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Caching in the ORM

Every application is different, we could have models whose data change frequently and others that rarely change. Accessing database systems is often one of the most common bottlenecks in terms of performance. This is due to the complex connection/communication processes that PHP must do in each request to obtain data from the database. Therefore, if we want to achieve good performance we need to add some layers of caching where the application requires it.

This chapter explains the possible points where it is possible to implement caching to improve performance. The framework gives you the tools to implement the cache where you demand of it according to the architecture of your application.

Caching Resultsets

A well established technique to avoid the continuous access to the database is to cache resultsets that don’t change frequently using a system with faster access (usually memory).

When Phalcon\Mvc\Model requires a service to cache resultsets, it will request it to the Dependency Injector Container with the convention name “modelsCache”.

As Phalcon provides a component to cache any kind of data, we’ll explain how to integrate it with Models. First, you must register it as a service in the services container:

<?php

//Set the models cache service
$di->set('modelsCache', function() {

    //Cache data for one day by default
    $frontCache = new \Phalcon\Cache\Frontend\Data(array(
        "lifetime" => 86400
    ));

    //Memcached connection settings
    $cache = new \Phalcon\Cache\Backend\Memcache($frontCache, array(
        "host" => "localhost",
        "port" => "11211"
    ));

    return $cache;
});

You have complete control in creating and customizing the cache before being used by registering the service as an anonymous function. Once the cache setup is properly defined you could cache resultsets as follows:

<?php

// Get products without caching
$products = Products::find();

// Just cache the resultset. The cache will expire in 1 hour (3600 seconds)
$products = Products::find(array(
    "cache" => array("key" => "my-cache")
));

// Cache the resultset for only for 5 minutes
$products = Products::find(array(
    "cache" => array("key" => "my-cache", "lifetime" => 300)
));

// Using a custom cache
$products = Products::find(array("cache" => $myCache));

Caching could be also applied to resultsets generated using relationships:

<?php

// Query some post
$post = Post::findFirst();

// Get comments related to a post, also cache it
$comments = $post->getComments(array(
    "cache" => array("key" => "my-key")
));

// Get comments related to a post, setting lifetime
$comments = $post->getComments(array(
    "cache" => array("key" => "my-key", "lifetime" => 3600)
));

When a cached resultset needs to be invalidated, you can simply delete it from the cache using the previously specified key.

Note that not all resultsets must be cached. Results that change very frequently should not be cached since they are invalidated very quickly and caching in that case impacts performance. Additionally, large datasets that do not change frequently could be cached, but that is a decision that the developer has to make based on the available caching mechanism and whether the performance impact to simply retrieve that data in the first place is acceptable.

Overriding find/findFirst

As seen above, these methods are available in models that inherit Phalcon\Mvc\Model:

<?php

class Robots extends Phalcon\Mvc\Model
{

    public static function find($parameters=null)
    {
        return parent::find($parameters);
    }

    public static function findFirst($parameters=null)
    {
        return parent::findFirst($parameters);
    }

}

By doing this, you’re intercepting all the calls to these methods, this way, you can add a cache layer or run the query if there is no cache. For example, a very basic cache implementation, uses a static property to avoid that a record would be queried several times in a same request:

<?php

class Robots extends Phalcon\Mvc\Model
{

    protected static $_cache = array();

    /**
     * Implement a method that returns a string key based
     * on the query parameters
     */
    protected static function _createKey($parameters)
    {
        $uniqueKey = array();
        foreach ($parameters as $key => $value) {
            if (is_scalar($value)) {
                $uniqueKey[] = $key . ':' . $value;
            } else {
                if (is_array($value)) {
                    $uniqueKey[] = $key . ':[' . self::_createKey($value) .']';
                }
            }
        }
        return join(',', $uniqueKey);
    }

    public static function find($parameters=null)
    {

        //Create an unique key based on the parameters
        $key = self::_createKey($parameters);

        if (!isset(self::$_cache[$key])) {
            //Store the result in the memory cache
            self::$_cache[$key] = parent::find($parameters);
        }

        //Return the result in the cache
        return self::$_cache[$key];
    }

    public static function findFirst($parameters=null)
    {
        // ...
    }

}

Access the database is several times slower than calculate a cache key, you’re free in implement the key generation strategy you find better for your needs. Note that a good key avoids collisions as much as possible, this means that different keys returns unrelated records to the find parameters.

