eZ Systems Website
  Editor documentation

  Developer documentation

  Back to the top

The documentation is moving!

We're moving our developer docs to Github and a new site.
The migration is still in progress, so please contact us in #documentation-contrib on eZ Community Slack if you have any questions or feedback.

This space will not be updated from now on except for critical fixes.

Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 47 Next »

For use with eZ Publish 5.4, go to the corresponding documentation page which covers the v1.0 version of the bundle compatible with eZ Publish 5.4.

What is Solr Search Engine Bundle?

ezplatform-solr-search-engine,as the package is called, aims to be a transparent drop-in replacement for the SQL-based "Legacy" search engine powering eZ Platform Search API by default. When you enable Solr and re-index your content, all your existing Search queries using SearchService will be powered by Solr automatically. This allows you to scale up your eZ Platform installation and be able to continue development locally against SQL engine, and have a test infrastructure, Staging and Prod powered by Solr. This removes considerable load from your database. See Architecture for further information on the architecture of eZ Platform.

Status of features:

  • Able to handle all eZ Platform queries
    • Much more suitable for handling field criteria (performance)
    • Scoring for content queries and sorting by them by default
  • Indexing plugins (Solr Bundle >= v1.2)
  • Solr 6 support (Solr Bundle >= v1.3)
    • Scoring for Location queries and sorting by them by default
  • Work in progress:
    • Faceting (possible to write your own since v1.0, ContentType/Section/User implemented since v1.4, suggested further changes to the API for Faceting can be found here)
    • Index time Boosting (Solr Bundle >= v1.4)
  • Future:
    • Solr cloud support
    • Highlighting
    • Spell checking
    • Query time Boosting

How to set up Solr Search engine

Step 0: Enable Solr Bundle

Not needed with eZ Platform

This step is not needed as of eZ Platform 15.09, however it is kept here for reference in case you have previously disabled the bundle.
  1. Check in composer.json if you have the ezsystems/ezplatform-solr-search-engine package, if not add/update composer dependencies:

    command line
  2. Make sure EzPublishSolrSearchEngineBundle is activated with the following line in the app/AppKernel.php file: new EzSystems\EzPlatformSolrSearchEngineBundle\EzSystemsEzPlatformSolrSearchEngineBundle()

Step 1: Configuring & Starting Solr

The example presents a configuration with single core, look to Solr documentation for configuring Solr in other ways, including examples.

Download and configure

Solr 4.10.4

First, download and extract Solr. Solr Bundle 1.x supports Solr 4.10.4:

Secondly, copy configuration files needed for eZ Solr Search Engine bundle, in the example below from the root of your project to the place you extracted Solr:

Command line example
Solr 6

SOLR BUNDLE >= 1.3.0First download and extract Solr, in Solr Bundle 1.3 and higher we also support Solr 6 (currently tested with Solr 6.4.2):

Secondly, copy configuration files needed for eZ Solr Search Engine bundle, here from the root of your project to the place you extracted Solr:

Command line example

Further configuration

Thirdly, on both Solr 4 and 6 Solr the bundle does not commit solr index changes directly on repository updates, leaving it up to you to tune this using solrconfig.xml as best practice suggests, for example:


Step 2: Configuring bundle

The Solr search engine bundle can be configured in many ways. The config further below assumes you have parameters set up for solr dsn and search engine (however both are optional), for example:


On to configuring the bundle.

Single Core example (default)

Out of the box in eZ Platform the following is enabled for a simple setup:


Shared Core example

In the following example we have decided to separate one language as the installation contains several similar languages, and one very different language that should receive proper language analysis for proper stemming and sorting behavior by Solr:

Multi Core example

If full language analysis features are preferred, then each language can be configured to separate cores.

Note: Please make sure to test this setup against single core setup, as it might perform worse than single core if your project uses a lot of language fallbacks per SiteAccess, as queries will then be performed across several cores at once.


Step 3: Configuring repository with the specific search engine

The following is an example of configuring Solr Search Engine, where connection name is same as in the example above, and engine is set to solr:

%search_engine% is a parameter that is configured in app/config/parameters.yml, and should be changed from its default value "legacy" to "solr" to activate Solr as the Search engine.

