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Getting Started

Doctrine 2 is an object-relational mapper (ORM) for PHP 5.3.0+ that provides transparent persistence for PHP objects. It uses the Data Mapper pattern at the heart of this project, aiming for a complete separation of the domain/business logic from the persistence in a relational database management system. The benefit of Doctrine for the programmer is the ability to focus solely on the object-oriented business logic and worry about persistence only as a secondary task. This doesn't mean persistence is not important to Doctrine 2, however it is our belief that there are considerable benefits for object-oriented programming if persistence and entities are kept perfectly separated.

What are Entities?

Entities are lightweight PHP Objects that don't need to extend any abstract base class or interface. An entity class must not be final or contain final methods. Additionally it must not implement clone nor wakeup or :doc:`do so safely <../cookbook/implementing-wakeup-or-clone>`.

See the :doc:`architecture chapter <../reference/architecture>` for a full list of the restrictions that your entities need to comply with.

An entity contains persistable properties. A persistable property is an instance variable of the entity that is saved into and retrieved from the database by Doctrine's data mapping capabilities.

An Example Model: Bug Tracker

For this Getting Started Guide for Doctrine we will implement the Bug Tracker domain model from the Zend_Db_Table documentation. Reading their documentation we can extract the requirements to be:

  • A Bugs has a description, creation date, status, reporter and engineer
  • A bug can occur on different products (platforms)
  • Products have a name.
  • Bug Reporter and Engineers are both Users of the System.
  • A user can create new bugs.
  • The assigned engineer can close a bug.
  • A user can see all his reported or assigned bugs.
  • Bugs can be paginated through a list-view.

Warning

This tutorial is incrementally building up your Doctrine 2 knowledge and even lets you make some mistakes, to show some common pitfalls in mapping Entities to a database. Don't blindly copy-paste the examples here, it is not production ready without the additional comments and knowledge this tutorial teaches.

A first prototype

A first simplified design for this domain model might look like the following set of classes:

<?php
class Bug
{
    public $id;
    public $description;
    public $created;
    public $status;
    public $products = array();
    public $reporter;
    public $engineer;
}
class Product
{
    public $id;
    public $name;
}
class User
{
    public $id;
    public $name;
    public $reportedBugs = array();
    public $assignedBugs = array();
}

Warning

This is only a prototype, please don't use public properties with Doctrine 2 at all, the "Queries for Application Use-Cases" section shows you why. In combination with proxies public properties can make up for pretty nasty bugs.

Because we will focus on the mapping aspect, no effort is being made to encapsulate the business logic in this example. All persistable properties are public in visibility. We will soon see that this is not the best solution in combination with Doctrine 2, one restriction that actually forces you to encapsulate your properties. For persistence Doctrine 2 actually uses Reflection to access the values in all your entities properties.

Many of the fields are single scalar values, for example the 3 ID fields of the entities, their names, description, status and change dates. Doctrine 2 can easily handle these single values as can any other ORM. From a point of our domain model they are ready to be used right now and we will see at a later stage how they are mapped to the database.

There are also several references between objects in this domain model, whose semantics are discussed case by case at this point to explain how Doctrine handles them. In general each OneToOne or ManyToOne Relation in the Database is replaced by an instance of the related object in the domain model. Each OneToMany or ManyToMany Relation is replaced by a collection of instances in the domain model.

If you think this through carefully you realize Doctrine 2 will load up the complete database in memory if you access one object. However by default Doctrine generates Lazy Load proxies of entities or collections of all the relations that haven't been explicitly retrieved from the database yet.

To be able to use lazyload with collections, simple PHP arrays have to be replaced by a generic collection interface Doctrine which tries to act as array as much as possible using ArrayAccess, IteratorAggregate and Countable interfaces. The class is the most simple implementation of this interface.

