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The Latest Java Topics

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Headless Setup of a Java Project with Tomcat, IntelliJ Community Edition and Tomcat Maven Plugin
Use IntelliJ Community Edition, Tomcat and Tomcat Maven Plugin.
December 5, 2014
by Taimur Mirza
· 46,945 Views · 2 Likes
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Java vs. Other Programming Languages: Does Java Come Out on Top?
Java is, arguably, one of the most popular programming languages amongst developers and is used to create web applications, customized software and web portals, including eCommerce and m-Commerce solutions. For many developers, programming languages begin and end with Java. While there is no doubt Java has been going strong over the years and therefore must be doing a whole lot of things right, it will be a mistake to think there is no other language as good as Java. The fact is, every language has strengths and weaknesses; yes even Java has a bunch of lacunae that get overlooked by programmers because of the truckload of benefits it brings to the table. As a programmer, it’s important to compare Java with other programing languages so that you are able to choose the best language for a particular project. This article compares Java to some other commonly used languages and tries to find out whether Java comes out on top. (Note: We have not drawn comparisons with each and every feature offered by the languages covered in this article. We have identified certain key features offered by them and talk about how they compare with similar features in Java.) 1. Python Python is a high-level language which fully supports object-oriented programming. Java on the other hand is not a pure object-oriented language. Python is a powerful easy-to-use scripting language that excels as a “glue” language because it connects system components, whereas Java is characterized as a low-level implementation language. One of the key differences between the two is that Python programs are shorter as compared to Java programs. Let’s for instance see the example of ‘Hello World’: ‘Hello World’ in Java: public class example{ public static void main(String[] args) { System.out.println(“hello world”);} } ‘Hello World’ in Python: print “hello world”; Python has rich built-in high-level data types and even supports dynamic typing; this makes it one of the preferred choices of newbie programmers as they have to write less code. But same is not the case with Java, as developers are required to define the type of each variable before using it. Swift, a programming language created by Apple this year for iOS and OS X development has some Python inspired syntax. Many large organizations like Google, Yahoo, NASA, etc. are making use of Python. If they can trust Python, you can too! All said and done, Python does have some flaws. Python programs are generally expected to run slower than Java programs making Java a favorable choice for enterprise level application development. Moreover, Java has much better library support for some of the use cases than Python. 2. C++ Java was basically derived from C++. However, there are a surprising number of differences between the two as the objectives were different for both these languages. C++ was designed mainly for systems programming and extending the C programming language whereas Java was created initially to support network computing. Though Java is fast as compared to Python, it runs significantly slower than C++. If we compare the libraries of two languages, C++ standard libraries are simple and robust, providing containers and associative arrays whereas Java has a powerful cross-platform library. The other crucial difference between the two is – in Java garbage collection happens automatically but there is no automatic garbage collection in C++; all objects must be destroyed manually through the code. There are pretty high chances of a developer forgetting to delete all objects at the end. This leads to an increase in size and memory of the software, which can lead to an increase in costing. 3. Ruby Ruby and Java have a lot in common, beginning with the fact that both are object-oriented languages and are strongly typed. The main difference between the two programming languages lies in the method of executing the code. Java code is first translated into virtual machine code which runs faster than Ruby’s interpreted code. Just like Python, the biggest reason developers prefer Ruby over Java is that a function that is implemented in Ruby will take fewer lines of code as compared to Java. This makes it easier for Ruby developers to manage the code. Generally, high traffic sites use Java rather than Ruby. A few years back, Twitter migrated to Java and Scala from Ruby. Java and Ruby can be used together, and they complement each other. JRuby, basically written in Java is an implementation of the Ruby programming language atop the Java Virtual Machine. 4. C# Since the last few years, there is a raging debate in the development community as to which language outperforms - Java or C#. If security or performance is being considered then both languages receive a similar score. However, Java has a comparative advantage over C# because it is a platform-independent language. It is supported on more operating systems than C# without recompiling code. On the other hand, C# is not quite platform independent as it can run on Windows and Mac OS-X but not Linux. The two languages are quite similar in syntax and programming style. Developers should opt for a language that is a perfect fit for their project requirement; the focus should be on using a language that ensures a project can be developed easily and efficiently. For instance, if you are developing an application for Windows desktop or Windows phone then pick C# but if developing for an Android phone, go with Java. 5. PHP PHP is a server side scripting language whereas Java is a general purpose language. These two languages are structurally different and mutually inclusive. PHP is a weakly typed language whereas Java is a strongly typed language where a programmer is required to declare a data type for each variable and/or value. This may make PHP more attractive to programmers as it does not adhere to fixed standards like Java, but in turn it may complicate certain tasks. Apart from the structural difference, a major difference between the two is that in PHP, the JVM is restarted after every request; this can result in extra performance problems. A programmer should choose PHP if he/she doesn’t have a lot of time to complete a project, but should go for Java if the project lays emphasis on features like scalability, performance and security. CONCLUSION After comparing Java with five languages, do we now have a clear answer whether Java is superior to all other languages? The answer is ‘YES’ and ‘NO’. YES, because it is a low level language that lets you understand the basics by implementing the algorithms in the simplest possible form and at the same time high level enough to implement any task efficiently. And No, because everything that can be written in Java can be written in other languages (like C#) but the reverse is not true. Java has evolved a lot since its inception and holds the lead in many areas of software development. So, its survivability is not in doubt. In fact, die hard Java folks are expected to stick to it for years! However, it is advisable programmers adopt a horses for courses policy while making use of a programming language. The choice of a language should be dependent on their needs and requirements not on the popularity of a language.
December 4, 2014
by Michael Georgiou
· 60,224 Views
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Hibernate: @Where Clause
Recently I’ve worked on a part of project where are a lot of entities. As in many other projects with the same feature there was implemented “soft delete” approach. That’s mean that when someone deletes any entity it remains in a database but a special field (e.g. ‘isDeleted’) changes its value to true. As you’ve already guessed in every SELECT operation for this kind of entities we need to apply condition: WHERE isDeleted = false It’s a little bit redundant and boring to append each time this condition to a SQL query. So I started look at solutions which could give me some elegant solution of the problem. Fortunately a colleague of mine have given me a hint how to deal with such cases. The answer is covered behind the Hibernate‘s annotation @Where. Let’s consider how we can decorate an entity with the @Where annotation to avoid extra condition in regular SQL queries: import org.hibernate.annotations.Where; import javax.persistence.*; @Entity @Table @Where(clause = "isDeleted='false'") public class Customer { @Id @GeneratedValue @Column private Integer id; @Column private String name; @Column private Boolean isDeleted; //Getters and setters } Now when you want to select Customer on JPA level you will always get only isDeleted=false records. It’s very convenient when you are working with “soft delete” or any other situation which requires permanent application of some condition. I hope it will be useful for your projects.
December 2, 2014
by Alexey Zvolinskiy
· 54,823 Views · 8 Likes
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Spring Integration Java DSL: Line by Line Tutorial
Originally authored by Artem Bilan on the SpringSource blog Dear Spring Community! Just after the Spring Integration Java DSL 1.0 GA release announcement I want to introduce the Spring Integration Java DSL to you as a line by line tutorial based on the classic Cafe Demo integration sample. We describe here Spring Boot support, Spring Framework Java and Annotation configuration, the IntegrationFlow feature and pay tribute to Java 8 Lambdasupport which was an inspiration for the DSL style. Of course, it is all backed by the Spring Integration Core project. But, before we launch into the description of the Cafe demonstration app here's a shorter example just to get started... @Configuration @EnableAutoConfiguration @IntegrationComponentScan public class Start { public static void main(String[] args) throws InterruptedException { ConfigurableApplicationContext ctx = SpringApplication.run(Start.class, args); List strings = Arrays.asList("foo", "bar"); System.out.println(ctx.getBean(Upcase.class).upcase(strings)); ctx.close(); } @MessagingGateway public interface Upcase { @Gateway(requestChannel = "upcase.input") Collection upcase(Collection strings); } @Bean public IntegrationFlow upcase() { return f -> f .split() // 1 .transform(String::toUpperCase) // 2 .aggregate(); // 3 } } We will leave the description of the infrastructure (annotations etc) to the main cafe flow description. Here, we want you to concentrate on the last @Bean, the IntegrationFlow as well as the gateway method which sends messages to that flow. In the main method we send a collection of strings to the gateway and print the results to STDOUT. The flow first splits the collection into individual Strings (1); each string is then transformed to upper case (2) and finally we re-aggregate them back into a collection (3) Since that's the end of the flow, the framework returns the result of the aggregation back to the gateway and the new payload becomes the return value from the gateway method. The equivalent XML configuration might be... or... Cafe Demo The purpose of the Cafe Demo application is to demonstrate how Enterprise Integration Patterns (EIP) can be used to reflect the order-delivery scenario in a real life cafe. With this application, we handle several drink orders - hot and iced. After running the application we can see in the standard output (System.out.println) how cold drinks are prepared quicker than hot. However the delivery for the whole order is postponed until the hot drink is ready. To reflect the domain model we have several classes: Order, OrderItem, Drink andDelivery. They all are mentioned in the integration scenario, but we won't analyze them here, because they are simple enough. The source code for our application is placed only in a single class; significant lines are annotated with a number corresponding to the comments, which follow: @SpringBootApplication // 1 @IntegrationComponentScan // 2 public class Application { public static void main(String[] args) throws Exception { ConfigurableApplicationContext ctx = SpringApplication.run(Application.class, args);// 3 Cafe cafe = ctx.getBean(Cafe.class); // 4 for (int i = 1; i <= 100; i++) { // 5 Order order = new Order(i); order.addItem(DrinkType.LATTE, 2, false); //hot order.addItem(DrinkType.MOCHA, 3, true); //iced cafe.placeOrder(order); } System.out.println("Hit 'Enter' to terminate"); // 6 System.in.read(); ctx.close(); } @MessagingGateway // 7 public interface Cafe { @Gateway(requestChannel = "orders.input") // 8 void placeOrder(Order order); // 9 } private AtomicInteger hotDrinkCounter = new AtomicInteger(); private AtomicInteger coldDrinkCounter = new AtomicInteger(); // 10 @Bean(name = PollerMetadata.DEFAULT_POLLER) public PollerMetadata poller() { // 11 return Pollers.fixedDelay(1000).get(); } @Bean public IntegrationFlow orders() { // 12 return f -> f // 13 .split(Order.class, Order::getItems) // 14 .channel(c -> c.executor(Executors.newCachedThreadPool()))// 15 .route(OrderItem::isIced, mapping -> mapping // 16 .subFlowMapping("true", sf -> sf // 17 .channel(c -> c.queue(10)) // 18 .publishSubscribeChannel(c -> c // 19 .subscribe(s -> // 20 s.handle(m -> sleepUninterruptibly(1, TimeUnit.SECONDS)))// 21 .subscribe(sub -> sub // 22 .transform(item -> Thread.currentThread().getName() + " prepared cold drink #" + this.coldDrinkCounter.incrementAndGet() + " for order #" + item.getOrderNumber() + ": " + item) // 23 .handle(m -> System.out.println(m.getPayload())))))// 24 .subFlowMapping("false", sf -> sf // 25 .channel(c -> c.queue(10)) .publishSubscribeChannel(c -> c .subscribe(s -> s.handle(m -> sleepUninterruptibly(5, TimeUnit.SECONDS)))// 26 .subscribe(sub -> sub .transform(item -> Thread.currentThread().getName() + " prepared hot drink #" + this.hotDrinkCounter.incrementAndGet() + " for order #" + item.getOrderNumber() + ": " + item) .handle(m -> System.out.println(m.getPayload())))))) .transform(orderItem -> new Drink(orderItem.getOrderNumber(), orderItem.getDrinkType(), orderItem.isIced(), orderItem.getShots())) // 27 .aggregate(aggregator -> aggregator // 28 .outputProcessor(group -> // 29 new Delivery(group.getMessages() .stream() .map(message -> (Drink) message.getPayload()) .collect(Collectors.toList()))) // 30 .correlationStrategy(m -> ((Drink) m.getPayload()).getOrderNumber()), null) // 31 .handle(CharacterStreamWritingMessageHandler.stdout()); // 32 } } Examining the code line by line... 1. @SpringBootApplication This new meta-annotation from Spring Boot 1.2. Includes @Configuration and@EnableAutoConfiguration. Since we are in a Spring Integration application and Spring Boot has auto-configuration for it, the @EnableIntegration is automatically applied, to initialize the Spring Integration infrastructure including an environment for the Java DSL -DslIntegrationConfigurationInitializer, which is picked up by theIntegrationConfigurationBeanFactoryPostProcessor from /META-INF/spring.factories. 2. @IntegrationComponentScan The Spring Integration analogue of @ComponentScan to scan components based on interfaces, (the Spring Framework's @ComponentScan only looks at classes). Spring Integration supports the discovery of interfaces annotated with @MessagingGateway (see #7 below). 3. ConfigurableApplicationContext ctx = SpringApplication.run(Application.class, args); The main method of our class is designed to start the Spring Boot application using the configuration from this class and starts an ApplicationContext via Spring Boot. In addition, it delegates command line arguments to the Spring Boot. For example you can specify --debug to see logs for the boot auto-configuration report. 4. Cafe cafe = ctx.getBean(Cafe.class); Since we already have an ApplicationContext we can start to interact with application. AndCafe is that entry point - in EIP terms a gateway. Gateways are simply interfaces and the application does not interact with the Messaging API; it simply deals with the domain (see #7 below). 5. for (int i = 1; i <= 100; i++) { To demonstrate the cafe "work" we intiate 100 orders with two drinks - one hot and one iced. And send the Order to the Cafe gateway. 6. System.out.println("Hit 'Enter' to terminate"); Typically Spring Integration application are asynchronous, hence to avoid early exit from themain Thread we block the main method until some end-user interaction through the command line. Non daemon threads will keep the application open but System.read()provides us with a mechanism to close the application cleanly. 7. @MessagingGateway The annotation to mark a business interface to indicate it is a gateway between the end-application and integration layer. It is an analogue of component from Spring Integration XML configuration. Spring Integration creates a Proxy for this interface and populates it as a bean in the application context. The purpose of this Proxy is to wrap parameters in a Message object and send it to the MessageChannel according to the provided options. 8. @Gateway(requestChannel = "orders.input") The method level annotation to distinct business logic by methods as well as by the target integration flows. In this sample we use a requestChannel reference of orders.input, which is a MessageChannel bean name of our IntegrationFlow input channel (see below #13). 9. void placeOrder(Order order); The interface method is a central point to interact from end-application with the integration layer. This method has a void return type. It means that our integration flow is one-wayand we just send messages to the integration flow, but don't wait for a reply. 10. private AtomicInteger hotDrinkCounter = new AtomicInteger(); private AtomicInteger coldDrinkCounter = new AtomicInteger(); Two counters to gather the information how our cafe works with drinks. 11. @Bean(name = PollerMetadata.DEFAULT_POLLER) public PollerMetadata poller() { The default poller bean. It is a analogue of component from Spring Integration XML configuration. Required for endpoints where the inputChannelis a PollableChannel. In this case, it is necessary for the two Cafe queues - hot and iced (see below #18). Here we use the Pollers factory from the DSL project and use its method-chain fluent API to build the poller metadata. Note that Pollers can be used directly from an IntegrationFlow definition, if a specific poller (rather than the default poller) is needed for an endpoint. 