If you need the same functionality in two projects, you should reuse code between them, right? Or should you? For as long as there has been a profession of software engineering, we have tried to achieve more reuse. But reuse has both a benefit and a cost. Too often, the cost is forgotten. In this article, I examine the economics of reuse. True story: One of the earliest projects to embrace object-oriented programming in the 1990s did so with the goal of maximizing reuse. The team responsible for creating the company wide framework used the following formula for calculating the value of their work: [Value of reuse] = [numbers of uses of framework] * [value of the framework to reusers] – [cost of developing the framework] This formula is obviously correct, but this is where they went horribly wrong: The organization said [value of framework to reusers] = [cost of developing framework]. In other words: The more expensive it was to create, the more valuable it was to use. We have clearly progressed beyond this thinking. A more updated formula would say: [value of framework to reusers] = [cost of developing the feature in question]. But even this is too optimistic. No library comes for free to its users. At the very least, you have to discover the features and learn about the details. The cost of reusing depends on many factors, such as the quality of the framework and the documentation and also upon the type of feature. A complex algorithm with a simple interface is cheap to use, while most domain-specific frameworks require relatively much work to reuse. We can express this as a reuse value factor, likely between 90% and 50%. For most cases, my guess would be at about 75%. So we have: [value of reuse] = [number of users] * ([cost of feature] * [reuse cost factor]) – [cost of developing the reusable component] What about the other important factor: [cost of developing the reusable component]? It’s easy to assume that the cost of developing a feature in a framework is equal to that of developing the feature in an application, but on further analysis shows that this is far from true. A reusable component needs more documentation, it needs to handle more special cases and it has a slower feedback cycle. This cost is actually substantial and may mean that it costs between 150% to 300% or more to develop a feature for reuse. Personally, I think the reusability cost factor lies around 300%. And the lower this number, the higher the cost factor of reuse is likely to be, because that may mean we skimped on documentation etc. A revised number would be: [value of reuse] = [number of users] * ([cost of feature] * [reuse value factor]) – [reusability cost factor] * [cost of feature] Or [value of reuse] = [cost of feature] * ([number of users] * [reuse value factor] – [reusability cost factor]) The more complex formula actually lets us make a few predictions. Let’s say we assume a reuse value factor of 75 % (meaning that it requires 1/4 of the effort to reuse a library rather than creating the feature from scratch) and a reusability cost factor of 300 % (meaning that it requires three times the effort to create something that’s worth reusing). This means: [value of reuse] = [cost of feature] * ([number of users] * 75% – 300%) This equation breaks even when [number of users] = 4. That means that to get any value from your reused component, you better have five or more reusers or you have to find a way to substantially improve the [reuse value factor] or [reusability cost factor]. Very smart people have failed to do this. Improving the value: Increase the number of reusers: Simple enough, but when you do, you risk that the [reuse value factor] goes down as the framework doesn’t suit everybody equally well. Reduce the cost of reusing the library: This means investing in documentation, improving your design, improving testing to reduce the number of bugs, handle bug reports and feature requests faster from your reusers – all of which increase your cost reusability cost factor. Reduce the extra work in making the library reusable: The most important way to reduce the cost of developing for reuse is to choose the right kind of problem to solve. Problems with a small surface and big volume are best. That means: Easy to describe, hard to implement. Sadly, most of the juiciest fruit was picked years ago by the standard library in your programming language and by open source frameworks. On a global scale, reuse has saved the software industry tremendous amounts. In an organization, it can be hard to get the same effect. Reuse comes at a cost to the reuser and to the developer of the reusable library. How do you evaluate and improve your [reuse value factor] and your [reusability cost factor]?

In a previous post, I presented a method of loading initial data into a Django database by using a custom management command. An accompanying task is cleaning the database up. Here I want to discuss a few options for doing that. First, some general design notes on Django management commands. If you run manage.py help you’ll see a whole bunch of commands starting with sql. These all share a common idiom – print SQL statements to the standard output. Almost all DB engines have means to pipe commands from the standard input, so this plays great with the Unix philosophy of building pipes of single-task programs. Django even provides a convenient shortcut for us to access the actual DB that’s being used with a given project – the dbshell command. As an example, we have the sqlflush command, which returns a list of the SQL statements required to return all tables in the database to the state they were in just after they were installed. In a simple blog-like application with "post" and "tag" models, it may return something like: $ python manage.py sqlflush BEGIN; DELETE FROM "auth_permission"; DELETE FROM "auth_group"; DELETE FROM "django_content_type"; DELETE FROM "django_session"; DELETE FROM "blogapp_tag"; DELETE FROM "auth_user_groups"; DELETE FROM "auth_group_permissions"; DELETE FROM "auth_user_user_permissions"; DELETE FROM "blogapp_post"; DELETE FROM "blogapp_post_tags"; DELETE FROM "auth_user"; DELETE FROM "django_admin_log"; COMMIT; Note there’s a lot of tables here, because the project also installed the admin and auth applications from django.contrib. We can actually execute these SQL statements, and thus wipe out all the DB tables in our database, by running: $ python manage.py sqlflush | python manage.py dbshell For this particular sequence, since it’s so useful, Django has a special built-in command named flush. But there’s a problem with running flush that may or may not bother you, depending on what your goals are. It wipes out all tables, and this means authentication data as well. So if you’ve created a default admin user when jump-starting the application, you’ll have to re-create it now. Perhaps there’s a more gentle way to delete just your app’s data, without messing with the other apps? Yes. In fact, I’m going to show a number of ways. First, let’s see what other existing management commands have to offer. sqlclear will emit the commands needed to drop all tables in a given app. For example: $ python manage.py sqlclear blogapp BEGIN; DROP TABLE "blogapp_tag"; DROP TABLE "blogapp_post"; DROP TABLE "blogapp_post_tags"; COMMIT; So we can use it to target a specific app, rather than using the kill-all approach of flush. There’s a catch, though. While flush runs delete to wipe all data from the tables, sqlclear removes the actual tables. So in order to be able to work with the database, these tables have to be re-created. Worry not, there’s a command for that: $ python manage.py sql blogapp BEGIN; CREATE TABLE "blogapp_post_tags" ( "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT, "post_id" integer NOT NULL REFERENCES "blogapp_post" ("id"), "tag_id" varchar(50) NOT NULL REFERENCES "blogapp_tag" ("name"), UNIQUE ("post_id", "tag_id") ) ; CREATE TABLE "blogapp_post" ( "id" integer NOT NULL PRIMARY KEY AUTOINCREMENT, <.......> ) ; CREATE TABLE "blogapp_tag" ( <.......> ) ; COMMIT; So here’s a first way to do a DB cleanup: pipe sqlclear appname into dbshell. Then pipe sql appname to dbshell. An alternative way, which I like less, is to take the subset of DELETE statements generated by sqlflush, save them in a text file, and pipe it through to dbshell when needed. For example, for the blog app discussed above, these statements should do it: BEGIN; DELETE FROM "blogapp_tag"; DELETE FROM "blogapp_post"; DELETE FROM "blogapp_post_tags"; DELETE COMMIT; The reason I don’t like it is that it forces you to have explicit table names stored somewhere, which is a duplication of the existing models. If you happen to change some of your foreign keys, for example, tables will need changing so this file will have to be regenerated. The approach I like best is more programmatic. Django’s model API is flexible and convenient, and we can just use it in a custom management command: from django.core.management.base import BaseCommand from blogapp.models import Post, Tag class Command(BaseCommand): def handle(self, *args, **options): Tag.objects.all().delete() Post.objects.all().delete() Save this code as blogapp/management/commands/clear_models.py, and now it can be invoked with: $ python manage.py clear_models

