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In Relation To Vlad Mihalcea

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Hibernate Community Newsletter 6/2017

Posted by    |       |    Tagged as Discussions Hibernate ORM

Welcome to the Hibernate community newsletter in which we share blog posts, forum, and StackOverflow questions that are especially relevant to our users.

Articles

Implementing the soft delete pattern with Hibernate is trivial. Check out this article for more details.

Sri Vikram Sundar wrote a very detailed tutorial about integrating Spring MVC, MySQL, and Hibernate.

Stefan Pröll wrote two articles about using Hibernate Search and Spring Boot:

Baeldung features an article about using the Hibernate-specific @Immutable annotation to mark entities that should never be modified, which allow Hibernate to enable some flush-time performance optimizations.

For our Portuguese readers, Rafael Ponte wrote a guide to controlling transactions programmatically in Legacy Systems using Java 8 Lambdas and the Template Pattern. For non-Portuguese readers, you can use Google Translate since most Romance languages are easily translated into English.

Time to upgrade

Hibernate ORM 5.1.5 and 5.2.9 have been released.

Hibernate Community Newsletter 5/2017

Posted by    |       |    Tagged as Discussions Hibernate ORM

Welcome to the Hibernate community newsletter in which we share blog posts, forum, and StackOverflow questions that are especially relevant to our users.

Interviews

Don’t miss our Hibernate developer interviews with Marco Pivetta and Kevin Peters.

If you want to share your story about Hibernate, let us know, and we can share it with our huge community of passionate developers.

Books

Javin Paul, a long-time Java blogger, gives a review of the two best Hibernate books for Java developers.

Thorben Janssen is now writing a Hibernate Tips book, and you can get a free copy if you want to review it.

Articles

Nowadays, many RDBMS support JSON column types and Hibernate makes it very easy to use JSON object as entity attributes as this article demonstrates it.

Encrypting and decrypting column values is easy-peasy when using Hibernate. Check out this article for a detailed tutorial on this topic.

Arnold Gálovics wrote a very good article how the LazyInitializationException works in Hibernate.

Craig Andrews is building a Hibernate SpringCache prototype which acts like a Hibernate second-level cache implementation on top of Spring Cache. The idea is very interesting, and we are looking for your feedback on this topic.

Our colleague, Chris Cranford have a talk about Hibernate Performance at DevNexus, and here are the slides.

If you’re using MySQL, then you should know that we refactored the MySQL Dialects so that it’s much easier for you to match a Hibernate Dialect with a given MySQL server version.

Concurrency Control is a very interesting topic, and if you every wondered how MVCC (Multi-Version Concurrency Control) works, then this article is going to unravel how INERT, UPDATE, and DELETE statements work in MVCC-based database engines.

Thorben Janssen wrote two articles about Hibernate Search, one about custom Analyzers and another one about Facets.

Time to upgrade

Meet Kevin Peters

Posted by    |       |    Tagged as Discussions Hibernate ORM Interview

In this post, I’d like you to meet Kevin Peters, a Software Developer from Germany and Hibernate aficionado.

Kevin Peters, align=

Hi, Kevin. Would you like to introduce yourself and tell us a little bit about your developer experience?

My name is Kevin Peters, and I live in Germany where I work as a Software Developer. My first contact with the Java language was around 2005 during my vocational training, and I fell in love with it immediately.

I worked for several companies leveraging Java and Spring to implement ERP extensions, customizing eCommerce systems and PIM solutions. Nearly one year ago, I joined the GBTEC Software + Consulting AG, one of the leading suppliers of business process management (BPM) software, and there we are now reimplementing a BPM system in a cloud-based manner using Dockerized Spring Boot microservices.

You have recently mentioned on Twitter a DataSource proxy solution for validating auto-generated statements. Can you tell us what about this tool and how it works?

We use Spring Data JPA with Hibernate as JPA provider to implement our persistence layer, and we really enjoy the convenience coming along with it. But we also know about the "common" obstacles like Cartesian Products or the N+1 query problem while working with an ORM framework.

