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In Relation To Hibernate ORM

In Relation To Hibernate ORM

Java 6 compiler plugins and typesafe criteria queries

Posted by    |       |    Tagged as Hibernate ORM JPA

There's been plenty of discussion in the JPA group about my typesafe criteria proposal. My new favorite feature of the Java language is javax.annotation.Processor. Java 6 annotation processors are derived from the APT tool that existed in JDK 5, but are built into javac. Really, the name annotation processor is misleading, since this feature is only incidentally related to annotations. The Processor is really a fairly general purpose compiler plugin. If, like me, you've never been a fan of code generation, now is the time to reconsider. A Java 6 Processor can:

  • analyze the compiler's metamodel of the Java source code that is being compiled
  • search the source path for other metadata, such as XML
  • generate new types, which will also be compiled, or other files

Best of all, this functionality requires no special tool or commandline options to javac. All you need to do is put the jar containing your Processor in the classpath, and the compiler does the rest!

In the typesafe query API, I want to use this to work around Java's lack of a typesafe metamodel for fields and methods of a class. The basic idea is that the compiler plugin will generate a metamodel type for each persistent class in the application.

Suppose we have the following persistent class:

@Entity
public class Order {
    @Id long id;
	
    boolean filled;
    Date date;

    @OneToMany Set<Item> items;

    @ManyToOne Shop shop;
	
    //getters and setters...
}

Then a class named Order_ would be generated, with a static member of each persistent attribute of Order, that the application could use to refer to the attributes in queries.

After several iterations, we've settled on the following format for the generated type:

import javax.jpa.metamodel.Attribute;
import javax.jpa.metamodel.Set;
import javax.jpa.metamodel.Metamodel;

@Metamodel
public abstract class Order_ {
    public static Attribute<Order, Long> id;
    public static Attribute<Order, Boolean> filled;
    public static Attribute<Order, Date> date;
    public static Set<Order, Item> items;
    public static Attribute<Order, Shop> shop;
}

The JPA provider would be responsible for initializing the values of these members when the persistence unit is initialized.

Now, criteria queries would look like the following:

Root<Item> item = q.addRoot(Item.class);
Path<String> shopName = item.get(Item_.order)
                            .get(Order_.shop)
                            .get(Shop_.name);
q.select(item)
 .where( qb.equal(shopName, "amazon.com") );

Which is equivalent to:

select item 
from Item item
where item.shop.name = 'amazon.com'

Or like:

Root<Order> order = q.addRoot(Order.class);
Join<Item, Product> product = order.join(Order_.items)
		                   .join(Item_.product);
		
Path<BigDecimal> price = product.get(Product_.price);
Path<Boolean> filled = order.get(Order_.filled);
Path<Date> date = order.get(Order_.date);
		
q.select(order, product)
 .where( qb.and( qb.gt(price, 100.00), qb.not(filled) ) )
 .order( qb.ascending(price), qb.descending(date) );

Which is equivalent to:

select order, product 
 from Order order 
    join order.items item
    join item.product product
 where
    product.price > 100 and not order.filled
 order by
    product.price asc, order.date desc

The queries are almost completely typesafe. Because of the generic type parameters of Attribute:

  • I can't pass an attribute of Order to a Join or Path that represents an Item, and
  • I can't try to perform a comparison like gt() on a Path that represents a boolean attribute, or not() on a Path that represents an attribute of type Date.

There's some skeptics in the expert group, but my feeling is that once people get used to the idea that type generation is no longer something that gets in your way during development, we're going to see a lot more frameworks using this kind of approach. I certainly think this API is a big improvement over the previous proposal:

Root item = q.addRoot(Item.class);
Path shopName = item.get("order")
                    .get("shop")
                    .get("name");
q.select(item)
 .where( qb.equal(shopName, "amazon.com") );

Or:

Root order = q.addRoot(Order.class);
Join product = order.join("items")
		    .join("product");
		
Path price = product.get("price");
Path filled = order.get("filled");
Path date = order.get("date");
		
q.select(order, product)
 .where( qb.and( qb.gt(price, 100.00), qb.not(filled) ) )
 .order( qb.ascending(price), qb.descending(date) );

Both these queries are riddled with non-typesafe method invocations which can't be validated without executing the query.

A typesafe criteria query API for JPA

Posted by    |       |    Tagged as Hibernate ORM JPA

The public draft of the JPA 2.0 specification is already out and includes a much-awaited feature: an API that lets you create queries by calling methods of Java objects, instead of by embedding JPA-QL into strings that are parsed by the JPA implementation. You can learn more about the API proposed by the public draft at Linda's blog.

There's several reasons to prefer the API-based approach:

  • It's easier to build queries dynamically, to handle cases where the query structure varies depending upon runtime conditions.
  • Since the query is parsed by the Java compiler, no special tooling is needed in order to get syntactic validation, autocompletion and refactoring support.

(Note that JPA-QL syntax validation and autocompletion is available is some IDEs - in JBoss Tools, for example.)

There's two major problems with criteria query APIs in the Java language:

  • The queries are more verbose and less readable.
  • Attributes must be specified using string-based names.

