A CDI Primer: Part 4

In the previous post, we learned that the only Contextuals that matter, really, are Beans, and we learned a little bit about injection points and loosely how they’re filled.

In this post we’ll look at how CDI actually discovers things, and how it normalizes them into Bean implementations, and how it marries them with Context implementations to figure out what their lifecycles are going to be.

The Container Lifecycle

CDI has a very well-specified lifecycle.  There is a general startup phase during which all the raw materials in the world are discovered, arranged and pared down to form a network of Bean implementations that produce and consume each other.  Once that startup phase has completed, the actual application—whatever it might be, that makes use of all these producers and consumers—starts, and runs, and does its thing.  Then there is a shutdown free-for-all where all Bean implementations can, indirectly, get a chance to clean up, and that’s all there is to it.

But what are you, the end-user, the ordinary developer, supposed to do with all this?  In your hand, you have a class that has some injection points in it (fields or methods annotated with Inject), and you want them filled.  What does this have to do with Bean implementations?  After all, your class doesn’t implement Bean.  We’ll see how internally, in a way, it sort of does.

Discovering Things

As part of the startup phase, CDI performs type discovery and bean discovery.

Type discovery is a fancy name for taking stock of what classes exist on the classpath.  Plugins, called portable extensions, can affect this; that’s a subject for another day.  For now, know that CDI will scan the classpath for particular classes and will add them to a set of such classes that represents its type world.

Once types have been discovered, CDI performs bean discovery, where some of those types it found lying around are normalized into Bean implementations internally.

It’s important to realize what’s going on here.  For the typical developer scenario, most classes that are discovered are turned into producers.  This can be a little counterintuitive—I don’t know about you, but that’s not usually what I think of when I have a class in my hand named with a noun, like Person or Customer.  Really?  Customer is a producer?  A producer of what?  Well, of instances of itself, it turns out.  Which of course we all actually know, because it has a constructor.

Managed Beans

So consider our ongoing stupid example of a Backpack class, with a simple zero-argument constructor, annotated with Singleton, and a Gorp-typed field annotated with Inject.  Let’s say that CDI discovers it.  Internally during bean discovery CDI creates a Bean to represent it:

• whose create() method calls the zero-argument Backpack constructor
• whose destroy() method does nothing
• whose getTypes() method returns a Set that includes Backpack.class
• whose getBeanClass() method returns  Backpack.class
• whose getScope() method returns Singleton.class
• whose getInjectionPoints() method returns a Set that includes an InjectionPoint whose getType() method returns Gorp.class and whose getMember() method returns the Field in question

A Bean implementation built internally like this is called a managed bean, and the class itself is frequently called a managed bean as well.

It’s important to realize that for a given managed bean one of its bean types and its bean class are always identical.

Producer Methods

Another very common kind of bean is a producer method.  In this case, CDI has done its type discovery, and has found a class called CandyShop also annotated with Singleton (I’m picking Singleton because it is a scope that everyone is intuitively familiar with.)  Let’s say this class has a method in it declared like this:

@Produces
@Singleton
public Candy produceCandy() {
  return new Candy();
}

This time, CDI will create a Bean internally for CandyShop that looks a lot like the one above, namely:

• whose create() method calls the zero-argument CandyShop constructor
• whose destroy() method does nothing
• whose getTypes() method returns a Set that includes CandyShop.class
• whose getBeanClass() method returns  CandyShop.class
• whose getScope() method returns Singleton.class

But then it will also create a Bean internally that represents the producer method:

• whose create() method calls the produceCandy() method
• whose destroy() method does nothing
• whose getTypes() method returns a Set that includes Candy.class
• whose getBeanClass() method returns  CandyShop.class
• whose getScope() method returns Singleton.class

Do you see that the bean class here is CandyShop but the getTypes() method returns a Set of bean types that includes Candy.class, not CandyShop.class?  The takeaway here is that usually when you’re considering a true CDI bean you are, as a normal developer, interested in one of its bean types, not its bean class.  In other words, you’re interested in (in this example) Candy.class, and normally not so interested in the fact that the producer method that creates its instances happens to be housed in a class called CandyShop.  The terminology in the documentation certainly does its best to make this about as clear as mud.

Producer Fields

Just as you can have a producer method whose bean class is one thing while its bean types are another, you can have a producer field.  Let’s say our CandyShop class from the example above also has a field in it declared like this:

@Produces
@Singleton
private PeanutButter peanutButter;

Once again, CDI will create a Bean for CandyShop, just as it did before, and here it will also create another Bean:

• whose create() method returns the value of the peanutButter field
• whose destroy() method does nothing
• whose getTypes() method returns a Set that includes PeanutButter.class
• whose getBeanClass() method returns  CandyShop.class
• whose getScope() method returns Singleton.class

In practice, producer fields are comparatively rare.  They exist primarily to bridge the worlds of Java EE, where you might have a field that is annotated with Resource (so is being set by some kind of JNDI-aware machinery), and CDI where you can have the very same field annotated with Produces.  This lets CDI set up a Bean implementation under the covers that creates instances from Java EE-land without any other aspects of the CDI ecosystem really being aware that Java EE is even in the picture.

Decorators and Interceptors

Two other primary Bean implementations are Decorators and Interceptors.  I’m not going to talk about them because although it may look like it by this point I’m not writing a book.  Suffice it to say they are represented in the CDI ecosystem by Beans, and so are inherently producers of things, which can also be counterintuitive.

Custom Beans

Finally, without digging deep into portable extensions, we can at least say that portable extensions have a variety of ways to cause a Bean implementation to be created by hand at container startup time.  When Beans are added into the system this way, the portable extension has absolute full control over them.

Putting It Together

The biggest takeaway here is that everything in CDI is a Bean.  In the documentation, almost everything is a little-b bean.  A bean, represented by a Bean, is fundamentally a producer of something.  There are recipes that we’ve just enumerated that translate ordinary Java constructs into Bean implementations when bean discovery is performed: a creator and a destroyer (Contextual) together with bean types and a scope (BeanAttributes), a hosting bean class and a set of injection points (Bean).

There’s another thing that falls out of this.  Bean is a parameterized type: you have a Bean<T>.  The <T> is, however, always usage-specific, because it comes by way of Contextual, whose usage of its type parameter is the return type from its create method.  That is, <T> represents one of a Bean‘s bean types—one of the kinds of things it can make—not its bean class—the class hosting the producer method or constructor.

Consider a Bean<Person>.  Because a Bean<Person> is a Contextual<Person>, it follows that you can call its create method and get a Person back.  But it does not follow that calling its getBeanClass() method will return Person.class!  Perhaps the Bean<Person> you are looking at represents a producer method, or a producer field, for example.

Finally

So finally we can see how CDI makes @Inject work, which was what we set out to do in part 0:

• CDI discovers types
• For each type found during type discovery, CDI creates a Bean to represent it, or at least tries to
• For each producer method and producer field (and other cases), CDI creates another Bean to represent it
• For every InjectionPoint found in this pile of Beans, CDI performs typesafe resolution to see what Beans have bean types that “match” the InjectionPoint‘s type
• Assuming that all slots get matched up to producers, whenever CDI needs to obtain an instance of something, it does so through the right Context which is in the business of handing out contextual instances
• CDI can find the right Context by checking out the scope available from each Bean
• Ultimately the Context, when asked to produce an instance of something, will call through to a Bean‘s create method

I’ve deliberately left out qualifiers, which are extremely important, but are deserving of their own article later.

There’s much more to say about CDI, but I think I’ll stop there for now.

Thanks for reading this primer!

A CDI Primer: Part 3

In the previous post, we learned about typesafe resolution (the process of matching producers (Contextual implementations) with consumers) and where, exactly, Contexts fit in.

We also learned that you can “label” a Context with a scope, an annotation class standing in for the kind of lifecycle you want a Context whose getScope method returns it to implement.

We also learned that in some unspecified way you can apply the same annotation to a Contextual implementation.

The net result was that we sketched out our first hazy picture of how a Gorp-typed slot in a consumer (Backpack) might receive a singleton Gorp produced by a Contextual implementation whose type parameter is Gorp.  (If you’re wondering what all this is about, I heartily recommend you start at the beginning with part 0.)

Nevertheless, as we did this, we waved our hands furiously over certain details.  Specifically, while describing typesafe resolution, we made many references to CDI linking together producers and consumers without describing exactly how this happens, and we spoke a lot about Contextuals, but never really covered what they are, exactly.  We’ll look into that in some detail in this article.

Contextual Implementations: Beans

Throughout this series of articles, we’ve talked about Contextuals as being CDI’s implementation of producers in the dependency injection mindset (which we described in part 0).

Contextuals produce contextual instances.  And contextual instances are what Contexts supply to fill @Inject-annotated slots.  You get all that by this point I’m sure.  But we haven’t discussed what Contextuals are.

