In this tip you can see how to use the Angular Websocket module for connecting client applications to servers.

Posted by Gilad F on Back& Blog. Current approaches to web development rely upon having two kinds of intelligence built into your application – business intelligence in the server, and presentation intelligence on the client side. This institutes a clear delineation in responsibilities, which is often desirable from an architectural standpoint. However, this approach does have some drawbacks. Processing time for business logic, for example, is centralized on the server. This can introduce bottlenecks in the application’s performance, or add complexity when it comes to cross-server communication. For smaller applications that nonetheless have a large user base, this can often be the single greatest performance concern – the time spent computing solutions by the server. One way this can be offset is through the use of Object-Relational Mapping, or ORM. Below we’ll look at the concept of ORM, and how creating an ORM system in Angular can help make your application smarter. What is an ORM? Simply put, Object-Relational Mapping is the concept of creating representations of your underlying data that know how to manage themselves. Most web applications boil down to four basic actions, known as the “CRUD” approach – Create a record, Retrieve records, Update a record, or Delete a record. With an ORM, you simply encapsulate each of these functions within a class that represents a given record in the database. In essence, the objects you create to represent your data on the front end also know how to manipulate that data on the back end. Why Use an ORM? The primary benefit of an ORM is that it hides a lot of the functional complexity of database integration behind an established API. Communication with the database to implement each of the CRUD methods can be complex, but once it’s been accomplished for one model it can be easily ported to all of the other models in your system. An ORM focuses on hiding as much of this code as possible, allowing your models to care only about how they are represented – and how they interact with other elements in the system. A series of calls to establish a connection to the database, for example, becomes a single call to a method named “Save” on the model instance. This also allows you to centralize your database code, giving you only one location where you need to look for database-related bugs instead of having to search a complex code base for different custom data communication handlers. Why Use an ORM in Angular? While the JavaScript stack is particularly performant when compared to more heavyweight offerings such as Rails and Django, it still faces the issues common to the standard web application architecture – the server has the potential to be a bottleneck, handling the incoming traffic from a number of locations. By focusing your development efforts to create a pure CRUD API in your server, and developing a rudimentary ORM in Angular, you can offload a lot of that processing load to the client machines – in essence parallelizing the process at the expense of increased network communication. This allows you to reduce the overall dependence of your application on the server, making the server a “thin” client that simply updates the database based upon the API calls issued by the client. After a certain point, your back-end can be outsourced completely to an external provider that specializes in providing this type of access – such as Backand – allowing you to completely offload scalability and security concerns. In essence, it allows you to focus on your application as opposed to focusing on the attendant resources. Conclusion Object-Relational Mapping is a powerful paradigm that eases communication with a database for the basic CRUD activities associated with web applications. As most existing web development environments focus on implementing ORM on the server side, this can result in performance and communication bottlenecks – not to mention increased infrastructure costs. By offloading some of these ORM tasks to AngularJS, you can parallelize many of these tasks and reduce overall server load, in some cases obviating the need for the server entirely. If your application is facing a bloated back-end communication pattern, it might be worth your time to look at working towards implementation of a client-side ORM system. Build your Angular app and connect it to any database with Backand today. – Get started now.translate in hindi

In this article I am going to present a solution about sending SMS messages in Java for those developers and marketers who think – like me – that SMS is not dead.

I’ve lost count of the number of times I’ve seen code which fail-fast validates the state of something, using an approach like public class PersonValidator { public boolean validate(Person person) { boolean valid = person != null; if (valid) valid = person.givenName != null; if (valid) valid = person.familyName != null; if (valid) valid = person.age != null; if (valid) valid = person.gender != null; // ...and many more } } It works, but it’s a brute force approach that’s filled with repetition due to the valid check. If your code style enforces braces for if statements (+1 for that), your method is also three times longer and growing every time a new check is added to the validator. Using Java 8’s new stream API, we can improve this by taking the guard condition of if (valid) and making a generic validator that handles the plumbing for you. import java.util.LinkedList; import java.util.List; import java.util.function.Predicate; public class GenericValidator implements Predicate { private final List> validators = new LinkedList<>(); public GenericValidator(List> validators) { this.validators.addAll(validators); } @Override public boolean test(final T toValidate) { return validators.parallelStream() .allMatch(predicate -> predicate.test(toValidate)); } } Using this, we can rewrite the Person validator to be a specification of the required validations. public class PersonValidator extends GenericValidator { private static final List> VALIDATORS = new LinkedList<>(); static { VALIDATORS.add(person -> person.givenName != null); VALIDATORS.add(person -> person.familyName != null); VALIDATORS.add(person -> person.age != null); VALIDATORS.add(person -> person.gender != null); // ...and many more } public PersonValidator() { super(VALIDATORS); } } PersonValidator, and all your other validators, can now focus completely on validation. The behaviour hasn’t changed – the validation still fails fast. There’s no boiler plate, which is A Good Thing. This one’s going in the toolbox.

Traditional web development builds a bridge between the front end, where the user performs their manipulations of the application’s data, and the back end, where that data is stored. In traditional web development, this process is driven by successive networking calls, communicating changes between the server and the client via re-rendering the involved pages. AngularJS enhances this with two-way data binding. Below we’ll look at what two-way data binding is, and how it differs from the traditional data processing approach. The Traditional Approach Most web frameworks focus on one-way data binding. This involves reading the input from the DOM, serializing the data, sending it to the server, waiting for the process to finish, then modifying the DOM to indicate any errors, or reloading the DOM if the call is successful. While this provides a traditional web application all the time it needs to perform data processing, this benefit is only really applicable to web apps with highly complex data structures. If your application has a simpler data format, with relatively flat models, then the extra work can needlessly complicate the process. Furthermore, all models need to wait for server confirmation before their data can be updated, meaning that related data depending upon those models won’t have the latest information. Tying Together the UI and the Model AngularJS addresses this with two-way data binding. With two-way data binding, the user interface changes are immediately reflected in the underlying data model, and vice-versa. This allows the data model to serve as an atomic unit that the view of the application can always depend upon to be accurate. Many web frameworks implement this type of data binding with a complex series of event listeners and event handlers – an approach that can quickly become fragile. AngularJS, on the other hand, makes this approach to data a primary part of its architecture. Instead of creating a series of callbacks to handle the changing data, AngularJS does this automatically without any needed intervention by the programmer Benefits and Considerations The primary benefit of two-way data binding is that updates to (and retrievals from) the underlying data store happen more or less automatically. When the data store updates, the UI updates as well. This allows you to remove a lot of logic from the front-end display code, particularly when making effective use of AngularJS’s declarative approach to UI presentation. In essence, it allows for true data encapsulation on the front-end, reducing the need to do complex and destructive manipulation of the DOM. While this solves a lot of problems with a website’s presentation architecture, there are some disadvantages to take into consideration. First, AngularJS uses a dirty-checking approach that can be slow in some browsers – not a problem for thin presentation pages, but any page with heavy processing may run into problems in older browsers. Additionally, two-way binding is only truly beneficial for relatively simple objects. Any data that requires heavy parsing work, or extensive manipulation and processing, will simply not work well with two-way binding. Additionally, some uses of Angular – such as using the same binding directive more than once – can break the data binding process. Conclusion While the traditional approach to data binding has a lot of benefits when it comes to performing complex data manipulations and calculations, it can introduce some problems with respect to the design of the web application’s front-end architecture. With AngularJS’s use of two-way data binding, your application can greatly simplify its presentation layer, allowing the UI to be built off of a cleaner, less-destructive approach to DOM presentation. While it isn’t useful in every situation, the two-way data binding AngularJS provides can greatly ease web application development, and reduce the pain faced by your front-end developers. Build your Angular app and connect it to any database with Backand today. – Get started now.

Recently I wanted to extract certain data from an output log. Here’s part of the log file: 2015-01-06 11:33:03 b.s.d.task [INFO] Emitting: eVentToRequestsBolt __ack_ack [-6722594615019711369 -1335723027906100557] 2015-01-06 11:33:03 c.s.p.d.PackagesProvider [INFO] ===---> Loaded package com.foo.bar 2015-01-06 11:33:04 b.s.d.executor [INFO] Processing received message source: eventToManageBolt:2, stream: __ack_ack, id: {}, [-6722594615019711369 -1335723027906100557] 2015-01-06 11:33:04 c.s.p.d.PackagesProvider [INFO] ===---> Loaded package co.il.boo 2015-01-06 11:33:04 c.s.p.d.PackagesProvider [INFO] ===---> Loaded package dot.org.biz I decided to do it using the Java8 Stream and Lambda Expression features. Read the file First, I needed to read the log file and put the lines in a Stream: Stream lines = Files.lines(Paths.get(args[1])); Filter relevant lines I needed to get the packages names and write them into another file. Not all lines contained the data I need, hence filter only relevant ones. lines.filter(line -> line.contains("===---> Loaded package")) Parsing the relevant lines Then, I needed to parse the relevant lines. I did it by first splitting each line to an array of Strings and then taking the last element in that array. In other words, I did a double mapping. First a line to an array and then an array to a String. .map(line -> line.split(" ")) .map(arr -> arr[arr.length - 1]) Writing to output file The last part was taking each string and write it to a file. That was the terminal operation. .forEach(package -> writeToFile(fw, package)); writeToFile is a method I created. The reason is that Java File System throws IOException. You can’t use checked exceptions in lambda expressions. Here’s a full example (note, I don’t check input) import java.io.FileWriter; import java.io.IOException; import java.nio.file.Files; import java.nio.file.Paths; import java.util.Arrays; import java.util.List; import java.util.stream.Stream; public class App { public static void main(String[] args) throws IOException { Stream lines = null; if (args.length == 2) { lines = Files.lines(Paths.get(args[1])); } else { String s1 = "2015-01-06 11:33:03 b.s.d.task [INFO] Emitting: adEventToRequestsBolt __ack_ack [-6722594615019711369 -1335723027906100557]"; String s2 = "2015-01-06 11:33:03 b.s.d.executor [INFO] Processing received message source: eventToManageBolt:2, stream: __ack_ack, id: {}, [-6722594615019711369 -1335723027906100557]"; String s3 = "2015-01-06 11:33:04 c.s.p.d.PackagesProvider [INFO] ===---> Loaded package com.foo.bar"; String s4 = "2015-01-06 11:33:04 c.s.p.d.PackagesProvider [INFO] ===---> Loaded package co.il.boo"; String s5 = "2015-01-06 11:33:04 c.s.p.d.PackagesProvider [INFO] ===---> Loaded package dot.org.biz"; List rows = Arrays.asList(s1, s2, s3, s4, s5); lines = rows.stream(); } new App().parse(lines, args[0]); } private void parse(Stream lines, String output) throws IOException { final FileWriter fw = new FileWriter(output); //@formatter:off lines.filter(line -> line.contains("===---> Loaded package")) .map(line -> line.split(" ")) .map(arr -> arr[arr.length - 1]) .forEach(package -> writeToFile(fw, package)); //@formatter:on fw.close(); lines.close(); } private void writeToFile(FileWriter fw, String package) { try { fw.write(String.format("%s%n", package)); } catch (IOException e) { throw new RuntimeException(e); } } } If you enjoyed this article and want to learn more about Java Streams, check out this collection of tutorials and articles on all things Java Streams.