The first problem isn't really solvable without major new language features (usually described as DSL support). The second problem could easily be solved by adding a typesafe literal syntax for methods and fields to Java. This is now a sorely needed feature of the language, it's especially useful in combination with annotations.

There have been some previous efforts to work around the lack of method and field literals. One recent example is LIQUidFORM. Unfortunately that particular approach forces you to represent every persistent attribute as a public getter method, which is not a restriction that is acceptable in the JPA specification.

I've proposed a different approach to the JPA EG. This approach comes in three layers:

  • A metamodel API for JPA
  • A query API where types and attributes are specified in terms of metamodel API objects
  • Support for third-party tooling which would generate a typesafe metamodel from the entity classes

Let's go layer-by layer.

The Metamodel

The metamodel API is a bit like the Java reflection API, except that it is provided by the JPA persistence provider, is aware of the JPA metadata, and uses generics in a clever way. (Also it uses unchecked exceptions.)

For example, to obtain an object that represents an entity, we call the MetaModel object:

import javax.jpa.metamodel.Entity;
...
Entity<Order> order = metaModel.entity(Order.class);
Entity<Item> item = metaModel.entity(Item.class);
Entity<Product> item = metaModel.entity(Product.class);

To obtain attributes of the entity, we need to use string-based names, as usual:

import javax.jpa.metamodel.Attribute;
import javax.jpa.metamodel.Set;
...
Set<Order, Item> orderItems = order.set("items", Item.class);
Attribute<Item, Integer> itemQuantity = item.att("quantity", Integer.class);
Attribute<Item, Product> itemProduct = item.att("product", Product.class);
Attribute<Product, BigDecimal> productPrice = product.att("price", BigDecimal.class)

Notice how the metamodel types which represent attributes are parameterized not only by the type of the attribute they represent, but also by the type that they belong to.

Also notice that this code is non-typesafe and can fail at runtime if no persistent attribute with the given type and name exists in the entity class. This is the only non-typesafe code we'll see - our goal is keep the rest of the API completely typesafe. How does that help us? Well, the trick here is to notice that the metamodel objects represent completely static information about a persistent classes, state that doesn't change at runtime. So we can:

  • obtain and cache these objects at system intialization time, forcing any errors to occur upfront, or even
  • let a tool that has access to our persistent classes generate the code that obtains and caches metamodel objects.

That's much better than having these errors occur at query execution time, as they do in the previous criteria query proposal.

The metamodel API is generally useful, even independent of the query API. Currently it's very difficult to write generic code that interacts with JPA because JPA metadata may be partitioned between annotations and various XML documents.

But, of course, the most popular use of the metamodel is to build queries.

Queries

To construct a query, we pass metamodel objects to the QueryBuilder API:

Query query = queryBuilder.create();

Root<Order> orderRoot = query.addRoot(order);
Join<Order, Item> orderItemJoin = orderRoot.join(orderItems);
Join<Item, Product> itemProductJoin = orderItemJoin.join(itemProduct);

Expression<Integer> quantity = orderItemJoin.get(itemQuantity);
Expression<BigDecimal> price = itemProductJoin.get(productPrice);

Expression<Number> itemTotal = queryBuilder.prod(quantity, price);
Expression<Boolean> largeItem = queryBuilder.gt(itemTotal, 100);

query.restrict(largeItem)
     .select(order)
     .distinct(true);

For comparison, here is the same query expressed using the API proposed in the public draft:

Query query = queryBuilder.createQueryDefinition();

DomainObject orderRoot = query.addRoot(Order.class);
DomainObject orderItemJoin = orderRoot.join("items");
DomainObject itemProductJoin = orderItemJoin.join("product");

Expression quantity = orderItemJoin.get("quantity");
Expression price = itemProductJoin.get("price");

Expression itemTotal = quantity.times(price);
Predicate largeItem = queryBuilder.greaterThan(100);

query.where(largeItem);
     .selectDistinct(order);

Of course, this query could be written more compactly in either API, but I'm trying to draw attention to the generic types of the objects that make up the query. The type parameters prevent me from writing something like this:

orderItemJoin.get(productPrice); //compiler error

The use of generics means the compiler can detect when we try to create a path expression by combining a queried entity of one type and an attribute of some other type. The metamodel object productPrice has type Attribute<Product, BigDecimal> and therefore cannot be passed to the get() method of orderItemJoin. get() only accepts Attribute<Item, ?>, since orderItemJoin is of type Join<Order, Item>.

Expressions are also parameterized by the expression type, so the compiler detect mistakes like:

queryBuilder.gt(stringExpression, numericExpression); //error

Indeed, the API has sufficient typesafeness that it's more or less impossible to build an unexecutable query.

Generating a typesafe metamodel

It's completely possible to build queries with only the metamodel API and the query API. But to really make the most of these APIs, the final piece of the puzzle is a little code generation tool. This tooling doesn't need to be defined by the JPA specification, and different tools don't need to generate exactly the same code. Nevertheless, the generated code will always be portable between all JPA implementations. All the tool does is reflect upon the persistent entities and create a class or classes that statically cache references to the metamodel Entity and Attribute objects.

