this case study and short revisit of the JVM JIT compilation process. In order to understand the impact of not using JIT for your Java application, I recommend that you preform the following experiment: Generate load to your application with JIT enabled and capture some baseline data such as CPU %, response time, # requests etc. Disable JIT. Redo the same testing and compare the results. I’m looking forward for your comments and please share any experience you may have with JIT.

Introduction The purpose of this article is to see how to integrate Spring Security on top of an Openxava standalone application. Openxava builds portlets as well as standalone applications. When working with portlets deployed on a portal such as Liferay, they handle secured access by configuration. A standalone application lets you have to handle this functionality yourself. This page will illustrate how to add spring security (authentication/authorisation) functionalities. The focus will be on the authorizations aspects since authorization is often enterprise-environment specific. To demonstrate the integration, this article will use the minuteproject Lazuly showcase application generated for Openxava. The first part identifies and explains the actions to undertake. The second part explains what minuteproject can do to fasten your development by generated a customed spring-security integration for you Openxava application. Eventually a set of tests will ensure that the resulting application is correctly protected for URL direct access as well as content display. Furthermore, the integration is technologically non-intruisive. You do not have to change Openxava code for it to work. Spring-Security Openxava integration Technical Access URL access The url pattern is the following http://servername:port/applicationcontext/xava/module.jsp?application=appName&module=moduleName given like that it is hard to protect. The module and application are passed as parameters. The URL has to be revisited with http://servername:port/applicationcontext/applicationPath/module And the 'parameter' access are banned. Enabling new URL access Add a servlet package net.sf.minuteproject.openxava.web.servlet; import java.io.*; import javax.servlet.*; import javax.servlet.http.*; public class ModuleHomeServlet extends HttpServlet { protected void doGet(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { RequestDispatcher dispatcher; String [] uri = request.getRequestURI().split("/"); if (uri.length < 4) { dispatcher = request.getRequestDispatcher("/xava/homeMenu.jsp"); } else { dispatcher = request.getRequestDispatcher( "/xava/home.jsp?application=" + uri[1] + "&module=" + uri[3]); } dispatcher.forward(request, response); } protected void doPost(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { doGet(request, response); } } homeMenu.jsp is a page including a header with menu (to protect and whose menu link URL are correspond to the secured format) and a footer. Add a servlet configuration Servlet configuration snippet done in Openxava servlets.xml. moduleHome net.sf.minuteproject.openxava.web.servlet.ModuleHomeServlet moduleHome /MenuModules/* This snippet will be package in war web.xml at build time by OpenXava ant script. Jsp access Prohibit any Openxava jsp access except the one of the menu To do that add an spring applicationContext-security.xml in you classpath (ex: Openxava src folder). ... This means that all path after xava will be accessible (ex: css...) safe jsp expect one homeMenu.jsp is available to all registered user (ie having role ROLE_APPLICATION_USER cf attribution at authorisation part further). Of course ensure that the role ROLE_NOT_PRESENT is really not present in your app. Business Access The idea is to give CRUD access on a entity base on role. Define roles and UC To be more explicit, I define 3 roles with their scope. Administrator can administrate ROLE and COUNTRY entities Application_user can manage all the other conference related tables safe the master data table mentionned above. Reviewer can access to the statistic views but not the administration. Both reviewer and Administrator can do what Application_user can do. In applicationContext-security.xml the role can be mapped to specific URLs Impact of the roles access on your model modal navigation Be coherent As I said before 'the CRUD access on a entity is role based' but the affectation mechanism has to reflect that. OpenXava has annotation to create an entity from another one. It is then logical that we cannot create entity B from entity A, if we do not have CRUD rights on entity B. The mechanism will consist in this case of affectation only with search functionalities. In our scenario it means that a user with 'application_user' only can select a country but can not create any (no create