In the above example, we used a cache in memory, it is useful as a first level cache. Once we have the memory cache, we can implement a second level cache layer like APC/XCache or a NoSQL database:

<?php

public static function find($parameters=null)
{

    //Create an unique key based on the parameters
    $key = self::_createKey($parameters);

    if (!isset(self::$_cache[$key])) {

        //We're using APC as second cache
        if (apc_exists($key)) {

            $data = apc_fetch($key);

            //Store the result in the memory cache
            self::$_cache[$key] = $data;

            return $data;
        }

        //There are no memory or apc cache
        $data = parent::find($parameters);

        //Store the result in the memory cache
        self::$_cache[$key] = $data;

        //Store the result in APC
        apc_store($key, $data);

        return $data;
    }

    //Return the result in the cache
    return self::$_cache[$key];
}

This gives you full control on how the the caches must be implemented for each model, if this strategy is common to several models you can create a base class for all of them:

<?php

class CacheableModel extends Phalcon\Mvc\Model
{

    protected static function _createKey($parameters)
    {
        // .. create a cache key based on the parameters
    }

    public static function find($parameters=null)
    {
        //.. custom caching strategy
    }

    public static function findFirst($parameters=null)
    {
        //.. custom caching strategy
    }
}

Then use this class as base class for each ‘Cacheable’ model:

<?php

class Robots extends CacheableModel
{

}

Forcing Cache

Earlier we saw how Phalcon\Mvc\Model has a built-in integration with the caching component provided by the framework. To make a record/resultset cacheable we pass the key ‘cache’ in the array of parameters:

<?php

// Cache the resultset for only for 5 minutes
$products = Products::find(array(
    "cache" => array("key" => "my-cache", "lifetime" => 300)
));

This gives us the freedom to cache specific queries, however if we want to cache globally every query performed over the model, we can override the find/findFirst method to force every query to be cached:

<?php

class Robots extends Phalcon\Mvc\Model
{

    protected static function _createKey($parameters)
    {
        // .. create a cache key based on the parameters
    }

    public static function find($parameters=null)
    {

        //Convert the parameters to an array
        if (!is_array($parameters)) {
            $parameters = array($parameters);
        }

        //Check if a cache key wasn't passed
        //and create the cache parameters
        if (!isset($parameters['cache'])) {
            $parameters['cache'] = array(
                "key" => self::_createKey($parameters),
                "lifetime" => 300
            );
        }

        return parent::find($parameters);
    }

    public static function findFirst($parameters=null)
    {
        //...
    }

}

Caching PHQL Queries

All queries in the ORM, no matter how high level syntax we used to create them are handled internally using PHQL. This language gives you much more freedom to create all kinds of queries. Of course these queries can be cached:

<?php

$phql = "SELECT * FROM Cars WHERE name = :name:";

$query = $this->modelsManager->createQuery($phql);

$query->cache(array(
    "key" => "cars-by-name",
    "lifetime" => 300
));

$cars = $query->execute(array(
    'name' => 'Audi'
));

If you don’t want to use the implicit cache just save the resulset into your favorite cache backend:

<?php

$phql = "SELECT * FROM Cars WHERE name = :name:";

$cars = $this->modelsManager->executeQuery($phql, array(
    'name' => 'Audi'
));

apc_store('my-cars', $cars);

Caching based on Conditions

In this scenario, the cache is implemented conditionally according to current conditions received. According to the range where the primary key is located we choose a different cache backend:

Type Cache Backend
1 - 10000 mongo1
10000 - 20000 mongo2
> 20000 mongo3

The easiest way is adding an static method to the model that chooses the right cache to be used:

<?php

class Robots extends \Phalcon\Mvc\Model
{

    public static function queryCache($initial, $final)
    {
        if ($initial >= 1 && $final < 10000) {
            return self::find(array(
                'id >= ' . $initial . ' AND id <= '.$final,
                'cache' => array('service' => 'mongo1')
            ));
        }
        if ($initial >= 10000 && $final <= 20000) {
            return self::find(array(
                'id >= ' . $initial . ' AND id <= '.$final,
                'cache' => array('service' => 'mongo2')
            ));
        }
        if ($initial > 20000) {
            return self::find(array(
                'id >= ' . $initial,
                'cache' => array('service' => 'mongo3')
            ));
        }
    }

}

This approach solves the problem, however, if we want to add other parameters such orders or conditions we would have to create a more complicated method. Additionally, this method does not work if the data is obtained using related records or a find/findFirst:

<?php

$robots = Robots::find('id < 1000');
$robots = Robots::find('id > 100 AND type = "A"');
$robots = Robots::find('(id > 100 AND type = "A") AND id < 2000');

