Getting Started with Doctrine¶
This guide covers getting started with the Doctrine ORM. After working through the guide you should know:
How to install and configure Doctrine by connecting it to a database
Doctrine をデータベースに接続してインストールおよび設定する方法Mapping PHP objects to database tables
PHP オブジェクトをデータベース テーブルにマッピングするGenerating a database schema from PHP objects
PHP オブジェクトからデータベース スキーマを生成するUsing the
EntityManagerto insert, update, delete and find objects in the database.EntityManager を使用して、データベース内のオブジェクトを挿入、更新、削除、および検索します。
Guide Assumptions¶
This guide is designed for beginners that haven’t worked with Doctrine ORM before. There are some prerequisites for the tutorial that have to be installed:
PHP (latest stable version)
PHP (最新の安定版)Composer Package Manager (Install Composer)
Composer パッケージ マネージャー (Composer のインストール)
The code of this tutorial is available on Github.
What is Doctrine?¶
Doctrine ORM is an object-relational mapper (ORM) for PHP 7.1+ that provides transparent persistence for PHP objects. It uses the Data Mapper pattern at the heart, aiming for a complete separation of your domain/business logic from the persistence in a relational database management system.
The benefit of Doctrine for the programmer is the ability to focus on the object-oriented business logic and worry about persistence only as a secondary problem. This doesn’t mean persistence is downplayed by Doctrine 2, however it is our belief that there are considerable benefits for object-oriented programming if persistence and entities are kept separated.
What are Entities?¶
Entities are PHP Objects that can be identified over many requests by a unique identifier or primary key. These classes don’t need to extend any abstract base class or interface.
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 entity class must not be final nor read-only, although it can contain final methods or read-only properties.
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:
A Bug has a description, creation date, status, reporter and engineer
バグには、説明、作成日、ステータス、レポーター、およびエンジニアがあります。A Bug can occur on different Products (platforms)
異なる製品 (プラットフォーム) でバグが発生する可能性がありますA Product has a name.
製品には名前があります。Bug reporters and engineers are both Users of the system.
バグ報告者とエンジニアはどちらもシステムのユーザーです。A User can create new Bugs.
ユーザーは新しいバグを作成できます。The assigned engineer can close a Bug.
割り当てられたエンジニアはバグをクローズできます。A User can see all their reported or assigned Bugs.
ユーザーは、報告または割り当てられたすべてのバグを表示できます。Bugs can be paginated through a list-view.
バグは、リスト ビューを介してページ付けできます。
Project Setup¶
Create a new empty folder for this tutorial project, for example
doctrine2-tutorial and create a new file composer.json inside
that directory with the following contents:
{
"require": {
"doctrine/orm": "^2.11.0",
"doctrine/dbal": "^3.2",
"symfony/yaml": "^5.4",
"symfony/cache": "^5.4"
},
"autoload": {
"psr-0": {"": "src/"}
}
}
Install Doctrine using the Composer Dependency Management tool, by calling:
$ composer install
This will install the packages Doctrine Common, Doctrine DBAL, Doctrine ORM,
into the vendor directory.
Add the following directories:
doctrine2-tutorial
|-- config
| `-- xml
| `-- yaml
`-- src
Note
The YAML driver is deprecated and will be removed in version 3.0. It is strongly recommended to switch to one of the other mappings.
Note
It is strongly recommended that you require doctrine/dbal in your
composer.json as well, because using the ORM means mapping objects
and their fields to database tables and their columns, and that
requires mentioning so-called types that are defined in doctrine/dbal
in your application. Having an explicit requirement means you control
when the upgrade to the next major version happens, so that you can
do the necessary changes in your application beforehand.