Why do we need this code generator? Because writing Attribute<Item, Integer> itemQuantity = item.att("quantity", Integer.class); by hand is tedious and slightly error prone, and because your refactoring tool probably isn't smart enough to change the string based name when you refactor the name of the attribute of the persistent class. Code generation tools don't make these kind of errors, and they don't mind re-doing their work from scratch each time you ask them to.

In a nutshell: the tool uses the non-typesafe metamodel API to build a typesafe metamodel.

The most exciting possibility is that this code generation tool could be an APT plugin for javac. You wouldn't have to run the code generator explicitly, since APT is now fully integrated into the Java compiler. (Or, it could be an IDE plugin.)

But didn't code generation tools go out of fashion recently? Wasn't one of the great features of ORM solutions like Hibernate and JPA that they didn't rely upon code generation? Well, I'm a great believer in using whatever tool is the right solution to the problem at hand. Code generation has certainly been applied to problems where it wasn't the best solution. On the other hand, I don't see anyone bashing ANTLR or JavaCC for their use of code generation to solve the problem they address. In this case, we're working around a specific problem in the Java type system: the lack of a typesafe metamodel (reflection is one of the worst-designed language features). And code generation is simply the only solution that works. Indeed, for this problem it works well.

Don't worry, the generated code won't be hard to understand ... it might look something like this, for example:

public class persistent {
	static Metamodel metaModel;

	public static Entity<model.Order> order = metaModel.entity(model.Order.class);
	public static class Order {
		public static Attribute<model.Order, Long> id = order.id(Long.class);
		public static Set<model.Order, model.Item> items = order.set("items", model.Item.class);
		public static Attribute<model.Order, Boolean> filled = order.att("filled", Boolean.class);
		public static Attribute<model.Order, Date> date = order.att("date", Date.class);
	}

	public static Entity<model.Item> item = metaModel.entity(model.Item.class);
	public static class Item {
		public static Attribute<model.Item, Long> id = item.id(Long.class);
		public static Attribute<model.Item, model.Product> product = item.att("product", model.Product.class);
		public static Attribute<model.Item, model.Order> order = item.att("order", model.Order.class);
		public static Attribute<model.Item, Integer> quantity = item.att("quantity", Integer.class);
	}

	public static Entity<model.Product> product = metaModel.entity(model.Product.class);
	public static class Product {
		public static Attribute<model.Product, Long> id = product.id(Long.class);
		public static Set<model.Product, model.Item> items = product.set("items", model.Item.class);
		public static Attribute<model.Product, String> description = product.att("description", String.class);
		public static Attribute<model.Product, BigDecimal> price = product.att("price", BigDecimal.class);
	}

}

This class just let's us refer to attributes of the entities easily. For example, we could type persistent.Order.id to refer to the id attribute of Order. Or persistent.Product.description to refer to the description of the Product.

I am please to announce the GA release of Hibernate Search 3.1. This release focuses on performance improvement and code robustness but also add interesting new features focused on usability:

  • An analyzer configuration model to declaratively use and compose features like phonetic approximation, n-gram approximation, search by synonyms, stop words filtering, elision correction, unaccented search and many more.
  • A lot of performance improvements at indexing time (including reduced lock contention, parallel execution).
  • A lot of performance improvements at query time (including I/O reduction both for Lucene and SQL, and better concurrency).
  • Additional new features both for indexing and querying (including support for term vector, access to scoped analyzer at query time and access to results explanation).

A more detailed overlook of the features follows

Analyzer

  • Support for declarative analyzer composition through the Solr library

Analyzers can now be declaratively composed as a tokenizer and a set of filters. This enable easy composition of the following features: phonetic approximation, n-gram approximation, search by synonyms, stop words filtering, elision correction, unaccented search and so on.

  • Support for dynamic analyzers

Allows a given entity to defined of the analyzer used at runtime. A typical use case is multi-language support where the language varies from one entity instance to an other.

Indexing

Indexing performance has been enhanced and new controls have been added

New features

  • Better control over massive manual indexing (flushToIndexes())
  • Support for term vector
  • Support for custom similarity
  • Better control over index writing (RAM consumption, non-compound file format flag, ...)
  • Better support for large index replication

Performance improvements

  • Improve contention and lock window during indexing
  • Reduce the number of index opening/closing
  • Indexing is done in parallel per directory

Querying

New useful features have been added to queries and performance has been improved.