Now that we know this, we have to clear up our domain model to cope with the assumptions about related collections:

<?php
use Doctrine\Common\Collections\ArrayCollection;

class Bug
{
    public $products = null;

    public function __construct()
    {
        $this->products = new ArrayCollection();
    }
}

class User
{
    public $reportedBugs = null;
    public $assignedBugs = null;

    public function __construct()
    {
        $this->reportedBugs = new ArrayCollection();
        $this->assignedBugs = new ArrayCollection();
    }
}

Whenever an entity is recreated from the database, an Collection implementation of the type Doctrine is injected into your entity instead of an array. Compared to the ArrayCollection this implementation helps the Doctrine ORM understand the changes that have happened to the collection which are noteworthy for persistence.

Warning

Lazy load proxies always contain an instance of Doctrine's EntityManager and all its dependencies. Therefore a var_dump() will possibly dump a very large recursive structure which is impossible to render and read. You have to use Doctrine\Common\Util\Debug::dump() to restrict the dumping to a human readable level. Additionally you should be aware that dumping the EntityManager to a Browser may take several minutes, and the Debug::dump() method just ignores any occurrences of it in Proxy instances.

Because we only work with collections for the references we must be careful to implement a bidirectional reference in the domain model. The concept of owning or inverse side of a relation is central to this notion and should always be kept in mind. The following assumptions are made about relations and have to be followed to be able to work with Doctrine 2. These assumptions are not unique to Doctrine 2 but are best practices in handling database relations and Object-Relational Mapping.

  • Changes to Collections are saved or updated, when the entity on the owning side of the collection is saved or updated.
  • Saving an Entity at the inverse side of a relation never triggers a persist operation to changes to the collection.
  • In a one-to-one relation the entity holding the foreign key of the related entity on its own database table is always the owning side of the relation.
  • In a many-to-many relation, both sides can be the owning side of the relation. However in a bi-directional many-to-many relation only one is allowed to be.
  • In a many-to-one relation the Many-side is the owning side by default, because it holds the foreign key.
  • The OneToMany side of a relation is inverse by default, since the foreign key is saved on the Many side. A OneToMany relation can only be the owning side, if its implemented using a ManyToMany relation with join table and restricting the one side to allow only UNIQUE values per database constraint.

Note

Consistency of bi-directional references on the inverse side of a relation have to be managed in userland application code. Doctrine cannot magically update your collections to be consistent.

In the case of Users and Bugs we have references back and forth to the assigned and reported bugs from a user, making this relation bi-directional. We have to change the code to ensure consistency of the bi-directional reference:

<?php
class Bug
{
    private $engineer;
    private $reporter;

    public function setEngineer($engineer)
    {
        $engineer->assignedToBug($this);
        $this->engineer = $engineer;
    }

    public function setReporter($reporter)
    {
        $reporter->addReportedBug($this);
        $this->reporter = $reporter;
    }

    public function getEngineer()
    {
        return $this->engineer;
    }

    public function getReporter()
    {
        return $this->reporter;
    }
}
class User
{
    private $reportedBugs = null;
    private $assignedBugs = null;

    public function addReportedBug($bug)
    {
        $this->reportedBugs[] = $bug;
    }

    public function assignedToBug($bug)
    {
        $this->assignedBugs[] = $bug;
    }
}

I chose to name the inverse methods in past-tense, which should indicate that the actual assigning has already taken place and the methods are only used for ensuring consistency of the references. You can see from User::addReportedBug() and User::assignedToBug() that using this method in userland alone would not add the Bug to the collection of the owning side in Bug::$reporter or Bug::$engineer. Using these methods and calling Doctrine for persistence would not update the collections representation in the database.

Only using Bug::setEngineer() or Bug::setReporter() correctly saves the relation information. We also set both collection instance variables to protected, however with PHP 5.3's new features Doctrine is still able to use Reflection to set and get values from protected and private properties.

