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Execution via CLI Command | https://pimcore.com/docs/platform//Datahub_File_Export/Export_Setup#execution-via-cli-command | Execution via CLI Command
The export command also can be setup and executed directly as cronjob by just executing the datahub:export:file command (for details
see --help option). This might be useful, when more custom execution definitions are necessary or special infrastructure
requirements exist.
For this execution option, no Symfony messenger queue is necessary. | [
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] |
Customize and Extend | https://pimcore.com/docs/platform//Datahub_File_Export/Customize_and_Extend#customize-and-extend | Customize and Extend
There are multiple ways for extending the file export adapter.
It is possible to add additional file types and transmitters (see below) and there are a couple of events
that allow to further customize the export.
In addition to that, it is also possible to completely customize the whole exporter by providing a custom
exporter service. This gives you full control over the whole export process and allows things like adding custom
query conditions for the workspaces etc. | [
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Additional Transmitters | https://pimcore.com/docs/platform//Datahub_File_Export/Customize_and_Extend#additional-transmitters | Additional Transmitters
Transmitters are responsible for delivering the file to its desired destination (local directory, remote location, etc.).
If you want to add further transmitters just provide a PHP service class like this:
<?php
namespace AppBundle\DataHubFileExport\Exporter\Transmitter;
class MyCustomTransmitter extends \Pimcore\Bundle\DataHubFileExportBundle\Exporter\Transmitter\AbstractTransmitter {
public function execute()
{
$exportType = $this->getExporterType();
$tmpFile = $exportType->getTmpFile();
$config = $exportType->getExporter()->getDataHubConfiguration()->getConfiguration();
$transmitterConfig = $config['deliveryDestination']['transmitter_myCustomTransmitter'];
var_dump($transmitterConfig); exit;
//push it somewhere
}
}
... and add it as a Service with the tag pimcore.datahub.fileExport.exporter.transmitter
AppBundle\DataSyndicator\Exporter\Transmitter\MyCustomTransmitter:
shared: false
tags:
- { name: "pimcore.datahub.fileExport.exporter.transmitter", type: "myCustomTransmitter" }
For the JavaScript part (custom configuration fields for your transmitter) you can provide a fieldset like follows.
If you registered the PHP Service with the type myCustomTransmitter, your id has to be transmitter_myCustomTransmitter
(type prefixed with transmitter_). Please make sure that the id naming convention is correct.
pimcoreDataHubFileExportBundlePlugin.transmitter.myCustomTransmitter = function () {
let id = "transmitter_myCustomTransmitter";
return {
xtype: "fieldset",
title: t("plugin_pimcore_datahub_delivery_destination_transmitter_myCustomTransmitter"),
width: 600,
itemId: id,
defaultType: 'textfield',
hidden: false,
items: [{
fieldLabel: t("plugin_pimcore_datahub_delivery_destination_directory"),
name: id + ".directory",
width: 560,
value: this.getValue('deliveryDestination.'+ id +'.directory')
}
]
};
};
If you don't need further configuration, you can just define an empty function, so the transmitter shows up in the
Delivery type dropdown:
pimcoreDataHubFileExportBundlePlugin.transmitter.myCustomTransmitter = function () {};
Please make sure with bundle priorities, that your Bundle is loaded after the DataHub File Export,
otherwise you will get a Javascript error because the variable doesn't exist.
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Additional Exporter Types | https://pimcore.com/docs/platform//Datahub_File_Export/Customize_and_Extend#additional-exporter-types | Additional Exporter Types
To add additional exporter types (besides CSV, XML and JSON) just have a look at the existing ones. You can create
custom exporter types by just adding additional services add extend the Pimcore\Bundle\DataHubFileExportBundle\Exporter\Type\AbstractExporter
class and register them with the tag pimcore.datahub.fileExport.exporter.type.
AppBundle\Exporter\Type\JSON:
shared: false
tags:
- { name: "pimcore.datahub.fileExport.exporter.type", type: "MY_JSON" }
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Customize built in Exporter Types/Transmitters | https://pimcore.com/docs/platform//Datahub_File_Export/Customize_and_Extend#customize-built-in-exporter-typestransmitters | Customize built in Exporter Types/Transmitters
To customize the built in exporter/transmitter you can override the existing services. Please take a look at
Service definition of the bundle on how they are defined.
If you want to override the XML exporter type, you could do it like this:
Create your service class e.g:
<?php
namespace AppBundle\DataSyndicator\Exporter\Type;
class XML extends \Pimcore\Bundle\DataHubFileExportBundle\Exporter\Type\XML
{
protected $itemKey = 'myCustomItemKey';
protected function writeData($data)
{
return parent::writeData($data);
}
protected function getExistingData(): array
{
return parent::getExistingData();
}
}
... and override the service definition in your services.yml with:
Pimcore\Bundle\DataHubFileExportBundle\Exporter\Type\XML:
class: AppBundle\DataSyndicator\Exporter\Type\XML
shared: false
tags:
- { name: "pimcore.datahub.fileExport.exporter.type", type: "XML" }
This would just change the XML node item key from item to myCustomItemKey. | [
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Custom exporter services | https://pimcore.com/docs/platform//Datahub_File_Export/Customize_and_Extend#custom-exporter-services | Custom exporter services
The exporter service implements and controls the whole export process. The default bundle configuration for the file exporter
looks like this. So you can override custom parts if you need it.
pimcore_data_hub_file_export:
defaultExporter: 'pimcore.datahub.fileExport.exporter.file'
By default, the pimcore.datahub.fileExport.exporter.file service (see settings above) is used to execute the
export. You can change the exporter globally (settings above) or per export configuration.