or update icons available). It is also true at the menu level, a user is entitled to see only its menu items corresponding to its profile. Here the menu is done in JSP. To secure the access you can wrap to code to secure with taglib code coming with spring security or add a little taglib such as the following isUserInRole.tag located in web/WEB-INF/tags/common. Wrap the code to protect here the administrator menu and each menu item Administration CountryRole Authentication/Authorization For the user to operate, he must be authenticated and authorised (moment where his role profile is loaded granting him with business access rights). I use an simple authentication and authorisation based a DB information. Of course you are not supposed to use that in production ;) In applicationContext-security.xml add the following snippet. java:comp/env/jdbc/conferenceDS Both authorisation and authentication queries have to be valid. Here, they are done on top of views, which means that you have to implement 2 views: user_authentication and user_authorisation. The datasource is the same as the one of the Openxava application View gives you flexibility because if you have indirection level of granularity such as (user-role-permission), your view can associate user to role Authentication flow Eventually you need to handle an authentication flow composed of welcome page login page access denied page logout link The flow is handled by applicationContext-security.xml Add the following snippet. Login.jsp is strongly inspired by spring petclinic sample Login test Locale is: Your login attempt was not successful, try again. Reason: . User:Password:Don't ask for my password for two weeks index.jsp Welcome to Conference login accessDenied.jsp Access denied! Not to forget a logout functionality here added on the menu Logoff Spring security dependencies Add spring security jars into web/WEB-INF/lib spring-aop-3.0.4.RELEASE.jar spring-asm-3.0.4.RELEASE.jar spring-beans-3.0.4.RELEASE.jar spring-context-3.0.4.RELEASE.jar spring-core-3.0.4.RELEASE.jar spring-expression-3.0.4.RELEASE.jar spring-jdbc-3.0.4.RELEASE.jar spring-security-acl-2.0.3.jar spring-security-config-3.1.0.M1.jar spring-security-core-2.0.3.jar spring-security-core-3.1.0.M1.jar spring-security-core-tiger-2.0.3.jar spring-security-taglibs-2.0.3.jar spring-security-web-3.1.0.M1.jar spring-tx-3.0.4.RELEASE.jar spring-web-3.0.4.RELEASE.jar Spring security context Spring security context had been mentioned at different level, here is the complete version java:comp/env/jdbc/conferenceDS Reference the context Openxava listeners.xml is the place where you can set web.xml-snippets to be package in web.xml at Openxava build time Add the following snippet org.springframework.web.context.ContextLoaderListener contextConfigLocation classpath:applicationContext-security.xml springSecurityFilterChain org.springframework.web.filter.DelegatingFilterProxy springSecurityFilterChain /* The minuteproject way Doing the integration can be time consuming. As you can notice there is some effort to have the code compliant for a webapp here Openxava to be bodyguard by Spring-Security. Meanwhile when dealing with data centric application, this knowledge can be crystalized to be instantly available. Because...there is an underlying concept that guides our choice and lead to best pratices. It is one thing to execute them, it is another to state it. The question is how do we specify which entity to access and to which role. The idea is to express with simplicity the relationship between role or permission and action. In our case the actions are: a full CRUD an affectation mechanism The full CRUD is associated to a specific role. The affection (linkage of an entity from another by search) is when to entities are linked but not all the role of the main entities are the same as the roles of the target. Otherwise affection goes with creation and update. And the roles are: Administrator Application_user Reviewer Now it is time for a primary school exercice If you represent an entity-relationship diagram, you should see boxes and links. Boxes for entities and links for relationships. Give each role/permission a color. Paint all the boxes that are full CRUD with the corresponding role color... Yes, you may paint the same box twice (resulting is color combination). The result gives you the Color access spectrum of your DB. Of course, we can further decline the gradient with other function (read-only, controller specific...) But the underlying idea is evident. What Minuteproject allows you to do it by enriching your model with this color spectrum at the entity level or at the package level. This enables you to work with concept only closed to UC agnostic of technology implementations. Minuteproject configuration snippet Generation