New features

  • Expose entity-scoped and named analyzer for easy reuse at query time
  • Filter results (DocIdSet) can now be cached declaratively (default)
  • Query results Explanation is now exposed for better debugging information

Performance improvements

  • Reduces the number of database roundtrips on multi-entity searches
  • Faster Lucene queries on indexes containing a single entity type (generally the case)
  • Better performance on projected properties (no noticeable overhead compared to raw Lucene calls)
  • Reduction of I/O consumption on Lucene by reading only the necessary fields of a document (when possible)
  • Reduction of document reads (during pagination and on getResultSize() calls)
  • Faster index reopening (keeps unchanged segments opened)
  • Better index reader concurrency (use of the read only flag)

Libraries

  • Migration to Lucene 2.4 (and its performance improvements)
  • Upgrade to Hibernate Core 3.3
  • Use SLF4J as log facade

Bug fixes

  • Fix a few race conditions on multi core machines
  • Resources are properly discarded at SessionFactory.close()
  • Fix bug related to embedded entities and @Indexed (HSEARCH-142)
  • Filter instances are properly cached now
  • And more (see the change logs)

Download and all

You can download the release here. Changelogs are available on JIRA. Migrating to this version is recommended for all users (see the Migration guide).

Many thanks to everyone who contributed to the development and test of this release. Especially, many thanks to Sanne and Hardy who worked tirelessly pushing new features and enhancements and fixing bugs while John and I where finishing Hibernate Search in Action.

We have some features on the work that we could not put in 3.1, so stay tuned.

Web Beans and the EE platform

Posted by    |       |    Tagged as CDI Hibernate ORM

If there's one thing that we really want to get right as Web Beans goes from Public Draft to Proposed Final draft, it's integration with the Java EE platform. Up to this point, most of the work we've been doing as an EG was focused on nailing down the programming model, the semantics of the Web Beans services, and the behavior of the Web Bean manager. We've been writing the spec to assume that Web Beans implementations should be pluggable between different Java EE containers, because this is a direction that a lot of folks in the Java EE community believe that the EE platform should move in, and because we would like Web Beans to help show the way for other specifications such as EJB, JTA and perhaps even Servlets (note that JPA and JSF already support this).

Since the release of the Public Draft, our main focus has shifted to the integration problem. Web Beans generated a bunch of controversy when the draft was circulated to the EE platform expert group and proposed by Sun for inclusion in the Web Profile. That's not surprising - Web Beans solves some very important problems that lots of people have strong opinions on. I've also had a number of more technical discussions with the EE and EJB spec leads and with the EJB expert group. A number of concerns have emerged, which we're now attempting to address.

Let me share my take on these issues, and some directions we might pursue. But first...

...some history

In the days of EJB 1.x and 2.x, a major complaint against EJB was that the programming model was too restrictive. The specification imposed many annoying, distracting and unnecessary requirements upon developers. EJB 3.0 changed all that. Gone were the most of these annoying coding restrictions. In place of verbose XML deployment descriptors, EJB 3.0 was the first Java component model to be based around the use of annotations. In place of JNDI lookups was a simple dependency injection model, which ended up being generalized at the EE 5 platform level. I was a member of the EJB 3.0 expert group, and remain proud of what we accomplished.

However, the Java EE 5 dependency injection model was criticized from the outset. Many folks, including Rod Johnson of SpringSource, argued that the lack of support for injection of Java classes which were not EJBs was a fatal flaw. (At the time I did not agree, but I've changed my mind since.) On the other hand, I was dissatisfied with the lack of a contextual lifecycle model - though, in fairness, some other DI solutions of the time, including Spring, also lacked a contextual model. I was also unhappy with the mismatch between the JSF (XML-based, contextual) dependency injection model and the platform-level (annotation-based, non-contextual) model. This mismatch made it difficult to integrate EJB components with JSF.

Most of the changes introduced in EJB 3.0 and JPA 1.0 have stood the test of time remarkably well. The EE 5 dependency injection model has not. Contextual lifecycle management is now a standard feature of dependency injection solutions including Seam, Spring and Guice. Most importantly, Guice showed us the folly of using string-based names to identify implementations of an API. And Seam showed how to simplify application development by unifying dependency management in the web and EJB tiers.

Web Beans was initiated to address these problems. The original JSR proposal complained that:

  • EJB components are not aware of the web-tier request, session and application contexts and do not have access to state associated with those contexts. Nor may the lifecycle of a stateful EJB component be scoped to a web-tier context.
  • The JSF component model is not consistent with Java EE ... dependency injection...

The JSR promised to unif[y] the two component models and enabl[e] a considerable simplification to the programming model.

A new dependency injection model was needed: a model that provided contextual lifecycle management to transactional EE components.

Is Web Beans a component model?

In the Web Beans Early Draft, we characterized Web Beans as a component model. The specification defined two things:

  1. a set of restrictions that a Java class or EJB session bean must satisfy in order to be a Web Bean (principally, but not only, that it must explicitly specify @Component or another deployment type), and
  2. the services that would then be available to the Web Bean.

I viewed this as a unifying component model: a unification that would solve a major problem that has existed since J2EE - that the Java EE web tier has a completely different component model (actually, component models plural) to the transactional tier. It promised to tear down the wall between the two tiers, allowing transactional components to be aware of state related to the Web request. It promised a truly uniform programming model for components concerned with orchestration of the Web request, and components concerned with managing data access (at least when JSF was used).

This turned out to be the wrong approach. The strong feedback from the EE group was that Web Beans shouldn't define a new component model. The feedback from the EE spec leads at Sun was that the services defined by Web Beans should be available to all kinds of Java EE components - not just those which satisfied our definition of a Web Bean.

