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Version 1.0.x of Solr Bundle primarily aims to be used as replacement for Legacy (SQL-based) search engine for better scalability and performance (especially with field criteria and sort clauses). And while it also provides better full text search thanks to Solr, more advance search features like Faceting will come in later releases.

 

 

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 Search API by default. By enabling Solr and re-indexing 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, thus removing considerable load from your database so it can focus on more important things, like publishing (wink).

See Architecture page for further information on the architecture of eZ Platform.

How to set up Solr Search engine

Step 1: Enabling the Bundle

Not needed with eZ Platform

This step is not needed for eZ Platform as of 15.09, however it is kept here for reference in case you have previously disabled the bundle.

 

  1. Add/Update composer dependencies:

    command line
  2. Activate EzPublishSolrSearchEngineBundle by adding the following lines to your app/AppKernel.php file: new EzSystems\EzPlatformSolrSearchEngineBundle\EzSystemsEzPlatformSolrSearchEngineBundle()

Step 2: Configuring & Starting Solr

 

Example here is for single core, look to Solr documentation for configuring Solr in other ways, also see the provided configuration for some examples.

 

First download and extract Solr, we currently support Solr 4.10.4:

 

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

 

Thirdly, Solr 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, example config:

solrconfig.xml

Step 3: Configuring bundle

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

parameters.yml


On to configuring the bundle.

Single Core example (default)

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

config.yml

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:

config.yml

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.

config.yml

 

Step 4: Configuring repository with the specific search engine

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

ezplatform.yml

%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 5: 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 6: 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 is on purpose not committing changes directly on Repository updates (on indexing), but letting 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: An open issue exists where you can find further info https://jira.ez.no/browse/EZP-25325

Last step is to execute initial indexation of data:

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 https://ezcommunity.slack.com/messages/ezplatform-use/

Document Field Mappers

AS OF V1.2, AVAILABLE IN EZ PLATFORM V1.7 AND HIGHER

As a developer you will often find the need to index some additional data in the search engine. The use cases for this are wide, for example the data could come from an external source (for example 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
    • ezpublish.search.solr.document_field_mapper.block
  • all block documents per translation
    • ContentTranslationFieldMapper
    • ezpublish.search.solr.field_mapper.block_translation
  • Content documents
    • ContentFieldMapper
    • ezpublish.search.solr.document_field_mapper.content
  • Content documents per translation
    • ContentTranslationFieldMapper
    • ezpublish.search.solr.field_mapper.content_translation
  • Location documents
    • LocationFieldMapper
    • ezpublish.search.solr.field_mapper.location

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:

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