Obtaining the EntityManager¶
Doctrine’s public interface is through the EntityManager. This class
provides access points to the complete lifecycle management for your entities,
and transforms entities from and back to persistence. You have to
configure and create it to use your entities with Doctrine ORM. I
will show the configuration steps and then discuss them step by
step:
<?php
// bootstrap.php
use Doctrine\DBAL\DriverManager;
use Doctrine\ORM\EntityManager;
use Doctrine\ORM\ORMSetup;
require_once "vendor/autoload.php";
// Create a simple "default" Doctrine ORM configuration for Attributes
$config = ORMSetup::createAttributeMetadataConfiguration(
paths: array(__DIR__."/src"),
isDevMode: true,
);
// or if you prefer annotation, YAML or XML
// $config = ORMSetup::createAnnotationMetadataConfiguration(
// paths: array(__DIR__."/src"),
// isDevMode: true,
// );
// $config = ORMSetup::createXMLMetadataConfiguration(
// paths: array(__DIR__."/config/xml"),
// isDevMode: true,
//);
// $config = ORMSetup::createYAMLMetadataConfiguration(
// paths: array(__DIR__."/config/yaml"),
// isDevMode: true,
// );
// configuring the database connection
$connection = DriverManager::getConnection([
'driver' => 'pdo_sqlite',
'path' => __DIR__ . '/db.sqlite',
], $config)
// obtaining the entity manager
$entityManager = new EntityManager($connection, $config);
Note
The YAML driver is deprecated and will be removed in version 3.0. It is strongly recommended to switch to one of the other mappings.
The require_once statement sets up the class autoloading for Doctrine and
its dependencies using Composer’s autoloader.
The second block consists of the instantiation of the ORM
Configuration object using the ORMSetup helper. It assumes a bunch
of defaults that you don’t have to bother about for now. You can
read up on the configuration details in the
reference chapter on configuration.
The third block shows the configuration options required to connect to a database. In this case, we’ll use a file-based SQLite database. All the configuration options for all the shipped drivers are given in the DBAL Configuration section of the manual.
The last block shows how the EntityManager is obtained from a
factory method.
Generating the Database Schema¶
Doctrine has a command-line interface that allows you to access the SchemaTool, a component that can generate a relational database schema based entirely on the defined entity classes and their metadata. For this tool to work, you need to create an executable console script as described in the tools chapter.
If you created the bootstrap.php file as described in the previous section,
that script could look like this:
#!/usr/bin/env php
<?php
// bin/doctrine
use Doctrine\ORM\Tools\Console\ConsoleRunner;
use Doctrine\ORM\Tools\Console\EntityManagerProvider\SingleManagerProvider;
// Adjust this path to your actual bootstrap.php
require __DIR__ . 'path/to/your/bootstrap.php';
ConsoleRunner::run(
new SingleManagerProvider($entityManager)
);
In the following examples, we will assume that this script has been created as
bin/doctrine.
$ php bin/doctrine orm:schema-tool:create
Since we haven’t added any entity metadata in src yet, you’ll see a message
stating “No Metadata Classes to process.” In the next section, we’ll create a
Product entity along with the corresponding metadata, and run this command again.
Note that as you modify your entities’ metadata during the development process, you’ll need to update your database schema to stay in sync with the metadata. You can easily recreate the database using the following commands:
$ php bin/doctrine orm:schema-tool:drop --force
$ php bin/doctrine orm:schema-tool:create
Or you can use the update functionality:
$ php bin/doctrine orm:schema-tool:update --force
The updating of databases uses a diff algorithm for a given
database schema. This is a cornerstone of the Doctrine\DBAL package,
which can even be used without the Doctrine ORM package.
Starting with the Product Entity¶
We start with the simplest entity, the Product. Create a src/Product.php file to contain the Product
entity definition:
<?php
// src/Product.php
class Product
{
private int|null $id = null;
private string $name;
}
When creating entity classes, all of the fields should be private.
Use protected when strictly needed and very rarely if not ever public.
Adding behavior to Entities¶
There are two options to define methods in entities: getters/setters, or mutators and DTOs, respectively for anemic entities or rich entities.
Anemic entities: Getters and setters
The most popular method is to create two kinds of methods to read (getter) and update (setter) the object’s properties.
The id field has no setter since, generally speaking, your code should not set this value since it represents a database id value. (Note that Doctrine itself can still set the value using the Reflection API instead of a defined setter function.)
Note
Doctrine ORM does not use any of the methods you defined: it uses
reflection to read and write values to your objects, and will never
call methods, not even __construct.
This approach is mostly used when you want to focus on behavior-less entities, and when you want to have all your business logic in your services rather than in the objects themselves.