Strictly speaking, of course, a Contextual implementation only has to implement the create and destroy methods.  Great.

Let’s say you write a two-method-long class that does that.  Now what?  Nothing, that’s what.

It turns out that CDI doesn’t really give you an “in” using this interface: you can compile a Contextual implementation, stick it somewhere, and it will happily sit there until the end of time waiting to be discovered and used, which will never happen.

But a subclass (subinterface) of Contextual is Bean, and we’ve all heard that term before.

As it turns out, the only direct subtype of Contextual that CDI inherently knows about is Bean.

So in most cases where I’ve written about Contextuals, you can substitute Beans, and be just fine.  A Bean “is a” Contextual, and CDI deals primarily in Beans.  (There are mechanisms throughout CDI for getting Bean implementations “into” the system, but none for directly getting “raw” Contextuals that are not Beans into the system.  We’ll cover this interesting structural fiesta below.)

So if that’s all true, why have I been talking about Contextuals all this time, and not Beans?

Because Contextual is the part of the Bean interface that deals with production (it consists solely of create and destroy methods, after all).  The rest of the Bean interface, as we’ll see, deals with other things.

We’ve backed into this series of articles from the production end: we have been shining a light on exactly how “CDI makes @Inject work”.  So production has been front and center, and that’s what Contextuals give you.

Now with the production facet of Beans under our belts, we can turn our attention to the other facets.

Let’s start with one such facet—the BeanAttributes interface.

BeanAttributes

CDI was defined originally back in an era where inheritance was used a lot, and composition…not so much.  As a result some compositional concerns in CDI are expressed—conveniently but a little opaquely—in terms of inheritance.  This is true of the trio formed by Bean, BeanAttributes and Contextual.  Luckily we can tease them apart.

Here is a class diagram showing that Bean inherits from both Contextual and BeanAttributes:

This is certainly obviously how the interfaces are actually structured, but it hides the more important fact that each of the collections of methods defined by each interface is really a facet of the same underlying object.  With only a few rare exceptions, CDI assumes that the object “behind the curtain” of a Contextual interface, for example, will also implement Bean.

That is, a Bean “is a” Contextual, sure, but really a Bean “has a” Contextual facet: it has a facet that deals with production.  We’ve covered Contextual extensively.

A Bean also “is a” BeanAttributes, but really, again, Bean “has a” BeanAttributes facet: it has a facet that deals only with discovery- and typesafe resolution-related concerns.  (You’ll note in particular that the T type parameter used by create and destroy is not used anywhere in the BeanAttributes interface!)

A BeanAttributes is a facet of a Bean that is concerned with its overall place in the CDI world.  We’ll look at its methods selectively and carefully, ignoring those that don’t yet make any sense.

(And finally the collection of methods defined by the Bean interface itself is a facet of a Bean implementation that is concerned with its role as a consumer.  We’ll cover this below.)

getScope()

The first BeanAttributes method of interest we’ll consider is getScope(), which returns an annotation class representing a scope.

Here we can finally see explicitly what we handwaved over in part 2: effectively in CDI, every Contextual implementation is always also a BeanAttributes implementation, so every Contextual is capable of essentially reporting which Context manages the lifecycle of its produced objects.  See part 2 for more on this.

This lets BeanAttributes that are producers (which is to say all of them, since in CDI’s ecosystem they’re all also effectively Contextuals) still have a say in the lifecycle management of their produced objects, but they don’t actually have to implement that management themselves.  Nice.

getTypes()

The next one is getTypes(), which reports the Set of Types that a producer can make.  Again, this method only makes sense when it is tacitly understood that BeanAttributes and Contextual are always facets of the same underlying object, i.e. that all BeanAttributes are always producers (Contextuals).

So, for example, if your Contextual implementation gets instantiated with a type parameter value of Object, then if your Contextual implementation is also a BeanAttributes implementation, as it should be, you can specify with this method exactly what subtypes of Object your create method produces.

CDI calls this method to gain insight into how to “fill” a consumer’s @Inject-annotated slot with an appropriately-typed contextual instance.  When trying to locate a suitable producer it can winnow the field by looking at the return value from this method and perform typesafe resolution using the results.  (For more on typesafe resolution, see part 2.)

Other BeanAttributes Methods

We’re going to table discussion of the other BeanAttributes methods for now, as they’re really another layer on top of these fundamentals.  We’ll come back to them in a later article.

Bean

Finally, the third facet of the Bean interface consists of the methods it defines itself apart from those defined by Contextual and BeanAttributes.  These methods are related to a producer’s also being a consumer.

On Consuming Producers, Producer Classes and InjectionPoints

Back in part 0, we saw that there’s nothing wrong with a producer also being a consumer!  Producers frequently need to consume raw materials to do their jobs.

We also saw that producers come in many abstract flavors: methods, fields and constructors.

A producer also needs a “host class” (a method, field or constructor has to “live in” a class, after all), and in part 0 we decided to call such host classes producer classes for want of a better term.  (CDI calls them “bean classes” for reasons we are only now capable of understanding and which we’ll look into below.)

We’ve also talked throughout this article series about consumers and producers in terms of “slots” and “filling slots”.  I have a Backpack; it has an @Inject-annotated Gorp-typed “slot”; CDI performs automatic wiring and “fills” the “slot” with a contextual instance of Gorp sourced from the right Context by way of a Contextual implementation.  (We went into some detail on this example in part 1.)

In the spirit of less handwaving, let’s call these slots what they’re actually called in CDI: injection points.

An injection point is a slot that can be filled with a contextual instance.  It is a point at which CDI performs (dependency) injection.  Injection points are represented in CDI by the appropriately-named interface InjectionPoint.  InjectionPoints have a type (and some other stuff, which we’ll cover another day).

So our Backpack consumer has a Gorp-typed injection point.

While it does not explicitly use these terms, CDI says that a consumer simply is something with InjectionPoints: it is a Thing With Slots That Have To Be Filled.

As we’ve seen, effectively all Contextuals—all producers—are also Beans.

And we’ve seen that a producer can be a consumer.

And finally we’ve seen that a producer is housed in a producer class, which I’ve told you CDI calls a bean class.

So it should come as no surprise that this consumer facet of a Bean is represented by two methods:

• getInjectionPoints()
• getBeanClass()

getInjectionPoints is pretty simple: it returns the set of “slots” that the producer needs values for in order to do its job.  If the producer is a method, for example, then the injection points will represent the method’s parameters.  If the producer is ultimately represented by a constructor, for a more complicated example, the injection points will represent possibly the constructor itself as well as any other @Inject-annotated fields and methods in the class.

getBeanClass is a little trickier, and is in my experience one of the most misunderstood methods in all of CDI.

​​getBeanClass()

getBeanClass returns the producer class, not the class of the thing being produced.

That is, if you have a producer that is a method, getBeanClass returns its “host class”—its declaring class—not the class of its return type.  This will become important when we talk about CDI producer methods.

Similarly, if you have a producer that is a field, getBeanClass returns its declaring class, not the class of the field.  This will become important when we talk about CDI producer fields.

Finally, if you have a producer that is fundamentally a constructor, obviously a constructor makes instances of its own declaring class, so getBeanClass will return the producer class, sure, but that will also be the class of the thing being constructed!  This will become important when we talk about the most common kind of Bean implementation found in CDI: the managed bean.

The most important things to take away from these CDI internals so far are:

• CDI has many ways of discovering things, but all producers and consumers from the dependency injection mindset can be represented in CDI as Bean implementations
• a Bean is fundamentally a producer of things, not the things produced, and a consumer only secondarily
• all Contextual implementations normally found in a CDI application are Bean implementations too

Automatic Wiring (Almost Entirely) Demystified

Our picture of how CDI accomplishes automatic wiring just got a little clearer.  Every producer in the system now has a facility for reporting:

• what kinds of things it makes (getTypes())
• what Context the things it makes should “belong” to (getScope())
• what it needs to do its job (getInjectionPoints())
• what class it “lives in”, of which an instance might need to be produced for the producer to be invoked (getBeanClass())

If CDI could find Bean implementations in various flavors lying around, and then normalize them into true Bean implementations in memory, it could match the Gorp-typed InjectionPoint of the Backpack-typed Bean implementation to hopefully the one Bean implementation whose getTypes method contains Gorp.class in its return value.  It could then locate the appropriate Context implementation, by looking at the return value of the getScope method, and could ask that Context to get a Gorp.  It could then use the InjectionPoint to set the actual Gorp value.

That is, of course, exactly what CDI does.

In the next post, we’ll get rid of the remaining handwavy bits and will look at how CDI:

• “normalizes” “Bean implementations in various flavors lying around” into “true Bean implementations in memory”
• “locate[s] the appropriate Context implementation”
• Uses “the InjectionPoint to set the actual Gorp value”

Thanks for reading along so far!