The Bug::$reporter and Bug::$engineer properties are Many-To-One relations, which point to a User. In a normalized relational model the foreign key is saved on the Bug's table, hence in our object-relation model the Bug is at the owning side of the relation. You should always make sure that the use-cases of your domain model should drive which side is an inverse or owning one in your Doctrine mapping. In our example, whenever a new bug is saved or an engineer is assigned to the bug, we don't want to update the User to persist the reference, but the Bug. This is the case with the Bug being at the owning side of the relation.

Bugs reference Products by a uni-directional ManyToMany relation in the database that points from from Bugs to Products.

<?php
class Bug
{
    private $products = null;

    public function assignToProduct($product)
    {
        $this->products[] = $product;
    }

    public function getProducts()
    {
        return $this->products;
    }
}

We are now finished with the domain model given the requirements. From the simple model with public properties only we had to do quite some work to get to a model where we encapsulated the references between the objects to make sure we don't break its consistent state when using Doctrine.

However up to now the assumptions Doctrine imposed on our business objects have not restricting us much in our domain modelling capabilities. Actually we would have encapsulated access to all the properties anyways by using object-oriented best-practices.

Metadata Mappings for our Entities

Up to now we have only implemented our Entities as Data-Structures without actually telling Doctrine how to persist them in the database. If perfect in-memory databases would exist, we could now finish the application using these entities by implementing code to fulfil all the requirements. However the world isn't perfect and we have to persist our entities in some storage to make sure we don't loose their state. Doctrine currently serves Relational Database Management Systems. In the future we are thinking to support NoSQL vendors like CouchDb or MongoDb, however this is still far in the future.

The next step for persistence with Doctrine is to describe the structure of our domain model entities to Doctrine using a metadata language. The metadata language describes how entities, their properties and references should be persisted and what constraints should be applied to them.

Metadata for entities are loaded using a Doctrine\ORM\Mapping\Driver\Driver implementation and Doctrine 2 already comes with XML, YAML and Annotations Drivers. This Getting Started Guide will show the mappings for all Mapping Drivers. References in the text will be made to the XML mapping.

Since we haven't namespaced our three entities, we have to implement three mapping files called Bug.dcm.xml, Product.dcm.xml and User.dcm.xml (or .yml) and put them into a distinct folder for mapping configurations. For the annotations driver we need to use doc-block comments on the entity classes themselves.

The first discussed definition will be for the Product, since it is the most simple one:

The top-level entity definition tag specifies information about the class and table-name. The primitive type Product::$name is defined as field attributes. The Id property is defined with the id tag. The id has a generator tag nested inside which defines that the primary key generation mechanism automatically uses the database platforms native id generation strategy, for example AUTO INCREMENT in the case of MySql or Sequences in the case of PostgreSql and Oracle.

We then go on specifying the definition of a Bug:

Here again we have the entity, id and primitive type definitions. The column names are used from the Zend_Db_Table examples and have different names than the properties on the Bug class. Additionally for the "created" field it is specified that it is of the Type "DATETIME", which translates the YYYY-mm-dd HH:mm:ss Database format into a PHP DateTime instance and back.

After the field definitions the two qualified references to the user entity are defined. They are created by the many-to-one tag. The class name of the related entity has to be specified with the target-entity attribute, which is enough information for the database mapper to access the foreign-table. Since reporter and engineer are on the owning side of a bi-directional relation we also have to specify the inversed-by attribute. They have to point to the field names on the inverse side of the relationship. We will see in the next example that the inversed-by attribute has a counterpart mapped-by which makes that the inverse side.

The last missing property is the Bug::$products collection. It holds all products where the specific bug is occurring in. Again you have to define the target-entity and field attributes on the many-to-many tag. Furthermore you have to specify the details of the many-to-many join-table and its foreign key columns. The definition is rather complex, however relying on the XML auto-completion I got it working easily, although I forget the schema details all the time.

The last missing definition is that of the User entity:

Here are some new things to mention about the one-to-many tags. Remember that we discussed about the inverse and owning side. Now both reportedBugs and assignedBugs are inverse relations, which means the join details have already been defined on the owning side. Therefore we only have to specify the property on the Bug class that holds the owning sides.