Byte Buddy is a code generation library for creating Java classes during the runtime of a Java application and without the help of a compiler. Other than the code generation utilities that ship with the Java Class Library, Byte Buddy allows the creation of arbitrary classes and is not limited to implementing interfaces for the creation of runtime proxies. In order to use Byte Buddy, one does not require an understanding of Java byte code or the class file format. In contrast, Byte Buddy’s API aims for code that is concise and easy to understand for everybody. Nevertheless, Byte Buddy remains fully customizable down to the possibility of defining custom byte code. Furthermore, the API was designed to be as non-intrusive as possible and as a result, Byte Buddy does not leave any trace in the classes that were created by it. For this reason, the generated classes can exist without requiring Byte Buddy on the class path. Because of this feature, Byte Buddy’s mascot was chosen to be a ghost. Byte Buddy is written in Java 6 but supports the generation of classes for any Java version. Byte Buddy is a light-weight library and only depends on the visitor API of the Java byte code parser library ASM which does itself not require any further dependencies. At first sight, runtime code generation can appear to be some sort of black magic that should be avoided and only few developers write applications that explicitly generate code during their runtime. However, this picture changes when creating libraries that need to interact with arbitrary code and types that are unknown at compile time. In this context, a library implementer must often choose between either requiring a user to implement library-proprietary interfaces or to generate code at runtime when the user’s types becomes first known to the library. Many known libraries such as for example Spring or Hibernate choose the latter approach which is popular among their users under the term of using Plain Old Java Objects. As a result, code generation has become an ubiquitous concept in the Java space. Byte Buddy is an attempt to innovate the runtime creation of Java types in order to provide a better tool set to those relying on code generation. Hello World Saying Hello World with Byte Buddy is as easy as it can get. Any creation of a Java class starts with an instance of the ByteBuddy class which represents a configuration for creating new types: Class dynamicType = new ByteBuddy() .subclass(Object.class) .method(named("toString")).intercept(FixedValue.value("Hello World!")) .make() .load(getClass().getClassLoader(), ClassLoadingStrategy.Default.WRAPPER) .getLoaded(); assertThat(dynamicType.newInstance().toString(), is("Hello World!")); The default ByteBuddy configuration which is used in the above example creatse a Java class in the newest version of the class file format that is understood by the processing Java virtual machine. As hopefully obvious from the example code, the created type will extend the Object class and intercept its toString method which should return a fixed value of Hello World!. The method to be intercepted is identified by a so-called method matcher. In the above example, a predefined method matcher named(String) is used which identifies a method by its exact name. Byte Buddy comes with numerous predefined and well-tested method matchers which are collected in the MethodMatchers class. The creation of custom matchers is however as simple as implementing the (functional) MethodMatcher interface. For implementing the toString method, the FixedValue class defines a constant return value for the intercepted method. Defining a constant value is only one example of many method interceptors that ship with Byte Buddy. By implementing the Instrumentation interface, a method could however even be defined by custom byte code. Finally, the described Java class is created and then loaded into the Java virtual machine. For this purpose, a target class loader is required as well as a class loading strategy where we choose a wrapper strategy. The latter creates a new child class loader which wraps the given class loader and only knows about the newly created dynamic type. Eventually, we can convince ourselves of the result by calling the toString method on an instance of the created class and finding the return value to represent the constant value we expected. Where to go from here? Byte Buddy is a comprehensive library and we only scratched the surface of Byte Buddy's capabilities. However, Byte Buddy aims for being easy to use by providing a domain-specific language for creating classes. Most runtime code generation can be done by writing readable code and without any knowledge of Java's class file format. If you want to learn more about Byte Buddy, you can find such a tutorial on Byte Buddy's web page. Furthermore, Byte Buddy comes with a detailed in-code documentation and extensive test case coverage which can also serve as example code. you can also find the source code of Byte Buddy on GitHub .

History I think it’s important to take a look at the evolution of Interceptors in Java EE because of the simple fact that it started as an EJB-specific item and later evolved into a separate spec which is now open for extension by other Java EE specifications. Version 1.0 Interceptors were first introduced in EJB 3.0 (part of Java EE 5). Interceptors did not have a dedicated spec but they were versioned 1.0 and bought basic AOP related features to managed beans (POJOs) via simple annotations @AroundInvoke – to annotate methods containing the interception logic for target class methods @Intercerptors – to bind the the interceptor classes with their target classes/methods Capability to configure interceptors for an entire module (EJB JAR) via the deployment descriptor @ExcludeDefaultInterceptors – to mute default interceptors defined in the deployment descriptor @ExcludeClassInterceptors – to mute a globally defined (class level) interceptor for a particular method/constructor of the class Interceptors 1.1 Along came Java EE 6 with EJB 3.1 – Interceptors 1.1 was still included in the EJB spec document @InterceptorBinding – a type safe way of specifying interceptors of a class or a method. Please note that this annotation was leveraged by CDI 1.0 (another specification introduced in Java EE 6) and its details are present in the CDI 1.0 spec doc rather than EJB 3.1 (light bulb moment … at least for me) @Interceptor – Used to explicitly declare a class containing an interception logic in a specific method (annotated with @AroundInvoke etc) as an interceptor along with an appropriate Interceptor Binding. This too was mentioned in the CDI 1.0 documentation only. @AroundTimeout – used to intercept time outs of EJB timers along with a way to obtain an instance of the Timer being intercepted (viajavax.interceptor.InvocationContext.getTimer()) Interceptors 1.2 Interceptors were split off into an individual spec in Java EE 7 and thus Interceptors 1.2came into being Interceptors 1.2 was a maintenance release on top of 1.1 and hence the JSR number still remained the same as EJB 3.1 (JSR 318) Interceptor.Priority (static class) – to provide capability to define the order (priority) in which the interceptors need to invoked. @AroundConstruct – used to intercept the construction of the target class i.e. invoke logic prior to the constructor of the target class is invoked It’s important to bear in mind that Interceptors are applicable to managed beans in general. Managed Beans themselves are simple POJOs which are privileged to basic services by the container – Interceptors are one of them along with life cycle callbacks, resource injection. Memory Aid It’s helpful to think of Interceptors as components which can interpose on beans throughout their life cycle before they are even constructed – @AroundConstruct after they are constructed – @PostConstruct during their life time (method invocation) – @AroundInvoke prior to destruction – @PreDestroy time outs of EJBs – @AroundTimeout Let’s look at some of the traits of Interceptors in more detail and try to answer questions like where are they applied and what do they intercept ? how to bind interceptors to the target (class) they are supposed to intercept ? Interceptors Types (based on the intercepted component) Method Interceptors Achieved by @AroundInvoke public class MethodInterceptor{ @AroundInvoke public Object interceptorMethod(InvocationContext ictx) throws Exception{ //logic goes here } } @Stateless public class AnEJB{ @Interceptors(MethodInterceptor.class) public void bizMethod(){ //any calls to this method will be intercepted by MethodInterceptor.interceptorMethod() } } The method containing the logic can be part of separate class as well as the target class (class to be intercepted) itself. Lifecycle Callback interceptors Decorate the method with @AroundConstruct in order to intercept the constructor invocation for a class public class ConstructorInterceptor{ @AroundConstruct public Object interceptorMethod(InvocationContext ictx) throws Exception{ //logic goes here } } public class APOJO{ @Interceptors(ConstructorInterceptor.class) public APOJO(){ //any calls to this constructor will be intercepted by ConstructorInterceptor.interceptorMethod() } } The method annotated with @AroundConstruct cannot be a part of the intercepted class. It has to be defined using a separate Interceptor class Use the @PostConstruct annotation on a method in order to intercept a call back method on a managed bean. Just to clarify again – the Interceptor spec does not define a new annotation as such. One needs to reuse the @PostConstruct (part of theCommon Annotations spec) on the interceptor method. public class PostConstructInterceptor{ @PostConstruct public void interceptorMethod(InvocationContext ictx) throws Exception{ //logic goes here } } @Interceptors(PostConstructInterceptor.class) public class APOJO{ @PostConstruct public void bizMethod(){ //any calls to this method will be intercepted by PostConstructInterceptor.interceptorMethod() } } The @PreDestroy (another call back annotation defined in Common Annotations spec) annotation is used in a similar fashion Time-out Interceptors As mentioned above – @AroundTimeout used to intercept time outs of EJB timers along with a way to obtain an instance of the Timer being intercepted (viajavax.interceptor.InvocationContext.getTimer()) Applying/Binding Interceptors Using @Interceptors As shown in above examples – just use the @Interceptors annotation to specify the interceptor classes @Interceptors can be applied on a class level (automatically applicable to all the methods of a class), to a particular method or multiple methods and constructor in case of a constructor specific interceptor using @AroundConstruct Using @IntercerptorBinding Interceptor Bindings (explained above) – Use @IntercerptorBinding annotation to define a binding annotation which is further used on the interceptor class as well as the target class (whose method, constructor etc needs to be intercepted) @InterceptorBinding @Target({TYPE, METHOD, CONSTRUCTOR}) @Retention(RUNTIME) public @interface @Auditable { } @Auditable @Interceptor public class AuditInterceptor { @AroundInvoke public Object audit(InvocationContext ictx) throws Exception{ //logic goes here } } @Stateless @Auditable public class AnEJB{ public void bizMethod(){ //any calls to this method will be intercepted by AuditInterceptor.audit() } } Deployment Descriptor One can also use deployment descriptors to bind interceptors and target classes either in an explicit fashion as well as in override mode to annotations. This was a rather quick overview of Java EE interceptors. Hopefully the right trigger for you to dig deeper :-) Cheers !

