33rd Degree day 1 review

33rd Degree is over. After the one last year, my expectations were very high, but Grzegorz Duda once again proved he’s more than able to deliver. With up to five tracks (most of the time: four presentations + one workshop), and ~650 attendees,  there was a lot to see and a lot to do, thus everyone will probably have a little bit different story to tell. Here is mine. Twitter: From Ruby on Rails to the JVM The conference started with  Raffi Krikorian from Twitter, talking about their use for JVM. Twitter was build with Ruby but with their performance management a lot of the backend was moved to Scala, Java and Closure. Raffi noted, that for Ruby programmers Scala was easier to grasp than Java, more natural, which is quite interesting considering how many PHP guys move to Ruby these days because of the same reasons. Perhaps the path of learning Jacek Laskowski once described (Java -> Groovy -> Scala/Closure) may be on par with PHP -> Ruby -> Scala. It definitely feels like Scala is the holy grail of languages these days. Raffi also noted, that while JVM delivered speed and a concurrency model to Twitter stack, it wasn’t enough, and they’ve build/customized their own Garbage Collector. My guess is that Scala/Closure could also be used because of a nice concurrency solutions (STM, immutables and so on). Raffi pointed out, that with the scale of Twitter, you easily get 3 million hits per second, and that means you probably have 3 edge cases every second. I’d love to learn listen to lessons they’ve learned from this.   Complexity of Complexity The second keynote of the first day, was Ken Sipe talking about complexity. He made a good point that there is a difference between complex and complicated, and that we often recognize things as complex only because we are less familiar with them. This goes more interesting the moment you realize that the shift in last 20 years of computer languages, from the “Less is more” paradigm (think Java, ASM) to “More is better” (Groovy/Scala/Closure), where you have more complex language, with more powerful and less verbose syntax, that is actually not more complicated, it just looks less familiar. So while 10 years ago, I really liked Java as a general purpose language for it’s small set of rules that could get you everywhere, it turned out that to do most of the real world stuff, a lot of code had to be written. The situation got better thanks to libraries/frameworks and so on, but it’s just patching. New languages have a lot of stuff build into, which makes their set of rules and syntax much more complex, but once you get familiar, the real world usage is simple, faster, better, with less traps laying around, waiting for you to fall. Ken also pointed out, that while Entity Service Bus looks really simple on diagrams, it’s usually very difficult and complicated to use from the perspective of the programmer. And that’s probably why it gets chosen so often – the guys selling/buying it, look no deeper than on the diagram.   Pointy haired bosses and pragmatic programmers: Facts and Fallacies of Software Development Dima got lucky. Or maybe not. Venkat Subramaniam is the kind of a speaker that talk about very simple things in a way, which makes everyone either laugh or reflect. Yes, he is a showman, but hey, that’s actually good, because even if you know the subject quite well, his talks are still very entertaining. This talk was very generic (here’s my thesis: the longer the title, the more generic the talk will be), interesting and fun, but at the end I’m unable to see anything new I’d have learned, apart from the distinction between Dynamic vs Static and Strong vs Weak typing, which I’ve seen the last year, but managed to forgot. This may be a very interesting argument for all those who are afraid of Groovy/Ruby, after bad experience with PHP or Perl. Build Trust in Your Build to Deployment Flow! Frederic Simon talked about DevOps and deployment, and that was a miss in my  schedule, because of two reasons. First, the talk was aimed at DevOps specifically, and while the subject is trendy lately, without big-scale problems, deployment is a process I usually set up and forget about. It just works, mostly because I only have to deal with one (current) project at a time.  