A CDI Primer: Part 2

In the previous post we covered Contexts and Contextuals and the relationship between them.  A Contextual, briefly, is the CDI representation of a producer (a CDI-independent concept within the dependency injection mindset we covered in part 0) focused solely on the mechanics of production, with no responsibility for caching or storage or any other kind of lifecycle management.  A Context is CDI’s façade of sorts for Contextuals that has no responsibility for making objects of a given kind—it uses Contextuals for that—but all kinds of responsibility for managing the lifecycles of those manufactured or acquired objects.

We also learned that contextual instances are effectively the return values from the Context#get(Contextual, CreationalContext) method invoked on a given Context (and by extension the return values of implementations of the Contextual#create(CreationalContext) method.)  If your class has an @Inject-annotated “slot” in it, and it gets “filled” by CDI, then you just took delivery of a contextual instance from a Context, created by a Contextual.

In this post we’ll start looking at the actual mechanics that CDI uses to match contextual instances to consumer “slots”, and the beginnings of how those pieces of the machinery are found in the first place.

A Digression on Java Generics

And now, for everyone’s favorite subject: Java generics.

First, some housekeeping.  I’m going to run right into the utterly awful WordPress editor which is schizophrenic about angle brackets.  Java generics feature a lot of angle brackets.  They disappear in WordPress.  (Using ampersand-lt-semicolon and similar SGML-entity-based “solutions” doesn’t work, because the helpful editor will expand it in place, then save the result, neutering the attempt to use them in the first place.)  So I’ll use curly braces instead.  Just squint a lot and you might even be able to see them as angle brackets.

Suppose I have a field whose type is List{Number} and you have a List{Integer}.  Can I take your List{Integer} and put it into my List{Number}-typed field?  No, I cannot.  You can learn more about this from the Java Tutorial if you need to.  This is a case of trying to figure out assignability of parameterized types (like List{Number} and Class{T} and so on).  In order to do wiring properly, you—or the magic system that is going to do the wiring for you, like CDI—have to get this right.

Now, if I have a field whose type is List{? extends Number} and you have a List{Integer}, that will “go into” my field just fine.  So the person or machine doing wiring has to take wildcards into account as well.

Typesafe Resolution

This process of accounting for all sorts of different types—simple-typed slots like fields with types like Number or complicated slots with parameterized types like List{Number}—and matching those slots to compatible types, such as the return types of all producers in the system, is known as typesafe resolution.  “Typesafe” here is meant to emphasize the fact that—unlike some other dependency injection frameworks such as the machinery that was in Java EE at the time—CDI matches types, not names: your @Inject-annotated field’s type is matched to a producer’s type.  (Earlier dependency injection frameworks used name matches, which are more brittle.)  “Resolution” refers to the fact that a consumer’s slot has been matched, or resolved, to a particular production type—and thereby to a particular dependency.

Let’s say that CDI can somehow find all the slots in my classes that need contextual instances.  And it can find producers that make all different sorts of contextual instances of all different sorts of types.  If there is exactly one producer in that big pile of producers (of any kind—constructor, method, field…) whose production type is assignable to a given slot, then we have a match: we say that typesafe resolution has completed successfully, and we know that that wiring can be set up automatically.  If I have a slot that asks for a Gorp, and there is exactly one producer that returns a Gorp (or a Gorp subclass), then as we saw back in part 1 we can just “see” that that producer should be called to fill that slot.  CDI can therefore also “see” that this is the case, so is able to make it work.

Unsatisfied Dependencies

What happens when there is no producer whose production type is assignable to my @Inject-annotated field’s type?  We say in this case that typesafe resolution failed because we have an unsatisfied dependency.  I asked for a Gorp , but there wasn’t any Gorp producer that could respond.  The wiring cannot be completed automatically.

Ambiguous Dependencies

What happens when there are lots of producers whose production types are all assignable to my @Inject-annotated field’s type?  We say in this case that typesafe resolution failed because it was ambiguous.  The wiring cannot be completed automatically.  Without further information, CDI can’t make a call on which producer to select to produce an object to go in the right slot.

Finding the Right Context

Let’s say that I have a class named Backpack with a field whose type is Gorp, and there is exactly one producer in the world (represented as always in CDI by a Contextual under the covers) in some handwavy unspecified fashion that returns Gorp, and so CDI in the abstract is able to at least conceptually connect the two—i.e. typesafe resolution succeeds.

While talking about typesafe resolution, we’ve been talking about consumers and producers (Contextuals), but we’ve quietly tabled any mention of Contexts.  Let’s bring them back into the conversation.

Recall that a Context is responsible for fronting a producer (a Contextual), and for deciding when and for how long to cache its results, and that it is a Context implementation that ultimately supplies dependencies, calling upon the services of a Contextual implementation when required.

Graphically, our little case might look like this, using UML notation:

Here, I’ve colored the CDI internal interfaces gray, our application classes (Backpack and Gorp) cyan, and then have highlighted in pink and red respectively a hypothetical Context implementation and a hypothetical Contextual implementation.  I’ve also used «stereotypes» to help with keeping the terminology straight.  Once again I’m going to have to use curly braces in my text below instead of angle brackets thanks to the WordPress editor’s many flaws.

You can see that in general a Context uses a variety of Contextual implementations to serve dependencies.

You can also see that in this case there is a Some Context Implementation? that fronts a Some Contextual{Gorp} Implementation? that is the ultimate producer of Gorp instances.

The Context implementation is going to have rules in it about when to return the same Gorp instance and when to create a new one.

The Contextual{Gorp} implementation is the producer and is going to be concerned with how to make a Gorp instance.

These classes are components in the same way that our Backpack and Gorp classes are components.  There can be many Context implementations in the system, and there can be many Contextual implementations in the system, all supplying different types, and all blissfully unaware of who might be asking for those types.  Further, a Contextual doesn’t know what Contexts might be using it, and a Context doesn’t know what Contextuals there are in the world.

So how does CDI figure out which Context implementation to pick to serve up Backpack‘s Gorp dependency?  And, even if it somehow magically does that, how does it then also figure out that the Context in question should use a particular Contextual to “back” it?

You can see, I hope, that there must be some kind of a mechanism available to let CDI know at the very least how a Contextual implementation might be linked with a Context implementation.  That hinting mechanism is a CDI construct called a scope.

Scopes

If a Context implementation is where contextual instances used by consumers come from, then a scope is a construct that indicates to CDI that this Contextual over here “goes with” that Context over there.

That is, in a very abstract sense—and we’ll get concrete soon enough—you mark a Contextual in some way that lets CDI see from that marking that the Contextual “belongs” to a certain Context implementation.

So if there is a Context in the world in some kind of handwavy unspecified fashion, and it can somehow identify itself to CDI as a producer of singletons (let’s say), and you have a Contextual implementation whose returned objects you want to be singletons, then you brand your Contextual in a particular way that identifies it as belonging to the singleton Context implementation.

The shape that this mechanism actually takes in CDI is very simple.  A scope is a particular kind of annotation class.  (Scopes happen to be any annotation classes that are themselves annotated with either javax.inject.Scope or javax.enterprise.context.NormalScope, but for this discussion we don’t really care about that for the moment.)

Let’s keep rolling with our singleton Gorp case.

When we introduced Contexts, we focused exclusively on the get methods.  But there is another interesting method on Context.  It is getScope.

That method returns an annotation class that basically ends up labelling the Context implementation.  The Context can now be matched or looked up under this annotation class label.

So, for example, CDI happens to ship with a built-in Context whose getScope method returns javax.inject.Singleton.class.

On the “other side”, it turns out you can mark certain Contextual implementations with that same annotation.  We’ll see exactly what shape this takes a little later; for now just know you can do it.

So if our Contextual{Gorp} implementation is somehow annotated with javax.inject.Singleton, then CDI now has what it needs: it can find the Context implementation indexed under Singleton.class, and “link” it with the Contextual{Gorp} implementation annotated with that annotation.

Then, assuming that typesafe resolution has succeeded, as it would in our trivial example, CDI now knows that it can complete the wiring automatically: our Backpack class will make an implicit request of CDI’s built-in-Context-implementation-associated-with-Singleton.class, and that Context implementation will use the Contextual{Gorp} that was annotated in some handwavy way with @Singleton.  The circuit is complete.

Our Backpack can now take delivery of a Gorp and anyone else who asks for a Gorp will get back the very same Gorp instance, not a new one.

Enough Handwaving

We’ve done a lot of handwaving to get to this point.

• We’ve handwaved over what Contextual implementations can look like.
• We’ve handwaved over how CDI figures out what producers and consumers exist in its world.
• We’ve handwaved over how CDI figures out what Contexts exist in its world.
• We’ve handwaved over exactly when CDI performs all this discovery.

We’ve probably also handwaved over a lot of other stuff.

At least some of the handwaving will start to end in the next post!

A CDI Primer: Part 1

In the previous article, we dabbled briefly in looking at the surface of the iceberg that is the CDI machine for making @Inject work as a way of answering some basic questions about what, exactly, CDI does and why you might want to use it.