API Management? Did you say “API Management?” Software application development models are evolutionary things. New technologies are always being created and require new approaches. It’s frequently the case today, that a service oriented architecture (SOA) model is used and that the end product is a software service that can be used by applications. The explosion in growth of mobile devices has only accelerated this trend. Every new mobile phone sold is another platform onto which applications are deployed. These applications are often built from services provided from multiple sources. The applications often consume these services through their APIs. OK, that’s all interesting, but why does this matter? Here’s why: If you are providing a service, you’d probably like to receive payment when it’s used by an application. For example, let’s say that you’ve spent months creating a new service that provides incredibly accurate and timely driving directions. You can imagine every mobile phone GPS app making use of your service someday. That is, however, assuming that you can find a way to enforce a contract on consumers of the API and provide them with a service level agreement (SLA). Also, you have to find a way to actually track consumers’ use of the API so that you can actually enforce that SLA. Finally, you have to have the means to update a service and publish new versions of services. Likewise, if you are consuming a service, for example, if you want to build the killer app that will use that cool new mapping service, you have to have the means to find the API, identify the API’s endpoint, and register your usage of the API with its provider. The approach that is followed to fulfill both service providers’ and consumers’ needs is...API Management. JBoss apiman 1.0 apiman is JBoss’ open source API Management system. apiman fulfills service API providers’ and consumers’ needs by implementing: API Manager - The API Manager provides an easy way for API/service providers to use a web UI to define service contracts for their APIs, apply these contracts across multiple APIs, and control role-based user access and API versioning. These contracts can govern access to services and limits on the rate at which consumers can access services. The same UI enables API consumers to easily locate and access APIs. API Gateway - The gateway applies the service contract policies of API Management by enforcing at runtime the rules defined in the contracts and tracking the service API consumers’ use of the APIs for every request made to the services. The way that the API Gateway works is that the consumer of the service accesses the service through a URL that designates the API Gateway as a proxy for the service. If the policies defined to govern access to the service (see a later section in this post for a discussion of apiman polices), the API Gateway then proxies requests to the service’s backend API implementation. The best way to understand API Management with apiman is to see it in action. In this post, we’ll install apiman 1.0, configure an API with contracts through the API Manager, and watch the API Gateway control access to the API and track its use. Prerequisites We don’t need very much to run apiman out of the box. Before we install apiman, you’ll have to have Java (version 1.7 or newer) installed on your system. You’ll also need to git and maven installed to be able to build the example service that we’ll use. A note on software versions: In this post we’ll use the latest available version of apiman as of December 2014. As if this writing, version 1.0 of apiman was just released (December 2014). Depending on the versions of software that you use, some screen displays may look a bit different. Getting apiman Like all JBoss software, installation of apiman is simple. First, you will need an application server on which to install and run apiman. We’ll use the open source JBoss WildFly server release 8.2 (http://www.wildfly.org/). To make things easier, apiman includes a pointer to JBoss WildFly on its download page here: http://www.apiman.io/latest/download.html To install WildFly, simply download http://download.jboss.org/wildfly/8.2.0.Final/wildfly-8.2.0.Final.zip and unzip the file into the directory in which you want to run the sever. Then, download the apiman 1.0 WildFly overlay zip file inside the directory that was created when you un-zipped the WildFly download. The apiman 1.0 WildFly overlay zip file is available here: http://downloads.jboss.org/overlord/apiman/1.0.0.Final/apiman-distro-wildfly8-1.0.0.Final-overlay.zip The commands that you will execute will look something like this: mkdir apiman cd apiman unzip wildfly-8.2.0.Final.zip unzip -o apiman-distro-wildfly8-1.0.0.Final-overlay.zip -d wildfly-8.2.0.Final Then, to start the server, execute these commands: cd wildfly-8.2.0.Final ./bin/standalone.sh -c standalone-apiman.xml The server will write logging messages to the screen. When you see some messages that look like this, you’ll know that the server is up and running with apiman installed: 13:57:03,229 INFO [org.jboss.as.server] (ServerService Thread Pool -- 29) JBAS018559: Deployed "apiman-ds.xml" (runtime-name : "apiman-ds.xml") 13:57:03,261 INFO [org.jboss.as] (Controller Boot Thread) JBAS015961: Http management interface listening on http://127.0.0.1:9990/management 13:57:03,262 INFO [org.jboss.as] (Controller Boot Thread) JBAS015951: Admin console listening on http://127.0.0.1:9990 13:57:03,262 INFO [org.jboss.as] (Controller Boot Thread) JBAS015874: WildFly 8.2.0.Final "Tweek" started in 5518ms - Started 754 of 858 services (171 services are lazy, passive or on-demand) If this were a production server, the first thing that we’d do is to change the OOTB default admin username and/or password. apiman is configured by default to use JBoss KeyCloak (http://keycloak.jboss.org/) for password security. Also, the default database used by apiman to store contract and service information is the H2 database. For a production server, you’d want to reconfigure this to use a production database. Note: apiman includes DDLs for both MySQL and PostgreSQL. For the purposes of our demo, we’ll keep things simple and use the default configuration. To access apiman’s API Manager UI, go to: http://localhost:8080/apiman-manager, and log in. The admin user account that we’ll use has a username of “admin” and a password of “admin123!” You should see a screen that looks like this: Before we start using apiman, let’s take a look at how apiman defines how services and the meta data on which they depend are organized. Policies, Plans, and Organizations apiman uses a hierarchical data model that consists of these elements: Polices, Plans, and Organizations: Policies Policies are at the lowest level of the data model, and they are the basis on which the higher level elements of the data model are built. A policy defines an action that is performed by the API Gateway at runtime. Everything defined in the API Manager UI is there to enable apiman to apply policies to requests made to services. When a request to a service is made, apiman creates a chain of policies to be applied to that request. apiman policy chains define a specific sequence order in which the policies defined in the API Manager UI are applied to service requests. The sequence in which incoming service requests have policies applied is: First, at the application level. In apiman, an application is contracted to use one or more services. Second, at the plan level. In apiman, policies are organized into groups called plans. (We’ll discuss plans in the next section of this post.) Third, at the individual service level. What happens is that when a service request is received by the API Gateway at runtime, the policy chain is applied in the order of application, plan, and service. If no failures, such as a rate counter being exceeded, occur, the API Gateway sends the request to the service’s backend API implementation. As we mentioned earlier in this post, the API Gateway acts as a proxy for the service: Next, when the API Gateway receives a response from the service’s backend implementation, the policy chain is applied again, but this time in the reverse order. The service policies are applied first, then the plan policies, and finally the application policies. If no failures occur, then the service response is sent back to the consumer of the service. By applying the policy chain twice, both for the originating incoming request and the resulting response, apiman allows policy implementations two opportunities to provide management functionality during the lifecycle. The following diagram illustrates this two-way approach to applying policies: Plans In apiman, a “plan” is a set policies that together define the level of service that apiman provides for service. Plans enable apiman users to define multiple different levels of service for their APIs, based on policies. It’s common to define different plans for the same service, where the differences depend on configuration options. For example, a group or company may offer both a “gold” and “silver” plan for the same service. The gold plan may be more expensive than the silver plan, but it may offer a higher level of service requests in a given (and configurable) time period. Organizations The “organization” is at top level of the apiman data model. An organization contains and manages all elements used by a company, university, group inside a company, etc. for API management with apiman. All plans, services, applications, and users for a group are defined in an apiman organization. In this way, an organization acts as a container of other elements. Users must be associated with an organization before they can use apiman to create or consume services. apiman implements role-based access controls for users. The role assigned to a user defines the actions that a user can perform and the elements that a user can manage. Before we can define a service, the policies that govern how it is accessed, the users who will be able to access, and the organizations that will create and consume it, we need a service and a client to access that service. Luckily, creating the service and deploying it to our WildFly server, and accessing it through a client are easy. Getting and Building and Deploying the Example Service The source code for the example service is contained in a git repo (http://git-scm.com) hosted at github (https://github.com/apiman). To download a copy of the example service, navigate to the directory in which you want to build the service and execute this git command: git clone [email protected]:apiman/apiman-quickstarts.git As the source code is downloading, you'll see output that looks like this: git clone [email protected]:apiman/apiman-quickstarts.git Initialized empty Git repository in /tmp/tmp/apiman-quickstarts/.git/ remote: Counting objects: 104, done. remote: Total 104 (delta 0), reused 0 (delta 0) Receiving objects: 100% (104/104), 18.16 KiB, done. Resolving deltas: 100% (40/40), done. And, after the download is complete, you'll see a populated directory tree that looks like this: └── apiman-quickstarts ├── echo-service │ ├── pom.xml │ ├── README.md │ └── src │ └── main │ ├── java │ │ └── io │ │ └── apiman │ │ └── quickstarts │ │ └── echo │ │ ├── EchoResponse.java │ │ └── EchoServlet.java │ └── webapp │ └── WEB-INF │ ├── jboss-web.xml │ └── web.xml ├── LICENSE ├── pom.xml ├── README.md ├── release.sh └── src └── main └── assembly └── dist.xml As we mentioned earlier in the post, the example service is very simple. The only action that the service performs is to echo back in responses the meta data in the REST (http://en.wikipedia.org/wiki/Representational_state_transfer) requests that it receives. Maven is used to build the service. To build the service into a deployable .war file, navigate to the directory into which you downloaded the service example: cd apiman-quickstarts/echo-service And then execute this maven command: mvn package As the service is being built into a .war file, you'll see output that looks like this: [INFO] Scanning for projects... [INFO] [INFO] Using the builder org.apache.maven.lifecycle.internal.builder.singlethreaded.SingleThreadedBuilder with a thread count of 1 [INFO] [INFO] ------------------------------------------------------------------------ [INFO] Building apiman-quickstarts-echo-service 1.0.1-SNAPSHOT [INFO] ------------------------------------------------------------------------ [INFO] [INFO] --- maven-resources-plugin:2.6:resources (default-resources) @ apiman-quickstarts-echo-service --- [INFO] Using 'UTF-8' encoding to copy filtered resources. [INFO] skip non existing resourceDirectory /jboss/local/redhat_git/apiman-quickstarts/echo-service/src/main/resources [INFO] [INFO] --- maven-compiler-plugin:2.5.1:compile (default-compile) @ apiman-quickstarts-echo-service --- [INFO] Compiling 2 source files to /jboss/local/redhat_git/apiman-quickstarts/echo-service/target/classes [INFO] [INFO] --- maven-resources-plugin:2.6:testResources (default-testResources) @ apiman-quickstarts-echo-service --- [INFO] Using 'UTF-8' encoding to copy filtered resources. [INFO] skip non existing resourceDirectory /jboss/local/redhat_git/apiman-quickstarts/echo-service/src/test/resources [INFO] [INFO] --- maven-compiler-plugin:2.5.1:testCompile (default-testCompile) @ apiman-quickstarts-echo-service --- [INFO] No sources to compile [INFO] [INFO] --- maven-surefire-plugin:2.12.4:test (default-test) @ apiman-quickstarts-echo-service --- [INFO] No tests to run. [INFO] [INFO] --- maven-war-plugin:2.2:war (default-war) @ apiman-quickstarts-echo-service --- [INFO] Packaging webapp [INFO] Assembling webapp in [/jboss/local/redhat_git/apiman-quickstarts/echo-service/target/apiman-quickstarts-echo-service-1.0.1-SNAPSHOT] [INFO] Processing war project [INFO] Copying webapp resources [/jboss/local/redhat_git/apiman-quickstarts/echo-service/src/main/webapp] [INFO] Webapp assembled in [23 msecs] [INFO] Building war: /jboss/local/redhat_git/apiman-quickstarts/echo-service/target/apiman-quickstarts-echo-service-1.0.1-SNAPSHOT.war [INFO] WEB-INF/web.xml already added, skipping [INFO] ------------------------------------------------------------------------ [INFO] BUILD SUCCESS [INFO] ------------------------------------------------------------------------ [INFO] Total time: 1.184 s [INFO] Finished at: 2014-12-26T16:11:19-05:00 [INFO] Final Memory: 14M/295M [INFO] ------------------------------------------------------------------------ If you look closely, near the end of the output, you'll see the location of the .war file: /jboss/local/redhat_git/apiman-quickstarts/echo-service/target/apiman-quickstarts-echo-service-1.0.1-SNAPSHOT.war To deploy the service, we can copy the .war file to our WildFly server's "deployments" directory. After you copy the service's .war file to the deployments directory, you'll see output like this generated by the WildFly server: 16:54:44,313 INFO [org.jboss.as.server.deployment] (MSC service thread 1-7) JBAS015876: Starting deployment of "apiman-quickstarts-echo-service-1.0.1-SNAPSHOT.war" (runtime-name: "apiman-quickstarts-echo-service-1.0.1-SNAPSHOT.war") 16:54:44,397 INFO [org.wildfly.extension.undertow] (MSC service thread 1-16) JBAS017534: Registered web context: /apiman-echo 16:54:44,455 INFO [org.jboss.as.server] (DeploymentScanner-threads - 1) JBAS018559: Deployed "apiman-quickstarts-echo-service-1.0.1-SNAPSHOT.war" (runtime-name : "apiman-quickstarts-echo-service-1.0.1-SNAPSHOT.war") Make special note of this line of output: 16:54:44,397 INFO [org.wildfly.extension.undertow] (MSC service thread 1-16) JBAS017534: Registered web context: /apiman-echo This output indicates that the URL of the deployed example service is: [a href="http://localhost:8080/apiman-echo" style="text-decoration: none;"]http://localhost:8080/apiman-echo Remember, however, that this is the URL of the deployed example service if we access it directly. We'll refer to this as the "unmanaged service" as we are able to connect to the service directly, without going through the API Gateway. The URL to access the service through the API Gateway ("the managed service") at runtime will be different. Now that our example service is installed, it’s time to install and configure our client to access the server. Accessing the Example Service Through a Client There are a lot of options available when it comes to what we can use for a client to access our service. We’ll keep the client simple so that we can keep our focus on apiman and simply install a REST client into the FireFox browser. The REST Client FireFox add-on (http://restclient.net/) is available here: https://addons.mozilla.org/en-US/firefox/addon/restclient/versions/2.0.3 After you install the client into FireFox, you can access the deployed service using the URL that we just defined. If you execute a GET command, you’ll see output that looks like this: Now that our example service is built, deployed and running, it’s time to create the organizations for the service provider and the service consumer. The differences between the requirements of the two organizations will be evident in their apiman configuration properties. Creating Users for the Service Provider and Consumer Before we create the organizations, we have to create a user for each organization. We'll start by creating the service provider user. To do this, logout from the admin account in the API Manager UI. The login dialog will then be displayed. Select the "New user" Option and register the service provider user: Then, logout and repeat the process to register a new application developer user too: Now that the new users are registered we can create the organizations. Creating the Service Producer Organization To create the service producer organization, log back into the API Manager UI as the servprov user and select “Create a new Organization”: Select a name and description for the organization, and press “Create Organization”: And, here’s our organization: Note that in a production environment, users would request membership in an organization. The approval process for accepting new members into an organization would follow the organization's workflow, but this would be handled outside of the API Manager. For the purposes of our demonstration, we'll keep things simple. Configuring the Service, its Policies, and Plans To configure the service, we’ll first create a plan to contain the policies that we want applied by the API Gateway at runtime when requests to the service are made. To create a new plan, select the “Plans” tab. We’ll create a “gold” plan: Once the plan is created, we will add policies to it: apiman provides several OOTB policies. Since we want to be able to demonstrate a policy being applied, we’ll select a Rate Limiting Policy, and set its limit to a very low level. If our service receives more than 10 requests in a day, the policy should block all subsequent requests. So much for a “gold” level of service! After we create the policy and add it to the plan, we have to lock the plan: And, here is the finished, and locked plan: At this point, additional plans can be defined for the service. We’ll also create a “silver” plan, that will offer a lower level of service (i.e., a request rate limit lower than 10 per day) than the gold plan. Since the process to create this silver plan is identical to that of the gold plan, we’ll skip the screenshots. Now that the two plans are complete and locked, it’s time to define the service. We’ll give the service an appropriate name, so that providers and consumers alike will be able to run a query in the API Manager to find it. After the service is defined, we have to define its implementation. In the context of the API Manager, the API Endpoint is the service’s direct URL. Remember that the API Gateway will act as a proxy for the service, so it must know the service’s actual URL. In the case of our example service, the URL is: http://localhost:8080/apiman-echo The plans tab shows which plans are available to be applied to the service: Let’s make our service more secure by adding an authentication policy that will require users to login before they can access the service. Select the Policies tab, and then define a simple authentication policy. Remember the user name and password that you define here as we’ll need them later on when send requests to the service. After the authentication policy is added, we can publish the service to the API Gateway: And, here it is, the published service: OK, that finishes the definition of the service provider organization and the publication of the service. Next, we'll switch over to the service consumer side and create the service consumer organization and register an application to connect to the managed service through the proxy of the API Gateway. The Service Consumer Organization We'll repeat the process that we used to create the application development organization. Log in to the API Manager UI as the “appdev” user and create the organization: Unlike the process we used when we created the elements used by the service provider, the first step that we’ll take is to create a new application and then search for the service to be used by the application: Searching for the service is easy, as we were careful to set the service name to something memorable: Select the service name, and then specify the plan to be used. We’ll splurge and use the gold plan: Next, select “create contract” for the plan: Then, agree to the contract terms (which seem to be written in a strange form of Latin in the apiman 1.0 release): The last step is to register the application with the API Gateway so that the gateway can act as a proxy for the service: Congratulations! All the steps necessary to provide and consume the service are complete! There’s just one more step that we have to take in order for clients to be able access the service through the API Gateway. Remember the URL that we used to access the unmanaged service directly? Well, forget it. In order to access the managed service through the API Gateway acting as a proxy for other service we have to obtain the managed service's URL. In the API Manager UI, head on over to the "APIs" tab for the application, click on the the “>” character to the left of the service name. This will expose the API Key and the service’s HTTP endpoint in the API Gateway: In order to be able access the service through the API Gateway, we have to provide the API Key with each request. The API Key can be provided either through an HTTP Header (X-API-Key) or a URL query parameter. Luckily, the API Manager UI does the latter for us. Select the icon to the right of the HTTP Endpoint and this dialog is displayed: Copy the URL into the clipboard. We’ll need to enter this into the client in a bit. The combined API Key and HTTP endpoint should look something like this: http://localhost:8080/apiman-gateway/ACMEServices/echo/1.0?apikey=c374c202-d4b3-4442-b9e4-c6654f406e3d Accessing the Managed Service Through the apiman API Gateway, Watching the Policies at Runtime Thanks for hanging in there! The set up is done. Now, we can fire up the client and watch the policies in action as they are applied at runtime by the API Gateway, for example: Open the client, and enter the URL for the managed service (http://localhost:8080/apiman-gateway/ACMEServices/echo/1.0?apikey=c374c202-d4b3-4442-b9e4-c6654f406e3d) What happens first is that the authentication policy is applied and a login dialog is then displayed: Enter the username and password (user1/password) that we defined when we created the authentication policy to access the service. The fact that you are seeing this dialog confirms that you are accessing the managed service and are not accessing the service directly. When you send a GET request to the service, you should see a successful response: So far so good. Now, send 10 more requests and you will see a response that looks like this as the gold plan rate limit is exceeded: And there it is. Your gold plan has been exceeded. Maybe next time you’ll spend a little more and get the platinum plan! ;-) Wrap-up Let’s recap what we just accomplished in this demo: We installed apiman 1.0 onto a WildFly server instance. We used git to download and maven to build a sample REST client. As a service provider, we created an organization, defined policies based on service use limit rates and user authentication, and a plan, and assigned them to a service. As a service consumer, we searched for and found that service, and assigned it to an application. As a client, we accessed the service and observed how the API Gateway managed the service. And, if you note, in the process of doing all this, the only code that we had to write or build was for the client. We were able to fully configure the service, policies, plans, and the application in the API Manager UI. What’s Next? In this post, we’ve only scratched the surface of API Management with apiman. To learn more about apiman, you can explore its website here: http://www.apiman.io/ Join the project mailing list here: https://lists.jboss.org/mailman/listinfo/apiman-user And, better still, get involved! Contribute bug reports or feature requests. Write about your own experiences with apiman. Download the apiman source code, take a look around, and contribute your own additions. apiman 1.0 was just released, there’s no better time to join in and contribute! Acknowledgements The author would like to acknowledge Eric Wittmann for his (never impatient) review comments and suggestions on writing this post! Downloads Used in this Article REST Client (http://restclient.net/) FireFox Add-On - https://addons.mozilla.org/en-US/firefox/addon/restclient/versions/2.0.3 Echo service source code - https://github.com/EricWittmann/apiman-quickstarts apiman 1.0 - http://downloads.jboss.org/overlord/apiman/1.0.0.Final/apiman-distro-wildfly8-1.0.0.Final-overlay.zip WildFly 8.2.0 - http://download.jboss.org/wildfly/8.2.0.Final/wildfly-8.2.0.Final.zip Git - http://git-scm.com Maven - http://maven.apache.org References http://www.apiman.io/ apiman tutorial videos - https://vimeo.com/user34396826 http://www.softwareag.com/blog/reality_check/index.php/soa-what/what-is-api-management/ http://keycloak.jboss.org/