Getters and setters are a common convention which makes it possible to expose each field of your entity to the external world, while allowing you to keep some type safety in place.
Such an approach is a good choice for RAD (rapid application development), but may lead to problems later down the road, because providing such an easy way to modify any field in your entity means that the entity itself cannot guarantee validity of its internal state. Having any object in invalid state is dangerous:
An invalid state can bring bugs in your business logic.
無効な状態は、ビジネス ロジックにバグをもたらす可能性があります。The state can be implicitly saved in the database: any forgotten
flushcan persist the broken state.状態はデータベースに暗黙的に保存できます。忘れたフラッシュは壊れた状態を保持できます。If persisted, the corrupted data will be retrieved later in your application when the data is loaded again, thereby leading to bugs in your business logic.
永続化された場合、破損したデータは後でデータが再度読み込まれたときにアプリケーションで取得されるため、ビジネス ロジックにバグが発生します。When bugs occur after corrupted data is persisted, troubleshooting will become much harder, and you might be aware of the bug too late to fix it in a proper manner.
破損したデータが残った後にバグが発生すると、トラブルシューティングが非常に困難になり、適切な方法で修正するには遅すぎるバグに気付く可能性があります。
implicitly saved in database, thereby leading to corrupted or inconsistent data in your storage, and later in your application when the data is loaded again.
Note
This method, although very common, is inappropriate for Domain Driven Design (DDD <https://en.wikipedia.org/wiki/Domain-driven_design>) where methods should represent real business operations and not simple property change, And business invariants should be maintained both in the application state (entities in this case) and in the database, with no space for data corruption.
Here is an example of a simple anemic entity:
In the example above, we avoid all possible logic in the entity and only care about putting and retrieving data into it without validation (except the one provided by type-hints) nor consideration about the object’s state.
As Doctrine ORM is a persistence tool for your domain, the state of an object is really important. This is why we strongly recommend using rich entities.
Rich entities: Mutators and DTOs
We recommend using a rich entity design and rely on more complex mutators, and if needed based on DTOs. In this design, you should not use getters nor setters, and instead, implement methods that represent the behavior of your domain.
For example, when having a User entity, we could foresee
the following kind of optimization.
Example of a rich entity with proper accessors and mutators:
Note
Please note that this example is only a stub. When going further in the documentation, we will update this object with more behavior and maybe update some methods.
The entities should only mutate state after checking that all business logic
invariants are being respected.
Additionally, our entities should never see their state change without
validation. For example, creating a new Product() object without any data
makes it an invalid object.
Rich entities should represent behavior, not data, therefore
they should be valid even after a __construct() call.
To help creating such objects, we can rely on DTOs, and/or make
our entities always up-to-date. This can be performed with static constructors,
or rich mutators that accept DTOs as parameters.
The role of the DTO is to maintain the entity’s state and to help us rely
upon objects that correctly represent the data that is used to mutate the
entity.
Note
A DTO <https://en.wikipedia.org/wiki/Data_transfer_object> is an object
that only carries data without any logic. Its only goal is to be transferred
from one service to another.
A DTO often represents data sent by a client and that has to be validated,
but can also be used as simple data carrier for other cases.
By using DTOs, if we take our previous User example, we could create
a ProfileEditingForm DTO that will be a plain model, totally unrelated to
our database, that will be populated via a form and validated.
Then we can add a new mutator to our User:
There are several advantages to using such a model:
Entity state is always valid. Since no setters exist, this means that we
エンティティの状態は常に有効です。セッターが存在しないため、これは次のことを意味します。
only update portions of the entity that should already be valid.
Instead of having plain getters and setters, our entity now has
プレーンなゲッターとセッターの代わりに、私たちのエンティティは
real behavior: it is much easier to determine the logic in the domain.
DTOs can be reused in other components, for example deserializing mixed
DTO は他のコンポーネントで再利用できます。
content, using forms…
Classic and static constructors can be used to manage different ways to
クラシック コンストラクターと静的コンストラクターを使用して、さまざまな方法を管理できます。
create our objects, and they can also use DTOs.
Anemic entities tend to isolate the entity from logic, whereas rich
貧弱なエンティティは、エンティティをロジックから分離する傾向がありますが、リッチなエンティティは
entities allow putting the logic in the object itself, including data validation.