Java EE in general and Context and Dependency Injection has been part of the Vaadin ecosystem since ages. Recently, Spring Vaadin is a joint effort of the Vaadin and the Spring teams to bring the Spring framework into the Vaadin ecosystem, lead by Petter Holmström for Vaadin and Josh Long for Pivotal. Integration is based on the Spring Boot project - and its sub-modules, that aims to ease creating new Spring web projects. This article assumes the reader is familiar enough with Spring Boot. If not the case, please take some time to get to understand basic notions about the library. Note that at the time of this writing, there's no release for Spring Vaadin. You'll need to clone the project and build it yourself. The first step is to create the UI. In order to display usage of Spring's Dependency Injection, it should use a service dependency. Let's injection the UI through Constructor Injection to favor immutability. The only addition to a standard UI is to annotate it with org.vaadin.spring.@VaadinUI. @VaadinUI public class VaadinSpringExampleUi extends UI { private HelloService helloService; public VaadinSpringExampleUi(HelloService helloService) { this.helloService = helloService; } @Override protected void init(VaadinRequest vaadinRequest) { String hello = helloService.sayHello(); setContent(new Label(hello)); } } The second step is standard Spring Java configuration. Let's create two configuration classes, one for the main context and the other for the web one. Two thing of note: The method instantiating the previous UI has to be annotated with org.vaadin.spring.@UIScope in addition to standard Spring org.springframework.context.annotation.@Bean to bind the bean lifecycle to the new scope provided by the Spring Vaadin library. At the time of this writing, a RequestContextListener bean must be provided. In order to be compliant with future versions of the library, it's a good practice to annotate the instantiating method with @ConditionalOnMissingBean(RequestContextListener.class). @Configuration public class MainConfig { @Bean public HelloService helloService() { return new HelloService(); } } @Configuration public class WebConfig extends MainConfig { @Bean @ConditionalOnMissingBean(RequestContextListener.class) public RequestContextListener requestContextListener() { return new RequestContextListener(); } @Bean @UIScope public VaadinSpringExampleUi exampleUi() { return new VaadinSpringExampleUi(helloService()); } } The final step is to create a dedicated WebApplicationInitializer. Spring Boot already offers a concrete implementation, we just need to reference our previous configuration classes as well as those provided by Spring Vaadin, namely VaadinAutoConfiguration and VaadinConfiguration. public class ApplicationInitializer extends SpringBootServletInitializer { @Override protected SpringApplicationBuilder configure(SpringApplicationBuilder application) { return application.showBanner(false) .sources(MainConfig.class) .sources(VaadinAutoConfiguration.class, VaadinConfiguration.class) .sources(WebConfig.class); } } At this point, we demonstrated a working Spring Vaadin sample application. Code for this article can be browsed and forked on Github.

Spring Data modules provides various modules to work with various types of datasources like RDBMS, NOSQL stores etc in unified way. In my previous article SpringMVC4 + Spring Data JPA + SpringSecurity configuration using JavaConfig I have explained how to configure Spring Data JPA using JavaConfig. Now in this post let us see how we can use Spring Data JPA repositories and export JPA entities as REST endpoints using Spring Data REST. First let us configure spring-data-jpa and spring-data-rest-webmvc dependencies in our pom.xml. org.springframework.data spring-data-jpa 1.5.0.RELEASE org.springframework.data spring-data-rest-webmvc 2.0.0.RELEASE Make sure you have latest released versions configured correctly, otherwise you will encounter the following error: java.lang.ClassNotFoundException: org.springframework.data.mapping.SimplePropertyHandler Create JPA entities. @Entity @Table(name = "USERS") public class User implements Serializable { private static final long serialVersionUID = 1L; @Id @GeneratedValue(strategy = GenerationType.IDENTITY) @Column(name = "user_id") private Integer id; @Column(name = "username", nullable = false, unique = true, length = 50) private String userName; @Column(name = "password", nullable = false, length = 50) private String password; @Column(name = "firstname", nullable = false, length = 50) private String firstName; @Column(name = "lastname", length = 50) private String lastName; @Column(name = "email", nullable = false, unique = true, length = 50) private String email; @Temporal(TemporalType.DATE) private Date dob; private boolean enabled=true; @OneToMany(fetch=FetchType.EAGER, cascade=CascadeType.ALL) @JoinColumn(name="user_id") private Set roles = new HashSet<>(); @OneToMany(mappedBy = "user") private List contacts = new ArrayList<>(); //setters and getters } @Entity @Table(name = "ROLES") public class Role implements Serializable { private static final long serialVersionUID = 1L; @Id @GeneratedValue(strategy = GenerationType.IDENTITY) @Column(name = "role_id") private Integer id; @Column(name="role_name",nullable=false) private String roleName; //setters and getters } @Entity @Table(name = "CONTACTS") public class Contact implements Serializable { private static final long serialVersionUID = 1L; @Id @GeneratedValue(strategy = GenerationType.IDENTITY) @Column(name = "contact_id") private Integer id; @Column(name = "firstname", nullable = false, length = 50) private String firstName; @Column(name = "lastname", length = 50) private String lastName; @Column(name = "email", nullable = false, unique = true, length = 50) private String email; @Temporal(TemporalType.DATE) private Date dob; @ManyToOne @JoinColumn(name = "user_id") private User user; //setters and getters } Configure DispatcherServlet using AbstractAnnotationConfigDispatcherServletInitializer. Observe that we have added RepositoryRestMvcConfiguration.class to getServletConfigClasses() method. RepositoryRestMvcConfiguration is the one which does the heavy lifting of looking for Spring Data Repositories and exporting them as REST endpoints. package com.sivalabs.springdatarest.web.config; import javax.servlet.Filter; import org.springframework.data.rest.webmvc.config.RepositoryRestMvcConfiguration; import org.springframework.orm.jpa.support.OpenEntityManagerInViewFilter; import org.springframework.web.servlet.support.AbstractAnnotationConfigDispatcherServletInitializer; import com.sivalabs.springdatarest.config.AppConfig; public class SpringWebAppInitializer extends AbstractAnnotationConfigDispatcherServletInitializer { @Override protected Class[] getRootConfigClasses() { return new Class[] { AppConfig.class}; } @Override protected Class[] getServletConfigClasses() { return new Class[] { WebMvcConfig.class, RepositoryRestMvcConfiguration.class }; } @Override protected String[] getServletMappings() { return new String[] { "/rest/*" }; } @Override protected Filter[] getServletFilters() { return new Filter[]{ new OpenEntityManagerInViewFilter() }; } } Create Spring Data JPA repositories for JPA entities. public interface UserRepository extends JpaRepository { } public interface RoleRepository extends JpaRepository { } public interface ContactRepository extends JpaRepository { } That's it. Spring Data REST will take care of rest of the things. You can use spring Rest Shell https://github.com/spring-projects/rest-shell or Chrome's Postman Addon to test the exported REST services. D:\rest-shell-1.2.1.RELEASE\bin>rest-shell http://localhost:8080:> Now we can change the baseUri using baseUri command as follows: http://localhost:8080:>baseUri http://localhost:8080/spring-data-rest-demo/rest/ http://localhost:8080/spring-data-rest-demo/rest/> http://localhost:8080/spring-data-rest-demo/rest/>list rel href ====================================================================================== users http://localhost:8080/spring-data-rest-demo/rest/users{?page,size,sort} roles http://localhost:8080/spring-data-rest-demo/rest/roles{?page,size,sort} contacts http://localhost:8080/spring-data-rest-demo/rest/contacts{?page,size,sort} Note: It seems there is an issue with rest-shell when the DispatcherServlet url mapped to "/" and issue list command it responds with "No resources found". http://localhost:8080/spring-data-rest-demo/rest/>get users/ { "_links": { "self": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/{?page,size,sort}", "templated": true }, "search": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/search" } }, "_embedded": { "users": [ { "userName": "admin", "password": "admin", "firstName": "Administrator", "lastName": null, "email": "[email protected]", "dob": null, "enabled": true, "_links": { "self": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/1" }, "roles": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/1/roles" }, "contacts": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/1/contacts" } } }, { "userName": "siva", "password": "siva", "firstName": "Siva", "lastName": null, "email": "[email protected]", "dob": null, "enabled": true, "_links": { "self": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/2" }, "roles": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/2/roles" }, "contacts": { "href": "http://localhost:8080/spring-data-rest-demo/rest/users/2/contacts" } } } ] }, "page": { "size": 20, "totalElements": 2, "totalPages": 1, "number": 0 } } You can find the source code at https://github.com/sivaprasadreddy/sivalabs-blog-samples-code/tree/master/spring-data-rest-demo For more Info on Spring Rest Shell: https://github.com/spring-projects/rest-shell

Here is a short snippet of Ansible playbook that installs R and any required packages to any nodes of the cluster: - name: Making sure R is installed apt: pkg=r-base state=installed - name: adding a few R packages command: /usr/bin/Rscript --slave --no-save --no-restore-history -e "if (! ('{{item}' %in% installed.packages()[,'Package'])) install.packages(pkgs={{item}, repos=c('http://www.freestatistics.org/cran/'))" with_items: - rjson - rPython - plyr - psych - reshape2 You should replace the repos with one chosen from the list of Cran mirrors. Note that the command above installs each package only if it is not already present, but messes up the “changed” status of Ansible’s PLAY RECAP by incorrectly reporting a change per R package at every run. Find more big data technical posts on my blog.

