2010-11-01 23:16:12 +03:00
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Aggregate Fields
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================
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2010-12-03 22:13:10 +03:00
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.. sectionauthor:: Benjamin Eberlei <kontakt@beberlei.de>
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2010-11-01 23:16:12 +03:00
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You will often come across the requirement to display aggregate
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values of data that can be computed by using the MIN, MAX, COUNT or
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SUM SQL functions. For any ORM this is a tricky issue
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traditionally. Doctrine 2 offers several ways to get access to
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these values and this article will describe all of them from
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different perspectives.
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You will see that aggregate fields can become very explicit
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features in your domain model and how this potentially complex
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business rules can be easily tested.
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An example model
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----------------
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Say you want to model a bank account and all their entries. Entries
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into the account can either be of positive or negative money
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values. Each account has a credit limit and the account is never
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allowed to have a balance below that value.
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For simplicity we live in a world were money is composed of
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integers only. Also we omit the receiver/sender name, stated reason
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for transfer and the execution date. These all would have to be
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added on the ``Entry`` object.
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Our entities look like:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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namespace Bank\Entities;
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/**
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* @Entity
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*/
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class Account
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{
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/** @Id @GeneratedValue @Column(type="integer") */
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private $id;
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/** @Column(type="string", unique=true) */
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private $no;
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/**
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2011-07-09 23:26:13 +04:00
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* @OneToMany(targetEntity="Entry", mappedBy="account", cascade={"persist"})
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2010-11-01 23:16:12 +03:00
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*/
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private $entries;
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/**
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* @Column(type="integer")
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*/
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private $maxCredit = 0;
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public function __construct($no, $maxCredit = 0)
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{
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$this->no = $no;
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$this->maxCredit = $maxCredit;
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$this->entries = new \Doctrine\Common\Collections\ArrayCollection();
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}
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}
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/**
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* @Entity
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*/
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class Entry
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{
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/** @Id @GeneratedValue @Column(type="integer") */
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private $id;
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/**
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* @ManyToOne(targetEntity="Account", inversedBy="entries")
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*/
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private $account;
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/**
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* @Column(type="integer")
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*/
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private $amount;
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public function __construct($account, $amount)
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{
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$this->account = $account;
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$this->amount = $amount;
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// more stuff here, from/to whom, stated reason, execution date and such
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}
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public function getAmount()
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{
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return $this->amount;
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}
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}
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Using DQL
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---------
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The Doctrine Query Language allows you to select for aggregate
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values computed from fields of your Domain Model. You can select
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the current balance of your account by calling:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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$dql = "SELECT SUM(e.amount) AS balance FROM Bank\Entities\Entry e " .
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"WHERE e.account = ?1";
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$balance = $em->createQuery($dql)
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->setParameter(1, $myAccountId)
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->getSingleScalarResult();
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The ``$em`` variable in this (and forthcoming) example holds the
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Doctrine ``EntityManager``. We create a query for the SUM of all
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amounts (negative amounts are withdraws) and retrieve them as a
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single scalar result, essentially return only the first column of
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the first row.
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This approach is simple and powerful, however it has a serious
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drawback. We have to execute a specific query for the balance
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whenever we need it.
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To implement a powerful domain model we would rather have access to
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the balance from our ``Account`` entity during all times (even if
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the Account was not persisted in the database before!).
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Also an additional requirement is the max credit per ``Account``
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rule.
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We cannot reliably enforce this rule in our ``Account`` entity with
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the DQL retrieval of the balance. There are many different ways to
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retrieve accounts. We cannot guarantee that we can execute the
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aggregation query for all these use-cases, let alone that a
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userland programmer checks this balance against newly added
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entries.
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Using your Domain Model
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-----------------------
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``Account`` and all the ``Entry`` instances are connected through a
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collection, which means we can compute this value at runtime:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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class Account
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{
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// .. previous code
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public function getBalance()
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{
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$balance = 0;
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foreach ($this->entries AS $entry) {
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$balance += $entry->getAmount();
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}
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return $balance;
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}
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}
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Now we can always call ``Account::getBalance()`` to access the
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current account balance.
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To enforce the max credit rule we have to implement the "Aggregate
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Root" pattern as described in Eric Evans book on Domain Driven
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Design. Described with one sentence, an aggregate root controls the
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instance creation, access and manipulation of its children.