In our daily technical discussions and during knowledge transfer sessions we try to raise awareness for these topics among our colleagues, and in my opinion, the best way to achieve this is implementing tests and real world code examples showing that practically.

I started to prepare a small mapping example for one of our technical meetings, called "techtime", to demonstrate the "unordered element collection recreation" issue, and I wanted to show the unexpected amount of queries fired in this simple use case.

Fortunately, I came across the ttddyy/datasource-proxy GitHub project which helped me a lot to make that problem tangible. The datasource-proxy project empowers you to wrap your existing datasource with a proxy and allows you to count all executed queries separated by query type (e.g. INSERT, UPDATE, etc.). With that opportunity you can not only write tests which assert that you are doing the right thing within your use cases, you can also check if you are doing it in an effective way and avoid the traps I did mention before.

At the time when our Coding Architect Ingo Griebsch suggested to use this approach to enhance our test environment by automating the hunt for performance penalties, you caught us talking about your article on Twitter.

Proxies are a great way to add cross-cutting concerns without cluttering business logic. For instance, FlexyPool brings Monitoring and Fallback capabilities to connection pools. Are you using Proxies for other concerns as well, like logging statements?

There are many ways to enrich application code with proxies, facades or aspects. Starting with small things like logging with a facade like SLF4J, using Spring Security for access control, Hystrix service-to-service communication or even "basic" stuff like transactions in Spring Data, all these features are working with proxies, and we won’t miss them anymore.

Why did you choose Hibernate for that particular project, and did it meet your expectations, especially when it comes to application performance?

Hibernate provides a lot of convenience to us, especially if we combine it with Spring Data JPA. But the fact I enjoy most is that you can still switch to Hibernate specific features like Hibernate Named Queries or special Hibernate annotations.

It’s important to know when you can relax using "magic" ORM features and when the opposite is needed - forgo bidirectional relations and write HQL instead or even using database native queries to receive complex data. In our opinion, Hibernate offers the best balance between convenience and performance if one knows how to use it.

Hence, we have a quite complex data model and customers which store a lot of data it’s vital for our software to fetch and write data in a performant way in every of our use cases. And in case of any doubts, at least your articles help us getting things done right.

We always value feedback from our users, so can you tell us what you’d like us to improve or are there features that we should add support for?

In general, we love the feature set of Hibernate. Only the support of UNION HQL queries/Criteria API would be an awesome feature that we missed recently.

Thank you, Kevin, for taking your time. It is a great honor to have you here. To reach Kevin, you can follow him on Twitter.

Meet Marco Pivetta

Posted by    |       |    Tagged as Discussions Hibernate ORM Interview

In this post, I’d like you to meet Marco Pivetta, who is one of the maintainer of Doctrine, a suite of PHP projects that were inspired by Hibernate ORM.

Marco Pivetta, align=

Hi, Marco. Would you like to introduce yourself and tell us a little bit about your developer experience?

I’m Marco "Ocramius" Pivetta, an Italian PHP consultant, currently living in Germany. Yes, the nickname is weird, but it comes from an era of Quake 3 Arena, Unreal Tournament & co.

I’ve been tinkering with computers since I was a child, and have been working with PHP for more than half my life now, developing a love-hate relationship with the language. Interestingly, I didn’t start with the usual Joomla/Wordpress/Drupal/etc, but built a quite complex website that interacted with a browser game called "OGame", and scraped game information through a Firefox addon that would then provide an additional information to the players.

The reason why this project ("stogame") is important for me is that it included extremely challenging problems to be solved for a rookie with no help at all, and is still one of the most complex projects that I worked on:

  • XSS/SQL injections - had those, wasn’t fun

  • queuing mechanisms to sync browser extensions and the website - invented my own system

  • optimizing queries and indexes on ~60Gb of MySQL MyISAM tables

  • disaster recoveries on such a system - had those too, wasn’t fun either

  • real-time push mechanisms for clients via BOSHXMPP

  • simplistic prediction engine to aid players in decision making

All of the above were built by 15-years-old-me by just spending countless sleepless nights on it, and also jeopardizing my school evaluations. Still, this was before libraries, design patterns, mentoring, Github: only me, some friends, and a good amount of design and prediction work.