Every once in a while, I run into an interesting problem related to connections and pooling with ActiveMQ, and today I’d like to discuss something that is not always very clear and could potentially cause you to drink heavily when using ActiveMQ and Camel JMS. Not to say that you won’t want to drink heavily when using ActiveMQ and Camel anyway… in celebration of how delightful integration and messaging become when using them of course. So first up. Connection pooling. Sure, you’ve always heard to pool your connections. What does that really mean, and why do you want to do it? Opening up a connection to an ActiveMQ broker is a relativley expensive operation when compared to other actions like creating a session or consumer. So when sending or receiving messages and generally interacting with the broker, you’d like to reuse existing connections if possible. What you don’t want to do is rely on a JMS library (like Spring JmsTemplate for example) that opens and closes connections for each send or receive of a message… unless you can pool/cache your connections. So if we can agree that pooling connections is a good idea, take a look at an example config: You may even want to use Apache Camel and its wonderful camel-jms component because doing otherwise would just be silly. So maybe you want to set up a JMS config similar to so: This config basically means for consumers, set up 15 concurrent consumers, use transactions (local), use PERSISTENT messages for producers, set a timeout for 10000 for request-reply etc, etc. Huge note: If you want a more thorough taste of the configs for the jms component, especially around caching consumers, transactions and more, please take a look at Torsten’s excellent blog on Camel JMS with transactions – lesson learned. Maybe you should also spend some time poking around his blog as he’s got lots of good Camel/ActiveMQ stuff too Awesome so far. We have a connection pool of 10 connections, we will expect 10 sessions per connection (for a total of 100 sessions if we needed that…), and 15 concurrent consumers. We should be able to deal with some serious load, right? Take a look at this route here. It’s simple enough, exposes the activemq component (which will use the jmsConfig from above, so 15 concurrent consumers) and just does some logging: from("activemq:test.queue") .routeId("test.queue.routeId") .to("log:org.apache.camel.blog?groupSize=100"); Try and run this. You will find your consumers blocked up right away and stack traces will show this beauty: "Camel (camel-1) thread #1 - JmsConsumer[test.queue]" daemon prio=5 tid=7f81eb4bc000 nid=0x10abbb000 in Object.wait() [10abba000] java.lang.Thread.State: WAITING (on object monitor) at java.lang.Object.wait(Native Method) - waiting on <7f40e9070> (a org.apache.commons.pool.impl.GenericKeyedObjectPool$Latch) at java.lang.Object.wait(Object.java:485) at org.apache.commons.pool.impl.GenericKeyedObjectPool.borrowObject(GenericKeyedObjectPool.java:1151) - locked <7f40e9070> (a org.apache.commons.pool.impl.GenericKeyedObjectPool$Latch) at org.apache.activemq.pool.ConnectionPool.createSession(ConnectionPool.java:146) at org.apache.activemq.pool.PooledConnection.createSession(PooledConnection.java:173) at org.springframework.jms.support.JmsAccessor.createSession(JmsAccessor.java:196) .... How can that possibly be? We have connection pooling… we have sessions per connection set to 10 per connection, so how are we all blocked up on creating new sessions? The answer is you’re exhausting the number of sessions, as you can expect by the stack trace. But how? And how much do I need to drink to resolve this? Well hold on now. Grab a beer and hear me out. First understand this. ActiveMQ’s pooling implementation uses commons-pool and the maxActiveSessionsPerConnection attribute is actually mapped to the maxActive property of the underlying pool. From the docs this means: maxActive controls the maximum number of objects (per key) that can allocated by the pool (checked out to client threads, or idle in the pool) at one time. The key here is “key” (literally… the ‘per key’ clause of the documentation). So in the ActiveMQ implementation the key is an object that represents 1) whether the session mode is transacted and 2) what the acknowledgement mode is () as seen here. So in plain terms, you’ll end up with a “maxActive” sessions for each key that’s used on that connection.. so if you have clients that use transactions, no transactions, client-ack, auto-ack, transacted-session, dups-okay, etc you can start to see that you’d end up with “maxActive” sessions for each permutation. So if you have maxActiveSesssionsPerConnection set to 10, you could really end up with 10 x 2 x 4 == 80 sessions. This is something to tuck away in the back of your mind. The second key here is that when the camel-jms component sets up consumers, it ends up sharing a single connection among all the consumers specified by the concurrentConsumers session. This is an interesting point, because camel-jms uses the underlying Spring framework’s DefaultMessageListenerContainer and unfortunately this restriction comes from that library. So if you have 15 concurrent consumers, they will all share a single connection (even if pooling… it will grab one connection from the pool and hold it). So if you have 15 consumers that each share a connection, each share a transacted mode, each share an ack mode, then you end up trying to create 15 sessions for that one connection. And you end up with the above. So my rule of thumb for avoiding these scenarios: Understand exactly what each of your producers and consumers are doing, what their TX and ACK modes are Always tune the max sessions param when you NEED to (too many session threads? i dunno..) but always do concurrentConsumers+1 as the value AT LEAST If producers and consumers are producing/consuming the same destination SPLIT UP THE CONNECTION POOL: one pool for consumers, one pool for producers Dunno how valuable this info will be, but I wanted to jot it down for myself. If someone else finds it valuable, or has questions, let me know in the comments.