Not much love for Dart. Second, while Frederic has a fabulous accent and a nice, loud voice, he tends to start each sentence loud and fade the sound at the end. This, together with mics failing him badly, made half of the presentation hard to grasp unless you were sitting in the first row. I’m not saying the presentation was bad, far from it, it just clearly wasn’t for me. I’ve left a few minutes before the end, to see how many people came to Dart presentation by Mike West. I was kind of interested, since I’m following Warsaw Google Technology User Group and heard a few voices about why I should pay attentions to that new Google language. As you can see from the picture on the right, the majority tends to disagree with that opinion.   Non blocking, composable reactive web programming with Iteratees Sadek Drobi’s talk about Iteratees in Play 2.0 was very refreshing. Perhaps because I’ve never used Play before, but the presentation was flawless, with well explained problems, concepts and solutions. Sadek started with a reflection on how much CPU we waste waiting for IO in web development, then moved to Play’s Iteratees, to explain the concept and implementation, which while very different from the that overused Request/Servlet model, looked really nice and simple. I’m not sure though, how much the problem is present when you have a simple service, serving static content before your app server. Think apache (and faster) before tomcat. That won’t fix the upload/download issue though, which is beautifully solved in Play 2.0 The Future of the Java Platform: Java SE 8 & Beyond Simon Ritter is an intriguing fellow. If you take a glance at his work history (AT&T UNIX System Labs -> Novell -> Sun -> Oracle), you can easily see, he’s a heavy weight player. His presentation was rich in content, no corpo-bullshit. He started with a bit of history of JCP and how it looks like right now, then moved to the most interesting stuff, changes. Now I could give you a summary here, but there is really no point: you’d be much better taking look at the slides. There are only 48 of them, but everything is self-explanatory. To Java SE 8 and Beyond! | Simon Ritter While I’m very disappointed with the speed of changes, especially when compared to the C# world, I’m glad with the direction and the fact that they finally want to BREAK the compatibility with the broken stuff (generics, etc.).  Moving to other languages I guess I won’t be the one to scream “My god, finally!” somewhere in 2017, though. All the changes together look very promising, it’s just that I’d like to have them like… now? Next year max, not near the heat death of the universe. Simon also revealed one of the great mysteries of Java, to me: The original idea behind JNI was to make it hard to write, to discourage people form using it. On a side note, did you know Tegra3 has actually 5 cores? You use 4 of them, and then switch to the other one, when you battery gets low. BOF: Spring and CloudFoundry Having most of my folks moved to see “Typesafe stack 2.0” fabulously organized by Rafał Wasilewski and  Wojtek Erbetowski (with both of whom I had a pleasure to travel to the conference) and knowing it will be recorded, I’ve decided to see what Josh Long has to say about CloudFoundry, a subject I find very intriguing after the de facto fiasco of Google App Engine. The audience was small but vibrant, mostly users of Amazon EC2, and while it turned out that Josh didn’t have much, with pricing and details not yet public, the fact that Spring Source has already created their own competition (Could Foundry is both an Open Source app and a service), takes a lot from my anxiety. For the review of the second day of the conference, go here.
33rd Degree is over. After the one last year, my expectations were very high, but Grzegorz Duda once again proved he’s more than able to deliver. With up to five tracks (most of the time: four presentations + one workshop), and ~650 attendees,  there was a lot to see and a lot to do, thus everyone will probably have a little bit different story to tell. Here is mine.