I then moved on, gave up on the project, failed university (I’m a terrible student), got a few jobs and started using frameworks. Eventually, I got to work with all of the typical DB abstraction approaches:

  • Active Record (with ZendFramework)

  • Table Data Gateway - in a custom solution

  • Data Mapper - in a Java EE project

I liked the JPA approach in the Java EE project so much that I started looking for a PHP analogue solution for my daytime job, and ended up discovering Doctrine 2.

Since then, I started getting more and more involved with the project, starting from answering questions on the mailing list and StackOverflow. Benjamin Eberlei, who was the lead on the project at that time, pushed me towards contributing with actual code changes back in 2011.

Eventually, I became part of the maintainers of the project, and that also boosted my career, allowing me to become a consultant for Roave, which allows me to see dozens of different projects, teams and tools every month, as well as a public speaker.

You are one of the developers of Doctrine ORM framework. Can you please tell us what’s the goal of Doctrine?

I am actually not one of the developers, but one of the current maintainers. The initial designers of the current Doctrine 2 ORM, as far as I know, are Jonathan Wage, Guilherme Blanco, Benjamin Eberlei and Roman Borschel. I can probably still answer the question: Doctrine ORM tries to abstract the "database thinking" away from PHP software projects, while still being a leaky abstraction on purpose.

To clarify, most PHP developers are used to developing applications from the database up to the application layer, rather than from the domain logic down, and that’s a quite widespread problem that leads to hardly maintainable and unreadable code. This tool gets rid of most of those problems, by still allowing developers to access the database directly when needed.

Ruby on Rails employs the Active Record pattern. Why did Doctrine choose the ORM paradigm instead?

Interestingly, Doctrine 1.x was an Active Record library, and also a quite good one, but it became evident quite quickly that the JPA specification and Data Mapper plus Unit of Work were better solutions altogether.

Specifically, the Data Mapper approach allows consumers of the library to write abstractions that decouple the tool from the domain almost completely (there are always limitations to this). The Unit of Work pattern has an increased memory impact for PHP applications, but also massively reduces required query operations (via in-memory identity maps) while adding some transactional boundaries, and that is a big win for most PHP apps, which often don’t even use transactions at all.

There are more advantages, but I personally wouldn’t ever consider using Active Record again due to its limitations and inherent framework coupling. This doesn’t mean that Active Record doesn’t work, but I’ve been burnt many more times with AR than with DM.

Since Hibernate ORM has been influencing Doctrine, can you tell use the similarities and differences between these two frameworks?

Doctrine is hugely inspired by Hibernate and the JPA, although we couldn’t really copy things, both due to licensing issues and life-cycle differences in Java and PHP software.

Doctrine resembles Hibernate in the Unit of Work, mappings, basic event system, second level cache and the DQL language (HQL in Hibernate). We even designed an annotation system for PHP, since the language doesn’t support them, and it currently is the de-facto standard for custom annotations in PHP libraries, and we initially only needed this to simulate inline mappings like Hibernate allows them.

Where things differ a lot are flexibility and lifecycle, since Java is an AOT-compiled language with a powerful JIT and generally deployed in long-running applications.

PHP is an interpreted language, and its strength is also its pitfall: the typical share-nothing architecture allows for short-lived, memory-safe, retry-able application runs. That also means that we have no connection pooling, and the ORM internals are much more inflexible and less event-driven than Hibernate’s due to memory and execution time constraints. That also means that we rarely encounter memory issues due to large Unit of Work instances, and connections and entity instances aren’t shared across separate web application page loads, and slow ORM will unlikely slow down an entire application server.

Another huge difference is managed state: DETACHED makes little sense in the PHP world, since a detached entity may only come from serialized state. In Doctrine 3.x, we are planning to remove support for detaching entities, since storing serialized objects in PHP is generally leading to security issues and more trouble.