12. @Bean public IntegrationFlow orders() { The IntegrationFlow bean definition. It is the central component of the Spring Integration Java DSL, although it does not play any role at runtime, just during the bean registration phase. All other code below registers Spring Integration components (MessageChannel,MessageHandler, EventDrivenConsumer, MessageProducer, MessageSource etc.) in theIntegrationFlow object, which is parsed by the IntegrationFlowBeanPostProcessor to process those components and register them as beans in the application context as necessary (some elements, such as channels may already exist). 13. return f -> f The IntegrationFlow is a Consumer functional interface, so we can minimize our code and concentrate just only on the integration scenario requirements. Its Lambda acceptsIntegrationFlowDefinition as an argument. This class offers a comprehensive set of methods which can be composed to the chain. We call these EIP-methods, because they provide implementations for EI patterns and populate components from Spring Integration Core. During the bean registration phase, the IntegrationFlowBeanPostProcessor converts this inline (Lambda) IntegrationFlow to a StandardIntegrationFlow and processes its components. The same we can achieve using IntegrationFlows factory (e.g.IntegrationFlow.from("channelX"). ... .get()), but we find the Lambda definition more elegant. An IntegrationFlow definition using a Lambda populates DirectChannel as an inputChannel of the flow and it is registered in the application context as a bean with the name orders.input in this our sample (flow bean name + ".input"). That's why we use that name for the Cafe gateway. 14. .split(Order.class, Order::getItems) Since our integration flow accepts message through the orders.input channel, we are ready to consume and process them. The first EIP-method in our scenario is .split(). We know that the message payload from orders.input channel is an Order domain object, so we can simply use its type here and use the Java 8 method-reference feature. The first parameter is a type of message payload we expect, and the second is a method reference to the getItems() method, which returns Collection. So, this performs thesplit EI pattern, when we send each collection entry as a separate message to the next channel. In the background, the .split() method registers a MethodInvokingSplitterMessageHandler implementation and the EventDrivenConsumer for thatMessageHandler, and wiring in the orders.input channel as the inputChannel. 15. .channel(c -> c.executor(Executors.newCachedThreadPool())) The .channel() EIP-method allows the specification of concrete MessageChannels between endpoints, as it is done via output-channel/input-channel attributes pair with Spring Integration XML configuration. By default, endpoints in the DSL integration flow definition are wired with DirectChannels, which get the bean names based on theIntegrationFlow bean name and index in the flow chain. In this case we use anotherLambda expression, which selects a specific MessageChannel implementation from itsChannels factory and configures it with the fluent API. The current channel here is anExecutorChannel, to allow to distribute messages from the splitter to separateThreads, to process them in parallel in the downstream flow. 16. .route(OrderItem::isIced, mapping -> mapping The next EIP-method in our scenario is .route(), to send hot/iced order items to different Cafe kitchens. We again use here a method reference (isIced()) to get theroutingKey from the incoming message. The second Lambda parameter represents arouter mapping - something similar to sub-element for the component from Spring Integration XML configuration. However since we are using Java we can go a bit further with its Lambda support! The Spring Integration Java DSL introduced thesubflow definition for routers in addition to traditional channel mapping. Each subflow is executed depending on the routing and, if the subflow produces a result, it is passed to the next element in the flow definition after the router. 17. .subFlowMapping("true", sf -> sf Specifies the integration flow for the current router's mappingKey. We have in this samples two subflows - hot and iced. The subflow is the same IntegrationFlow functional interface, therefore we can use its Lambda exactly the same as we do on the top levelIntegrationFlow definition. The subflows don't have any runtime dependency with its parent, it's just a logical relationship. 18. .channel(c -> c.queue(10)) We already know that a Lambda definition for the IntegrationFlow starts from[FLOW_BEAN_NAME].input DirectChannel, so it may be a question "how does it work here if we specify .channel() again?". The DSL takes care of such a case and wires those two channels with a BridgeHandler and endpoint. In our sample, we use here a restrictedQueueChannel to reflect the Cafe kitchen busy state from real life. And here is a place where we need that global poller for the next endpoint which is listening on this channel. 19. .publishSubscribeChannel(c -> c The .publishSubscribeChannel() EIP-method is a variant of the .channel() for aMessageChannels.publishSubscribe(), but with the .subscribe() option when we can specify subflow as a subscriber to the channel. Right, subflow one more time! So, subflows can be specified to any depth. Independently of the presence .subscribe() subflows, the next endpoint in the parent flow is also a subscriber to this .publishSubscribeChannel(). Since we are in the .route() subflow already, the last subscriber is an implicit BridgeHandlerwhich just pops the message to the top level - to a similar implicit BridgeHandler to pop message to the next .transform() endpoint in the main flow. And one more note about this current position of our flow: the previous EIP-method is .channel(c -> c.queue(10)) and this one is for MessageChannel too. So, they are again tied with an implicit BridgeHandleras well. In a real application we could avoid this .publishSubscribeChannel() just with the single .handle() for the Cafe kitchen, but our goal here to cover DSL features as much as possible. That's why we distribute the kitchen work to several subflows for the samePublishSubscribeChannel. 20. .subscribe(s -> The .subscribe() method accepts an IntegrationFlow as parameter, which can be specified as Lambda to configure subscriber as subflow. We use here several subflow subscribers to avoid multi-line Lambdas and cover some DSL as we as Spring Integration capabilities. 21. s.handle(m -> sleepUninterruptibly(1, TimeUnit.SECONDS))) Here we use a simple .handle() EIP-method just to block the current Thread for some timeout to demonstrate how quickly the Cafe kitchen prepares a drink. Here we use Google Guava Uninterruptibles.sleepUninterruptibly, to avoid using a try...catch block within the Lambda expression, although you can do that and your Lambda will be multi-line. Or you can move that code to a separate method and use it here as method reference. Since we don't use any Executor on the .publishSubscribeChannel() all subscribers will beperformed sequentially on the same Thread; in our case it is one of TaskScheduler's Threads from poller on the previous QueueChannel. That's why this sleep blocks all downstream process and allows to demonstrate the busy state for that restricted to 10QueueChannel. 22. .subscribe(sub -> sub The next subflow subscriber which will be performed only after that sleep with 1 second foriced drink. We use here one more subflow because .handle() of previous one is one-way with the nature of the Lambda for MessageHandler. That's why, to go ahead with process of our whole flow, we have several subscribers: some of subflows finish after their work and don't return anything to the parent flow. 23. .transform(item -> Thread.currentThread().getName() + " prepared cold drink #" + this.coldDrinkCounter.incrementAndGet() + " for order #" + item.getOrderNumber() + ": " + item) The transformer in the current subscriber subflow is to convert the OrderItem to the friendly STDOUT message for the next .handle. Here we see the use of generics with the Lambda expression. This is implemented using the GenericTransformer functional interface. 24. .handle(m -> System.out.println(m.getPayload()))))) The .handle() here just to demonstrate how to use Lambda expression to print thepayload to STDOUT. It is a signal that our drink is ready. After that the final (implicit) subscriber to the PublishSubscribeChannel just sends the message with the OrderItemto the .transform() in the main flow. 25. .subFlowMapping("false", sf -> sf The .subFlowMapping() for the hot drinks. Actually it is similar to the previous iceddrinks subflow, but with specific hot business logic. 26. s.handle(m -> sleepUninterruptibly(5, TimeUnit.SECONDS))) The sleepUninterruptibly for hot drinks. Right, we need more time to boil the water! 27. .transform(orderItem -> new Drink(orderItem.getOrderNumber(), orderItem.getDrinkType(), orderItem.isIced(), orderItem.getShots())) The main OrderItem to Drink transformer, which is performed when the .route()subflow returns its result after the Cafe kitchen subscribers have finished preparing the drink. 28. .aggregate(aggregator -> aggregator The .aggregate() EIP-method provides similar options to configure anAggregatingMessageHandler and its endpoint, like we can do with the component when using Spring Integration XML configuration. Of course, with the Java DSL we have more power to configure the aggregator just in place, without any other extra beans. And Lambdas come to the rescue again! From the Cafe business logic perspective we compose theDelivery for the initial Order, since we .split() the original order to the OrderItems near the beginning. 29. .outputProcessor(group -> The .outputProcessor() of the AggregatorSpec allows us to emit a custom result after aggregator completes the group. It's an analogue of ref/method from the component or the @Aggregator annotation on a POJO method. Our goal here to compose aDelivery for all Drinks. 30. new Delivery(group.getMessages() .stream() .map(message -> (Drink) message.getPayload()) .collect(Collectors.toList()))) As you see we use here the Java 8 Stream feature for Collection. We iterate over messages from the released MessageGroup and convert (map) each of them to its Drinkpayload. The result of the Stream (.collect()) (a list of Drinks) is passed to theDelivery constructor. The Message with this new Delivery payload is sent to the next endpoint in our Cafe scenario. 31. .correlationStrategy(m -> ((Drink) m.getPayload()).getOrderNumber()), null) The .correlationStrategy() Lambda demonstrates how we can customize an aggregator behaviour. Of course, we can rely here just only on a built-in SequenceDetails from Spring Integration, which is populated by default from .split() in the beginning of our flow to each split message, but the Lambda sample for the CorrelationStrategy is included for illustration. (With XML, we could have used a correlation-expression or a customCorrelationStrategy). The second argument in this line for the .aggregate() EIP-method is for the endpointConfigurer to customize options like autoStartup,requiresReply, adviceChain etc. We use here null to show that we rely on the default options for the endpoint. Many of EIP-methods provide overloaded versions with and withoutendpointConfigurer, but .aggregate() requires an endpoint argument, to avoid an explicit cast for the AggregatorSpec Lambda argument. 32. .handle(CharacterStreamWritingMessageHandler.stdout()); It is the end of our flow - the Delivery is delivered to the client! We just print here the message payload to STDOUT using out-of-the-boxCharacterStreamWritingMessageHandler from Spring Integration Core. This is a case to show how existing components from Spring Integration Core (and its modules) can be used from the Java DSL. Well, we have finished describing the Cafe Demo sample based on the Spring Integration Java DSL. Compare it with XML sample to get more information regarding Spring Integration. This is not an overall tutorial to the DSL stuff. We don't review here theendpointConfigurer options, Transformers factory, the IntegrationComponentSpechierarchy, the NamespaceFactories, how we can specify several IntegrationFlow beans and wire them to a single application etc., see the Reference Manual for more information. At least this line-by-line tutorial should show you Spring Integration Java DSL basics and its seamless fusion between Spring Framework Java & Annotation configuration, Spring Integration foundation and Java 8 Lambda support! Also see the si4demo to see the evolution of Spring Integration including the Java DSL, as shown at the 2014 SpringOne/2GX Conference. (Video should be available soon). As always, we look forward to your comments and feedback (StackOverflow (spring-integration tag), Spring JIRA, GitHub) and we very much welcome contributions! P.S. Even if this tutorial is fully based on the Java 8 Lambda support, we don't want to miss pre Java 8 users, we are going to provide similar non-Lambda blog post. Stay tuned!
December 1, 2014
by Pieter Humphrey
· 20,517 Views
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Converting between Completablefuture and Observable
CompletableFuture from Java 8 is an advanced abstraction over a promise that value of type T will be available in the future. Observable is quite similar, but it promises arbitrary number of items in the future, from 0 to infinity. These two representations of asynchronous results are quite similar to the point where Observable with just one item can be used instead of CompletableFuture and vice-versa. On the other hand CompletableFuture is more specialized and because it's now part of JDK, should become prevalent quite soon. Let's celebrate RxJava 1.0 release with a short article showing how to convert between the two, without loosing asynchronous and event-driven nature of them. From CompletableFuture to Observable CompletableFuture represents one value in the future, so turning it into Observable is rather simple. When Futurecompletes with some value, Observable will emit that value as well immediately and close stream: class FuturesTest extends Specification { public static final String MSG = "Don't panic" def 'should convert completed Future to completed Observable'() { given: CompletableFuture future = CompletableFuture.completedFuture("Abc") when: Observable observable = Futures.toObservable(future) then: observable.toBlocking().toIterable().toList() == ["Abc"] } def 'should convert failed Future into Observable with failure'() { given: CompletableFuture future = failedFuture(new IllegalStateException(MSG)) when: Observable observable = Futures.toObservable(future) then: observable .onErrorReturn({ th -> th.message } as Func1) .toBlocking() .toIterable() .toList() == [MSG] } CompletableFuture failedFuture(Exception error) { CompletableFuture future = new CompletableFuture() future.completeExceptionally(error) return future } } First test of not-yet-implemented Futures.toObservable() converts Future into Observable and makes sure value is propagated correctly. Second test created failed Future, replaces failure with exception's message and makes sure exception was propagated. The implementation is much shorter: public static Observable toObservable(CompletableFuture future) { return Observable.create(subscriber -> future.whenComplete((result, error) -> { if (error != null) { subscriber.onError(error); } else { subscriber.onNext(result); subscriber.onCompleted(); } })); } NB: Observable.fromFuture() exists, however we want to take full advantage of ComplatableFuture's asynchronous operators. From Observable toCompletableFuture> There are actually two ways to convert Observable to Future - creating CompletableFuture> orCompletableFuture (if we assume Observable has just one item). Let's start from the former case, described with the following test cases: def 'should convert Observable with many items to Future of list'() { given: Observable observable = Observable.just(1, 2, 3) when: CompletableFuture> future = Futures.fromObservable(observable) then: future.get() == [1, 2, 3] } def 'should return failed Future when after few items exception was emitted'() { given: Observable observable = Observable.just(1, 2, 3) .concatWith(Observable.error(new IllegalStateException(MSG))) when: Futures.fromObservable(observable) then: def e = thrown(Exception) e.message == MSG } Obviously Future doesn't complete until source Observable signals end of stream. Thus Observable.never() would never complete wrapping Future, rather then completing it with empty list. The implementation is much shorter and sweeter: public static CompletableFuture> fromObservable(Observable observable) { final CompletableFuture> future = new CompletableFuture<>(); observable .doOnError(future::completeExceptionally) .toList() .forEach(future::complete); return future; } The key is Observable.toList() that conveniently converts from Observable and Observable>. The latter emits one item of List type when source Observable finishes. From Observable to CompletableFuture Special case of the previous transformation happens when we know that CompletableFuture will return exactly one item. In that case we can convert it directly to CompletableFuture, rather than CompletableFuture>with one item only. Tests first: def 'should convert Observable with single item to Future'() { given: Observable observable = Observable.just(1) when: CompletableFuture future = Futures.fromSingleObservable(observable) then: future.get() == 1 } def 'should create failed Future when Observable fails'() { given: Observable observable = Observable. error(new IllegalStateException(MSG)) when: Futures.fromSingleObservable(observable) then: def e = thrown(Exception) e.message == MSG } def 'should fail when single Observable produces too many items'() { given: Observable observable = Observable.just(1, 2) when: Futures.fromSingleObservable(observable) then: def e = thrown(Exception) e.message.contains("too many elements") } Again the implementation is quite straightforward and almost identical: public static CompletableFuture> fromObservable(Observable observable) { final CompletableFuture> future = new CompletableFuture<>(); observable .doOnError(future::completeExceptionally) .toList() .forEach(future::complete); return future; } Helpers methods above aren't fully robust yet, but if you ever need to convert between JDK 8 and RxJava style of asynchronous computing, this article should be enough to get you started.