This example has a fair overview of the most basic features of the metadata definition language.

Obtaining the EntityManager

Doctrine's public interface is the EntityManager, it provides the access point to the complete lifecycle management of your entities and transforms entities from and back to persistence. You have to configure and create it to use your entities with Doctrine 2. I will show the configuration steps and then discuss them step by step:

<?php
// Setup Autoloader (1)
// See :doc:`Configuration <../reference/configuration>` for up to date autoloading details.

$config = new Doctrine\ORM\Configuration(); // (2)

// Proxy Configuration (3)
$config->setProxyDir(__DIR__.'/lib/MyProject/Proxies');
$config->setProxyNamespace('MyProject\Proxies');
$config->setAutoGenerateProxyClasses((APPLICATION_ENV == "development"));

// Mapping Configuration (4)
$driverImpl = new Doctrine\ORM\Mapping\Driver\XmlDriver(__DIR__."/config/mappings/xml");
//$driverImpl = new Doctrine\ORM\Mapping\Driver\XmlDriver(__DIR__."/config/mappings/yml");
//$driverImpl = $config->newDefaultAnnotationDriver(__DIR__."/entities");
$config->setMetadataDriverImpl($driverImpl);

// Caching Configuration (5)
if (APPLICATION_ENV == "development") {
    $cache = new \Doctrine\Common\Cache\ArrayCache();
} else {
    $cache = new \Doctrine\Common\Cache\ApcCache();
}
$config->setMetadataCacheImpl($cache);
$config->setQueryCacheImpl($cache);

// database configuration parameters (6)
$conn = array(
    'driver' => 'pdo_sqlite',
    'path' => __DIR__ . '/db.sqlite',
);

// obtaining the entity manager (7)
$evm = new Doctrine\Common\EventManager()
$entityManager = \Doctrine\ORM\EntityManager::create($conn, $config, $evm);

The first block sets up the autoloading capabilities of Doctrine. I am registering the Doctrine namespace to the given path. To add your own namespace you can instantiate another ClassLoader with different namespace and path arguments. There is no requirement to use the Doctrine ClassLoader for your autoloading needs, you can use whatever suits you best.

The second block contains of the instantiation of the ORM Configuration object. Besides the configuration shown in the next blocks there are several others with are all explained in the :doc:`Configuration section of the manual <../reference/configuration>`.

The Proxy Configuration is a required block for your application, you have to specify where Doctrine writes the PHP code for Proxy Generation. Proxies are children of your entities generated by Doctrine to allow for type-safe lazy loading. We will see in a later chapter how exactly this works. Besides the path to the proxies we also specify which namespace they will reside under as well as a flag autoGenerateProxyClasses indicating that proxies should be re-generated on each request, which is recommended for development. In production this should be prevented at all costs, the proxy class generation can be quite costly.

The fourth block contains the mapping driver details. We will use XML Mapping in this example, so we configure the XmlDriver instance with a path to mappings configuration folder where we put the Bug.dcm.xml, Product.dcm.xml and User.dcm.xml.

In the 5th block the caching configuration is set. In production we use caching only on a per request-basis using the ArrayCache. In production it is literally required to use Apc, Memcache or XCache to get the full speed out of Doctrine. Internally Doctrine uses caching heavily for the Metadata and DQL Query Language so make sure you use a caching mechanism.

The 6th block shows the configuration options required to connect to a database, in my case a file-based sqlite database. All the configuration options for all the shipped drivers are given in the DBAL Configuration section of the manual.

The last block shows how the EntityManager is obtained from a factory method, Here we also pass in an EventManager instance which is optional. However using the EventManager you can hook in to the lifecycle of entities, which is a common use-case, so you know how to configure it already.

Generating the Database Schema

Now that we have defined the Metadata Mappings and bootstrapped the EntityManager we want to generate the relational database schema from it. Doctrine has a Command-Line-Interface that allows you to access the SchemaTool, a component that generates the required tables to work with the metadata.