The next step for persistence with Doctrine is to describe the structure of
the Product entity 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 an Entity can be configured using attributes directly in the Entity class itself, or in an external XML or YAML file. This Getting Started guide will demonstrate metadata mappings using all three methods, but you only need to choose one.
Note
The YAML driver is deprecated and will be removed in version 3.0. It is strongly recommended to switch to one of the other mappings.
# config/yaml/Product.dcm.yml
Product:
type: entity
table: products
id:
id:
type: integer
generator:
strategy: AUTO
fields:
name:
type: string
The top-level entity definition specifies information about
the class and table name. The primitive type Product#name is
defined as a field attribute. The id property is defined with
the id tag. It has a generator tag nested inside, which
specifies that the primary key generation mechanism should automatically
use the database platform’s native id generation strategy (for
example, AUTO INCREMENT in the case of MySql, or Sequences in the
case of PostgreSql and Oracle).
Now that we have defined our first entity and its metadata, let’s update the database schema:
$ php bin/doctrine orm:schema-tool:update --force --dump-sql
Specifying both flags --force and --dump-sql will cause the DDL
statements to be executed and then printed to the screen.
Now, we’ll create a new script to insert products into the database:
<?php
// create_product.php <name>
require_once "bootstrap.php";
$newProductName = $argv[1];
$product = new Product();
$product->setName($newProductName);
$entityManager->persist($product);
$entityManager->flush();
echo "Created Product with ID " . $product->getId() . "\n";
Call this script from the command-line to see how new products are created:
$ php create_product.php ORM
$ php create_product.php DBAL
What is happening here? Using the Product class is pretty standard OOP.
The interesting bits are the use of the EntityManager service. To
notify the EntityManager that a new entity should be inserted into the database,
you have to call persist(). To initiate a transaction to actually perform
the insertion, you have to explicitly call flush() on the EntityManager.
This distinction between persist and flush is what allows the aggregation of
all database writes (INSERT, UPDATE, DELETE) into one single transaction, which
is executed when flush() is called. Using this approach, the write-performance
is significantly better than in a scenario in which writes are performed on
each entity in isolation.
Next, we’ll fetch a list of all the Products in the database. Let’s create a new script for this:
<?php
// list_products.php
require_once "bootstrap.php";
$productRepository = $entityManager->getRepository('Product');
$products = $productRepository->findAll();
foreach ($products as $product) {
echo sprintf("-%s\n", $product->getName());
}
The EntityManager#getRepository() method can create a finder object (called
a repository) for every type of entity. It is provided by Doctrine and contains
some finder methods like findAll().
Let’s continue by creating a script to display the name of a product based on its ID:
<?php
// show_product.php <id>
require_once "bootstrap.php";
$id = $argv[1];
$product = $entityManager->find('Product', $id);
if ($product === null) {
echo "No product found.\n";
exit(1);
}
echo sprintf("-%s\n", $product->getName());
Next we’ll update a product’s name, given its id. This simple example will
help demonstrate Doctrine’s implementation of the UnitOfWork pattern. Doctrine
keeps track of all the entities that were retrieved from the Entity Manager,
and can detect when any of those entities’ properties have been modified.
As a result, rather than needing to call persist($entity) for each individual
entity whose properties were changed, a single call to flush() at the end of a
request is sufficient to update the database for all of the modified entities.
<?php
// update_product.php <id> <new-name>
require_once "bootstrap.php";
$id = $argv[1];
$newName = $argv[2];
$product = $entityManager->find('Product', $id);
if ($product === null) {
echo "Product $id does not exist.\n";
exit(1);
}
$product->setName($newName);
$entityManager->flush();
After calling this script on one of the existing products, you can verify the
product name changed by calling the show_product.php script.
Adding Bug and User Entities¶
We continue with the bug tracker example by creating the Bug and User
classes. We’ll store them in src/Bug.php and src/User.php, respectively.
