mkcg/php-query-model

Agnostic model to efficiently query and scroll any kind of data (SQL, Search engine, HTTP API, CSV, ...) and push them anywhere with a ETL

0.9.14 2020-08-11 15:10 UTC

Requires

• php: ^7.2.0
• psr/http-client: ^1.0

Suggests

• algolia/algoliasearch-client-php: Needed to use the algolia driver
• doctrine/dbal: Needed to use the doctrine driver
• ethanhann/redisearch-php: Needed to use the redisearch driver
• guzzle/guzzle: Needed to use the Guzzle adapter
• guzzlehttp/guzzle: Needed to use the GuzzleHttp adapter
• mongodb/mongodb: Needed to use the Mongodb driver
• predis/predis: Needed to use the redis driver

GPL-3.0-only

• Kévin Masseix
• Mounir R'Quiba

• redis
• database
• mongodb
• http
• csv
• doctrine
• Sitemap
• elasticsearch
• rss
• robots.txt
• projection
• aggregation
• etl
• cqrs
• redisearch

README

Simple multi-database library to search content on different engines and aggregate those results into document-oriented structures.

The library define the class MKCG\Model\DBAL\QueryEngine to build documents using different Drivers.

It also defines a simple ETL to be able to easily and efficiently synchronize content between different datasources.

Engine API

The QueryEngine API define two methods : query() and scroll().

Each one can fetch and build documents using the provided \MKCG\Model\Model with the appropriate \MKCG\Model\DBAL\QueryCriteria. However, the scroll() method return a \Generator and internally performs multiple batches to efficiently scroll big collections.

Examples

$model = Schema\User::make('default', 'user')
    ->with(Schema\Address::make())
    ->with(Schema\Post::make());

$criteria = (new QueryCriteria())
    ->forCollection('user')
        ->addFilter('status', FilterInterface::FILTER_IN, [ 2 , 3 , 5 , 7 ])
        ->addFilter('registered_at', FilterInterface::FILTER_GREATER_THAN_EQUAL, '2000-01-01')
        ->addSort('firstname', 'ASC')
        ->addSort('lastname', 'ASC')
        ->setLimit(10)
    ->forCollection('addresses')
        ->setLimitByParent(2)
    ->forCollection('posts')
        ->addFilter('title', FilterInterface::FILTER_FULLTEXT_MATCH, 'ab')
;

$users = $engine->query($model, $criteria);

echo json_encode($users->getContent(), JSON_PRETTY_PRINT) . "\n";
echo "\nFound : " . $users->getCount() . " users\n";


$iterator = $engine->scroll($model, $criteria);

foreach ($iterator as $user) {
    echo json_encode($user, JSON_PRETTY_PRINT) . "\n";
}

Drivers definition

Each Driver is responsible to perform queries on a single datasource (database, HTTP API, local files, ...) and must :

• implements the MKCG\Model\DBAL\Drivers\DriverInterface
• registered inside the QueryEngine

Example

use MKCG\Model\DBAL\QueryEngine;
use MKCG\Model\DBAL\Drivers;

$mongoClient = new MongoDB\Client('mongodb://root:password@mongodb');

$redisClient = new \Predis\Client([
    'scheme' => 'tcp',
    'host' => 'redisearch',
    'port' => 6379
]);

$sqlConnection = \Doctrine\DBAL\DriverManager::getConnection([
    'user' => 'root',
    'password' => 'root',
    'host' => 'mysql',
    'driver' => 'pdo_mysql',
]);

$engine = (new QueryEngine('mysql'))
    ->registerDriver(new Drivers\Doctrine($sqlConnection), 'mysql')
    ->registerDriver(new Drivers\CsvReader($fixturePath), 'csv')
    ->registerDriver(new Drivers\RssReader(new Adapters\Guzzle), 'rss')
    ->registerDriver(new Drivers\SitemapReader(new Adapters\Guzzle), 'sitemap')
    ->registerDriver(new Drivers\Http(new Adapters\Guzzle), 'http')
    ->registerDriver(new Drivers\HttpRobot(new Adapters\Guzzle), 'http_robot')
    ->registerDriver(new Drivers\MongoDB($mongoClient), 'mongodb')

Runtime behaviors

Drivers

Type	Name	Description
Document-oriented database	MongoDB	Driver for MongoDB 3.6+
Relational database	Doctrine	Doctrine DBAL Adapter (MySQL, MariaDB are supported, other might not)
Search engine	Elasticsearch	Driver for Elasticsearch 5+ (Work in progress)
Search engine	Redisearch	Driver for redisearch
File reader	CsvReader
HTTP	Http	Interact with remote url (Work in progress)
HTTP	HttpRobot	Parse robots.txt from remote url (Work in progress)
RSS	RssReader	Extract RSS from remote url
Sitemap	SitemapReader	Extract Sitemap urlset from remote url