For the command-line tool to work a cli-config.php file has to be present in the project root directory, where you will execute the doctrine command. Its a fairly simple file:

<?php
$helperSet = new \Symfony\Component\Console\Helper\HelperSet(array(
    'em' => new \Doctrine\ORM\Tools\Console\Helper\EntityManagerHelper($entityManager)
));

You can then change into your project directory and call the Doctrine command-line tool:

doctrine@my-desktop> cd myproject/
doctrine@my-desktop> doctrine orm:schema-tool:create

Note

The doctrine command will only be present if you installed Doctrine from PEAR. Otherwise you will have to dig into the bin/doctrine.php code of your Doctrine 2 directory to setup your doctrine command-line client.

See the :doc:`Tools section of the manual <../reference/tools>` on how to setup the Doctrine console correctly.

During the development you probably need to re-create the database several times when changing the Entity metadata. You can then either re-create the database:

doctrine@my-desktop> doctrine orm:schema-tool:drop --force
doctrine@my-desktop> doctrine orm:schema-tool:create

Or use the update functionality:

doctrine@my-desktop> doctrine orm:schema-tool:update --force

The updating of databases uses a Diff Algorithm for a given Database Schema, a cornerstone of the Doctrine\DBAL package, which can even be used without the Doctrine ORM package. However its not available in SQLite since it does not support ALTER TABLE.

Writing Entities into the Database

Having created the schema we can now start and save entities in the database. For starters we need a create user use-case:

<?php
$newUsername = "beberlei";

$user = new User();
$user->name = $newUsername;

$entityManager->persist($user);
$entityManager->flush();

Products can also be created:

<?php
$newProductName = "My Product";

$product = new Product();
$product->name = $newProductName;

$entityManager->persist($product);
$entityManager->flush();

So what is happening in those two snippets? In both examples the class creation is pretty standard, the interesting bits are the communication with the EntityManager. To notify the EntityManager that a new entity should be inserted into the database you have to call persist(). However the EntityManager does not act on this, its merely notified. You have to explicitly call flush() to have the EntityManager write those two entities to the database.

You might wonder why does this distinction between persist notification and flush exist? Doctrine 2 uses the UnitOfWork pattern to aggregate all writes (INSERT, UDPATE, DELETE) into one single fast transaction, which is executed when flush is called. Using this approach the write-performance is significantly faster than in a scenario where updates are done for each entity in isolation. In more complex scenarios than the previous two, you are free to request updates on many different entities and all flush them at once.

Doctrine's UnitOfWork detects entities that have changed after retrieval from the database automatically when the flush operation is called, so that you only have to keep track of those entities that are new or to be removed and pass them to EntityManager#persist() and EntityManager#remove() respectively. This comparison to find dirty entities that need updating is using a very efficient algorithm that has almost no additional memory overhead and can even save you computing power by only updating those database columns that really changed.

We are now getting to the "Create a New Bug" requirement and the code for this scenario may look like this:

<?php
$reporter = $entityManager->find("User", $theReporterId);
$engineer = $entityManager->find("User", $theDefaultEngineerId);

$bug = new Bug();
$bug->description = "Something does not work!";
$bug->created = new DateTime("now");
$bug->status = "NEW";

foreach ($productIds AS $productId) {
    $product = $entityManager->find("Product", $productId);
    $bug->assignToProduct($product);
}

$bug->setReporter($reporter);
$bug->setEngineer($engineer);

$entityManager->persist($bug);
$entityManager->flush();

echo "Your new Bug Id: ".$bug->id."\n";

This is the first contact with the read API of the EntityManager, showing that a call to EntityManager#find($name, $id) returns a single instance of an entity queried by primary key. Besides this we see the persist + flush pattern again to save the Bug into the database.

See how simple relating Bug, Reporter, Engineer and Products is done by using the discussed methods in the "A first prototype" section. The UnitOfWork will detect this relations when flush is called and relate them in the database appropriately.