As you can see, the differences are indeed mostly in the lifecycle, but each language and framework has its strengths and pitfalls.

We always value feedback from our users, so can you tell us what you’d like us to improve or are there features that we should add support for?

I’m probably being weird here, but I don’t lack any particular features from either ORM at this time. What would be interesting is reducing support for entity and transaction lifecycle events, since most consumers of these ORMs tend to code application and domain logic in those, while they were mostly intended for technical tasks, such as creating audit logs and executing pre- and post- DB cleanup tasks.

A possible improvement is to explore saving/loading of single aggregate-root-acting entities attached to a Unit of Work, which is only responsible for tracking state in child aggregates. This is only to prevent sharing entity references across aggregates, and to prevent DB transactions from crossing aggregate root boundaries.

Thank you, Marco, for taking your time. It is a great honor to have you here. To reach Marco, you can follow him on Twitter.

The MySQL Dialect refactoring

Posted by    |       |    Tagged as Discussions Hibernate ORM

Starting with Hibernate ORM 5.2.8, MariaDB gets its own Hibernate dialects.

Why?

While working on the new MariaDB Dialects, I realized that the MySQL Dialects would benefit from simplifying the version hierarchy.

Previously, the MySQL Dialects used to looks like that:

MySQL Dialects before refactoring, align=

As you can see, because of the various MySQL storage engines (e.g. MyISAM and InnoDB), the class hierarchy has diverged in multiple branches. Once we integrated Hibernate Spatial, the MySQL Dialects have become even more convoluted.

For this reason, we created the HHH-11473 Jira issue, which is fixed in Hibernate 5.2.9.

How do we stand now?

After refactoring, the MySQL Dialects look as follows:

MySQL Dialects after refactoring, align=

The following Dialects have been deprecated, therefore, they were not added to the class diagram above:

MySQLMyISAMDialect

Use MySQLDialect instead, as well as the hibernate.dialect.storage_engine=myisam Environment Variable or System Property.

MySQLInnoDBDialect

Use MySQLDialect instead, as well as the hibernate.dialect.storage_engine=innodb Environment Variable or System Property.

MySQL5InnoDBDialect

Use MySQL5Dialect instead, as well as the hibernate.dialect.storage_engine=innodb Environment Variable or System Property.

MySQL57InnoDBDialect

Use MySQL57Dialect instead.

MySQL5InnoDBSpatialDialect

Use MySQL5SpatialDialect instead, as well as the hibernate.dialect.storage_engine=innodb Environment Variable or System Property.

MySQL56InnoDBSpatialDialect

Use MySQL56SpatialDialect which defaults to InnoDB by default.

The MySQLStorageEngine abstraction encapsulates the difference between various storage engines, By delegating this responsibility to a new abstraction, the MySQL Dialect hierarchy got a lot simpler.

Traditionally, MySQL used the non-transactional MyISAM storage engine, and this is the default storage engine for all Dialects that are older than MySQL55Dialect. From MySQL55Dialect onwards, the InnoDB storage engine is used by default.

You can always override the default storage engine by providing the hibernate.dialect.storage_engine Environment Variable or System Property. Unlike other Hibernate configuration properties, this one must not be provided via persistence.xml because the Dialect is bootstrapped prior to the configuration management mechanism.

Conclusion

The deprecated Dialects will be available for a while, but they will surely be removed in a future version of Hibernate, so you better use the new ones instead. This refactoring is useful for two reasons. First, supporting MySQL 8.0 requires a single Dialect, not two. Second, it’s easier for our users as well since the choice is much more straightforward now since there is only one Dialect associated to a given MySQL version.

Hibernate Community Newsletter 4/2017

Posted by    |       |    Tagged as Discussions Hibernate ORM

Welcome to the Hibernate community newsletter in which we share blog posts, forum, and StackOverflow questions that are especially relevant to our users.

Looking for your feedback

We are looking for your feedback in about Hibernate bootstrap in cloud environments. Check out this article for more details. If you have any idea or proposal, don’t hesitate to use the comments section below the aforementioned article.