Features supported by driver

Driver	Scrollable	Filterable	Sortable	Aggregatable	Count
CsvReader	YES	YES	NO	YES	YES
Doctrine	YES	YES	YES	YES	YES
Http	YES	YES	NO	NO	NO
HttpRobot	YES	NO	NO	NO	NO
MongoDB	YES	YES	YES	YES	YES
Redisearch	YES	YES	YES	YES	YES
RssReader	YES	YES	NO	NO	NO
SitemapReader	YES	YES	NO	NO	NO
Algolia
Cassandra
Elasticsearch
PostgreSQL
ScyllaDB
Solr

Query criteria options

HTTP-based drivers :

• HTTP
• HttpRobot
• RssReader
• SitemapReader
• Elasticsearch

Result-based filterable drivers :

• CsvReader
• RssReader
• SitemapReader

Option	Drivers	Description
case_sensitive	MongoDB, Result-based filterable drivers	Perform case sensitive FILTER_FULLTEXT_MATCH search , default : false
filepath	CsvReader	Absolute or relative filepath of the CSV
delimiter	CsvReader	Field delimiter
json_formatter	HTTP	Format JSON response body using a callback
multiple_requests	none , used by the QueryEngine	Disable sub-requests batching when including sub-models
url	HTTP-based drivers	Define the URL to use to query
url_generator	HTTP-based drivers	Use a callback to generate the URL to use based on the Query
max_query_time	HTTP-based drivers , MongoDB	Max query time in milliseconds , default : 5000 (5 seconds)
allow_partial	MongoDB , Elasticsearch	Allow partial results to be returned , default : false
readPreference	MongoDB	https://docs.mongodb.com/manual/core/read-preference/index.html
readConcern	MongoDB	https://docs.mongodb.com/manual/reference/read-concern/index.html
batchSize	MongoDB	https://docs.mongodb.com/manual/reference/method/cursor.batchSize/index.html
diacriticSensitive	MongoDB	https://docs.mongodb.com/manual/reference/operator/query/text/index.html
name	all	Overrides the name defined into the SchemaInterface

When both url_generator and url are provided, then only url_generator is used.

Filters

Name	Constant name	Description
IN	FILTER_IN
NOT IN	FILTER_NOT_IN
GT	FILTER_GREATER_THAN
GTE	FILTER_GREATER_THAN_EQUAL
LT	FILTER_LESS_THAN
LTE	FILTER_LESS_THAN_EQUAL
MATCH	FILTER_FULLTEXT_MATCH	Text search
CUSTOM	FILTER_CUSTOM	Allow to use a callable to apply complex filters

Constants are defined by the interface MKCG\Model\DBAL\FilterInterface

Filters supported by driver

Driver	IN	NOT IN	GT	GTE	LT	LTE	MATCH	CUSTOM
Http	NO	NO	NO	NO	NO	NO	NO	NO
HttpRobot	NO	NO	NO	NO	NO	NO	NO	NO
Doctrine	YES	YES	YES	YES	YES	YES	Interpreted as LIKE "%value%"	YES
Elasticsearch	YES	YES	YES	YES	YES	YES	YES , using elasticsearch match filter	WIP
MongoDB	YES	YES	YES	YES	YES	YES	YES , using mongodb $text operator	YES
Redisearch	YES	YES	YES	YES	YES	YES	YES , using redisearch search syntax	NO
CsvReader	YES	YES	YES	YES	YES	YES	Interpreted as LIKE "%value%"	YES
RssReader	YES	YES	YES	YES	YES	YES	Interpreted as LIKE "%value%"	YES
SitemapReader	YES	YES	YES	YES	YES	YES	Interpreted as LIKE "%value%"	YES

CUSTOM filter type

Custom filters can be applied by providing a callable to the QueryCriteria instance :

(new QueryCriteria())
    ->forCollection('order')
        ->addCallableFilter(function(Query $query, ...$arguments) {
            // do something
        })

The first argument of the callable SHOULD always be the Query instance. Other arguments might change depending on the driver.