We also, much more importantly, looked into the dependency injection mindset.  We talked about abstract notions of producers and consumers and wiring them together.  We introduced the idea that if you look through the right lenses, fields, methods and constructors can all be producers housed in particular producer classes.  And finally we pointed out that producers can be consumers and vice versa.

Now let’s talk about lifecycles.

Object Lifecycles and “Producer Proxies”

When a producer of any kind “wants” to make or supply or acquire an object, two decisions have to be made:

1. how to make or supply or acquire the object
2. when to make or supply or acquire the object regardless of how that happens

Some producers, as we saw in the previous article, are, as often found in the trenches of enterprise Java development, what I’ll call singleton suppliers.  They acquire the (mostly!) One True Instance™ of the object in question somehow, sometimes creating it once if necessary, sometimes by interrogating some ancient snarling hairball of a legacy system, and then from that time forward in the whole life of the application, that’s the object you get if you ask them to supply it to you.

Other producers, like constructors, create a new object each time one is to be produced because they can’t do anything else, or they’re kind of uninterested in the ways that they might be called, so they shrug and say, hey, if you want a new object, call me; otherwise, don’t; I don’t store or cache nothin’.

What’s interesting about producers of any kind, in isolation, without any other technologies such as CDI or its subsystems in play, is: producers in isolation combine how an object is produced with when it is produced.

For example, what I’ll call singleton suppliers—those all-too-common “enterprisey” methods that somehow acquire a Singleton From Elsewhere™ and then return it when asked—are combining the mechanics of how the singleton is produced (maybe it’s looked up from some other system) with when it is produced (maybe this system lookup only happens once and then the result is stored as a static singleton).

Or constructors: if you acquire an object from a constructor—a kind of producer, remember—then no matter what you do and no matter what it does you’ll get a new instance of the produced object each time because that’s what constructors do.

What would be nice is to let producers do what they do—acquire or make things when called for—and have there be some other subsystem that controls when a produced object is handed to a consumer.  Something that can go “back to the well”—the producer “well”—when needed, but not when not needed, and is in full control of when that happens, but does not itself know how the manufactured items it is storing or caching are made.  Something that is kind of like a proxy for producers: something that can stand in front of them and hand out their results when appropriate, regardless of how they were made or from what system they were acquired, according to its own notions of lifecycle.

In such a situation a producer can focus on how to acquire an object but not on how to cache it; a producer proxy can focus on when to cache an object, if at all, and when to clear the cache; a consumer, in grand dependency injection mindset fashion, can remain blissfully ignorant of both of these things.

Also in grand dependency injection mindset fashion, we want this producer proxy (my term, incidentally, not CDI’s) to not look up or acquire or otherwise scrounge around for its relevant producer(s).  We want it to simply declare somehow that it needs one, and then punt the problem of getting one to its caller (we’ll talk about who that might be in a moment).

CDI implements this producer proxy concept with a construct called a Context and it is the first CDI construct we’ll look at in depth.

Contexts…

The first thing to know about a Context is that as a CDI end user you’ll interact with it many, many times—and as a consumer you’ll never see it or know that’s what you’re doing.

A Context, in other words, is part of the internal CDI plumbing by which automatic wiring between producers and consumers is implemented.

A Context is the nexus where a consumer needing an object of a certain kind is wired in an abstract fashion to a producer that is capable of producing objects of that kind, and where the lifecycle of such a produced object is managed.

Inside the depths of CDI, when you mark a field or a parameter with @Inject, CDI asks a particular Context for the kind of object you want.  That Context, in turn, ends up asking a producer, when necessary, to make or acquire the kind of object that should go in your @Inject-annotated slot.

From the standpoint of a Context, a producer is represented by something kind of odd called a Contextual.  A Contextual is simply a producer that can also destroy the things it makes.  A Contextual can make any number of different things of a given type (so, for example, a Contextual whose type parameter is Object could make Gorp, Chocolate, PeanutButter or whatever).  Most of the time, though, a given Contextual makes one kind of thing.

Finally, a Contextual should not have, as its core concern, or any concern if at all possible, how long an object should live—it is a “pure” producer: it just makes ’em, ma’am, it doesn’t hang onto ’em.

Here is what the contents of the Contextual interface look like, in their entirety, and for now we can ignore the second of these two methods:

I hope you can see how simple that is.

Contextual is another one of those interfaces that is in the internals of CDI.  You rarely, if ever, implement it directly.  But you could.  And you do in some cases, usually indirectly, as we’ll see much later.

For example, ignoring CreationalContext—a subject for a later post—you could see that you might implement the create method in such a way that it wraps a constructor invocation (you’d be implementing a producer that is constructor-based).  Or you could see that you could implement the create method in such a way that it wraps a method invocation (you’d be implementing a producer that is method-based), though consuming other dependencies in this case might be a little trickier.  Or a field access.  And in many cases your destroy implementation might not have to do anything.

The takeaway here is that you can represent all producers as Contextuals of a particular kind.

Context, then, uses Contextuals to produce the objects it will then manage the lifecycle of.  Here are the (relevant at the moment) contents of this interface, and trust me when I tell you that for now we can ignore the second method:

Again, very simple.

The first method is the real workhorse.  It takes in a Contextual and a CreationalContext, as you can see.  Once again, we’ll ignore the CreationalContext.  (The second method is for certain cases where CDI wants to ensure that no creation at all happens: it just wants the Context to supply a cached instance if one exists; it doesn’t want the Context to make a new one.  We’ll ignore it for the sake of mental clarity.)

The first method’s contract is to acquire and return a T.  You’ll note that Context itself is not a parameterized type (it doesn’t have any angle brackets or type parameters in its name).  So you can see here that a Context can get a whole variety of different kinds of objects.

You can also probably squint and see that if I tell you (as I have) that a Context‘s responsibility is to manage the lifecycle of objects, not actually make them, then when it decides that it needs a new one it can (and should) just call the create method on the Contextual that has just been handed to it.  The Context knows “when”; the Contextual knows “how”.

If it already has an existing instance and has determined that this incoming demand can be satisfied by the existing instance, well, then it can just hand it back.

That’s all very convenient.  So a Context as a consumer remains blissfully ignorant of what kind of Contextual (producer) has been handed to it, and can use this raw material if it wants in order to fulfill its contract of supplying T instances.  And the Contextual can remain blissfully ignorant of lifecycle and caching concerns and can just return Its Thing™, whatever that might be, when asked to make it.

…and Dependency Injection

CDI stands for Contexts and Dependency Injection.  And now with the introduction of Contexts we have an incomplete and blurry view—but a view nonetheless—of how the major parts work together, and why “Contexts” is important enough to be listed in the title of the specification:

• A consumer of some kind (your business-critical class) gets wired in some currently opaque-to-us way (involving @Inject) to a Context implementation that supplies it with the dependency it needs (via the Context#get(Contextual, CreationalContext) method).
• The Context implementation gets wired in some opaque way to a Contextual implementation that knows how, but not necessarily when, to make those kinds of things.
• A Contextual is a kind of producer but everybody but the Contextual implementation itself doesn’t know what kind.

The result is that CDI is now conceptually capable of injecting dependencies, taking into account desired lifecycles, and letting producers and consumers and producer proxies all focus on what they do best, and on nothing else.

Contextual Instances

I’ve spoken very loosely about producers making things of a particular kind.  And I’ve spoken equally loosely about consumers needing things of a particular kind.  And I’ve spoken just as loosely about the wiring process where a producer of a thing of a particular kind gets wired in some fashion to a consumer that needs those things, mediated by a producer proxy—a neutral term I invented to describe the lifecycle/lifespan-managing component that decouples when something is handed out from how it is made or acquired.

Now we’ve also learned that producers in CDI are represented by Contextuals and are effectively “fronted” by Contexts, and that producer proxies are represented by Contexts, and that Contexts therefore are the sources of instances that producers—Contextuals—make.  Consequently when a Context‘s get method hands you (indirectly) an object, that object is known throughout CDI’s literature as a contextual instance.  It is an instance of something that a given Context manages.

Still speaking loosely, when you ask for a Gorp to be supplied to you (injected) by CDI by using the @Inject annotation, you’re going to get a contextual instance of Gorp in the annotated “slot”.

Or, equivalently: if an object “comes out of” a Context, then it is a contextual instance, and its existence must be owed to the fact that CDI invoked get on a Context and the Context ultimately invoked the create method of a Contextual that produced it.  CDI “knows about” all contextual instances.  CDI does not know about (for the most part) objects that are not contextual instances.

In the next post, we’ll look at the mechanics of how CDI wires Contextual implementations that can make certain contextual instances of particular kinds to Context implementations that implement a lifecycle, and how CDI wires consumers of contextual instances to Context instances that can provide them.