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In our case we want to enforce that new entries can only added to
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the ``Account`` by using a designated method. The ``Account`` is
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the aggregate root of this relation. We can also enforce the
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correctness of the bi-directional ``Account`` <-> ``Entry``
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relation with this method:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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class Account
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{
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public function addEntry($amount)
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{
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$this->assertAcceptEntryAllowed($amount);
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$e = new Entry($this, $amount);
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$this->entries[] = $e;
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return $e;
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}
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}
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Now look at the following test-code for our entities:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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class AccountTest extends \PHPUnit_Framework_TestCase
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{
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public function testAddEntry()
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{
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$account = new Account("123456", $maxCredit = 200);
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$this->assertEquals(0, $account->getBalance());
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$account->addEntry(500);
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$this->assertEquals(500, $account->getBalance());
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$account->addEntry(-700);
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$this->assertEquals(-200, $account->getBalance());
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}
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public function testExceedMaxLimit()
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{
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$account = new Account("123456", $maxCredit = 200);
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$this->setExpectedException("Exception");
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$account->addEntry(-1000);
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}
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}
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To enforce our rule we can now implement the assertion in
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``Account::addEntry``:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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class Account
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{
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private function assertAcceptEntryAllowed($amount)
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{
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$futureBalance = $this->getBalance() + $amount;
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$allowedMinimalBalance = ($this->maxCredit * -1);
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if ($futureBalance < $allowedMinimalBalance) {
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throw new Exception("Credit Limit exceeded, entry is not allowed!");
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}
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}
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}
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We haven't talked to the entity manager for persistence of our
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account example before. You can call
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``EntityManager::persist($account)`` and then
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``EntityManager::flush()`` at any point to save the account to the
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database. All the nested ``Entry`` objects are automatically
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flushed to the database also.
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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$account = new Account("123456", 200);
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$account->addEntry(500);
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$account->addEntry(-200);
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$em->persist($account);
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$em->flush();
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The current implementation has a considerable drawback. To get the
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balance, we have to initialize the complete ``Account::$entries``
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collection, possibly a very large one. This can considerably hurt
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the performance of your application.
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Using an Aggregate Field
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------------------------
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To overcome the previously mentioned issue (initializing the whole
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entries collection) we want to add an aggregate field called
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"balance" on the Account and adjust the code in
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``Account::getBalance()`` and ``Account:addEntry()``:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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class Account
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{
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/**
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* @Column(type="integer")
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*/
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private $balance = 0;
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public function getBalance()
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{
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return $this->balance;
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}
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public function addEntry($amount)
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{
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$this->assertAcceptEntryAllowed($amount);
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$e = new Entry($this, $amount);
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$this->entries[] = $e;
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$this->balance += $amount;
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return $e;
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}
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}
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This is a very simple change, but all the tests still pass. Our
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account entities return the correct balance. Now calling the
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``Account::getBalance()`` method will not occur the overhead of
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loading all entries anymore. Adding a new Entry to the
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``Account::$entities`` will also not initialize the collection
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internally.
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Adding a new entry is therefore very performant and explicitly
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hooked into the domain model. It will only update the account with
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the current balance and insert the new entry into the database.
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Tackling Race Conditions with Aggregate Fields
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----------------------------------------------
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Whenever you denormalize your database schema race-conditions can
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potentially lead to inconsistent state. See this example:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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// The Account $accId has a balance of 0 and a max credit limit of 200:
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// request 1 account
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$account1 = $em->find('Bank\Entities\Account', $accId);
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// request 2 account
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$account2 = $em->find('Bank\Entities\Account', $accId);
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$account1->addEntry(-200);
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$account2->addEntry(-200);
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// now request 1 and 2 both flush the changes.
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The aggregate field ``Account::$balance`` is now -200, however the
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SUM over all entries amounts yields -400. A violation of our max
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credit rule.
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You can use both optimistic or pessimistic locking to save-guard
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your aggregate fields against this kind of race-conditions. Reading
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Eric Evans DDD carefully he mentions that the "Aggregate Root"
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(Account in our example) needs a locking mechanism.
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Optimistic locking is as easy as adding a version column:
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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class Amount
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{
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/** @Column(type="integer") @Version */
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private $version;
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}
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The previous example would then throw an exception in the face of
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whatever request saves the entity last (and would create the
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inconsistent state).
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Pessimistic locking requires an additional flag set on the
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``EntityManager::find()`` call, enabling write locking directly in
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the database using a FOR UPDATE.
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2010-12-03 22:13:10 +03:00
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.. code-block:: php
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2010-11-01 23:16:12 +03:00
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<?php
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use Doctrine\DBAL\LockMode;
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$account = $em->find('Bank\Entities\Account', $accId, LockMode::PESSIMISTIC_READ);
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Keeping Updates and Deletes in Sync
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-----------------------------------
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The example shown in this article does not allow changes to the
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value in ``Entry``, which considerably simplifies the effort to
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keep ``Account::$balance`` in sync. If your use-case allows fields
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to be updated or related entities to be removed you have to
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encapsulate this logic in your "Aggregate Root" entity and adjust
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the aggregate field accordingly.
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Conclusion
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----------
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This article described how to obtain aggregate values using DQL or
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your domain model. It showed how you can easily add an aggregate
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field that offers serious performance benefits over iterating all
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the related objects that make up an aggregate value. Finally I
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showed how you can ensure that your aggregate fields do not get out
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of sync due to race-conditions and concurrent access.
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