Articles

Sometimes, it’s easy to miss the basic concepts, and relational databases are no different. Check out this article about how does a relational database work.

We released dedicated Dialects for MariaDB, so you don’t have to use the MySQL-specific Dialects when working with MariaDB.

Integration testing is of paramount importance when building an enterprise application. However, many projects rely on in-memory databases (e.g. H2, HSQLDB) for testing, while in production they use Oracle, SQL Server, PostgreSQL or MySQL. In this article, you’ll find how you can run integration tests faster using tmpfs and Docker.

If you’re using JCache through Spring, Hibernate, and Ehcache, this article explains how you can prevent spontaneous cache creation.

Emmanouil Gkatziouras wrote two articles about Hibernate and Hazelcast as a 2nd-level caching provider:

Russ Thomas wrote https://sqljudo.wordpress.com/2014/12/29/what-every-dba-and-swe-should-know-about-ef/[a comprehensive list of ORM Anti-Patterns. Although the article was written for Entity Framework, the tups apply to JPA or Hibernate.

For our Portuguese readers, Rhuan Henrique Rocha da Silva wrote an article about the meaning of mappedBy in JPA and Hibernate.

Thorben Janssen wrote an article about adding Full-Test Search capabilities to a Hibernate application.

Questions and answers

MariaDB Dialects

Posted by    |       |    Tagged as Discussions Hibernate ORM

Starting with Hibernate ORM 5.2.8, MariaDB gets its own Hibernate dialects.

About MariaDB

MariaDB is a MySQL fork that emerged in 2009 as a drop-in replacement for MySQL. While for a while, MariaDB and MySQL offered similar functionalities, with time, both MariaDB and MySQL have diverged.

For this reason, we created the HHH-11457 issue, which is fixed in the Hibernate ORM 5.2.8.

Dialect variants

For the moment, you can use one of the following two options:

MariaDBDialect

which is the base class for all MariaDB dialects and it works with any MariaDB version

MariaDB53Dialect

which is intended to be used with MariaDB 5.3 or newer versions

In time, we will add new Dialects based on newer capabilities introduced by MariaDB.

Connection properties

While to connect to a MySQL application, the connection properties look as follows:

  • 'db.dialect' : 'org.hibernate.dialect.MySQL57InnoDBDialect',

  • 'jdbc.driver': 'com.mysql.jdbc.Driver',

  • 'jdbc.user' : 'hibernate_orm_test',

  • 'jdbc.pass' : 'hibernate_orm_test',

  • 'jdbc.url' : 'jdbc:mysql://127.0.0.1/hibernate_orm_test'

For MariaDB, the connection properties look like this:

  • 'db.dialect' : 'org.hibernate.dialect.MariaDB53Dialect',

  • 'jdbc.driver': 'org.mariadb.jdbc.Driver',

  • 'jdbc.user' : 'hibernate_orm_test',

  • 'jdbc.pass' : 'hibernate_orm_test',

  • 'jdbc.url' : 'jdbc:mariadb://127.0.0.1/hibernate_orm_test'

While the URL includes the mariadb database identifier, the MariaDB53Dialect supports Time and Timestamp with microsecond precision, just like MySQL57InnoDBDialect.

Conclusion

If you are using MariaDB, it’s best to use the MariaDB-specific Dialects from now on since it’s much easier to match the MariaDB version with its appropriate Hibernate Dialect.

Hibernate Community Newsletter 3/2017

Posted by    |       |    Tagged as Discussions Hibernate ORM

Welcome to the Hibernate community newsletter in which we share blog posts, forum, and StackOverflow questions that are especially relevant to our users.

Articles

If you’re using MySQL, then the GenerationType.AUTO identifier strategy is not the best option. Check out this article for more details and a very simple workaround.

Injecting a JPA/Hibernate Entity Managers wit CDI and Weld is extremely easy. Check out this article for more details.

Concurrency Control is a very difficult topic, and relational databases are no different. If you wonder how different database systems prevent Phantom reads or you are curious about how Two-phase Locking and MVCC work, you should definitely read this article.