Minuteproject configuration full The configuration is similar to lazuly show case enhanced with security aspects org.gjt.mm.mysql.Driver jdbc:mysql://127.0.0.1:3306/conference root mysql The main points are exclude entities starting with user_ (i.e. the security entity used by spring configuration) add security access on package level package admin is accessible by role administrator only package statistics is accessible by role reviewer only default package (conference) is accessible by any application_user add spring-security track in the target add reference in openxava to spring-security The track springsecurity holding the configuration is not yet bundled in minuteproject release 0.8 but will be present for 0.8.1+. Set up Database Implement the views Here a very dummy implementation. create view user_authentication as select email as username, first_name as password, '1' as active from conference_member ; create view user_authorisation as select cm.email as username, r.name as role from conference_member cm, role r, member_role mr where mr.role_id = r.id and mr.conference_member_id = cm.id union select cm.email as username, concat('ROLE_',r.name) as role from conference_member cm, role r, member_role mr where mr.role_id = r.id and mr.conference_member_id = cm.id ; As you can not there is a little redundancy in the user_authentication view, since sometimes the role administrator is refered sometimes role_administrator. This will be homogenized in next release. Add some default value Here a very dummy implementation. INSERT INTO country (id, name, iso_name) VALUES (-1, 'France', 'FR'); INSERT INTO address (id, street1, street2, country_id) VALUES(-1, 'rue 1', 'rue 2', -1); INSERT INTO conference_member (id, conference_id, first_name, last_name, email, address_id, status ) VALUES (-1, -1, 'f', 'a', '[email protected]', -1, 'ACTIVE' ); INSERT INTO role (id, name) VALUES (-1, 'ADMINSTRATOR' ); INSERT INTO role (id, name) VALUES (-2, 'ROLE_APPLICATION_USER' ); INSERT INTO member_role (conference_member_id, role_id) VALUES (-1, -1); INSERT INTO member_role (conference_member_id, role_id) VALUES (-1, -2); So when user [email protected] connects he will get the role Administrator which allows him to access the administrator menu and create a new role called 'REVIEWER'. He can also create a new conference member and associate with the role 'REVIEWER'. Set up Application Download the lazuly-openxava-springsecurity minuteproject configuration from google code minuteproject. Copy file into /mywork/config Execute In /mywork/config: model-generation.cmd mp-config-LAZULY-Openxava-with-spring-security.xml The generated code goes to /DEV/output/openxava-springsecurity/conference Packaging Here the packaging/deployment is a 2 steps exercices (unfortunately): there is no more the start-tomcat/stop-tomcat command in OX distribution spring dependencies are not included Steps Check that Openxava 4.3 is available, and OX_HOME is set to Openxava 4.3 from /DEV/output/openxava-springsecurity/conference run build-conference(.cmd/sh). This will trigger the build that is successful but not the deployment due to information before. Open the project generated by the build in Openxava workspace Add Spring security dependencies Start tomcat server (remark: The Datasource for the application is present in tomcat/config/context.xml) Deploy Enjoy Testing Welcome page Default URL at context root of the application. Login page Any other direct called where the user is not authenticated will be intercepted and routed to this page Contextual Menu The user have access to the admin and conference part not the statistics. The URLs have been modified. When the user tries to access the standard OX style URL he recieves an access denied (ex: module.jsp) Add role reviewer Add user Affect user with role reviewer and default (application_user) Logoff (click logoff) Login as Reviewer On login page enter [email protected] and password=b In the contextual menu you do see the 'admin' package' And you get an access deny when manipulating directly the URL Now the application is secured. Conclusion This article showed the configuration and manipulation to integrate spring security with openxava in a non-intrusive manner. It stressed a new concept 'DB color access spectrum' and how to densify the security information in minuteproject configuration. DB color access spectrum is a concept which ask only to be extended: Ad-hoc functions, controllers Store procedures It is simple to express and analyst friendly. It is not bound to a technology. It is a step in easily defining fine grain access, its combination with profile based access and state based access (to do manually... for the moment ;)) could pave the way to intuitive and implicit workflows instead of heavy BPM solutions.