First of all, let me tell this out loud: Spring is no longer XML-heavy. As a matter of fact you can write Spring applications these days with minimal or no XML at all, using plenty of annotations, Java configuration and Spring Boot. Seriously stop ranting about Spring and XML, it's the thing the of the past. That being said you might still be using XML for couple of reasons: you are stuck with legacy code base, you chose XML for other reasons or you use Spring as a foundation for some framework/platform. The last case is actually quite common, for example Mule ESB and ActiveMQ use Spring underneath to wire up their dependencies. Moreover Spring XML is their way to configure the framework. However configuring message broker or enterprise service bus using plain Spring s would be cumbersome and verbose. Luckily Spring supports writing custom namespaces that can be embedded within standard Spring configuration files. These custom snippets of XML are preprocessed at runtime and can register many bean definitions at once in a concise and pleasantly looking (as far as XML allows) format. In a way custom namespaces are like macros that expand at runtime into multiple bean definitions. To give you a feeling of what are we aiming at, imagine a standard "enterprise" application that has several business entities. For each entity we define three, almost identical, beans: repository, service and controller. They are always wired in a similar way and only differ in small details. To begin with, our Spring XML looks like this (I am pasting screenshot with thumbnail to spare your eyes, it's huge and bloated): This is a "layered" architecture, thus we will call our custom namespace called onion - because onions have layers - and also because systems designed this way make me cry. By the end of this article you will learn how to collapse this pile of XML into: Look closely, it's still Spring XML file that is perfectly understandable by this framework - and you will learn how to achieve this. You can run arbitrary code for each top-level custom XML tag, e.g. single occurrence of registers repository, service and controller bean definitions all at once. The first thing to implement is writing a custom XML schema for our namespace. This is not that hard and will allow IntelliJ IDEA to show code completion in XML: Once the schema is completed we must register it in Spring using two files: /META-INF/spring.schemas: http\://nurkiewicz.blogspot.com/spring/onion/spring-onion.xsd=/com/blogspot/nurkiewicz/onion/ns/spring-onion.xsd /META-INF/spring.handlers: http\://nurkiewicz.blogspot.com/spring/onion/spring-onion.xsd=com.blogspot.nurkiewicz.onion.ns.OnionNamespaceHandler One maps schema URL into schema location locally, another points to so-called namespace handler. This class is fairly straightforward - it tells what to do with every top-level custom XML tag coming from this namespace encountered in Spring configuration file: import org.springframework.beans.factory.xml.NamespaceHandlerSupport; public class OnionNamespaceHandler extends NamespaceHandlerSupport { public void init() { registerBeanDefinitionParser("entity", new EntityBeanDefinitionParser()); registerBeanDefinitionParser("converter", new ConverterBeanDefinitionParser()); } } So, when piece of XML is found by Spring, it knows that our ConverterBeanDefinitionParser needs to be used. Remember that if our custom tag has children (like in the case of ), bean definition parser is called only for top-level tag. It is up to us how we parse and handle children. OK, so single tag is suppose to create the following two beans: The responsibility of bean definition parser is to programmatically register bean definitions otherwise defined in XML. I won't go into details of the API, but compare it with the XML snippet above, they match closely to each other: import org.w3c.dom.Element; public class ConverterBeanDefinitionParser extends AbstractBeanDefinitionParser { @Override protected AbstractBeanDefinition parseInternal(Element converterElement, ParserContext parserContext) { final String format = converterElement.getAttribute("format"); final String lenientStr = converterElement.getAttribute("lenient"); final boolean lenient = lenientStr != null? Boolean.valueOf(lenientStr) : true; final BeanDefinitionRegistry registry = parserContext.getRegistry(); final AbstractBeanDefinition converterBeanDef = converterBeanDef(format, lenient); registry.registerBeanDefinition(format + "Converter", converterBeanDef); final AbstractBeanDefinition readerBeanDef = readerBeanDef(format); registry.registerBeanDefinition(format + "Reader", readerBeanDef); return null; } private AbstractBeanDefinition readerBeanDef(String format) { return BeanDefinitionBuilder. rootBeanDefinition(ReaderFactoryBean.class). addPropertyValue("format", format). getBeanDefinition(); } private AbstractBeanDefinition converterBeanDef(String format, boolean lenient) { AbstractBeanDefinition converterBeanDef = BeanDefinitionBuilder. rootBeanDefinition(Converter.class.getName()). addConstructorArgValue(format + ".xml"). addConstructorArgValue(lenient). addPropertyReference("reader", format + "Reader"). getBeanDefinition(); converterBeanDef.setFactoryBeanName("convertersFactory"); converterBeanDef.setFactoryMethodName("build"); return converterBeanDef; } } Do you see how parseInternal() receives XML Element representing tag, extracts attributes and registers bean definitions? It's up to you how many beans you define in AbstractBeanDefinitionParser implementation. Just remember that we are barely constructing the configuration here, no instantiation took place yet. Once the XML file is fully parsed and all bean definition parsers triggered, Spring will start bootstrapping our application. One thing to keep in mind is returning null in the end. The API sort of expects you to return single bean definition. However no need to restrict ourselves, null is fine. The second custom tag that we support is that registers three beans at once. It's similar and thus not that interesting, see full source of EntityBeanDefinitionParser. One important implementation detail that can be found there is the usage of ManagedList. Documentation vaguely mentions it but it's quite valuable. If you want to define a list of beans to be injected knowing their IDs, a simple List is not sufficient, you must explicitly tell Spring you mean a list of bean references: List converterRefs = new ManagedList<>(); for (String converterName : converters) { converterRefs.add(new RuntimeBeanReference(converterName)); } return BeanDefinitionBuilder. rootBeanDefinition("com.blogspot.nurkiewicz.FooService"). addPropertyValue("converters", converterRefs). getBeanDefinition(); Using JAXB to simplify bean definition parsers OK, so by now you should be familiar with custom Spring namespaces and how they can help you. However they are quite low level by requiring you to parse custom tags using raw XML DOM API. However my team mate discovered that since we already have XSD schema file, why not use JAXB to handle XML parsing? First we ask maven to generate Java beans representing XML types and elements during build: org.jvnet.jaxb2.maven2 maven-jaxb22-plugin 0.8.3 xjc generate src/main/resources/com/blogspot/nurkiewicz/onion/ns com.blogspot.nurkiewicz.onion.ns.xml Under /target/generated-sources/xjc you will discover couple of Java files. I like generated JAXB models to have some commons prefix like Xml, which can be easily achieved with custom bindings.xjb file placed next to spring-onion.xsd: How does it change our custom bean definition parser? Previously we had this: final String clazz = entityElement.getAttribute("class"); //... final NodeList pageNodes = entityElement.getElementsByTagNameNS(NS, "page"); for (int i = 0; i < pageNodes.getLength(); ++i) { //...final String clazz = entityElement.getAttribute("class"); //... final NodeList pageNodes = entityElement.getElementsByTagNameNS(NS, "page"); for (int i = 0; i < pageNodes.getLength(); ++i) { //... Now we simply traverse Java beans: final XmlEntity entity = JaxbHelper.unmarshal(entityElement); final String clazz = entity.getClazz(); //... for (XmlPage page : entity.getPage()) { //... JaxbHelper is just a simple tool that hides checked exceptions and JAXB mechanics from outside: public class JaxbHelper { private static final Unmarshaller unmarshaller = create(); private static Unmarshaller create() { try { return JAXBContext.newInstance("com.blogspot.nurkiewicz.onion.ns.xml").createUnmarshaller(); } catch (JAXBException e) { throw Throwables.propagate(e); } } public static T unmarshal(Element elem) { try { return (T) unmarshaller.unmarshal(elem); } catch (JAXBException e) { throw Throwables.propagate(e); } } } Couple of words as a summary. First of all I don't encourage you to auto-generate repository/service/controller bean definitions for every entity. Actually it's a poor practice but the domain is familiar to all of us so I thought it will be a good example. Secondly, more important, custom XML namespaces are a powerful tool that should be used as a last resort when everything else fails, namely abstract beans, factory beans and Java configuration. Typically you'll want this kind of feature in frameworks or tools built in top of Spring. In that case check out full source code on GitHub.