To create a custom exporter service you have to register the class as a public service. | [
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Definition | https://pimcore.com/docs/platform//Datahub_File_Export/Customize_and_Extend#definition | Definition
app.datahub.my-exporter:
class: AppBundle\DataSyndicator\Exporter\File
public: true
shared: false
tags:
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] |
Implementation | https://pimcore.com/docs/platform//Datahub_File_Export/Customize_and_Extend#implementation | Implementation
<?php
namespace AppBundle\DataSyndicator\Exporter;
class File extends \Pimcore\Bundle\DataHubFileExportBundle\Exporter\File {
public function execute($data)
{
//var_dump($this->getDataHubConfiguration()->getName());
//do some custom stuff instead of calling the parent
return parent::execute($data);
}
}
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File exporter - Events | https://pimcore.com/docs/platform//Datahub_File_Export/Events#file-exporter---events | File exporter - Events
There are a couple of events which you can use to modify the export.
pimcore.dataobject.postCsvItemExport
Pimcore\Bundle\DataHubFileExportBundle\Event\IsValidExportItemEvent
Pimcore\Bundle\DataHubFileExportBundle\Event\FilterExistingDataEvent
Pimcore\Bundle\DataHubFileExportBundle\Event\PreWriteDataEvent
Pimcore\Bundle\DataHubFileExportBundle\Event\RelevantItemListEvent
Pimcore\Bundle\DataHubFileExportBundle\Event\FilenameEvent
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Sample implementation | https://pimcore.com/docs/platform//Datahub_File_Export/Events#sample-implementation | Sample implementation | [
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Sample configuration for EventListener | https://pimcore.com/docs/platform//Datahub_File_Export/Events#sample-configuration-for-eventlistener | Sample configuration for EventListener
AppBundle\EventListener\DataHubFileExportListener:
tags:
- { name: kernel.event_listener, event: pimcore.dataobject.postCsvItemExport, method: postCsvItemExport }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubFileExportBundle\Event\IsValidExportItemEvent, method: isValidExportItem }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubFileExportBundle\Event\FilterExistingDataEvent, method: filterExistingData }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubFileExportBundle\Event\PreWriteDataEvent, method: preWriteData }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubFileExportBundle\Event\RelevantItemListEvent, method: relevantItemList }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubFileExportBundle\Event\FilenameEvent, method: modifyFilename }
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] |
The appropriate EventListener would look like this | https://pimcore.com/docs/platform//Datahub_File_Export/Events#the-appropriate-eventlistener-would-look-like-this | The appropriate EventListener would look like this
<?php
/**
* Pimcore
*
* This source file is available under two different licenses:
* - GNU General Public License version 3 (GPLv3)
* - Pimcore Commercial License (PCL)
* Full copyright and license information is available in
* LICENSE.md which is distributed with this source code.
*
* @copyright Copyright (c) Pimcore GmbH (http://www.pimcore.org)
* @license http://www.pimcore.org/license GPLv3 and PCL
*/
namespace AppBundle\EventListener;
use Pimcore\Bundle\DataHubFileExportBundle\Event\FilenameEvent;
use Pimcore\Bundle\DataHubFileExportBundle\Event\FilterExistingDataEvent;
use Pimcore\Bundle\DataHubFileExportBundle\Event\IsValidExportItemEvent;
use Pimcore\Bundle\DataHubFileExportBundle\Event\PreWriteDataEvent;
use Pimcore\Bundle\DataHubFileExportBundle\Event\RelevantItemListEvent;
use Pimcore\DataObject\Import\Resolver\Filename;
use Symfony\Component\EventDispatcher\GenericEvent;
use \Pimcore\Bundle\DataHubFileExportBundle\Exporter\AbstractExporter;
use Pimcore\Model\DataObject;
class DataHubFileExportListener
{
public static function postCsvItemExport(\Pimcore\Event\Model\DataObjectEvent $event ){
$object = $event->getObject();
if($object instanceof \Pimcore\Model\DataObject\Car){
$context = $event->getArgument('context');
if($context['source'] == 'pimcore_data_hub_file_export'){
$objectData = $event->getArgument('objectData');
/**
* @var $exporter \Pimcore\Bundle\DataHubFileExportBundle\Exporter\AbstractExporter
*/
if($context['configId']){ //from preview mode
$config = \Pimcore\Bundle\DataHubBundle\Configuration::getByName($context['configId']);
$exporter = \Pimcore\Bundle\DataHubFileExportBundle\Helper::getExporterService($config);
}else{
$exporter = $context['exporter']; //from export
}
$dataHubConfig = $exporter->getDataHubConfiguration();
$objectData['id'] .= 'modified by ev';
if($dataHubConfig->getName() == 'test-json'){
$objectData['name'] = $objectData['name'] . ' - Modified by event';
if($objectData['manufacturer']){
$objectData['manufacturer'] = 'xxx - ' . $objectData['manufacturer'];
}
$event->setArgument('objectData',$objectData);
}
}elseif($context['source'] == 'pimcore-export'){
//pimcore grid export
$objectData = $event->getArgument('objectData');
$objectData['fullpath'] .= '- Modified....';
$event->setArgument('objectData',$objectData);
}
}
}
public static function modifyFilename(FilenameEvent $event){
/**
* @var $exporter AbstractExporter
*/
$exporter = $event->getExporter();
$filename = $event->getFilename();
$filename = strtoupper($filename);
$event->setFilename($filename);
}
public static function isValidExportItem(IsValidExportItemEvent $event){
/**
* @var $exporter AbstractExporter
*/
$exporter = $event->getExporter();
$object = $event->getObject();
if($object->getId() == 82){
$event->setIsValid(false);
}
}
public static function relevantItemList(RelevantItemListEvent $event){
/**
* @var $exporter AbstractExporter
* @var $list \Pimcore\Model\DataObject\Listing
*/
$exporter = $event->getExporter();
$list = $event->getList();
$condition = $list->getCondition();
$db = \Pimcore\Db::get();
$list->setCondition($condition .= ' AND ' . $db->quoteIdentifier(DataObject\Service::getVersionDependentDatabaseColumnName('o_id')) . '=123');
}
public static function preWriteData(PreWriteDataEvent $event){
/**
* @var $exporter AbstractExporter
*/
$exporter = $event->getExporter();
$data = $event->getData();
foreach($data as $i => $e){
$e['name'] = 'hello - ' . $i;
$data[$i] = $e;
}
$event->setData($data);
}
public static function filterExistingData(FilterExistingDataEvent $event){
/**
* @var $exporter \Pimcore\Bundle\DataHubFileExportBundle\Exporter\AbstractExporter
*/
$exporter = $event->getExporter();
$data = $event->getData();
foreach($data as $i => $e){
$o = \Pimcore\Model\DataObject\Concrete::getById($e['id']);
if(!$exporter->isValidExportItem($o)){
unset($data[$i]);
}
}
$event->setData($data);
}
}
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Datahub_File_Export | https://pimcore.com/docs/platform//Datahub_File_Export#datahub_file_export | Datahub_File_Export
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title: Datahub File Export | https://pimcore.com/docs/platform//Datahub_File_Export#title:-datahub-file-export | title: Datahub File Export | [
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Pimcore Datahub File Export | https://pimcore.com/docs/platform//Datahub_File_Export#pimcore-datahub-file-export | Pimcore Datahub File Export
This extension allows the publishing of the data stored in Pimcore automatically to flat CSV, XML, or JSON files
with simple configurations inside Pimcore's Datahub.