Queries for Application Use-Cases

List of Bugs

Using the previous examples we can fill up the database quite a bit, however we now need to discuss how to query the underlying mapper for the required view representations. When opening the application, bugs can be paginated through a list-view, which is the first read-only use-case:

<?php
$dql = "SELECT b, e, r FROM Bug b JOIN b.engineer e JOIN b.reporter r ORDER BY b.created DESC";

$query = $entityManager->createQuery($dql);
$query->setMaxResults(30);
$bugs = $query->getResult();

foreach($bugs AS $bug) {
    echo $bug->description." - ".$bug->created->format('d.m.Y')."\n";
    echo "    Reported by: ".$bug->getReporter()->name."\n";
    echo "    Assigned to: ".$bug->getEngineer()->name."\n";
    foreach($bug->getProducts() AS $product) {
        echo "    Platform: ".$product->name."\n";
    }
    echo "\n";
}

The DQL Query in this example fetches the 30 most recent bugs with their respective engineer and reporter in one single SQL statement. The console output of this script is then:

Something does not work! - 02.04.2010
    Reported by: beberlei
    Assigned to: beberlei
    Platform: My Product

Note

Dql is not Sql

You may wonder why we start writing SQL at the beginning of this use-case. Don't we use an ORM to get rid of all the endless hand-writing of SQL? Doctrine introduces DQL which is best described as object-query-language and is a dialect of OQL and similar to HQL or JPQL. It does not know the concept of columns and tables, but only those of Entity-Class and property. Using the Metadata we defined before it allows for very short distinctive and powerful queries.

An important reason why DQL is favourable to the Query API of most ORMs is its similarity to SQL. The DQL language allows query constructs that most ORMs don't, GROUP BY even with HAVING, Sub-selects, Fetch-Joins of nested classes, mixed results with entities and scalar data such as COUNT() results and much more. Using DQL you should seldom come to the point where you want to throw your ORM into the dumpster, because it doesn't support some the more powerful SQL concepts.

Besides handwriting DQL you can however also use the QueryBuilder retrieved by calling $entityManager->createQueryBuilder() which is a Query Object around the DQL language.

As a last resort you can however also use Native SQL and a description of the result set to retrieve entities from the database. DQL boils down to a Native SQL statement and a ResultSetMapping instance itself. Using Native SQL you could even use stored procedures for data retrieval, or make use of advanced non-portable database queries like PostgreSql's recursive queries.

Array Hydration of the Bug List

In the previous use-case we retrieved the result as their respective object instances. We are not limited to retrieving objects only from Doctrine however. For a simple list view like the previous one we only need read access to our entities and can switch the hydration from objects to simple PHP arrays instead. This can obviously yield considerable performance benefits for read-only requests.

Implementing the same list view as before using array hydration we can rewrite our code:

<?php
$dql = "SELECT b, e, r, p FROM Bug b JOIN b.engineer e ".
       "JOIN b.reporter r JOIN b.products p ORDER BY b.created DESC";
$query = $entityManager->createQuery($dql);
$bugs = $query->getArrayResult();

foreach ($bugs AS $bug) {
    echo $bug['description'] . " - " . $bug['created']->format('d.m.Y')."\n";
    echo "    Reported by: ".$bug['reporter']['name']."\n";
    echo "    Assigned to: ".$bug['engineer']['name']."\n";
    foreach($bug['products'] AS $product) {
        echo "    Platform: ".$product['name']."\n";
    }
    echo "\n";
}

There is one significant difference in the DQL query however, we have to add an additional fetch-join for the products connected to a bug. The resulting SQL query for this single select statement is pretty large, however still more efficient to retrieve compared to hydrating objects.