over the past few months i've had a series of articles ( part 1 , part 2 , part 3 ) discussing indexeddb. in the last article i built a full, if rather simple, application that let you write notes. (i'm a sucker for note taking applications.) when i built the application, i intentionally did not use a framework. i tried to write nice, clear code of course, but i wanted to avoid anything that wasn't 100% necessary to demonstrate the application and indexeddb. in the perspective of an article, i think this was the right decision to make. i wanted my readers to focus on the feature and not anything else. but i thought this would be an excellent opportunity to try angularjs again. for the most part, this conversion worked perfectly. this may sound lame, but i found myself grinning as i built this application. i'm a firm believer that if something makes you happy then it is probably good for you. ;) i still find myself a bit... not confused... but slowed down by the module system and dependency injection. these are both things i grasp in general, but in angularjs they feel a bit awkward to me. it feels like something i'll never be able to code from memory, but will need to reference older applications to remind me. i'm not saying they are wrong of course, they just don't feel natural to me yet. on the flip side, the binding support is incredible. i love working with html templates and $scope. it feels incredibly powerful. heck, being able to add an input field and use it as a filter in approximately 30 seconds was mind blowing. one issue i ran into and i'm not convinced i created the best solution for was the async nature of indexeddb's database open logic. angularjs has a promises library built in and it works incredibly well for my application in general. but i needed the entire application to be bootstrapped to an async call for database startup. i got around that with two things that felt a bit like a hack. first, my home view (get all notes) ran a call to an init function to ensure the db was already open. so consider this init(): function init() { var deferred = $q.defer(); if(setup) { deferred.resolve(true); return deferred.promise; } var openrequest = window.indexeddb.open("indexeddb_angular",1); openrequest.onerror = function(e) { console.log("error opening db"); console.dir(e); deferred.reject(e.tostring()); }; openrequest.onupgradeneeded = function(e) { var thisdb = e.target.result; var objectstore; //create note os if(!thisdb.objectstorenames.contains("note")) { objectstore = thisdb.createobjectstore("note", { keypath: "id", autoincrement:true }); objectstore.createindex("titlelc", "titlelc", { unique: false }); objectstore.createindex("tags","tags", {unique:false,multientry:true}); } }; openrequest.onsuccess = function(e) { db = e.target.result; db.onerror = function(event) { // generic error handler for all errors targeted at this database's // requests! deferred.reject("database error: " + event.target.errorcode); }; setup=true; deferred.resolve(true); }; return deferred.promise; } this logic is similar to what i had in the non-framework app but i've made use of promises and a flag to remember when i've already opened the database. this lets me then tie to init() in my getnotes logic. function getnotes() { var deferred = $q.defer(); init().then(function() { var result = []; var handleresult = function(event) { var cursor = event.target.result; if (cursor) { result.push({key:cursor.key, title:cursor.value.title, updated:cursor.value.updated}); cursor.continue(); } }; var transaction = db.transaction(["note"], "readonly"); var objectstore = transaction.objectstore("note"); objectstore.opencursor().onsuccess = handleresult; transaction.oncomplete = function(event) { deferred.resolve(result); }; }); return deferred.promise; } all of this worked ok - but i ran into an issue on the other pages of my application. if for example you bookmarked the edit link for a note, you would run into an error. i could have applied the same fix in my service layer (run init first), but it just felt wrong. so instead i did this in my app.js: $rootscope.$on("$routechangestart", function(event,currentroute, previousroute){ if(!persistanceservice.ready() && $location.path() != '/home') { $location.path('/home'); }; }); the ready call was simply a wrapper to the flag variable. so yeah, this worked for me, but i still think there is (probably) a nicer solution. anyway, if you want to check it out, just hit the demo link below. i want to give a shoutout to sharon diorio for giving me a lot of help/tips/support while i built this app. p.s. i assume this is obvious, but i'm not really offering this up as a "best practices" angularjs application. i assume i could have done about every part better. ;)

JDave, Concordion, Easyb, JBehave, Cucumber are all compared here briefly for your convenience.

i built an android demo app so i could test my understanding of displaying bitmaps on a canvas. i had done scaling of bitmaps, rotation of bitmaps, and translation from one origin to another, but i had not done more than one of those transformations at a time. the demo app is shown in the figures above. there are two images in the center of the screen. each image is scaled to fit within the light blue region. when you press the rotate button, each of the images is rotated around its center, while maintaining its position in the center of the region on the screen. the scale button resizes the images. there are three different sizes. each time you touch scale, it switches to the next size. the offset cycles you through four different offsets. in the app mainactivity, two instances of starshipview are in the layout. in the oncreate method, each view is assigned a bitmap. sv.setbitmapfromresource (r.drawable.starship1); sv.setscale (1.0f); sv.invalidate (); the onclick method in mainactivity gets called whenever a button is clicked. the code in onclick finds the two views in its layout and sets properties that control the amount of rotation, size of the bitmap, and x and y offsets. sv.setscale (newscale1); sv.setdegrees (degrees1); sv.setoffsetx (newoffset1); sv.setoffsety (newoffset1); sv.invalidate (); inside class starshipview, in the ondraw method, the bitmap assigned to the view is written to the canvas. the code is actually very simple, once you get comfortable with using matrix objects to do the work. here’s what goes on in the ondraw method of class starshipview. first, the matrix object is set so it will fit the bitmap into the rectangle for the view. for this demo app, i chose some interesting sizes to test this part of the code. the starship image is 512 x 512. it is scaled to fit into the 96 dp area on the left. the star field image on the right is 96 x 96 is displayed in the 120 dp square on the right. the second step is to translate the view up and left by half the width and half the height. that is done because rotation is around the top left point (the origin) of the view. rotation follows that step. it is very simple: “matrix.postrotate (rotation)”. /** * draw the bitmap onto the canvas. * * the following transformations are done using a matrix object: * (1) the bitmap is scaled to fit within the view; * (2) the bitmap is translated up and left half the width and height, to support rotation around the center; * (3) the bitmap is rotated n degrees; * (4) the bitmap is translated to the specified offset valuess. */ @override public void ondraw(canvas canvas) { if (pbitmap == null) return; // use the same matrix over and over again to minimize // allocation in ondraw. matrix matrix = mmatrix; matrix.reset (); float vw = this.getwidth (); float vh = this.getheight (); float hvw = vw / 2; float hvh = vh / 2; float bw = (float) pbitmap.getwidth (); float bh = (float) pbitmap.getheight (); // first scale the bitmap to fit into the view. // use either scale factor for width and height, // whichever is the smallest. float s1x = vw / bw; float s1y = vh / bh; float s1 = (s1x < s1y) ? s1x : s1y; matrix.postscale (s1, s1); // translate the image up and left half the height // and width so rotation (below) is around the center. matrix.posttranslate(-hvw, -hvh); // rotate the bitmap the specified number of degrees. int rotation = getdegrees (); matrix.postrotate(rotation); // if the bitmap is to be scaled, do so. // also figure out the x and y offset values, which start // with the values assigned to the view // and are adjusted based on the scale. float offsetx = getoffsetx (), offsety = getoffsety (); if (pscale != 1.0f) { matrix.postscale (pscale, pscale); float sx = (0.0f + pscale) * vw / 2; float sy = (0.0f + pscale) * vh / 2; offsetx += sx; offsety+= sy; } else { offsetx += hvw; offsety += hvh; } // the last translation moves the bitmap to where it has to be to have its top left point be // where it should be following the rotation and scaling. matrix.posttranslate (offsetx, offsety); // finally, draw the bitmap using the matrix as a guide. canvas.drawbitmap (pbitmap, matrix, null); } once the bitmap is rotated, it needs to have its location translated to the place where it should display in the view. that is specified in the offsetx and offsety values. so you see one more matrix.posttranslate call in the method. the final action in the ondraw method is the drawing of the bitmap. notice that the drawbitmap method uses the matrix with the various transformations encoded in it. source code you can download the source code for this demo from the wglxy.com website. click here: download zip file from wglxy.com . the zip is attached at the bottom of that page. after you import the project into eclipse, it’s a good idea to use the project – clean menu item to rebuild the project. this demo app was compiled with android 4.4 (api 19). it works in all api levels from api 10 on up. references as with many other problems, i found very good advice on stackoverflow. a stackoverflow post on rotating images around the center of the image helped me.