It represents a good solution for exporting data on a regular base. | [
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Features in a Nutshell | https://pimcore.com/docs/platform//Datahub_File_Export#features-in-a-nutshell | Features in a Nutshell
Schema and exposed data configuration like with other Datahub adapters via drag & drop
Export format definition as csv, xml or json
Data delivery to specific targets like local directory, SFTP upload or HTTP POST
Caching of exported data to get high performance exports.
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Documentation Overview | https://pimcore.com/docs/platform//Datahub_File_Export#documentation-overview | Documentation Overview
Installation
Basic configuration
Export setup
Customize or extend the Bundle
Events
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Further Information | https://pimcore.com/docs/platform//Datahub_File_Export#further-information | Further Information
On other Pimcore Datahub adapters:
Datahub (GraphQL API)
Datahub Simple Rest API
Datahub Productsup
Datahub CI Hub
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Upgrade Notes | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation/Upgrade_Notes#upgrade-notes | Upgrade Notes
Things to consider before or when upgrading to new versions. | [
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v2.0.0 | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation/Upgrade_Notes#v2.0.0 | v2.0.0
It is possible to add more than one API-key per configuration now. Therefore, the API-key gets stored as an array
in the configuration. Configurations from previous versions are still supported, but they get converted to the new format
as soon as they get saved.
Removed Elasticsearch 6 and Elasticsearch 7 support, added support for Elasticsearch 8
Changed elasticsearch client configuration
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v1.7.2 | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation/Upgrade_Notes#v1.7.2 | v1.7.2
Data type for asset fileSize was changed to long (was int). If you run into issues regarding the fileSize, please
re-index your data.
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v1.5.x to v1.6.0 | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation/Upgrade_Notes#v1.5.x-to-v1.6.0 | v1.5.x to v1.6.0
Default number of shards is now set to 1 (was 5). To change the value back to 5, see Indexing Options section
in Indexing Details.
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Installation | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#installation | Installation | [
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Required Bundles | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#required-bundles | Required Bundles
This bundle depends on Pimcore Datahub bundle. This needs
to be installed first. | [
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Installation Process | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#installation-process | Installation Process | [
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For Pimcore >= 10.5 | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#for-pimcore->=-10.5 | For Pimcore >= 10.5
To install Datahub Simple Rest API for Pimcore 10.5 or higher version, follow the three steps below:
Install the required dependencies:
composer require pimcore/data-hub-simple-rest
Make sure the bundle is enabled in the config/bundles.php file. The following lines should be added:
use Pimcore\Bundle\DataHubSimpleRestBundle\PimcoreDataHubSimpleRestBundle;
// ...
return [
// ...
// make sure PimcoreDataHubBundle is added before to that list
// ...
PimcoreDataHubSimpleRestBundle::class => ['all' => true],
// ...
];
Install the bundle:
bin/console pimcore:bundle:enable PimcoreDataHubSimpleRestBundle
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For Older Versions | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#for-older-versions | For Older Versions
To install the Datahub Simple Rest API bundle for older versions of Pimcore, please run the following commands instead:
composer require pimcore/data-hub-simple-rest
bin/console pimcore:bundle:enable PimcoreDataHubSimpleRestBundle
bin/console pimcore:bundle:install PimcoreDataHubSimpleRestBundle
Make sure the Datahub bundle's priority is higher than the Datahub Simple Rest API bundle's.
This can be specified as a parameter during bundle enablement or in the Pimcore extension manager.
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Configure Elasticsearch Client | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#configure-elasticsearch-client | Configure Elasticsearch Client
Elasticsearch client configuration takes place via Pimcore Elasticsearch Client Bundle and has two parts.
Configuring an elasticsearch client.
Define the client to be used by simple rest API.
# Configure an elasticsearch client
pimcore_elasticsearch_client:
es_clients:
default:
hosts: ['elastic:9200']
username: 'elastic'
password: 'somethingsecret'
logger_channel: 'pimcore.elasicsearch'
# Define the client to be used by simple rest API
pimcore_data_hub_simple_rest:
es_client_name: default # default is default value here, just need to be specified when other client should be used.