November 27, 2014
by Tomasz Nurkiewicz
· 15,212 Views · 3 Likes
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From Vaadin to Docker - A Novice's Journey
I’m a huge Vaadin fan and I’ve created a Github workshop I can demo at conferences. A common issue with such kind of workshops is that attendees have to prepare their workstations in advance… and there’s always a significant part of them that comes with not everything ready. At this point, two options are available to the speaker: either wait for each of the attendee to finish the preparation – too bad for the people who took the time at home to do that, or start anyway – and lose the not-ready part. Given the current buzz around Docker, I thought that could be a very good way to make the workshop preparation quicker – only one step, and hasslefree – no problem regarding the quirks of your operation system. The required steps I ask the attendees are the following: Install Git Install Java, Maven and Tomcat Clone the git repo Build the project (to prepare the Maven repository) Deploy the built webapp Start Tomcat These should directly be automated into Docker. As I wasted much time getting this to work, here’s the tale of my journey in achieving this (be warned, it’s quite long). If you’ve got similar use-cases, I hope it will be useful in you getting things done faster. Starting with Docker The first step was to get to know the basics about Docker. Fortunately, I had the chance to attend a Docker workshop by David Gageot at Duchess Swiss. This included both Docker installation and basics of Dockerfile. I assume readers have likewise a basic understanding of Docker. For those who don’t, I guess browsing the Docker’s official documentation is a nice idea: Installation Dockerfile reference Building my first Dockerfile The Docker image can be built with the following command ran into the directory of the Dockerfile: $ docker build -t vaadinworkshop . The first issues one can encounter when playing with Docker the first time, is to get the following error message: Get http:///var/run/docker.sock/v1.14/containers/json: dial unix /var/run/docker.sock: no such file or directory The reason is because one didn’t export the required environment variables displayed by the boot2docker information message. If you lost the exact data, no worry, just use the shellinit boot2docker parameter: $ boot2docker shellinit Writing /Users/i303869/.docker/boot2docker-vm/ca.pem: Writing /Users/i303869/.docker/boot2docker-vm/cert.pem: Writing /Users/i303869/.docker/boot2docker-vm/key.pem: export DOCKER_HOST=tcp://192.168.59.103:2376 export DOCKER_CERT_PATH=/Users/i303869/.docker/boot2docker-vm Copy-paste the export lines above will solve the issue. These can also be set in one’s .bashrc script as it seems these values seldom change. Next in line is the following error: Get http://192.168.59.103:2376/v1.14/containers/json: malformed HTTP response "x15x03x01x00x02x02" This error message seems to be because of a mismatch between versions of the client and the server. It seems it is because of a bug on Mac OSX when upgrading. For a long term solution, reinstall Docker from scratch; for a quick fix, use the --tls flag with the docker command. As it is quite cumbersome to type it everything, one can alias it: $ alias docker="docker --tls" My last mistake when building the image comes from building the Dockerfile from a not empty directory. Docker sends every file it finds in the directory of the Dockerfile to the Docker container for build: $ docker --tls build -t vaadinworkshop . Sending build context to Docker daemon Too many kB Fix: do not try this at home and start from a directory container the Dockerfile only. Starting from scratch Dockerfiles describe images – images are built as a layered list of instructions. Docker images are designed around single inheritance: one image has to be set a single parent. An image requiring no parent starts from scratch, but Docker provides 4 base official distributions: busybox, debian, ubuntu and centos (operating systems are generally a good start). Whatever you want to achieve, it is necessary to choose the right parent. Given the requirements I set for myself (Java, Maven, Tomcat and Git), I tried to find the right starting image. Many Dockerfiles are already available online on the Docker hub. The browsing app is quite good, but to be really honest, the search can really be improved. My intention was to use the image that matched the most of my requirements, then fill the gap. I could find no image providing Git, but I thought the dgageot/maven Dockerfile would be a nice starting point. The problem is that the base image is a busybox and provides no installer out-of-the-box (apt-get, yum, whatever). For this reason, David uses a lot of curl to get Java 8 and Maven in his Dockerfiles. I foolishly thought I could use a different flavor of busybox that provides the opkg installer. After a while, I accumulated many problems, resolving one heading to another. In the end, I finally decided to use the OS I was most comfortable with and to install everything myself: FROM ubuntu:utopic Scripting Java installation Installing git, maven and tomcat packages is very straightforward (if you don’t forget to use the non-interactive options) with RUN and apt-get: RUN apt-get update && \ apt-get install -y --force-yes git maven tomcat8 Java doesn’t fall into this nice pattern, as Oracle wants you to accept the license. Nice people did however publish it to a third-party repo. Steps are the following: Add the needed package repository Configure the system to automatically accept the license Configure the system to add un-certified packages Update the list of repositories At last, install the package Also add a package for Java 8 system configuration. RUN echo "deb http://ppa.launchpad.net/webupd8team/java/ubuntu precise main" | tee -a /etc/apt/sources.list && \ echo oracle-java8-installer shared/accepted-oracle-license-v1-1 select true | /usr/bin/debconf-set-selections && \ apt-key adv --keyserver keyserver.ubuntu.com --recv-keys EEA14886 RUN apt-get update && \ apt-get install -y --force-yes oracle-java8-installer oracle-java8-set-default Building the sources Getting the workshop’s sources and building them is quite straightforward with the following instructions: RUN git clone https://github.com/nfrankel/vaadin7-workshop.git WORKDIR /vaadin7-workshop RUN mvn package The drawback of this approach is that Maven will start from a fresh repository, and thus download the Internet the first time it is launched. At first, I wanted to mount a volume from the host to the container to share the ~/.m2/repository folder to avoid this, but I noticed this could only be done at runtime through the -v option as the VOLUME instruction cannot point to a host directory. Starting the image The simplest command to start the created Docker image is the following: $ docker run -p 8080:8080 Do not forget the port forwarding from the container to the host, 8080 for the standard HTTP port. Also, note that it’s not necessary to run the container as a daemon (with the -d option). The added value of that is that the standard output of the CMD (see below) will be redirected to the host. When running as a daemon and wanting to check the logs, one has to execute bash in the container, which requires a sequence of cumbersome manipulations. Configuring and launching Tomcat Tomcat can be launched when starting the container by just adding the following instruction to the Dockerfile: CMD ["catalina.sh", "run"] However, trying to start the container at this point will result in the following error: Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.ClassLoaderFactory validateFile WARNING: Problem with directory [/usr/share/tomcat8/common/classes], exists: [false], isDirectory: [false], canRead: [false] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.ClassLoaderFactory validateFile WARNING: Problem with directory [/usr/share/tomcat8/common], exists: [false], isDirectory: [false], canRead: [false] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.ClassLoaderFactory validateFile WARNING: Problem with directory [/usr/share/tomcat8/server/classes], exists: [false], isDirectory: [false], canRead: [false] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.ClassLoaderFactory validateFile WARNING: Problem with directory [/usr/share/tomcat8/server], exists: [false], isDirectory: [false], canRead: [false] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.ClassLoaderFactory validateFile WARNING: Problem with directory [/usr/share/tomcat8/shared/classes], exists: [false], isDirectory: [false], canRead: [false] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.ClassLoaderFactory validateFile WARNING: Problem with directory [/usr/share/tomcat8/shared], exists: [false], isDirectory: [false], canRead: [false] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.Catalina initDirs SEVERE: Cannot find specified temporary folder at /usr/share/tomcat8/temp Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.Catalina load WARNING: Unable to load server configuration from [/usr/share/tomcat8/conf/server.xml] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.Catalina initDirs SEVERE: Cannot find specified temporary folder at /usr/share/tomcat8/temp Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.Catalina load WARNING: Unable to load server configuration from [/usr/share/tomcat8/conf/server.xml] Nov 15, 2014 9:24:18 PM org.apache.catalina.startup.Catalina start SEVERE: Cannot start server. Server instance is not configured. I have no idea why, but it seems Tomcat 8 on Ubuntu is not configured in any meaningful way. Everything is available but we need some symbolic links here and there as well as creating the temp directory. This translates into the following instruction in the Dockerfile: RUN ln -s /var/lib/tomcat8/common $CATALINA_HOME/common && \ ln -s /var/lib/tomcat8/server $CATALINA_HOME/server && \ ln -s /var/lib/tomcat8/shared $CATALINA_HOME/shared && \ ln -s /etc/tomcat8 $CATALINA_HOME/conf && \ mkdir $CATALINA_HOME/temp The final trick is to connect the exploded webapp folder created by Maven to Tomcat’s webapps folder, which it looks for deployments: RUN mkdir $CATALINA_HOME/webapps && \ ln -s /vaadin7-workshop/target/workshop-7.2-1.0-SNAPSHOT/ $CATALINA_HOME/webapps/vaadinworkshop At this point, the Holy Grail is not far away, you just have to browse the URL… if only we knew what the IP was. Since running on Mac, there’s an additional VM beside the host and the container that’s involved. To get this IP, type: $ boot2docker ip The VM's Host only interface IP address is: 192.168.59.103 Now, browsing http://192.168.59.103:8080/vaadinworkshop/ will bring us to the familiar workshop screen: Developing from there Everything works fine but didn’t we just forget about one important thing, like how workshop attendees are supposed to work on the sources? Easy enough, just mount the volume when starting the container: docker run -v /Users//vaadin7-workshop:/vaadin7-workshop -p 8080:8080 vaadinworkshop Note that the host volume must be part of /Users and if on OSX, it must use boot2docker v. 1.3+. Unfortunately, it seems now is the showstopper, as mounting an empty directory from the host to the container will not make the container’s directory available from the host. On the contrary, it will empty the container’s directory given that the host’s directory doesn’t exist… It seems there’s an issue in Docker on Mac. The installation of JHipster runs into the same problem, and proposes to use the Samba Docker folder sharing project. I’m afraid I was too lazy to go further at this point. However, this taught me much about Docker, its usages and use-cases (as well as OSX integration limitations). For those who are interested, you’ll find below the Docker file. Happy Docker! FROM ubuntu:utopic MAINTAINER Nicolas Frankel # Config to get to install Java 8 w/o interaction RUN echo "deb http://ppa.launchpad.net/webupd8team/java/ubuntu precise main" | tee -a /etc/apt/sources.list && echo oracle-java8-installer shared/accepted-oracle-license-v1-1 select true | /usr/bin/debconf-set-selections && apt-key adv --keyserver keyserver.ubuntu.com --recv-keys EEA14886 RUN apt-get update && apt-get install -y --force-yes git oracle-java8-installer oracle-java8-set-default maven tomcat8 RUN git clone https://github.com/nfrankel/vaadin7-workshop.git WORKDIR /vaadin7-workshop RUN git checkout v7.2-1 RUN mvn package ENV JAVA_HOME /usr/lib/jvm/java-8-oracle ENV CATALINA_HOME /usr/share/tomcat8 ENV PATH $PATH:$CATALINA_HOME/bin # Configure Tomcat 8 directories RUN ln -s /var/lib/tomcat8/common $CATALINA_HOME/common && ln -s /var/lib/tomcat8/server $CATALINA_HOME/server && ln -s /var/lib/tomcat8/shared $CATALINA_HOME/shared && ln -s /etc/tomcat8 $CATALINA_HOME/conf && mkdir $CATALINA_HOME/temp && mkdir $CATALINA_HOME/webapps && ln -s /vaadin7-workshop/target/workshop-7.2-1.0-SNAPSHOT/ $CATALINA_HOME/webapps/vaadinworkshop VOLUME ["/vaadin7-workshop"] CMD ["catalina.sh", "run"] # docker build -t vaadinworkshop . # docker run -v ~/vaadin7-workshop training/webapp -p 8080:8080 vaadinworkshop
November 25, 2014
by Nicolas Fränkel
· 13,044 Views
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Spring Integration Java DSL 1.0 GA Released
[This article was written by Artem Bilan.] Dear Spring community, As we promised in the Release Candidate blog post, we are pleased to announce that the Spring Integration Java DSL 1.0 GA is now available. As usual, use the Release Repository with Maven or Gradle, or download a distribution archive, to give it a spin. See the project home page for more information. First of all, we are glad to share with you that on Nov 12, 2014, DZone research recognized Spring Integration as the leader in the ESB / Integration framework space, leading with 42% marketshare, in a publication of their recent survey results. And the report is the most popular DZone Guide in November, with more than 12 000 downloads already! Don't miss it: very exciting. We hope the release of the Spring Integration Java DSL adds more excitement!. Many thanks to all contributors, including several who are new to the community. The release includes just a few bug fixes, since the release candidate, and a lot of JavaDocs! Not specifically related to the the release, I want to present here some resources on the matter. We are observing many valuable DSL questions on Stack Overflow. Josh Long's tech tip showing how we can use together Spring Boot, REST, Spring Integration 4.1 WebSocket support and Spring Integration Java DSL plus Java 8 features. The Jdbc Splitter implementation in the project tests. My gist to demonstrate how we can use Reactor Streams together with the Spring Integration Java DSL. Dave Syer has started to use Spring Integration Java DSL in the Spring Cloud Bus project. Don't miss the si4demo to see the evolution of Spring Integration including the Java DSL, as shown at the 2014 SpringOne/2GX Conference. (Video should be available soon). Especial thanks to Biju Kunjummen who has done some nice articles on DZone to introduce Spring Integration Java DSL: https://dzone.com/articles/spring-integration-java-dsl, https://dzone.com/articles/spring-integration-java-dsl-0. And of course, with the latest Spring XD, we can build Modules based on @Configuration including Spring Integration Java DSL IntegrationFlow definitions. Just after this announcement I'm going to publish a DSL Tutorial to explain concepts and features using the Java DSL version of the Cafe Demo sample as material. As always, we look forward to your comments and feedback (StackOverflow (spring-integration tag), Spring JIRA, GitHub) and we very much welcome contributions!