Strategy Pattern is one of the patterns from the Design Patterns : Elements of Reusable Object book. The intent of the strategy pattern as stated in the book is: Define a family of algorithms, encapsulate each one, and make them interchangeable. Strategy lets the algorithm vary independently from clients that use it. In this post I would like to give an example or two on strategy pattern and then rewrite the same example using lambda expressions to be introduced in Java 8. Strategy Pattern: An example Consider an interface declaring the strategy: interface Strategy{ public void performTask(); } Consider two implementations of this strategy: class LazyStratgey implements Strategy{ @Override public void performTask() { System.out.println("Perform task a day before deadline!"); } } class ActiveStratgey implements Strategy{ @Override public void performTask() { System.out.println("Perform task now!"); } } The above strategies are naive and I have kept it simple to help readers grasp it quickly. And lets see these strategies in action: public class StartegyPatternOldWay { public static void main(String[] args) { List strategies = Arrays.asList( new LazyStratgey(), new ActiveStratgey() ); for(Strategy stg : strategies){ stg.performTask(); } } } The output for the above is: Perform task a day before deadline! Perform task now! Strategy Pattern: An example with Lambda expressions Lets look at the same example using Lambda expressions. For this we will retain our Strategy interface, but we need not create different implementation of the interface, instead we make use of lambda expressions to create different implementations of the strategy. The below code shows it in action: import java.util.Arrays; import java.util.List; public class StrategyPatternOnSteroids { public static void main(String[] args) { System.out.println("Strategy pattern on Steroids"); List strategies = Arrays.asList( () -> {System.out.println("Perform task a day before deadline!");}, () -> {System.out.println("Perform task now!");} ); strategies.forEach((elem) -> elem.performTask()); } } The output for the above is: Strategy pattern on Steroids Perform task a day before deadline! Perform task now! In the example using lambda expression, we avoided the use of class declaration for different strategies implementation and instead made use of the lambda expressions. Strategy Pattern: Another Example This example is inspired from Neal Ford’s article on IBM Developer works: Functional Design Pattern-1. The idea of the example is exactly similar, but Neal Ford uses Scala and I am using Java for the same with a few changes in the naming conventions. Lets look at an interface Computation which also declares a generic type T apart from a method compute which takes in two parameters. interface Computation { public T compute(T n, T m); } We can have different implementations of the computation like: IntSum – which returns the sum of two integers, IntDifference – which returns the difference of two integers and IntProduct – which returns the product of two integers. class IntSum implements Computation { @Override public Integer compute(Integer n, Integer m) { return n + m; } } class IntProduct implements Computation { @Override public Integer compute(Integer n, Integer m) { return n * m; } } class IntDifference implements Computation { @Override public Integer compute(Integer n, Integer m) { return n - m; } } Now lets look at these strategies in action in the below code: public class AnotherStrategyPattern { public static void main(String[] args) { List computations = Arrays.asList( new IntSum(), new IntDifference(), new IntProduct() ); for (Computation comp : computations) { System.out.println(comp.compute(10, 4)); } } }public class AnotherStrategyPattern { public static void main(String[] args) { List computations = Arrays.asList( new IntSum(), new IntDifference(), new IntProduct() ); for (Computation comp : computations) { System.out.println(comp.compute(10, 4)); } } } The output for the above is: 14 6 40 Strategy Pattern: Another Example with lambda expressions Now lets look at the same example using Lambda expressions. As in the previous example as well we need not declare classes for different implementation of the strategy i.e the Computation interface, instead we make use of lambda expressions to achieve the same. Lets look at an example: public class AnotherStrategyPatternWithLambdas { public static void main(String[] args) { List> computations = Arrays.asList( (n, m)-> { return n+m; }, (n, m)-> { return n*m; }, (n, m)-> { return n-m; } ); computations.forEach((comp) -> System.out.println(comp.compute(10, 4))); } } The output for above is 14 6 40 From the above examples we can see that using Lambda expressions will help in reducing lot of boilerplate code to achieve more concise code. And with practice one can get used to reading lambda expressions.