<?php
// src/Bug.php
use Doctrine\ORM\Mapping as ORM;
#[ORM\Entity]
#[ORM\Table(name: 'bugs')]
class Bug
{
#[ORM\Id]
#[ORM\Column(type: 'integer')]
#[ORM\GeneratedValue]
private int $id;
#[ORM\Column(type: 'string')]
private string $description;
#[ORM\Column(type: 'datetime')]
private DateTime $created;
#[ORM\Column(type: 'string')]
private string $status;
public function getId(): int|null
{
return $this->id;
}
public function getDescription(): string
{
return $this->description;
}
public function setDescription(string $description): void
{
$this->description = $description;
}
public function setCreated(DateTime $created)
{
$this->created = $created;
}
public function getCreated(): DateTime
{
return $this->created;
}
public function setStatus($status): void
{
$this->status = $status;
}
public function getStatus():string
{
return $this->status;
}
}
<?php
// src/User.php
use Doctrine\ORM\Mapping as ORM;
#[ORM\Entity]
#[ORM\Table(name: 'users')]
class User
{
/** @var int */
#[ORM\Id]
#[ORM\GeneratedValue]
#[ORM\Column(type: 'integer')]
private int|null $id = null;
/** @var string */
#[ORM\Column(type: 'string')]
private string $name;
public function getId(): int|null
{
return $this->id;
}
public function getName(): string
{
return $this->name;
}
public function setName(string $name): void
{
$this->name = $name;
}
}
All of the properties we’ve seen so far are of simple types (integer, string, and datetime). But now, we’ll add properties that will store objects of specific entity types in order to model the relationships between different entities.
At the database level, relationships between entities are represented by foreign keys. But with Doctrine, you’ll never have to (and never should) work with the foreign keys directly. You should only work with objects that represent foreign keys through their own identities.
For every foreign key you either have a Doctrine ManyToOne or OneToOne association. On the inverse sides of these foreign keys you can have OneToMany associations. Obviously you can have ManyToMany associations that connect two tables with each other through a join table with two foreign keys.
Now that you know the basics about references in Doctrine, we can extend the domain model to match the requirements:
<?php
// src/Bug.php
use Doctrine\Common\Collections\ArrayCollection;
use Doctrine\Common\Collections\Collection;
class Bug
{
// ... (previous code)
/** @var Collection<int, Product> */
private Collection $products;
public function __construct()
{
$this->products = new ArrayCollection();
}
}
<?php
// src/User.php
use Doctrine\Common\Collections\ArrayCollection;
class User
{
// ... (previous code)
/** @var Collection<int, Bug> */
private Collection $reportedBugs;
/** @var Collection<int, Bug> */
private Collection $assignedBugs;
public function __construct()
{
$this->reportedBugs = new ArrayCollection();
$this->assignedBugs = new ArrayCollection();
}
}
Note
Whenever an entity is created from the database, a Collection
implementation of the type PersistentCollection will be injected into
your entity instead of an ArrayCollection. This helps Doctrine ORM
understand the changes that have happened to the collection that are
noteworthy for persistence.
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 ORM. These assumptions are not unique to Doctrine ORM but are best practices in handling database relations and Object-Relational Mapping.
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.
1 対 1 の関係では、関連するエンティティの外部キーを独自のデータベース テーブルに保持しているエンティティが、常に関係の所有側になります。In a many-to-one relation, the Many-side is the owning side by default because it holds the foreign key. Accordingly, the One-side is the inverse side by default.
多対 1 の関係では、多側が外部キーを保持するため、デフォルトで所有側になります。したがって、片側はデフォルトで反対側です。In a many-to-one relation, the One-side can only be the owning side if the relation is implemented as a ManyToMany with a join table, and the One-side is restricted to allow only UNIQUE values per database constraint.
多対 1 のリレーションでは、リレーションが結合テーブルを使用して ManyToMany として実装されている場合にのみ One-side を所有側にすることができ、One-side はデータベース制約ごとに UNIQUE 値のみを許可するように制限されています。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 side is allowed to be the owning side.
多対多の関係では、両側が関係の所有側になることができます。ただし、双方向の多対多の関係では、一方の側だけが所有側になることができます。Changes to Collections are saved or updated, when the entity on the owning side of the collection is saved or updated.
コレクションの所有側のエンティティが保存または更新されると、コレクションへの変更が保存または更新されます。Saving an Entity at the inverse side of a relation never triggers a persist operation to changes to the collection.