At Sun's urging, we made two changes to the specification. The first was primarily a language change. We repositioned Web Beans as a set of services, provided by a Manager analogous to the JTA TransactionManager, instead of a component model with a Container. But this also implied two more technical changes:

  1. we dramatically loosened the restrictions on what objects are Web Beans, so that every EJB session bean and every JavaBean is now a Web Bean, without any requirement for explicit declaration, and
  2. we provided a set of SPIs to allow objects which are not JavaBeans or EJB session beans to take advantage of the services provided by the Web Bean manager.

In particular, we provided injection into Servlets and message-driven beans (objects which by nature are not injectable) and an SPI that allowed other EE technologies and thirdparty frameworks to offer their components up for injection by Web Beans, and take advantage of the Web Beans services.

This was certainly the right thing to do, and the Web Beans specification is now more powerful and less intrusive. It still promises a more uniform programming model, but a side effect of these changes was that the model became even more generally useful, and even less specific to JSF and EJB. This isn't the first time I've seen something like that happen: the EJB 3.0 expert group also produced some technology (JPA, EE 5 dependency injection) that ended up being applied more generally than was originally envisaged.

Is Web Beans still a component model?

Unfortunately, some people are still not satisfied. A number of members of the platform expert group believe that the notion of a simple Web Bean still specifies a new component model. So what, exactly, is a simple Web Bean, and why do we need them?

A simple Web Bean is nothing new. It's just a Java class. You've already written hundreds or even thousands of simple Web Beans. Every JavaBean is a simple Web Bean. All we're trying to do is allow objects which were not specifically written as EJBs to be injectable and take advantage of the Web Beans services.

A simple Web Bean has the following advantages over an EJB session bean:

  • it does not need to be explicitly declared as an EJB using a component-defining annotation or XML
  • its interfaces do not need to be explicitly declared using @Local or @LocalBean
  • it can be final, or have final methods
  • it has a more natural lifecycle and concurrency model - the normal lifecycle for a Java class, instead of the enhanced lifecycle/concurrency semantics defined by EJB
  • if it's a stateful object, it does not require a @Remove method
  • it can take advantage of constructor injection

You can use preexisting JavaBeans and many other Java classes as simple Web Beans. As a side effect, simple Web Beans reduce the mental gap for new Java EE users who might be, initially, scared off by the unfamiliar EJB semantics - and the rather painful requirements to explicitly designate business interfaces and add empty @Remove methods - and let these new users get started with container-managed objects more easily.

On the other hand, unlike session beans, simple Web Beans, as currently defined:

  • don't have method-level transaction demarcation or security
  • can't have timeouts or asynchronous methods
  • can't have remote interfaces or be web service endpoints
  • don't have container-managed concurrency (locks)
  • don't support instance-level passivation or pooling

Therefore, in my opinion (an opinion shared the current and previous EJB spec leads), simple Web Beans don't compete with EJB as a solution for the transactional tier of the application. In fact, simple Web Beans aren't really anything new - Java EE developers already use EJBs and JavaBeans side by side. Web Beans just makes their life a little easier.

But some folks disagree. For example, one expert is worried that by providing something called a simple Web Bean, we're encouraging people to use them instead of EJB. The risk is that developers will be guided away from the use of non-simple EJBs. This has become a real sticking point in the EE group, and threatens to derail the whole Web Beans effort.

Of course, we're trying to work through this. One possibility is that we could move the definition of a simple Web Bean to the EJB specification, as a new EJB component type. Another possibility is to simply drop simple Web Beans from the specification, and ask everyone to write all their objects as EJBs.

Personally, I can't imagine releasing Java EE 6 with a dependency injection solution that doesn't support JavaBeans. All the other solutions in the space support both JavaBeans and EJB. EE 5 missed this boat - I don't want EE 6 to repeat the mistake. And I think that this is a case where users want to make the decision about when to use EJB. They don't want us to force a decision down their throats.

Injection of other EE resource types

A second issue raised by the EE experts is that the Web Beans specification does not currently define support for injection of all the various Java EE resource types. Specifically, Web Beans does not explicitly define injection of JDBC datasources, connections, web service endpoints, remote EJBs or persistence contexts. Of course, you can still use the existing Java EE 5 @Resource and @PersistenceContext annotations to inject Java EE resources, but then you'll miss out on the advantages of the more flexible and more typesafe model defined by Web Beans.

Well, the true situation is that injection of EE resources (or anything else at all) is already supported by Web Beans, assuming that the Java EE container calls an appropriate Web Beans SPI at initialization time. But neither the EE specification nor the Web Beans specification requires it to do so. So this is an issue that should be easy to fix.

Pluggability

We put a fair amount of effort into defining the interaction between the EE container and the Web Bean manager, for the purpose of supporting pluggable Web Bean managers. However, nothing that is currently defined imposes any new requirement upon the EE container. Unfortunately, at this point, there remain a number of open issues in the specification that can only be resolved by either:

  • dropping the requirement for pluggability or
  • imposing new requirements upon the EE container.