Find by Primary Key

The next Use-Case is displaying a Bug by primary key. This could be done using DQL as in the previous example with a where clause, however there is a convenience method on the Entity Manager that handles loading by primary key, which we have already seen in the write scenarios:

<?php
$bug = $entityManager->find("Bug", (int)$theBugId);

However we will soon see another problem with our entities using this approach. Try displaying the engineer's name:

<?php
echo "Bug: ".$bug->description."\n";
echo "Engineer: ".$bug->getEngineer()->name."\n";

It will be null! What is happening? It worked in the previous example, so it can't be a problem with the persistence code of Doctrine. What is it then? You walked in the public property trap.

Since we only retrieved the bug by primary key both the engineer and reporter are not immediately loaded from the database but are replaced by LazyLoading proxies. Sample code of this proxy generated code can be found in the specified Proxy Directory, it looks like:

<?php
namespace MyProject\Proxies;

/**
 * THIS CLASS WAS GENERATED BY THE DOCTRINE ORM. DO NOT EDIT THIS FILE.
 */
class UserProxy extends \User implements \Doctrine\ORM\Proxy\Proxy
{
    // .. lazy load code here

    public function addReportedBug($bug)
    {
        $this->_load();
        return parent::addReportedBug($bug);
    }

    public function assignedToBug($bug)
    {
        $this->_load();
        return parent::assignedToBug($bug);
    }
}

See how upon each method call the proxy is lazily loaded from the database? Using public properties however we never call a method and Doctrine has no way to hook into the PHP Engine to detect a direct access to a public property and trigger the lazy load. We need to rewrite our entities, make all the properties private or protected and add getters and setters to get a working example:

<?php
echo "Bug: ".$bug->getDescription()."\n";
echo "Engineer: ".$bug->getEngineer()->getName()."\n";

/**
Bug: Something does not work!
Engineer: beberlei
*/

Being required to use private or protected properties Doctrine 2 actually enforces you to encapsulate your objects according to object-oriented best-practices.

Dashboard of the User

For the next use-case we want to retrieve the dashboard view, a list of all open bugs the user reported or was assigned to. This will be achieved using DQL again, this time with some WHERE clauses and usage of bound parameters:

<?php
$dql = "SELECT b, e, r FROM Bug b JOIN b.engineer e JOIN b.reporter r ".
       "WHERE b.status = 'OPEN' AND e.id = ?1 OR r.id = ?1 ORDER BY b.created DESC";

$myBugs = $entityManager->createQuery($dql)
                        ->setParameter(1, $theUserId)
                        ->setMaxResults(15)
                        ->getResult();

foreach ($myBugs AS $bug) {
    echo $bug->getDescription()."\n";
}

That is it for the read-scenarios of this example, we will continue with the last missing bit, engineers being able to close a bug.

Number of Bugs

Until now we only retrieved entities or their array representation. Doctrine also supports the retrieval of non-entities through DQL. These values are called "scalar result values" and may even be aggregate values using COUNT, SUM, MIN, MAX or AVG functions.

We will need this knowledge to retrieve the number of open bugs grouped by product:

<?php
$dql = "SELECT p.id, p.name, count(b.id) AS openBugs FROM Bug b ".
       "JOIN b.products p WHERE b.status = 'OPEN' GROUP BY p.id";
$productBugs = $entityManager->createQuery($dql)->getScalarResult();

foreach($productBugs as $productBug) {
    echo $productBug['name']." has " . $productBug['openBugs'] . " open bugs!\n";
}

Updating Entities

There is a single use-case missing from the requirements, Engineers should be able to close a bug. This looks like:

<?php
$bug = $entityManager->find("Bug", (int)$theBugId);
$bug->close();

$entityManager->flush();

When retrieving the Bug from the database it is inserted into the IdentityMap inside the UnitOfWork of Doctrine. This means your Bug with exactly this id can only exist once during the whole request no matter how often you call EntityManager#find(). It even detects entities that are hydrated using DQL and are already present in the Identity Map.

When flush is called the EntityManager loops over all the entities in the identity map and performs a comparison between the values originally retrieved from the database and those values the entity currently has. If at least one of these properties is different the entity is scheduled for an UPDATE against the database. Only the changed columns are updated, which offers a pretty good performance improvement compared to updating all the properties.