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Further Configuration Options | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#further-configuration-options | Further Configuration Options
Configure Elasticsearch hosts and index name prefix with symfony configuration:
pimcore_data_hub_simple_rest:
# Prefix for index names
index_name_prefix: datahub_restindex_
# Limit of page size and offset when paging only works via page cursor (and not page numbers anymore). Limit 10000 comes from Elasticsearch.
max_results_window: 10000
# Options to configure indexing behaviour
indexing_options:
assets:
# Enable indexing for exif data
enable_exif: true
# Enable indexing for xmp data
enable_xmp: true
# Enable indexing for iptc data
enable_iptc: true
global_options:
# Enable numeric detection for dynamic objects (like embedded asset meta data, etc.)
numeric_detection: false
# Enable date detection for dynamic objects (like embedded asset meta data, etc.)
date_detection: true
# Configure number of shards for created indices
number_of_shards_config:
# default number is picked if no index specific settings is set
default_number: 1
# Define number of shards for certain indices. Define index name (without -odd/-even postfix) as key, and number of shards as value.
index_specific: []
# Configure index queue processing via symfony messenger
messenger_queue_processing:
# Activate queue processing via symfony messenger.
activated: false
# Lifetime of tmp store entry for current worker count entry. After lifetime, the value will be cleared. Default to 1 hour.
worker_count_lifetime: 3600
# Count of items processed per worker message.
worker_item_count: 400
# Count of maximum parallel worker messages for queue processing.
worker_count: 3
Supported elasticsearch versions: 8
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Index Processing | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#index-processing | Index Processing
To make sure indexing queue is processed and index is filled, there are two possible ways: | [
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Command Based | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#command-based | Command Based
For command based queue processing, following command has to be executed on regular base, e.g. every 5 minutes.
*/5 * * * * php /home/project/www/bin/console datahub:simple-rest:process-queue
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Symfony Messenger Based | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Installation#symfony-messenger-based | Symfony Messenger Based
For symfony messenger based queue processing, at least following configuration needs to be done in symfony configuration:
pimcore_data_hub_simple_rest:
messenger_queue_processing:
activated: true
If activated, the processing is kicked off automatically with the datahub_simplerest_update_queue_dispatching maintenance task.
In addition to that, following settings are available. They all have meaningful default values though:
worker_count: Count of maximum parallel worker messages for queue processing
worker_item_count: Count of items processed per worker message.
worker_count_lifetime: Lifetime of tmp store entry for current worker count entry. After lifetime, the value will be cleared.
Messages are dispatched via pimcore_index_queues transport. So make sure, you have
workers processing this transport when activating the messenger based queue processing. | [
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] |
Endpoint Configuration Details | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Endpoint_Configuration#endpoint-configuration-details | Endpoint Configuration Details
Every Datahub configuration creates a separate endpoint with its own settings and its own data. Following
configuration options are possible for each endpoint. | [
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] |
General | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Endpoint_Configuration#general | General
See type and name of configuration and define description and if the endpoint is active or not.
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] |
Schema Definition | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Endpoint_Configuration#schema-definition | Schema Definition
Define available data entities and their schema (= available fields) for the endpoint. Also define if assets
should be considered in tree items and search requests and if originals and/or what thumbnails should be used
for delivery.
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Workspaces | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Endpoint_Configuration#workspaces | Workspaces
Define workspaces for assets and data objects and so manage what data should be actually exposed via the endpoint.
It is possible to include and explicitly exclude folders.
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Label Settings | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Endpoint_Configuration#label-settings | Label Settings
Define nice looking labels for different languages for each field. Each request includes the labels for used fields
in response in an additional data structure. They then can be used by the client application.
Additionally define what fields will be considered for aggregation calculation for facet navigation.
Please consider that the field list is build based on indexed data. So saving the configuration and processing
index queue might be necessary to see up-to-date list here.
The current queue status is shown in bottom toolbar of configuration editor.
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] |
Delivery Settings | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Endpoint_Configuration#delivery-settings | Delivery Settings
Define (or generate) an API key for securing the endpoint. This API key needs to be sent as security header with
every request.
| [
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0.41535821557044983,
-0.32690560817718506,
0.6558695435523987,
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0.5074745416641235,
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Index Structure | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Indexing_Details#index-structure | Index Structure
All data that is delivered by simple rest endpoints is indexed in elasticsearch indices. Queries
and data delivery takes place directly out of the elasticsearch (not from Pimcore database).
For each Datahub configuration separate elasticsearch indices will be created and updated.
Indexing of data takes places asynchronously with an update queue and the process queue command
datahub:simple-rest:process-queue. This command needs to be executed on a regular base, e.g.
every 5 minutes.
Index mapping and queue filling takes place automatically when creating and updating Datahub
configurations. In addition, also commands for index management are available
(datahub:simple-rest:create-or-update-mapping, datahub:simple-rest:init-index).
Per endpoint, multiple indices are created - one for each dataobject class, one for dataobject folders,
one for assets and one for asset folders.
For assets meta data exif, xmp and iptc, indexed dynamic objects are used. It might be necessary
to turn off the indexing for these objects in order to avoid indexing conflicts or when the
limit of maximum data fields is reached.
Indexing can be turned off in bundle configuration in indexing_options area. Then data is stored
in index and delivered via endpoint, but it is not indexed.
Tree Hierarchy Management
The indexing process tries to keep a valid folder structure in index. Based on workspace settings
a combined parent folder is calculated. This combined parent folder, might be a sub folder of the parent folder in Pimcore folder structure,
and all element paths are rewritten to it.
Also it might be possible, that due to workspace and data schema settings, missing links in folder structure
occur. In this case, the indexing process creates virtual folders to fill up these gaps.