in-line predicates can create a maintenance nightmare. writing in-line lambda expressions and using the stream interfaces to perform common operations on collections can be awesome. assume the following example: list getadultmales (list persons) { return persons.stream().filter(p -> p.getage() > adult && p.getsex() == sexenum.male ).collect(collectors.tolist()); } that’s fun! but things like this also lead to software that is costly to maintain. at least in an enterprise application, where most of your code handles business logic, your development team will grow the tenancy to write the same similar set of predicate rules again and again. that is not what you want on your project. it breaks three important principles for growing maintainable and stable enterprise applications: dry (don’t repeat yourself): writing code more than once is not a good fit for a lazy developer it also makes your software more difficult to maintain because it becomes harder to make your business logic consistent readability : following clean-code best practices, 80% of writing code is reading the code that already exists. having complicated lambda expressions is still a bit hard to read compared to a simple one-line statement. testability : your business logic needs to be well-tested. it is adviced to unit-test your complex predicates. and that is just much easier to do when you separate your business predicate from your operational code. and from a personal point of view… that method still contains too much boilerplate code… imports to the rescue! fortunately, we have a very good suggestion in the world of unit testing on how we could improve on this. imagine the following example: import static somepackage.personpredicate; ... list getadultmales (list persons) { return persons.stream().filter( isadultmale() ).collect(collectors.tolist()); } what we did here was: create a personpredicate class define a “factory” method that creates the lambda predicate for us statically import the factory method into our old class this is how such a predicate class could look like, located next to your person domain entity: public personpredicate { public static predicate isadultmale() { return p -> p.getage() > adult && p.getsex() == sexenum.male; } } wait… why don’t we just create a “ismaleadult” boolean function on the person class itself like we would do in domain driven development? i agreed, that is also an option… but as time goes on and your software project becomes bigger and loaded with functionality and data… you will again break your clean code principles: the class becomes bloated with all kind of function and conditions your class and tests become huge, more difficult to handle and change (*) (*) and yes… even if you do your best to separate your concerns and use composition patterns adding some defaults… working with domain objects, we can imagine that some operations (such as filter) are often executed on domain entities. taking that into account, it would make sense to let our entities implement some interface that offers us some default methods. for example: public interface domainoperations { default list filter(predicate predicate) { return persons.stream().filter( predicate ) .collect(collectors.tolist()); } } when our person entity implements this interface, we can clean-up our code even more: list getadultmales (list persons) { return persons.filter( isadultmale() ); } and there we go… conclusion moving your predicates to a predicate helper class offers some good advantages in the long run: predicate classes are easy to test and change your domain objects remain clean and focussed on representing your domain, not your business logic you optimize the re-usability of your code and, in the end, reduce your maintenance you seperate your business from operational concerns references clean code: a handbook of agile software craftsmanship [robert c. martin] practical unit testing with junit and mockito [tomek kaczanowski] state of the collections [http://cr.openjdk.java.net/~briangoetz/lambda/collections-overview.html] notes the code above is served as an example to illustrate the principles i wanted to discuss. however, i did not proof-run this code yet (it’s still on my todo list). some modifications may be needed for your project.

Expose two very popular JMS implementations, Apache ActiveMQand JBoss HornetQ, to be available to web front-end (JavaScript) using STOMP over Websockets.

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In a previous post, I described Babylon.js, a brand new 3D engine for WebGL and JavaScript. Among others features, Babylon.js is capable of loading a JSON file through the .babylon file format. During this post, I will show you how to use Babylon.js API to load a scene created with Blender. Creating a scene and exporting a .babylon file with Blender In my previous post, I already described how to install the .babylon exporter in Blender, but for the sake of comprehension, I copy/paste the process here: First of all, please download the exporter script right here: http://www.babylonjs.com/Blender2Babylon.zip. To install it in Blender, please follow this small guide: Unzip the file to your Blender’s plugins folder (Should be C:\Program Files\Blender Foundation\Blender\2.67\scripts\addons for Blender 2.67 x64). Launch Blender and go