Entity Repositories

For now we have not discussed how to separate the Doctrine query logic from your model. In Doctrine 1 there was the concept of Doctrine_Table instances for this seperation. The similar concept in Doctrine2 is called Entity Repositories, integrating the repository pattern at the heart of Doctrine.

Every Entity uses a default repository by default and offers a bunch of convenience methods that you can use to query for instances of that Entity. Take for example our Product entity. If we wanted to Query by name, we can use:

<?php
$product = $entityManager->getRepository('Product')
                         ->findOneBy(array('name' => $productName));

The method findOneBy() takes an array of fields or association keys and the values to match against.

If you want to find all entities matching a condition you can use findBy(), for example querying for all closed bugs:

<?php
$bugs = $entityManager->getRepository('Bug')
                      ->findBy(array('status' => 'CLOSED'));

foreach ($bugs AS $bug) {
    // do stuff
}

Compared to DQL these query methods are falling short of functionality very fast. Doctrine offers you a convenient way to extend the functionalities of the default EntityRepository and put all the specialized DQL query logic on it. For this you have to create a subclass of Doctrine\ORM\EntityRepository, in our case a BugRepository and group all the previoiusly discussed query functionality in it:

<?php

use Doctrine\ORM\EntityRepository;

class BugRepository extends EntityRepository
{
    public function getRecentBugs($number = 30)
    {
        $dql = "SELECT b, e, r FROM Bug b JOIN b.engineer e JOIN b.reporter r ORDER BY b.created DESC";

        $query = $this->getEntityManager()->createQuery($dql);
        $query->setMaxResults($number);
        return $query->getResult();
    }

    public function getRecentBugsArray($number = 30)
    {
        $dql = "SELECT b, e, r, p FROM Bug b JOIN b.engineer e ".
               "JOIN b.reporter r JOIN b.products p ORDER BY b.created DESC";
        $query = $this->getEntityManager()->createQuery($dql);
        $query->setMaxResults($number);
        return $query->getArrayResult();
    }

    public function getUsersBugs($userId, $number = 15)
    {
        $dql = "SELECT b, e, r FROM Bug b JOIN b.engineer e JOIN b.reporter r ".
               "WHERE b.status = 'OPEN' AND e.id = ?1 OR r.id = ?1 ORDER BY b.created DESC";

        return $this->getEntityManager()->createQuery($dql)
                             ->setParameter(1, $userId)
                             ->setMaxResults($number)
                             ->getResult();
    }

    public function getOpenBugsByProduct()
    {
        $dql = "SELECT p.id, p.name, count(b.id) AS openBugs FROM Bug b ".
               "JOIN b.products p WHERE b.status = 'OPEN' GROUP BY p.id";
        return $this->getEntityManager()->createQuery($dql)->getScalarResult();
    }
}

To be able to use this query logic through $this->getEntityManager()->getRepository('Bug') we have to adjust the metadata slightly.

Now we can remove our query logic in all the places and instead use them through the EntityRepository. As an example here is the code of the first use case "List of Bugs":

<?php
$bugs = $entityManager->getRepository('Bug')->getRecentBugs();

foreach($bugs AS $bug) {
    echo $bug->description." - ".$bug->created->format('d.m.Y')."\n";
    echo "    Reported by: ".$bug->getReporter()->name."\n";
    echo "    Assigned to: ".$bug->getEngineer()->name."\n";
    foreach($bug->getProducts() AS $product) {
        echo "    Platform: ".$product->name."\n";
    }
    echo "\n";
}

Using EntityRepositories you can avoid coupling your model with specific query logic. You can also re-use query logic easily throughout your application.

Conclusion

This tutorial is over here, I hope you had fun. Additional content will be added to this tutorial incrementally, topics will include:

  • More on Association Mappings
  • Lifecycle Events triggered in the UnitOfWork
  • Ordering of Collections

Additional details on all the topics discussed here can be found in the respective manual chapters.

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