A CDI Primer: Part 0

So many tutorials about CDI have been written I’m a little nervous putting down my own.  But here we are.

I believe that most of the CDI articles and posts I’ve read over my many, many years of programming don’t follow the right road for developers just starting out with CDI.  As a result, people think of CDI as magic.  Because its terminology is also unusual, misconceptions get built upon at the earliest stages of learning and you end up with developers sticking beans.xml files everywhere in a prayer to the gods to get their stuff to somehow work.

I also want to try to get the high level concepts in place first before diving deeper.  As a result, I’m going to speak a bit fast and loose here to start with.  My hope is that over time these foundations will demystify the great CDI machine.

Lastly, I’m primarily focusing on CDI alone, i.e. not on any aspect of its integrations with technologies like Java EE.

Let’s dive in.  We’ll start with a section that deals with CDI and @Inject, since that’s how most people first encounter CDI, but then we’ll move rapidly on to the dependency injection mindset, which is much more important.

CDI Makes @Inject Work

For anyone wondering “what is CDI? Why would I use it?” the quickest answer that makes immediate sense is:

CDI is the magic machine that lets you use @javax.inject.Inject.

OK, so why would I use @Inject?  What does it do for me?

Field Injection

Let’s say you have an instance field in your class, and you want it magically set to something, regardless of whether it’s public, protected, package-protected or private.

Do this:

@Inject // magic!
private Gorp myGorp;

CDI makes that work.

That is, some Gorp instance (we’ll talk about which one, and where it came from, in a bit) will get put there by CDI.  Cool!

Think a bit about this: you didn’t have to go hunting around for a Gorp instance yourself.  You didn’t have to look up what kind of Gorp to make from a properties file or JNDI or ServiceLocator or anything like that.  You asked for a Gorp, and a Gorp was delivered unto you from outer space.  Nice.  Simple.  Less of your code; therefore fewer bugs that will be assigned to you.  A smaller mental model: fewer second- or third-order concepts in your head means more clarity in programming the important stuff you need to do.

Injection is the overall term for this kind of magic: something comes along (CDI in this case) and injects a Gorp into, in this case, an instance field of your (business-critical, of course) class.  The thing that is being injected is a dependency: it’s something you need for some reason, so therefore whether you like it or not you depend on it.

So when you get a dependency injected into something, you have dependency injection.

We’ll call this particular case of injection field injection.

Where else can you use @Inject?

Method Parameter Injection

When CDI is in the world, you can also use @Inject on methods.  It’s the same kind of thing.  If you do this:

@Inject
private void consume(final Gorp gorp) {
  // nom nom
}

…the gorp “slot” will be filled with a Gorp instance (as before, we’ll talk about which one, and where it came from, and when in a bit) by CDI.  This is often referred to as setter injection, or setter method injection, or parameter injection, and you might think your method therefore has to be named something like setGorp, but it can be named anything.  The important part is that @Inject “goes on” the method.

Methods with @Inject “on” them can have as many parameters as you want.  CDI will try to “fill” all of them.  So if you do this:

@Inject
private void consume(final Gorp gorp, final Cheese cheese) {
  // nom nom nom nom
}

…CDI will “fill” the gorp “slot” with a Gorp instance, and the cheese “slot” with a Cheese instance.

Constructor Parameter Injection

CDI also makes @Inject on constructors work.  Constructors can be public, protected, package-private or private.  Just as with methods, @Inject-annotated constructors’ parameter “slots” will be “filled” by CDI.  So if you do this:

@Inject
private Chocolate(final PeanutButter peanutButter) {
  super();
}

…the peanutButter “slot” will be filled by CDI with a PeanutButter instance.

Making @Inject Work Is a Kind of Dependency Injection

This style of programming is lumped under the term dependency injection.  The idea is that you, the programmer, never look up or make or seek or acquire what you need (your dependencies).  Instead you “take in” what you need.

You force your caller to hand you your raw materials instead of hounding off and scavenging them yourself.  Always be lazy!

So if you’re writing a Chocolate, and you need a PeanutButter, you do not do this:

// Here is an example of a class that is *not* using
// dependency injection.  It is brittle and hard to test.
public class Chocolate {

  private final PeanutButter peanutButter;

  // Note that the constructor doesn't "take in" anything.
  // Yet the peanutButter field still needs to be "filled".
  // I wonder how that will happen?
  public Chocolate() {
    super();
    // You've seen this kind of thing in your job before.
    // There's the magic "look up the thing" method.
    // My experience has been that LDAP is usually involved. 😃
    this.peanutButter = lookupPeanutButter();
  }

  // Here is the magic "look up the thing" method.
  private PeanutButter lookupPeanutButter() {
    // Almost always there's LDAP or a singleton being used. 😞
    final GroceryStore singleton = GroceryStore.instance();
    // When this lookup breaks, was it because the GroceryStore
    // couldn't be found? or the PeanutButter? You will see
    // anti-patterns like this throughout enterprise Java
    // programming.
    return (PeanutButter) singleton.get("Peanut Butter");
  }

}

In the class above, really what you need is a PeanutButter.  It doesn’t really matter where it came from, just that you “take it in”.  So whether or not you’re ever going to use CDI or Spring or anything else, please write your class like this instead:

public class Chocolate {

  private final PeanutButter peanutButter;

  public Chocolate(final PeanutButter peanutButter) {
    super();
    this.peanutButter = peanutButter;
  }

}

What’s nice is that your class has now punted the problem of how to acquire the PeanutButter to the caller.  Now the caller has to figure that out.  Your Chocolate class is much simpler and easier to deal with.  As someone experiencing the glories of your world-changing code for the first time, I can understand it better and marvel more at your brilliance.

If, on top of this well-designed class, you now put @Inject in the right place, then CDI’s magic can supply—inject—the PeanutButter.  That is, CDI becomes the caller:

public class Chocolate {

  private final PeanutButter peanutButter;

  // Let's use constructor parameter injection
  @Inject
  public Chocolate(final PeanutButter peanutButter) {
    super();
    this.peanutButter = peanutButter;
  }

}

The Dependency Injection Mindset

Now kindly forget CDI for a moment (and Spring if you’re coming from that background).

What is really important here is the mindset.

That mindset is: in any class you’re writing, take in only what you need to get your job done.  Pare it down more and more and more until you truly have the object you need.  Always be lazy; make your caller do the work of finding your dependencies!

Try if you can to pass them in in the constructor of your class and set them in private final instance fields.  Immutability is good!

The more you relentlessly and recursively pursue this mindset, the simpler your classes will be and the more clear the dependencies between them will be.

The fact that some of them might be “injected” by some kind of magic machine like CDI is utterly immaterial to your class design.  The dependency injection mindset is much more about the “dependency” part and much less about the “injection” part.

If there’s one thing you take away from this series of articles, let it be that programming using the dependency injection mindset—even if you never use a dependency injection framework like CDI (or Spring, or Jersey’s HK2)—is its own goodness.

Consumption

Within the dependency injection mindset, there are consumers and producers.

Consumers are like the Chocolate class above: they “take in” stuff, do their work, and are done.  A good consumer declares dependencies on exactly what it needs and doesn’t worry about how that stuff gets made or supplied or looked up or acquired.  In CDI, using @Inject at some location indicates that you’re doing consumer work there.

Consumption is the heart of the dependency injection mindset.

Production

Up to this point we’ve been focused on not worrying about where, for example, instances of PeanutButter come from or who makes them or how many little subassemblies go into ultimately manufacturing one.  All of these concerns are part of production.

For this article, a producer is something whose primary job is “handing out” an instance of something.  Sometimes “handing out” means “creating”, and sometimes it means acquiring or looking up.

Sometimes a producer “knows” it should hand out the same thing over and over again.  If you’ve programmed in Java for any length of time, you’ve run into someone somewhere who uses singletons and methods to hand them out.  These methods that return singletons are doing production work—they’re producers.

If you squint right, and look at things a certain way, another kind of producer that hands out the same thing over and over again is a field!  So looked at under the right lights, a field can be a producer.

Other times a producer “knows” it should hand out a new thing whenever called for.  Again, if you’ve been in the Java enterprise world for a while you’ve seen various Factory-suffixed classes.  Typically they have methods that start with create or make or get and they create or make something (often times a thing whose class is named the same thing as the factory class, minus the Factory suffix) and return it whenever they’re invoked.  These methods too are producers.

These kind of method-based producers obviously live “inside” classes (they’re methods, after all).  The things they make may or may not be instances of the classes the producers live inside.  For example, a PeanutButterFactory class may contain an acquirePeanutButter method that returns a PeanutButter instance.  Note that the class that houses the PeanutButter producer—PeanutButterFactory—in this case is not the same as the class of the return type of the method—PeanutButter.

Just so we can talk about things later let’s call the “housing” of a producer (whether it’s a field or a method) a producer class.  As we’ve seen above, in general—but with one notable exception described immediately below—the class of the thing being made (the field’s type, or the method’s return type) need not be the same as the producer class housing the producer (the field or the method) that makes the thing.