Twitter: From Ruby on Rails to the JVM

Raffi Krikorian talking about Twitter and JVM

The conference started with  Raffi Krikorian from Twitter, talking about their use for JVM. Twitter was build with Ruby but with their performance management a lot of the backend was moved to Scala, Java and Closure. Raffi noted, that for Ruby programmers Scala was easier to grasp than Java, more natural, which is quite interesting considering how many PHP guys move to Ruby these days because of the same reasons. Perhaps the path of learning Jacek Laskowski once described (Java -> Groovy -> Scala/Closure) may be on par with PHP -> Ruby -> Scala. It definitely feels like Scala is the holy grail of languages these days.

Raffi also noted, that while JVM delivered speed and a concurrency model to Twitter stack, it wasn’t enough, and they’ve build/customized their own Garbage Collector. My guess is that Scala/Closure could also be used because of a nice concurrency solutions (STM, immutables and so on).

Raffi pointed out, that with the scale of Twitter, you easily get 3 million hits per second, and that means you probably have 3 edge cases every second. I’d love to learn listen to lessons they’ve learned from this.

 

Complexity of Complexity

The second keynote of the first day, was Ken Sipe talking about complexity. He made a good point that there is a difference between complex and complicated, and that we often recognize things as complex only because we are less familiar with them. This goes more interesting the moment you realize that the shift in last 20 years of computer languages, from the “Less is more” paradigm (think Java, ASM) to “More is better” (Groovy/Scala/Closure), where you have more complex language, with more powerful and less verbose syntax, that is actually not more complicated, it just looks less familiar.

So while 10 years ago, I really liked Java as a general purpose language for it’s small set of rules that could get you everywhere, it turned out that to do most of the real world stuff, a lot of code had to be written. The situation got better thanks to libraries/frameworks and so on, but it’s just patching. New languages have a lot of stuff build into, which makes their set of rules and syntax much more complex, but once you get familiar, the real world usage is simple, faster, better, with less traps laying around, waiting for you to fall.

Ken also pointed out, that while Entity Service Bus looks really simple on diagrams, it’s usually very difficult and complicated to use from the perspective of the programmer. And that’s probably why it gets chosen so often – the guys selling/buying it, look no deeper than on the diagram.

 

Pointy haired bosses and pragmatic programmers: Facts and Fallacies of Software Development

Venkat Subramaniam with Dima
Dima got lucky. Or maybe not.

Venkat Subramaniam is the kind of a speaker that talk about very simple things in a way, which makes everyone either laugh or reflect. Yes, he is a showman, but hey, that’s actually good, because even if you know the subject quite well, his talks are still very entertaining.
This talk was very generic (here’s my thesis: the longer the title, the more generic the talk will be), interesting and fun, but at the end I’m unable to see anything new I’d have learned, apart from the distinction between Dynamic vs Static and Strong vs Weak typing, which I’ve seen the last year, but managed to forgot. This may be a very interesting argument for all those who are afraid of Groovy/Ruby, after bad experience with PHP or Perl.

Build Trust in Your Build to Deployment Flow!


Frederic Simon talked about DevOps and deployment, and that was a miss in my  schedule, because of two reasons. First, the talk was aimed at DevOps specifically, and while the subject is trendy lately, without big-scale problems, deployment is a process I usually set up and forget about. It just works, mostly because I only have to deal with one (current) project at a time. 
Not much love for Dart.

Second, while Frederic has a fabulous accent and a nice, loud voice, he tends to start each sentence loud and fade the sound at the end. This, together with mics failing him badly, made half of the presentation hard to grasp unless you were sitting in the first row.

I’m not saying the presentation was bad, far from it, it just clearly wasn’t for me.
I’ve left a few minutes before the end, to see how many people came to Dart presentation by Mike West. I was kind of interested, since I’m following Warsaw Google Technology User Group and heard a few voices about why I should pay attentions to that new Google language. As you can see from the picture on the right, the majority tends to disagree with that opinion.

 

Non blocking, composable reactive web programming with Iteratees

Sadek Drobi’s talk about Iteratees in Play 2.0 was very refreshing. Perhaps because I’ve never used Play before, but the presentation was flawless, with well explained problems, concepts and solutions.
Sadek started with a reflection on how much CPU we waste waiting for IO in web development, then moved to Play’s Iteratees, to explain the concept and implementation, which while very different from the that overused Request/Servlet model, looked really nice and simple. I’m not sure though, how much the problem is present when you have a simple service, serving static content before your app server. Think apache (and faster) before tomcat. That won’t fix the upload/download issue though, which is beautifully solved in Play 2.0

The Future of the Java Platform: Java SE 8 & Beyond


Simon Ritter is an intriguing fellow. If you take a glance at his work history (AT&T UNIX System Labs -> Novell -> Sun -> Oracle), you can easily see, he’s a heavy weight player.
His presentation was rich in content, no corpo-bullshit. He started with a bit of history of JCP and how it looks like right now, then moved to the most interesting stuff, changes. Now I could give you a summary here, but there is really no point: you’d be much better taking look at the slides. There are only 48 of them, but everything is self-explanatory.