(Search for Open issue in the Public Draft if you're interested in knowing exactly what new requirements would be imposed upon the Java EE container.)

Either of these paths is technically feasible, but one of them is a lot more work and involves a lot more coordination between the various expert groups, some of which are already struggling to meet tight deadlines. If Web Beans is required in Java EE 6, it's not clear that pluggability is truly of great value to users. Does anyone really need to switch out their Web Bean manager?

I'd love to hear from the community whether pluggability is really worth pursuing.

Packages and naming

Quite a number of people hate the name Web Beans, which they see as obscuring the generality of the model we've defined. I view the name as more of a catchy brand than a definition of what Web Beans does. Think of Microsoft and .net. I don't mind changing the name, but nobody has yet suggested a great alternative. For one thing, I hate acronyms, and something descriptive like Java Dependency Injection wouldn't really capture all that Web Beans does.

Independently of this objection, quite a number of people think that it would be better to package our annotations by concern rather than putting them all in the package javax.webbeans. For example, the following package layout might make better sense:

  • javax.dependency - DI-related annotations: binding types, deployment types, @Initializer, @Produces, etc.
  • javax.contexts - scope-related annotations, Context interface
  • javax.interceptor (which already exists) - interceptor and decorator related annotations
  • javax.events - @Observes, event bus interfaces

I see repackaging as a great idea.

The good news

The good news is that there's very little debate about the actual technical details of the (Guice and Seam inspired) dependency injection model in Web Beans. The feedback I'm getting from spec reviewers is uniformly positive. This gives me a lot of confidence that the more political issues are also solvable.

What do you think?

The issues I've discussed in this post are important to all members of the Java EE community and to the future direction of the Java EE platform. I don't believe that we should be making these decisions behind closed doors, without the involvement of users. Please speak up and let us know what you want us to do. And please take the time to learn more about Web Beans.

Hibernate Search 3.0.0.Beta2 is out with a bunch of new interesting features:

  • shared Lucene IndexReader, significantly increasing the performances especially in read mostly applications
  • ability to customize the object graph fetching strategy
  • properties projection from the Lucene index
  • ability to sort queries (thanks to Hardy Ferentschik)
  • expose the total number of matching results regardless of pagination

Performance

Hibernate Search can now share IndexReaders across queries and threads, making them much more efficient especially on applications where the number of reads is much higher than the number of updates. Opening and warming a Lucene IndexReader can be a relatively costly operation compared to a single query. To enable sharing, just add the following property

hibernate.search.reader.strategy shared

Object loading has been enhanced as well. You can for example define the exact fetching strategy used to load the expected object graph, pretty much like you would do it in a Criteria or HQL query, allowing per use case optimization.

Some use cases do not mandate a fully loaded object. Hibernate Search now allow properties projection from the Lucene index. At the cost of storing the value in the index, you can now retrieve a specific subset of properties. The behavior is similar to HQL or Criteria query projections.

fullTextQuery.setIndexProjection( "id", "summary", "body", "mainAuthor.name" ).list();

Query flexibility

I already talked about the customizable fetching strategy and projection.

The default sorting on Hibernate Search queries is per relevance, but you can now customize this strategy and sort per field(s).

Regardless of the pagination process, it is interesting to know the total number of matching elements. While costly in plain SQL, this information is provided out-of-the-box by Apache Lucene. getResultSize() is now exposed by the FullTextQuery. From this information, you can for example:

  • implement the search engine feature '1-10 of about 888,000,000'
  • implement a fast pagination navigation
  • implement a multi step search engine (gradually enabling approximations if the restricted query(ies) return no or not enough results)

For more information, check the the release notes and download the bundle . Hibernate Search 3.0.0.Beta2 is compatible with Hibernate Core 3.2.x (from 3.2.2), Hibernate Annotations 3.3.x and Hibernate EntityManaher 3.3.x.

Hibernate: 2 Million Downloads + 5 Years = 25 Books

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Happy Birthday Hibernate! Now that the first copies of Java Persistence with Hibernate are shipping (still waiting for mine though), the first people who should get one are Hibernate contributors. Manning Publications sponsors 25 copies of the book, and we'll distribute them in exchange for 25 Hibernate forum credits. See this page for details.

Also, I'm not sure I promised Gavin to never show this, but this is how the Hibernate website looked like five years ago: Old Hibernate Website[1]

Say what you want about the look of the page, some of that content is still here today unchanged. Good stuff.

Hibernate 3.2, Java Persistence provider final released

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The Hibernate developer team released Hibernate 3.2.0 GA today, this release is now ready for production use. Please read the migration guidelines if you are upgrading from an earlier version.

In addition to Hibernate Core, final releases of the Java Persistence provider are now available with Hibernate Annotations and Hibernate EntityManager. The Hibernate Java Persistence provider has been certified with the Sun TCK. You can use the Java Persistence API and annotation metadata in any Java project, inside or outside any Java EE 5.0 application server. If you are upgrading from an earlier version of the Hibernate Java Persistence provider, please see the migration guidelines.