Arno Huetter wrote a list of tips to improve application performance when you’re using JPA and Hibernate.

If you’re working on a database system which does not allow you to create temporary tables, then rest assured. Hibernate 5.2.8 adds support for non-temporary table bulk-id strategies.

If you want to separate the entity validation logic from the entity data structures, Hibernate Validator is a very attractive solution.

Time to upgrade

This article is about the HHH-11262 JIRA issue which now allows the bulk-id strategies to work even when you cannot create temporary tables.

Class diagram

Considering we have the following entities:

Class diagram, align=

The Person entity is the base class of this entity inheritance model, and is mapped as follows:

@Entity(name = "Person")
@Inheritance(
    strategy = InheritanceType.JOINED
)
public class Person
    implements Serializable {

    @Id
    private Integer id;

    @Id
    private String companyName;

    private String name;

    private boolean employed;

    //Getters and setters omitted for brevity

    @Override
    public boolean equals(Object o) {
        if ( this == o ) {
            return true;
        }
        if ( !( o instanceof Person ) ) {
            return false;
        }
        Person person = (Person) o;
        return Objects.equals(
            getId(),
            person.getId()
        ) &&
        Objects.equals(
            getCompanyName(),
            person.getCompanyName()
        );
    }

    @Override
    public int hashCode() {
        return Objects.hash(
            getId(), getCompanyName()
        );
    }
}

Both the Doctor and Engineer entity classes extend the Person base class:

@Entity(name = "Doctor")
public class Doctor
    extends Person {
}

@Entity(name = "Engineer")
public class Engineer
    extends Person {

    private boolean fellow;

    //Getters and setters omitted for brevity
}

Inheritance tree bulk processing

Now, when you try to execute a bulk entity query:

int updateCount = session.createQuery(
    "delete from Person where employed = :employed" )
.setParameter( "employed", false )
.executeUpdate();

Hibernate executes the following statements:

create temporary table
    HT_Person
(
    id int4 not null,
    companyName varchar(255) not null
)

insert
into
    HT_Person
    select
        p.id as id,
        p.companyName as companyName
    from
        Person p
    where
        p.employed = ?

delete
from
    Engineer
where
    (
        id, companyName
    ) IN (
        select
            id,
            companyName
        from
            HT_Person
    )

delete
from
    Doctor
where
    (
        id, companyName
    ) IN (
        select
            id,
            companyName
        from
            HT_Person
    )

delete
from
    Person
where
    (
        id, companyName
    ) IN (
        select
            id,
            companyName
        from
            HT_Person
    )

HT_Person is a temporary table that Hibernate creates to hold all the entity identifiers that are to be updated or deleted by the bulk id operation. The temporary table can be either global or local, depending on the underlying database capabilities.

What if you cannot create a temporary table?

As the HHH-11262 issue describes, there are use cases when the application developer cannot use temporary tables because the database user lacks this privilege.

In this case, we defined several options which you can choose depending on your database capabilities:

  • InlineIdsInClauseBulkIdStrategy

  • InlineIdsSubSelectValueListBulkIdStrategy

  • InlineIdsOrClauseBulkIdStrategy

  • CteValuesListBulkIdStrategy

InlineIdsInClauseBulkIdStrategy

To use this strategy, you need to configure the following configuration property:

<property name="hibernate.hql.bulk_id_strategy"
          value="org.hibernate.hql.spi.id.inline.InlineIdsInClauseBulkIdStrategy"
/>

Now, when running the previous test case, Hibernate generates the following SQL statements:

select
    p.id as id,
    p.companyName as companyName
from
    Person p
where
    p.employed = ?

delete
from
    Engineer
where
        ( id, companyName )
    in (
        ( 1,'Red Hat USA' ),
        ( 3,'Red Hat USA' ),
        ( 1,'Red Hat Europe' ),
        ( 3,'Red Hat Europe' )
    )

delete
from
    Doctor
where
        ( id, companyName )
    in (
        ( 1,'Red Hat USA' ),
        ( 3,'Red Hat USA' ),
        ( 1,'Red Hat Europe' ),
        ( 3,'Red Hat Europe' )
    )

delete
from
    Person
where
        ( id, companyName )
    in (
        ( 1,'Red Hat USA' ),
        ( 3,'Red Hat USA' ),
        ( 1,'Red Hat Europe' ),
        ( 3,'Red Hat Europe' )
    )

So, the entity identifiers are selected first and used for each particular update or delete statement.