While I’m very disappointed with the speed of changes, especially when compared to the C# world, I’m glad with the direction and the fact that they finally want to BREAK the compatibility with the broken stuff (generics, etc.).  Moving to other languages I guess I won’t be the one to scream “My god, finally!” somewhere in 2017, though. All the changes together look very promising, it’s just that I’d like to have them like… now? Next year max, not near the heat death of the universe.

Simon also revealed one of the great mysteries of Java, to me:

The original idea behind JNI was to make it hard to write, to discourage people form using it.

On a side note, did you know Tegra3 has actually 5 cores? You use 4 of them, and then switch to the other one, when you battery gets low.

BOF: Spring and CloudFoundry

Having most of my folks moved to see “Typesafe stack 2.0” fabulously organized by Rafał Wasilewski and  Wojtek Erbetowski (with both of whom I had a pleasure to travel to the conference) and knowing it will be recorded, I’ve decided to see what Josh Long has to say about CloudFoundry, a subject I find very intriguing after the de facto fiasco of Google App Engine.

The audience was small but vibrant, mostly users of Amazon EC2, and while it turned out that Josh didn’t have much, with pricing and details not yet public, the fact that Spring Source has already created their own competition (Could Foundry is both an Open Source app and a service), takes a lot from my anxiety.

For the review of the second day of the conference, go here.

You May Also Like

Integration testing custom validation constraints in Jersey 2

I recently joined a team trying to switch a monolithic legacy system into set of RESTful services in Java. They decided to use latest 2.x version of Jersey as a REST container which was not a first choice for me, since I’m not a big fan of JSR-* specs. But now I must admit that JAX-RS 2.x is doing things right: requires almost zero boilerplate code, support auto-discovery of features and prefers convention over configuration like other modern frameworks. Since the spec is still young, it’s hard to find good tutorials and kick-off projects with some working code. I created jersey2-starter project on GitHub which can be used as starting point for your own production-ready RESTful service. In this post I’d like to cover how to implement and integration test your own validation constraints of REST resources.

Custom constraints

One of the issues which bothers me when coding REST in Java is littering your class model with annotations. Suppose you want to build a simple Todo list REST service, when using Jackson, validation and Spring Data, you can easily end up with this as your entity class:

@Document
public class Todo {
    private Long id;
    @NotNull
    private String description;
    @NotNull
    private Boolean completed;
    @NotNull
    private DateTime dueDate;

    @JsonCreator
    public Todo(@JsonProperty("description") String description, @JsonProperty("dueDate") DateTime dueDate) {
        this.description = description;
        this.dueDate = dueDate;
        this.completed = false;
    }
    // getters and setters
}

Your domain model is now effectively blured by messy annotations almost everywhere. Let’s see what we can do with validation constraints (@NotNulls). Some may say that you could introduce some DTO layer with own validation rules, but it conflicts for me with pure REST API design, which stands that you operate on resources which should map to your domain classes. On the other hand - what does it mean that Todo object is valid? When you create a Todo you should provide a description and due date, but what when you’re updating? You should be able to change any of description, due date (postponing) and completion flag (marking as done) - but you should provide at least one of these as valid modification. So my idea is to introduce custom validation constraints, different ones for creation and modification:

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForCreation.Validator.class)
public @interface ValidForCreation {
    //...
    class Validator implements ConstraintValidator<ValidForCreation, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && todo.getDescription() != null
                && todo.getDueDate() != null;
        }
    }
}

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForModification.Validator.class)
public @interface ValidForModification {
    //...
    class Validator implements ConstraintValidator<ValidForModification, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && (todo.getDescription() != null || todo.getDueDate() != null || todo.isCompleted() != null);
        }
    }
}

And now you can move validation annotations to the definition of a REST endpoint:

@POST
@Consumes(APPLICATION_JSON)
public Response create(@ValidForCreation Todo todo) {...}

@PUT
@Consumes(APPLICATION_JSON)
public Response update(@ValidForModification Todo todo) {...}

And now you can remove those NotNulls from your model.