November 25, 2014
by Pieter Humphrey
· 5,122 Views
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A XSS filter for Java EE web apps
Cross Site Scripting, or XSS, is a fairly common vector used to attack web sites. It involves user generated code being redisplayed by a website with all the privileges and security rights that a browser assigns to code originating from the current host. If the user code is something like , then you have a problem. OWASP is an organisation that provides guidance on web security, and they have a page that provides a suggested method for avoiding XSS in JavaEE web app. You can read this document at https://www.owasp.org/index.php/How_to_add_validation_logic_to_HttpServletRequest. The library being demonstrated here is based off the ideas presented in that article, but fleshed out to be more flexible and easy to deploy. We call this library the (unimaginatively named) Parameter Validation Filter, or PVF. PVF is implemented as a Servlet filter that intercepts requests to web pages, runs submitted parameters through a configurable sequence of validation rules, and either sanitises the parameters before they are sent through to the web application, or returns a HTTP error code if validation errors were detected. We have made the following assumptions when developing this library: Client side validation will prevent legitimate users from submitting invalid data. The PVF library should prevent further processing if invalid data is submitted in the majority of cases. Occasionally it might be appropriate to sanitise submitted data, but any sanitisation should be trivial (like the removal of whitespace). To make use of the PVF library, you’ll need to add it to your project. This artifact is currently in the Sonatype staging repo, so you'll need to add that repo to your Maven config. See http://stackoverflow.com/questions/13945757/how-do-you-import-a-maven-dependency-from-sonatype-org for details. com.matthewcasperson parameter_validation_filter LATEST The filter then needs to be added to the web.xml file with the following settings. You may want to configure the url-pattern to match the pages that you actually want to protect. ParameterValidationFilter com.matthewcasperson.validation.filter.ParameterValidationFilter configFile /WEB-INF/xml/pvf.xml ParameterValidationFilter *.jsp Finally you need to create a file called WEB-INF/xml/pvf.xml. This file defines the custom validation rules applied to the parameters being sent to your web applications. true com.matthewcasperson.validation.ruleimpl.TrimTextValidationRule com.matthewcasperson.validation.ruleimpl.FailIfNotCanonicalizedValidationRule com.matthewcasperson.validation.ruleimpl.FailIfContainsHTMLValidationRule .* .* false false The XML has been commented to make it easier to understand, but there are a few interesting elements: paramNamePatternString, which has been configured to enable the validation chain to match all parameters requestURIPatternString, which has been configured to enable the chain to match all URIs The three elements called validationRuleName, which reference the full class name of the validation rules that will be applied to each parameter passed into our web application Although this is a simple example, the three validation rules that have been implemented (TrimTextValidationRule, FailIfNotCanonicalizedValidationRule and FailIfContainsHTMLValidationRule) are quite effective at preventing a malicious user from submitting parameters that contain XSS code. The first rule, TrimTextValidationRule, simply strips away any whitespace on either side of the parameter. This uses the trim() function any developer should be familiar with. The second rule, FailIfNotCanonicalizedValidationRule, will prevent further processing if the supplied parameter has already been encoded. No legitimate user will have a need to supply text like %3Cscript%3EdoEvil()%3B%3C%2Fscript%3E, so any time encoded text is found we simply return with a HTTP 400 error code. This rule makes use of the ESAPI library supplied by OWASP. Like the second rule, the third rule will prevent further processing if the supplied parameter has any special HTML characters. If you would like your customers to be able to pass through characters like &, this rule is too broad. However, it is almost always valid to block special HTML characters. If you want to see how effective this simple validation chain is, check out the live demo at http://pvftest-matthewcasperson.rhcloud.com/. You may want to take a look at https://www.owasp.org/index.php/XSS_Filter_Evasion_Cheat_Sheet to find some XSS patterns that are often used to bypass XSS filters. Moving forward we will be looking to implement more targeted validation rules, especially those that can’t be easily implemented as regex matches (like making sure a date if after today, or that a number is between two values etc). If you have any suggestions, or find any bugs, feel free to fork the code from our GitHub repo . We do hope to get some public feedback in order to make this library as robust as it can be.
November 22, 2014
by Matthew Casperson
· 21,681 Views · 3 Likes
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How to Compress Responses in Java REST API with GZip and Jersey
There may be cases when your REST api provides responses that are very long, and we all know how important transfer speed and bandwidth still are on mobile devices/networks. I think this is the first performance optimization point one needs to address, when developing REST apis that support mobile apps. Guess what? Because responses are text, we can compress them. And with today’s power of smartphones and tablets uncompressing them on the client side should not be a big deal… So in this post I will present how you can SELECTIVELY compress your REST API responses, if you’ve built it in Java with Jersey, which is the JAX-RS Reference Implementation (and more)… 1. Jersey filters and interceptors Well, thanks to Jersey’s powerful Filters and Interceptors features, the implementation is fairly easy. Whereas filters are primarily intended to manipulate request and response parameters like HTTP headers, URIs and/or HTTP methods, interceptors are intended to manipulate entities, via manipulating entity input/output streams. You’ve seen the power of filters in my posts How to add CORS support on the server side in Java with Jersey, where I’ve shown how to CORS-enable a REST API and How to log in Spring with SLF4J and Logback, where I’ve shown how to log requests and responses from the REST API , but for compressing will be using a GZip WriterInterceptor. A writer interceptor is used for cases where entity is written to the “wire”, which on the server side as in this case, means when writing out a response entity. 1.1. GZip Writer Interceptor So let’s have a look at our GZip Writer Interceptor: package org.codingpedia.demo.rest.interceptors; import java.io.IOException; import java.io.OutputStream; import java.util.zip.GZIPOutputStream; import javax.ws.rs.WebApplicationException; import javax.ws.rs.core.MultivaluedMap; import javax.ws.rs.ext.WriterInterceptor; import javax.ws.rs.ext.WriterInterceptorContext; @Provider @Compress public class GZIPWriterInterceptor implements WriterInterceptor { @Override public void aroundWriteTo(WriterInterceptorContext context) throws IOException, WebApplicationException { MultivaluedMap headers = context.getHeaders(); headers.add("Content-Encoding", "gzip"); final OutputStream outputStream = context.getOutputStream(); context.setOutputStream(new GZIPOutputStream(outputStream)); context.proceed(); } } Note: it implements the WriterInterceptor, which is an interface for message body writer interceptors that wrap around calls to javax.ws.rs.ext.MessageBodyWriter.writeTo providers implementing WriterInterceptor contract must be either programmatically registered in a JAX-RS runtime or must be annotated with @Provider annotation to be automatically discovered by the JAX-RS runtime during a provider scanning phase. @Compress is the name binding annotation, which we will discuss more detailed in the coming paragraph “The interceptor gets a output stream from the WriterInterceptorContext and sets a new one which is a GZIP wrapper of the original output stream. After all interceptors are executed the output stream lastly set to the WriterInterceptorContext will be used for serialization of the entity. In the example above the entity bytes will be written to the GZIPOutputStream which will compress the stream data and write them to the original output stream. The original stream is always the stream which writes the data to the “wire”. When the interceptor is used on the server, the original output stream is the stream into which writes data to the underlying server container stream that sends the response to the client.” [2] “The overridden method aroundWriteTo() gets WriterInterceptorContext as a parameter. This context contains getters and setters for header parameters, request properties, entity, entity stream and other properties.” [2]; when you compress your response you should set the “Content-Encoding” header to “gzip” 1.2. Compress annotation Filters and interceptors can be name-bound. Name binding is a concept that allows to say to a JAX-RS runtime that a specific filter or interceptor will be executed only for a specific resource method. When a filter or an interceptor is limited only to a specific resource method we say that it is name-bound. Filters and interceptors that do not have such a limitation are called global. In our case we’ve built the @Compress annotation: package org.codingpedia.demo.rest.interceptors; import java.lang.annotation.Retention; import java.lang.annotation.RetentionPolicy; import javax.ws.rs.NameBinding; //@Compress annotation is the name binding annotation @NameBinding @Retention(RetentionPolicy.RUNTIME) public @interface Compress {} and used it to mark methods on resources which should be gzipped (e.g. when GET-ing all the podcasts with the PodcastsResource): @Component @Path("/podcasts") public class PodcastsResource { @Autowired private PodcastService podcastService; ........................... /* * *********************************** READ *********************************** */ /** * Returns all resources (podcasts) from the database * * @return * @throws IOException * @throws JsonMappingException * @throws JsonGenerationException * @throws AppException */ @GET @Compress @Produces({ MediaType.APPLICATION_JSON, MediaType.APPLICATION_XML }) public List getPodcasts( @QueryParam("orderByInsertionDate") String orderByInsertionDate, @QueryParam("numberDaysToLookBack") Integer numberDaysToLookBack) throws IOException, AppException { List podcasts = podcastService.getPodcasts( orderByInsertionDate, numberDaysToLookBack); return podcasts; } ........................... } 2. Testing 2.1. SOAPui Well, if you are testing with SOAPui, you can issue the following request against the PodcastsResource Request: GET http://localhost:8888/demo-rest-jersey-spring/podcasts/?orderByInsertionDate=DESC HTTP/1.1 Accept-Encoding: gzip,deflate Accept: application/json, application/xml Host: localhost:8888 Connection: Keep-Alive User-Agent: Apache-HttpClient/4.1.1 (java 1.5) Response: HTTP/1.1 200 OK Content-Type: application/json Content-Encoding: gzip Content-Length: 409 Server: Jetty(9.0.7.v20131107) [ { "id": 2, "title": "Quarks & Co - zum Mitnehmen", "linkOnPodcastpedia": "http://www.podcastpedia.org/quarks", "feed": "http://podcast.wdr.de/quarks.xml", "description": "Quarks & Co: Das Wissenschaftsmagazin", "insertionDate": "2014-10-29T10:46:13.00+0100" }, { "id": 1, "title": "- The Naked Scientists Podcast - Stripping Down Science", "linkOnPodcastpedia": "http://www.podcastpedia.org/podcasts/792/-The-Naked-Scientists-Podcast-Stripping-Down-Science", "feed": "feed_placeholder", "description": "The Naked Scientists flagship science show brings you a lighthearted look at the latest scientific breakthroughs, interviews with the world top scientists, answers to your science questions and science experiments to try at home.", "insertionDate": "2014-10-29T10:46:02.00+0100" } ] SOAPui recognizes the Content-Type: gzip header, we’ve added in the GZIPWriterInterceptor and automatically uncompresses the response and displays it readable to the human eye. Well, that’s it. You’ve learned how Jersey makes it straightforward to compress the REST api responses. Tip: If you want really learn how to design and implement REST API in Java read the following Tutorial – REST API design and implementation in Java with Jersey and Spring
November 18, 2014
by Adrian Matei
· 62,802 Views · 2 Likes
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Using Eclipse's Link Source Feature
NOTE: Apparently a bundle with a linked source will not be exported or built in an update site built. also Tycho will complain that it can't find linked sources, which severely limits the possibilities. A workaround is to export the bundles as plain old jars (this works fine for some reason), but the problem is far from ideal. See bug reports: https://bugs.eclipse.org/bugs/show_bug.cgi?id=457192 https://bugs.eclipse.org/bugs/show_bug.cgi?id=66177 Introduction I've been using Eclipse for more than ten years now, and so I like to think I know my way around it's offerings, but every now and then I get pleasantly surprised by discovering a feature – which usually had been there all along- but for which I finally have made the time to investigate. In this case, I am talking about the 'Link Source' feature in the Project Properties tab. Most experienced Eclipse users will at some point wander through the project properties, for instance when certain libraries are not found by the compiler, or when a plugin project starts to behave unexpectedly. The Project Properties tab comes into play when the Manifest.MF file no longer provides the answers for certain problems you face, and you need to delve deeper into the classpath and project settings. It also becomes topical when you need to make a custom project. At Project Chaupal we are currently maintaining and updating the code from Project JXTA. JXTA has been around for quite a bit in the open source community, and the development has had its ups and downs, so the code could do with a makeover here and there. I've been involved with keeping the code available in OSGI since 2006 or so – also with its ups and downs- and one of my ideals would be to automatically generate the OSGI bundles straight from the JXTA sources, without any handwork. The JXTA jar ships with a large number of third party libraries (e.g. Jetty and Log4j), some of which are available as OSGI bundles, so I don't want to include them in the JXTA OSGI bundle I make. A list of dependencies in the Manifest should be enough! Some of the third party libraries also aim to provide the same functionality (e.g. the database functionality provided by Derby and H2), so I would prefer to divide this over two bundles, and then just select the bundle that is needed. Ever since JXTA 2.6, the code has been mavenised, and so the code now conforms to the typical structure that Maven requires, with a specific location for JAVA code (src/main/java), resources (src/main/resources) and tests (src/main/test). I prefer to use Tycho for my OSGI bundles, so the regular Eclipse tooling is leading. As a result my goal is to: Create separate bundles for the core and the test source code Add the required resources, such as .properties files and the likes Split the core source code over different bundles, so that every bundle depends on one third party library at the most. It took me a day or two to get everything the way I wanted it, but in the end it was surprisingly easy, so I thought I'd share the experience.This tutorial assumes that you are well-versed in Eclipse and OSGI development. If not, a good tutorial on the subject can be found here. Preparation As was described earlier, the plan is to use a Maven project (available on GitHub) as a source for a number of OSGI bundles. For starters, we need to do the following; Prepare an Eclipse IDE with Egit and, optionally, with support for GitHub. As always, Lars Vogel's tutorial provides an excellent guide to achieve this. With the GitHub support you can actually search for the required repository, and clone it in your workspace within minutes. Add Maven Support for Eclipse. The tutorial can be found here. We now have an Eclipse IDE with one project loaded in the workspace, which conforms to the Maven structure. Now we can start to do the magic! Extracting Source Files in an OSGI Project First create a new plugin project, using the wizard (File → new → Plugin Project). Fill in the required details as requested (target platform→OSGI framework) and press 'finish'. We now have a standard textbook OSGI bundle project. For the sake of argument, let's call this bundle org.mybundle.host. Now we are going to add java source files and resources from the Maven project: open the project properties tab (right mouse click → properties) select the 'Java build path' option and choose the 'source' tab press 'Link Source' and browse to the 'main/java' subfolder of the Maven project. Close the project properties Include the source folder in the build.properties file and clean the workspace Update the Manifest to include the required dependencies, and export the packages as needed As you can see, the java files have been included in the bundle project, and will compile in a normal fashion. TIP: Currently the source file will by default have the same name as the folder. You can change this in the 'link source' wizard. For instance, you can delete the 'src' folder that is created by default, and replace it with the linked source if you want. This should only be considered if you are not going to make specific java files in the bundle. Next we are going to include the resources, such as .properties files that are included in the Maven project. As an exercise, we will exclude all html files that may be included. Open the project properties and follow the steps described previously, but now select the main/resources folder. Then press the 'next' tab, instead of closing You can now select which files to include or exclude in your bundle. Select the 'exclude' tab, and enter the following pattern: **/*.htm*. Close the project properties, update the build path and clean the project We have now included the desired resources, and in principle the bundle should now work as desired. With the include and exclude tabs, you can determine which files and folders you want to add to your bundle. The inclusion and exclusion patterns follow the conventions used by Apache ANT. TIP: You can check if the bundle has the correct source and resource files by opening a file explorer (in Windows) and browsing to the 'bin' folder of your bundle project. If you first refresh your bundle project (F5 in the Eclipse IDE), the correct class and resource files should be present there. NOTE: Although I would not recommend it, it is possible to link the sources of multiple non-OSGI code sources this way. Even though the folders need different names, they will be built as if they are one source folder. Now we create a second plugin project for the test files. We will call this bundle org.mybundle.test Open the project properties and follow the steps described previously, but now select the main/test folder. If required, you can exclude certain tests in the 'exclude' tab Close the project properties, update the build path and clean the project In the manifest editor, include the dependencies to org.mybundle.host, and for instance JUnit and JMock. When there are no more compiler errors, your two bundles should behave as regular OSGI bundles, with the only difference that the sources are extracted from the Maven project. TIP: It is also possible to make fragment bundles this way, and you can include library resources in your bundle (such as third party jars). This way you can restructure a non-OSGI project at will Using Variables When you store your projects in the cloud, such as on gitHub, you may often find multiple versions of your workspace scattered over different computers, and your repositories stored on different drives. This means that linking your sources with absolute paths, as we have done previously, is not a very versatile approach. Especially with linking this may become problematic, as the linked source project (e.g. the maven project) can be stored on a different location than the project that uses the source files. Luckily eclipse allows you to define variables in your project, which can help either to standardise the relative locations or, if this is not possible, to easily modify the links. In order to achive this, follow these steps: Select the project properties, and select the 'Java Build Path' option. Add or Edit a link source, and select the 'variables' button. Add one or more new variables by pressing the 'New' button and entering the locations. Then press 'OK' As an example, the following three variables point to two GitHub projects, one which holds the Maven project, while the bundle project is located in the same subfolder: - GITHUB_LOC: C:/Users/MyName/MyGithubLocation - MYPROJECT_LOC: ${GITHUB_LOC}/MyProject - MYSOURCEPROJECT_LOC: ${MYPROJECT_LOC}/MySource Now all you have to do is change the 'Linked folder location' to: MYSOURCEPROJECT_LOC/src/main/java in order to include the Maven project in your bundle.You can then also add a resource folder: MYSOURCEPROJECT_LOC/src/main/resources TIP: In the above example with a Maven project, the linked folder name will default to 'java' (and the resources to 'resources'). It is recommended to leave it that way, because you can then use the 'src' folder for bundle specific code that yuo may want to add, like a decalarative service. Also remember to update the build path to include the folders your project needs. Conclusion The 'link source' option provides a powerful way to make non-OSGI code accessible as OSGI bundles. The inclusion and exclusion patterns allow you to customise the bundles to your needs.