This article represents facts on what would it take to build one or more jar files for a given framework/library using Maven, provided the framework’s downloadable files consisted of pom.xml. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. So far, whenever I came across pom.xml file in the framework that I downloaded in order to get the jar file, I hated it. I used to, then, go to internet and get the compiled jar file(s) for the framework/library. And, good thing is that I have been able to get my work done. This was purely out of my laziness that I did not use to build using maven.Then, I got a chance to work with Twitter HBC library (Java) for integrating with Twitter. And, I downloaded it and wanted to get one or more jar files. And, once again, I came across apom.xml in root folder and unique pom.xml files in hbc-core, hbc-twitter4j and hbc-examples folder. This time, I decided to build the hbc jar files on my system.Following are some of the steps I took to build hbc jar files and get dependencies to run the program using hbc jar files. Download and install Maven. Anyone wanting to install/configure Maven, go to this Maven in 5 Minutes page. It clearly states what needs to be done to install/configure Maven. Once configured, open a command prompt and execute command “mvn -version”. If the version information of Maven is displayed, you are all set. Once determined, go to the folder which consists of pom.xml file. In present case, go to hbc root folder. Go to hbc root folder, hbc-master. Execute following command to build the hbc jar files and also obtain the dependencies (jar files) required to run the library. Command is “mvn clean install -U dependency:copy-dependencies“. This command built the source file and created two different jar files in hbc-twitter4j/target (hbc-twitter4j-2.2.1-SNAPSHOT.jar) and hbc-core/target (hbc-core-2.2.1-SNAPSHOT.jar). Further to that, it downloaded all the dependent jar files in repective target/dependency folder.