Some Driver apply filters on fetched results and expect a false return value when the filter does not match. Internaly they apply a array_filter on each fetched result before :

• CsvReader
• RssReader
• SitemapReader

callable arguments by Driver

Driver	First argument	Second argument
Doctrine	\MKCG\Model\DBAL\Query	\Doctrine\DBAL\Query\QueryBuilder
CsvReader	\MKCG\Model\DBAL\Query	array representing a raw item
RssReader	\MKCG\Model\DBAL\Query	array representing a raw item
SitemapReader	\MKCG\Model\DBAL\Query	array representing a raw item
MongoDB	\MKCG\Model\DBAL\Quert	array representing the filters passed as first argument of \MongoDB\Collection::find()

ETL

A deadly simple ETL is defined as a single class \MKCG\Model\ETL. It can be used in combination with the QueryEngine scroll API to transform then push content to different loaders;

Example

function pipelineEtl(QueryEngine $engine)
{
    $model = Schema\Product::make('default', 'products');
    $criteria = (new QueryCriteria())
        ->forCollection('products')
            ->addFilter('sku.color', FilterInterface::FILTER_IN, ['aqua', 'purple'])
        ;

    $iterator = $engine->scroll($model, $criteria, 100);

    $pushed = ETL::extract($engine->scroll($model, $criteria, 100), 1000, 500)
        ->transform(function($item) {
            return [
                'id' => $item['_id'],
                'sku' => $item['sku']
            ];
        })
        ->transform(function($item) {
            return $item + [
                'sku_count' => count($item['sku'] ?? [])
            ];
        })
        ->load(function(iterable $bulk) {
            echo sprintf("[ETL] Loader 1 - Loading %d elements\n", count($bulk));
        })
        ->load(function(iterable $bulk) {
            echo sprintf("[ETL] Loader 2 - Loading %d elements\n", count($bulk));
        })
        ->load(function(iterable $bulk) {
            echo sprintf("[ETL] Loader 3 - Loading %d elements\n", count($bulk));
        })
        ->run();

    echo sprintf("[ETL] Pushed %d elements\n", $pushed);
}

Aggregations

NAME	Description
TERMS	Number of distinct elements by field , with the field filters considered by the aggregation
FACET	Number of distinct elements by field , with the field filters excluded by the aggregation
AVERAGE	Average value of a numeric field
MIN	Min value of a field
MAX	Max value of a field
QUANTILE	Quantile value of a field

Aggregrations supported

Driver	TERMS	FACET	AVERAGE	MIN	MAX	QUANTILE
CsvReader	NO	NO	YES	YES	YES	NO
Doctrine	YES	YES	YES	YES	YES	YES
MongoDB	YES	YES	YES	YES	YES	YES
Redisearch	YES	YES	YES	YES	YES	YES

Test and examples

No tests are provided although some will be made using Behat for the release of the version 1.0.0. However a fully functionnal example is provided in examples/ and build documents using different kinds of Drivers

From : ./examples

docker-compose up --build -d
docker exec -it php_query_model sh -c "cd /home/php-query-model/examples && composer install"
docker exec -it php_query_model sh -c "php /home/php-query-model/examples/index.php"

By default this will run only two functions (located in index.php)

pipelineEtl($engine);
searchOrder($engine);
// searchProducts($engine);
// searchGithubRobot($engine);
// searchSitemaps($engine);
// searchPackages($engine);
// searchUsers($engine);
// searchHackerNews($engine);

The pipelineEtl use the Engine scroll API to iterates a list of Product stored in MongoDB and apply different transformationsbefore pushing content with three loaders using the ETL component.

The searchOrder use the Engine scroll API to :

• scan a CSV file containing ecommerce Order
  • then inject their corresponding Product stored on MongoDB
  • then inject their correspondng customers stored as User into MySQL
    • with their first two defined Address also stored in Mysql
    • and all their Post stored in Mysql

You might want to uncomment the other search functions to execute HTTP queries and fetch :

• https://github.com/robots.txt with searchGithubRobot
• https://news.ycombinator.com/ top stories with searchHackerNews
• https://packagist.org/feeds/packages.rss RSS feed with searchPackages
• https://www.sitemaps.org/sitemap.xml Sitemap with searchSitemaps

Roadmap

Expected features

Work In progress

Feature	Description
Elasticsearch Driver
Callable validation	Validate callable arguments using Reflection and PHP tokens

Backlog

Feature	Description
Async HTTP requests	Perform non-blocking HTTP requests
Lazy requests	Only perform requests when the content is manipulated
Cacheable requests	Cache results and detect what to invalidate using surrogate keys
Content synchronizer	Use streamed eventlog to synchronize content between each datasource
Error handling strategies	Allow to apply different strategy in case of a failure : crash, retry, fallback...
Generate schema classes	Generate Schema classes by analyzing each database schema
Content lifecycle	Allow to create / update / delete content

Drivers "nice to have"

Database Drivers

• Algolia
• ArangoDB
• Cassandra
• \Illuminate\Eloquent (library used by Laravel)
• Neo4J
• PostgreSQL
• ScyllaDB
• Solr

Streaming

• Kafka
• MySQL binlog
• RabbitMQ

Storage

• AWS S3
• File system
• OpenIO

Infrastructure

• AWS
• OVH

Service

• Cloudinary
• Sendinblue

Social Network

• Facebook
• LinkedIn
• Twitter

Contribution

Feel free to open a merge request for any suggestion or to contribute to this project.