Finally, there are producers all over the place in plain sight that you may not think of.  They create new things every time when called for.  They’re called constructors!  Constructors have an interesting property, which is that they must be housed in the class that is the class of the instances they make.  So, for example, a PeanutButter constructor makes PeanutButter instances and can’t make anything else.

Another way to put this is that in the case of constructors, the producer class’ producer (the constructor) makes instances of the producer class itself.

So fields, methods and constructors are all producers if you look at them as sources of objects that someone might need.

Production and Consumption

Oftentimes, a method or constructor that is making or getting things to hand to a caller will need other raw materials to get the job done.  Maybe, as in our examples earlier, a producer of PeanutButter instances needs to get them from a GroceryStore.

Following the dependency injection mindset, there’s nothing to prevent a producer from also being a consumer!  That is, a method that for various business-related reasons returns or creates a PeanutButter instance from a GroceryStory shouldn’t look up a GroceryStore instance, or set about some other means of creating a GroceryStore, it should simply declare that it needs one.

Here’s what a PeanutButter-returning producer (method) might look like when it’s designed from within the dependency injection mindset.  Note that there’s no GroceryStore acquisition going on (no singletons, no LDAP, no database servers, no configuration subsystem):

public PeanutButter acquirePeanutButter(final GroceryStore store) {
  return store.get("Peanut butter");
}

Note that this method is a producer when we’re looking at it as a source of PeanutButter instances, and a consumer when we’re looking at it as something that needs a GroceryStore to do its job.

Wiring It Up

Suppose now we’ve written several classes using our dependency injection mindset.

So in our left hand we have consumers that need things to do their job.  In our right hand we have producers that make things should they ever be needed by someone (and may also consume things as part of that production process).

We can tell just by surveying the landscape that that method over there that returns PeanutButter instances—a PeanutButter producer—”goes with” this consumer over here, Chocolate, whose constructor needs PeanutButter instances.

Again, just by looking at things, we can see that if we wanted to ever instantiate a Chocolate for any reason, we’re first going to need a PeanutButter.

To get a PeanutButter, we’re going to have to call that PeanutButter-returning method.

To call that PeanutButter-returning method, we’re going to have to create an instance of the class it “lives” in, then…oops, we’re going to need a GroceryStore because—remember? see the examples above—the PeanutButter-returning method needs a GroceryStore to do its job.  So we’ll need to recursively go through this effort with GroceryStore—maybe it in turn is produced by a producer, or maybe we can just call its constructor.

This process of figuring out these relationships and instantiating the right things in the right order in order to come up with other things is known generically and colloquially as wiring.  You can do it by hand.  It’s not magic.

Wiring By Hand

For example, at the initialization of our program somewhere we could do something like this (this example deliberately has a few problems):

final GroceryStore groceryStore = new GroceryStore();
groceryStore.put("Peanut butter", new AdamsChunky());
final PeanutButterFactory factory = new PeanutButterFactory();
final PeanutButter peanutButter = factory.acquirePeanutButter(groceryStore);
final Chocolate c = new Chocolate(peanutButter);

This is an example of (deliberately slightly bad, but not awful) wiring by hand, but it shows wiring nonetheless.

We’ve made many choices here.  Some are obvious; some, when generalized into your enterprise project of choice beyond this stupid example—swap in your favorite system you love to hate in place of GroceryStore, for example—are perhaps not so easy to see:

• We’ve chosen the kind of GroceryStore.
• We’ve chosen the kind of PeanutButter.
• We’ve explicitly said that our PeanutButter instance, regardless of what choice we made a line above, is going to come out of a GroceryStore.
• We’ve also said that PeanutButter instances can be acquired from a factory method.  (Hmm; can that method be subclassed?  Are there now two “sources of truth” or more for PeanutButter instances?)
• We’ve implied that PeanutButter instances are (effectively) singletons.  Maybe we didn’t mean to do this.  Maybe this matters; maybe not.

So we’ve deferred certain choices—a Chocolate takes in a PeanutButter, but isn’t choosy about what kind, or where it came from; a GroceryStore presumably allows you to put any kind of PeanutButter you like; we’ve abstracted the production of PeanutButter behind a black-box method (acquirePeanutButter)—which is nice.  But it is important to note that we’ve wired in many other hardcoded choices above.

Many enterprise projects will have something like this, and a well-meaning developer will say, ah, hardcoding is bad; let’s allow someone to configure the kind of PeanutButter to use so it isn’t always AdamsChunky.  So they introduce a configuration file or mechanism that looks up the kind of PeanutButter to use—and now we’re out of the dependency injection mindset.  Oops!

That is: there will now be code in this initialization sequence that requires a certain configuration mechanism to look up the precise type of PeanutButter required.  Then someone will come along and try to abstract that configuration mechanism.  These are instances of slightly buried service locator patterns applied intentionally and unintentionally in the initialization code—and then suddenly it turns out that for reasons no one is entirely sure of you have to have an LDAP server or database running in order to test a Chocolate instance.  Ugh!  What happened to our “just declare the thing you need”?

And where does CDI come in?

Automatic Wiring

CDI is that well-meaning developer, and the author of the initialization code above, but way better: it does the wiring correctly, automatically and well without interfering with the dependency injection mindset.  As you can probably see by now, that initialization code is the process of matching producers with consumers, and that is exactly what (this area of) CDI does.  It has been doing this work correctly and well for many, many years.

Armed with this foundation (the dependency injection mindset, seeing the world in terms of producers and consumers and a middle-player that wires them together properly and efficiently), we can move on in the next post to how CDI does this.

microBean™ MicroProfile Config 1.3 Implementation

I put together an Apache-2.0-licensed MicroProfile Config 1.3 implementation that passes the MicroProfile Config version 1.3 TCK.  I hope you find it interesting!

Understanding Kubernetes’ tools/cache package: part 11—Towards a Kubernetes controller CDI 2.0 portable extension

In part 10, we laid out what we need to do to make a simple programming model available to an end user who wants to be notified of Kubernetes events in the same style as Go programmers using the tools/cache package.  This series starts with part 0.

Here we’ll look at implementing a CDI 2.0 portable extension that enables this lean programming model.

From part 10, we sketched out the idea of pairing an observer method with a producer method, using the same qualifiers on both the producer method’s return type and on the observer method’s event type.  Linked in this way, you now have the ability to build boilerplate machinery in between the Listable-and-VersionWatchable made by the producer method and the event observed by the observer method, and the end user doesn’t have to know about or invoke any of it: her events “just work” assuming this extension is present, opaquely, at runtime.

This post will make use of the microbean-kubernetes-controller framework, the Java Kubernetes controller framework built up over the course of this series (you can start at the beginning if you like).  This framework is CDI-independent.  We’ll adapt it to CDI 2.0 so end users don’t have to deal with any boilerplate.

As discussed, our portable extension will have to:

• find beans that have Listable and VersionWatchable among their bean types
• find observer methods observing Event objects that contain Kubernetes resources in them
• ensure that for any given observer method whose event parameter is qualified with a set of qualifier annotations, there exists a producer method (or any other kind of CDI bean, actually) with the right kind of type that is also qualified by those same qualifier annotations (or no event delivery will take place)
• have some way of recognizing that arbitrary qualifier annotations defined by the user are those that should be used to identify Kubernetes events—i.e. some way of meta-qualifying a qualifier annotation that appears on relevant producer methods and relevant event parameters

We can do all these things thanks to the well-defined lifecycle mandated by CDI.

First, we’ll sketch out a meta-qualifier annotation named KubernetesEventSelector.  The intent of this meta-annotation will be that if you put it on a qualifier annotation that you create, then your qualifier annotation will be treated as a qualifier that is trying to say something specifically about sets of Kubernetes events.

Here’s what that might look like:

Now as an end user if I define my own qualifier annotation and annotate it with KubernetesEventSelector:

…I will have expressed my intent that when we “see” this annotation:

@AllConfigMapEvents

…we are talking about choosing Kubernetes events in some handwavy manner, and not something else.

So now our as-yet-to-be-written portable extension has at least the theoretical means to find event parameters and beans and see if they’re qualified with qualifiers that, in turn, are annotated with @KubernetesEventSelector.  Those will be the only things of interest to this extension.

Next, we’ll take advantage of the CDI lifecycle and the prescribed order of things and recognize that bean processing happens before observer method processing.  So let’s start with looking for those beans that have Listable and VersionWatchable among their bean types.

We’re going to run into a problem right away.  We would like to look for beans whose bean types are of type X where X is some type that extends Listable and VersionWatchable, but otherwise we don’t really care what X actually is.  But producer methods must return concrete types without type variables in them.