The IN clause row value expression has long been supported by Oracle, PostgreSQL, and nowadays by MySQL 5.7. However, SQL Server 2014 does not support this syntax, so you’ll have to use a different strategy.

InlineIdsSubSelectValueListBulkIdStrategy

To use this strategy, you need to configure the following configuration property:

<property name="hibernate.hql.bulk_id_strategy"
          value="org.hibernate.hql.spi.id.inline.InlineIdsSubSelectValueListBulkIdStrategy"
/>

Now, when running the previous test case, Hibernate generates the following SQL statements:

select
    p.id as id,
    p.companyName as companyName
from
    Person p
where
    p.employed = ?

delete
from
    Engineer
where
    ( id, companyName ) in (
        select
            id,
            companyName
        from (
        values
            ( 1,'Red Hat USA' ),
            ( 3,'Red Hat USA' ),
            ( 1,'Red Hat Europe' ),
            ( 3,'Red Hat Europe' )
        ) as HT
            (id, companyName)
    )

delete
from
    Doctor
where
    ( id, companyName ) in (
         select
            id,
            companyName
        from (
        values
            ( 1,'Red Hat USA' ),
            ( 3,'Red Hat USA' ),
            ( 1,'Red Hat Europe' ),
            ( 3,'Red Hat Europe' )
        ) as HT
            (id, companyName)
    )

delete
from
    Person
where
    ( id, companyName ) in (
        select
            id,
            companyName
        from (
        values
            ( 1,'Red Hat USA' ),
            ( 3,'Red Hat USA' ),
            ( 1,'Red Hat Europe' ),
            ( 3,'Red Hat Europe' )
        ) as HT
            (id, companyName)
    )

The underlying database must support the VALUES list clause, like PostgreSQL or SQL Server 2008. However, this strategy requires the IN-clause row value expression for composite identifiers so you can use this strategy only with PostgreSQL.

InlineIdsOrClauseBulkIdStrategy

To use this strategy, you need to configure the following configuration property:

<property name="hibernate.hql.bulk_id_strategy"
          value="org.hibernate.hql.spi.id.inline.InlineIdsOrClauseBulkIdStrategy"
/>

Now, when running the previous test case, Hibernate generates the following SQL statements:

select
    p.id as id,
    p.companyName as companyName
from
    Person p
where
    p.employed = ?

delete
from
    Engineer
where
    ( id = 1 and companyName = 'Red Hat USA' )
or  ( id = 3 and companyName = 'Red Hat USA' )
or  ( id = 1 and companyName = 'Red Hat Europe' )
or  ( id = 3 and companyName = 'Red Hat Europe' )

delete
from
    Doctor
where
    ( id = 1 and companyName = 'Red Hat USA' )
or  ( id = 3 and companyName = 'Red Hat USA' )
or  ( id = 1 and companyName = 'Red Hat Europe' )
or  ( id = 3 and companyName = 'Red Hat Europe' )

delete
from
    Person
where
    ( id = 1 and companyName = 'Red Hat USA' )
or  ( id = 3 and companyName = 'Red Hat USA' )
or  ( id = 1 and companyName = 'Red Hat Europe' )
or  ( id = 3 and companyName = 'Red Hat Europe' )

This strategy has the advantage of being supported by all the major relational database systems (e.g. Oracle, SQL Server, MySQL, and PostgreSQL).