November 13, 2014
by Kees Pieters
· 16,267 Views · 1 Like
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Missing Stack Traces for Repeated Exceptions
A long while ago a optimisation was added to the JVM so that if the same exception is thrown again and again and again a single instance of the Exception is created without the stack trace filled in in order to increase performance. This is an excellent idea unless you are trying to diagnose a problem and you have missed the original error. If you forgot about this optimisation you send the afternoon looking at the following log output and weeping slightly. (In my defence I have a little one in the house hence the fuzzy brain and lack of blogging action this year) java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException java.lang.ArrayIndexOutOfBoundsException ... java.lang.Exception: Uncaught exceptions during test at oracle.jdevstudio-testware-tests.level0.testADFcMATS(/.../work/mw9111/jdeveloper/jdev/extensions/oracle.jdevstudio-testware-tests/abbot/common-adf/CreateNewCustomAppAndProjectWithName.xml:25) at oracle.jdevstudio-testware-tests.level0.testADFcMATS(/.../work/mw9111/jdeveloper/jdev/extensions/oracle.jdevstudio-testware-tests/abbot/level0/testADFcMATS.xml:94) at oracle.abbot.JDevScriptFixture.runTest(JDevScriptFixture.java:555) at junit.framework.TestCase.runBare(TestCase.java:134) at junit.framework.TestResult$1.protect(TestResult.java:110) at junit.framework.TestResult.runProtected(TestResult.java:128) at junit.framework.TestResult.run(TestResult.java:113) at junit.framework.TestCase.run(TestCase.java:124) at junit.framework.TestSuite.runTest(TestSuite.java:243) at junit.framework.TestSuite.run(TestSuite.java:238) at junit.textui.TestRunner.doRun(TestRunner.java:116) at junit.textui.TestRunner.doRun(TestRunner.java:109) at oracle.abbot.AbbotRunner.run(AbbotRunner.java:614) at oracle.abbot.AbbotAddin$IdeAbbotRunner.run(AbbotAddin.java:634) at java.lang.Thread.run(Thread.java:745) Caused by: java.lang.ArrayIndexOutOfBoundsException [Crickets] It turns out that you can turn off this optimisation with a simple flag: java -XX:-OmitStackTraceInFastThrow .... In my particular case the actual exception causing this trouble was a NPE from the GlyphView code in JDK8. (One that is being caused by a glitch in hotspot it seems) But that in turn was causing the AIOOBE in some logging code clouding the issue even more. This in particular is a good flag to add by default when running your automated tests, particularly in combination with the stack trace length override I have talked about before.
November 9, 2014
by Gerard Davison
· 11,553 Views · 1 Like
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Java regex matching hashmap
A hashmap which maintains keys as regular expressions. Any pattern matching the expression will be able to retrieve the same value. Internally it maintains two maps, one containing the regex to value, and another containing matched pattern to regex. Whenever there is a new pattern to 'get', there will be a O(n) search through the compiled regex(s) (which have been 'put' as keys) to find a match. Existing patterns will have constant time lookup through two maps. import java.util.ArrayList; import java.util.Collection; import java.util.HashMap; import java.util.Iterator; import java.util.List; import java.util.Map; import java.util.Set; import java.util.WeakHashMap; import java.util.regex.Pattern; public class RegexHashMap implements Map { private class PatternMatcher { private final String regex; private final Pattern compiled; PatternMatcher(String name) { regex = name; compiled = Pattern.compile(regex); } boolean matched(String string) { if(compiled.matcher(string).matches()) { ref.put(string, regex); return true; } return false; } } /** * Map of input to pattern */ private final Map ref; /** * Map of pattern to value */ private final Map map; /** * Compiled patterns */ private final List matchers; @Override public String toString() { return "RegexHashMap [ref=" + ref + ", map=" + map + "]"; } /** * */ public RegexHashMap() { ref = new WeakHashMap(); map = new HashMap(); matchers = new ArrayList(); } /** * Returns the value to which the specified key pattern is mapped, or null if this map contains no mapping for the key pattern */ @Override public V get(Object weakKey) { if(!ref.containsKey(weakKey)) { for(PatternMatcher matcher : matchers) { if(matcher.matched((String) weakKey)) { break; } } } if(ref.containsKey(weakKey)) { return map.get(ref.get(weakKey)); } return null; } /** * Associates a specified regular expression to a particular value */ @Override public V put(String key, V value) { V v = map.put(key, value); if (v == null) { matchers.add(new PatternMatcher(key)); } return v; } /** * Removes the regular expression key */ @Override public V remove(Object key) { V v = map.remove(key); if(v != null) { for(Iterator iter = matchers.iterator(); iter.hasNext();) { PatternMatcher matcher = iter.next(); if(matcher.regex.equals(key)) { iter.remove(); break; } } for(Iterator> iter = ref.entrySet().iterator(); iter.hasNext();) { Entry entry = iter.next(); if(entry.getValue().equals(key)) { iter.remove(); } } } return v; } /** * Set of view on the regular expression keys */ @Override public Set> entrySet() { return map.entrySet(); } @Override public void putAll(Map m) { for(Entry entry : m.entrySet()) { put(entry.getKey(), entry.getValue()); } } @Override public int size() { return map.size(); } @Override public boolean isEmpty() { return map.isEmpty(); } /** * Returns true if this map contains a mapping for the specified regular expression key. */ @Override public boolean containsKey(Object key) { return map.containsKey(key); } /** * Returns true if this map contains a mapping for the specified regular expression matched pattern. * @param key * @return */ public boolean containsKeyPattern(Object key) { return ref.containsKey(key); } @Override public boolean containsValue(Object value) { return map.containsValue(value); } @Override public void clear() { map.clear(); matchers.clear(); ref.clear(); } /** * Returns a Set view of the regular expression keys contained in this map. */ @Override public Set keySet() { return map.keySet(); } /** * Returns a Set view of the regex matched patterns contained in this map. The set is backed by the map, so changes to the map are reflected in the set, and vice-versa. * @return */ public Set keySetPattern() { return ref.keySet(); } @Override public Collection values() { return map.values(); } /** * Produces a map of patterns to values, based on the regex put in this map * @param patterns * @return */ public Map transform(List patterns) { for(String pattern : patterns) { get(pattern); } Map transformed = new HashMap(); for(Entry entry : ref.entrySet()) { transformed.put(entry.getKey(), map.get(entry.getValue())); } return transformed; } public static void main(String...strings) { RegexHashMap rh = new RegexHashMap(); rh.put("[o|O][s|S][e|E].?[1|2]", "This is a regex match"); rh.put("account", "This is a direct match"); System.out.println(rh); System.out.println("get:ose-1 -> "+rh.get("ose-1")); System.out.println("get:OSE2 -> "+rh.get("OSE2")); System.out.println("get:OSE112 -> "+rh.get("OSE112")); System.out.println("get:ose-2 -> "+rh.get("ose-2")); System.out.println("get:account -> "+rh.get("account")); System.out.println(rh); } }
November 7, 2014
by Sutanu Dalui
· 23,834 Views
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Hibernate Collections: Optimistic Locking
Introduction Hibernate provides an optimistic locking mechanism to prevent lost updates even for long-conversations. In conjunction with an entity storage, spanning over multiple user requests (extended persistence context or detached entities) Hibernate can guarantee application-level repeatable-reads. The dirty checking mechanism detects entity state changes and increments the entity version. While basic property changes are always taken into consideration, Hibernate collections are more subtle in this regard. Owned vs. Inverse Collections In relational databases, two records are associated through a foreign key reference. In this relationship, the referenced record is the parent while the referencing row (the foreign key side) is the child. A non-null foreign key may only reference an existing parent record. In the Object-oriented space this association can be represented in both directions. We can have a many-to-one reference from a child to parent and the parent can also have a one-to-many children collection. Because both sides could potentially control the database foreign key state, we must ensure that only one side is the owner of this association. Only the owningside state changes are propagated to the database. The non-owning side has been traditionally referred as the inverse side. Next I’ll describe the most common ways of modelling this association. The Unidirectional Parent-Owning-Side-Child Association Mapping Only the parent side has a @OneToMany non-inverse children collection. The child entity doesn’t reference the parent entity at all. @Entity(name = "post") public class Post { ... @OneToMany(cascade = CascadeType.ALL, orphanRemoval = true) private List comments = new ArrayList (); ... } The Unidirectional Parent-Owning-Side-Child Component Association Mapping Mapping The child side doesn’t always have to be an entity and we might model it as acomponent type instead. An Embeddable object (component type) may contain both basic types and association mappings but it can never contain an @Id. The Embeddable object is persisted/removed along with its owning entity. The parent has an @ElementCollection children association. The child entity may only reference the parent through the non-queryable Hibernate specific @Parentannotation. @Entity(name = "post") public class Post { ... @ElementCollection @JoinTable(name = "post_comments", joinColumns = @JoinColumn(name = "post_id")) @OrderColumn(name = "comment_index") private List comments = new ArrayList (); ... public void addComment(Comment comment) { comment.setPost(this); comments.add(comment); } } @Embeddable public class Comment { ... @Parent private Post post; ... } The Bidirectional Parent-Owning-Side-Child Association Mapping The parent is the owning side so it has a @OneToMany non-inverse (without a mappedBy directive) children collection. The child entity references the parent entity through a @ManyToOne association that’s neither insertable nor updatable: @Entity(name = "post") public class Post { ... @OneToMany(cascade = CascadeType.ALL, orphanRemoval = true) private List comments = new ArrayList (); ... public void addComment(Comment comment) { comment.setPost(this); comments.add(comment); } } @Entity(name = "comment") public class Comment ... @ManyToOne @JoinColumn(name = "post_id", insertable = false, updatable = false) private Post post; ... } The Bidirectional Parent-Owning-Side-Child Association Mapping The child entity references the parent entity through a @ManyToOne association, and the parent has a mappedBy @OneToMany children collection. The parent side is the inverse side so only the @ManyToOne state changes are propagated to the database. Even if there’s only one owning side, it’s always a good practice to keep both sides in sync by using the add/removeChild() methods. @Entity(name = "post") public class Post { ... @OneToMany(cascade = CascadeType.ALL, orphanRemoval = true, mappedBy = "post") private List comments = new ArrayList (); ... public void addComment(Comment comment) { comment.setPost(this); comments.add(comment); } } @Entity(name = "comment") public class Comment { ... @ManyToOne private Post post; ... } The Unidirectional Parent-Owning-Side-Child Association Mapping The child entity references the parent through a @ManyToOne association. The parent doesn’t have a @OneToMany children collection so the child entity becomes the owning side. This association mapping resembles the relational data foreign key linkage. @Entity(name = "comment") public class Comment { ... @ManyToOne private Post post; ... } Collection Versioning The 3.4.2 section of the JPA 2.1 specification defines optimistic locking as: The version attribute is updated by the persistence provider runtime when the object is written to the database. All non-relationship fields and proper ties and all relationships owned by the entity are included in version checks[35]. [35] This includes owned relationships maintained in join tables N.B. Only owning-side children collection can update the parent version. Testing Time Let’s test how the parent-child association type affects the parent versioning. Because we are interested in the children collection dirty checking, theunidirectional child-owning-side-parent association is going to be skipped, as in that case the parent doesn’t contain a children collection. Test Case The following test case is going to be used for all collection type use cases: protected void simulateConcurrentTransactions(final boolean shouldIncrementParentVersion) { final ExecutorService executorService = Executors.newSingleThreadExecutor(); doInTransaction(new TransactionCallable () { @Override public Void execute(Session session) { try { P post = postClass.newInstance(); post.setId(1L); post.setName("Hibernate training"); session.persist(post); return null; } catch (Exception e) { throw new IllegalArgumentException(e); } } }); doInTransaction(new TransactionCallable () { @Override public Void execute(final Session session) { final P post = (P) session.get(postClass, 1L); try { executorService.submit(new Callable () { @Override public Void call() throws Exception { return doInTransaction(new TransactionCallable () { @Override public Void execute(Session _session) { try { P otherThreadPost = (P) _session.get(postClass, 1L); int loadTimeVersion = otherThreadPost.getVersion(); assertNotSame(post, otherThreadPost); assertEquals(0L, otherThreadPost.getVersion()); C comment = commentClass.newInstance(); comment.setReview("Good post!"); otherThreadPost.addComment(comment); _session.flush(); if (shouldIncrementParentVersion) { assertEquals(otherThreadPost.getVersion(), loadTimeVersion + 1); } else { assertEquals(otherThreadPost.getVersion(), loadTimeVersion); } return null; } catch (Exception e) { throw new IllegalArgumentException(e); } } }); } }).get(); } catch (Exception e) { throw new IllegalArgumentException(e); } post.setName("Hibernate Master Class"); session.flush(); return null; } }); } The Unidirectional Parent-Owning-Side-Child Association Testing #create tables Query:{[create table comment (idbigint generated by default as identity (start with 1), review varchar(255), primary key (id))][]} Query:{[create table post (idbigint not null, name varchar(255), version integer not null, primary key (id))][]} Query:{[create table post_comment (post_id bigint not null, comments_id bigint not null, comment_index integer not null, primary key (post_id, comment_index))][]} Query:{[alter table post_comment add constraint FK_se9l149iyyao6va95afioxsrl foreign key (comments_id) references comment][]} Query:{[alter table post_comment add constraint FK_6o1igdm04v78cwqre59or1yj1 foreign key (post_id) references post][]} #insert post in primary transaction Query:{[insert into post (name, version, id) values (?, ?, ?)][Hibernate training,0,1]} #select post in secondary transaction Query:{[selectentityopti0_.idas id1_1_0_, entityopti0_.name as name2_1_0_, entityopti0_.version as version3_1_0_ from post entityopti0_ where entityopti0_.id=?][1]} #insert comment in secondary transaction #optimistic locking post version update in secondary transaction Query:{[insert into comment (id, review) values (default, ?)][Good post!]