to File/User Préférences/Addon and select Import-Export category. You will be able to activate Babylon.js exporter. Create your scene Go to File/Export and select Babylon.js format. Choose a filename and you are done ! Once the exporter is installed, you can unleash your artist side and create the most beautiful scene your imagination can produce. In my case, it will be fairly simple: A camera A point light A plane for the ground A sphere Just to be something a bit less austere, I will add some colors for the ground and the sphere: I will also add a texture for the sphere. This texture will be used for the diffuse channel of the material: Please pay attention to: Use Alpha checkbox to indicate to Babylon.js to use alpha values from the texture Color checkbox to indicate that this texture must be use for diffuse color Once you are satisfied (You can obviously create a more complex scene), just go to File/Export/Babylon.js to create your .babylon file. Loading your .babylon Inside your page/app First of all, you should create a simple html web page: This page is pretty simple because all you need is just a canvas and a reference to babylon.js. Then you will have to use BABYLON.SceneLoader object to load your scene. To do so, just add this script block right after the canvas: the Load function takes the following parameters: scene folder (can be empty to use the same folder as your page) scene file name a reference to the engine a callback to give you the loaded scene (in my case, I use this callback to attach the camera to the canvas and to launch my render loop) a callback for progress report Once the scene is loaded, just wait for the textures and shaders to be ready, connect the camera to the canvas and let’s go! Fairly simple, isn’t it? Please note that the textures and the .babylon file must be side by side Another function is also available to interact with .babylon files: BABYLON.SceneLoader.importMesh: BABYLON.SceneLoader.ImportMesh("spaceship", "Scenes/SpaceDek/", "SpaceDek.babylon", scene, function (newMeshes, particleSystems) { }); This function is intended to import meshes (with their materials and particle systems) from a scene to another. It takes the following parameters: object name (if you omit this parameter, all the objects are imported) scene folder (can be empty to use the same folder as your page) scene file name a reference to the target scene a callback to give you the list of imported meshes and particle systems Playing with your scene The result is as expected: a orange plane lighted by a point light with a floating sphere using an RGBA texture for its diffuse color. You can use the mouse and the cursors keys to move: &lt;br&gt; For IE11 preview, you can also directly try the result just here: http://www.babylonjs.com/tutorials/blogs/loadScene/loadscene.html The full source code is also available there: http://www.babylonjs.com/tutorials/blogs/loadScene/loadScene.zip Enjoy! Others chapters If you want to go more deeply into babylon.js, here are some useful links: Introducing Babylon.js: http://blogs.msdn.com/b/eternalcoding/archive/2013/06/27/babylon-js-a-complete-javascript-framework-for-building-3d-games-with-html-5-and-webgl.aspx How to load a scene exported from Blender: http://blogs.msdn.com/b/eternalcoding/archive/2013/06/28/babylon-js-how-to-load-a-babylon-file-produced-with-blender.aspx

What is the Default? Usually in most installations, binary log files are located in the MySQL default directory (/var/lib/mysql) just next to the data files. Why Should I Move the Binary Logs to Another Directory? Each data modification (INSERT, UPDATE, DELETE...) and data definition (ALTER, ADD, DROP...) statement that you perform in your server are recorded in the Log files. Therefore, each time you make any of these statements, you actually update both your data files and your log files. The result is high IO utilization that is focused on a specific disk area. A common recommendation in the database field is to separate these files to two different disks in order to get a better performance. How to Perform it? Change the log-bin variable in the my.cnf to log-bin=/path/to/new/directory/mysql-bin Purge as many files as you can (PURGE BINLOG...) in order to minimize the number of moved files (see stop 4). Stop the master (service mysql stop). Move the files to the new directory: mv /var/lib/mysql/mysql-bin.* /path/to/new/directory Start the master again (service mysql start). Bottom Line Few steps and your server is ready for more traffic and data. Keep Performing, Moshe Kaplan