Integration testing

There are in general two approaches to integration testing:

  • test is being run on separate JVM than the app, which is deployed on some other integration environment
  • test deploys the application programmatically in the setup block.

Both of these have their pros and cons, but for small enough servoces, I personally prefer the second approach. It’s much easier to setup and you have only one JVM started, which makes debugging really easy. You can use a generic framework like Arquillian for starting your application in a container environment, but I prefer simple solutions and just use emdedded Jetty. To make test setup 100% production equivalent, I’m creating full Jetty’s WebAppContext and have to resolve all runtime dependencies for Jersey auto-discovery to work. This can be simply achieved with Maven resolved from Shrinkwrap - an Arquillian subproject:

    WebAppContext webAppContext = new WebAppContext();
    webAppContext.setResourceBase("src/main/webapp");
    webAppContext.setContextPath("/");
    File[] mavenLibs = Maven.resolver().loadPomFromFile("pom.xml")
                .importCompileAndRuntimeDependencies()
                .resolve().withTransitivity().asFile();
    for (File file: mavenLibs) {
        webAppContext.getMetaData().addWebInfJar(new FileResource(file.toURI()));
    }
    webAppContext.getMetaData().addContainerResource(new FileResource(new File("./target/classes").toURI()));

    webAppContext.setConfigurations(new Configuration[] {
        new AnnotationConfiguration(),
        new WebXmlConfiguration(),
        new WebInfConfiguration()
    });
    server.setHandler(webAppContext);

(this Stackoverflow thread inspired me a lot here)

Now it’s time for the last part of the post: parametrizing our integration tests. Since we want to test validation constraints, there are many edge paths to check (and make your code coverage close to 100%). Writing one test per each case could be a bad idea. Among the many solutions for JUnit I’m most convinced to the Junit Params by Pragmatists team. It’s really simple and have nice concept of JQuery-like helper for creating providers. Here is my tests code (I’m also using builder pattern here to create various kinds of Todos):

@Test
@Parameters(method = "provideInvalidTodosForCreation")
public void shouldRejectInvalidTodoWhenCreate(Todo todo) {
    Response response = createTarget().request().post(Entity.json(todo));

    assertThat(response.getStatus()).isEqualTo(BAD_REQUEST.getStatusCode());
}

private static Object[] provideInvalidTodosForCreation() {
    return $(
        new TodoBuilder().withDescription("test").build(),
        new TodoBuilder().withDueDate(DateTime.now()).build(),
        new TodoBuilder().withId(123L).build(),
        new TodoBuilder().build()
    );
}

OK, enough of reading, feel free to clone the project and start writing your REST services!

I recently joined a team trying to switch a monolithic legacy system into set of RESTful services in Java. They decided to use latest 2.x version of Jersey as a REST container which was not a first choice for me, since I’m not a big fan of JSR-* specs. But now I must admit that JAX-RS 2.x is doing things right: requires almost zero boilerplate code, support auto-discovery of features and prefers convention over configuration like other modern frameworks. Since the spec is still young, it’s hard to find good tutorials and kick-off projects with some working code. I created jersey2-starter project on GitHub which can be used as starting point for your own production-ready RESTful service. In this post I’d like to cover how to implement and integration test your own validation constraints of REST resources.

Custom constraints

One of the issues which bothers me when coding REST in Java is littering your class model with annotations. Suppose you want to build a simple Todo list REST service, when using Jackson, validation and Spring Data, you can easily end up with this as your entity class:

@Document
public class Todo {
    private Long id;
    @NotNull
    private String description;
    @NotNull
    private Boolean completed;
    @NotNull
    private DateTime dueDate;

    @JsonCreator
    public Todo(@JsonProperty("description") String description, @JsonProperty("dueDate") DateTime dueDate) {
        this.description = description;
        this.dueDate = dueDate;
        this.completed = false;
    }
    // getters and setters
}