For updating whole index structure after changes, multiple runs of datahub:simple-rest:process-queue might
be necessary (since additional items might be added to queue during queue processing). | [
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Indexing Options | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Indexing_Details#indexing-options | Indexing Options
Via symfony configuration, detailed indexing options can be configured. | [
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Global Options | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Indexing_Details#global-options | Global Options
Define some global options like automatic data type detection for dynamic objects.
pimcore_data_hub_simple_rest:
indexing_options:
global_options:
# Enable numeric detection for dynamic objects (like embedded asset meta data, etc.)
numeric_detection: false
# Enable date detection for dynamic objects (like embedded asset meta data, etc.)
date_detection: true
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Assets | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Indexing_Details#assets | Assets
Define, if embedded metadata of assets should be indexed. If, they will be indexed as dynamic objects.
pimcore_data_hub_simple_rest:
indexing_options:
assets:
# Enable indexing for exif data
enable_exif: true
# Enable indexing for xmp data
enable_xmp: true
# Enable indexing for iptc data
enable_iptc: true
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Number of Shards | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Indexing_Details#number-of-shards | Number of Shards
By default, number of shards for indexes is set to 1. Configurations allow to change that for all created indices via
the default_number and on index level via the index_specific setting if needed.
# Configure number of shards for created indices
pimcore_data_hub_simple_rest:
indexing_options:
number_of_shards_config:
# default number is picked if no index specific settings is set
default_number: 3
# Define number of shards for certain indices. Define index name (without -odd/-even postfix) as key, and number of shards as value.
index_specific:
enterprise_simple_rest__pt_rest__asset: 5
enterprise_simple_rest__<ENDPOINTNAME>__<asset|DataObjectClass>: 3
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] |
Query Filters | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Filtering_and_Paging#query-filters | Query Filters
Querying can be done using a limited and simplifed subset of the syntax described
here.
Note
There might restrictions regarding nesting levels.
If you are using Pimcore 11 you need to remove the o_ prefix.
For example use
where ((`modificationDate` = '1000') AND ((`id` = '3') OR (`key` = 'lorem-ipsum') ) )
instead of
where ((`o_modificationDate` = '1000') AND ((`o_id` = '3') OR (`o_key` = 'lorem-ipsum') ) )
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] |
Supported Logic Operators | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Filtering_and_Paging#supported-logic-operators | Supported Logic Operators
$not
$or
$and
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] |
Examples | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Filtering_and_Paging#examples | Examples
q={"modificationDate" : "1000"}
... SQL equivalent ...
where ((`modificationDate` = '1000') )
q=[{"creationDate" : "1000"}, {"modificationDate" : "9999"}]
...
where ( ((`creationDate` = '1000') ) AND ((`modificationDate` = '9999') ) )
q={"modificationDate" : "1000"}, "$or": [{"o_id": "3"}, {"o_key": "lorem-ipsum"}]}
...
where ((`o_modificationDate` = '1000') AND ((`o_id` = '3') OR (`o_key` = 'lorem-ipsum') ) )
q={"$and" : [{"o_published": "0"}, {"o_modificationDate" : "1000", "$or": [{"o_id": "3"}, {"o_key": "lorem-ipsum"}]}]}
...
where ( ((`o_published` = '0') ) AND ((`o_modificationDate` = '1000') AND ((`o_id` = '3') OR (`o_key` = 'lorem-ipsum') ) ) )
q={"o_type": {"$not": "folder"}}
...
(( NOT `o_type` ='object') )
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Paging | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Filtering_and_Paging#paging | Paging
The paging can be done via the page_cursor parameter in the query. When loading the next page of a result, use the
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Technical Details | https://pimcore.com/docs/platform//Datahub_Simple_Rest/Filtering_and_Paging#technical-details | Technical Details
The page_cursor has two operation modes:
for pages below the configured max results window, it uses a numeric value and ES from query.
for pages after the max results window, it uses the search_after option of ES - as also suggested
here.
The max results window can be configured via symfony configuration:
pimcore_data_hub_simple_rest:
# Limit of page size and offset when paging only works via page cursor (and not page numbers anymore). Limit 10000 comes from Elasticsearch.
max_results_window: 10000
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Datahub_Simple_Rest | https://pimcore.com/docs/platform//Datahub_Simple_Rest#datahub_simple_rest | Datahub_Simple_Rest
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title: Datahub Simple Rest API | https://pimcore.com/docs/platform//Datahub_Simple_Rest#title:-datahub-simple-rest-api | title: Datahub Simple Rest API | [
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Pimcore Datahub Simple Rest API | https://pimcore.com/docs/platform//Datahub_Simple_Rest#pimcore-datahub-simple-rest-api | Pimcore Datahub Simple Rest API
This extension adds a simple read-only rest API endpoint to Pimcore Datahub for assets and data objects. All
exposed data can be configured, is indexed in Elasticsearch and delivered from there for better query
performance and scalability.
Therefore, it can be used to connect Pimcore to other systems or to connect frontend applications. | [
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] |
Features in a Nutshell | https://pimcore.com/docs/platform//Datahub_Simple_Rest#features-in-a-nutshell | Features in a Nutshell
Schema and exposed data configuration like with other Datahub adapters
Data indexed in and delivered from Elasticsearch indices (no additional load on database when accessing data via rest endpoints)
Endpoint documentation and test via Swagger UI
Three available endpoints:
tree-items: loads all elements of a tree level
search: searches elements, returns elements of all types, no folder structures
get-element: gets one single element by type and id.
Endpoint security via bearer token that has to be sent as a header with every request.