} Query:{[update post setname=?, version=? where id=? and version=?][Hibernate training,1,1,0]} Query:{[insert into post_comment (post_id, comment_index, comments_id) values (?, ?, ?)][1,0,1]} #optimistic locking exception in primary transaction Query:{[update post setname=?, version=? where id=? and version=?][Hibernate Master Class,1,1,0]} org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.vladmihalcea.hibernate.masterclass.laboratory.concurrency.EntityOptimisticLockingOnUnidirectionalCollectionTest$Post#1] The Unidirectional Parent-Owning-Side-Child Component Association Testing #create tables Query:{[create table post (idbigint not null, name varchar(255), version integer not null, primary key (id))][]} Query:{[create table post_comments (post_id bigint not null, review varchar(255), comment_index integer not null, primary key (post_id, comment_index))][]} Query:{[alter table post_comments add constraint FK_gh9apqeduab8cs0ohcq1dgukp foreign key (post_id) references post][]} #insert post in primary transaction Query:{[insert into post (name, version, id) values (?, ?, ?)][Hibernate training,0,1]} #select post in secondary transaction Query:{[selectentityopti0_.idas id1_0_0_, entityopti0_.name as name2_0_0_, entityopti0_.version as version3_0_0_ from post entityopti0_ where entityopti0_.id=?][1]} Query:{[selectcomments0_.post_id as post_id1_0_0_, comments0_.review as review2_1_0_, comments0_.comment_index as comment_3_0_ from post_comments comments0_ where comments0_.post_id=?][1]} #insert comment in secondary transaction #optimistic locking post version update in secondary transaction Query:{[update post setname=?, version=? where id=? and version=?][Hibernate training,1,1,0]} Query:{[insert into post_comments (post_id, comment_index, review) values (?, ?, ?)][1,0,Good post!]} #optimistic locking exception in primary transaction Query:{[update post setname=?, version=? where id=? and version=?][Hibernate Master Class,1,1,0]} org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.vladmihalcea.hibernate.masterclass.laboratory.concurrency.EntityOptimisticLockingOnComponentCollectionTest$Post#1] The Bidirectional Parent-Owning-Side-Child Association Testing #create tables Query:{[create table comment (idbigint generated by default as identity (start with 1), review varchar(255), post_id bigint, primary key (id))][]} Query:{[create table post (idbigint not null, name varchar(255), version integer not null, primary key (id))][]} Query:{[create table post_comment (post_id bigint not null, comments_id bigint not null)][]} Query:{[alter table post_comment add constraint UK_se9l149iyyao6va95afioxsrl unique (comments_id)][]} Query:{[alter table comment add constraint FK_f1sl0xkd2lucs7bve3ktt3tu5 foreign key (post_id) references post][]} Query:{[alter table post_comment add constraint FK_se9l149iyyao6va95afioxsrl foreign key (comments_id) references comment][]} Query:{[alter table post_comment add constraint FK_6o1igdm04v78cwqre59or1yj1 foreign key (post_id) references post][]} #insert post in primary transaction Query:{[insert into post (name, version, id) values (?, ?, ?)][Hibernate training,0,1]} #select post in secondary transaction Query:{[selectentityopti0_.idas id1_1_0_, entityopti0_.name as name2_1_0_, entityopti0_.version as version3_1_0_ from post entityopti0_ where entityopti0_.id=?][1]} Query:{[selectcomments0_.post_id as post_id1_1_0_, comments0_.comments_id as comments2_2_0_, entityopti1_.idas id1_0_1_, entityopti1_.post_id as post_id3_0_1_, entityopti1_.review as review2_0_1_, entityopti2_.idas id1_1_2_, entityopti2_.name as name2_1_2_, entityopti2_.version as version3_1_2_ from post_comment comments0_ inner joincomment entityopti1_ on comments0_.comments_id=entityopti1_.idleft outer joinpost entityopti2_ on entityopti1_.post_id=entityopti2_.idwhere comments0_.post_id=?][1]} #insert comment in secondary transaction #optimistic locking post version update in secondary transaction Query:{[insert into comment (id, review) values (default, ?)][Good post!]} Query:{[update post setname=?, version=? where id=? and version=?][Hibernate training,1,1,0]} Query:{[insert into post_comment (post_id, comments_id) values (?, ?)][1,1]} #optimistic locking exception in primary transaction Query:{[update post setname=?, version=? where id=? and version=?][Hibernate Master Class,1,1,0]} org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.vladmihalcea.hibernate.masterclass.laboratory.concurrency.EntityOptimisticLockingOnBidirectionalParentOwningCollectionTest$Post#1] The Bidirectional Parent-Owning-Side-Child Association Testing #create tables Query:{[create table comment (idbigint generated by default as identity (start with 1), review varchar(255), post_id bigint, primary key (id))][]} Query:{[create table post (idbigint not null, name varchar(255), version integer not null, primary key (id))][]} Query:{[alter table comment add constraint FK_f1sl0xkd2lucs7bve3ktt3tu5 foreign key (post_id) references post][]} #insert post in primary transaction Query:{[insert into post (name, version, id) values (?, ?, ?)][Hibernate training,0,1]} #select post in secondary transaction Query:{[selectentityopti0_.idas id1_1_0_, entityopti0_.name as name2_1_0_, entityopti0_.version as version3_1_0_ from post entityopti0_ where entityopti0_.id=?][1]} #insert comment in secondary transaction #post version is not incremented in secondary transaction Query:{[insert into comment (id, post_id, review) values (default, ?, ?)][1,Good post!]} Query:{[selectcount(id) from comment where post_id =?][1]} #update works in primary transaction Query:{[update post setname=?, version=? where id=? and version=?][Hibernate Master Class,1,1,0]} If you enjoy reading this article, you might want to subscribe to my newsletter and get a discount for my book as well. Overruling Default Collection Versioning If the default owning-side collection versioning is not suitable for your use case, you can always overrule it with Hibernate [a href="http://docs.jboss.org/hibernate/annotations/3.5/reference/en/html_single/#d0e2903" style="font-family: inherit; font-size: 14px; font-style: inherit; font-weight: inherit; text-decoration: none; color: rgb(1, 160, 219); -webkit-tap-highlight-color: rgb(240, 29, 79); background: transparent;"]@OptimisticLock annotation. Let’s overrule the default parent version update mechanism for bidirectional parent-owning-side-child association: @Entity(name = "post") public class Post { ... @OneToMany(cascade = CascadeType.ALL, orphanRemoval = true) @OptimisticLock(excluded = true) private List comments = new ArrayList (); ... public void addComment(Comment comment) { comment.setPost(this); comments.add(comment); } } @Entity(name = "comment") public class Comment { ... @ManyToOne @JoinColumn(name = "post_id", insertable = false, updatable = false) private Post post; ... } This time, the children collection changes won’t trigger a parent version update: #create tables Query:{[create table comment (idbigint generated by default as identity (start with 1), review varchar(255), post_id bigint, primary key (id))][]} Query:{[create table post (idbigint not null, name varchar(255), version integer not null, primary key (id))][]} Query:{[create table post_comment (post_id bigint not null, comments_id bigint not null)][]} Query:{[]} Query:{[alter table comment add constraint FK_f1sl0xkd2lucs7bve3ktt3tu5 foreign key (post_id) references post][]} Query:{[alter table post_comment add constraint FK_se9l149iyyao6va95afioxsrl foreign key (comments_id) references comment][]} Query:{[alter table post_comment add constraint FK_6o1igdm04v78cwqre59or1yj1 foreign key (post_id) references post][]} #insert post in primary transaction Query:{[insert into post (name, version, id) values (?, ?, ?)][Hibernate training,0,1]} #select post in secondary transaction Query:{[selectentityopti0_.idas id1_1_0_, entityopti0_.name as name2_1_0_, entityopti0_.version as version3_1_0_ from post entityopti0_ where entityopti0_.id=?][1]} Query:{[selectcomments0_.post_id as post_id1_1_0_, comments0_.comments_id as comments2_2_0_, entityopti1_.idas id1_0_1_, entityopti1_.post_id as post_id3_0_1_, entityopti1_.review as review2_0_1_, entityopti2_.idas id1_1_2_, entityopti2_.name as name2_1_2_, entityopti2_.version as version3_1_2_ from post_comment comments0_ inner joincomment entityopti1_ on comments0_.comments_id=entityopti1_.idleft outer joinpost entityopti2_ on entityopti1_.post_id=entityopti2_.idwhere comments0_.post_id=?][1]} #insert comment in secondary transaction Query:{[insert into comment (id, review) values (default, ?)][Good post!]} Query:{[insert into post_comment (post_id, comments_id) values (?, ?)][1,1]} #update works in primary transaction Query:{[update post setname=?, version=? where id=? and version=?][Hibernate Master Class,1,1,0]} If you enjoyed this article, I bet you are going to love my book as well. Conclusion It’s very important to understand how various modeling structures impact concurrency patterns. The owning side collections changes are taken into consideration when incrementing the parent version number, and you can always bypass it using the @OptimisticLock annotation. Code available on GitHub. If you have enjoyed reading my article and you’re looking forward to getting instant email notifications of my latest posts, you just need to follow my blog.
November 4, 2014
by Vlad Mihalcea
· 61,869 Views · 1 Like
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Spring Caching Abstraction and Google Guava Cache
Spring provides a great out of the box support for caching expensive method calls. The caching abstraction is covered in a great detail here. My objective here is to cover one of the newer cache implementations that Spring now provides with 4.0+ version of the framework - using Google Guava Cache In brief, consider a service which has a few slow methods: public class DummyBookService implements BookService { @Override public Book loadBook(String isbn) { // Slow method 1. } @Override public List loadBookByAuthor(String author) { // Slow method 2 } } With Spring Caching abstraction, repeated calls with the same parameter can be sped up by an annotation on the method along these lines - here the result of loadBook is being cached in to a "book" cache and listing of books cached into another "books" cache: public class DummyBookService implements BookService { @Override @Cacheable("book") public Book loadBook(String isbn) { // slow response time.. } @Override @Cacheable("books") public List loadBookByAuthor(String author) { // Slow listing } } Now, Caching abstraction support requires a CacheManager to be available which is responsible for managing the underlying caches to store the cached results, with the new Guava Cache support the CacheManager is along these lines: @Bean public CacheManager cacheManager() { return new GuavaCacheManager("books", "book"); } Google Guava Cache provides a rich API to be able to pre-load the cache, set eviction duration based on last access or created time, set the size of the cache etc, if the cache is to be customized then a guava CacheBuilder can be passed to the CacheManager for this customization: @Bean public CacheManager cacheManager() { GuavaCacheManager guavaCacheManager = new GuavaCacheManager(); guavaCacheManager.setCacheBuilder(CacheBuilder.newBuilder().expireAfterAccess(30, TimeUnit.MINUTES)); return guavaCacheManager; } This works well if all the caches have a similar configuration, what if the caches need to be configured differently - for eg. in the sample above, I may want the "book" cache to never expire but the "books" cache to have an expiration of 30 mins, then the GuavaCacheManager abstraction does not work well, instead a better solution is actually to use a SimpleCacheManager which provides a more direct way to get to the cache and can be configured this way: @Bean public CacheManager cacheManager() { SimpleCacheManager simpleCacheManager = new SimpleCacheManager(); GuavaCache cache1 = new GuavaCache("book", CacheBuilder.newBuilder().build()); GuavaCache cache2 = new GuavaCache("books", CacheBuilder.newBuilder() .expireAfterAccess(30, TimeUnit.MINUTES) .build()); simpleCacheManager.setCaches(Arrays.asList(cache1, cache2)); return simpleCacheManager; } This approach works very nicely, if required certain caches can be configured to be backed by a different caching engines itself, say a simple hashmap, some by Guava or EhCache some by distributed caches like Gemfire.