CteValuesListBulkIdStrategy

To use this strategy, you need to configure the following configuration property:

<property name="hibernate.hql.bulk_id_strategy"
          value="org.hibernate.hql.spi.id.inline.CteValuesListBulkIdStrategy"
/>

Now, when running the previous test case, Hibernate generates the following SQL statements:

select
    p.id as id,
    p.companyName as companyName
from
    Person p
where
    p.employed = ?

with HT_Person (id,companyName ) as (
    select id, companyName
    from (
    values
        (?, ?),
        (?, ?),
        (?, ?),
        (?, ?)
    ) as HT (id, companyName) )
delete
from
    Engineer
where
    ( id, companyName ) in (
        select
            id, companyName
        from
            HT_Person
    )

with HT_Person (id,companyName ) as (
    select id, companyName
    from (
    values
        (?, ?),
        (?, ?),
        (?, ?),
        (?, ?)
    ) as HT (id, companyName) )
delete
from
    Doctor
where
    ( id, companyName ) in (
        select
            id, companyName
        from
            HT_Person
    )


with HT_Person (id,companyName ) as (
    select id, companyName
    from (
    values
        (?, ?),
        (?, ?),
        (?, ?),
        (?, ?)
    ) as HT (id, companyName) )
delete
from
    Person
where
    ( id, companyName ) in (
        select
            id, companyName
        from
            HT_Person
    )

The underlying database must support the CTE (Common Table Expressions) that can be referenced from non-query statements as well, like PostgreSQL since 9.1 or SQL Server since 2005. The underlying database must also support the VALUES list clause, like PostgreSQL or SQL Server 2008.

However, this strategy requires the IN-clause row value expression for composite identifiers, so you can only use this strategy only with PostgreSQL.

Conclusion

If you can use temporary tables, that’s probably the best choice. However, if you are not allowed to create temporary tables, you must pick one of these four strategies that works with your underlying database. Before making your mind, you should benchmark which one works best for your current workload. For instance, CTE are optimization fences in PostgreSQL, so make sure you measure before taking a decision.

If you’re using Oracle or MySQL 5.7, you can choose either InlineIdsOrClauseBulkIdStrategy or InlineIdsInClauseBulkIdStrategy. For older version of MySQL, then you can only use InlineIdsOrClauseBulkIdStrategy.

If you’re using SQL Server, InlineIdsOrClauseBulkIdStrategy is the only option for you.

If you’re using PostgreSQL, then you have the luxury of choosing any of these four strategies.

Hibernate Community Newsletter 2/2017

Posted by    |       |    Tagged as Discussions Hibernate ORM

Welcome to the Hibernate community newsletter in which we share blog posts, forum, and StackOverflow questions that are especially relevant to our users.

Interviews

Don’t miss our Hibernate developer interview with Dmitry Alexandrov.

If you want to share your story about Hibernate, let us know, and we can share it with our huge community of passionate developers.

Articles

I was told about a new blog post which proclaims that Lazy loading is a code smell. Well, in my experience, this is exactly the opposite since I’m a strong believer that EAGER fetching is almost always a bad way of fetching data. After reading Sebastian Malaca’s article, I managed to find a very interesting series of article on mixing JPA and DDD (Domain-driven design).

DDD is a great approach. However, trying to treat a relational database as if it were a document store can be very detrimental to application performance. All in all, JPA entities are not the same as DDD entities. In fact, JPA entities are just the persistent state of the Domain Model.

Orlando L Otero wrote a tutorial about implementing a Multitenant architecture on top of Spring, Hibernate, and PostgreSQL. Related to Multitenancy, I found this Microsoft article from 2006 very relevant to the day.

Choosing the right entity identifier strategy requires some knowledge of the underlying JPA provider. For this reason, if you want portability, check out how you can replace the suboptimal TABLE strategy with SEQUENCE or IDENTITY.

Thorben Janssen wrote a short guide which introduces several JPQL query features. For more on this topic, check out the exhaustive JPQL and HQL chapter in the Hibernate 5 User Guide.

Hibernate entity queries are suitable when you want to modify the fetched entities, and taking advantage of the dirty checking mechanism. However, if you want to take advantage of advanced SQL query capabilities, you need native SQL queries. Check out this article to learn why native SQL queries are a Magic Wand.

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