Datahub Simple Rest API available endpoints | [
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Documentation Overview | https://pimcore.com/docs/platform//Datahub_Simple_Rest#documentation-overview | Documentation Overview
Installation & Bundle Configuration
Endpoint Configuration Details
Indexing Details
Filter Details
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Further Information | https://pimcore.com/docs/platform//Datahub_Simple_Rest#further-information | Further Information
On other Pimcore Datahub extensions:
Datahub (GraphQL API)
Datahub File Export
Datahub Productsup
Datahub CI Hub
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Upgrade Information | https://pimcore.com/docs/platform//Datahub_Productsup/Installation/Upgrade#upgrade-information | Upgrade Information
Following steps are necessary during updating to newer versions. | [
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Upgrade to 2.0.0 | https://pimcore.com/docs/platform//Datahub_Productsup/Installation/Upgrade#upgrade-to-2.0.0 | Upgrade to 2.0.0
Added support for Pimcore v11 and dropped support for all previous Pimcore versions.
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Upgrade to 1.1.0 | https://pimcore.com/docs/platform//Datahub_Productsup/Installation/Upgrade#upgrade-to-1.1.0 | Upgrade to 1.1.0
Execute all migrations of the bundle.
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Upgrade to Pimcore X | https://pimcore.com/docs/platform//Datahub_Productsup/Installation/Upgrade#upgrade-to-pimcore-x | Upgrade to Pimcore X
Update to latest (allowed) bundle version in Pimcore 6.9 and execute all migrations.
Then update to Pimcore X.
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Installation | https://pimcore.com/docs/platform//Datahub_Productsup/Installation#installation | Installation | [
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] |
Required Bundles | https://pimcore.com/docs/platform//Datahub_Productsup/Installation#required-bundles | Required Bundles
This bundle depends on two other bundles that need to be installed first:
Pimcore Datahub
Pimcore Datahub file export
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Installation Process | https://pimcore.com/docs/platform//Datahub_Productsup/Installation#installation-process | Installation Process | [
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For Pimcore >= 10.5 | https://pimcore.com/docs/platform//Datahub_Productsup/Installation#for-pimcore->=-10.5 | For Pimcore >= 10.5
To install Datahub Productsup for Pimcore 10.5 or higher, follow the three steps below:
Install the required dependencies:
composer require pimcore/data-hub-productsup
Make sure the bundle is enabled in the config/bundles.php file. The following lines should be added:
use Pimcore\Bundle\DataHubProductsupBundle\PimcoreDataHubProductsupBundle;
// ...
return [
// ...
// make sure that the required bundles are added before to that list
// ...
PimcoreDataHubProductsupBundle::class => ['all' => true],
// ...
];
Install the bundle:
bin/console pimcore:bundle:install PimcoreDataHubProductsupBundle
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For Older Versions | https://pimcore.com/docs/platform//Datahub_Productsup/Installation#for-older-versions | For Older Versions
To install the Datahub Productsup bundle for older versions of Pimcore, please run the following commands instead:
composer require pimcore/data-hub-productsup
bin/console pimcore:bundle:enable PimcoreDataHubProductsupBundle
bin/console pimcore:bundle:install PimcoreDataHubProductsupBundle
Please make sure, that the bundles are loaded in following order:
PimcoreDataHubBundle
PimcoreDataHubFileExportBundle
PimcoreDataHubProductsupBundle
Custom Bundles which extend bundles from above
This priority order can be specified as a parameter during bundle enablement or in the Pimcore extension manager.
After the installation you should see the Productsup adapter in the Datahub configuration panel:
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Basic configuration | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#basic-configuration | Basic configuration | [
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General settings | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#general-settings | General settings
Active: Enable/Disable the endpoint.
Description: Provide a description for the endpoint.
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Schema definition | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#schema-definition | Schema definition
Configure the exported data with drag & drop as you do it in the regular grid column definition in Pimcore.
Optionally define image / video thumbnails if you are going to export assets - if no thumbnail is selected, the original asset path is used.
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] |
Workspace definition | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#workspace-definition | Workspace definition
Workspaces - restrict the export to specific folders.
Custom export class - define a custom Class which should execute the export - default is to
Pimcore\Bundle\DataHubProductsupBundle\Exporter\Productsup.
If you want to filter further items you can use the pimcore.datahub.fileExport.isValidExportItem event or overwrite
the getQueryCondition() of the exporter class.
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Trigger for delivery | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#trigger-for-delivery | Trigger for delivery
Defines when the data should be written to the cache.
Disabled: The export ist just done by the export command in the ProcessManger (more details later on).
Each export is a full export.
Deliver directly on save: When the object is saved, the data is directly written to the cache table. This should
only be used if you have simple objects and inheritance is not enabled, because of possible save performance impacts.
Populate to queue: When an object is saved, only a queue item created. The export ist done later on (asynchronously).
So there is no performance drawback when you save the object because the "heavy work" is done in the background later on.
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Delivery endpoint | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#delivery-endpoint | Delivery endpoint
Activate delivery endpoint: Generally enables the endpoint. productsup fetches the product data from this endpoint,
the URL of the endpoint is shown in the configuration panel.
Security Token: This token has to be sent as Bearer Token by productsup (HTTP Header with the name Authorization).
Please keep in mind, that the check for the token is disabled if you are logged in to Pimcore and have permission to access
the Datahub.
Valid GET parameters for the endpoint are: page, per_page, since_modification_date.
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Order endpoint | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#order-endpoint | Order endpoint
Activate order endpoint: Generally enables the endpoint. productsup pushes the orders to this endpoint.
Parent folder: The folder where to productsup orders should be saved to.
Security Token: This token has to be sent as Bearer Token by productsup (HTTP Header with the name Authorization).
Please keep in mind, that the check for the token is disabled if you are logged in to Pimcore and have permission to access
the Datahub.
A sample request payload can be found here.
For development purpose you can load the data from a file e.g. /data-hub/productsup/order-push/products-up?file=/vendor/pimcore/data-hub-productsup/doc/examples/order.json.
This will only work when Pimcore runs in debug mode.