November 3, 2014
by Biju Kunjummen
· 60,174 Views · 8 Likes
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BigList: a Scalable High-Performance List for Java
As memory gets cheaper and cheaper, our applications can keep more data readily available in main memory, or even all as in case of in-memory databases. To make real use of the growing heap memory, appropriate data structures must be used. Interesting enough, there seem to be no specialized implementations for lists - by far the most used collection. This article introduces BigList, a list designed for handling large collections where large means that all data still fit completely in the heap memory. The article will show the special requirements for handling large collections, how BigList is implemented and how it compares to other list implementations. 1. Requirements What are the special requirements we need to handle large collections efficiently? Memory: Sparing use of memory: The list should need little memory for its own implementation so memory can be used for storing application data. Specialized versions for primitives: It must be possible to store common primitives like ints in a memory saving way. Avoid copying large data blocks: If the list grows or shrinks, only a small part of the data must be copied around, as this operation becomes expensive and needs the same amount of memory again. Data sharing: copying collections is a frequent operation which should be efficiently possible even if the collection is large. An efficient implementation requires some sort of data sharing as copying all elements is per se a costly operation. Performance: Good performance for normal operations like reading, storing, adding or removing single elements. Great performance for bulk operations like adding or removing multiple elements. Predictable overhead of operations, so similar operations should need a similar amount of time without excessive worst case scenarios. If an implementation does not offer these features, some operations will not only be slow for really large collections, but will becomse just not feasible because memory or CPU usage will be too exhaustive. Introduction to BigList BigList is a member of the Brownies Collections library which also includes GapList, the fastest list implementation known. GapList is a drop-in replacement for ArrayList, LinkedList, or ArrayDequeue and offers fast access by index and fast insertion/removal at the beginning and at the end at the same time. GapList however has not been designed to cope with large collections, so adding or removing elements can make it necessary to copy a lot of elements around which will lead to performance problems. Also copying a large collection becomes an expensive operation, both in term of time and memory consumption. It will simply not be possible to make a copy of a large collections if not the same amount of memory is available a second time. And this is a common operation as you often want to return a copy of an internal list through your API which has no reference the original list. BigList addresses both problems. The first problem is solved by storing the collection elements in fixed size blocks. Add or remove operations are then implemented to use only data from one block. The copying problem is solved by maintaining a reference count on the fixed size blocks which allows to implement a copy-on-write approach. For efficient access to the fixed size blocks, they are maintained in a specialized tree structure. 2. BigList Details Each BigList instance stores the following information: Elements are stored in in fixed-size blocks A single block is implemented as GapList with a reference count for sharing All blocks are maintained in a tree for fast access Access information for the current block is cached for better performance The following illustration shows these details for two instances of BigList which share one block. 2.1 Use of Blocks Elements are stored in in fixed-size blocks with a default block size of 1000. Where this default may look pretty small, it is most of the time a good choice because it guarantees that write operation only need to move few elements. Read operations will profit from locality of reference by using the currently cached block to be fast. It is however possible to specify the block size for each created BigList instance. All blocks except the first are allocated with this fixed size and will not grow or shrink. The first block will grow to the specified block size to save memory for small lists. If a block has reached its maximum size and more data must be stored within, the block needs to be split up in two blocks before more elements can be stored. If elements are added to the head or tail of the list, the block will only be filled up to a threshold of 95%. This allows inserts into the block without the immediate need for split operations. To save memory, blocks are also merged. This happens automatically if two adjacent blocks are both filled less than 35% after a remove operation. 2.2 Locality of Reference For each operation on BigList, the affected block must be determined first. As predicted by locality of reference, most of the time the affected block will be the same as for the last operation. The implementation of BigList has therefore been designed to profit from locality of reference which makes common operations like iterating over a list very efficient. Instead of always traversing the block tree to determine the block needed for an operation, lower and upper index of the last used block are cached. So if the next operation happens near to the previous one, the same block can be used again without need to traverse the tree. 2.3 Reference Counting To support a copy-on-write approach, BigList stores a reference count for each fixed size blocks indicating whether this block is private or shared. Initially all lists are private having a reference count of 0, so that modification are allowed. If a list is copied, the reference count is incremented which prohibits further modifications. Before a modification then can be made, the block must be copied decrementing the block's reference count and setting the reference count of the copy to 0. The reference count of a block is then decremented by the finalizer of BigList. 3. Benchmarks To prove the excellence of BigList in time and memory consumption, we compare it with some other List implementations. And here are the nominees: Type Library Description BigList brownie-collections List optimized for storing large number of elements. Elements stored in fixed size blocks which are maintained in a tree. GapList brownie-collections Fastest list implementation known. Fast access by index and fast insertion/removal at end and at beginning. ArrayList JDK Maintains elements in a single array. Fast access by index, fast insertion/removal at end, but slow at beginning. LinkedList JDK Elements stored using a linked list. Slow access by index. Memory overhead for each element stored. TreeList commons-collections Elements stored in a tree. All operations are not really fast, but there are no very slow operations. Memory overhead for each element stored. FastTable javolution Elements stored in a "fractal"-like data structure. Good performance and use of memory. However no bulk operations and collection does not shrink. 3.1 Handling Objects In the first part of the benchmark, we compare memory consumption and performance of the different list implementations. Let's first have a look at the memory consumption. The following table shows the bytes used to hold a list with 1'000'000 null elements: BigList GapList ArrayList LinkedList TreeList FastTable 32 bit 4'298'466 4'021'296 4'861'992 8'000'028 18'000'028 4'142'892 64 bit 8'544'254 8'042'552 9'723'964 16'000'044 26'000'044 8'222'988 We can see that BigList, GapList, ArrayList, and FastTable only add small overhead to the stored elements, where as Linkedlist needs twice the memory and TreeList even more. Now to the performance. Here are the results of 9 benchmarks which have been run for each of the 6 candidates with JDK 8 in a 32 bit Windows environment and a list of 1'000'000 elements: The result table can be read as follows: the fastest candidate for each test has a relative performance indicator of 1 the value for the other candidates indicate how many times they have been slower, so a factor of 3 means that this implementation was 3 times slower than the best one The different factor are colored like this: 
factor 1: green (best)
 factor <5: blue (good) 
factor <25: yellow (moderate) 
factor >25: red (poor) If we look the benchmark result, we can see that the performance of BigList is best for all expect two benchmarks. The only moderate result is produces in getting elements in a totally random order. This could be expected as there is no locality of reference which can be exploited, so for each access, the block tree must be traversed to find the correct block. Luckily this is a rare use case in real applications. And the benchmark "Get local" shows that performance is back to good as soon as elements next to each other must be retrieved - as it is the case if we iterate over a range. 3.2 Handling Primitives In the second part of the benchmark, we want see how big the savings are if we use a data structure specialized for storing primitives compared to strong wrapped objects. For this reason, we compare IntBigList and BigList. The following table shows memory needed to store 1'000'000 integer values: BigList IntBigList 32 bit 16'298'454 4'534'840 64 bit 28'544'234 4'570'432 Obviously it is easy to save a lot of memory. In a 32 bit environment, IntBigList just needs 25% percent of memory, in a 64 bit environment only 14%! These figures become plausible if you recall that a simple object needs 8 bytes in a 32 bit, but already 16 bytes in a 64 bit environment, where as a primitive integer value always only needs 4 bytes. The measurable performance gain is not so impressive, it is something below 10% for simple get operations and something above 10% for add and remove operations. These numbers show that the JVM is impressively fast in creating wrapper objects and boxing and unboxing primitive values. We must however also consider that each created object will need to be garbage collected once and therefore adds to the total load of the JVM. 4. Summary BigList is a scalable high-performance list for storing large collections. Its design guarantees that all operations will be predictable and efficient both in term of performance and memory consumption, even copying large collections is tremendous fast. Benchmarks haven proven this and shown that BigList outperform other known list implementations. The library also offers specialized implementations for primitive types like IntBigList which save much memory and provide superior performance. BigList for handling objects and the specializations for handling primitives are part of the Brownies Collections library and can be downloaded from http://www.magicwerk.org/collections.
November 3, 2014
by Thomas Mauch
· 33,038 Views · 10 Likes
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How to Setup Custom SSLSocketFactory's TrustManager per Each URL Connection
We can see from javadoc that javax.net.ssl.HttpsURLConnection provided a static method to override withsetDefaultSSLSocketFory() method. This allow you to supply a custom javax.net.ssl.TrustManagerthat may verify your own CA certs handshake and validation etc. But this will override the default for all "https" URLs per your JVM! So how can we override just a single https URL? Looking at javax.net.ssl.HttpsURLConnection again we see instance method for setSSLSocketFactory(), but we can't instantiate HttpsURLConnection object directly! It took me some digging to realized that the java.net.URL is actually an factory class for its implementation! One can get an instance like this using new URL("https://localhost").openConnection() To complete this article, I will provide a simple working example that demonstrate this. package zemian; import java.io.BufferedReader; import java.io.InputStream; import java.io.InputStreamReader; import java.net.URL; import java.net.URLConnection; import java.security.SecureRandom; import java.security.cert.X509Certificate; import javax.net.ssl.HttpsURLConnection; import javax.net.ssl.SSLContext; import javax.net.ssl.SSLSocketFactory; import javax.net.ssl.TrustManager; import javax.net.ssl.X509TrustManager; public class WGetText { public static void main(String[] args) throws Exception { String urlString = System.getProperty("url", "https://google.com"); URL url = new URL(urlString); URLConnection urlConnection = url.openConnection(); HttpsURLConnection httpsUrlConnection = (HttpsURLConnection) urlConnection; SSLSocketFactory sslSocketFactory = createSslSocketFactory(); httpsUrlConnection.setSSLSocketFactory(sslSocketFactory); try (InputStream inputStream = httpsUrlConnection.getInputStream()) { BufferedReader reader = new BufferedReader(new InputStreamReader(inputStream)); String line = null; while ((line = reader.readLine()) != null) { System.out.println(line); } } } private static SSLSocketFactory createSslSocketFactory() throws Exception { TrustManager[] byPassTrustManagers = new TrustManager[] { new X509TrustManager() { public X509Certificate[] getAcceptedIssuers() { return new X509Certificate[0]; } public void checkClientTrusted(X509Certificate[] chain, String authType) { } public void checkServerTrusted(X509Certificate[] chain, String authType) { } } }; SSLContext sslContext = SSLContext.getInstance("TLS"); sslContext.init(null, byPassTrustManagers, new SecureRandom()); return sslContext.getSocketFactory(); } }
October 31, 2014
by Zemian Deng
· 38,918 Views · 1 Like
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Spring Integration Error Handling with Router, ErrorChannel, and Transformer
This article explains how errors are handled when using the messaging system with Spring Integration and how to handle route and redirect to specific channel.
October 31, 2014
by Upender Chinthala
· 48,258 Views · 9 Likes
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Building a REST API with JAXB, Spring Boot and Spring Data
if someone asked you to develop a rest api on the jvm, which frameworks would you use? i was recently tasked with such a project. my client asked me to implement a rest api to ingest requests from a 3rd party. the project entailed consuming xml requests, storing the data in a database, then exposing the data to internal application with a json endpoint. finally, it would allow taking in a json request and turning it into an xml request back to the 3rd party. with the recent release of apache camel 2.14 and my success using it , i started by copying my apache camel / cxf / spring boot project and trimming it down to the bare essentials. i whipped together a simple hello world service using camel and spring mvc. i also integrated swagger into both. both implementations were pretty easy to create ( sample code ), but i decided to use spring mvc. my reasons were simple: its rest support was more mature, i knew it well, and spring mvc test makes it easy to test apis. camel's swagger support without web.xml as part of the aforementioned spike, i learned out how to configure camel's rest and swagger support using spring's javaconfig and no web.xml. i made this into a sample project and put it on github as camel-rest-swagger . this article shows how i built a rest api with java 8, spring boot/mvc, jaxb and spring data (jpa and rest components). i stumbled a few times while developing this project, but figured out how to get over all the hurdles. i hope this helps the team that's now maintaining this project (my last day was friday) and those that are trying to do something similar. xml to java with jaxb the data we needed to ingest from a 3rd party was based on the ncpdp standards. as a member, we were able to download a number of xsd files, put them in our project and generate java classes to handle the incoming/outgoing requests. i used the maven-jaxb2-plugin to generate the java classes. org.jvnet.jaxb2.maven2 maven-jaxb2-plugin 0.8.3 generate -xtostring -xequals -xhashcode -xcopyable org.jvnet.jaxb2_commons jaxb2-basics 0.6.4 src/main/resources/schemas/ncpdp the first error i ran into was about a property already being defined. [info] --- maven-jaxb2-plugin:0.8.3:generate (default) @ spring-app --- [error] error while parsing schema(s).location [ file:/users/mraible/dev/spring-app/src/main/resources/schemas/ncpdp/structures.xsd{1811,48}]. com.sun.istack.saxparseexception2; systemid: file:/users/mraible/dev/spring-app/src/main/resources/schemas/ncpdp/structures.xsd; linenumber: 1811; columnnumber: 48; property "multipletimingmodifierandtimingandduration" is already defined. use to resolve this conflict. at com.sun.tools.xjc.errorreceiver.error(errorreceiver.java:86) i was able to workaround this by upgrading to maven-jaxb2-plugin version 0.9.1. i created a controller and stubbed out a response with hard-coded data. i confirmed the incoming xml-to-java marshalling worked by testing with a sample request provided by our 3rd party customer. i started with a curl command, because it was easy to use and could be run by anyone with the file and curl installed. curl -x post -h 'accept: application/xml' -h 'content-type: application/xml' \ --data-binary @sample-request.xml http://localhost:8080/api/message -v this is when i ran into another stumbling block: the response wasn't getting marshalled back to xml correctly. after some research, i found out this was caused by the lack of @xmlrootelement annotations on my generated classes. i posted a question to stack overflow titled returning jaxb-generated elements from spring boot controller . after banging my head against the wall for a couple days, i figured out the solution . i created a bindings.xjb file in the same directory as my schemas. this causes jaxb to generate @xmlrootelement on classes. to add namespaces prefixes to the returned xml, i had to modify the maven-jaxb2-plugin to add a couple arguments. -extension -xnamespace-prefix and add a dependency: org.jvnet.jaxb2_commons jaxb2-namespace-prefix 1.1 then i modified bindings.xjb to include the package and prefix settings. i also moved into a global setting. i eventually had to add prefixes for all schemas and their packages. i learned how to add prefixes from the namespace-prefix plugins page . finally, i customized the code-generation process to generate joda-time's datetime instead of the default xmlgregoriancalendar . this involved a couple custom xmladapters and a couple additional lines in bindings.xjb . you can see the adapters and bindings.xjb with all necessary prefixes in this gist . nicolas fränkel's customize your jaxb bindings was a great resource for making all this work. i wrote a test to prove that the ingest api worked as desired. @runwith(springjunit4classrunner.class) @springapplicationconfiguration(classes = application.class) @webappconfiguration @dirtiescontext(classmode = dirtiescontext.classmode.after_class) public class initiaterequestcontrollertest { @inject private initiaterequestcontroller controller; private mockmvc mockmvc; @before public void setup() { mockitoannotations.initmocks(this); this.mockmvc = mockmvcbuilders.standalonesetup(controller).build(); } @test public void testgetnotallowedonmessagesapi() throws exception { mockmvc.perform(get("/api/initiate") .accept(mediatype.application_xml)) .andexpect(status().ismethodnotallowed()); } @test public void testpostpainitiationrequest() throws exception { string request = new scanner(new classpathresource("sample-request.xml").getfile()).usedelimiter("\\z").next(); mockmvc.perform(post("/api/initiate") .accept(mediatype.application_xml) .contenttype(mediatype.application_xml) .content(request)) .andexpect(status().isok()) .andexpect(content().contenttype(mediatype.application_xml)) .andexpect(xpath("/message/header/to").string("3rdparty")) .andexpect(xpath("/message/header/sendersoftware/sendersoftwaredeveloper").string("hid")) .andexpect(xpath("/message/body/status/code").string("010")); } } spring data for jpa and rest with jaxb out of the way, i turned to creating an internal api that could be used by another application. spring data was fresh in my mind after reading about it last summer. i created classes for entities i wanted to persist, using lombok's @data to reduce boilerplate. i read the accessing data with jpa guide, created a couple repositories and wrote some tests to prove they worked. i ran into an issue trying to persist joda's datetime and found jadira provided a solution. i added its usertype.core as a dependency to my pom.xml: org.jadira.usertype usertype.core 3.2.0.ga ... and annotated datetime variables accordingly. @column(name = "last_modified", nullable = false) @type(type="org.jadira.usertype.dateandtime.joda.persistentdatetime") private datetime lastmodified; with jpa working, i turned to exposing rest endpoints. i used accessing jpa data with rest as a guide and was looking at json in my browser in a matter of minutes. i was surprised to see a "profile" service listed next to mine, and posted a question to the spring boot team. oliver gierke provided an excellent answer . swagger spring mvc's integration for swagger has greatly improved since i last wrote about it . now you can enable it with a @enableswagger annotation. below is the swaggerconfig class i used to configure swagger and read properties from application.yml . @configuration @enableswagger public class swaggerconfig implements environmentaware { public static final string default_include_pattern = "/api/.