What we’ll do instead is look for the most general type in the fabric8 Kubernetes model hierarchy that implements or extends both Listable and VersionWatchable and deal with that.  That type happens to be Operation.  We’ll keep track during bean processing of all Beans that match these types.  That means it doesn’t matter if the bean in question is a producer method, a producer field, a managed bean, a synthetic bean or any of the other kinds of beans you can cause to come into existence in a CDI world: they’ll all be accounted for.

Now, obviously we’re not actually interested in all beans whose bean types include Operation.  We’re interested in those that have been explicitly “tagged” with the KubernetesEventSelector annotation.

It would be nice if there were a convenience method of sorts in CDI that would let you ask a bean for its qualifiers but would restrict the returned set to only those qualifiers that, in turn, are meta-qualified with something else (like KubernetesEventSelector).  Unfortunately, there is not, so we’ll have to do this ourselves.

So, refined: we’ll keep track of Beans with Operation (and hence by definition Listable and VersionWatchable) among their bean types, and with KubernetesEventSelector-qualified qualifiers.  We’ll keep track of those annotations, too.

Once we do this, we’ll have some machinery that can now pick out sources for raw materials that we’ll need to feed to a Reflector.

But obviously we don’t really want to do any of this if there aren’t any observer methods around.  Fortunately but also unfortunately, bean processing happens before observer method processing, so we will do this work, and then discard it if we don’t find any relevant observer methods.

What’s a relevant observer method?  In this case it’s an observer method whose (a) AbstractEvent-typed event parameter is (b) qualified by one or more qualifier annotations that are themselves (c) meta-qualified by KubernetesEventSelector, and that (d) “matches” an equivalent set of qualifiers on an Operation-typed bean type.  This means that indirectly the observer method will “watch” for what the producer method is indirectly providing access to.

Here’s an example observer method:

Note the usage of the @AllConfigMapEvents qualifier we defined earlier in this blog post, and note that the event parameter so qualified is an Event.  Let’s say we found a “matching” producer method:

Note the Operation return type and the matching qualifier-meta-qualified-with-KubernetesEventSelector that decorates it (@AllConfigMapEvents).  Do you see how it “matches” the observer method’s event parameter qualifier (also @AllConfigMapEvents)?  This is the linkage that connects this producer method with the observer method that observes events that will result from the producer method’s existence.

So once we have a mapping from a Bean to a set of relevant qualifier annotations, then we can see if, during observer method processing, we’re talking about the first observer method that should cause our boilerplate machinery to get invoked.  If there are many observer methods that “match” a relevant producer method, that’s fine; that just indicates that the very same Kubernetes event might be processed by many observers.  The point is, before we jump through all the hoops to set up lists and watches and so on, we should make sure that someone is actually going to take advantage of our work.

So once we “get a match”, we can build the boilerplate for all matches of the same type, once.

For each distinct match, we’ll need a new Controller.  The controller will need an instance of whatever the producer method is making (some kind of Operation, which is by definition both a Listable and a VersionWatchable).

The Controller, in turn, will need some kind of Map representing Kubernetes objects we “know about”.  That Map will be empty to start with, since we don’t know about any Kubernetes objects yet.  But if, down the road, a deletion gets skipped (maybe due to a watch timing out or a disconnect), we need to retroactively fire a delete if, say, the Kubernetes list of relevant objects is “less than” our “known objects”, and we’ll need to know what object was actually deleted.

The Controller will also need some kind of Consumer (a siphon) that will slurp up EventQueues and dispatch their events in order without blocking threads.  That Consumer will also need to update that very same Map of “known objects” as it does so.

Finally, that Consumer of EventQueues will also need a mechanism to link it to the native CDI event broadcast mechanism which will take care of actually dispatching events to observer methods.

Whew!  Let’s do the easy boring stuff first.

The first lifecycle event that looks good is ProcessBean.  If we could process all beans whose types are Operation here, in one place, regardless of whether the bean in question is a producer method, managed bean, etc. that would be great.  As it turns out for various obscure reasons, we can’t.  So we’ll implement a lifecycle event observer method for each type of bean, and route all their stuff to a common private method for processing:

And the processPotentialEventSelectorBean method that these all effectively delegate to might look like this:

…where the Annotations utility method can be found elsewhere, and where the getOperationType() method might look like this:

So at the end of all this we’ll have a Map, eventSelectorBeans, that has as its keys Sets of Annotation instances that have KubernetesEventSelector somewhere “on” them, and has as its values Beans that are qualified with those annotations.

Now we’ll need to route all observer method processing to something similar (fortunately, this is a great deal simpler).  Recall that we are guaranteed by contract that observer method processing happens after discovering beans, so by this point we already have knowledge of any producer methods or managed beans “making” Operation instances of various kinds:

(Above, we also keep track of whether the observer method in question is synchronous or asynchronous.)

Finally, we can clean up a little bit after bean discovery is all done:

At the end of all of this bean discovery, we have a Set of Bean instances stored in a beans instance variable that (a) “make” Operation instances, (b) are appropriately meta-qualified to declare their interest in taking part in Kubernetes event production, and (c) have at least one observer method interested in their effects.

Let’s build some controllers and start them when the user’s program comes up!

We’ll begin by observing the initialization of the application scope, which is exactly equal to the start of a CDI application.

When this happens, our beans instance variable will contain some of the materials to build a Controller.  For each Bean in there, we’ll “instantiate” it (by way of a beanManager.getReference() call, create a new Controller, hook that Controller up to the right kind of EventDistributor, start the Controller and keep track of it for later cleanup:

In the above code example, you’ll see a reference to a CDIEventDistributor.  That private class is a Consumer of events that simply fires them using the existing CDI broadcasting mechanism:

Finally, when the user’s application stops, we should clean up after ourselves.  We observe the imminent destruction of the application scope and close everything we started up:

The net effect is that if you put this portable extension and its dependencies on the classpath of your CDI 2.0 application and author a producer method and observer method pair (and nothing else), your CDI application will receive Kubernetes events and should behave semantically like any other kind of Kubernetes controller.

The fledgling project housing all this code is microbean-kubernetes-controller-cdi and is available on Github under the Apache 2.0 license.

Understanding Kubernetes’ tools/cache package: part 10—Designing Kubernetes controllers in CDI 2.0

In part 9 of this series (you may want to start at the beginning), we put together a sketch of what has become a Kubernetes controller framework in Java.  The framework represents most of the concerns of a subset of the Kubernetes tools/cache package, including the SharedIndexInformer, Reflector, Controller, Indexer, DeltaFIFO, Store and ListerWatcher concepts.

But if you want to write a controller, you don’t (I’m presuming) want to deal with any of that boilerplate.  You want to express that you:

• are interested in receiving notifications of additions, modifications and deletions of certain Kubernetes resources
• know what to do when you receive such notifications

The other stuff—all the reflectors and controllers and informers and caches and whatnot—is simply a means to an end, so we should attempt to make it disappear.

CDI 2.0 gives us the means to do this.  Let’s lay out what we’ll need to do.  We’ll work backwards.

First, we’ll make use of the standard observer method mechanism to know what to do when we receive event notifications.  We’ll sketch our as-of-now incomplete observer method like this:

private final void onConfigMapEvent(@Observes final SomeKindOfEventNotYetDefined configMapEvent) {
  // configMapEvent should tell us: was it an addition? a modification? a removal?
  // Which ConfigMap?  What did it look like before it was modified? etc.
}

Let’s pretend that something somewhere is firing these events.  Then we could receive one here, open it up, and see what happened.  Sounds good.

Missing from our sketch is some indication as to which ConfigMaps we’d like to see events for.  Maybe we want to see all of them.  Maybe we only are interested in some meeting certain criteria.

Well, that’s what qualifiers are made for.  We’ll refine our hazy little sketch to look like this:

private final void onConfigMapEvent(@Observes @CertainConfigMaps final SomeKindOfEventNotYetDefined configMapEvent) {
  // configMapEvent should tell us: was it an addition? a modification? a removal?
  // Which ConfigMap?  What did it look like before it was modified? etc.
}

Note the addition of the @CertainConfigMaps qualifier annotation that I just made up.

OK, if we stare at that for a while as good CDI citizens, this looks nice and complete and idiomatic: this observer method looks for SomeKindOfEventNotYetDefined events, whatever they are, qualified with the @CertainConfigMaps qualifier and will be notified if ever they should be fired.  Presumably those events, whatever they are, will contain a ConfigMap or an old ConfigMap and a new one along with some indication of what happened to it or them.  Sounds good.  This is stuff the end user obviously has to write, and it’s stuff that she should write, and it’s probably about as concise as we’re going to get.  It’s nice and declarative and simple and straightforward.

So who’s going to fire them?  The person writing this method obviously shouldn’t have to care.

As we’ve seen in the previous parts of this series, if you look at things a certain way, Kubernetes itself is a distributed message bus.  So the short answer is: Kubernetes will fire them.