longpolling ; also known as reverse ajax or comet, is a push method that operates seamlessly in javascript aided web browsers. although advanced push techniques such as sse and websocket with html 5 are already available, either these technologies are still in the process of development or they are not supported entirely by web browsers, longpolling and similar techniques be in demand. in longpolling technique, the web browser makes a request to the server, and this request is suspended on the server until a ready response ( resource ) is founded. the pending http request is sent back to the available source web browser when a response is obtained. the web browser transmits a new polling message as soon as it gets the http response, and this process repeats itself until a new http response is ready.. from time to time, the failure of the pending polling request originating from server, web browser or current network environment can also be a matter. in this case, web browser takes the error information from the server, sent a request once more and then the polling starts again. in longpolling technique, xmlhttprequest object which is a javascript object can be used on the web browser side. forthcoming asyncronousresponse objects with jax-rs 2 can be used on the server side in terms of flexibility and convenience. now, i would like to share with you a chat application instance that contains the association of longpolling technique and jax-rs 2 within java ee 7 . dependent library chat application can easily operate on a servlet container, but available container environment must comply with the standard servlet 3 because jax-rs 2 uses forthcoming asynchronous handlers together with servlet 3 on the container. org.glassfish.jersey.containers jersey-container-servlet 2.0 note: jersey is the reference implementer library of the standard jax-rs. http://jersey.java.net/ jetty 9 or tomcat 7 can be used for the servlet 3 support . entry point of the chat application (rest endpoint) @applicationpath("app") public class app extends application { @override public set> getclasses() { set> sets=new hashset<>(); sets.add(chat.class); return sets; } } the above application class type object that is wrapped with @applicationpath notation contains the entry point of the chat application. the defined chat class into the hashset is described as a rest resource belonging to the chat application. chat resource @path("/chat") public class chat { final static map waiters = new concurrenthashmap<>(); final static executorservice ex = executors.newsinglethreadexecutor(); @path("/{nick}") @get @produces("text/plain") public void hangup(@suspended asyncresponse asyncresp, @pathparam("nick") string nick) { waiters.put(nick, asyncresp); } @path("/{nick}") @post @produces("text/plain") @consumes("text/plain") public string sendmessage(final @pathparam("nick") string nick, final string message) { ex.submit(new runnable() { @override public void run() { set nicks = waiters.keyset(); for (string n : nicks) { // sends message to all, except sender if (!n.equalsignorecase(nick)) waiters.get(n).resume(nick + " said that: " + message); } } }); return "message is sent.."; } } asyncresponse type parameter that is found as a parameter on hangup(..) method defines the longpolling response object which will be suspended on the server. while asyncresponse type objects can be provided from jax-rs environment automatically, these suspended objects can be submitted to the user (web browser) as a response at any time. the second parameter [ @pathparam("nick") string nick ] found on the hangup(..) method obtains the user nick name which is sent to the method on the url. the information about suspended asyncresponse objects belong to which user is needed subsequently. concurrenthashmap that is a structure of a concurrent map can be used for this purpose. in this way,each nick -> asyncresponse object that is sent to thehangup(..) method will be kept under record. the second method of the chat class sendmessage(..) can be accessed with http /post method and operates as restful method which derives chat messages from the web browser. when users submit a chat message with the knowledge of nick name to the server, sendmessage(..) restful method obtains this information from the method parameters, and this information is being transacted as asynchronous through the executorservice object. of course a simple thread can be used instead of executorservice object that is used in here. just as new thread( new runnable(){ … } ).start(); . the key issue here is the running of the sent message at the background and to prevent the interruption of default /post request, more precisely, to prevent the waiting of message information made push to all users. the nick -> asyncresponse pair that is filled in the previous hangup(..) method in the concurrenthashmap is consumed into the runnable task object which is found in the sendmessage(..) method, and this chat message is transmitted to all suspended asyncresponse objects except the user itself. the resume() method included in the asyncresponse objects allows the @suspended response object to respond. that is to say, ( suspend ) before, and then ( resume ) when chat message resource become ready. html components nick:message: post in the above html page, there are a nick input object, a text area object where the message will be entered and an html button where the message will be sent and these are lined in an html table object. the textarea is made as disabled initially because it is expected to enter the nick name firstly from the user when the application is started. when the user sends the first request (nick name), unchangeable state of this field is modified and is made message writable. also, when nick name is sent to the server (i.e. when the first polling request is made), html table row element which is a class type ( ) is hidden. chat application is required to provide xmlhttprequest objects and http requests as asynchronous. in this application we will benefit from jquery ajax library which