it's very important to learn hadoop by practice. one of the learning curves is how to write the first map reduce app and debug in favorite ide, eclipse. do we need any eclipse plugins? no, we do not. we can do hadoop development without map reduce plugins this tutorial will show you how to set up eclipse and run your map reduce project and mapreduce job right from your ide. before you read further, you should have setup hadoop single node cluster and your machine. you can download the eclipse project from github . use case: we will explore the weather data to find maximum temperature from tom white’s book hadoop: definitive guide (3rd edition) chapter 2 and run it using toolrunner i am using linux mint 15 on virtualbox vm instance. in addition, you should have hadoop (mrv1 am using 1.2.1) single node cluster installed and running, if you have not done so, would strongly recommend you do it from here download eclipse ide, as of writing this, latest version of eclipse is kepler 1. create new java project 2. add dependencies jars right click on project properties and select java build path add all jars from $hadoop_home/lib and $hadoop_home (where hadoop core and tools jar lives) 3. create mapper package com.letsdobigdata; import java.io.ioexception; import org.apache.hadoop.io.intwritable; import org.apache.hadoop.io.longwritable; import org.apache.hadoop.io.text; import org.apache.hadoop.mapreduce.mapper; public class maxtemperaturemapper extends mapper { private static final int missing = 9999; @override public void map(longwritable key, text value, context context) throws ioexception, interruptedexception { string line = value.tostring(); string year = line.substring(15, 19); int airtemperature; if (line.charat(87) == '+') { // parseint doesn't like leading plus // signs airtemperature = integer.parseint(line.substring(88, 92)); } else { airtemperature = integer.parseint(line.substring(87, 92)); } string quality = line.substring(92, 93); if (airtemperature != missing && quality.matches("[01459]")) { context.write(new text(year), new intwritable(airtemperature)); } } } 4. create reducer package com.letsdobigdata; import java.io.ioexception; import org.apache.hadoop.io.intwritable; import org.apache.hadoop.io.text; import org.apache.hadoop.mapreduce.reducer; public class maxtemperaturereducer extends reducer { @override public void reduce(text key, iterable values, context context) throws ioexception, interruptedexception { int maxvalue = integer.min_value; for (intwritable value : values) { maxvalue = math.max(maxvalue, value.get()); } context.write(key, new intwritable(maxvalue)); } } 5. create driver for mapreduce job map reduce job is executed by useful hadoop utility class toolrunner package com.letsdobigdata; import org.apache.hadoop.conf.configured; import org.apache.hadoop.fs.path; import org.apache.hadoop.io.intwritable; import org.apache.hadoop.io.text; import org.apache.hadoop.mapreduce.job; import org.apache.hadoop.mapreduce.lib.input.fileinputformat; import org.apache.hadoop.mapreduce.lib.output.fileoutputformat; import org.apache.hadoop.util.tool; import org.apache.hadoop.util.toolrunner; /*this class is responsible for running map reduce job*/ public class maxtemperaturedriver extends configured implements tool{ public int run(string[] args) throws exception { if(args.length !=2) { system.err.println("usage: maxtemperaturedriver "); system.exit(-1); } job job = new job(); job.setjarbyclass(maxtemperaturedriver.class); job.setjobname("max temperature"); fileinputformat.addinputpath(job, new path(args[0])); fileoutputformat.setoutputpath(job,new path(args[1])); job.setmapperclass(maxtemperaturemapper.class); job.setreducerclass(maxtemperaturereducer.class); job.setoutputkeyclass(text.class); job.setoutputvalueclass(intwritable.class); system.exit(job.waitforcompletion(true) ? 0:1); boolean success = job.waitforcompletion(true); return success ? 0 : 1; } public static void main(string[] args) throws exception { maxtemperaturedriver driver = new maxtemperaturedriver(); int exitcode = toolrunner.run(driver, args); system.exit(exitcode); } } 6. supply input and output we need to supply input file that will be used during map phase and the final output will be generated in output directory by reduct task. edit run configuration and supply command line arguments. sample.txt reside in the project root. your project explorer should contain following ] 7. map reduce job execution 8. final output if you managed to come this far, once the job is complete, it will create output directory with _success and part_nnnnn , double click to view it in eclipse editor and you will see we have supplied 5 rows of weather data (downloaded from ncdc weather) and we wanted to find out the maximum temperature in a given year from input file and the output will contain 2 rows with max temperature in (centigrade) for each supplied year 1949 111 (11.1 c) 1950 22 (2.2 c) make sure you delete the output directory next time running your application else you will get an error from hadoop saying directory already exists. happy hadooping!

This article presents the usage of sripted data set in the eclipse's BIRT.