That’s glib, of course.  Kubernetes will fire them—and our Reflector will do what is necessary to reflect them speedily and robustly into an EventCache.  Then something else will have to harvest events from the cache.  That something had also better be able to distribute those events to interested listeners, like our observer method above.

Finally, all of this will have to have queues of various kinds in the mix to make sure that no given harvesting thread or distributing thread or caching thread is blocked while it goes about its business (or that if absolutely necessary it is blocked for the shortest possible time).  That, after all, is what the Kubernetes client-go tools/cache package is all about, so it’s what microbean-kubernetes-controller is all about.

OK, that’s all fine, but, if you notice, this subassembly—with Kubernetes and a Reflector at its “left” end and our observer method at its “right” end—starts with a specification of things to list and watch.  If we can provide just that part, thus defining the inputs for the “left” end, then all the other stuff in the middle is boilerplate, and all we have to do is attach our observer method to the “right” end with a little more boilerplate, and the end user might not ever even have to see the boilerplate!

So let’s look at the “left” end: we know we’re going to have to talk to Kubernetes using the fabric8 Kubernetes client, so that’s where we’ll start.

The good news about picking the fabric8 Kubernetes client is that it is built around a domain-specific language that makes expressing things relatively easy.  For example, you can tell a KubernetesClient to get you a Thing™ that can then get you a list of ConfigMap resources from Kubernetes like this:

client.configMaps();

That returns some sort of massively parameterized MixedOperation, but normally when you program against a model like this you worry very little about these intermediate types in the chain of builders and whatnot that result from this style of fluent programming.

However, in this case, do take note of the fact that a MixedOperation implements both Listable and VersionWatchable.  Note further that a MixedOperation is just a special kind of Operation.  Finally, recall that our Reflector needs some kind of thing that is both a Listable and a VersionWatchable to get started: in part 0, we learned about why this is.

So, in other words, you can create a new Reflector that will reflect Kubernetes events concerning ConfigMaps by supplying client.configMaps() as the first parameter of its constructor.

That’s our “left” end of this subassembly.  If you can get your hands on a Thing™ that is both a Listable and a VersionWatchable then you can create the whole rest of the subassembly and route reflected events to appropriate observer methods.

Now, in CDI, any time you need a Thing™, you don’t make it yourself.  You look around for it, or you declare that someone else needs to provide it.  We will treat, in other words, an Operation as a CDI bean.

An Operation implementation is extremely unlikely to be a managed bean—a plain-old-Java-object (POJO) just lying around somewhere with some bean-defining annotations on it.  Instead, as we’ve seen, you make an Operation by way of a method invocation on a KubernetesClient (like configMaps()).

CDI producer methods are one kind of CDI bean that fit this bill perfectly!  Suppose we have a producer method somewhere sketched out like this:

@Produces
@ApplicationScoped
@CertainConfigMaps
private static final Operation<ConfigMap, ConfigMapList, DoneableConfigMap, Resource<ConfigMap, DoneableConfigMap>> selectAllConfigMaps(final KubernetesClient client) {
return client.configMaps();
}

Then so long as someone somewhere has made a KubernetesClient for us, it will be injected as this producer method’s sole parameter.  That means we can use it to return an Operation.  That means we have the “left” end of our subassembly.

(As it happens, there’s a handy little project that does expose a KubernetesClient as a CDI bean; it’s named microbean-kubernetes-client-cdi.  If that’s on your CDI 2.0 classpath, you can inject KubernetesClient wherever you want it.)

Note as well here that the @CertainConfigMaps annotation that was part of our (still unfinished) observer method sketch is qualifying the return type.

From here, you can see, I hope, that if we have a machine that can

• gather up all the CDI beans that are qualified with a given qualifier (like @CertainConfigMaps) or set of qualifiers, regardless of how those beans are made or who makes them, and
• can also gather up all the observer methods that observe events qualified with that same qualifier or those same qualifiers, then
• we have the means to unite a producer of raw materials needed to pump Kubernetes events into the system, and a consumer of those events to get them out of the system!

We’ll build this machine in the next post.

 

Components and Environments

I am playing around with the concepts of components and environments in my microbean experiments.

The fundamental idea behind microbean is that with CDI 2.0 every last piece of your application can be its own self-contained artifact (including the main class with its main() method).  Each such artifact is a CDI bean archive.  When you put them all together on the classpath and run java org.microbean.main.Main, then your application works.  This might include running servers, deploying things, and so on, but it’s all loosely coupled and tiny. It is the act of bringing these archives together—drawing a lasso around them with a CLASSPATH—that constitutes deployment.

As we’ve seen, CDI has the notion of a bean archive, but it doesn’t really have a notion of a group of bean archives.  I am going to use the wonderfully overloaded term component to describe this concept.

These components might need some other facilities provided by various portable extensions.  There is a hazy way in which a group of portable extensions providing services is different from a group of bean archives providing business logic.  I’ll call this aggregation an environment.

With these provisional terms in place, we can thus say that components run in environments.  We can also say that environments support components.

Then the act of deploying a microbean application becomes: pick one or more environments and one or more components and put them on the classpath, and then run java org.microbean.main.Main (or any other main class that simply starts up a CDI SE container and shuts it down; this just happens to be a convenient prefabricated one).

How could we represent these components?  On disk, we don’t really want to represent them at all.  A component as used here is a notional construct, after all: it’s a bunch of jars that belong together in some way.  For management purposes, however, representing them in Maven pom.xml files of a particular kind looks like a good way to go.

This also seems to be a good way to represent environments as well.

Maven’s pom.xml file and the dependency graph it implies is one of the most misunderstood artifacts in all of Java software engineering.  Most developers know that it describes a project and its dependencies, but did you know you can include a non-jar project pom.xml file (an artifact of type pom) as a dependency itself, thus effectively pulling in (transitively) its dependencies?  This can lead to version surprises, but did you know that a pom.xml‘s section can be used to lock down the version of a given artifact, whether it appears directly or transitively as a dependency? Finally, to complete the puzzle, did you know that a pom.xml can, itself, appear in its own <dependencyManagement> section, thus offering a way to lock its own version down as well as those of its dependencies?

These features mean that we can define both components and environments as artifacts of type pom.  I’ll be exploring these concepts over the next few blog posts.

MicroBean Launcher

This is the eleventh of a series of posts on some of the personal projects I’ve been working on.  As I hope you’ll see, they all fit together.  The previous post covered MicroBean Commons CLI.

This post covers MicroBean Launcher.  Its website is here, its source code is here and its binaries are available from Maven Central.

MicroBean Launcher lets you run a Java SE CDI 2.0 application from the command line by specifying Maven artifact coordinates to other bean archives, transitively resolving them and their dependencies, using MicroBean Maven CDI, to your local Maven repository.

To install MicroBean Launcher, place it (and its minimal dependencies) on your classpath.

Here is an example of its usage, assuming it and its dependencies are on your classpath already:

java org.microbean.launcher.main.Main --artifactPath com.foobar:frobnicator:1.0,com.foobar:caturgiator:2.0

This command will download, if necessary, com.foobar‘s frobnicator jar artifact at version 1.0 and com.foobar‘s caturgiator jar artifact at version 2.0.  These files and their transitive compile- and runtime-scoped dependencies will be placed in the current user’s local Maven repository (~/.m2/repository by default, but the user’s ~/.m2/settings.xml file, which can dictate where the local repository is, is honored).  (If the artifacts already exist, then no download happens.)  A classpath will be built out of all of these artifacts and effectively appended to the current classpath, and MicroBean Main will be invoked.

Why is this useful?  For one, specifying a classpath can now be done in terms of Maven artifact coordinates instead of local filesystem references.  Because MicroBean Maven CDI is in charge of dependency resolution using Maven’s own resolution machinery under the covers, you don’t need to be aware of whether the artifacts in question were downloaded or already present.

But more than this, note that in the last ten blog posts the installation instructions have been the same: you place whatever bean archive is being described on your classpath.  This is one of the nice things about CDI: CDI archives are loosely coupled modules that can be discovered.

This means you can compose a Java SE CDI 2.0 application together by simply referring to Maven artifacts.

Specifically, assuming you have MicroBean Launcher and its dependencies on your CLASSPATH, if you write, say, a JAX-RS Application and a root resource class that it exposes, and place them on your classpath, then you can run that application immediately, downloading only what you need and only what you don’t already have, by running a command line similar to the following:

java org.microbean.launcher.main.Main --artifactPath org.microbean:microbean-jersey-container-grizzly2-http-cdi-extension,org.microbean:microbean-jersey-container-grizzly2-http-cdi,org.microbean:microbean-grizzly-http-server-cdi

Note in particular that your application remains standards-compliant, and you selected the server you wanted to use to run it dynamically from the command line.  You wrote only the code you needed to and none other.

Note that the second time you run this all of the artifacts will already be present on your system.

These are early days for these personal projects and I’ll have plenty more to say about them in the future.  Thanks for reading!