Recently at DevSKiller.com we've decided to move majority of our stuff to simple containers. It was pretty easy due to use of Spring Boot uber-jars, but the problem was in NewRelic agents which should have to be included separately. That caused uncomfortable situation so we decided to solve it by including NewRelic agent into our uber-jar applications. If you also want to simplify your life please follow provided instructions :) At first we have to add proper dependency into our pom.xml descriptor: com.newrelic.agent.java< newrelic-agent 3.12.1 provided Now since we have proper jar included into our project it's time to unpack the dependency to have all necessary classes in our application jar file: org.apache.maven.plugins maven-dependency-plugin 2.9 prepare-package unpack-dependencies newrelic-agent ${project.build.outputDirectory} After this step we've all agent related classes accessible directly from our jar. But still the file cannot be used as an agent jar. There are some important manifest entries that have to be present in every agent jar. The most important is the Premain-Class attribute specifying main agent class including premain() method. In case of NewRelic it's also important to include Can-Redefine-Classes and Can-Retransform-Classes attributes. The easiest way to do that is to extend maven-jar-plugin configuration: org.apache.maven.plugins maven-jar-plugin 2.5 com.newrelic.bootstrap.BootstrapAgent true true Now is coming the tricky part :) NewRelic agent also contains class with main() method which causes that Spring Boot repackager plugin is unable to find single main() method so build fails. It's not a problem but we have to remember to specify proper main class in spring-boot-maven-plugin (or in gradle plugin): my.custom.Application That's all! You can execute your application with following command: java -javaagent:myapp.jar -jar myapp.jar Last but not least: don't forget to include NewRelic configuration file (newrelic.yml) in the same directory as your application jar. The other solution is to set newrelic.config.file system property to point the fully qualified file name.

One of the goals of JBoss AS7 was to make it much more secure by default, when compared to previous versions. One of the areas which was directly impacted by this goal was that you could no longer expect the server to expose some service on a port and get access to it without any authentication/authorization. Remember that in previous versions of JBoss AS you could access the JNDI port, the JMX port without any authentication/authorization, as long as those ports were opened for communication remotely. Finer grained authorizations on such ports for communications, in JBoss AS7, allows the server to control who gets to invoke operations over that port. Of course, this is not just limited to JBoss AS7 but continues to be the goal in WildFly (which is the rename of JBoss Application Server). In fact, WildFly has gone one step further and now has the feature of "one single port" for all communication. JMX communication in JBoss AS7 and WildFly With that background, we'll now focus on JMX communication in JBoss AS7 and WildFly. I'll use WildFly (8.2.0 Final) as a reference for the rest of this article, but the same details apply (with minor changes) to other major versions of JBoss AS7 and WildFly, that have been released till date. WildFly server is composed of "subsystems", each of which expose a particular set of functionality. For example, there's the EE subsystem which supports the Java EE feature set. Then there's the Undertow subsystem which supports web/HTTP server functionality. Similarly, there's a JMX subsystem which exposes the JMX feature set on the server. As you all are aware, I'm sure, JMX service is standardly used for monitoring and even managing Java servers and this includes managing the servers remotely. The JMX subsystem in WildFly allows remote access to the JMX service and port 9990 is what is used for that remote JMX communication. JConsole for remote JMX access against JBoss AS7 and WildFly Java (JDK) comes bundled with the JConsole tool which allows connecting to local or remote Java runtimes which expose the JMX service. The tool is easy to use, all you have to do is run the jconsole command it will show up a graphical menu listing any local Java processes and also an option to specify a remote URL to connect to a remote process: # Start the JConsole $JAVA_HOME/bin/jconsole Let's assume that you have started WildFly standalone server, locally. Now when you start the jconsole, you'll notice that the WildFly Java process is listed in the local running processes to which you can connect to. When you select the WildFly Java instance, you'll be auto connected to it and you'll notice MBeans that are exposed by the server. However, in the context of this article, this "local process" mode in JConsole isn't what we are interested in. Let's use the "Remote process" option in that JConsole menu which allows you to specify the remote URL to connect to the Java runtime and username and password to use to connect to that instance. Even though our WildFly server is running locally, we can use this "Remote process" option to try and connect to it. So let's try it out. Before that though, let's consider a the following few points: Remember that the JMX subsystem in WildFly allows remote access on port 9990 For remote access to JMX, the URL is of the format - service:jmx:[vendor-specific-protocol]://[host]:[port]. The vendor specific protocol is the interesting bit here. In the case of WildFly that vendor-specific-protocol is http-remoting-jmx. Remember that WildFly is secure by default which means that just because the JMX subsystem exposes 9990 port for remote communication, it doesn't mean it's open for communication to anyone. In order to be allowed to communicate over this port, the caller client is expected to be authenticated and authorized. This is backed by the "ManagementRealm" in WildFly. Users authenticated and authorized against this realm are allowed access to that port. Keeping those points in mind, let's first create a user in the Management Realm. This can be done using the add-user command line script (which is present in JBOSS_HOME/bin folder). I won't go into the details of that since there's enough documentation for that. Let's just assume that I created a user named "wflyadmin" with an appropriate password in the Management Realm. To verify that the user has been properly created, in the right realm, let's access the WildFly admin console at the URL http://localhost:9990/console. You'll be asked for username and password for access. Use the same username and password of the newly created user. If the login works, then you are good. If not, then make sure you have done things right while adding the new user (as I said I won't go into the details of adding a new user since it's going to just stretch this article unnecessarily long). So at this point we have created a user named "wflyadmin" belonging to ManagementRealm. We'll be using this same user account for accessing the JMX service on WildFly, through JConsole. So let's now bring up the jconsole as usual: $JAVA_HOME/bin/jconsole On the JConsole menu let's again select the "Remote process" option and use the following URL in the URL text box: service:jmx:http-remoting-jmx://localhost:9990 Note: For JBoss AS 7.x and JBoss EAP 6.x, the vendor specific protocol is remoting-jmx and the port for communication is 9999. So the URL will be service:jmx:remoting-jmx://localhost:9999 In the username and password textboxes, use the same user/pass that you newly created. Finally, click on Connect. What do you see? It doesn't work! The connection fails. So what went wrong? Why isn't the JConsole remote access to WildFly not working? You did all the obvious things necessary to access the WildFly JMX service remotely but you keep seeing that JConsole can't connect to it. What could be the reason? Remember, in one of those points earlier, I noted that the "vendor specific protocol" is an interesting bit? We use http-remoting-jmx and that protocol internally relies on certain WildFly/JBoss specific libraries, primarily for remote communication and authentication and authorization. These libraries are WildFly server specific and hence aren't part of the standard Java runtime environment. When you start jconsole, it uses a standard classpath which just has the relevant libraries that are part of the JDK/JRE. To solve this problem, what you need to do is bring in the WildFly server specific libraries into the classpath of JConsole. Before looking into how to do that, let's see which are the WildFly specific libraries that are needed. All the necessary classes for this to work are part of the jboss-cli-client.jar which is present in JBOSS_HOME/bin/client/ folder. So all we need to do in include this jar in the classpath of the jconsole tool. To do that we use the -J option of jconsole tool which allows passing parameters to the Java runtime of jconsole. The command to do that is: $JAVA_HOME/bin/jconsole -J-Djava.class.path=$JAVA_HOME/lib/tools.jar:$JAVA_HOME/lib/jconsole.jar:/opt/wildfly-8.2.0.Final/bin/client/jboss-cli-client.jar (Note that for Windows the classpath separator is the semi-colon character instead of the colon) Note, the server specific jar for JBoss AS 7.x and JBoss EAP 6.x is named jboss-client.jar and is present at the same JBOSS_HOME/bin/client directory location. So we are passing -Djava.class.path as the parameter to the jconsole Java runtime, using the -J option. Notice that we have specified more than just our server specific jar in that classpath. That's because, using the -Djava.class.path is expected to contain the complete classpath. We are including the jars from the Java JDK lib folder that are necessary for JConsole and also our server specific jar in that classpath. Running that command should bring up JConsole as usual and let's go ahead and select the "Remote process" option and specify the same URL as before: service:jmx:http-remoting-jmx://localhost:9990 and the same username and password as before and click Connect. This time you should be able to connect and should start seeing the MBeans and others services exposed over JMX. How about providing a script which does this necessary classpath setup? Since it's a common thing to try and use JConsole for remote access against WildFly, it's reasonable to expect to have a script which sets up the classpath (as above) and you could then just use that script. That's why WildFly ships such a script. It's in the JBOSS_HOME/bin folder and is called jconsole.sh (and jconsole.bat for Windows). This is just a wrapper script which internally invokes the jconsole tool present in Java JDK, after setting up the classpath appropriately. All you have to do is run: $JBOSS_HOME/bin/jconsole.sh What about using JConsole from a really remote machine, against WildFly? So far we were using the jconsole tool that was present on the same machine as the WildFly instance, which meant that we have filesystem access to the WildFly server specific jars present in the WildFly installation directory on the filesystem. This allowed us to setup the classpath for jconsole to point to the jar on the local filesystem? What if you wanted to run jconsole from a remote machine against a WildFly server which is installed and running on a different machine. In that case, your remote client machine won't be having filesystem access to the WildFly installation directory. So to get jconsole running in such a scenario, you will have to copy over the JBOSS_HOME/bin/jboss-cli-client.jar to your remote client machine, to a directory of your choice and then setup the classpath for jconsole tool as explained earlier and point it to that jar location. That should get you access to JMX services of WildFly from jconsole on a remote machine. More questions? If you still have problems getting this to work or have other questions, please start a discussion in the JBoss community forums here https://developer.jboss.org/en/wildfly/content.