Step 4: Clear prod cache

While Symfony dev environment keeps track of changes to yml files, prod does not, so to make sure Symfony reads the new config we clear cache:

Step 5: Run CLI indexing command

Make sure to configure your setup for indexing

Some exceptions might happen on indexing if you have not configured your setup correctly, here are the most common issues you may encounter:
  • Exception if Binary files in database have an invalid path prefix
    • Make sure ezplatform.yml configuration  var_dir is configured properly.
    • If your database is inconsistent in regards to file paths, try to update entries to be correct (but make sure to make a backup first).
  • Exception on unsupported Field Types
    • Make sure to implement all Field Types in your installation, or to configure missing ones as NullType if implementation is not needed.
  • Content not immediately available 
    • Solr Bundle on purpose does not commit changes directly on Repository updates (on indexing), but lets you control this using Solr configuration. Adjust Solr autoSoftCommit visibility of change to search index) and/or autoCommit (hard commit, for durability and replication) to balance performance and load on your Solr instance against needs you have for "NRT".
  • Running out of memory during indexing
    • In general make sure to run indexing using prod environment to avoid debuggers and loggers from filing up memory.
    • Flysystem: You can find further info in:

The last step is to execute the initial indexation of data:

SOLR BUNDLE >= 1.2Since eZ Platform v1.7.0 the ezplatform:solr_create_index command is deprecated, use php app/console ezplatform:reindex instead:

Configuring the Solr Search engine Bundle

For configuration of Solr connection for your repository, see How to set up Solr Search engine above.

Boost configuration


Boosting currently happens when indexing, so if you change your configuration you'll need to re-index (this is expected behavior). This can possibly be solved by a contribution to change boosting to be performed on query time.

Boosting tells the search engine which parts of the content model have more importance when searching, and is an important part of tuning your search results relevance. Importance is defined using a numeric value, where 1.0 is default, values higher than that are more important, and values lower (down to 0.0) are less important.

Boosting is configured per connection that you configure to use for a given repository, like in the example below:

config.yml snippet example


The configuration above will result in the following boosting (Content Type / Field):
  • article/title: 2.0
  • news/title: 3.0
  • blog_post/title:  1.5
  • news/description:  1.0 (default)
  • article/text (meta): 5.0
  • blog_post/name  (meta) 10.0
  • article/name  (meta) 2.0

Extending the Solr Search engine Bundle

Document Field Mappers

SOLR BUNDLE >= 1.2Starting with eZ Platform 1.7: as a developer you will often find the need to index some additional data in the search engine. The use cases for this are varied, for example the data could come from an external source (e.g. from recommendation system), or from an internal source. The common use case for the latter is indexing data through the Location hierarchy, for example from the parent Location to the child Location, or in the opposite direction, indexing child data on the parent Location. The reason might be you want to find the content with fulltext search, or you want to simplify search for a complicated data model. To do this effectively, you first need to understand how the data is indexed with Solr Search engine. Documents are indexed per translation, as Content blocks. In Solr, a block is a nested document structure. In our case, parent document represents Content, and Locations are indexed as child documents of the Content. To avoid duplication, full text data is indexed on the Content document only. Knowing this, you have the option to index additional data on:

  • all block documents (meaning Content and its Locations, all translations)
  • all block documents per translation
  • Content documents
  • Content documents per translation
  • Location documents

Indexing additional data is done by implementing a document field mapper and registering it at one of the five extension points described above. You can create the field mapper class anywhere inside your bundle, as long as when you register it as a service, the "class" parameter" in your services.yml matches the correct path. We have three different field mappers. Each mapper implements two methods, by the same name, but accepting different arguments:

  • ContentFieldMapper
    • ::accept(Content $content)
    • ::mapFields(Content $content)
  • ContentTranslationFieldMapper
    • ::accept(Content $content, $languageCode)
    • ::mapFields(Content $content, $languageCode)
  • LocationFieldMapper
    • ::accept(Location $content)
    • ::mapFields(Location $content)

These can be used on the extension points by registering them with the container using service tags, as follows:

  • all block documents
    • ContentFieldMapper
  • all block documents per translation
    • ContentTranslationFieldMapper
  • Content documents
    • ContentFieldMapper
  • Content documents per translation
    • ContentTranslationFieldMapper
  • Location documents
    • LocationFieldMapper

The following example shows how to index data from the parent Location content, in order to make it available for full text search on the children content. A concrete use case could be indexing webinar data on the webinar events, which are children of the webinar. Field mapper could then look something like this:

Since we index full text data only on the Content document, you would register the service like this:

Providing feedback

After completing the installation you are now free to use your site as usual. If you get any exceptions for missing features, have feedback on performance, or want to discuss, join our community slack channel at

  • No labels