We'd like to thank all contributors and users for their issue reports!

Download the latest releases...

Hibernate 3.2: Transformers for HQL and SQL

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People using the Criteria API have either transparently or knowingly used a ResultTransformer . A ResultTransformer is a nice and simple interface that allows you to transform any Criteria result element. E.g. you can make any Criteria result be returned as a java.util.Map or as a non-entity Bean.

Criteria Transformers

Imagine you have a StudentDTO class:

public class StudentDTO {
  private String studentName;
  private String courseDescription;
  
  public StudentDTO() { }
      
  ...
} 

Then you can make the Criteria return non-entity classes instead of scalars or entities by applying a ResultTransformer:

List resultWithAliasedBean = s.createCriteria(Enrolment.class)
  .createAlias("student", "st").createAlias("course", "co")
  .setProjection( Projections.projectionList()
                   .add( Projections.property("st.name"), "studentName" )
                   .add( Projections.property("co.description"), "courseDescription" )
          )
          .setResultTransformer( Transformers.aliasToBean(StudentDTO.class) )
          .list();

 StudentDTO dto = (StudentDTO)resultWithAliasedBean.get(0);  

This is how ResultTransformer have been available since we introduced projection to the Criteria API in Hibernate 3.

It is just one example of the built in transformers and users can provide their own transformers if they so please.

Jealous programming

Since I am more a HQL/SQL guy I have been jealous on Criteria for having this feature and I have seen many requests for adding it to all our query facilities.

Today I put an end to this jealousy and introduced ResultTransformer for HQL and SQL in Hibernate 3.2.

HQL Transformers

In HQL we already had a kind of result transformers via the (select new http://www.hibernate.org/hib_docs/v3/reference/en/html/queryhql.html#queryhql-select) syntax, but for returning non-entity beans it only provided value injection of these beans via its constructor. Thus if you used the same DTO in many different scenarios you could end up having many constructors on this DTO purely for allowing the select new functionality to work.

Now you can get the value injected via property methods or fields instead, removing the need for explicit constructors.

List resultWithAliasedBean = s.createQuery(
  "select e.student.name as studentName," +
  "       e.course.description as courseDescription" +
  "from   Enrolment as e")
  .setResultTransformer( Transformers.aliasToBean(StudentDTO.class))
  .list();

StudentDTO dto = (StudentDTO) resultWithAliasedBean.get(0);

SQL Transformers

With native sql returning non-entity beans or Map's is often more useful instead of basic Object[]. With result transformers that is now possible.

List resultWithAliasedBean = s.createSQLQuery(
  "SELECT st.name as studentName, co.description as courseDescription " +
  "FROM Enrolment e " +
  "INNER JOIN Student st on e.studentId=st.studentId " +
  "INNER JOIN Course co on e.courseCode=co.courseCode")
  .addScalar("studentName")
  .addScalar("courseDescription")
  .setResultTransformer( Transformers.aliasToBean(StudentDTO.class))
  .list();

StudentDTO dto =(StudentDTO) resultWithAliasedBean.get(0);

Tip: the addScalar() calls were required on HSQLDB to make it match a property name since it returns column names in all uppercase (e.g. STUDENTNAME). This could also be solved with a custom transformer that search the property names instead of using exact match - maybe we should provide a fuzzyAliasToBean() method ;)

Map vs. Object[]

Since you can also use a transformer that return a Map from alias to value/entity (e.g. Transformers.ALIASTOMAP), you are no longer required to mess with index based Object arrays when working with a result.

List iter = s.createQuery(
  "select e.student.name as studentName," +
  "       e.course.description as courseDescription" +
  "from   Enrolment as e")
  .setResultTransformer( Transformers.ALIAS_TO_MAP )
  .iterate();

String name = (Map)(iter.next()).get("studentName");

Again, this works equally well for Criteria, HQL and native SQL.

Reaching Nirvana of native sql

We still miss a few things, but with the addition of ResultTranformer support for SQL and the other additions lately to the native sql functionality in Hibernate we are close to reach the Nirvana of native sql support.

Combined with StatelessSession you actually now got a very flexible and full powered sql executor which transparently can map to and from objects with native sql without any ORM overhead.

...and when you get tired of managing the sql, objectstate, lifecycles, caching etc. of your objects manually and want to benefit from the power of an ORM then you got it all readily available to you ;)

Pro Hibernate 3 deadlocking example

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A bug report was recently opened in Hibernate's JIRA stating that Hibernate incorrectly handles deadlock scenarios. The basis for the report was an example in the /Pro Hibernate 3/ book (Chapter 9). For those perhaps not familiar with the term deadlock, the basic gist is that two processes each hold resource locks that the other needs to complete processing. While this phenomena is not restricted to databases, in database terms the idea is that the first process (P1) holds a write lock on a given row (R1) while the second process (P2) holds a write lock on another row (R2). Now, to complete its processing P1 needs to acquire a write lock on R2, but cannot do so because P2 already holds its write lock. Conversely, P2 needs to acquire a write lock on R1 in order to complete its processing, but cannot because P1 already holds its write lock. So neither P1 nor P2 can complete its processing because each is indefinitely waiting on the other to release the needed lock, which neither can do until its processing is complete. The two processes are said to be deadlocked in this situation.