facilitates these operations and uses xmlhttprequest objects in the background. in addition to jquery dependence, there is a chat.js script that was written by us in the project. chat.js // the polling function must be called once, //it will call itself recursively in case of error or performance. var poolit = function () { $.ajax({ type: "get", url: "/app/chat/" + $("#nick").val(), // access to the hangup(..) method datatype: "text", // incoming data type text success: function (message) { // the message is added to the element when it is received. $("ul").append("" + message + ""); poolit(); // link to the re-polling when a message is consumed. }, error: function () { poolit(); // start re-polling if an error occurs. } }); } // when the submit button is clicked; $("button").click(function () { if ($(".nick").css("visibility") === "visible") { // if line is visible; $("textarea").prop("disabled", false); // able to enter data $(".nick").css("visibility", "hidden"); // make line invisible; $("span").html("chat started.."); // information message // polling operation must be initiated at a time poolit(); } else // if it is not the first time ; $.ajax({ type: "post", // http post request url: "/app/chat/" + $("#nick").val(),// access to the sendmessage(..) method. datatype: "text", // incoming data type -> text data: $("textarea").val(), // chat message to send contenttype: "text/plain", // the type of the sent message success: function (data) { $("span").html(data); // it writes [message is sent..] if successful. // blink effect $("span").fadeout('fast', function () { $(this).fadein('fast'); }); } }); }); testing the application because the jetty 9.0.0.rc2 plugin is included in the pom.xml configuration file of the application, the application can be easily run with > mvn jetty:run-war command. the application can be accessed at http://localhost:8080/ after above goal run. you can access source code and live example follow the next url => http://en.kodcu.com/2013/06/jax-rs-2-and-longpolling-based-chat-application/

A lot of times you need to to assign some functionality to some keyboard shortcut like F5 or Ctrl+R in your application. JavaFx also provides KeyCodeCombination API for handling multiple key events. scene.setOnKeyPressed(new EventHandler() { public void handle(final KeyEvent keyEvent) { if (keyEvent.getCode() == KeyCode.F5) { System.out.println("F5 pressed"); //Stop letting it do anything else keyEvent.consume(); } } }); final KeyCombination keyComb1 = new KeyCodeCombination(KeyCode.R, KeyCombination.CONTROL_DOWN); scene.addEventHandler(KeyEvent.KEY_RELEASED, new EventHandler() { @Override public void handle(KeyEvent event) { if (keyComb1.match(event)) { System.out.println("Ctrl+R pressed"); } } });

This technical tip shows how to Add, Delete & Get Attachment in a PDF Document using Aspose.Pdf for Java. In order to add attachment in a PDF document, you need to create a FileSpecification object with the file, which needs to be added, and the file description. After that the FileSpecification object can be added to EmbeddedFiles collection of Document object using add(..) method of EmbeddedFiles collection. The attachments of the PDF document can found in the EmbeddedFiles collection of the Document object. In order to delete all the attachments, you only need to call the delete(..) method of the EmbeddedFiles collection and then save the updated file using save method of the Document object. //Add attachment in a PDF document. //open document com.aspose.pdf.Document pdfDocument = new com.aspose.pdf.Document("input.pdf"); //setup new file to be added as attachment com.aspose.pdf.FileSpecification fileSpecification = new com.aspose.pdf.FileSpecification("sample.txt", "Sample text file"); //add attachment to document's attachment collection pdfDocument.getEmbeddedFiles().add(fileSpecification); // Save updated document containing table object pdfDocument.save("output.pdf"); //Delete all the attachments from the PDF document. //open document com.aspose.pdf.Document pdfDocument = new com.aspose.pdf.Document("input.pdf"); //delete all attachments pdfDocument.getEmbeddedFiles().delete(); //save updated file pdfDocument.save("output.pdf"); //Get an individual attachment from the PDF document. //open document com.aspose.pdf.Document pdfDocument = new com.aspose.pdf.Document("input.pdf"); //get particular embedded file com.aspose.pdf.FileSpecification fileSpecification = pdfDocument.getEmbeddedFiles().get_Item(1); //get the file properties System.out.printf("Name: - " + fileSpecification.getName()); System.out.printf("\nDescription: - " + fileSpecification.getDescription()); System.out.printf("\nMime Type: - " + fileSpecification.getMIMEType()); // get attachment form PDF file try { InputStream input = fileSpecification.getContents(); File file = new File(fileSpecification.getName()); // create path for file from pdf file.getParentFile().mkdirs(); // create and extract file from pdf java.io.FileOutputStream output = new java.io.FileOutputStream(fileSpecification.getName(), true); byte[] buffer = new byte[4096]; int n = 0; while (-1 != (n = input.read(buffer))) output.write(buffer, 0, n); // close InputStream object input.close(); output.close(); } catch (IOException e) { e.printStackTrace(); } // close Document object pdfDocument.dispose();