I was recently asked about the benefits and wisdom of using off heap memory in Java. The answers may be of interest to others facing the same choices. Off heap memory is nothing special. The thread stacks, application code, NIO buffers are all off heap. In fact in C and C++, you only have unmanaged memory as it does not have a managed heap by default. The use of managed memory or "heap" in Java is a special feature of the language. Note: Java is not the only language to do this. new Object() vs Object pool vs Off Heap memory. new Object() Before Java 5.0, using object pools was very popular. Creating objects was still very expensive. However, from Java 5.0, object allocation and garbage cleanup was made much cheaper, and developers found they got a performance speed up and a simplification of their code by removing object pools and just creating new objects whenever needed. Before Java 5.0, almost any object pool, even an object pool which used objects provided an improvement, from Java 5.0 pooling only expensive objects obviously made sense e.g. threads, socket and database connections. Object pools In the low latency space it was still apparent that recycling mutable objects improved performance by reduced pressure on your CPU caches. These objects have to have simple life cycles and have a simple structure, but you could see significant improvements in performance and jitter by using them. Another area where it made sense to use object pools is when loading large amounts of data with many duplicate objects. With a significant reduction in memory usage and a reduction in the number of objects the GC had to manage, you saw a reduction in GC times and an increase in throughput. These object pools were designed to be more light weight than say using a synchronized HashMap, and so they still helped. Take this StringInterner class as an example. You pass it a recycled mutable StringBuilder of the text you want as a String and it will provide a String which matches. Passing a String would be inefficient as you would have already created the object. The StringBuilder can be recycled. Note: this structure has an interesting property that requires no additional thread safety features, like volatile or synchronized, other than is provided by the minimum Java guarantees. i.e. you can see the final fields in a String correctly and only read consistent references. public class StringInterner { private final String[] interner; private final int mask; public StringInterner(int capacity) { int n = Maths.nextPower2(capacity, 128); interner = new String[n]; mask = n - 1; } private static boolean isEqual(@Nullable CharSequence s, @NotNull CharSequence cs) { if (s == null) return false; if (s.length() != cs.length()) return false; for (int i = 0; i < cs.length(); i++) if (s.charAt(i) != cs.charAt(i)) return false; return true; } @NotNull public String intern(@NotNull CharSequence cs) { long hash = 0; for (int i = 0; i < cs.length(); i++) hash = 57 * hash + cs.charAt(i); int h = (int) Maths.hash(hash) & mask; String s = interner[h]; if (isEqual(s, cs)) return s; String s2 = cs.toString(); return interner[h] = s2; } } Off heap memory usage Using off heap memory and using object pools both help reduce GC pauses, this is their only similarity. Object pools are good for short lived mutable objects, expensive to create objects and long live immutable objects where there is a lot of duplication. Medium lived mutable objects, or complex objects are more likely to be better left to the GC to handle. However, medium to long lived mutable objects suffer in a number of ways which off heap memory solves. Off heap memory provides; Scalability to large memory sizes e.g. over 1 TB and larger than main memory. Notional impact on GC pause times. Sharing between processes, reducing duplication between JVMs, and making it easier to split JVMs. Persistence for faster restarts or replying of production data in test. The use of off heap memory gives you more options in terms of how you design your system. The most important improvement is not performance, but determinism. Off heap and testing One of the biggest challenges in high performance computing is reproducing obscure bugs and being able to prove you have fixed them. By storing all your input events and data off heap in a persisted way you can turn your critical systems into a series of complex state machines. (Or in simple cases, just one state machine) In this way you get reproducible behaviour and performance between test and production.A number of investment banks use this technique to replay a system reliably to any event in the day and work out exactly why that event was processed the way it was. More importantly, once you have a fix you can show that you have fixed the issue which occurred in production, instead of finding an issue and hoping this was the issue.Along with deterministic behaviour comes deterministic performance. In test environments, you can replay the events with realistic timings and show the latency distribution you expect to get in production. Some system jitter can't be reproduce esp if the hardware is not the same, but you can get pretty close when you take a statistical view. To avoid taking a day to replay a day of data you can add a threshold. e.g. if the time between events is more than 10 ms you might only wait 10 ms. This can allow you to replay a day of events with realistic timing in under an hour and see whether your changes have improved your latency distribution or not. By going more low level don't you lose some of "compile once, run anywhere"? To some degree this is true, but it is far less than you might think. When you are working closer the processor and so you are more dependant on how the processor, or OS behaves. Fortunately, most systems use AMD/Intel processors and even ARM processors are becoming more compatible in terms of the low level guarantees they provide. There is also differences in the OSes, and these techniques tend to work better on Linux than Windows. However, if you develop on MacOSX or Windows and use Linux for production, you shouldn't have any issues. This is what we do at Higher Frequency Trading. What new problems are we creating by using off heap? Nothing comes for free, and this is the case with off heap. The biggest issue with off heap is your data structures become less natural. You either need a simple data structure which can be mapped directly to off heap, or you have a complex data structure which serializes and deserializes to put it off heap. Obvious using serialization has its own headaches and performance hit. Using serialization thus much slower than on heap objects.In the financial world, most high ticking data structure are flat and simple, full of primitives which maps nicely off heap with little overhead. However, this doesn't apply in all applications and you can get complex nested data structures e.g. graphs, which you can end up having to cache some objects on-heap as well.Another problem is that the JVM limits how much of the system you can use. You don't have to worry about the JVM overloading the system so much. With off heap, some limitations are lifted and you can use data structures much larger than main memory, and you start having to worry about what kind of disk sub-system you have if you do this. For example, you don't want to be paging to a HDD which has 80 IOPS, instead you are likely to want an SSD with 80,000 IOPS (Input/Ouput Operations per Second) or better i.e. 1000x faster. How does OpenHFT help? OpenHFT has a number of libraries to hide the fact you are really using native memory to store your data. These data structures are persisted and can be used with little or no garbage. These are used in applications which run all day without a minor collection Chronicle Queue - Persisted queue of events. Supports concurrent writers across JVMs on the same machine and concurrent readers across machines. Micro-second latencies and sustained throughputs in the millions of messages per second. Chronicle Map - Native or Persisted storage of a key-value Map. Can be shared between JVMs on the same machine, replicated via UDP or TCP and/or accessed remotely via TCP. Micro-second latencies and sustained read/write rates in the millions of operations per second per machine. Thread Affinity - Binding of critical threads to isolated cores or logical cpus to minimise jitter. Can reduce jitter by a factor of 1000. Which API to use? If you need to record every event -> Chronicle Queue If you only need the latest result for a unique key -> Chronicle Map If you care about 20 micro-second jitter -> Thread Affinity Conclusion Off heap memory can have challenges but also come with a lot of benefits. Where you see the biggest gain and compares with other solutions introduced to achieve scalability. Off heap is likely to be simpler and much faster than using partitioned/sharded on heap caches, messaging solutions, or out of process databases. By being faster, you may find that some of the tricks you need to do to give you the performance you need are no longer required. e.g. off heap solutions can support synchronous writes to the OS, instead of having to perform them asynchronously with the risk of data loss.The biggest gain however, can be your startup time, giving you a production system which restarts much faster. e.g. mapping in a 1 TB data set can take 10 milli-seconds, and ease of reproducibility in test by replaying every event in order you get the same behaviour every time. This allows you to produce quality systems you can rely on.

This article represents code samples representing lambda expression and the related ease with which one could print key and value of a Map object using one liner. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Code Sample – Printing Map using BiConsumer Functional Interface Following is detail for Map.forEach API in Java 8. Read further on this page. default void forEach(BiConsumer action) Performs the given action for each entry in this map until all entries have been processed or the action throws an exception. Unless otherwise specified by the implementing class, actions are performed in the order of entry set iteration (if an iteration order is specified.) Exceptions thrown by the action are relayed to the caller. Pay attention to following: Traditional way of printing key & value would require one to get an iterator of Map.Entry objects and print key and values Lambda expression way represents defining a BiConsumer implementation by passing two input arguments as key and value of Map and printing their values. public static void main(String[] args) { Map map = new HashMap(); String[][] tempStrArr = {{"Chris","USA"}, {"Raju","India"}, {"Lynda","Canada"} }; // Create a Map using String Array for( int i = 0; i < tempStrArr.length; i++ ) { map.put( tempStrArr[i][0], tempStrArr[i][1] ); } // Traditional way of printing key, value Iterator> iter = map.entrySet().iterator(); if( iter != null ) { while( iter.hasNext() ) { Map.Entry entry = iter.next(); System.out.println( "Key: " + entry.getKey() + "\t" + " Value: " + entry.getValue() ); } } // Using Lambda Expression: All in One line map.forEach( (key, value) -> { System.out.println( "Key: " + key + "\t" + " Value: " + value ); }); }

Learn how to deploy static content on a JBoss server.