$robots = Robots::find(array(
    '(id > ?0 AND type = "A") AND id < ?1',
    'bind' => array(100, 2000),
    'order' => 'type'
));

To achieve this we need to intercept the intermediate representation (IR) generated by the PHQL parser and thus customize the cache everything possible:

The first is create a custom builder, so we can generate a totally customized query:

<?php

class CustomQueryBuilder extends Phalcon\Mvc\Model\Query\Builder
{

    public function getQuery()
    {
        $query = new CustomQuery($this->getPhql());
        $query->setDI($this->getDI());
        return $query;
    }

}

Instead of directly returning a Phalcon\Mvc\Model\Query, our custom builder returns a CustomQuery instance, this class looks like:

<?php

class CustomQuery extends Phalcon\Mvc\Model\Query
{

    /**
     * The execute method is overridden
     */
    public function execute($params=null, $types=null)
    {
        //Parse the intermediate representation for the SELECT
        $ir = $this->parse();

        //Check if the query has conditions
        if (isset($ir['where'])) {

            //The fields in the conditions can have any order
            //We need to recursively check the conditions tree
            //to find the info we're looking for
            $visitor = new CustomNodeVisitor();

            //Recursively visits the nodes
            $visitor->visit($ir['where']);

            $initial = $visitor->getInitial();
            $final = $visitor->getFinal();

            //Select the cache according to the range
            //...

            //Check if the cache has data
            //...
        }

        //Execute the query
        $result = $this->_executeSelect($ir, $params, $types);

        //cache the result
        //...

        return $result;
    }

}

Implementing a helper (CustomNodeVisitor) that recursively checks the conditions looking for fields that tell us the possible range to be used in the cache:

<?php

class CustomNodeVisitor
{

    protected $_initial = 0;

    protected $_final = 25000;

    public function visit($node)
    {
        switch ($node['type']) {

            case 'binary-op':

                $left = $this->visit($node['left']);
                $right = $this->visit($node['right']);
                if (!$left || !$right) {
                    return false;
                }

                if ($left=='id') {
                    if ($node['op'] == '>') {
                        $this->_initial = $right;
                    }
                    if ($node['op'] == '=') {
                        $this->_initial = $right;
                    }
                    if ($node['op'] == '>=')    {
                        $this->_initial = $right;
                    }
                    if ($node['op'] == '<') {
                        $this->_final = $right;
                    }
                    if ($node['op'] == '<=')    {
                        $this->_final = $right;
                    }
                }
                break;

            case 'qualified':
                if ($node['name'] == 'id') {
                    return 'id';
                }
                break;

            case 'literal':
                return $node['value'];

            default:
                return false;
        }
    }

    public function getInitial()
    {
        return $this->_initial;
    }

    public function getFinal()
    {
        return $this->_final;
    }
}

Finally, we can replace the find method in the Robots model to use the custom classes we’ve created:

<?php

class Robots extends Phalcon\Mvc\Model
{
    public static function find($parameters=null)
    {

        if (!is_array($parameters)) {
            $parameters = array($parameters);
        }

        $builder = new CustomQueryBuilder($parameters);
        $builder->from(get_called_class());

        if (isset($parameters['bind'])) {
            return $builder->getQuery()->execute($parameters['bind']);
        } else {
            return $builder->getQuery()->execute();
        }

    }
}

Caching of PHQL planning

As well as most moderns database systems PHQL internally caches the execution plan, if the same statement is executed several times PHQL reuses the previously generated plan improving performance, for a developer to take better advantage of this is highly recommended build all your SQL statements passing variable parameters as bound parameters:

<?php

for ($i = 1; $i <= 10; $i++) {

    $phql = "SELECT * FROM Store\Robots WHERE id = " . $i;
    $robots = $this->modelsManager->executeQuery($phql);

    //...
}

In the above example, ten plans were generated increasing the memory usage and processing in the application. Rewriting the code to take advantage of bound parameters reduces the processing by both ORM and database system:

<?php

$phql = "SELECT * FROM Store\Robots WHERE id = ?0";

for ($i = 1; $i <= 10; $i++) {

    $robots = $this->modelsManager->executeQuery($phql, array($i));

    //...
}

Performance can be also improved reusing the PHQL query:

<?php

$phql = "SELECT * FROM Store\Robots WHERE id = ?0";
$query = $this->modelsManager->createQuery($phql);

for ($i = 1; $i <= 10; $i++) {

    $robots = $query->execute($phql, array($i));

    //...
}

Execution plans for queries involving prepared statements are also cached by most database systems reducing the overall execution time, also protecting your application against SQL Injections.