リレーションの逆側でエンティティを保存しても、コレクションへの変更に対する永続化操作がトリガーされることはありません。
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
// src/Bug.php
class Bug
{
// ... (previous code)
private User $engineer;
private User $reporter;
public function setEngineer(User $engineer): void
{
$engineer->assignedToBug($this);
$this->engineer = $engineer;
}
public function setReporter(User $reporter): void
{
$reporter->addReportedBug($this);
$this->reporter = $reporter;
}
public function getEngineer(): User
{
return $this->engineer;
}
public function getReporter(): User
{
return $this->reporter;
}
}
<?php
// src/User.php
class User
{
// ... (previous code)
/** @var Collection<int, Bug> */
private Collection $reportedBugs;
/** @var Collection<int, Bug> */
private Collection $assignedBugs;
public function addReportedBug(Bug $bug): void
{
$this->reportedBugs[] = $bug;
}
public function assignedToBug(Bug $bug): void
{
$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. This approach is my personal preference, you can choose whatever method to make this work.
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.
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 Bugs to Products.
<?php
// src/Bug.php
class Bug
{
// ... (previous code)
/** @var Collection<int, Product> */
private Collection $products;
public function assignToProduct(Product $product): void
{
$this->products[] = $product;
}
/** @return Collection<int, Product> */
public function getProducts(): Collection
{
return $this->products;
}
}
We are now finished with the domain model given the requirements.
Lets add metadata mappings for the Bug entity, as we did for
the Product before:
Note
The YAML driver is deprecated and will be removed in version 3.0. It is strongly recommended to switch to one of the other mappings.
# config/yaml/Bug.dcm.yml
Bug:
type: entity
table: bugs
id:
id:
type: integer
generator:
strategy: AUTO
fields:
description:
type: text
created:
type: datetime
status:
type: string
manyToOne:
reporter:
targetEntity: User
inversedBy: reportedBugs
engineer:
targetEntity: User
inversedBy: assignedBugs
manyToMany:
products:
targetEntity: Product
Here we have the entity, id and primitive type definitions.
For the “created” field we have used the datetime type,
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 definition is for the Bug#products collection. It
holds all products where the specific bug occurs. Again
you have to define the target-entity and field attributes
on the many-to-many tag.
Finally, we’ll add metadata mappings for the User entity.
Note
The YAML driver is deprecated and will be removed in version 3.0. It is strongly recommended to switch to one of the other mappings.
# config/yaml/User.dcm.yml
User:
type: entity
table: users
id:
id:
type: integer
generator:
strategy: AUTO
fields:
name:
type: string
oneToMany:
reportedBugs:
targetEntity: Bug
mappedBy: reporter
assignedBugs:
targetEntity: Bug
mappedBy: engineer
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.
Update your database schema by running:
$ php bin/doctrine orm:schema-tool:update --force
Implementing more Requirements¶
So far, we’ve seen the most basic features of the metadata definition language.
To explore additional functionality, let’s first create new User entities:
<?php
// create_user.php
require_once "bootstrap.php";
$newUsername = $argv[1];
$user = new User();
$user->setName($newUsername);
$entityManager->persist($user);
$entityManager->flush();
echo "Created User with ID " . $user->getId() . "\n";
Now call:
$ php create_user.php beberlei
We now have the necessary data to create a new Bug entity:
<?php
// create_bug.php <reporter-id> <engineer-id> <product-ids>
require_once "bootstrap.php";
$reporterId = $argv[1];
$engineerId = $argv[2];
$productIds = explode(",", $argv[3]);
$reporter = $entityManager->find("User", $reporterId);
$engineer = $entityManager->find("User", $engineerId);
if (!$reporter || !$engineer) {
echo "No reporter and/or engineer found for the given id(s).\n";
exit(1);
}
$bug = new Bug();
$bug->setDescription("Something does not work!");
$bug->setCreated(new DateTime("now"));
$bug->setStatus("OPEN");
foreach ($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->getId()."\n";
Since we only have one user and product, probably with the ID of 1, we can call this script as follows:
php create_bug.php 1 1 1
See how simple it is to relate a Bug, Reporter, Engineer and Products?