Your domain model is now effectively blured by messy annotations almost everywhere. Let’s see what we can do with validation constraints (@NotNulls). Some may say that you could introduce some DTO layer with own validation rules, but it conflicts for me with pure REST API design, which stands that you operate on resources which should map to your domain classes. On the other hand - what does it mean that Todo object is valid? When you create a Todo you should provide a description and due date, but what when you’re updating? You should be able to change any of description, due date (postponing) and completion flag (marking as done) - but you should provide at least one of these as valid modification. So my idea is to introduce custom validation constraints, different ones for creation and modification:

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForCreation.Validator.class)
public @interface ValidForCreation {
    //...
    class Validator implements ConstraintValidator<ValidForCreation, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && todo.getDescription() != null
                && todo.getDueDate() != null;
        }
    }
}

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForModification.Validator.class)
public @interface ValidForModification {
    //...
    class Validator implements ConstraintValidator<ValidForModification, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && (todo.getDescription() != null || todo.getDueDate() != null || todo.isCompleted() != null);
        }
    }
}

And now you can move validation annotations to the definition of a REST endpoint:

@POST
@Consumes(APPLICATION_JSON)
public Response create(@ValidForCreation Todo todo) {...}

@PUT
@Consumes(APPLICATION_JSON)
public Response update(@ValidForModification Todo todo) {...}

And now you can remove those NotNulls from your model.

Integration testing

There are in general two approaches to integration testing:

  • test is being run on separate JVM than the app, which is deployed on some other integration environment
  • test deploys the application programmatically in the setup block.

Both of these have their pros and cons, but for small enough servoces, I personally prefer the second approach. It’s much easier to setup and you have only one JVM started, which makes debugging really easy. You can use a generic framework like Arquillian for starting your application in a container environment, but I prefer simple solutions and just use emdedded Jetty. To make test setup 100% production equivalent, I’m creating full Jetty’s WebAppContext and have to resolve all runtime dependencies for Jersey auto-discovery to work. This can be simply achieved with Maven resolved from Shrinkwrap - an Arquillian subproject:

    WebAppContext webAppContext = new WebAppContext();
    webAppContext.setResourceBase("src/main/webapp");
    webAppContext.setContextPath("/");
    File[] mavenLibs = Maven.resolver().loadPomFromFile("pom.xml")
                .importCompileAndRuntimeDependencies()
                .resolve().withTransitivity().asFile();
    for (File file: mavenLibs) {
        webAppContext.getMetaData().addWebInfJar(new FileResource(file.toURI()));
    }
    webAppContext.getMetaData().addContainerResource(new FileResource(new File("./target/classes").toURI()));

    webAppContext.setConfigurations(new Configuration[] {
        new AnnotationConfiguration(),
        new WebXmlConfiguration(),
        new WebInfConfiguration()
    });
    server.setHandler(webAppContext);

(this Stackoverflow thread inspired me a lot here)

Now it’s time for the last part of the post: parametrizing our integration tests. Since we want to test validation constraints, there are many edge paths to check (and make your code coverage close to 100%). Writing one test per each case could be a bad idea. Among the many solutions for JUnit I’m most convinced to the Junit Params by Pragmatists team. It’s really simple and have nice concept of JQuery-like helper for creating providers. Here is my tests code (I’m also using builder pattern here to create various kinds of Todos):

@Test
@Parameters(method = "provideInvalidTodosForCreation")
public void shouldRejectInvalidTodoWhenCreate(Todo todo) {
    Response response = createTarget().request().post(Entity.json(todo));

    assertThat(response.getStatus()).isEqualTo(BAD_REQUEST.getStatusCode());
}

private static Object[] provideInvalidTodosForCreation() {
    return $(
        new TodoBuilder().withDescription("test").build(),
        new TodoBuilder().withDueDate(DateTime.now()).build(),
        new TodoBuilder().withId(123L).build(),
        new TodoBuilder().build()
    );
}

OK, enough of reading, feel free to clone the project and start writing your REST services!

Rapid js + css development

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