*"; private relaxedpropertyresolver propertyresolver; @override public void setenvironment(environment environment) { this.propertyresolver = new relaxedpropertyresolver(environment, "swagger."); } /** * swagger spring mvc configuration */ @bean public swaggerspringmvcplugin swaggerspringmvcplugin(springswaggerconfig springswaggerconfig) { return new swaggerspringmvcplugin(springswaggerconfig) .apiinfo(apiinfo()) .genericmodelsubstitutes(responseentity.class) .includepatterns(default_include_pattern); } /** * api info as it appears on the swagger-ui page */ private apiinfo apiinfo() { return new apiinfo( propertyresolver.getproperty("title"), propertyresolver.getproperty("description"), propertyresolver.getproperty("termsofserviceurl"), propertyresolver.getproperty("contact"), propertyresolver.getproperty("license"), propertyresolver.getproperty("licenseurl")); } } after getting swagger to work, i discovered that endpoints published with @repositoryrestresource aren't picked up by swagger. there is an open issue for spring data support in the swagger-springmvc project. liquibase integration i configured this project to use h2 in development and postgresql in production. i used spring profiles to do this and copied xml/yaml (for maven and application*.yml files) from a previously created jhipster project. next, i needed to create a database. i decided to use liquibase to create tables, rather than hibernate's schema-export. i chose liquibase over flyway based of discussions in the jhipster project . to use liquibase with spring boot is dead simple: add the following dependency to pom.xml, then place changelog files in src/main/resources/db/changelog . org.liquibase liquibase-core i started by using hibernate's schema-export and changing hibernate.ddl-auto to "create-drop" in application-dev.yml . i also commented out the liquibase-core dependency. then i setup a postgresql database and started the app with "mvn spring-boot:run -pprod". i generated the liquibase changelog from an existing schema using the following command (after downloading and installing liquibase). liquibase --driver=org.postgresql.driver --classpath="/users/mraible/.m2/repository/org/postgresql/postgresql/9.3-1102-jdbc41/postgresql-9.3-1102-jdbc41.jar:/users/mraible/snakeyaml-1.11.jar" --changelogfile=/users/mraible/dev/spring-app/src/main/resources/db/changelog/db.changelog-02.yaml --url="jdbc:postgresql://localhost:5432/mydb" --username=user --password=pass generatechangelog i did find one bug - the generatechangelog command generates too many constraints in version 3.2.2 . i was able to fix this by manually editing the generated yaml file. tip: if you want to drop all tables in your database to verify liquibase creation is working in postgesql, run the following commands: psql -d mydb drop schema public cascade; create schema public; after writing minimal code for spring data and configuring liquibase to create tables/relationships, i relaxed a bit, documented how everything worked and added a loggingfilter . the loggingfilter was handy for viewing api requests and responses. @bean public filterregistrationbean loggingfilter() { loggingfilter filter = new loggingfilter(); filterregistrationbean registrationbean = new filterregistrationbean(); registrationbean.setfilter(filter); registrationbean.seturlpatterns(arrays.aslist("/api/*")); return registrationbean; } accessing api with resttemplate the final step i needed to do was figure out how to access my new and fancy api with resttemplate . at first, i thought it would be easy. then i realized that spring data produces a hal -compliant api, so its content is embedded inside an "_embedded" json key. after much trial and error, i discovered i needed to create a resttemplate with hal and joda-time awareness. @bean public resttemplate resttemplate() { objectmapper mapper = new objectmapper(); mapper.configure(deserializationfeature.fail_on_unknown_properties, false); mapper.registermodule(new jackson2halmodule()); mapper.registermodule(new jodamodule()); mappingjackson2httpmessageconverter converter = new mappingjackson2httpmessageconverter(); converter.setsupportedmediatypes(mediatype.parsemediatypes("application/hal+json")); converter.setobjectmapper(mapper); stringhttpmessageconverter stringconverter = new stringhttpmessageconverter(); stringconverter.setsupportedmediatypes(mediatype.parsemediatypes("application/xml")); list> converters = new arraylist<>(); converters.add(converter); converters.add(stringconverter); return new resttemplate(converters); } the jodamodule was provided by the following dependency: com.fasterxml.jackson.datatype jackson-datatype-joda with the configuration complete, i was able to write a messagesapiitest integration test that posts a request and retrieves it using the api. the api was secured using basic authentication, so it took me a bit to figure out how to make that work with resttemplate. willie wheeler's basic authentication with spring resttemplate was a big help. @runwith(springjunit4classrunner.class) @contextconfiguration(classes = integrationtestconfig.class) public class messagesapiitest { private final static log log = logfactory.getlog(messagesapiitest.class); @value("http://${app.host}/api/initiate") private string initiateapi; @value("http://${app.host}/api/messages") private string messagesapi; @value("${app.host}") private string host; @inject private resttemplate resttemplate; @before public void setup() throws exception { string request = new scanner(new classpathresource("sample-request.xml").getfile()).usedelimiter("\\z").next(); responseentity response = resttemplate.exchange(gettesturl(initiateapi), httpmethod.post, getbasicauthheaders(request), org.ncpdp.schema.transport.message.class, collections.emptymap()); assertequals(httpstatus.ok, response.getstatuscode()); } @test public void testgetmessages() { httpentity request = getbasicauthheaders(null); responseentity> result = resttemplate.exchange(gettesturl(messagesapi), httpmethod.get, request, new parameterizedtypereference>() {}); httpstatus status = result.getstatuscode(); collection messages = result.getbody().getcontent(); log.debug("messages found: " + messages.size()); assertequals(httpstatus.ok, status); for (message message : messages) { log.debug("message.id: " + message.getid()); log.debug("message.datecreated: " + message.getdatecreated()); } } private httpentity getbasicauthheaders(string body) { string plaincreds = "user:pass"; byte[] plaincredsbytes = plaincreds.getbytes(); byte[] base64credsbytes = base64.encodebase64(plaincredsbytes); string base64creds = new string(base64credsbytes); httpheaders headers = new httpheaders(); headers.add("authorization", "basic " + base64creds); headers.add("content-type", "application/xml"); if (body == null) { return new httpentity<>(headers); } else { return new httpentity<>(body, headers); } } } to get spring data to populate the message id, i created a custom restconfig class to expose it. i learned how to do this from tommy ziegler . /** * used to expose ids for resources. */ @configuration public class restconfig extends repositoryrestmvcconfiguration { @override protected void configurerepositoryrestconfiguration(repositoryrestconfiguration config) { config.exposeidsfor(message.class); config.setbaseuri("/api"); } } summary this article explains how i built a rest api using jaxb, spring boot, spring data and liquibase. it was relatively easy to build, but required some tricks to access it with spring's resttemplate. figuring out how to customize jaxb's code generation was also essential to make things work. i started developing the project with spring boot 1.1.7, but upgraded to 1.2.0.m2 after i found it supported log4j2 and configuring spring data rest's base uri in application.yml. when i handed the project off to my client last week, it was using 1.2.0.build-snapshot because of a bug when running in tomcat . this was an enjoyable project to work on. i especially liked how easy spring data makes it to expose jpa entities in an api. spring boot made things easy to configure once again and liquibase seems like a nice tool for database migrations. if someone asked me to develop a rest api on the jvm, which frameworks would i use? spring boot, spring data, jackson, joda-time, lombok and liquibase. these frameworks worked really well for me on this particular project.
October 30, 2014
by Matt Raible
· 64,343 Views
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Parsing a Tab Delimited File Using OpenCSV
I prefer OpenCSV for CSV parsing in Java. That library also supports parsing of tab delimited files, here's how: Just a quick gist: import au.com.bytecode.opencsv.CSVReader; public class LoadTest { @Test public void testLoad(String row) throws IOException, JobNotFoundException, InterruptedException { CSVReader reader = new CSVReader(new FileReader("/Users/bone/Desktop/foo_data.tab"), '\t'); String[] record; while ((record = reader.readNext()) != null) { for (String value : record) { System.out.println(value); // Debug only } } } }
October 24, 2014
by Brian O' Neill
· 24,307 Views
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Understanding Information Retrieval by Using Apache Lucene and Tika - Part 1
introduction in this tutorial, the apache lucene and apache tika frameworks will be explained through their core concepts (e.g. parsing, mime detection, content analysis, indexing, scoring, boosting) via illustrative examples that should be applicable to not only seasoned software developers but to beginners to content analysis and programming as well. we assume you have a working knowledge of the java™ programming language and plenty of content to analyze. throughout this tutorial, you will learn: how to use apache tika's api and its most relevant functions how to develop code with apache lucene api and its most important modules how to integrate apache lucene and apache tika in order to build your own piece of software that stores and retrieves information efficiently. (project code is available for download) what are lucene and tika? according to apache lucene's site, apache lucene represents an open source java library for indexing and searching from within large collections of documents. the index size represents roughly 20-30% the size of text indexed and the search algorithms provide features like: ranked searching - best results returned first many powerful query types: phrase queries, wildcard queries, proximity queries, range queries and more. in this tutorial we will demonstrate only phrase queries. fielded search (e.g. title, author, contents) sorting by any field flexible faceting, highlighting, joins and result grouping pluggable ranking models, including the vector space model and okapi bm25 but lucene's main purpose is to deal directly with text and we want to manipulate documents, who have various formats and encoding. for parsing document content and their properties the apache tika library it is necessary. apache tika is a library that provides a flexible and robust set of interfaces that can be used in any context where metadata analyzis and structured text extraction is needed. the key component of apache tika is the parser (org.apache.tika.parser.parser ) interface because it hides the complexity of different file formats while providing a simple and powerful mechanism to extract structured text content and metadata from all sorts of documents. criterias for tika parsing design streamed parsing the interface should require neither the client application nor the parser implementation to keep the full document content in memory or spooled to disk. this allows even huge documents to be parsed without excessive resource requirements. structured content a parser implementation should be able to include structural information (headings, links, etc.) in the extracted content. a client application can use this information for example to better judge the relevance of different parts of the parsed document. input metadata a client application should be able to include metadata like the file name or declared content type with the document to be parsed. the parser implementation can use this information to better guide the parsing process. output metadata a parser implementation should be able to return document metadata in addition to document content. many document formats contain metadata like the name of the author that may be useful to client applications. context sensitivity while the default settings and behaviour of tika parsers should work well for most use cases, there are still situations where more fine-grained control over the parsing process is desirable. it should be easy to inject such context-specific information to the parsing process without breaking the layers of abstraction. requirements maven 2.0 or higher java 1.6 se or higher lesson 1: automate metadata extraction from any file type our premisses are the following: we have a collection of documents stored on disk/database and we would like to index them; these documents can be word documents, pdfs, htmls, plain text files etc. as we are developers, we would like to write reusable code that extracts file properties regarding format (metadata) and file content. apache tika has a mimetype repository and a set of schemes (any combination of mime magic, url patterns, xml root characters, or file extensions) to determine if a particular file, url, or piece of content matches one of its known types. if the content does match, tika has detected its mimetype and can proceed to select the appropriate parser. in the sample code, the file type detection and its parsing is being covered inside the class com.retriever.lucene.index.indexcreator , method indexfile. listing 1.1 analyzing a file with tika public static documentwithabstract indexfile(analyzer analyzer, file file) throws ioexception { metadata metadata = new metadata(); contenthandler handler = new bodycontenthandler(10 * 1024 * 1024); parsecontext context = new parsecontext(); parser parser = new autodetectparser(); inputstream stream = new fileinputstream(file); //open stream try { parser.parse(stream, handler, metadata, context); //parse the stream } catch (tikaexception e) { e.printstacktrace(); } catch (saxexception e) { e.printstacktrace(); } finally { stream.close(); //close the stream } //more code here } the above code displays how a file it is being parsed using org.apache.tika.parser.autodetectparser; this kind of implementation was chosen because we would like to achieve parsing documents disregarding their format. also, for handling the content the org.apache.tika.sax.bodycontenthandler wasconstructed with a writelimit given as parameter ( 10*1024*1024); this type of constructor creates a content handler that writes xhtml body character events to an internal string buffer and in case of documents with large content is less likely to throw a saxexception (thrown when the default write limit is reached). as a result of our parsing we have obtained a metadata object that we can now use to detect file properties (title or any other header specific to a document format). metadata processing can be done as described below ( com.retriever.lucene.index.indexcreator , method indexfiledescriptors) : listing 1.2 processing metadata private static document indexfiledescriptors(string filename, metadata metadata) { document doc = new document(); //store file name in a separate textfield doc.add(new textfield(isearchconstants.field_file, filename, store.yes)); for (string key : metadata.names()) { string name = key.tolowercase(); string value = metadata.get(key); if (stringutils.isblank(value)) { continue; } if ("keywords".equalsignorecase(key)) { for (string keyword : value.split(",?(\\s+)")) { doc.add(new textfield(name, keyword, store.yes)); } } else if (isearchconstants.field_title.equalsignorecase(key)) { doc.add(new textfield(name, value, store.yes)); } else { doc.add(new textfield(name, filename, store.no)); } } in the method presented above we store the file name in a separate field and also the document's title ( a document can have a title different from its file name); we are not interested in storing other informations.
October 22, 2014
by Ana-Maria Mihalceanu
· 18,828 Views · 4 Likes
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