Almost all databases have support to circumvent this scenario by specifying that locks should be timed-out after a certain period of time; after the time-out period, one of the processes is forced to rollback and release its locks, allowing the other to continue and complete. While this works, it is not ideal as it requires that the processes remained deadlocked until the underlying timeout period is exceeded. A better solution is for the database to actively seek out deadlock situations and immediately force one of the deadlock participants to rollback and release its locks, which most databases do in fact also support.

So now back to the /Pro Hibernate 3/ example. Let me say up front that I have not read the book and so do not understand the background discussion in the chapter nor the authors' intent/exceptations in regards to the particular example code. I only know the expectations of a (quite possibly mis-guided) reader. So what this example attempts to do is to spawn two threads that each use their own Hibernate Session to load the same two objects in reverse order and then modify their properties. So the above mentioned reader expects that this sould cause a deadlock scenario to occur. But it does not. Or more correctly, in my running of the example, it typically does not, although the results are inconsistent. Sometimes a deadlock is reported; but the vast majority of runs actually just succeed. Why is that the case?

So here is what really happens in this example code. As I mentioned before, the example attempts to load the same two objects in reverse order. The example uses the entities Publisher and Subscriber. The first thread (T1) loads a given Publisher and modifies its state; it is then forced to wait. The second thread (T2) loads a given Subscriber and modified its state; it is then forced to wait. Then both threads are released from their waiting state. From there, T1 loads the same Subscriber previously loaded by T2 and modifies its state; T2 loads the same Publisher previously loaded by T1 and modifies its state. The thing you need to keep in mind here is that so far neither of these two Sessions have actually been flushed, thus no UPDATE statements have actually occurred against the database at this point. The flush occurs on each Session after each thread's second load and modify sequence. Thus, until that point neither thread (i.e. the corresponding database process) is actually holding any write locks on the underlying data. Clearly, the outcome here is going to depend upon the manner in which the two threads are actually allowed to re-awaken by the underlying threading model, and in particular whether the UPDATE statements from the two sessions happen to get interleaved. If the two threads happen to interleave their requests to the database (i.e. T1's UPDATE PUBLISHER happens first, T2's UPDATE SUBSCRIBER hapens second, etc) then a deadlock will occur; if not interleaved, then the outcome will be success.

There are three ways to inequivocally ensure that lock acquisition errors in the database force one of these two transactions to fail in this example:

  • use of SERIALIZABLE transaction isolation in the database
  • flushing the sesssion after each state change (and the end of the example code's step1() and step2() methods)
  • use of locking (either optimistic or pessimistic)

Seems simple enough. Yet apparently not simple enough for the reader of the /Pro Hibernate 3/ book that opened the previously mentioned JIRA case. After all this was explained to him, he wrote me some ill-tempered, misconception-laden replies in private emails. I am not going to go into all the misconceptions here, but one in particular I think needs to be exposed as many developers without a lot of database background seem to stumble over various concepts relating to transactions. Isolation and locking are not the same thing. In fact, to a large degreee, they actually have completely opposite goals and purposes. Transaction isolation aims to isolate or insulate one transaction from other concurrent transactions, such that operations performed in one transaction do not effect (to varying degrees, based on the exact isolation mode employed) operations performed in others. Locking, on the other hand, has essentially the exact opposite goal; it seeks to ensure that certain operations performed in a transaction do have certain effects on other concurrent transactions. In fact locking really has nothing to do with transactions at all except for the fact that their duration is typically scoped to the transaction in which they are acquired and that their presence/absense might affect the outcome of the different transactions. Perhaps, although I cannot say for sure, this confusion comes from the fact that a lot of databases use locking as the basis for their isolation model. But that is just an implementation detail and some databases such as Oracle, Postgres, and the newest SQL Server have very sophisticated and modern isolation engines not at all based on locking.

Hibernate 3.1.1 released

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Hibernate 3.1.1 has been released earlier this week. This maintenance release focused on bugfixes and improvements, especially regarding:

  • SQL Server support
  • DML-style HQL (UPDATE, DELETE, INSERT INTO... SELECT)
  • Native Query support
  • Connection handling

For details check out the release notes

Hibernate 3.1 introduced non OLTP features as well as better environment integration:

  • Custom strategy for session handling through CurrentSessionContext including 2 default implementations (JTA based and ThreadLocal based session handling)
  • more natural and aggressive connection handling in J2EE and J2SE environments
  • command-oriented API (StatelessSession API) for operations on huge number of objects
  • bulk UPDATE, DELETE, INSERT INTO ... SELECT for multi table entities
  • extra lazy collections for huge collection handling
  • use of join fetch on collection through scrollable resultsets through break processing
  • database generated properties (including database timestamps)
  • additional ON clauses for joins
  • dirty checking short-cuts for instrumented classes

Downloads are available here

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