what can one create during the new year and christmas holidays? as it turned down – quite enough. even if you have two kids and a bunch of family members whom you want to visit. the only thing you cannot accomplish in time is to finish an article for dzone. it takes a lot of time, nearly the entire january. by the 5th of january i had a laptop and a couple of days to spend on some development. having estimated what i can do here, i decided to create a mobile app that would work faster than the original. for this, i needed to find communicative creators of a popular app. hence, i found a “ spender ” app in the app store. it is a simple app for tracking your budget. with it, you can estimate how effectively you spend your money in the end of each month. by the 5th of january, this app was in top-10 in the russian app store. i also found their dev-story on iphones.ru. in their dev-story, the developers wrote that after completing their previous project, they had three-four free days. so, they decided to create a new app during this free time. their product manager and programmers helped them with positioning the app and its key features. this encouraged me and i began to think how to create nearly the same app in 2 days . note: the original app was updated in the middle of january, and now it looks a little different from my app. anyway, you can find its screenshots in the dev-story. i already had the experience of mobile app development using c# and cocoa. since this was my personal free time, i wanted to use it with maximum effectiveness. even if i didn’t succeed, i was eager to learn a new framework or programming language. i was working for devexpress from 2006 till2011 and have been reading their announces since i left the company. so, i knew that they created a mobile js-framework based on cordova/phonegap. they made it after i left the company, so i was curious to try it. the gartner research company reports that by august, 2013 most of the enterprise mobile software was created using phonegap or phonegap-based products (like kony ). from my consumer experience, it's far from true. maybe i was wrong? i'm not so good at html and javascript. i can create mark-up with stackoverflow.com and i can write simple selectors with jquery. i can also find the required information in their documentation. in other words, html+js was a gap in my knowledge and i was ready to fill it or gain some experience. thus, i planned to create a cross-platform application that could become an advantage over the original ios-only spender app. moreover, i wanted to spend my time in the most effective way. on the one hand, i had a potentially effective js framework, on the other – a lack of js experience. i hoped that the js framework advantages could balance my poor experience. since i like to use a vcs during development, i'll try to recover my progress. you can download complete apps here: ios , android i'm not sure i can provide public access to my repo, because it contains images i bought from fotolia and third-party libraries, each with a difference license. i'm not a lawyer, so i’d prefer not to take the risk. the most curious of you can take a look into the app bundle itself. js wasn't minified. place: tula, russia, date: january, 5, 2014 +20 minutes spent on installing node.js and cordova cli +10 minutes downloaded a template app from cordova. added a template from phonejs. created a git-repo, registered it in webstorm. added a new record to the httpd.conf in order to have an ability to debug my future app in the browser. +38 minutes changed the app namespace to "io.nikitin.thriftbox". added navigation. phonejs is an mvc-framework. each app screen is represented as a collection of html markup (views) and fabric function (viewmodel). here is how it looks at its simplest // view content and thriftbox.home = function (params) { // request parameters taken from uri return {}; // viewmodel instance }; then view and view model are bound via knockout-bindings . to be in time, i create only two screens: expense input and monthly expense report. +4 hours 20 minutes here i got stuck for the first time. i couldn't create a markup of digit buttons. the original app had a huge keyboard that looked like a calculator or dialer. i found out that it was not that easy to create such a keyboard, even using a table tag. in the iphone retina screen, 1px borders between buttons changed their colors after clicking on the buttons. on my iphone, the difference in colors was very noticeable. i had to invent how to tackle this. i tried to implement buttons using div s. but i couldn't achieve a border width of 1 px and make all buttons look equal in different screens. three hours later i gave up the idea of using divs and moved forward. +28 minutes removing a clicked button indicator on ios. ios displays a gray indicator around tapped links and objects with the onclick event handler. since i had my own indicator of a tapped object (the tapped button became darker), i didn't need the default indicator. i solved this problem using the dxaction event: was: 1 became: 1 this event is an extended variation of a "click" event: its handler supports uri navigation between views and correctly works in the scrollable area. +14 minutes the buttonpress event handler shown in the previous example now validates numbers from user input. var number = ko.observable(null); var isvalidnumber = ko.computed(function() { return number() && parsefloat(number()) > 0; }); ...... function buttonpress(button) { if (button) { if (number()) number(number() + button); else number(button); } else if (number()) number(number().substr(0, number().length - 1)); } var viewmodel = { number: number, isvalidnumber: isvalidnumber, viewshowing: viewshowing, buttonpress: buttonpress }; ..... +8 minutes added a fastclick.js , which removes a delay between tapping the screen and raising the 'click' event on phones. the mobile browser delays the raising of the click event by default to be sure the end-user will not perform a double tap. for the end-user, this looks as if the app is sluggish. you click buttons much faster than an app responds. fastclick.js handles the touchstart event and then creates all the click event process logic. btw, adding this library was a mistake; later i'll tell why. +4 minutes added a limitation to the length of user input numbers. corrected the font size for a better look-and-feel. +58 minutes added a choice of an expense category. added a scrollable pane with available categories below the input field. video . it took less time than it could be. in the phonejs component collection, i found dxtileview . it provides a kinetic scrolling with the required appearance out-of-the-box. it's not easy to implement kinetic scrolling by yourself and thus it’s great that this scrolling is enabled for ios only - android doesn't have it. it was 7:40 pm, so, i decided to continue the next day. place: tula, russia, date: january, 5, 2014 +3 hours 9 minutes storing data on a local storage. phonejs contains classes for working with data: selection, filtering, sorting, and grouping. there are several approaches to store data: odata and localstorage. i didn't want to implement a server side for a free app, and decided to use localstorage. later i found out that this was not an ideal decision. for example, when updating to ios 5.1 user data is erased , other people complained that localstorage is cleared regularly or even when shutting the device down. i didn't want to risk, so i used file api of phonegap. documentation says that this api is based on w3c file api. in fact, this means that this api differs in safari for mac os, chrome for mac os, cordova for ios and cordova for android. file api implementation is different for ios and android . e.g. android implementation doesn't contain the 'blob' class and 'window.permanent' constant. ii however implements the 'localfilesystem' and 'localfilesystem.persistent' classes. the laptop browser provides additional api for requesting an additional storage space, which mobile browsers don't provide. the available documentation for this api adds more problems. i found several articles searching by "html5 file api". and, i couldn't find an article that would cover all my questions. finally i created a new class for working with fileapi. this class supports cordova 3.3 on ios, android, and chrome 32 for mac os and windows 8. you can find it here: https://github.com/chebum/filestorage-for-phone.js/blob/master/filestorage.js you can use it as follows: // in this example i create data/records file in the documents folder of the app fs.initfileapi(1000000, true) .then(function () { var records = new fs.filearraystore({ key: "id", filename: "records" }); return records.insert({ customer: "peter" }) }) .then(function () { alert("record saved!"); }); // or use low-level api: fs.initfileapi(100000, true) .then(function() { return fs.writefile("file1", "file content") }) .then(function() { alert("file saved!"); }); +33 minutes saving the added records to the storage. category list is stored in arraystore , to simplify the selection operations. +26 minutes creating layout for the app's views. phonejs provides several layouts that are the placeholders for the views. my app's start page didn't fit into any of the available layout, so i have chosen the emptylayout. but, it doesn't provide animation effects when navigating through views. i copied the emptylayout code and added an attribute that had animation effects. +1 h. 51 min. template's about screen was redesigned to a report screen, empty by that moment. created a viewmodel that selects data for a current month. added localization date formatting for the screen caption. +59 minutes added the display of expenses grouped by categories for a current month. +28 minutes added the selection of months for which the report should be generated. end-users can tap the screen header to select the required month. +1 h. 20 min. added cordova-plugin statusbar that didn't work outof-the-box. i found that the reference to cordova.js was commented in the phonejs app template: as a result, the native part of my app didn't work. +39 minutes in the report screen, the upper part was changed to dxtoolbar . +22 minutes i discoveredwhy the dxbutton click event handler didn't work. removing the fastclick.js solved my problem, but caused a delay between tapping and event raising. i've changed the dxaction event subscription to 'touchstart'. +25 minutes formatting output strings when generating a report. at night i dreamed of crappy buttons in the application’s main screen. places: tula, vnukovo airport, date: january, 7-8, 2014 i had an early flight to budapest from vnukovo, and because i had no time in the afternoon, i gradually completed at the airport at night. as you know, it’s not very comfortable to sleep or sit in a café chair for a long time, but it turned out that programming was ok. +2 h. 5 min. in the morning, i decided to split the buttons in order to remove borders between them. i took the ios dialer keyboard as a sample. i created three keyboards. the button size changes depending on screen resolution: for 3.5'', 4'' and 5'' phones. each table cell contained a div with configured alignment. because of the lack of an incomplete vertical text alignment in html, the final css style for buttons ended to be quite complex: .home-view .buttons td div { color: #4a5360; border: 1px solid #4a5360; text-align: center; position: absolute; left: 50%; /* small buttons - default */ font-size: 26px; padding: 13px 0 13px 0; width: 52px; line-height: 26px; border-radius: 26px; margin-left: -27px; margin-top: -27px; } +1 h. 50 minutes i bought several vector icon sets on fotolia. i cut the required icons and converted them to png. it took me quite a long time, maybe, because it was 1.30 am :) +1 hour 10 minutes added a splash-screen for the app. +36 minutes created three sizes for the app icon. localized the app name for ios. +20 minutes hiding the splash screen after the app is completely loaded. +2 hours fixing multiple bugs. +2 hours creating screenshots for play store +30 minutes creating screenshots for app store +30 minutes writing an app description for two app stores. +1 h. 30 minutes submitting my app to the app store. here i faced with an issue with the app certification. my accountancy let's summarize the time i spent and divide it into categories. development: 21 hours 37 minutes graphics and texts: 8 hours 26 minutes totally: 30 hours 3 minutes as a result, i got a minimum-feature working app, though it is not as cool as the latest version of "spender". i couldn't create splitting expenses by days and income input. my app's ui could be more elegant as well. after analyzing the original 'spender' developer work, i got the following. they say that they involved four developers for three-four days. it is about 96-128 man-hours. i spent only 30 man-hours and got an app for three mobile platforms. ios and android versions are already in stores. the version for windows phone 8 requires a ui redesign. i can be proud of myself :). you can download complete apps here: ios , android

The Spring Expression Language (SpEL) is a powerful expression language that supports querying, manipulating as well as evaluating logical and mathematical expressions.

Introduction When using Spring to asynchronously execute pieces of your code you typically use the @Async annotation on your Spring @Components methods. When using the @Async annotation Spring will use AOP (Aspect Oriented Programming) to wrap your call in a Runnable. This Runnable will then be scheduled for execution on a TaskExecutor. Exception Handling Spring comes with a number of pre-packaged TaskExecutors which are documented in the Spring documentation here. In practice you will likely use the ThreadPoolTaskExecutor or the SimpleAsyncTaskExecutor. When doing so you might at times wonder why a task has not been executed. This happens when an exception occurs inside the method you are trying to execute asynchronous. The aforementioned task executors do not handle the exceptions so the execution fails silently. This problem can be solved by implementing your own AsyncTaskExecutor which handles the exceptions by logging them (or in any other way you wish). Bellow you'll find an example implementation of such a AsyncTaskExecutor. package nl.jborsje.blog.examples; import java.util.concurrent.Callable; import java.util.concurrent.Future; import org.springframework.core.task.AsyncTaskExecutor; import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor; public class ExceptionHandlingAsyncTaskExecutor implements AsyncTaskExecutor { private AsyncTaskExecutor executor; public ExceptionHandlingAsyncTaskExecutor(AsyncTaskExecutor executor) { this.executor = executor; } public void execute(Runnable task) { executor.execute(createWrappedRunnable(task)); } public void execute(Runnable task, long startTimeout) { executor.execute(createWrappedRunnable(task), startTimeout); } public Future submit(Runnable task) { return executor.submit(createWrappedRunnable(task)); } public Future submit(final Callable task) { return executor.submit(createCallable(task)); } private Callable createCallable(final Callable task) { return new Callable() { public T call() throws Exception { try { return task.call(); } catch (Exception ex) { handle(ex); throw ex; } } }; } private Runnable createWrappedRunnable(final Runnable task) { return new Runnable() { public void run() { try { task.run(); } catch (Exception ex) { handle(ex); } } }; } private void handle(Exception ex) { System.err.println("Error during @Async execution: " + ex); } } This task executor decorates another task executor and wraps all Runnables and Callables in versions which handle the exception. In order to be able to use this task executor it has to be configured in the Spring application context as a managed bean and it has to be passed the real executor (the one that does the actual work) in its constructor. An example of such a configuration can be found bellow. JUnit testing In the application context used for JUnit testing Spring beans the asynchronous execution of methods can be cumbersome. You typically want to validate the inner workings of your methods not Springs asynchronicity. To achieve this you can use the SyncTaskExecutor provided by Spring. This task executor runs the tasks it is given immediately on the thread that adds the task instead of using a thread pool and running the tasks asynchronous. This task executor is configured in the test scope application context as follows.