JSR 354 defines a new Java API for working with Money and Currencies, which is planned to be included in Java 9. In this post we will look at the current state of the reference implementation: JavaMoney. Like my post about the Java 8 Date/Time API this post will be mainly driven by code that shows the new API. But before we start, I want to quote a short section from the specification that pretty much sums up the motivation for this new API: Monetary values are a key feature of many applications, yet the JDK provides little or no support. The existing java.util.Currency class is strictly a structure used for representing current ISO 4217 currencies, but not associated values or custom currencies. The JDK also provides no support for monetary arithmetic or currency conversion, nor for a standard value type to represent a monetary amount. If you use Maven, you can easily try the current state of the reference implementation by adding the following dependency to your project: org.javamoney moneta 0.9 All specification classes and interfaces are located in the javax.money.* package. We will start with the two core interfaces CurrencyUnit and MonetaryAmount. After that, we will look into exchange rates, currency conversion and formatting. CurrencyUnit and MonetaryAmount CurrencyUnit models a currency. CurrencyUnit is very similar to the existing java.util.Currency class, except it allows custom implementations. According to the specification it should be possible that java.util.Currency implements CurrencyUnit. CurrencyUnit instances can be obtained using the MonetaryCurrencies factory: // getting CurrencyUnits by currency code CurrencyUnit euro = MonetaryCurrencies.getCurrency("EUR"); CurrencyUnit usDollar = MonetaryCurrencies.getCurrency("USD"); // getting CurrencyUnits by locale CurrencyUnit yen = MonetaryCurrencies.getCurrency(Locale.JAPAN); CurrencyUnit canadianDollar = MonetaryCurrencies.getCurrency(Locale.CANADA); MontetaryAmount represents a concrete numeric representation of a monetary amount. A MonetaryAmount is always bound to a CurrencyUnit. Like CurrencyUnit, MonetaryAmount is an interface that supports different implementations. CurrencyUnit and MonetaryAmount implementations must be immutable, thread safe, serializable and comparable. // get MonetaryAmount from CurrencyUnit CurrencyUnit euro = MonetaryCurrencies.getCurrency("EUR"); MonetaryAmount fiveEuro = Money.of(5, euro); // get MonetaryAmount from currency code MonetaryAmount tenUsDollar = Money.of(10, "USD"); // FastMoney is an alternative MonetaryAmount factory that focuses on performance MonetaryAmount sevenEuro = FastMoney.of(7, euro); Money and FastMoney are two MonetaryAmount implementations of JavaMoney. Money is the default implementation that stores number values using BigDecimal. FastMoney is an alternative implementation which stores amounts in long fields. According to the documentation operations on FastMoney are 10-15 times faster compared to Money. However, FastMoney is limited by the size and precision of the long type. Please note that Money and FastMoney are implementation specific classes (located in org.javamoney.moneta.* instead of javax.money.*). If you want to avoid implementation specific classes, you have to obtain a MonetaryAmountFactory to create a MonetaryAmount instance: MonetaryAmount specAmount = MonetaryAmounts.getDefaultAmountFactory() .setNumber(123.45) .setCurrency("USD") .create(); Two MontetaryAmount instances are considered equal if the implementation classes, the currency units and the numeric values are equal: MonetaryAmount oneEuro = Money.of(1, MonetaryCurrencies.getCurrency("EUR")); boolean isEqual = oneEuro.equals(Money.of(1, "EUR")); // true boolean isEqualFast = oneEuro.equals(FastMoney.of(1, "EUR")); // false MonetaryAmount has various methods that allow accessing the assigned currency, the numeric amount, its precision and more: MonetaryAmount monetaryAmount = Money.of(123.45, euro); CurrencyUnit currency = monetaryAmount.getCurrency(); NumberValue numberValue = monetaryAmount.getNumber(); int intValue = numberValue.intValue(); // 123 double doubleValue = numberValue.doubleValue(); // 123.45 long fractionDenominator = numberValue.getAmountFractionDenominator(); // 100 long fractionNumerator = numberValue.getAmountFractionNumerator(); // 45 int precision = numberValue.getPrecision(); // 5 // NumberValue extends java.lang.Number. // So we assign numberValue to a variable of type Number Number number = numberValue; Working with MonetaryAmounts Mathematical operations can be performed with MonetaryAmount: MonetaryAmount twelveEuro = fiveEuro.add(sevenEuro); // "EUR 12" MonetaryAmount twoEuro = sevenEuro.subtract(fiveEuro); // "EUR 2" MonetaryAmount sevenPointFiveEuro = fiveEuro.multiply(1.5); // "EUR 7.5" // MonetaryAmount can have a negative NumberValue MonetaryAmount minusTwoEuro = fiveEuro.subtract(sevenEuro); // "EUR -2" // some useful utility methods boolean greaterThan = sevenEuro.isGreaterThan(fiveEuro); // true boolean positive = sevenEuro.isPositive(); // true boolean zero = sevenEuro.isZero(); // false // Note that MonetaryAmounts need to have the same CurrencyUnit to do mathematical operations // this fails with: javax.money.MonetaryException: Currency mismatch: EUR/USD fiveEuro.add(tenUsDollar); Rounding is another important part when working with money. MonetaryAmounts can be rounded using a rounding operator: CurrencyUnit usd = MonetaryCurrencies.getCurrency("USD"); MonetaryAmount dollars = Money.of(12.34567, usd); MonetaryOperator roundingOperator = MonetaryRoundings.getRounding(usd); MonetaryAmount roundedDollars = dollars.with(roundingOperator); // USD 12.35 Here 12.3456 US Dollars are rounded with the default rounding for this currency. When working with collections of MonetaryAmounts, some nice utility methods for filtering, sorting and grouping are available. These methods can be used together with the Java 8 Stream API. Consider the following collection: List amounts = new ArrayList<>(); amounts.add(Money.of(2, "EUR")); amounts.add(Money.of(42, "USD")); amounts.add(Money.of(7, "USD")); amounts.add(Money.of(13.37, "JPY")); amounts.add(Money.of(18, "USD")); We can now filter amounts by CurrencyUnit: CurrencyUnit yen = MonetaryCurrencies.getCurrency("JPY"); CurrencyUnit dollar = MonetaryCurrencies.getCurrency("USD"); // filter by currency, get only dollars // result is [USD 18, USD 7, USD 42] List onlyDollar = amounts.stream() .filter(MonetaryFunctions.isCurrency(dollar)) .collect(Collectors.toList()); // filter by currency, get only dollars and yen // [USD 18, USD 7, JPY 13.37, USD 42] List onlyDollarAndYen = amounts.stream() .filter(MonetaryFunctions.isCurrency(dollar, yen)) .collect(Collectors.toList()); We can also filter out MonetaryAmounts smaller or greater than a specific threshold: MonetaryAmount tenDollar = Money.of(10, dollar); // [USD 42, USD 18] List greaterThanTenDollar = amounts.stream() .filter(MonetaryFunctions.isCurrency(dollar)) .filter(MonetaryFunctions.isGreaterThan(tenDollar)) .collect(Collectors.toList()); Sorting works in a similar way: // Sorting dollar values by number value // [USD 7, USD 18, USD 42] List sortedByAmount = onlyDollar.stream() .sorted(MonetaryFunctions.sortNumber()) .collect(Collectors.toList()); // Sorting by CurrencyUnit // [EUR 2, JPY 13.37, USD 42, USD 7, USD 18] List sortedByCurrencyUnit = amounts.stream() .sorted(MonetaryFunctions.sortCurrencyUnit()) .collect(Collectors.toList()); Grouping functions: // Grouping by CurrencyUnit // {USD=[USD 42, USD 7, USD 18], EUR=[EUR 2], JPY=[JPY 13.37]} Map> groupedByCurrency = amounts.stream() .collect(MonetaryFunctions.groupByCurrencyUnit()); // Grouping by summarizing MonetaryAmounts Map summary = amounts.stream() .collect(MonetaryFunctions.groupBySummarizingMonetary()).get(); // get summary for CurrencyUnit USD MonetarySummaryStatistics dollarSummary = summary.get(dollar); MonetaryAmount average = dollarSummary.getAverage(); // "USD 22.333333333333333333.." MonetaryAmount min = dollarSummary.getMin(); // "USD 7" MonetaryAmount max = dollarSummary.getMax(); // "USD 42" MonetaryAmount sum = dollarSummary.getSum(); // "USD 67" long count = dollarSummary.getCount(); // 3 MonetaryFunctions also provides reduction function that can be used to obtain the max, min and sum of a MonetaryAmount collection: List amounts = new ArrayList<>(); amounts.add(Money.of(10, "EUR")); amounts.add(Money.of(7.5, "EUR")); amounts.add(Money.of(12, "EUR")); Optional max = amounts.stream().reduce(MonetaryFunctions.max()); // "EUR 7.5" Optional min = amounts.stream().reduce(MonetaryFunctions.min()); // "EUR 12" Optional sum = amounts.stream().reduce(MonetaryFunctions.sum()); // "EUR 29.5" Custom MonetaryAmount operations MonetaryAmount provides a nice extension point called MonetaryOperator. MonetaryOperator is a functional interface that takes a MonetaryAmount as input and creates a new MonetaryAmount based on the input. // A monetary operator that returns 10% of the input MonetaryAmount // Implemented using Java 8 Lambdas MonetaryOperator tenPercentOperator = (MonetaryAmount amount) -> { BigDecimal baseAmount = amount.getNumber().numberValue(BigDecimal.class); BigDecimal tenPercent = baseAmount.multiply(new BigDecimal("0.1")); return Money.of(tenPercent, amount.getCurrency()); }; MonetaryAmount dollars = Money.of(12.34567, "USD"); // apply tenPercentOperator to MonetaryAmount MonetaryAmount tenPercentDollars = dollars.with(tenPercentOperator); // USD 1.234567 Some standard API features are implemented as MonetaryOperator. For example, the rounding features we saw above are implemented as MonetaryOperator. Exchange rates Currency exchange rates can be obtained using an ExchangeRateProvider. JavaMoney comes with multiple different ExchangeRateProvider implementations. The two most important implementations are ECBCurrentRateProvider and IMFRateProvider. ECBCurrentRateProvider queries the European Central Bank (ECB) data feed for getting current exchange rates while IMFRateProvider uses International Monetary Fund (IMF) conversion rates. // get the default ExchangeRateProvider (CompoundRateProvider) ExchangeRateProvider exchangeRateProvider = MonetaryConversions.getExchangeRateProvider(); // get the names of the default provider chain // [IDENT, ECB, IMF, ECB-HIST] List defaultProviderChain = MonetaryConversions.getDefaultProviderChain(); // get a specific ExchangeRateProvider (here ECB) ExchangeRateProvider ecbExchangeRateProvider = MonetaryConversions.getExchangeRateProvider("ECB"); If no specific ExchangeRateProvider is requested a CompoundRateProvider will be returned. CompoundRateProvider delegates exchange rate requests to a chain of ExchangeRateProviders and returns the result from the first provider that returns an adequate result. // get the exchange rate from euro to us dollar ExchangeRate rate = exchangeRateProvider.getExchangeRate("EUR", "USD"); NumberValue factor = rate.getFactor(); // 1.2537 (at time writing) CurrencyUnit baseCurrency = rate.getBaseCurrency(); // EUR CurrencyUnit targetCurrency = rate.getCurrency(); // USD Currency conversion Conversion between currencies is be done with CurrencyConversions that can be obtained from ExchangeRateProviders: // get the CurrencyConversion from the default provider chain CurrencyConversion dollarConversion = MonetaryConversions.getConversion("USD"); // get the CurrencyConversion from a specific provider CurrencyConversion ecbDollarConversion = ecbExchangeRateProvider.getCurrencyConversion("USD"); MonetaryAmount tenEuro = Money.of(10, "EUR"); // convert 10 euro to us dollar MonetaryAmount inDollar = tenEuro.with(dollarConversion); "USD 12.537" (at the time writing) Note that CurrencyConversion implements MonetaryOperator. Like other operators it can be applied using MonetaryAmount.with(). Formatting and parsing MonetaryAmounts can be parsed/formatted from/to string using a MonetaryAmountFormat: // formatting by locale specific formats MonetaryAmountFormat germanFormat = MonetaryFormats.getAmountFormat(Locale.GERMANY); MonetaryAmountFormat usFormat = MonetaryFormats.getAmountFormat(Locale.CANADA); MonetaryAmount amount = Money.of(12345.67, "USD"); String usFormatted = usFormat.format(amount); // "USD12,345.67" String germanFormatted = germanFormat.format(amount); // 12.345,67 USD // A MonetaryAmountFormat can also be used to parse MonetaryAmounts from strings MonetaryAmount parsed = germanFormat.parse("12,4 USD"); With AmountFormatQueryBuilder custom formats can be created: // Creating a custom MonetaryAmountFormat MonetaryAmountFormat customFormat = MonetaryFormats.getAmountFormat( AmountFormatQueryBuilder.of(Locale.US) .set(CurrencyStyle.NAME) .set("pattern", "00,00,00,00.00 ¤") .build()); // results in "00,01,23,45.67 US Dollar" String formatted = customFormat.format(amount); Note that the ¤ symbol (\u00A) is used as currency placeholder inside the pattern string. Summary We looked at many parts of the new Money and Currency API. The implementation already looks quite solid (but definitely needs some more documentation). I am looking forward to see this API in Java 9 :-) You can find all the examples shown here on GitHub.