Also recall that thanks to the UnitOfWork pattern, Doctrine will detect
these relations and update all of the modified entities in the database
automatically when flush() is called.
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
// list_bugs.php
require_once "bootstrap.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 $bug->getDescription()." - ".$bug->getCreated()->format('d.m.Y')."\n";
echo " Reported by: ".$bug->getReporter()->getName()."\n";
echo " Assigned to: ".$bug->getEngineer()->getName()."\n";
foreach ($bug->getProducts() as $product) {
echo " Platform: ".$product->getName()."\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.
If you need to build your query dynamically, you can use the QueryBuilder retrieved
by calling $entityManager->createQueryBuilder(). There are more
details about this in the relevant part of the documentation.
As a last resort you can still 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 results 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.
Hydration can be an expensive process so only retrieving what you need can yield considerable performance benefits for read-only requests.
Implementing the same list view as before using array hydration we can rewrite our code:
<?php
// list_bugs_array.php
require_once "bootstrap.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 EntityManager that
handles loading by primary key, which we have already seen in the
write scenarios:
<?php
// show_bug.php <id>
require_once "bootstrap.php";
$theBugId = $argv[1];
$bug = $entityManager->find("Bug", (int)$theBugId);
echo "Bug: ".$bug->getDescription()."\n";
echo "Engineer: ".$bug->getEngineer()->getName()."\n";
The output of the engineer’s name is fetched from the database! What is happening?
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. These proxies will load behind the scenes, when attempting to access any of their un-initialized state.
The call prints:
$ php show_bug.php 1
Bug: Something does not work!
Engineer: beberlei
Warning
Lazy loading additional data can be very convenient but the additional queries create an overhead. If you know that certain fields will always (or usually) be required by the query then you will get better performance by explicitly retrieving them all in the first query.
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
// dashboard.php <user-id>
require_once "bootstrap.php";
$theUserId = $argv[1];
$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, $theUserId)
->setMaxResults(15)
->getResult();
echo "You have created or assigned to " . count($myBugs) . " open bugs:\n\n";
foreach ($myBugs as $bug) {
echo $bug->getId() . " - " . $bug->getDescription()."\n";
}
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
// products.php
require_once "bootstrap.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
// src/Bug.php
class Bug
{
public function close()
{
$this->status = "CLOSE";
}
}
<?php
// close_bug.php <bug-id>
require_once "bootstrap.php";
$theBugId = $argv[1];
$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
separation. 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 $bug) {
// do stuff
}
Compared to DQL these query methods are falling short of functionality very fast.
Doctrine offers you a convenient way to extend the functionalities of the default EntityRepository
and put all the specialized DQL query logic on it. For this you have to create a subclass
of Doctrine\ORM\EntityRepository, in our case a BugRepository and group all
the previously discussed query functionality in it:
<?php
// src/BugRepository.php
use Doctrine\ORM\EntityRepository;
class BugRepository extends EntityRepository
{
public function getRecentBugs($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.
Note
The YAML driver is deprecated and will be removed in version 3.0. It is strongly recommended to switch to one of the other mappings.
Bug:
type: entity
repositoryClass: BugRepository
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
// list_bugs_repository.php
require_once "bootstrap.php";
$bugs = $entityManager->getRepository('Bug')->getRecentBugs();
foreach ($bugs as $bug) {
echo $bug->getDescription()." - ".$bug->getCreated()->format('d.m.Y')."\n";
echo " Reported by: ".$bug->getReporter()->getName()."\n";
echo " Assigned to: ".$bug->getEngineer()->getName()."\n";
foreach ($bug->getProducts() as $product) {
echo " Platform: ".$product->getName()."\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.
The method count() takes an array of fields or association keys and the values to match against.
This provides you with a convenient and lightweight way to count a resultset when you don’t need to
deal with it:
<?php
$productCount = $entityManager->getRepository(Product::class)
->count(['name' => $productName]);
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
関連マッピングの詳細Lifecycle Events triggered in the UnitOfWork
UnitOfWork でトリガーされるライフサイクル イベントOrdering of Collections
コレクションの注文
Additional details on all the topics discussed here can be found in the respective manual chapters.