Learn about using Mockito to create autowired fields.

As follow up to previous posts covering JMS, this post will delve into more depth on Spring's CachingConnectionFactory. Spring provides two implementations of the javax.jms.ConnectionFactory interface, namely, the SingleConnectionFactory and the CachingConnectionFactory. The SingleConnectionFactory returns as you might expect the same single connection upon all calls to the createConnection() method. This is fine for certain scenarios and applications but the CachingConnectionFactory provides a more performant and scalable solution. By default, a single session is cached so for a multi threaded application you would set the sessionCacheSize to be a more suitable number although this number wouldn't reflect the true number of sessions cached as this figure refers to the size of cache per session acknowledgement type eg AUTO_ACKNOWLEDGE, CLIENT_ACKNOWLEDGE, DUPS_OK_ACKNOWLEDGE and SESSION_TRANSACTED. By default, the CachingConnectionFactory will cache the Message Producers and Message Consumers for every session. As an aside the Message Consumers are cached using keys which include the JMS selector so the more fine grained the message filter the more Message Consumers there would be, and Message Consumers aren't closed until the session is closed and removed from the pool. An alternative is to use a Listener Container for consuming messages. Also to be noted is that on creating a CachingConnectionFactory instance, the reconnect on exception flag is set to be true. This should mean that the onException method on the default ExceptionListener class gets called which will reset the connections. You can also override the default exception listener with your own implementation. The below snippet of XML shows a simple configuration of a CachingConnectionFactory:

Introduction There are cases in which it is necessary to execute pieces of code asynchronous. An example is the sending of a (JMS) message from your system to another system. If it is not important for the database transaction whether or not the message has been sent successfully you can send the message asynchronous. The advantage is that the user does not have to wait in the front-end while the message is being send. Another example of possible asynchronous execution is the case where messages have a clear ordering. In order to try to prevent message A from being overtaken by message B you might want to schedule the sending of message B asynchronous with a delay. Spring Framework Spring supports the asynchronous execution of methods on your @Components by means of the @Async annotation. When using this annotation on a method of your @Component Spring will always execute this method asynchronous. The Spring framework will use AOP (Aspect Oriented Programming) on the Spring proxy of the @Component to wrap calls to this method in a Runnable and schedule this Runnable on a task executor. This task executor has a thread pool and when a thread in the pool becomes available the Runnable will be executed on this thread. The caller of the method annotated with @Async does not wait untill the Runnable has been executed but terminates after the Runnable has been scheduled. Return values If the method to be executed asynchronously has a return value it should return a Future in its signature. This Future can be used by the caller to track the progress of the asynchronous task and to retrieve the result of the task once it has been completely executed. The @Async method should return an ASyncResult (which implements the Future interface) containing the actual result. Transaction management If the @Async annotation is being used extra care should be taken with respect to transactions. In normal circumstances (without @Async) a transaction gets propagated through the call hierarchy from one Spring @Component to the other. However, when a @Transactional Spring @Component calls a method annotated with @Async this does not happen. The call to the asynchronous method is being scheduled and executed at a later time by a task executor and is thus handled as a 'fresh' call, i.e. without a transactional context. If the @Async method (or the @Component in which it is declared) is not @Transactional by itself Spring will not manage any needed transactions. In case the method sends a message to an ESB (Enterprise Service Bus) using JMS (or another protocol) this can lead to problems, because you probably want to use the transaction manager declared in your Spring application context (typically a JTA transaction manager). In order to make Spring manage the transaction of the @Async method either the @Component or the method itself should declare the @Transactional annotation, this way Spring will manage the transaction even if a method is being executed asynchronous. Caveats A final reminder: both @Transactional and @Async work with AOP an proxying. The methods to which these annotation are applied should be public, otherwise the annotations are not picked up by Spring. When JUnit testing methods annotated with @Async in combination with transactions and automatic rollbacks extra care should be taken, this will be the topic of another blog post in the near future.

I'm passionate about front end optimization and have been for years. My original inspiration was Steve Souders and his Even Faster Web Sites talk at OSCON 2008. Since then, I've optimized this blog, made it even faster with a new design, doubled the speed of several apps for clients and showed how to make AppFuse faster. As part of my Devoxx 2013 presentation, I showed how to do page speed optimization in a Java webapp. I developed a couple AngularJS apps last year. To concat and minify their stylesheets and scripts, I used mechanisms that already existed in the projects. On one project, it was Ant and its concat task. On the other, it was part of a Grails application, so I used the resources and yui-minify-resources plugins. The Angular project I'm working on now will be published on a web server, as well as bundled in an iOS native app. Therefore, I turned to Grunt to do the optimization this time. I found it to be quite simple, once I figured out how to make it work with Angular. Based on my findings, I submitted a pull request to add Grunt to angular-seed. Below are the steps I used to add Grunt to my Angular project. Install Grunt's command line interface with "sudo npm install -g grunt-cli". Edit package.json to include a version number (e.g. "version": "1.0.0"). Add Grunt plugins in package.json to do concat/minify/asset versioning: "grunt": "~0.4.1", "grunt-contrib-concat": "~0.3.0", "grunt-contrib-uglify": "~0.2.7", "grunt-contrib-cssmin": "~0.7.0", "grunt-usemin": "~2.0.2", "grunt-contrib-copy": "~0.5.0", "grunt-rev": "~0.1.0", "grunt-contrib-clean": "~0.5.0" Create a Gruntfile.js that runs all the plugins. module.exports = function (grunt) { grunt.initConfig({ pkg: grunt.file.readJSON('package.json'), clean: ["dist", '.tmp'], copy: { main: { expand: true, cwd: 'app/', src: ['**', '!js/**', '!lib/**', '!**/*.css'], dest: 'dist/' }, shims: { expand: true, cwd: 'app/lib/webshim/shims', src: ['**'], dest: 'dist/js/shims' } }, rev: { files: { src: ['dist/**/*.{js,css}', '!dist/js/shims/**'] } }, useminPrepare: { html: 'app/index.html' }, usemin: { html: ['dist/index.html'] }, uglify: { options: { report: 'min', mangle: false } } }); grunt.loadNpmTasks('grunt-contrib-clean'); grunt.loadNpmTasks('grunt-contrib-copy'); grunt.loadNpmTasks('grunt-contrib-concat'); grunt.loadNpmTasks('grunt-contrib-cssmin'); grunt.loadNpmTasks('grunt-contrib-uglify'); grunt.loadNpmTasks('grunt-rev'); grunt.loadNpmTasks('grunt-usemin'); // Tell Grunt what to do when we type "grunt" into the terminal grunt.registerTask('default', [ 'copy', 'useminPrepare', 'concat', 'uglify', 'cssmin', 'rev', 'usemin' ]); }; Add comments to app/index.html so usemin knows what files to process. The comments are the important part, your files will likely be different. ... A couple of things to note: 1) the copy task copies the "shims" directory from Webshims lib because it loads files dynamically and 2) setting "mangle: false" on the uglify task is necessary for Angular's dependency injection to work. I tried to use grunt-ngmin with uglify and had no luck. After making these changes, I'm able to run "grunt" and get an optimized version of my app in the "dist" folder of my project. For development, I continue to run the app from my "app" folder, so I don't currently have a need for watching and processing assets on-the-fly. That could change if I start using LESS or CoffeeScript. The results speak for themselves: from 27 requests to 5 on initial load, and only 3 requests for less than 2K after that. YSlow Page Speed No optimization 75 27 HTTP requests / 464K 55/100 Apache optimization (gzip and expires headers) 89 initial load: 26 requests / 166K primed cache: 4 requests / 40K 88/100 Apache + concat/minified/versioned files 98 initial load: 5 requests / 136K primed cache: 3 requests / 1.4K 93/100

Get started with Spring IDE and the Spring Tool Suite – a set of plugins to simplify the development of Spring-based applications in Eclipse.