Learn all about creating a microservices architecture on Java in this great tutorial.

this article represents the high level concept and code samples which could be used to create a binary search tree in java. please feel free to comment/suggest if i missed to mention one or more important points. also, sorry for the typos. following are the key points described later in this article: what is a binary search tree? what are different kind of traversals? code samples what is a binary search tree? a binary search tree is a binary tree in which every node contains a key that satisfies following criteria: the key in left child is less than the key in the parent node the key in the right child is more than the parent node the left and right child are again binary search trees. following diagram represents a binary search tree: what are different kind of traversals? following are three different kind of traversals: preorder traversal : in preorder traversal, the node is visted first and then, left and right sub-trees. inorder traversal : in inorder traversal, the node is visited between left and right sub-tree. postorder traversal : in postorder traversal, the node is visited after left and right subtrees. code sample – how to create a binary search tree if the numbers such as {20, 15, 200, 25, -5, 0, 100, 20, 12, 126, 1000, -150} are to be stored in a binarytree (represented by code below), following would get printed using different kind of traversal mechanism: //preorder traversal 20, 15, -5, -150, 0, 12, 200, 25, 20, 100, 126, 1000 // inorder traversal -150, -5, 0, 12, 15, 20, 20, 25, 100, 126, 200, 1000 //postorder traversal -150, 12, 0, -5, 15, 20, 126, 100, 25, 1000, 200, 20 following is the code for creating binary tree that uses following binarytree class and traversals: binarytree tree = new binarytree( 20 ); int[] nums = {15, 200, 25, -5, 0, 100, 20, 12, 126, 1000, -150}; for(int i : nums ) { tree.addnode( i ); } tree.traversepreorder(); tree.traverseinorder(); tree.traversepostorder(); following is the code for binarytree class: public class binarytree { private int data; private binarytree left; private binarytree right; public binarytree(int num) { this.data = num; this.left = null; this.right = null; } // as a convention, if the key to be inserted is less than the key of root node, then key is inserted in // left sub-tree; if key is greater, it is inserted in right sub-tree. if it is equal, as a convention, it // is inserted in right sub-tree public void addnode(int num) { if (num < this.data) { if (this.left != null) { this.left.addnode(num); } else { this.left = new binarytree(num); } } else { if (this.right != null) { this.right.addnode(num); } else { this.right = new binarytree(num); } } } // visit the node first, then left and right sub-trees public void traversepreorder() { system.out.println( this.data ); if( this.left != null ) { this.left.traversepreorder(); } if( this.right != null ) { this.right.traversepreorder(); } } // visit left sub-tree, then node and then, right sub-tree public void traverseinorder() { if( this.left != null ) { this.left.traverseinorder(); } system.out.println( this.data ); if( this.right != null ) { this.right.traverseinorder(); } } // visit left sub-tree, then right sub-tree and then the node public void traversepostorder() { if( this.left != null ) { this.left.traversepostorder(); } if( this.right != null ) { this.right.traversepostorder(); } system.out.println( this.data ); } }

Authors of PVS-Studio static code analyzers offer programmers to test their sight and to try finding errors in C/C++ code fragments. Code analyzers work tirelessly and are able to find many bugs that can be difficult to notice. We chose some code fragments in which we had founded some errors using PVS-Studio. Quiz is not intended to check C++ language knowledge. There are many quality and interesting tests. For instance, we would recommend this C++ Quiz then. In our case, we made our test just for fun. We quite frequently hear an opinion that code analyzers are pointless tools. It is possible to find misplaced parenthesis or comma in five seconds. However, analyzer would not find difficult logical errors. Therefore, this tool could be useful only for students. We decided to troll these people. There is a time limit in tests. We ask them to find an error in five seconds. Well, OK, not in five seconds, but in a minute. Fifteen randomly selected problems would be shown. Every solved problem worth one point, but only if user provided the answer in one minute. We want to stress that we are not talking about syntax errors. We found all these code fragments in open-source projects that compiles flawlessly. Let us explain on a pair of examples how to point out the correct answer. First example. For instance, you got this code: The bug here is highlighted with red color. Of course, there would be no such emphasizing in a quiz problem. Programmer accidently made a misprint and wrote index 3 instead of index 2. Mouse cursor movement would highlight fragments of code, such as words and numbers. You should point the cursor into number 3 and press left mouse button. This would be the correct answer. Second example. It is not always possible to point out the error exactly. Buffer size should be compared with number 48. An excess sizeof() operator was put there by accident. In result, buffer size is compared with size of int type. At my opinion, an error there is in sizeof operator, and it is required to point it out to score a correct answer. However, without knowledge about the whole text, it is possible to think this way. Sizeof operator should have evaluated the size of some buffer, but accidently evaluates the value of the macro. The error is in “SSL3_MASTER_SECRET_LENGTH” usage. In this case, the answer will be scored no matter what you choose: “sizeof” or “SSL3_MASTER_SECRET_LENGTH”. Good luck! You can start a game. Footnote. Test does not support mobile devices. It is very easy to miss with finger. We are working on new version of tests with better mobile devices support, new problems to solve etc. However, it is not implemented yet. We offer you to subscribe on twitter to read about our new and interesting news and to read about new things in a C++ world.

If you ever have a need to process messages serially with RabbitMQ with a cluster of listeners processing the messages, the best way that I have seen is to use a "exclusive consumer" flag on a listener with 1 thread on each listener processing the messages. Exclusive consumer flag ensures that only 1 consumer can read messages from the specific queue, and 1 thread on that consumer ensures that the messages are processed serially. There is a catch however, I will go over it later. Let me demonstrate this behavior with a Spring Boot and Spring Integration based RabbitMQ message consumer. First, this is the configuration for setting up a queue using Spring java configuration, note that since this is a Spring Boot application, it automatically creates a RabbitMQ connection factory when the Spring-amqp library is added to the list of dependencies: @Configuration @Configuration public class RabbitConfig { @Autowired private ConnectionFactory rabbitConnectionFactory; @Bean public Queue sampleQueue() { return new Queue("sample.queue", true, false, false); } } Given this sample queue, a listener which gets the messages from this queue and processes them looks like this, the flow is written using the excellent Spring integration Java DSL library: @Configuration public class RabbitInboundFlow { private static final Logger logger = LoggerFactory.getLogger(RabbitInboundFlow.class); @Autowired private RabbitConfig rabbitConfig; @Autowired private ConnectionFactory connectionFactory; @Bean public SimpleMessageListenerContainer simpleMessageListenerContainer() { SimpleMessageListenerContainer listenerContainer = new SimpleMessageListenerContainer(); listenerContainer.setConnectionFactory(this.connectionFactory); listenerContainer.setQueues(this.rabbitConfig.sampleQueue()); listenerContainer.setConcurrentConsumers(1); listenerContainer.setExclusive(true); return listenerContainer; } @Bean public IntegrationFlow inboundFlow() { return IntegrationFlows.from(Amqp.inboundAdapter(simpleMessageListenerContainer())) .transform(Transformers.objectToString()) .handle((m) -> { logger.info("Processed {}", m.getPayload()); }) .get(); } } The flow is very concisely expressed in the inboundFlow method, a message payload from RabbitMQ is transformed from byte array to String and finally processed by simply logging the message to the logs The important part of the flow is the listener configuration, note the flag which sets the consumer to be an exclusive consumer and within this consumer the number of threads processing is set to 1. Given this even if multiple instances of the application is started up only 1 of the listeners will be able to connect and process messages. Now for the catch, consider a case where the processing of messages takes a while to complete and rolls back during processing of the message. If the instance of the application handling the message were to be stopped in the middle of processing such a message, then the behavior is a different instance will start handling the messages in the queue, when the stopped instance rolls back the message, the rolled back message is then delivered to the new exclusive consumer, thus getting a message out of order. If you are interested in exploring this further, here is a github project to play with this feature: https://github.com/bijukunjummen/test-rabbit-exclusive