The data/payload from productsup is logged in the ApplicationLogger. If you encounter any problems, please take a
look at the logger (Component = data-hub-productsup).
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Saving Configurations | https://pimcore.com/docs/platform//Datahub_Productsup/Basic_Configuration#saving-configurations | Saving Configurations
There are two methods for saving configurations:
Save: Only saves configuration, does not have any influence on cached data or queue entries.
Save, reset and clear queue: Saves configurations, resets cache and resets and fills queue will all relevant
elements for this export.
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] |
Setup - Delivery endpoint | https://pimcore.com/docs/platform//Datahub_Productsup/Setup_Delivery#setup---delivery-endpoint | Setup - Delivery endpoint
The delivery endpoint uses cached items, so you have to set up a command which calculates these cached items on a
regular basis. If you have set the save hook to Deliver directly on save you can omit this step, but
it is recommended to set up the process because you can rebuild the cache table with it.
The command can be setup and executed directly as cronjob by just executing the datahub:export:productsup command (for details
see --help option). | [
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Events | https://pimcore.com/docs/platform//Datahub_Productsup/Events#events | Events
There are a couple of events which you can use to modify the exported data or to modify the imported order objects.
pimcore.dataobject.postCsvItemExport
Pimcore\Bundle\DataHubFileExportBundle\Event\IsValidExportItemEvent
Pimcore\Bundle\DataHubProductsupBundle\Event\DeliveryModifyResultEvent
Pimcore\Bundle\DataHubProductsupBundle\Event\OrderItemPreSaveEvent
Pimcore\Bundle\DataHubProductsupBundle\Event\OrderPreSaveEvent
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Sample implementation | https://pimcore.com/docs/platform//Datahub_Productsup/Events#sample-implementation | Sample implementation | [
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Sample configuration for EventListener | https://pimcore.com/docs/platform//Datahub_Productsup/Events#sample-configuration-for-eventlistener | Sample configuration for EventListener
AppBundle\EventListener\DataHubProductsupListener:
tags:
- { name: kernel.event_listener, event: pimcore.dataobject.postCsvItemExport, method: postCsvItemExport }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubFileExportBundle\Event\IsValidExportItemEvent, method: isValidExportItem }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubProductsupBundle\Event\DeliveryModifyResultEvent, method: modifyResult }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubProductsupBundle\Event\OrderItemPreSaveEvent, method: preOrderItemSave }
- { name: kernel.event_listener, event: Pimcore\Bundle\DataHubProductsupBundle\Event\OrderPreSaveEvent, method: orderPreSave }
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] |
The appropriate EventListener would look like this | https://pimcore.com/docs/platform//Datahub_Productsup/Events#the-appropriate-eventlistener-would-look-like-this | The appropriate EventListener would look like this
<?php
namespace AppBundle\EventListener;
use Pimcore\Bundle\DataHubProductsupBundle\Event\DeliveryModifyResultEvent;
use Pimcore\Bundle\DataHubProductsupBundle\Event\OrderItemPreSaveEvent;
use Pimcore\Bundle\DataHubProductsupBundle\Event\OrderPreSaveEvent;
use Pimcore\Bundle\DataHubFileExportBundle\Event\IsValidExportItemEvent;
class DataHubProductsupListener
{
public static function postCsvItemExport(\Pimcore\Event\Model\DataObjectEvent $event)
{
$object = $event->getObject();
if ($object instanceof \Pimcore\Model\DataObject\Car) {
$context = $event->getArgument('context');
if ($context['source'] == 'pimcore_data_hub_file_export') {
$objectData = $event->getArgument('objectData');
/**
* @var $exporter \Pimcore\Bundle\DataHubFileExportBundle\Exporter\AbstractExporter
*/
$exporter = $context['exporter'];
$dataHubConfig = $exporter->getDataHubConfiguration();
if ($dataHubConfig->getName() == 'products-up') {
$objectData['name'] = $objectData['name'] . ' - Modified by event';
$event->setArgument('objectData', $objectData);
}
} elseif ($context['source'] == 'pimcore-export') {
//pimcore grid export
$objectData = $event->getArgument('objectData');
$objectData['fullpath'] .= '- Modified....';
$event->setArgument('objectData', $objectData);
}
}
}
public static function isValidExportItem(IsValidExportItemEvent $event)
{
/**
* @var $exporter \Pimcore\Bundle\DataHubProductsupBundle\Exporter\Productsup
*/
$exporter = $event->getExporter();
$object = $event->getObject();
if ($object->getId() == 81) {
$event->setIsValid(false);
}
}
public static function modifyResult(DeliveryModifyResultEvent $event)
{
/**
* @var $dataHubConfig \Pimcore\Bundle\DataHubBundle\Configuration
* @var $list \Pimcore\Bundle\DataHubProductsupBundle\Model\CacheItem\Listing
*/
$dataHubConfig = $event->getConfiguration();
$list = $event->getList();
$data = $event->getData();
foreach ((array)$data as $k => $entry) {
$entry['price'] = 123.90;
$data[$k] = $entry;
}
$event->setData($data);
}
public static function preOrderItemSave(OrderItemPreSaveEvent $event)
{
$object = $event->getOrder();
if ($object instanceof \Pimcore\Model\DataObject\OnlineShopOrder) {
$orderItem = $event->getOrderItem();
$payload = $event->getPayload();
$data = $event->getData();
$config = $event->getConfiguration();
$orderItem->setProduct(\Pimcore\Model\DataObject::getById(82));
}
}
public static function orderPreSave(OrderPreSaveEvent $event)
{
$order = $event->getOrder();
if ($order instanceof \Pimcore\Model\DataObject\OnlineShopOrder) {
$payload = $event->getPayload();
$config = $event->getConfiguration();
$order->setKey('test23-' . time());
}
}
}
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Datahub_Productsup | https://pimcore.com/docs/platform//Datahub_Productsup#datahub_productsup | Datahub_Productsup
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title: Datahub Productsup | https://pimcore.com/docs/platform//Datahub_Productsup#title:-datahub-productsup | title: Datahub Productsup | [
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Pimcore DataHub Productsup | https://pimcore.com/docs/platform//Datahub_Productsup#pimcore-datahub-productsup | Pimcore DataHub Productsup
This bundle integrates product data syndication platform productsup to Pimcore Datahub
and allows:
to distribute product data to marketplaces and marketing channels
to import order data to Pimcore.
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Features in a Nutshell | https://pimcore.com/docs/platform//Datahub_Productsup#features-in-a-nutshell | Features in a Nutshell
Schema and exposed data configuration like with other Datahub adapters via drag & drop.
Caching of exported data to get a high performance API.
URL service which can be used by Productsup to retrieve the product data
URL service to import orders from Productsup.
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Documentation Overview | https://pimcore.com/docs/platform//Datahub_Productsup#documentation-overview | Documentation Overview
Installation
Basic configuration
Setup Delivery
Events
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Further Information | https://pimcore.com/docs/platform//Datahub_Productsup#further-information | Further Information
On other Pimcore Datahub adapters:
Datahub (GraphQL API)
Datahub Simple Rest API
Datahub File Export
Datahub CI Hub
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Installation | https://pimcore.com/docs/platform//Datahub_CI_Hub/Installation#installation | Installation | [
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] |
Required Bundles | https://pimcore.com/docs/platform//Datahub_CI_Hub/Installation#required-bundles | Required Bundles
This bundle depends on two other bundles that need to be installed first:
Pimcore Datahub
Pimcore Datahub Simple Rest API
| [
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Installation Process | https://pimcore.com/docs/platform//Datahub_CI_Hub/Installation#installation-process | Installation Process | [
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For Pimcore >= 10.5 | https://pimcore.com/docs/platform//Datahub_CI_Hub/Installation#for-pimcore->=-10.5 | For Pimcore >= 10.5
To install Pimcore Datahub CI Hub for Pimcore 10.5 or higher, follow the three steps below:
Install the required dependencies:
composer require pimcore/data-hub-ci-hub
Make sure the bundle is enabled in the config/bundles.php file. The following lines should be added:
use Pimcore\Bundle\DataHubCiHubBundle\PimcoreDataHubCiHubBundle;
// ...
return [
// ...
// make sure that the required bundles are added before to that list
// ...
PimcoreDataHubCiHubBundle::class => ['all' => true],
// ...
];
Install the bundle:
bin/console pimcore:bundle:install PimcoreDataHubCiHubBundle
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For Older Versions | https://pimcore.com/docs/platform//Datahub_CI_Hub/Installation#for-older-versions | For Older Versions
To install the Datahub CI Hub bundle for older versions of Pimcore, please run the following commands instead:
composer require pimcore/data-hub-ci-hub
bin/console pimcore:bundle:enable PimcoreDataHubCiHubBundle
bin/console pimcore:bundle:install PimcoreDataHubCiHubBundle
Please make sure, that the bundles are loaded in following order:
PimcoreDataHubBundle
PimcoreDataHubSimpleRestBundle
PimcoreDataHubCiHubBundle
Custom Bundles which extend bundles from above
This priority order can be specified as a parameter during bundle enablement or in the Pimcore extension manager.
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Upgrade Notes | https://pimcore.com/docs/platform//Datahub_CI_Hub/Upgrade_Notes#upgrade-notes | Upgrade Notes
Things to consider before or when upgrading to new versions. | [
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] |
v1.2.0 | https://pimcore.com/docs/platform//Datahub_CI_Hub/Upgrade_Notes#v1.2.0 | v1.2.0
It is possible to add more than one API-key per configuration now. Therefore, the API-key gets stored as an array
in the configuration. Configurations from previous versions are still supported, but they get converted to the new format
as soon as they get saved.
| [
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Datahub_CI_Hub | https://pimcore.com/docs/platform//Datahub_CI_Hub#datahub_ci_hub | Datahub_CI_Hub
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title: Datahub CI Hub | https://pimcore.com/docs/platform//Datahub_CI_Hub#title:-datahub-ci-hub | title: Datahub CI Hub | [
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Pimcore Datahub CI Hub integration | https://pimcore.com/docs/platform//Datahub_CI_Hub#pimcore-datahub-ci-hub-integration | Pimcore Datahub CI Hub integration
This bundle integrates CI Hub to Pimcore Datahub and therefore allows integrating Pimcore
assets and data objects directly into Adobe and Microsoft Products. | [
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Features in a Nutshell | https://pimcore.com/docs/platform//Datahub_CI_Hub#features-in-a-nutshell | Features in a Nutshell
Schema and exposed data configuration like with other Datahub adapters via drag & drop.
Caching of exported data to get a high performance API.
Possibility to use a token for connecting CI Hub with your Pimcore Datahub endpoint
Note: The endpoint config requires Assets Delivery thumbnail with name "galleryThumbnail" for seamless CI Hub integration.
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Documentation Overview | https://pimcore.com/docs/platform//Datahub_CI_Hub#documentation-overview | Documentation Overview
Since this bundle is based on the Pimcore Datahub Simple Rest API bundle,
see its documentation for details on configuration and usage.
For installation details see installation page. | [
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Further Information | https://pimcore.com/docs/platform//Datahub_CI_Hub#further-information | Further Information
On other Pimcore Datahub adapters:
Datahub (GraphQL API)
Datahub Simple Rest API
Datahub File Export
Datahub Productsup
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Installation | https://pimcore.com/docs/platform//Datahub_Webhooks/Installation#installation | Installation
:::info
This bundle is only supported on Pimcore Core Framework 11.
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